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WO2013030785A1 - Biomarkers for lysosomal storage disorders - Google Patents

Biomarkers for lysosomal storage disorders Download PDF

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Publication number
WO2013030785A1
WO2013030785A1 PCT/IB2012/054469 IB2012054469W WO2013030785A1 WO 2013030785 A1 WO2013030785 A1 WO 2013030785A1 IB 2012054469 W IB2012054469 W IB 2012054469W WO 2013030785 A1 WO2013030785 A1 WO 2013030785A1
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sample
metallothionein
protein
disease
mld
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PCT/IB2012/054469
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French (fr)
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Alessandra Biffi
Martina CESANI
Clemens R. Scherzer
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Ospedale San Raffaele Srl
Fondazione Telethon
The Brigham And Women's Hospital, Inc.
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Publication of WO2013030785A1 publication Critical patent/WO2013030785A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/825—Metallothioneins
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/825—Metallothioneins

Definitions

  • the present invention relates to methods useful in diagnosis and prognosis of a lysosomal storage disorder by determining the expression levels of one or more metallothioneins.
  • the present invention also relates to a method of monitoring the progress of a lysosomal storage disorder and its response to therapy by determining the expression levels of one or more metallothioneins.
  • Lysosomal Storage Disorders comprise a class of inherited diseases characterized by disruption of normal lysosomal function resulting in the accumulation of incompletely degraded substrates that have been targeted for degradation after endocytosis or autophagy.
  • the ensuing accumulation of the substrate itself or of the product(s) of an alternative metabolic route in lysosomes affects the architecture and function of the cells, leading to cell dysfunction or death. Further, the primary defect is frequently exacerbated by secondary responses. This is of particular relevance in the Central Nervous System (CNS) where neuroinflammation occurs representing a primary reaction to substrate accumulation within microglia and astrocytes and/or an inflammatory response to primary neuronal or oligodendroglial damage.
  • CNS Central Nervous System
  • Metachromatic Leukodystrophy a demyelinating LSD due to mutations in the Arylsulfatase A (ARSA) gene (Aicardi (1998) In Disease of the nervous system in childhood. Cambridge University Press; Kolodny and Neudorfer (2003) Metachromatic Leukodistrophy and Multiple Sulfatase Deficiency: Sulfatide Lipidosis. 3rd ed, Heinemann) is a prototypical example of LSD with progressive accumulation of un-degraded substrates in the nervous system and secondary neuroinflammation and degeneration.
  • Clinical manifestations consisting of severe and unrelenting motor and cognitive impairment, and disease progression are more severe in the early onset clinical variants, leading to death usually within the first decade of life.
  • a correlation between the phenotype of MLD patients and the type of ARSA mutation they bear has recently been demonstrated (Cesani et al. (2009) Hum Mutat, 30, E936-945; Biffi. et al. (2008) Clinical Genetics, 74, 349-357).
  • LSDs are rare diseases with variable phenotypes and unpredictable progression over long periods. Accordingly, there is an urgent need for identifying biomarkers associated with LSDs and which can be used to provide improved methods of diagnosing LSDs. Furthermore, considerable research activity is currently focused on developing strategies to target LSDs with CNS involvement. Gene therapy (Biffi et al. (2004) J. Clin. Invest., 113, 1118-1129; Biffi et al. (2006) J Clin. Invest., 116, 3070- 3082), enzyme replacement therapy (Matzner et al. (2005) Hum Mol Genet, 14, 1139- 1152; Matzner et al.
  • a method of diagnosis or prognosis of a lysosomal storage disorder in a subject wherein said method comprises
  • An increase in the expression level of metallothionein in a sample relative to a sample from a healthy subject may be indicative of a lysosomal storage disorder.
  • a lysosomal storage disorder in a subject, wherein said method comprises:
  • the finding of expression levels of metallothionein of at least about 1.5, 2, 5, 10 or 50 fold relative to a healthy subject may indicate the presence of an LSD.
  • the finding of expression levels of metallothionein of at least about 1.5, 2, 2.5, 3, 4 or 5 fold relative to a healthy subject when measuring metallothionein mRNA abundance in T-cells/mononuclear cells may indicate the presence of an LSD.
  • the finding of expression levels of metallothionein of at least about 10, 15 or 20 fold relative to a healthy subject when measuring metallothionein mRNA abundance in brain samples or nerve biopsies may indicate the presence of a lysosomal storage disorder.
  • a lysosomal storage disorder comprising the steps of:
  • An increase in metallothionein expression in the second sample relative to the first sample indicates disease progression.
  • a decrease in metallothionein expression in the second sample relative to the first sample indicates amelioration of the symptoms.
  • the second sample is obtained from the subject at least 1, 2, 5, 10, 20, 50, 100, 200 or 300 days after the first sample.
  • the second aspect of the invention may be used to momtor the progress of an LSD in response to treatment (e.g., by bone marrow transplantation, gene therapy treatment, enzyme replacement therapy) of the LSD.
  • the present invention may be used to assess the effectiveness of an LSD treatment.
  • the treatment may be administered between the taking of the first sample and the taking of the second sample from the patient.
  • the sample is nervous tissue, 3 ⁇ 4lood (including blood cells and plasma/serum) or cerebrospinal fluid.
  • the sample is a population of T cells.
  • the metallothionein expression levels may be determined by, for example, quantitative RT-PCR.
  • the metallothionein expression levels may be determined by an immunoassay such as enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunofluorescence assay (IF A), enzyme linked assay (EI A), luminescence immunoassay (LI A), or Western Blot (WB).
  • the immunoassay may use an antibody immunospecifc for the metallothionein to detect metallothionein protein levels.
  • the metallothionein protein levels may be determined also by HPLC and mass spectrometry (Monicou et al. (2010) Anal Chem 82 6947-57).
  • the metallothionein may be selected from the group consisting of MT1, MT2, MT3 and MT4.
  • the metallothionein is selected from the group consisting of MT1 and MT2.
  • the metallothionein is selected from the group consisting of MT1A, MT1E, MT1F, MT2, MT3 and MT4. In another embodiment, the metallothionein is selected from the group consisting of MT1A, MT1E and MT2A. In a further embodiment, the metallothionein is selected from the group consisting of MT1 A, MT1E, MT2A and MTE.
  • the methods of the present invention may comprise deternii ing the expression level of more than one metallothionein.
  • the method comprises determining the expression levels of MT1A, MT1E and MT2A.
  • the method comprises determining the expression levels of MT1A, MT1E, MT2A and/or MTE.
  • the methods of the present invention may identify the expression levels of metallothionein using antibodies raised against the general metallothionein protein.
  • an antibody directed against a metallothionein for use in a diagnostic for a lysosomal storage disorder.
  • the lysosomal storage disorder is selected from the group consisting of Metachromatic Leukodystrophy (MLD), Globoid Cell Leukodystrophy (GLD), Mucopolysaccharidosis type I (MPS I), Mucopolysaccharidosis type III (MPS III), Neimann Pick disease (NPC), Neuronal Ceroidolipofuscinosis (NCL) and Sandhoff disease (SD).
  • MLD Metachromatic Leukodystrophy
  • GLD Globoid Cell Leukodystrophy
  • MPS I Mucopolysaccharidosis type I
  • MPS III Mucopolysaccharidosis type III
  • NPC Neimann Pick disease
  • NCL Neuronal Ceroidolipofuscinosis
  • SD Sandhoff disease
  • the lysosomal storage disorder is MLD.
  • the subject is a human subject.
  • MTs Metallothionerns
  • MTs are a family of small (-6-7 kDa), heat-resistant proteins containing 25-30% cysteine residues that are evolutionarily highly conserved in a broad range of species from yeast to mammals.
  • MTs are up-regulated by glucocorticoids, oxidative stress and a variety of heavy metals, such as copper, cadmium, mercury and zinc (Andrews (2000) Biochem. Pharmacol. 59, 95-104).
  • Isoforms range from MT-1 to MT-4 and have slightly different amino acid composition.
  • MTs bind metals and protect against their toxicity, as was first demonstrated in aquatic species, such as fish, arthropods and molluscs from contaminated waters.
  • MTs are considered to act as antioxidants, although by undetermined mechanisms.
  • MTs have been found to protect against apoptosis/necrosis induced by oxidative stress, etoposide, cisplatin, doxorubicin and X-irradiation (Cai et al. (2004) Toxicol. Lett. 146, 217-226; Chimienti et al. (2001) Free Radicals Biol. Med. 31, 1179-1 190; Wang et al. (2001) J. Pharmacol. Exp. Ther. 298, 461-468).
  • Apo-MTs are effectively degraded by lysosomal cathepsins, while metal-conjugated MTs are more stable (Hahn et al. (2001) Exp. Mol. Med. 33, 32-36; Feldman et al. (1978) Biochim. Biophys. Acta 544, 638-646).
  • Baird et al (Biochem J. 2006 Feb 15;394(Pt l):275-83) proposes that MTs may stabilize lysosomes following autophagocytotic delivery to the lysosomal compartment and Lee et al. (Glia. 2010 Aug;58(10): 1186-96) discloses that MT-3 may regulate lysosomal function in cultured astrocytes under both normal and oxidative conditions.
  • the MT transcript and protein described herein may be selected from, for example, metallothionein-lA (MT1A), metallothionein-lB (MT1B), metallothionein-lE (MT1E), metallothionein-lF (MT1F), metallothionein-lG (MT1G), metallothionein- 1H (MT1H), metallothionein-11 pseudogene (MTlIp or MTE), metallothionein-lL (MTIL or MTIR), metallothionem-lM (MTIM or MTIK), metallothionein-lX (MT1X), metallothionein-2 (MT2), metallothionein-2A (MT2A) metallothionein-3 (MT3) or metallothionein-4 (MT4).
  • MT1A metallothionein-lA
  • MT1B metallothionein-lE
  • MT1F metallothi
  • NP_005937.2 (MT1A); NP_005938.1 (MT1B); NP_783316.2 (MT1E);
  • NPJ 05940.1 (MT1F); NPJ)05941.1 (MT1G); NPJ)05942.1 (MT1H); NP_789846.1 (MTIM); NP_005943.1 (MT1X); NP_005944.1 (MT2); NP_005945.1 (MT3); and NP_116324.1 (MT4).
  • Further NCBI accession numbers for MT1 A, MT1E, MT2A and MTE-MT1IP are: NM_005946.2, NMJ 75617.3, NMJ)05953.3 and
  • lysosomal storage disorder refers to any of a group of diseases resulting from abnormal metabolism resulting in accumulation of a substrate (for example sulfatides, heparan sulphate, glycolipids, ceramide) in the lysosome.
  • a substrate for example sulfatides, heparan sulphate, glycolipids, ceramide
  • LSDs are caused by lysosomal dysfunction usually as a consequence of deficiency of a single enzyme required for the metabolism of lipids, glycoproteins (sugar-containing proteins) or so-called mucopolysaccharides.
  • the lysosome is commonly referred to as the cell's recycling center because it processes unwanted material into substances that the cell can utilize. Lysosomes break down this unwanted matter via enzymes, highly specialized proteins essential for survival. Lysosomal disorders are triggered when a particular enzyme exists in too small an amount or is missing altogether. When this happens, substances accumulate in the cell. In other words, when the lysosome doesn't function normally, excess products destined for breakdown and recycling are stored in the cell.
  • Hurler-Scheie disease a -L-lduronidase
  • LSDs include Activator Deficiency/GM2 Gangliosidosis, Alpha- mannosidosis, Aspartylglucosaminuria, Cholesteryl ester storage disease, Chronic Hexosaminidase A Deficiency, Cystinosis, Danon disease, Fabry disease, Farber disease, Fucosidosis, Galactosialidosis, Gaucher Disease, GM1 gangliosidosis, I-Cell disease/Mucolipidosis II, Infantile Free Sialic Acid Storage Disease/ISSD, Juvenile Hexosaminidase A Deficiency, Krabbe disease, Lysosomal acid lipase deficiency, Metachromatic Leukodystrophy, Mucopolysaccharidoses disorders, Multiple sulfatase deficiency, Niemann-Pick Disease, Neuronal Ceroid Lipofuscinoses,
  • Metachromatic Leukodystrophy is a demyelinating LSD due to mutations in the Arylsulfatase A (ARSA) gene and is a prototypical example of LSD with progressive accumulation of un-degraded substrates in the nervous system and secondary neuroinflammation and degeneration.
  • the genetic transmission of MLD is autosomal recessive and its overall incidence is estimated to be 1:40.000-1 :100.000 (von Figura and Jaeken (2001) Metachromatic Leukodystrophy.
  • the disease is classified according to the age at onset of symptoms into late infantile, with onset of symptoms before 2 years of age, juvenile - further subdivided in early and late, with symptoms onset before 16 years of age, and adult forms with a later onset.
  • Clinical manifestations consisting of severe and unrelenting motor and cognitive impairment, and disease progression are more severe in the early onset clinical variants, leading to death usually within the first decade of life.
  • a correlation between the phenotype of MLD patients and the type of ARSA mutation they bear has recently been demonstrated (Cesani et al. (2009) Hum Mutat, 30, E936-945; Biffi. et al. (2008) Clinical Genetics, 74, 349-357).
  • Nermann Pick disease is characterised by mutations in the SMPDl gene (disease types A and B) and mutations in NPCl and NPC2 (disease type C, NPC). Symptoms are related to the organs in which they accumulate. Enlargement of the liver and spleen (hepato splenomegaly) may cause reduced appetite, abdominal distension and pain as well as thrombocytopenia secondary to splenomegaly. NPC disease is an inherited disorder that is characterized by defects in intracellular cholesterol sorting and transport. Under normal conditions, the cholesteryl ester derived from low density lipoprotein mediates a complex feedback mechanism that stabilizes the intracellular concentration of cholesterol.
  • lipid trafficking In NPC patients, a defect in the activities of the NPCl and NPC2 proteins results in a very slow efflux of unesterified cholesterol.
  • the ratio of unesterified cholesterol and bis(monoacylglycerol)phosphate (BMP) is important within the internal lysosomal membrane for the efficient hydrolysis of membrane components to occur.
  • BMP bis(monoacylglycerol)phosphate
  • Sandhoff disease also knowrr as Jatzkewitz-Pilz syndrome and Hexosaminidase A and B deficiency, is a rare autosomal recessive, genetic, lipid storage disorder.
  • Sandhoff disease is associated with mutations in the HEXB gene which encodes Beta- hexosaminidase subunit beta.
  • the disease results from the inability to create the beta- hexosaminidase A and beta-hexosaminidase B, which is an enzyme that leads to a build-up of GM2 gangliosides in tissues of the body. This build-up is toxic at high levels, which leads to a progressive destruction of the central nervous system, damages the tissues and eventually leads to death.
  • Krabbe disease also Icnown as Globoid Cell Leukodystrophy or Galactosylceramide Lipidosis
  • Krabbe disease is caused by mutations in the GALC gene located on chromosome 14 (14q31), which causes a deficiency of galactocerebrosidase enzyme.
  • the build up of unmetabolized lipids affects the growth of the nerve's protective myelin sheath (the covering that insulates many nerves) and causes severe degeneration of motor skills.
  • MPS Mucopolysaccharidoses
  • MPS I is divided into three subtypes based on severity of symptoms. All three types result from an absence of, or insufficient levels of, the enzyme alpha-L-iduronidase.
  • MPS I H also called Hurler syndrome or a-L-iduronidase deficiency
  • MPS I S Scheie syndrome
  • MPS I H-S Hurler-Scheie syndrome
  • Hurler-Scheie syndrome is less severe than Hurler syndrome alone.
  • MPS II Hunter syndrome or iduronate sulfatase deficiency, is caused by lack of the enzyme iduronate sulfatase
  • MPS III Sanfilippo syndrome
  • Sanfilippo A is the most severe of the MPS III disorders and is caused by the missing or altered enzyme heparan N-sulfatase. Children with Sanfilippo A have the shortest survival rate among those with the MPS III disorders.
  • Sanfilippo B is caused by the missing or deficient enzyme alpha-N acetylglucosaminidase.
  • Sanfilippo C results from the missing or altered enzyme acetyl-CoAlpha-glucosaminide acetyltransferase.
  • Sanfilippo D is caused by the missing or deficient enzyme N-acetylglucosamine 6- sulfatase.
  • MPS IV Morquio syndrome
  • Type A N- acetylgalactosamine 6-sulfatase
  • Type B beta-galactosidase
  • MPS VI Maroteaux-Lamy syndrome, share many of the_physical symptoms found in Hurler syndrome and is casused be the deficient enzyme N-acetylgalactosamine 4- sulfatase.
  • MPS VII Sly syndrome, one of the least common forms of the mucopolysaccharidoses, is caused by deficiency of the enzyme beta-glucuronidase.
  • NCL Neuronal Ceroid Lipofuscinoses
  • lipopigments lipopigments
  • PPT1 palmitoyl protein thioesterase 1
  • the CLN2 gene encodes a 46kDa protein called lysosomal tripeptidyl peptidase I (TPPI) which cleaves tripeptides from terminal amine groups of partially unfolded proteins. Mutations of the CLN2 gene which encodes lysosomal tripeptidyl peptidase I (TPPI) typically result in a Late Infantile NCL (Jansky-Bielschowsky disease, LINCL) phenotype.
  • TPPI lysosomal tripeptidyl peptidase I
  • Gaucher' s disease is characterized by accumulation of the glycolipid glucocerebroside.
  • Three phenotypes have been described for Gaucher's disease that are denoted by the absence (type 1) or presence of neurological involvement during childhood (type 2) or adolescence (type 3) (Grabowski (1993) Adv Hum Genet; 21 :377-441).
  • Type 1 Gaucher's disease is panethnic, but is especially prevalent among persons of Ashkenazi Jewish descent.
  • the N370S and 84GG mutations are the most frequent mutations in the glucocerebrosidase gene among Ashkenazi Jews.
  • Type 1 Gaucher's disease tends to be severe and progressive in Japanese patients (see, Ida et al., Type 1 Gaucher Disease Patients: Phenotypic Expression and Natural History in Japanese Patients, Blood Cells, Molecules and Diseases, 1984, 24(5):73-81).
  • Type 3 Gaucher's disease associated with one or two copies of glucocerebrosidase gene variant L444P is prevalent in Swedish patients from the Norrbotten region.
  • an “antibody” is understood within the scope of the invention to refer to an antibody that is an intact molecule as well as fragments or portions thereof, such as Fab, F(ab')2, Fv and scFv.
  • sample is understood within the scope of the invention to refer to a sample which is derived from a subject.
  • the biological sample may be obtained directly from the subject or may be derived from cultured cells obtained from said subject.
  • the sample can be a whole blood sample, plasma sample, serum sample, urine or urinary sediment sample, broncheoalveolar lavage fluid sample, lymph sample, cerebrospinal fluid sample, saliva sample, semen sample, breast milk sample, or feces sample.
  • the test sample can also be a tissue sample from liver, kidney, muscle, heart, lung, spleen, lymph node, bone marrow, skin, blood vessels and valves, eye, or brain.
  • the test sample is a population of T lymphocytes or mononuclear cells.
  • polypeptide and “peptide” refer to a polymer in which the monomers are amino acids and are joined together through peptide or disulfide bonds.
  • protein encompasses proteins that have been modified e.g.
  • glycoproteins lipoproteins etc.
  • the term protein also encompasses homologues and derivatives of known proteins, and fragments thereof.
  • an “immunoassay” is understood within the scope of the invention to include an enzyme- linked immunosorbant assay (ELISA), a radioimmunoassay (RIA), an enzyme immunoassay (EIA), an immunofluorescence assay (IF A) or a luminescence assay (LIA) or a Western Blot assay (WB) or any other immunoassay commonly known in the art.
  • ELISA enzyme- linked immunosorbant assay
  • RIA radioimmunoassay
  • EIA enzyme immunoassay
  • IF A immunofluorescence assay
  • LIA luminescence assay
  • WB Western Blot assay
  • a “subject” refers to either a human or non-human animal.
  • non-human animals include vertebrates, e.g., mammals, such as non-human primates (particularly higher primates), dogs, rodents (e.g., mice, rats, or guinea pigs), pigs and cats, etc.
  • the subject is a human.
  • FIG. 1 Metallothioneins are over-expressed in T lymphocytes of patients with MLD.
  • A 26 probes, including 5 metallothioneins (marked in gray), are differentially expressed in T lymphocytes of 24 patients with MLD compared to 24 age- and sex- matched controls (CTR) (fold change>1.5; False Discovery RateO.01).
  • CTR age- and sex- matched controls
  • each column represents an individual and each row a probe. As shown in the color bar, over-expression is visualized in red and under-expression is displayed in blue.
  • Figure 2 Metallothioneins-based expression signatures predict diagnosis and prognostic subtypes.
  • A) In the training set (n 32) individuals with MLD were classified with 94% sensitivity and 100% specificity.
  • (B) In the independent test set (n 16) patients with MLD were classified with 75% sensitivity and 100% specificity.
  • the confusion matrix indicates the number of individuals classified in each class using Prediction Analysis of Microarray (PAM).
  • C,D Classifying patients with MLD into clinically relevant prognostic classes based on gene expression.
  • Figure 3 Ingenuity Pathway Analysis shows association of oxidative stress- related pathways with MLD.
  • A Histogram showing the significance P value (- log(P value)) of the ten canonical pathways most significantly perturbed in MLD patients compared to controls based on Ingenuity Pathway Analysis. The pathways involved in oxidative stress (orange) and inflammation (blue) are highlighted.
  • B Graphical representation of the Protein Ubiquitination pathway, which is the most perturbed in MLD patients based on Ingenuity Pathway Analysis. The color scale indicates in gray the less differentially expressed genes and in red the more over- expressed ones.
  • MLD brain samples show diffuse architectural effacement, with medium-to-large size phagic cell engulfing the perivascular zones of the white matter.
  • Kluver-Barrera staining for myelin highlights diffuse dysmyelination in subcortical areas, with granular overload of phospholipidic components of myelin in the cytoplasm of the phagic cells.
  • FIG. 5 MTs are over-expressed in brain of LSD patients.
  • F, G Western blot immunoreactivity for MT proteins on samples from 5 LSD brains and 3 related controls (CTR), normalized for protein content as shown by actin immunoreactivity and compared to the signal from purified MT1 protein (CO+) (F), and on post-mortem CSF samples from 1 LSD patient, 1 Parkinson's Disease patient (PD) and 1 control individual (CTR) at decreasing volumes (25, 15 and 5 ⁇ ) (G).
  • MTs are a dynamic marker of disease progression and response to treatment
  • Figure 7 MT protein abundance in brain of GLD mice.
  • Figure 8 MT role is investigated in in vitro cultures.
  • A relative MT1 and MT2 mRNA expression in pure mouse astrocyte cultures after 6 (dark gray bars) and 24 (light gray bars) hours of contact with conditioned medium from resting or LPS- activated microglia, as compared to LPS-treated control astrocytes.
  • PBMC Peripheral blood mononuclear cells
  • CSF Post-mortem cerebrospinal fluid
  • mice were sacrificed at a late, symptomatic stage of the disease (10 months for MLD and MPS I, 35 days for GLD and MPS III and 3 to 4 months for SD); for the GLD model, mice were sacrificed also at day 9-12, and at day 40 after having received lethal irradiation and total bone marrow transplantation from wild-type sibling donors at post-natal day 8 as described (Visigalli et al. (2009) Neurobiology of disease, 34, 51-62). After sacrifice, blood was collected in EDTA and peripheral cells were obtained through lysis and stored at -80°C, while brains were perfused with PBS, collected and stored at -80°C.
  • RIN RNA integrity number
  • RNA pellet was washed once with 70% ethanol, let dry and re-suspended in RNase-free water.
  • RNA from mouse peripheral blood cells and astrocyte co-cultures was extracted respectively with RNeasy plus Micro and Mini Kits (Qiagen).
  • RNA samples 350 ng of total RNA from each specimen were transcribed into biotinilated cRNA (TotalPrep RNA amplification kit - Ambion). cRNA was purified and its concentration and integrity were determined (2100 Bioanalyzer - Agilent).
  • Microarray analysis was performed according to the MIAME guidelines. The data discussed in this application have been deposited in NCBI's Gene Expression Omnibus (Edgar et al. (2002) Nucleic acids research, 30, 207-210) and are accessible through GEO Series accession number GSE23350
  • IP A Ingenuity Pathway Analysis
  • Receiver-operating characteristic (ROC) curve was obtained plotting the average ⁇ SEM of False Positive and False Negative fractions for MT1A, MT1E, MT2A and MTE qPCR data, as calculated using the Web-based Calculator for ROC Curves at http://www.rad.jlrmi.edu/jeng/iavarad/roc/JROCFITi.html. Area under the ROC curve was calculated using the trapezoid rule. Primary cultures of pure astrocytes
  • cortical astrocytes Primary cultures of cortical astrocytes were prepared from 2 to 3 day-old C57 mice according to Consonni et al. (2011) Mol Cell Neurosci, 48, 151-160. Briefly, after dissection, cortices were cut into small sections with a razor blade. The pieces were collected and washed twice in Hank's Balanced Salt Solution supplemented with 10 mM Hepes Na pH 7.4, 12 mM MgS04, 50 U/ml penicillin and 50 ⁇ g/ml streptomycin (Gibco).
  • the tissue was then incubated, in two subsequent steps, with 2.5 mg/ml trypsin type IX in presence of 1 mg/ml deoxyribonuclease (Calbiochem) for 10 min at 37 °C and mechanically dissociated.
  • the supernatant obtained was diluted 1 :1 in medium containing 10% donor horse serum (PAA Laboratories GmbH). After centrifugation (100 g for 10 min), cells were plated in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 ⁇ g/ml streptomycin.
  • astrocytes were trypsinized and replated in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 ⁇ g/ml streptomycin onto poly-lysine-coated plastic multiwells. Cultures were maintained at 37°C in a 5% C0 2 humidified incubator, and experiments were performed within 3 days after re-plating. Conditioned medium obtained from resting or activated (with 10 ng/ml LPS) microglia was administered to pure astrocytic cultures in substitution of their culture medium either 6 or 24 hours before RNA extraction. 10 ng/ml LPS was added directly to astrocyte culture medium either 6 or 24 hours before RNA extraction and used as negative control for activation.
  • Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 ⁇ g/ml streptomycin onto
  • Serum- containing medium was added in order to inactivate papain and a first centrifugation was done at 1000 rpm for 10 minutes. After removing supernatant, this step was repeated with fresh serum-containing medium. After the second centrifugation, the pellet was more finely dissociated with a 200 ⁇ tip pipette and then centrifuged at 1000 rpm for 10 minutes. After resuspension of the pellet, the cell suspension was plated into a 12-multiwell plate (usually 10 wells/hemisphere, corresponding roughly to 40 cm ) in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 ⁇ g/ml streptomycin.
  • Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 ⁇ g/ml streptomycin.
  • a 24h-incubation was performed for: (i) 10 ⁇ dexamethasone; (ii) 10% serum from wild-type and late-symptomatic GLD mice; (iii) MT1 and MT2, 20 ⁇ g/ml each. At the end of stimulation, cells were collected for RNA extraction as previously described.
  • RNA from human T lymphocytes and brains and from murine brains and cells were reverse-transcribed into cDNA (High Capacity cDNA Reverse Transcription Kit and Superscript III First Strand Synthesis - Life Technologies).
  • qPCR was performed on an ABI 7900HT or Viia7 (Life Technologies) and analyzed " by comparative threshold cycle method using Taqman Gene Expression Assay primers and probes for human Metallothionein 1A, IE, 2 A and E, murine Metallothionein 1 and 2 and CXCL11, and glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) as reference gene (Life Technologies).
  • GPDH glyceraldehyde-3 -phosphate dehydrogenase
  • Immunohistochemistry Consecutive 4- ⁇ thick sections from formalin-fixed paraffin-embedded brain tissue samples of MLD and controls brains were prepared and stained with routine Hematoxylin-Eosin and Kluver-Barrera (Luxol Fast Blue) method for myelin. Irrimunostaining with anti-metallothionein (MT) monoclonal antibodies (Dako, clone E9, diluition 1 :50) was performed on both MLD and control brain sections.
  • MT anti-metallothionein
  • the membrane was stripped for 15' with Restore Buffer (Thermo Scientific), blocked and incubated for 3h with goat -actin antibody (Santa Cruz Biotechnology) 1 : 10000 in TBS-T 3% milk and lh with a-goat HRP-conjugated antibody (Santa Cruz Biotechnology) 1 :20000 in TBS-T 3% milk. Blots were developed with ECL system (Millipore).
  • Example 2 - Metallothioneins are over-expressed in T lymphocytes of patients with MLD
  • MT1A, MT1E, MT2A and MTE- MT1IP include a cluster comprising four members of the family of metallothioneins (MT1A, MT1E, MT2A and MTE- MT1IP; NCBI RefSeq: NM_005946.2, NM_175617.3, NM 005953.3 and NR_003669.1 respectively) and the metallothionein pseudogene MT1P3- C20ORF127, which show on average a 1.60-fold over-expression in MLD patients as compared to controls.
  • differentially expressed genes were related to immune function (such as TIMD4, TNFSF13B, GNLY or GZMH).
  • Example 3 Gene expression signatures predict diagnosis and prognostic subtypes of MLD
  • To identify a transcriptional profile associated with MLD we randomly chose a subset of patient and control samples to build first a diagnostic and then a prognostic classifier for MLD.
  • This training set comprised -67% of the subjects (32 of 48 individuals), including 8 randomly selected early-onset MLD patients, 8 randomly selected late-onset MLD patients, and 16 age-matched controls.
  • Biomarkers useful for predicting disease prognosis are clinically needed for MLD.
  • a second classifier specifically designed to predict clinical prognostic subtypes of MLD based on gene expression changes in T lymphocytes.
  • PAM Proc Natl Acad Sci U S A, 99, 6567-6572
  • 31-gene prognostic classifier that again included MTl A, MTIE and MT2A as well as most of the 15 genes comprising the diagnostic classifier (Table 3).
  • the 31-gene prognostic classifier accurately classified individuals into the prognostic groups of early-onset or late-onset disease, and controls.
  • Example 4 Pathway analysis indicates a role for metallothioneins in the MLD disease process
  • IP A Ingenuity Pathway Analysis
  • NRF2-mediated pathway is implicated in the recruitment of antioxidant protems aimed at reducing the cellular oxidative damage, and in the repair and removal of damaged proteins from the cytoplasm through activation of chaperones and stress response proteins, together with ubiquitination and proteasomal degradation proteins.
  • Protein Ubiquitination pathway is the most perturbed in MLD patients based on Ingenuity Pathway Analysis. Protein Ubiquitination pathway genes that were less differentially expressed genes and more over-expressed were identified ( Figure 3B).
  • Example 5 - Metallothioneins arc over-expressed in the brain of patients with MLD
  • Example 6 Metallothioneins are general markers of nervous tissue damage in LSDs
  • mice affected by MLD, GLD, MPSI and III and SD, all characterized by demyelination and/or neurodegeneration of differential severity.
  • Both murine MT1 and MT2, orthologous of the human isoforms MT1 and MT2 were significantly over- expressed in LSD mouse models ( Figure 7A).
  • Figure 7A As observed in humans, the extent of expression changes varied in each specific lysosomal storage disease, with the mouse model for GLD showing the highest transcript levels, (fold change of 5.5 for MT1 and of 8.0 for MT2).
  • Example 7 - Metallothioneins are dynamic markers of disease progression and therapeutic response.
  • Hematopoietic stem cell transplantation from healthy donors has been introduced historically in many LSDs and more recently in GLD as a procedure capable of delaying disease onset and attenuating the disease phenotype by providing the functional enzyme to the affected nervous tissue by the means of CNS-infiltrating donor-derived cells (Escolar et al (2005), N. Engl. J. Med., 352, 2069-2081).
  • GLD animals at post-natal day 8 underwent bone marrow transplantation from wild-type donors. Transplanted mice were sacrificed at day 40 when only mildly symptomatic.
  • MT expression levels in treated animals were significantly lower than the levels measured in untreated age-matched affected controls, which were moribund at this disease stage, indicating that MTs could represent a marker not only of disease progression but also of response to treatment (Figure 6A).
  • Example 8 The role of metallothioneins in brain oxidative stress and inflammation response is dissected in vitro.
  • microglia are known to be activated in the neuroiiiflammatory and neurodegenerative context typical of LSDs (Visigalli et al (2009)while astrocytes are the main source of MTs in the affected brain (Chung et al (2004) Journal of neurochemistry, 88, 454-461), as also confirmed by our data on mouse and human samples.
  • LSDs involve the CNS, and the LSD-associated neurological manifestations represent a major cause of morbidity and mortality for the affected patients.
  • a more reachable source such as blood cells
  • the transcriptome analysis performed on T lymphocytes of patients provided a progression biomarker useful not only for MLD but also for the broader class of LSDs with CNS involvement.
  • MT expression could possibly be activated as a consequence of the block of autophagy, which has been shown to be a direct consequence of the lysosomal dysfunction (Settieri et al (2008) Hum Mol Genet, 17, 119-129; Baird et al (2006) Biochem J, 394, 275-283), as an attempt by the cell to lower the oxidative stress, counteract the accumulating pro-apoptotic stimuli and mitigate tissue inflammation.
  • analysis on microarray data points to a selective perturbation of pathways related to oxidative stress and inflammation in MLD patients' samples.
  • MT increase both in the CNS and in blood, could also reflect a cell-extrinsic response to still unidentified soluble factors, as suggested by the mechanistic studies performed with GLD mouse serum.
  • Table 1 List of genes most differentially expressed in MLD patients compared to age- and sex-matched controls.
  • ATP1B1 ATPase Na+/K+ transporting, beta 1 polypeptide 0.6482 0.000070 0
  • TNFSF13B TNF (ligand) superfamily member 13b 1.5734 0.000556 0
  • TNFSF13B TNF (ligand) superfamily member 13b 1.5327 0.001947 0
  • EMP1 epithelial membrane protein 1 1.5823 0.002258 0
  • PRDM1 PR domain containing 1 with ZNF domain 1.5055 0.003636 0
  • GZMH granzyme H (cathepsin G-like 2, protein h-CCPX) 1.9466 0.008254 0
  • Table 2 List of genes belonging to the binary diagnostic classifier used to discriminate between MLD patients and controls.
  • ALOX5AP Arachidonate 5-lipoxygenase-activating protein 0.1316 -0.1316
  • IFITM2 Interferon induced transmembrane protein 2 -0.0262 0.0262
  • IFITM1 Interferon induced transmembrane protein 1 -0.0244 0.0244
  • Table 3 List of genes belonging to the diagnostic classifier used to discriminate between early-onset MLD patients, late-onset MLD patients and controls.
  • CNN2 Calponin 2 0 -0.1216 0
  • ALOX5AP Arachidonate 5-lipoxygenase-activating protein 0 0 -0.0994
  • SH2D1A SH2 domain protein 1A, Duncan's disease 0.0368 0 0
  • ANAPC10 anaphase promoting complex subunit 0 1.190 1.90E- -03
  • HLA-A major histocompatibility complex class I, A 1.033 6.01 E- -01
  • HLA-B major histocompatibility complex class I, B 1.042 4.95E- -01
  • HSP90AA1 heat shock protein 90kDa alpha (cytosolic), class A member 1 1.033 7.53E- -01
  • HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E- -02
  • HSPA6 heat shock 70kDa protein 6 (HSP70B') 1122 3.85E- -01
  • PSMA4 proteasome (prosome, macropain) subunit alpha type, 4 1.105 8.02E- -02
  • PSMA5 proteasome (prosome, macropain) subunit alpha type, 5 1.074 7.85E- -02
  • PSMB1 proteasome (prosome, macropain) subunit beta type, 1 1.035 4.01 E- -01
  • PSMB4 proteasome (prosome, macropain) subunit beta type, 4 1.024 4.61 E- -01
  • PSMB6 proteasome (prosome, macropain) subunit beta type, 6 1.058 2.70E- -01
  • PSMB8 proteasome prosome, macropain subunit, beta type, 8 (large 1.056 4.75E- -01 multifunctional peptidase 7)
  • PSMB9 proteasome prosome, macropain subunit, beta type, 9 (large 1.078 2.48E- -01 multifunctional peptidase 2)
  • PSMC1 proteasome prosome, macropain
  • 26S subunit ATPase
  • PSMC2 proteasome prosome, macropain
  • 26S subunit ATPase
  • PSMC4 proteasome prosome, macropain
  • 26S subunit ATPase
  • PSMC6 proteasome prosome, macropain
  • 26S subunit ATPase
  • PSMD6 proteasome prosome, macropain
  • 26S subunit non-ATPase
  • PSME1 proteasome (prosome, macropain) activator subunit 1 PA28 1.030 5.81 E- -01 alpha
  • PSME2 proteasome (prosome, macropain) activator subunit 2 PA28 1.040 5.84E- -01 beta
  • TAP1 transporter 1 1, ATP-binding cassette, sub-family B (MDR/TAP) 1.051 3.59E- -01
  • TAP2 transporter 2 ATP-binding cassette, sub-family B (MDR/TAP) 1.174 1.42E- -02
  • UBE2E1 ubiquitin-conjugating enzyme E2E 1 (UBC4/5 homoiog, yeast) 1.063 3.09E- -01
  • UBE2J1 ubiquitin-conjugating enzyme E2, J1 (UBC6 homoiog, yeast) 1.120 6.47E- -02
  • UBE2N ubiquitin-conjugating enzyme E2N (UBC13 homoiog, yeast) 1.048 2.13E- -01
  • UBE4A ubiquitination factor E4A (UFD2 homoiog, yeast) 1.052 4.43E- -01
  • UBE4B ubiquitination factor E4B (UFD2 homoiog, yeast) 1.080 8.18E- -02
  • UCHL3 ubiquitin carboxyl-terminal esterase L3 ubiquitin thiolesterase 1.070 1.35E- -01
  • NDUFAB1 NADH dehydrogenase (ubiquinone) 1 alpha/beta subcomplex, 1.140 5.07E- -02
  • NDUFC1 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1 , 1.087 9.10E- -02
  • PPA1 pyrophosphatase (inorganic) 1 1.048 3.51 E- -01
  • SDHC succinate dehydrogenase complex subunit C, integral 1.016 6.96E- -01 membrane protein, 15kDa
  • AIFM1 apoptosis-inducing factor, mitochondrion-associated, 1 1.032 3.75E- -01
  • APH1A anterior pharynx defective 1 homolog A (C. elegans) 1.015 8.34E- -01
  • APH1 B anterior pharynx defective 1 homolog B (C. elegans) 1.029 4.24E- -01
  • FIS1 fission 1 mitochondria outer membrane homolog (S. 1.006 9.02E- -01 cerevisiae)
  • MAP2K4 mitogen-activated protein kinase kinase 4 1.008 8.85E- -01
  • MAPK9 mitogen-activated protein kinase 9 1.028 6.41 E- -01
  • NDUFAB1 NADH dehydrogenase (ubiquinone) 1 alpha/beta subcomplex, 1.140 5.07E- -02 1 , 8kDa
  • SDHC succinate dehydrogenase complex subunit C, integral 1.016 6.96E- -01 membrane protein, 15kDa
  • CD3D CD3d molecule delta (CD3-TCR complex) 1.101 6.06E- -02
  • ELK1 ELK1 member of ETS oncogene family 1.006 9.34E- -01
  • EP300 E1 A binding protein p300 1.054 4.08E- -01
  • GTF2A2 general transcription factor IIA, 2, 12kDa 1.092 2.24E- -01
  • GTF2B general transcription factor IIB 1.037 3.44E- -01
  • GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E- -02
  • GTF2E2 general transcription factor HE, polypeptide 2, beta 34kDa 1.017 6.26E- -01
  • GTF2F2 general transcription factor IIF polypeptide 2, 30kDa 1.083 7.47E- -02
  • GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E- -02
  • GTF2H5 general transcription factor IIH polypeptide 5 1.185 1.55E- -02
  • HMGB1 high-mobility group box 1 1.198 1.35E- -02
  • HSP90AA1 heat shock protein 90kDa alpha (cytosolic), class A member 1 1.033 7.53E- -01
  • HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E- -02
  • HSPA6 heat shock 70kDa protein 6 (HSP70B') 1.122 3.85E- -01
  • IL5 interleukin 5 colony-stimulating factor, eosinophil
  • MAP2K1 mitogen-activated protein kinase kinase 1 1.005 9.21 E- -01
  • MAP2K4 mitogen-activated protein kinase kinase 4 1.008 8.85E- -01
  • MAP3K1 mitogen-activated protein kinase kinase kinase 1 1.136 1.72E- -01
  • MAP3K7 mitogen-activated protein kinase kinase kinase 7 1.035 4.72E- -01
  • MAPK1 mitogen-activated protein kinase 1 1.042 4.45E- -01
  • APK9 mitogen-activated protein kinase 9 1.028 6.41 E- -01
  • MAPK14 mitogen-activated protein kinase 14 1.006 8.97E- -01
  • NCOA1 nuclear receptor coactivator 1 1.051 3.70E- -01
  • NCOA2 nuclear receptor coactivator 2 1.010 8.62E- -01
  • NCOA3 nuclear receptor coactivator 3 1.030 5.51 E- -01
  • NFAT5 nuclear factor of activated T-cells 5 tonicity-responsive 1.056 4.46E- -01
  • NR3C1 nuclear receptor subfamily 3 group C, member 1 1.017 7.32E- -01
  • NRIP1 nuclear receptor interacting protein 1 1.007 9.20E- -01
  • PIK3CA phosphoinositide-3-kinase catalytic, alpha polypeptide 1.040 3.60E- -01
  • PLAU plasminogen activator urokinase 1.273 3.78E- -02
  • RNA II DNA directed polypeptide A, 220kDa 1.011 8.32E- -01
  • RNA II DNA directed polypeptide C, 33kDa 1.005 9.29E- -01
  • RNA II DNA directed polypeptide D 1.040 2.99E- -01
  • RNA II DNA directed polypeptide F 1.056 3.20E- -01
  • RNA II DNA directed polypeptide G 1.066 2.79E- -01
  • RNA II DNA directed polypeptide H 1.027 5.75E- -01
  • RNA II DNA directed polypeptide I, 14.5kDa 1.000 9.96E- -01
  • RNA polymerase II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E- -01 polymerase (RNA) II (DNA directed) polypeptide J2 1.035 7.06E- -01
  • PPP3CA protein phosphatase 3, catalytic subunit, alpha isozyme 1.017 7.37E- -01
  • PTGS2 prostaglandin-endoperoxide synthase 2 prostaglandin G/H 1.150 3.14E- -01 synthase and cyclooxygenase
  • TAF2 TAF2 RNA polymerase II TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E- -01 associated factor TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E- -01 associated factor TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E- -01 associated factor 150kDa
  • TAF5 TAF5 RNA polymerase II TAF5 TAF5 RNA polymerase II
  • TAF9 TAF9 RNA polymerase II TATA box binding protein (TBP)- 1.116 1.27E- -01 associated factor, 32kDa
  • TAF10 TAF10 RNA polymerase II TATA box binding protein (TBP)- 1.007 8.82E- -01 associated factor, 30kDa
  • TAF12 TAF12 RNA polymerase II TATA box binding protein (TBP)- 1.073 1.05E- -01 associated factor, 20kDa
  • TAF13 TAF13 RNA polymerase II TATA box binding protein (TBP)- 1.033 6.37E- -01 associated factor, 18kDa
  • TAF15 TAF15 RNA polymerase II TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E- -01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E- -01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E- -01 associated factor 68kDa
  • TAF1 L TAF1 RNA polymerase II
  • TAF4B TAF4b RNA polymerase II TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP) TATA box binding protein- 1.036 4.90E- -01 associated factor, 105kDa
  • TAF9B TAF9B RNA polymerase II TAF9B TAF9B RNA polymerase II
  • CD74 CD74 molecule major histocompatibility complex, class II 1.1 13 2.19E-01 invariant chain
  • HLA-A major histocompatibility complex class I, A 1.033 6.01 E-01
  • HLA-B major histocompatibility complex class I, B 1.042 4.95E-01
  • HLA-DMB major histocompatibility complex class II, DM beta 1.079 4.13E-01
  • HLA-DOA major histocompatibility complex class II, DO alpha 1.083 2.97E-01
  • HLA-DPA1 major histocompatibility complex, class II, DP alpha 1 1.193 2.41 E-01
  • HLA-DQA1 major histocompatibility complex, class II, DQ alpha 1 1.204 2.98E-01
  • HLA-F major histocompatibility complex class I, F 1.148 1.27E-01
  • HLA-G major histocompatibility complex class I, G 1.055 6.14E-01
  • PSMB8 proteasome prosome, macropain subunit, beta type, 8 (large 1.056 4.75E-01 multifunctional peptidase 7)
  • PSMB9 proteasome prosome, macropain subunit, beta type, 9 (large 1.078 2.48E-01 multifunctional peptidase 2)
  • TAP1 transporter 1 ATP-binding cassette, sub-family B (MDR/TAP) 1.051 3.59E-01-
  • TAP2 transporter 2 ATP-binding cassette, sub-family B (MDR/TAP) 1.174 1.42 E-02
  • HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E-02
  • MPP6 membrane protein, palmitoylated 6 (MAGUK p55 subfamily 1.047 4.61 E-01 member 6)
  • NME7 non-metastatic cells 7, protein expressed in (nucleoside- 1.062 2.42E-01 diphosphate kinase)
  • PNPT1 polyribonucleotide nucleotidyltransferase 1 1.12 3.82E-02
  • POLE2 polymerase DNA directed
  • epsilon 2 p59 subunit
  • RNA II DNA directed polypeptide A, 220kDa 1.011 8.32E-01
  • RNA II DNA directed polypeptide C, 33kDa 1.005 9.29E-01
  • RNA II DNA directed polypeptide F 1.056 3.20E-01
  • RNA II DNA directed polypeptide G 1.066 2.79E-01
  • RNA II DNA directed polypeptide H 1.027 5.75E-01
  • RNA II DNA directed polypeptide J, 13.3kDa 1.062 3.99E-01
  • RNA III DNA directed polypeptide A, 155kDa 1.011 8.72E-01
  • RNA III DNA directed polypeptide B 1.037 5.06E-01
  • RNA III DNA directed polypeptide C (62kD) 1.068 1.05E-01
  • RNA III DNA directed polypeptide H (22.9kD) 1.036 3.59E-01
  • RNA III DNA directed polypeptide K, 12.3 kDa 1.105 1.14E-01
  • PRIM1 primase DNA, polypeptide 1 (49kDa) 1.056 3.94E-01
  • PRPS2 phosphoribosyl pyrophosphate synthetase 2 1.16 4.62E-03
  • PSMC1 proteasome proteasome (prosome, macropain) 26S subunit, ATPase, 1 1.052 2.11 E-01
  • PSMC2 proteasome prosome, macropain
  • 26S subunit ATPase
  • PSMC4 proteasome prosome, macropain 26S subunit, ATPase, 4 1.04 3.05E-01
  • PSMC6 proteasome prosome, macropain 26S subunit, ATPase, 6 1.051 2.44E-01
  • TAF9 TAF9 RNA polymerase II TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
  • VPS4B vacuolar protein sorting 4 homolog B (S. cerevisiae) 1.026 6.24E-01
  • GTF2A2 general transcription factor IIA, 2, 12kDa 1.092 2.24E-01
  • GTF2B general transcription factor IIB 1.037 3.44E-01
  • GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E-02
  • GTF2E2 general transcription factor HE, polypeptide 2, beta 34kDa 1.017 6.26E-01
  • GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E-02
  • GTF2H5 general transcription factor IIH, polypeptide 5 1.185 1.55E-02
  • RNA II DNA directed polypeptide C, 33kDa 1 .005 9.29E-01
  • RNA II DNA directed polypeptide F 1.056 3.20E-01
  • RNA II DNA directed polypeptide G 1.066 2.79E-01
  • RNA II DNA directed polypeptide H 1.027 5.75E-01
  • RNA II DNA directed polypeptide J, 13.3kDa 1.062 3.99E-01
  • RNA II DNA directed polypeptide J2 1.035 7.06E-01
  • TAF2 TAF2 RNA polymerase II TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor 150kDa
  • TAF5 TAF5 RNA polymerase II TAF5 TAF5 RNA polymerase II
  • TAF9 TAF9 RNA polymerase II TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
  • TAF12 TAF12 RNA polymerase II TAF12 TAF12 RNA polymerase II
  • TATA box binding protein (TBP)- 1.073 1.05E-01 associated factor 20kDa
  • TAF13 TAF13 RNA polymerase II TATA box binding protein (TBP)- 1.033 6.37E-01 associated factor, 18kDa
  • TAF15 TAF15 RNA polymerase II TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TAF10 TAF10 RNA polymerase II TATA box binding protein (TBP)- 1.007 8.82E-01
  • TAF1 L TAF1 RNA polymerase II
  • TAF4B TAF4b RNA polymerase II TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor 105kDa
  • TAF9B TAF9B RNA polymerase II TAF9B TAF9B RNA polymerase II
  • APAF1 apoptotic peptidase activating factor 1 1.036 4.74E-01
  • CD3D CD3d molecule CD3D CD3d molecule, delta (CD3-TCR complex) 1.101 6.06E-02
  • CD3G CD3g molecule CD3G CD3g molecule, gamma (CD3-TCR complex) 1.016 7.89E-01
  • GZMB granzyme B (granzyme 2, cytotoxic T-lymphocyte-associated 1.389 5.20E-03 serine esterase 1 )
  • HLA-A major histocompatibility complex class I, A 1.033 6.01 E-01
  • HLA-B major histocompatibility complex class I, B 1.042 4.95E-01
  • HLA-DMB major histocompatibility complex class II, DM beta 1.079 4.13E-01
  • HLA-DOA major histocompatibility complex class II, DO alpha 1.083 2.97E-01
  • HLA-DPAT major histocompatibility complex class II, DP alpha 1 1.193 2.41 E-01
  • HLA-DQA1 major histocompatibility complex, class II, DQ alpha 1 1.204 2.98E-01
  • HLA-F major histocompatibility complex class I, F 1.148 1.27E-01
  • HLA-G major histocompatibility complex class I, G 1.055 6.14E-01
  • CTBP1 C-terminal binding protein 1 1.007 8.92E-01
  • GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E-02
  • GTF2F2 general transcription factor IIF polypeptide 2, 30kQa 1.083 7.47E-02
  • GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E-02
  • GTF2H5 general transcription factor IIH, polypeptide 5 1.185 1.55E-02
  • HNRNPD heterogeneous nuclear ribonucleoprotein D (AU-rich element 1.015 7.86E-01
  • RNA binding protein 1 37kDa
  • MAP2K1 mitogen -activated protein kinase kinase 1 1.005 9.21 E-01
  • NCOA1 nuclear receptor coactivator 1 1.051 3.70E-01
  • NR3C1 nuclear receptor subfamily 3 group C, member 1 (glucocorticoid 1.017 7.32E-01 receptor)
  • NRIP1 nuclear receptor interacting protein 1 1.007 9.20E-01
  • RNA II DNA directed polypeptide C, 33kDa 1.005 9.29E-01
  • RNA II DNA directed polypeptide F 1.056 3.20E-01
  • RNA II DNA directed polypeptide G 1.066 2.79E-01
  • RNA II DNA directed polypeptide H 1.027 5.75E-01
  • RNA POLR2J polymerase II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E-01
  • RNA POLR2J2/P polymerase II (DNA directed) polypeptide J2 1.035 7.06E-01
  • PRKDC protein kinase DNA-activated, catalytic polypeptide 1.025 - • 5-.91 E-01
  • TAF2 TAF2 RNA polymerase II TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor TAF2 TAF2 RNA polymerase II
  • TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor 150kDa
  • TAF5 TAF5 RNA polymerase II TAF5 TAF5 RNA polymerase II
  • TAF9 TAF9 RNA polymerase II TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
  • TAF12 TAF12 RNA polymerase II TAF12 TAF12 RNA polymerase II
  • TATA box binding protein (TBP)- 1.073 1.05E-01 associated factor 20kDa
  • TAF13 TAF13 RNA polymerase II TATA box binding protein (TBP)- 1.033 6.37E-01 associated factor, 18kDa
  • TAF15 TAF15 RNA polymerase II TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor TAF15 TAF15 RNA polymerase II
  • TAF10 TAF10 RNA polymerase II TATA box binding protein (TBP)- 1.007 8.82E-01
  • TAF1 L TAF1 RNA polymerase II
  • TAF4B TAF4b RNA polymerase II TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor TAF4B TAF4b RNA polymerase II
  • TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor 105kDa
  • TAF9B TAF9B RNA polymerase II TAF9B TAF9B RNA polymerase II
  • AKR1A1 aldo-keto reductase family 1 member A1 (aldehyde reductase) 1.009 8.80E- -01
  • EIF2AK3 eukaryotic translation initiation factor 2-alpha kinase 3 1.047 3.23E- -01
  • HERPUD1 homocysteine-inducible, endoplasmic reticulum stress- 1.092 7.29E- -02 inducible, ubiquitin-like domain member 1
  • HMOX1 heme oxygenase (decycling) 1 1.057 6.24E- -01

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Abstract

A method of diagnosis or prognosis of a lysosomal storage disorder in a subject, wherein said method comprises (i) providing a sample from said subject, (ii) determining the expression level of a metallothionein in said sample, (iii) comparing the expression level of the metallothionein in said sample with the expression level of the metallothionein in a sample from healthy subjects or in a previous sample from the same subject.

Description

Biomarkers for Lysosomal Storage Disorders
Field of the Invention
The present invention relates to methods useful in diagnosis and prognosis of a lysosomal storage disorder by determining the expression levels of one or more metallothioneins. The present invention also relates to a method of monitoring the progress of a lysosomal storage disorder and its response to therapy by determining the expression levels of one or more metallothioneins.
Background to the Invention
Lysosomal Storage Disorders (LSDs) comprise a class of inherited diseases characterized by disruption of normal lysosomal function resulting in the accumulation of incompletely degraded substrates that have been targeted for degradation after endocytosis or autophagy. The ensuing accumulation of the substrate itself or of the product(s) of an alternative metabolic route in lysosomes affects the architecture and function of the cells, leading to cell dysfunction or death. Further, the primary defect is frequently exacerbated by secondary responses. This is of particular relevance in the Central Nervous System (CNS) where neuroinflammation occurs representing a primary reaction to substrate accumulation within microglia and astrocytes and/or an inflammatory response to primary neuronal or oligodendroglial damage.
Metachromatic Leukodystrophy (MLD), a demyelinating LSD due to mutations in the Arylsulfatase A (ARSA) gene (Aicardi (1998) In Disease of the nervous system in childhood. Cambridge University Press; Kolodny and Neudorfer (2003) Metachromatic Leukodistrophy and Multiple Sulfatase Deficiency: Sulfatide Lipidosis. 3rd ed, Heinemann) is a prototypical example of LSD with progressive accumulation of un-degraded substrates in the nervous system and secondary neuroinflammation and degeneration. The genetic transmission of MLD is autosomal recessive and its overall incidence is estimated to be 1 :40.000-1 :100.000 (von Figura and Jaeken (2001) Metachromatic Leukodystrophy. The Metabolic and Molecular Bases of Inherited Diseases, 8th Ed Vol 3, pp 3695-3724).
Clinical manifestations, consisting of severe and unrelenting motor and cognitive impairment, and disease progression are more severe in the early onset clinical variants, leading to death usually within the first decade of life. A correlation between the phenotype of MLD patients and the type of ARSA mutation they bear has recently been demonstrated (Cesani et al. (2009) Hum Mutat, 30, E936-945; Biffi. et al. (2008) Clinical Genetics, 74, 349-357).
LSDs are rare diseases with variable phenotypes and unpredictable progression over long periods. Accordingly, there is an urgent need for identifying biomarkers associated with LSDs and which can be used to provide improved methods of diagnosing LSDs. Furthermore, considerable research activity is currently focused on developing strategies to target LSDs with CNS involvement. Gene therapy (Biffi et al. (2004) J. Clin. Invest., 113, 1118-1129; Biffi et al. (2006) J Clin. Invest., 116, 3070- 3082), enzyme replacement therapy (Matzner et al. (2005) Hum Mol Genet, 14, 1139- 1152; Matzner et al. (2009) Mol Ther, 17, 600-606), and small molecular weight compounds are advancing from pre-clinical to early clinical studies and may enable disease-modifying treatments for these so far incurable, devastating diseases. One major obstacle in designing clinical trials is the definition of suitable clinical endpoints. Because LSDs have variable phenotypes and unpredictable progression over long periods, it is difficult to predict which aspects of the complex CNS- associated pathology may be stabilized or improved by treatment and therefore to decide which clinical manifestations should be measured to demonstrate benefit from the novel treatments. Moreover, the target organs are not easily accessible to repeated follow-up evaluations. The availability of validated surrogate markers of brain disease that could be monitored in support of clinical endpoints would be of great benefit in this situation. Indeed, these markers could potentially provide an early indicator of efficacy, before significant changes in clinical symptoms can be observed.
Biochemical changes are well documented in peripheral blood of patients affected by a variety of neurological disorders (Scherzer et al. (2007) Proc Natl Acad Sci U S A, 104, 955-960; Scherzer et al. (2004) Arch Neurol, 61, 1200-1205; Jellinger et al. (2008) Journal of cellular and molecular medicine, 12, 1094-1117; Vogt et al. (2003) Annals of neurology, 53, 819-822; Comabella et al. (2005) Journal of neuroimmunology, 158, 231-239; Sumner et al. (2006) Neurology, 66, 1067-1073; Gregg et al. (2008). Genomics, 91, 22-29). Moreover, the circulating mononuclear cells of MLD patients, although not showing clear signs of functional impairment, indeed lack ARSA activity, as measured by a specific biochemical assay (Baum et al. (1950) Clin Chim Acta, 4, 4530). Unfortunately, thus far no clear correlation between the levels of ARSA expression/activity and patients' phenotypes has been established, rendering the enzyme poorly informative as a disease marker.
The identification of reliable dynamic biomarkers correlating with disease onset, progression, and response to treatment is highly needed for LSDs. However, dynamic, sensitive, reliable, and possibly polyvalent markers have yet to be identified. The present invention addresses this need.
Summary of Invention
According io a first aspect of the invention there is provided a method of diagnosis or prognosis of a lysosomal storage disorder in a subject, wherein said method comprises
(i) providing a sample from said subject,
(ii) deteraiining the expression level of a metallothionein in said sample,
(iii) comparing the expression level of the metallothionein in said sample with the expression level of the metallothionein in a sample from a healthy subject or a previous sample from said subject.
An increase in the expression level of metallothionein in a sample relative to a sample from a healthy subject may be indicative of a lysosomal storage disorder. The lower the expression level of metallothionein, the more favourable the prognosis.
According to one embodiment there is provided a method of diagnosis of a lysosomal storage disorder (LSD) in a subject, wherein said method comprises:
(i) providing a sample from said subject, (ii) determining the expression level of a metallothionein in said sample,
(iii) diagnosing a lysosomal storage disorder when the expression level of the metallothionein is increased compared to the expression level of a metallothionein in a sample from healthy subjects.
In various embodiments, the finding of expression levels of metallothionein of at least about 1.5, 2, 5, 10 or 50 fold relative to a healthy subject may indicate the presence of an LSD. In another embodiment, the finding of expression levels of metallothionein of at least about 1.5, 2, 2.5, 3, 4 or 5 fold relative to a healthy subject when measuring metallothionein mRNA abundance in T-cells/mononuclear cells may indicate the presence of an LSD. Preferably, the finding of expression levels of metallothionein of at least about 10, 15 or 20 fold relative to a healthy subject when measuring metallothionein mRNA abundance in brain samples or nerve biopsies may indicate the presence of a lysosomal storage disorder.
According to another aspect of the present invention there is provided a method for monitoring the progress of a lysosomal storage disorder (LSD) in a subject comprising the steps of:
(i) providing a first sample from a subject,
(ii) determining the expression level of a metallothionein in said first sample,
(iii) providing a second sample from the subject wherein said second sample is obtained from the subject after said first sample,
(iv) comparing the expression level of the metallothionein in the second sample with the expression level of the metallothionein in the first sample.
An increase in metallothionein expression in the second sample relative to the first sample indicates disease progression. A decrease in metallothionein expression in the second sample relative to the first sample indicates amelioration of the symptoms.
Preferably the second sample is obtained from the subject at least 1, 2, 5, 10, 20, 50, 100, 200 or 300 days after the first sample. The second aspect of the invention may be used to momtor the progress of an LSD in response to treatment (e.g., by bone marrow transplantation, gene therapy treatment, enzyme replacement therapy) of the LSD. Thus, the present invention may be used to assess the effectiveness of an LSD treatment. The treatment may be administered between the taking of the first sample and the taking of the second sample from the patient.
Preferably, the sample is nervous tissue, ¾lood (including blood cells and plasma/serum) or cerebrospinal fluid. In one embodiment, the sample is a population of T cells.
The metallothionein expression levels may be determined by, for example, quantitative RT-PCR. In one embodiment the metallothionein expression levels may be determined by an immunoassay such as enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunofluorescence assay (IF A), enzyme linked assay (EI A), luminescence immunoassay (LI A), or Western Blot (WB). The immunoassay may use an antibody immunospecifc for the metallothionein to detect metallothionein protein levels. The metallothionein protein levels may be determined also by HPLC and mass spectrometry (Monicou et al. (2010) Anal Chem 82 6947-57).
The metallothionein may be selected from the group consisting of MT1, MT2, MT3 and MT4.
In one embodiment, the metallothionein is selected from the group consisting of MT1 and MT2.
In one embodiment, the metallothionein is selected from the group consisting of MT1A, MT1E, MT1F, MT2, MT3 and MT4. In another embodiment, the metallothionein is selected from the group consisting of MT1A, MT1E and MT2A. In a further embodiment, the metallothionein is selected from the group consisting of MT1 A, MT1E, MT2A and MTE.
The methods of the present invention may comprise deternii ing the expression level of more than one metallothionein. In one embodiment the method comprises determining the expression levels of MT1A, MT1E and MT2A. In another embodiment the method comprises determining the expression levels of MT1A, MT1E, MT2A and/or MTE.
Indeed, due to the high similarity between members of the metallothionein family, the methods of the present invention may identify the expression levels of metallothionein using antibodies raised against the general metallothionein protein.
According to a third aspect of the present invention there is provided an antibody directed against a metallothionein for use in a diagnostic for a lysosomal storage disorder.
In a preferred embodiment, the lysosomal storage disorder is selected from the group consisting of Metachromatic Leukodystrophy (MLD), Globoid Cell Leukodystrophy (GLD), Mucopolysaccharidosis type I (MPS I), Mucopolysaccharidosis type III (MPS III), Neimann Pick disease (NPC), Neuronal Ceroidolipofuscinosis (NCL) and Sandhoff disease (SD).
In a particularly preferred embodiment, the lysosomal storage disorder is MLD. In a particularly preferred embodiment, the subject is a human subject.
Detailed Description
The practice of the present invention will employ, unless otherwise indicated, conventional techniques of chemistry, molecular biology, microbiology, recombinant DNA and immunology, which are within the capabilities of a person of ordinary skill in the art. Such techniques are explained in the literature. See, for example, J. Sambrook, E. F. Fritsch, and T. Maniatis, 1989, Molecular Cloning: A Laboratory Manual, Second Edition, Books 1-3, Col d Spring Harbor Laboratory Press; Ausubel, F. M. et al. (1995 and periodic supplements; Current Protocols in Molecular Biology, ch. 9, 13, and 16, John Wiley & Sons, New York, N.Y.); B. Roe, J. Crabtree, and A. Kahn, 1996, DNA Isolation and Sequencing: Essential Techniques, John Wiley & Sons; J. M. Polak and James O'D. McGee, 1990, In Situ Hybridization: Principles and Practice; Oxford University Press; M. J. Gait (Editor), 1984, Oligonucleotide Synthesis: A Practical Approach, Irl Press; D. M. J. Lilley and J. E. Dahlberg, 1992, Methods of Enzymology: DNA Structure Part A: Synthesis and Physical Analysis of DNA Methods in Enzymology, Academic Press; and E. M. Shevach and W. Strober, 1992 and periodic supplements, Current Protocols in Immunology, John Wiley & Sons, New York, NY. Each of these general texts is herein incorporated by reference.
Metallothioneins
Metallothionerns (MTs) are a family of small (-6-7 kDa), heat-resistant proteins containing 25-30% cysteine residues that are evolutionarily highly conserved in a broad range of species from yeast to mammals. MTs are up-regulated by glucocorticoids, oxidative stress and a variety of heavy metals, such as copper, cadmium, mercury and zinc (Andrews (2000) Biochem. Pharmacol. 59, 95-104). Isoforms range from MT-1 to MT-4 and have slightly different amino acid composition. MTs bind metals and protect against their toxicity, as was first demonstrated in aquatic species, such as fish, arthropods and molluscs from contaminated waters. Apart from binding heavy metals, MTs are considered to act as antioxidants, although by undetermined mechanisms. Thus MTs have been found to protect against apoptosis/necrosis induced by oxidative stress, etoposide, cisplatin, doxorubicin and X-irradiation (Cai et al. (2004) Toxicol. Lett. 146, 217-226; Chimienti et al. (2001) Free Radicals Biol. Med. 31, 1179-1 190; Wang et al. (2001) J. Pharmacol. Exp. Ther. 298, 461-468). Apo-MTs are effectively degraded by lysosomal cathepsins, while metal-conjugated MTs are more stable (Hahn et al. (2001) Exp. Mol. Med. 33, 32-36; Feldman et al. (1978) Biochim. Biophys. Acta 544, 638-646).
Baird et al (Biochem J. 2006 Feb 15;394(Pt l):275-83) proposes that MTs may stabilize lysosomes following autophagocytotic delivery to the lysosomal compartment and Lee et al. (Glia. 2010 Aug;58(10): 1186-96) discloses that MT-3 may regulate lysosomal function in cultured astrocytes under both normal and oxidative conditions. The MT transcript and protein described herein may be selected from, for example, metallothionein-lA (MT1A), metallothionein-lB (MT1B), metallothionein-lE (MT1E), metallothionein-lF (MT1F), metallothionein-lG (MT1G), metallothionein- 1H (MT1H), metallothionein-11 pseudogene (MTlIp or MTE), metallothionein-lL (MTIL or MTIR), metallothionem-lM (MTIM or MTIK), metallothionein-lX (MT1X), metallothionein-2 (MT2), metallothionein-2A (MT2A) metallothionein-3 (MT3) or metallothionein-4 (MT4).
The NCBI protein accession numbers of the main members of the family
are: NP_005937.2 (MT1A); NP_005938.1 (MT1B); NP_783316.2 (MT1E);
NPJ)05940.1 (MT1F); NPJ)05941.1 (MT1G); NPJ)05942.1 (MT1H); NP_789846.1 (MTIM); NP_005943.1 (MT1X); NP_005944.1 (MT2); NP_005945.1 (MT3); and NP_116324.1 (MT4). Further NCBI accession numbers for MT1 A, MT1E, MT2A and MTE-MT1IP are: NM_005946.2, NMJ 75617.3, NMJ)05953.3 and
NRJ303669.1 respectively.
Lysosomal storage disorders
As used herein the phrase "lysosomal storage disorder" (LSD) refers to any of a group of diseases resulting from abnormal metabolism resulting in accumulation of a substrate (for example sulfatides, heparan sulphate, glycolipids, ceramide) in the lysosome.
LSDs are caused by lysosomal dysfunction usually as a consequence of deficiency of a single enzyme required for the metabolism of lipids, glycoproteins (sugar-containing proteins) or so-called mucopolysaccharides.
The lysosome is commonly referred to as the cell's recycling center because it processes unwanted material into substances that the cell can utilize. Lysosomes break down this unwanted matter via enzymes, highly specialized proteins essential for survival. Lysosomal disorders are triggered when a particular enzyme exists in too small an amount or is missing altogether. When this happens, substances accumulate in the cell. In other words, when the lysosome doesn't function normally, excess products destined for breakdown and recycling are stored in the cell.
Below is a non-limiting list of exemplary LSDs and their associated defective enzyme.
Lysosomal storage disorder Defective enzyme
Pompe disease Acid a-glucosidase
Gaucher disease Acid β-glucosidase or glucocerebrosidase
GMi-gangliosidosis Acid β-galactosidase
Tay-Sachs disease β-Hexosaminidase A
Sandhoff disease β-Hexosaminidase B
Niemann-Pick disease Acid sphingomyelinase
Krabbe disease Galactocerebrosidase
Farber disease Acid ceramidase
Metachromatic leukodystrophy Arylsulfatase A
Hurler-Scheie disease a -L-lduronidase
Hunter disease lduronate-2-sul"fatase
Sanfilippo disease A Heparan N-sulfatase
Sanfilippo disease B a-N-Acetylglucosaminidase
Sanfilippo disease C Acetyl-CoA: a-glucosaminide N-acetyltransferase
Sanfilippo disease D N-Acetylglucosamine-6-sulfate sulfatase
Morquio disease A N-Acetylgalactosamine-6-sulfate sulfatase
Morquio disease B Acid β-galactosidase
Maroteaux-Lamy disease Arylsulfatase B
Sly disease β-Glucuronidase
Alpha-mannosidosis Acid a-rnannosidase
Beta-mannosidosis Acid β-mannosidase
Fucosidosis Acid -L-fucosidase
Sialidosis Sialidase
Schindler-Kanzaki disease a-N-acetylgalactosaminidase Example of LSDs include Activator Deficiency/GM2 Gangliosidosis, Alpha- mannosidosis, Aspartylglucosaminuria, Cholesteryl ester storage disease, Chronic Hexosaminidase A Deficiency, Cystinosis, Danon disease, Fabry disease, Farber disease, Fucosidosis, Galactosialidosis, Gaucher Disease, GM1 gangliosidosis, I-Cell disease/Mucolipidosis II, Infantile Free Sialic Acid Storage Disease/ISSD, Juvenile Hexosaminidase A Deficiency, Krabbe disease, Lysosomal acid lipase deficiency, Metachromatic Leukodystrophy, Mucopolysaccharidoses disorders, Multiple sulfatase deficiency, Niemann-Pick Disease, Neuronal Ceroid Lipofuscinoses, Pompe disease/Glycogen storage disease type II, Pycnodysostosis, Sandhoff disease, Schindler disease, Salla disease/Sialic Acid Storage Disease, Tay-Sachs/GM2 gangliosidosis and Wolman disease.
Some of these diseases are described in more detail below:
Metachromatic leukodystrophy
Metachromatic Leukodystrophy (MLD) is a demyelinating LSD due to mutations in the Arylsulfatase A (ARSA) gene and is a prototypical example of LSD with progressive accumulation of un-degraded substrates in the nervous system and secondary neuroinflammation and degeneration. The genetic transmission of MLD is autosomal recessive and its overall incidence is estimated to be 1:40.000-1 :100.000 (von Figura and Jaeken (2001) Metachromatic Leukodystrophy. The Metabolic and Molecular Bases of Inherited Diseases, , 8th Ed Vol 3, pp 3695-3724.).
The disease is classified according to the age at onset of symptoms into late infantile, with onset of symptoms before 2 years of age, juvenile - further subdivided in early and late, with symptoms onset before 16 years of age, and adult forms with a later onset. Clinical manifestations, consisting of severe and unrelenting motor and cognitive impairment, and disease progression are more severe in the early onset clinical variants, leading to death usually within the first decade of life. A correlation between the phenotype of MLD patients and the type of ARSA mutation they bear has recently been demonstrated (Cesani et al. (2009) Hum Mutat, 30, E936-945; Biffi. et al. (2008) Clinical Genetics, 74, 349-357). Neimann Pick disease
Nermann Pick disease is characterised by mutations in the SMPDl gene (disease types A and B) and mutations in NPCl and NPC2 (disease type C, NPC). Symptoms are related to the organs in which they accumulate. Enlargement of the liver and spleen (hepato splenomegaly) may cause reduced appetite, abdominal distension and pain as well as thrombocytopenia secondary to splenomegaly. NPC disease is an inherited disorder that is characterized by defects in intracellular cholesterol sorting and transport. Under normal conditions, the cholesteryl ester derived from low density lipoprotein mediates a complex feedback mechanism that stabilizes the intracellular concentration of cholesterol. In NPC patients, a defect in the activities of the NPCl and NPC2 proteins results in a very slow efflux of unesterified cholesterol. The ratio of unesterified cholesterol and bis(monoacylglycerol)phosphate (BMP) is important within the internal lysosomal membrane for the efficient hydrolysis of membrane components to occur. As a result, not only cholesterol, but other membrane components (i.e., sphingomyelin, BMP, glucosylceramide, glycospingolipids, phospholipids, and glycolipids) may secondarily accumulate depending on the cellular lipid profile. The defects in lipid trafficking that occur in NPC cells can lead to cell- autonomous death.
Sandhoff disease
Sandhoff disease, also knowrr as Jatzkewitz-Pilz syndrome and Hexosaminidase A and B deficiency, is a rare autosomal recessive, genetic, lipid storage disorder. Sandhoff disease is associated with mutations in the HEXB gene which encodes Beta- hexosaminidase subunit beta. The disease results from the inability to create the beta- hexosaminidase A and beta-hexosaminidase B, which is an enzyme that leads to a build-up of GM2 gangliosides in tissues of the body. This build-up is toxic at high levels, which leads to a progressive destruction of the central nervous system, damages the tissues and eventually leads to death. There are three subsets of the disease based on when the patient shows symptoms: classic infantile, juvenile and adult late onset. Each form is classified by the severity of the symptoms as well as the age in which the patient shows these symptoms (Zhang, et al. (1994) Human Molecular Genetics 3 (1): 139—145).
Krabbe disease
Krabbe disease (also Icnown as Globoid Cell Leukodystrophy or Galactosylceramide Lipidosis) is a degenerative disorder that affects the myelin sheath of the nervous system. Krabbe disease is caused by mutations in the GALC gene located on chromosome 14 (14q31), which causes a deficiency of galactocerebrosidase enzyme. The build up of unmetabolized lipids affects the growth of the nerve's protective myelin sheath (the covering that insulates many nerves) and causes severe degeneration of motor skills.
Mucopolysaccharidoses
Mucopolysaccharidoses (MPS) are a group of LSDs caused by the absence or malfunctioning of lysosomal enzymes needed to break down glycosaminoglycans.
MPS I is divided into three subtypes based on severity of symptoms. All three types result from an absence of, or insufficient levels of, the enzyme alpha-L-iduronidase. MPS I H (also called Hurler syndrome or a-L-iduronidase deficiency), is the most severe of the MPS I subtypes while MPS I S, Scheie syndrome, is the mildest form of MPS I. MPS I H-S, Hurler-Scheie syndrome, is less severe than Hurler syndrome alone.
MPS II, Hunter syndrome or iduronate sulfatase deficiency, is caused by lack of the enzyme iduronate sulfatase
MPS III, Sanfilippo syndrome, is marked by severe neurological symptoms. There are four distinct types of Sanfilippo syndrome, each caused by alteration of a different enzyme needed to completely break down the heparan sulfate sugar chain. Sanfilippo A is the most severe of the MPS III disorders and is caused by the missing or altered enzyme heparan N-sulfatase. Children with Sanfilippo A have the shortest survival rate among those with the MPS III disorders. Sanfilippo B is caused by the missing or deficient enzyme alpha-N acetylglucosaminidase. Sanfilippo C results from the missing or altered enzyme acetyl-CoAlpha-glucosaminide acetyltransferase. Sanfilippo D is caused by the missing or deficient enzyme N-acetylglucosamine 6- sulfatase.
MPS IV, Morquio syndrome, results from the missing or deficient enzymes N- acetylgalactosamine 6-sulfatase (Type A) or beta-galactosidase (Type B) needed to break down the keratan sulfate sugar chain.
MPS VI, Maroteaux-Lamy syndrome, share many of the_physical symptoms found in Hurler syndrome and is casused be the deficient enzyme N-acetylgalactosamine 4- sulfatase.
MPS VII, Sly syndrome, one of the least common forms of the mucopolysaccharidoses, is caused by deficiency of the enzyme beta-glucuronidase.
Neuronal Ceroid Lipo fuscinoses
Neuronal Ceroid Lipofuscinoses (NCL) is the general name for a family of neurodegenerative disorders that result from excessive accumulation of lipopigments (lipofuscin) in the body's tissues. These lipofuscin materials build up in neuronal cells and many organs, including the liver, spleen, myocardium, and kidneys. Mutations in the CLN1 gene induce Infantile NCL (Santavuori-Haltia disease, INCL). The mutation typically results in a deficient form of a lysosomal enzyme called palmitoyl protein thioesterase 1 (PPT1).
The CLN2 gene encodes a 46kDa protein called lysosomal tripeptidyl peptidase I (TPPI) which cleaves tripeptides from terminal amine groups of partially unfolded proteins. Mutations of the CLN2 gene which encodes lysosomal tripeptidyl peptidase I (TPPI) typically result in a Late Infantile NCL (Jansky-Bielschowsky disease, LINCL) phenotype.
Juvenile NCL (Batten disease, JNCL) has been associated with mutation in the CLN3 gene.
Gaucher' s disease Gaucher's disease, is characterized by accumulation of the glycolipid glucocerebroside. Three phenotypes have been described for Gaucher's disease that are denoted by the absence (type 1) or presence of neurological involvement during childhood (type 2) or adolescence (type 3) (Grabowski (1993) Adv Hum Genet; 21 :377-441). Type 1 Gaucher's disease is panethnic, but is especially prevalent among persons of Ashkenazi Jewish descent. The N370S and 84GG mutations are the most frequent mutations in the glucocerebrosidase gene among Ashkenazi Jews. Other rare glucocerebrosidase gene variants identified in patients of Ashkenazi descent with Gaucher's disease include L444P, IVS2+1G->A, V394L, and R496H. In contrast to presentation of Type 1 Gaucher's disease in Ashkenazi Jews, Type 1 Gaucher's disease tends to be severe and progressive in Japanese patients (see, Ida et al., Type 1 Gaucher Disease Patients: Phenotypic Expression and Natural History in Japanese Patients, Blood Cells, Molecules and Diseases, 1984, 24(5):73-81). In addition, Type 3 Gaucher's disease, associated with one or two copies of glucocerebrosidase gene variant L444P is prevalent in Swedish patients from the Norrbotten region.
Antibody
An "antibody" is understood within the scope of the invention to refer to an antibody that is an intact molecule as well as fragments or portions thereof, such as Fab, F(ab')2, Fv and scFv.
Sample
A "sample" is understood within the scope of the invention to refer to a sample which is derived from a subject. The biological sample may be obtained directly from the subject or may be derived from cultured cells obtained from said subject.
The sample can be a whole blood sample, plasma sample, serum sample, urine or urinary sediment sample, broncheoalveolar lavage fluid sample, lymph sample, cerebrospinal fluid sample, saliva sample, semen sample, breast milk sample, or feces sample. The test sample can also be a tissue sample from liver, kidney, muscle, heart, lung, spleen, lymph node, bone marrow, skin, blood vessels and valves, eye, or brain. In one embodiment, the test sample is a population of T lymphocytes or mononuclear cells.
Protein
A "protein" is understood within the scope of the invention to include single-chain polypeptide molecules, as well as multiple-polypeptide complexes where individual constituent polypeptides are linked by covalent or non-covalent means. As used herein, the terms "polypeptide" and "peptide" refer to a polymer in which the monomers are amino acids and are joined together through peptide or disulfide bonds.
Portions of the protein may be referred to as a "subunit" or a "domain" or "fragment" as applicable. The term protein encompasses proteins that have been modified e.g.
glycoproteins, lipoproteins etc. The term protein also encompasses homologues and derivatives of known proteins, and fragments thereof.
Immunoassay
An "immunoassay" is understood within the scope of the invention to include an enzyme- linked immunosorbant assay (ELISA), a radioimmunoassay (RIA), an enzyme immunoassay (EIA), an immunofluorescence assay (IF A) or a luminescence assay (LIA) or a Western Blot assay (WB) or any other immunoassay commonly known in the art.
Subject
A "subject" refers to either a human or non-human animal. Examples of non-human animals include vertebrates, e.g., mammals, such as non-human primates (particularly higher primates), dogs, rodents (e.g., mice, rats, or guinea pigs), pigs and cats, etc. In a preferred embodiment, the subject is a human.
By a healthy subject it is meant a corresponding subject that does not have an LSD. Further preferred features and embodiments of the present invention will now be described by way of non-limiting example and with reference to the accompanying drawings in which:
Figure 1: Metallothioneins are over-expressed in T lymphocytes of patients with MLD. (A) 26 probes, including 5 metallothioneins (marked in gray), are differentially expressed in T lymphocytes of 24 patients with MLD compared to 24 age- and sex- matched controls (CTR) (fold change>1.5; False Discovery RateO.01). In this heatmap each column represents an individual and each row a probe. As shown in the color bar, over-expression is visualized in red and under-expression is displayed in blue. (B, C) Over-expression of metallothioneins 1A, (MTIA), IE (MTIE), 2A (MT2A) and E (MTE) is confirmed by qPCR on T lymphocytes of MLD patients from the microarray cohort (MTIA: fold change=1.33; MTIE: fold change=2.29, P value=3.11E-6; MT2A: fold change=1.66, P value=3.74E-6; MTE: fold change=1.25) (B) and from an independent cohort of newly recruited early-onset MLD patients (n=7) and age-and sex-matched controls (n=9) (MTIA: fold change=2.25; MTIE: fold change=9.66, P value=0.015; MT2A: fold change=4.57, P value=0.0073; MTE: fold change=3.14) (C). (D) Receiver-operating characteristic (ROC) curve of the average ± SEM of False Positive and False Negative fractions for MTIA, MTIE, MT2A and MTE qPCR data, (area under the ROC curve: 0.75).
Figure 2: Metallothioneins-based expression signatures predict diagnosis and prognostic subtypes. (A,B) A 15-gene signature that includes methallothioneins MTIA, MTIE and MT2A accurately classifies patients with MLD based on gene expression in T lymphocytes. (A) In the training set (n = 32) individuals with MLD were classified with 94% sensitivity and 100% specificity. (B) In the independent test set (n = 16) patients with MLD were classified with 75% sensitivity and 100% specificity. The confusion matrix indicates the number of individuals classified in each class using Prediction Analysis of Microarray (PAM). (C,D) Classifying patients with MLD into clinically relevant prognostic classes based on gene expression. (C) In the training set (n = 32) patients with early-onset MLD (e-o MLD), late-onset MLD (l-o MLD) and controls were classified with 88% sensitivity and 100% specificity for both e-o MLD and l-o MLD. (D) In the independent test set (n = 16) patients with early-onset and late-onset MLD and 8 controls were classified with a sensitivity and specificity respectively of 50% and 100% for e-o MLD and of 75% and 92% for l-o MLD. The confusion matrix indicates the number of individuals classified in each class using PAM.
Figure 3: Ingenuity Pathway Analysis shows association of oxidative stress- related pathways with MLD. (A) Histogram showing the significance P value (- log(P value)) of the ten canonical pathways most significantly perturbed in MLD patients compared to controls based on Ingenuity Pathway Analysis. The pathways involved in oxidative stress (orange) and inflammation (blue) are highlighted. (B) Graphical representation of the Protein Ubiquitination pathway, which is the most perturbed in MLD patients based on Ingenuity Pathway Analysis. The color scale indicates in gray the less differentially expressed genes and in red the more over- expressed ones.
Figure 4: Metallothioneins are over-expressed in brain of MLD patients. (A)
Relative mRNA abundance of metallothioneins MTIA, MTIE, MT2A and MTE in white and gray matter portions of the frontal cortex of 4 MLD patients compared to 4 controls (mean ± SEM, *=P value<0.05). (B) immunohistochemistry images of the H&E, Kluver-Barrera and a-MT stainings on white and gray matter portions of a representative MLD brain and a related control brain (CTR); magnification 20X. A strong immunoreactivity for MTs can be observed in MLD brains, in subcortical white matter areas as well as in cortical regions, particularly restricted to cells morphologically identifiable as astrocytes. MLD brain samples show diffuse architectural effacement, with medium-to-large size phagic cell engulfing the perivascular zones of the white matter. Kluver-Barrera staining for myelin highlights diffuse dysmyelination in subcortical areas, with granular overload of phospholipidic components of myelin in the cytoplasm of the phagic cells.
Figure 5: MTs are over-expressed in brain of LSD patients. (A) Cumulative expression data of metallothioneins MTIA, MTIE, MT2A and MTE in brains from LSD patients (n=20) compared to controls (CTR; n=T7) (mean ± SEM; **=p value<0.01) (B-E) Relative mRNA abundance of MTIA (B), MTIE (C), MT2A (D) and MTE (E) for the separately analyzed LSDs (mean + SEM; **=P value<0.01 with one-way ANOVA with post-hoc Dunnett's analysis) (MLD n=4; MPSI n=3; MPSIII n=4; NPC n=3; NCL n=4; SD n=2; GLD n=2; CTR n=17). (F, G) Western blot immunoreactivity for MT proteins on samples from 5 LSD brains and 3 related controls (CTR), normalized for protein content as shown by actin immunoreactivity and compared to the signal from purified MT1 protein (CO+) (F), and on post-mortem CSF samples from 1 LSD patient, 1 Parkinson's Disease patient (PD) and 1 control individual (CTR) at decreasing volumes (25, 15 and 5 μΐ) (G).
Figure 6: MTs are a dynamic marker of disease progression and response to treatment (A) Relative abundance of MT1 and MT2 mRNA in blood cells of pre- symptomatic (9-12 days, n=9) and late symptomatic (25-35 days, n=18) GLD mice and in brain tissue of pre-symptomatic (9-12 days, n=8), late symptomatic (35 days, n=6) and transplanted (40 days, n=3) GLD mice compared to age-matched controls (mean + SEM. **=P value<0.01). (B) Comparison of the correlation between relative mRNA abundance of the average of MT1A, MT1E, MT2A and MTE and age (expressed in months) for early-onset MLD patients (dark gray squares) and for age- matched healthy controls (light gray dots). Pearson correlation coefficient: 0.617 P value=0.0432) for patients and 0.474 (P value=0.119) for controls.
Figure 7: MT protein abundance in brain of GLD mice. (A) qPCR data for MT1 and MT2 on brains from murine disease models at a late symptomatic stage -10 months for MLD (n=4) and MPS I (n=4), 35 days for GLD (n=6) and MPS III (n=4), 3 to 4 months for SD (n=5) - compared to controls (mean + SEM. *=P value<0.05 and **= value<0.01). (B) Quantification of the signal positive (+) area for MT and Glial Fibrillary Acid Protein (GFAP) signals in brain slices form 35 -day old GLD and age- matched control mice (n=3 sections per mouse, on 3 different mice); **=p value<0.01 with one-way ANOVA with post-hoc Bonferroni's analysis. (C) Representative immunofluorescence images showing GFAP+ MTs expressing astrocytes in the brain of GLD and control (CTR) mice; magnification 40x (80x in the insert).
Figure 8: MT role is investigated in in vitro cultures. (A) relative MT1 and MT2 mRNA expression in pure mouse astrocyte cultures after 6 (dark gray bars) and 24 (light gray bars) hours of contact with conditioned medium from resting or LPS- activated microglia, as compared to LPS-treated control astrocytes. (B) relative MTl and MT2 mRNA expression in cells freshly dissected from brain (0 days in culture) and astrocyte-microglia co-cultures (3, 7, 10 and 14 days in culture) isolated from 30- day old GLD mice, as compared to matched WT samples (n=4-8; mean ± SEM). (C) relative MTl and MT2 mRNA expression in WT astrocyte-microglia co-cultures exposed to pro-inflammatory (LPS) and pro-oxidative (H202+BSO) stimuli, alone or combined with anti-inflammatory (dexamethasone) or anti-oxidative (trolox) drugs, and to 10% serum from WT or late-symptomatic GLD mice (n=6-16; mean ± SEM; **=P valueO.Ol ; n.s= value>0.05 to control condition (first column); §=P value<0.05; §§= valueO.Ol ; n.s.=P value>0.05 respectively to dexamethasone-, trolox- or WT serum-treated controls). Astrocyte activation was assessed by CXCL11 expression (-= absence of transcript; += moderate presence of transcript; ++= strong presence of transcript). (D) Relative MTl and MT2 abundance in astrocyte-microglia co-cultures supplemented with 4 different kinds of horse serum, with or without activation with LPS.
Example 1 - Materials and methods
Patients' and normal donors' sample collection
Peripheral blood mononuclear cells (PBMC) were obtained from blood drawn of 24 MLD patients (13 Late Infantile, 7 Early Juvenile, 2 Late Juvenile and 2 Adult) and of 24 age- and sex-matched healthy controls at San Raffaele Hospital upon informed consent collection (in the context of the protocols LDM1 and TIGET 02, approved by the Institutional Ethical Board). A T lymphocyte culture was established by stimulating PBMC at day 0 with PHA (1 μ^ηιΐ) and from day 2 with IL-2 (300 U/ml) in IMDM 5% Human Serum (HS) for 10 days. At the end of the culture, cells were collected and stored in liquid nitrogen.
Post-mortem snap-frozen human brain samples from the frontal cortex of patients affected by MLD (n=4), MPSI (n=3), MPSIII (n=4), NPC (n=3), NCL (n=4), GLD (n=2) and SD (n=2), and of 17 age- and sex-matched controls were obtained from the NICHD Brain and Tissue Banlc for Developmental Disorders at University of Maryland, Baltimore.
Post-mortem formalin-fixed human brain samples from the frontal cortex of patients affected by MLD (n=2), and of age- and sex-matched controls (n=2) were obtained from the NICHD Brain and Tissue Bank for Developmental Disorders at University of Maryland, Baltimore.
Post-mortem cerebrospinal fluid (CSF) from patients affected by NCL (n=l) and PD (n=l), and of matched controls were obtained from the NICHD Brain and Tissue Bank for Developmental Disorders at University of Maryland, Baltimore.Protocols for gene expression analysis on human biospecimens were approved by the Institutional Review Board of Brigham and Women's Hospital.
Mouse tissue collection
All the animal use procedures described herein were approved by the Institutional Animal Care and Use Committee of the San Raffaele Scientific Institute. Animals from the mouse models of different LSD and age-matched wild-type siblings were sacrificed at a late, symptomatic stage of the disease (10 months for MLD and MPS I, 35 days for GLD and MPS III and 3 to 4 months for SD); for the GLD model, mice were sacrificed also at day 9-12, and at day 40 after having received lethal irradiation and total bone marrow transplantation from wild-type sibling donors at post-natal day 8 as described (Visigalli et al. (2009) Neurobiology of disease, 34, 51-62). After sacrifice, blood was collected in EDTA and peripheral cells were obtained through lysis and stored at -80°C, while brains were perfused with PBS, collected and stored at -80°C.
RNA extraction from human and murine samples
Frozen T lymphocytes were thawed, cultured for 18 hours in X-VIVO 10 5% HS + IL-2 100 U/ml, then collected, stratified over an equal volume of FBS and centrifuged for 15 minutes at 150 g. RNA was extracted (RNeasy Mini Kit - Qiagen) and RNA quality was assessed calculating the RNA integrity number (RIN) (2100 Bioanalyzer - Agilent) as described (Scherzer et al. (2008) PNAS, 105, 10907-10912). All samples had a RIN higher than 9. 200 of brain, tissue were re-suspended in 2 ml TRI Reagent (SIGMA), homogenized in ice and additioned with 400 μΐ chloroform: iso-amyl alcohol 24:1. After vigorous shake and 15 minutes centrifugation at 7000 g at 4°C, the aqueous phase was collected and RNA was precipitated by the addition of 1 volume of isopropanol and 10 minutes of spinning at 7000 g at 4°C. RNA pellet was washed once with 70% ethanol, let dry and re-suspended in RNase-free water.
RNA from mouse peripheral blood cells and astrocyte co-cultures was extracted respectively with RNeasy plus Micro and Mini Kits (Qiagen).
Microarray hybridization
350 ng of total RNA from each specimen were transcribed into biotinilated cRNA (TotalPrep RNA amplification kit - Ambion). cRNA was purified and its concentration and integrity were determined (2100 Bioanalyzer - Agilent).
1.5 μg of cRNA from 24 MLD patients and 24 age- and sex-matched controls were hybridized on 6-sample Illumina WG_v3 Beadchips, targeting more than 25,000 annotated genes with 48,804 probes derived from the National Center for Biotechnology Information Reference Sequence (NCBI) RefSeq (Build 36.2, Rel 22) and the UniGene (Build 199) databases, for 20 hours at 55°C, then Beadchips were washed two times, incubated with streptavidine-Cy3, dried and scanned on BeadArray Reader.
Genome-wide expression analysis
Microarray analysis was performed according to the MIAME guidelines. The data discussed in this application have been deposited in NCBI's Gene Expression Omnibus (Edgar et al. (2002) Nucleic acids research, 30, 207-210) and are accessible through GEO Series accession number GSE23350
(http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23350 .
Data were processed, normalized by "average normalization", and quality-controlled using GenomeStudio software (Illumina). Single gene analysis was performed only on probes with a detection p value < 0.0001 on at least one array (corresponding to 11,883 probes out of more than 48,000). Significance Analysis of Microarrays (SAM) (Stanford University Labs - Tusher et al (2001), PNAS, 98, 5116-5121) was used to identify the probes most differentially expressed between MLD patients and control groups. This conservative statistical analysis keeps the number of false positives at a minimum, although the number of false negatives is likely to remain high. Unsupervised hierarchical clustering using an algorithm in the DNA-Chip Analyzer (dChip) package (www.dchip.org) was used to group genes and samples according to relative variation in gene expression patterns and to generate graphical representations of relative gene expression levels.
Prediction Analysis of Microarrays (PAM) (Stanford University Labs (Tibshirani et al. (2002) Diagnosis Proc Natl Acad Sci U S A, 99, 6567-6572) using the "nearest shrunken centroids" statistic was applied to a training set of 16 MLD patients (analyzed altogether or divided into early-onset (late infantile) and late-onset (juvenile and adult) patients and 16 age- and sex-matched controls to build a binary diagnostic classifier (using the threshold value of 2.87, corresponding to the lowest training error). The classifier was then used to unsupervisedly classify the samples belonging to the test set (8 MLD patients and 8 age- and sex-matched controls) to the patient and control groups. A confusion matrix was used to present the outcome of the analysis. Sensitivity was calculated as the number of true patients divided by the sum of true patients and false controls. Specificity was calculated as the number of true controls divided by the sum -of true controls and false patients.
Ingenuity Pathway Analysis (IP A) software was used to perform the pathways analysis on the 11,883 expressed probes. The network score, based on the hypergeometric distribution, was the negative log of the P value calculated with the right-tailed Fisher's Exact test.
Receiver-operating characteristic (ROC) curve was obtained plotting the average ± SEM of False Positive and False Negative fractions for MT1A, MT1E, MT2A and MTE qPCR data, as calculated using the Web-based Calculator for ROC Curves at http://www.rad.jlrmi.edu/jeng/iavarad/roc/JROCFITi.html. Area under the ROC curve was calculated using the trapezoid rule. Primary cultures of pure astrocytes
Primary cultures of cortical astrocytes were prepared from 2 to 3 day-old C57 mice according to Consonni et al. (2011) Mol Cell Neurosci, 48, 151-160. Briefly, after dissection, cortices were cut into small sections with a razor blade. The pieces were collected and washed twice in Hank's Balanced Salt Solution supplemented with 10 mM Hepes Na pH 7.4, 12 mM MgS04, 50 U/ml penicillin and 50 μg/ml streptomycin (Gibco). The tissue was then incubated, in two subsequent steps, with 2.5 mg/ml trypsin type IX in presence of 1 mg/ml deoxyribonuclease (Calbiochem) for 10 min at 37 °C and mechanically dissociated. The supernatant obtained was diluted 1 :1 in medium containing 10% donor horse serum (PAA Laboratories GmbH). After centrifugation (100 g for 10 min), cells were plated in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 μg/ml streptomycin. Cells were maintained in 75 cm2 flasks (about 1 per pup) at 37 °C in a 5% C02 humidified incubator. In order to remove microglia and oligodendrocyte progenitors and obtain pure cultures of type- 1 astrocytes (>99.8%), flasks were shaken at 200 rpm for 24 h at 37°C at days 2 and 6 after dissection, in Mnimum Essential Medium with Hank's salts supplemented with 10%» donor horse serum (PAA Laboratories GmbH), 33 mM glucose, 2 mM glutamax and 10 mM Hepes/ Na pH 7.4. After reaching confluence, astrocytes were trypsinized and replated in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 μg/ml streptomycin onto poly-lysine-coated plastic multiwells. Cultures were maintained at 37°C in a 5% C02 humidified incubator, and experiments were performed within 3 days after re-plating. Conditioned medium obtained from resting or activated (with 10 ng/ml LPS) microglia was administered to pure astrocytic cultures in substitution of their culture medium either 6 or 24 hours before RNA extraction. 10 ng/ml LPS was added directly to astrocyte culture medium either 6 or 24 hours before RNA extraction and used as negative control for activation.
Primary co-cultures of microglia and astrocytes
Primary co-cultures of microglia and astrocytes were prepared from 30-day-old C57 mice. Briefly, after dissection, one hemisphere was cut into small sections with a razor blade, collected in 5 ml of freshly prepared digestion solution with 36.5 mg Papain (Wortington), 10 mg EDTA, 10 mg cystein, 0.5 mg DNAse I in 50 ml of Earle's Balanced Salt Solution, roughly dissociated with a 1 ml tip pipette and let incubate for 30 minutes at 37°C in a 5% C02 humidified incubator. Afterwards, a new dissociation was performed, until the suspension was nearly homogeneous. Serum- containing medium was added in order to inactivate papain and a first centrifugation was done at 1000 rpm for 10 minutes. After removing supernatant, this step was repeated with fresh serum-containing medium. After the second centrifugation, the pellet was more finely dissociated with a 200 μΐ tip pipette and then centrifuged at 1000 rpm for 10 minutes. After resuspension of the pellet, the cell suspension was plated into a 12-multiwell plate (usually 10 wells/hemisphere, corresponding roughly to 40 cm ) in Minimum Essential Medium Eagle supplemented with 10% donor horse serum, 33 mM glucose, 2 mM glutamax (Gibco), 50 U/ml penicillin, 50 μg/ml streptomycin. Cells were maintained at 37°C in a 5% C02 humidified incubator and washed with PBS the day after, and then every 4-6 days until stimulation (14 DIV). A 6h-incubation was performed for: (i) 10 ng/ml LPS; (ii) 100 μΜ H202 in combination with lmM BSO (L-Buthionine-sulfoximine); (iii) lmM Trolox (6-Hydroxy-2,5,7,8- tetramethylchroman-2-carboxylic acid). A 24h-incubation was performed for: (i) 10 μΜ dexamethasone; (ii) 10% serum from wild-type and late-symptomatic GLD mice; (iii) MT1 and MT2, 20 μg/ml each. At the end of stimulation, cells were collected for RNA extraction as previously described.
Quantitative RT-PCR
4 to 6 μg of RNA from human T lymphocytes and brains and from murine brains and cells were reverse-transcribed into cDNA (High Capacity cDNA Reverse Transcription Kit and Superscript III First Strand Synthesis - Life Technologies). qPCR was performed on an ABI 7900HT or Viia7 (Life Technologies) and analyzed" by comparative threshold cycle method using Taqman Gene Expression Assay primers and probes for human Metallothionein 1A, IE, 2 A and E, murine Metallothionein 1 and 2 and CXCL11, and glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) as reference gene (Life Technologies).
Immunohistochemistry Consecutive 4-μηι thick sections from formalin-fixed paraffin-embedded brain tissue samples of MLD and controls brains were prepared and stained with routine Hematoxylin-Eosin and Kluver-Barrera (Luxol Fast Blue) method for myelin. Irrimunostaining with anti-metallothionein (MT) monoclonal antibodies (Dako, clone E9, diluition 1 :50) was performed on both MLD and control brain sections.
Western Blot
50 μg of proteins from total brain lysates or 6-24 μΐ of thawed CSF,. together with MT1 and MT2 purified proteins (Enzo Life Science), were loaded on a Nu-PAGE 4- 12% Bis-Tris gel and run on a Western Blot apparatus at 200V for 40'. Proteins were transferred to a PVDF membrane on a wet chamber at 200mA for lh30\ The membrane was blocked for lh in TBS-T 5% milk, then incubated o/n with mouse a- MT antibody (DAKO) 1 :1000 in TBS-T 3% milk and for lh with a-mouse HRP- conjugated antibody (Millipore) 1 :10000 in TBS-T 3% milk. For actin determination, the membrane was stripped for 15' with Restore Buffer (Thermo Scientific), blocked and incubated for 3h with goat -actin antibody (Santa Cruz Biotechnology) 1 : 10000 in TBS-T 3% milk and lh with a-goat HRP-conjugated antibody (Santa Cruz Biotechnology) 1 :20000 in TBS-T 3% milk. Blots were developed with ECL system (Millipore).
Immunofluorescence
35 -day-old GLD mice and age-matched WT mice were sacrificed under deep anesthesia and perfused with PBS. Brains were isolated and fixed for 16 hours in 4% paraformaldehyde, equilibrated in 10-30% sucrose gradient in PBS for 48 hours and then embedded in OCT compound for quick freezing. For immunofluorescence staining, 16 micron cryostatic sections were incubated for 2 hours at RT with primary antibodies (mouse monoclonal (UC1MT) to Metallothionein (abl2228, abeam, Cambridge, MA) 1 :80; rabbit anti-glial fibrillary acidic protein (GFAP) (MCA1909; Serotec Ltd.) 1 :500) and for 1 hour 30 minutes at room temperature (RT) with secondary antibodies (goat anti-mouse Alexa Fluor488 (Molecular Probes Inc.) 1 :1000; goat anti-rabbit AlexaFluor546 (Molecular Probes Inc.) 1 :1000). Samples were visualized with Zeiss Axioskop2 microscope. Images were acquired using a Radiance 2100 camera (BioRad) and Laser Sharp 2000 acquisition software (Bio- Rad). The signal-positive area in each slide was quantified using ImageJ software as previously described (Visigalli et al (2009) Neurobiology of the disease, 34, 51-62).
Example 2 - Metallothioneins are over-expressed in T lymphocytes of patients with MLD
To identify dynamic biomarkers for MLD, we performed a genome-wide expression analysis on primary T lymphocytes from 24 MLD patients and 24 age- and sex- matched healthy controls. Applying the Significant Analysis of Microarrays (SAM - Tusher et al (2001), PNAS, 98, 5116-5121) algorithm with a cutoff fold change of 1.5, we found 23 transcripts (targeted by 26 probes) that were significantly differentially expressed in patients with MLD compared to controls, with a false discovery rate of <0.01. Twenty transcripts were over-expressed and three were under-expressed in the MLD patients' group (Figure 1A and Table 1). These include a cluster comprising four members of the family of metallothioneins (MT1A, MT1E, MT2A and MTE- MT1IP; NCBI RefSeq: NM_005946.2, NM_175617.3, NM 005953.3 and NR_003669.1 respectively) and the metallothionein pseudogene MT1P3- C20ORF127, which show on average a 1.60-fold over-expression in MLD patients as compared to controls.
The over-expression of MTs in patients with MLD was confirmed by quantitative PCR (qPCR) (Figure IB). A 4-gene classifier created with the qPCR data for MT- genes in MLD patients and controls showed good sensitivity and specificity (area under the receiver-operating characteristics curve (AUC) of 0.75) (Figure ID). In order to strengthen and confirm these data on an independent test set, we also tested MT expression on primary T lymphocytes from newly recruited early-onset MLD patients and controls. Interestingly, MT over-expression was confirmed, at even higher levels than previously observed, also in this new patients' cohort (Figure 1C).
In addition, several differentially expressed genes were related to immune function (such as TIMD4, TNFSF13B, GNLY or GZMH).
Example 3 - Gene expression signatures predict diagnosis and prognostic subtypes of MLD To identify a transcriptional profile associated with MLD, we randomly chose a subset of patient and control samples to build first a diagnostic and then a prognostic classifier for MLD. This training set comprised -67% of the subjects (32 of 48 individuals), including 8 randomly selected early-onset MLD patients, 8 randomly selected late-onset MLD patients, and 16 age-matched controls.
We applied the Prediction Analysis of Microarrays (PAM) (Tibshirani (2002) Proc Natl Acad Sci US A, 99, 6567-6572) based on the nearest shrunken centroids statistic to 11,883 probes to build a molecular diagnostic for MLD. We found that a 15-gene classifier, which included three members of the MT family (MTl A, MTIE and MT2A; Table 2), was highly accurate in classifying patients with MLD with a specificity of 100% and a sensitivity of 94% (Figure 2 A). Because multivariate analyses are prone to over-fitting (Hennecke and Scherzer (2008) Biomark Med, 2, 41-53; Ransohoff (2004) Nature reviews, 4, 309-314), it is critical to confirm the validity of a candidate classifier in an independent test set. The 15-gene classifier was tested in the validation set of 16 samples, including eight patients with MLD (four with early-onset and four with late-onset disease) and eight controls that had not been used for building the classifier. Satisfyingly, 6 of 8 patients and 8 of 8 controls were accurately classified (estimated specificity of 100% and sensitivity of 75%; Figure 2B) confirming that an MLD-expression signature is indeed detectable in T lymphocytes of patients with MLD.
Biomarkers useful for predicting disease prognosis are clinically needed for MLD. We thus built a second classifier specifically designed to predict clinical prognostic subtypes of MLD based on gene expression changes in T lymphocytes. Using PAM (Tibshirani (2002) Proc Natl Acad Sci U S A, 99, 6567-6572) we identified a 31-gene prognostic classifier that again included MTl A, MTIE and MT2A as well as most of the 15 genes comprising the diagnostic classifier (Table 3). The 31-gene prognostic classifier accurately classified individuals into the prognostic groups of early-onset or late-onset disease, and controls. In the training set, 7 of 8 early-onset patients, 7 of 8 late-onset patients, and 16 of 16 controls were correctly classified (Figure 2C). Importantly, in the test set, 2 of 4 early-onset patients and 3 of 4 late-onset patients and 8 of 8 controls were correctly classified (Figure 2D) with estimated sensitivities and specificities of 50% and 100% for early-onset disease, and 75% and 92% for late- onset disease. These data suggest that MT-based expression profiles allow diagnosis as well as clinically relevant prognostic subtypes for MLD based on gene expression in blood cells.
Example 4 - Pathway analysis indicates a role for metallothioneins in the MLD disease process
In order to gain some hints on the pathways altered in the MLD brain and the possible correlation between their perturbation and MT over-expression, the expression levels and the ontology of the 11,883 genes from Illumina chips, on patients and healthy donors were analyzed through Ingenuity Pathway Analysis (IP A) software. By the comparison of the differentially expressed genes between the two groups, the three top perturbed biological functions in MLD patients were Gene Expression, Cell Death and Cell Cycle (data not shown). Interestingly, analysis of the top ten most significantly perturbed pathways (p<0.05, Fisher's Exact Test; Tables 4-13) revealed that four of them were related to cellular oxidative stress (Protein Ubiquitination Pathway; Oxidative Phosphorylation; Mitochondrial Dysfunction; NRF2-mediated Oxidative Stress Response) and three of them were associated to inflammatory response (Glucocorticoid Receptor Signaling, Antigen Presentation Pathway, Cytotoxic T Lymphocyte-mediated Apoptosis of Target Cells). Strikingly, the great majority of the molecules belonging to these pathways were significantly up-regulated in MLD patients as compared to healthy controls (Figure 3 A and 3B and Tables 4-13). One of them, the NRF2-mediated pathway, is implicated in the recruitment of antioxidant protems aimed at reducing the cellular oxidative damage, and in the repair and removal of damaged proteins from the cytoplasm through activation of chaperones and stress response proteins, together with ubiquitination and proteasomal degradation proteins.
The Protein Ubiquitination pathway is the most perturbed in MLD patients based on Ingenuity Pathway Analysis. Protein Ubiquitination pathway genes that were less differentially expressed genes and more over-expressed were identified (Figure 3B). Example 5 - Metallothioneins arc over-expressed in the brain of patients with MLD
If over-expression of MTs in patient-derived T lymphocytes is found as peripheral marker of a general cellular disease process, equally dramatic changes in MT expression should be detectable in the brain of patients with MLD. We thus assessed whether over-expression of MTs was present also in the post-mortem CNS tissues of 4 MLD patients that died at advanced stages of their disease, compared to 4 age-, sex- , post-mortem interval- and RNA quality-matched controls. Interestingly, quantitative PCR showed that MT1A, MT1E, MT2A and MTE were robustly over-expressed in the frontal cortex of MLD patients as compared to controls, with a larger effect in the white as compared to the gray matter, as expected by the prevalent involvement of myelin-rich regions in the disease (Figure 4A). Of note, MT over-expression in the brain of MLD patients was greatly exceeding the levels originally observed in the T lymphocytes (average MT fold change of 25.46 in brain tissues, compared to average fold change of 1.63 in T lymphocytes).
Importantly, the MT increase in expression documented at the molecular level was reflected in an elevated immunoreactivity against MTs both in the white and gray matter regions of post-mortem samples from the same MLD patients (Figure 4B). Consistently with the disease setting, these images depict also a diffuse disruption of the tissue architecture, particularly evident in the white matter, with prevalence of engulfed phagic cells and loss of the myelin reticulum.
Example 6 - Metallothioneins are general markers of nervous tissue damage in LSDs
Beyond MLD, which has a relative low incidence, we then assessed whether MT over-expression could also be observed in other members of the much broader class of LSDs with nervous system involvement (over 40 different LSDs exist, with a combined incidence varying between 1 to 1500 and 1 to 7000 live births, the majority of which having nervous system involvement). We analyzed MT expression in post-mortem brain samples from a total of 20 patients affected by different LSDs, such as Mucopolysaccharidosis type I (MPSI), Mucopolysaccharidosis type III (MPSIII), Niemann-Pick disease (NPC), Neuronal Ceroidolipofuscinosis (NCL), Sandhoff disease (SD) and Globoid Cell Leukodystrophy (GLD), comparing them with the expression values in 17 age-, sex-, post-mortem interval- and RNA quality-matched controls. Expression analysis performed on the frontal cortex of these LSD patients showed a highly significant over-expression of MTs for all the analyzed genes (Figure 5 A). The separate analysis of the different disorders confirmed a pattern of increase in MT levels for all the analyzed diseases, with a differing extent of over-expression for the various transcripts in each clinical setting (Figures 5B-E).
The increase in MT expression was assessed also at the protein level through an immunoblot against MT proteins, reflecting the disease-specific degree of over- expression observed at the transcript level (Figure 5F). Interestingly, the same assay identified the presence of the MT protein also in the cerebrospinal fluid (CSF) of some LSD patients for which post-mortem samples were available, thus indicating CSF as a possible clinically accessible surrogate for brain MT assessment in the clinical evaluation of LSD patients (Figure 5G).
To further confirm that MT over-expression is associated with LSD brain disease, brain samples from animal models of different LSDs at late and symptomatic stage of the disease were analyzed. In particular, we included in the analysis samples from mice affected by MLD, GLD, MPSI and III and SD, all characterized by demyelination and/or neurodegeneration of differential severity. Both murine MT1 and MT2, orthologous of the human isoforms MT1 and MT2, were significantly over- expressed in LSD mouse models (Figure 7A). As observed in humans, the extent of expression changes varied in each specific lysosomal storage disease, with the mouse model for GLD showing the highest transcript levels, (fold change of 5.5 for MT1 and of 8.0 for MT2). Immunohistochemistry confirmed MT over-expression at the protein level on brain samples from GLD mice, and suggested that MTs are expressed predominantly by reactive astrocytes (Figures 7B and 7C). Example 7 - Metallothioneins are dynamic markers of disease progression and therapeutic response.
Intriguingly, when we performed a longitudinal study on GLD mice, which show a very severe and rapidly progressive brain disease, we detected a significant increase in the expression level of MTs along with disease progression, from pre-symptomatic (at 9-12 days post-natal) to late symptomatic animals (at 35 days post-natal), both in circulating blood cells and in brain tissue (Figure 6A).
Hematopoietic stem cell transplantation from healthy donors has been introduced historically in many LSDs and more recently in GLD as a procedure capable of delaying disease onset and attenuating the disease phenotype by providing the functional enzyme to the affected nervous tissue by the means of CNS-infiltrating donor-derived cells (Escolar et al (2005), N. Engl. J. Med., 352, 2069-2081). Thus, to assess whether MT expression levels could also vary according to the administration of a treatment capable of significantly ameliorating nervous system disease manifestations, GLD animals at post-natal day 8 underwent bone marrow transplantation from wild-type donors. Transplanted mice were sacrificed at day 40 when only mildly symptomatic. Remarkably, MT expression levels in treated animals were significantly lower than the levels measured in untreated age-matched affected controls, which were moribund at this disease stage, indicating that MTs could represent a marker not only of disease progression but also of response to treatment (Figure 6A).
In order to confirm these data in the patients' setting, we explored the relationship between MT expression and disease progression in our MLD patients by correlating MT qPCR data with patients' age at drawing. We restricted this analysis to the late infantile disease variant, which is characterized by a homogeneous clinical presentation and evolution, and a rapid disease progression (Biffi et al. (2008) Clinical Genetics, 74, 349-357). According to the literature and to our clinical experience, disease invariably presents itself between 12 and 24 months of age and homogenously progresses with time in late infantile MLD patients. Thus, patients' age at the time of blood drawing can be considered a good approximation of the advancement of the disease, the older being the patient the most severe and advanced being his/her disease status. Interestingly, the level of MT expression in blood significantly increased with patients' age at drawing (Figure 6B) (Pearson correlation coefficient = 0.617; P value = 0.0432). In healthy controls MTs did not materially correlate with age (Pearson correlation coefficient = 0.474; P value = 0.119).
Example 8 - The role of metallothioneins in brain oxidative stress and inflammation response is dissected in vitro.
The over-expression of MTs in LSDs with neurological involvement prompted us to deepen the current knowledge of their biologic role in inflammation and oxidative stress. We particularly focused our analysis on microglia and astrocytes: microglia are known to be activated in the neuroiiiflammatory and neurodegenerative context typical of LSDs (Visigalli et al (2009)while astrocytes are the main source of MTs in the affected brain (Chung et al (2004) Journal of neurochemistry, 88, 454-461), as also confirmed by our data on mouse and human samples.
Interestingly, MT transcripts increased in pure mouse astrocyte cultures upon contact with microglia-conditioned medium; of note, MT expression was even more significantly induced when astrocytes were placed in culture with medium conditioned by LPS-activated microglia (Figure 8A). These initial results suggested that a relationship exists between microglia resting/activated status and MT expression by surrounding astrocytes and prompted us to further investigate the microglia-astrocyte cross-talk in a co-culture setting, constituted roughly by 5% microglial cells and 95% astrocytes. We limited our analysis to WT cells since GLD cells, upon in vitro culture, down-regulate MT expression to normal cell levels, indicating that MT over-expression observed in vivo could represent more a response to extracellular milieu than a cell-intrinsic phenotype (Figure 6B; see also Figure 8D for the effects of serum on MT expression). In order to dissect the contribution of MTs to inflammation and oxidative stress, we stimulated WT cells with proinflammatory (LPS) and pro-oxidative (H202 in combination with glutathione depletion) stimuli, with or without a pre-treatment with an anti-inflammatory (dexamethasone) or anti-oxidative (trolox) drug. MTs increased upon both proinflammatory and oxidative stimuli as expected. Interestingly, the administration of the anti-inflammatory drug dexamethasone, either alone or in combination with the insulting stimuli, induced a significantly higher induction of MT expression than the insulting stimuli alone. The same effect could not be observed in the oxidative setting: the anti-oxidant molecule trolox, a derivative of vitamin E, while prevented MT increase upon oxidative stimulus administration, did not induce MT expression per se (Figure 8C).
Discussion
The identification of reliable dynamic biomarkers correlating with disease onset, progression and response to treatment is highly needed for LSDs. Many techniques have been and are currently employed to identify disease-specific biomarkers in different tissue samples from patients affected by a variety of LSDs (Schiffmann et al (2010) Clin J Am Soc Nephrol, 5, 360-364; Boot et al (2009) Expert Rev Proteomics, 6, 411-419; Clarke et al (2012) Molecular genetics and metabolism). However, sensitive, reliable and possibly dynamic markers have yet to be identified. Gene expression profiling could be of particular value for the identification of such markers in LSD patients. Indeed, when performed at the whole-genome level, it is a powerful tool to investigate the molecular signature associated with a particular condition and to highlight differences in the transcriptomes -of subjects or groups of subjects (Scherzer et al, (2007) PNAS, 104, 955-960; Scherzer et al (2004) Arch Neurol, 61, 1200-1205; Lipinski et al (2010) PNAS, 107, 14164-14169) Importantly, the reproducibility of gene expression profiling was demonstrated to be sufficiently reliable for clinical application (Shi et al (2006) Nat Biotechnol, 24, 1151-1161), with microarray instrumentations and microarray-based genetic signatures having recently received the approval from regulatory Agencies in the US and Europe.
Most LSDs involve the CNS, and the LSD-associated neurological manifestations represent a major cause of morbidity and mortality for the affected patients. In similar cases where the analysis of gene expression might be complicated by the scarce accessibility to the affected nervous tissue, a more reachable source, such as blood cells, has been successfully employed as a surrogate (Scherzer et al, (2007) PNAS, 104, 955-960). Here in the case of the prototypical LSD Metachromatic Leukodystrophy, the transcriptome analysis performed on T lymphocytes of patients provided a progression biomarker useful not only for MLD but also for the broader class of LSDs with CNS involvement. Indeed, within the list of genes differentially expressed between patients with MLD and age- and sex-matched healthy controls generated by our trariscriptome analysis, a consistent and significant increased expression of the class of MT genes was observed in the patients. Importantly, over-expression of members of the MT family was confirmed on MLD patients belonging to an independent cohort and observed also at the RNA and protein level in patients' nervous tissue. The relative abundance of the transcripts in brain from MLD patients was substantially higher than that observed in T lymphocytes, suggesting that increased expression of MTs could be directly linked to disease pathogenesis in the mostly affected tissue. Interestingly, the increased MT abundance observed in T lymphocytes in early-onset MLD patients as their disease progressed, together with the longitudinal studies performed on the mouse model of GLD, indicate a reactive role for MT expression in response to the advancement of the brain disorder. Moreover, the reduction of MT expression in mice successfully treated by bone marrow transplantation suggests that MTs could function not only as markers of disease progression but also as indicators of treatment response. Thus these data, despite being preliminary due to the limited number of patients analyzed and requiring replication in independent and prospective studies, indicate that MT transcripts could constitute a reliable and dynamic biomarker of MLD brain disease. Importantly, this marker could be broadly useful for lysosomal storage disorders, as MTs are also abnormally expressed in multiple LSDs. In fact, expression data in human and mouse brains from the other tested LSDs characterized by nervous tissue damage clearly demonstrated that MT over-expression is a feature shared by different members of this class, although with specific expression patterns in each disease. This is in accordance with the observation of MT over-expression in other neurodegenerative disorders (Hidalgo et al (2001) Brain research bulletin, 55, 133- 145; Ebadi et al (2005) Brain research, 134, 67-75; Gong et al (2000), Experimental neurology, 162, 27-36), and it suggests a role for this family of proteins in mitigating the inflammation and oxidative stress characteristic of neurodegenerative conditions. In particular, in LSDs MT expression could possibly be activated as a consequence of the block of autophagy, which has been shown to be a direct consequence of the lysosomal dysfunction (Settembre et al (2008) Hum Mol Genet, 17, 119-129; Baird et al (2006) Biochem J, 394, 275-283), as an attempt by the cell to lower the oxidative stress, counteract the accumulating pro-apoptotic stimuli and mitigate tissue inflammation. Indeed, analysis on microarray data points to a selective perturbation of pathways related to oxidative stress and inflammation in MLD patients' samples. MT increase, both in the CNS and in blood, could also reflect a cell-extrinsic response to still unidentified soluble factors, as suggested by the mechanistic studies performed with GLD mouse serum.
Our in vitro experiments on purified astrocyte-microglia co-cultures strengthened our knowledge of MT role in the nervous tissue elucidating a cross-talk between activated microglia and astrocytes and dissecting the separate contribution of inflammation and oxidative stress to the control of MT expression. In particular, we hypothesize that in the inflammation setting MTs exert both a protective and a reactive role, highlighted by an increase in expression upon both pro- and anti-inflammatory stimuli. On the contrary, the absence of such effect upon anti-oxidative molecule administration suggests a prevalent reactive role of MTs in the oxidative setting.
In conclusion, gene expression analysis performed on the blood of MLD patients and direct analysis of LSD brain tissues revealed MTs to be a novel, dynamic biomarker of disease progression and severity for this class of diseases. The analysis performed on various LSDs suggests that MT expression changes could represent a common reactive pathway in the affected LSD brain and potentially an early marker of treatment response, which could be serially monitored in accessible sources such as CSF of the affected individuals. Moreover, these findings provide a novel insight into the molecular mechanisms leading to tissue damage in LSD brains and into the reactive role played by MTs in nervous tissue damage.
Table 1: List of genes most differentially expressed in MLD patients compared to age- and sex-matched controls.
SYMBOL DEFINITION fold change P value FDR
MT1A metallothionein 1A 1.5448 0.000002 0
TIMD4 T-cell lg and mucin domain containing 4 1.6296 0.000022 0
MT2A metallothionein 2A 1.5307 0.000023 0
MT1 E metallothionein 1 E 1.8854 0.000028 0 C3orf14 1.6722 0.000046 0
C20orf127 1.5311 0.000053 0
ATP1B1 ATPase. Na+/K+ transporting, beta 1 polypeptide 0.6482 0.000070 0
KIAA1671 1.5997 0.000078 0
RN7SK RNA, 7SK small nuclear 1.5673 0.000106 0
MTE metallothionein E 1.5218 0.000156 0
RN7SK RNA, 7SK small nuclear 1.5205 0.000423 0
CYP1 B1 cytochrome P450, fam 1 , subfam B, polypeptide 1 3.2124 0.000438 0
TNFSF13B TNF (ligand) superfamily, member 13b 1.5734 0.000556 0
FCER2 Fc fragm of IgE, low affinity II, receptor for (CD23) 0.6578 0.000897 0
TNFSF13B TNF (ligand) superfamily, member 13b 1.5327 0.001947 0
EMP1 epithelial membrane protein 1 1.5823 0.002258 0
MCOLN2 mucolipin 2 1.6752 0.002264 0
EFHD1 EF-hand domain family, member D1 0.6655 0.002987 0
PRDM1 PR domain containing 1 , with ZNF domain 1.5055 0.003636 0
MYB v-myb myeloblastosis viral oncogene homolog 1.6162 0.004853 0
HOPX HOP homeobox 1.5704 0.005710 0
GZMH granzyme H (cathepsin G-like 2, protein h-CCPX) 1.9466 0.008254 0
BX097705 NCI_CGAP_Kid5 1.5706 0.009935 0
C12orf48 2.9225 0.010243 0
GNLY Granulysin 2.3955 0.012963 0
GNLY Granulysin 2.2851 0.013042 0
Legend: bold, genes belonging to MT family; italic, under-expressed genes. FDR = False Discovery Rate.
Table 2: List of genes belonging to the binary diagnostic classifier used to discriminate between MLD patients and controls.
SYMBOL DEFINITION MLD score CTR score
MT1A Metallothionein 1A 0.3123 -0.3123
MT2A Metallothionein 2A 0.1493 -0.1493
ADSS Adenylosuccinate synthase 0.1486 -0.1486 MT1 E Metallothionein 1 E 0.1365 -0.1365
ALOX5AP Arachidonate 5-lipoxygenase-activating protein 0.1316 -0.1316
SYT11 Synaptotagmin XI 0.0822 -0.0822
AGK Acylglycerol kinase 0.062 -0.062
HS.127310 0.0433 -0.0433
CYP1 B1 Cytochrome P450 fam 1 subfam B polypept 1 0.0407 -0.0407
IFITM2 Interferon induced transmembrane protein 2 -0.0262 0.0262
IFITM1 Interferon induced transmembrane protein 1 -0.0244 0.0244
ANXA7 Annexin A7 0.02 -0.02
KIAA1671 0.0177 -0.0177
ZFAND5 Zinc finger, AN 1 -type domain 5 0.0173 -0.0173
RPL18A Ribosomal protein L18a -0.006 0.006
Table 3: List of genes belonging to the diagnostic classifier used to discriminate between early-onset MLD patients, late-onset MLD patients and controls.
SYMBOL DEFINITION E-0 MLD L-0 MLD CTR score score score
MT1 E Metallothionein 1 E 0.3321 0 -0.1602
MT1A Metallothionein 1 A 0.108 0 -0.2822
DNCL1 Dynein, cytoplasmic, light polypeptide 1 0 0.2552 0
ANXA1 Annexin A1 0 0.1837 0
RPRC1 Arginine/proline rich coiled-coil 1 0.1678 -0.0753 0
PKM2 Pyruvate kinase, muscle, transcript variant 2 0 0.1366 0
LOC729985 0 0.1276 0
UNC84B Unc-84 homolog B (C. elegans) 0.0006 -0.1239 0
CNN2 Calponin 2 0 -0.1216 0
ADSS Adenylosuccinate synthase 0 0 -0.1145
MT2A Metallothionein 2A 0 0 -0.1123
FGD3 FYVE, RhoGEF and PH domain containing 3 0 -0.1036 0
GFM1 G elongation factor, mitochondrial 1 0.0995 0 0
ALOX5AP Arachidonate 5-lipoxygenase-activating protein 0 0 -0.0994
MDH2 Malate dehydrogenase 2 0.0569 0 0 JTB Jumping translocation breakpoint 0 0.0544 0
Mitogen-activated protein kinase kinase kinase
MAP4K2 kinase 2 0 -0.0492 - 0
SYT1 1 Synaptotagmin XI 0 0 -0.0473
FLOT2 Flotillin 2 0 -0.0434 0
Sparc/osteonectin, cwcv and kazal-like domains
SPOCK2 proteoglycan 2 0 -0.0422 0
SH2D1A SH2 domain protein 1A, Duncan's disease 0.0368 0 0
AGK Acylglycerol kinase 0 0 -0.03
LM04 LIM domain only 4 0 0.0293 0
MBP Myelin basic protein 0.027 0 0
CYP1 B1 Cytochrome P450 fam 1 subfam B polypept 1 0 0 -0.0259
ANXA7 Annexin A7 0.0015 0 -0.0094
HS.127310 0 0 -0.0092
SIPA1 Signal-induced proliferation-associated gene 1 0 -0.0048 0
RALA V-ral simian leukemia viral oncogene homolog A 0.0044 0 0
EVL Enah Vasp-like 0 -0.0042 0
C120RF48 0 0.0005 0
Table 4: list of genes belonging to the Protein Ubiquitination pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (122 observed genes out of 273 total genes; P value=1.87E-14).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
AMFR autocrine motility factor receptor 1.01 1 9.02E- -01
ANAPC10 anaphase promoting complex subunit 0 1.190 1.90E- -03
ANAPC11 anaphase promoting complex subunit 11 1.025 6.39E- -01
B2M beta-2-microglobulin 1.024 5.18E- -01
BIRC2 baculoviral IAP repeat containing 2 1.035 4.80E- -01
BIRC3 baculoviral IAP repeat containing 3 1.196 1.01 E- -01
BRCA1 breast cancer 1 , early onset 1.046 5.59E- -01
CDC23 cell division cycle 23 homolog (S. cerevisiae) 1.095 6.48E- -02
CUL2 cullin 2 1.004 9.47E- -01
DNAJA1 DnaJ (Hsp40) homolog, subfamily A, member 1 1.036 5.28E- -01
DNAJB1 DnaJ (Hsp40) homolog, subfamily B, member 1 1.015 6.95E- -01
DNAJB6 DnaJ (Hsp40) homolog, subfamily B, member 6 1.056 3.33E- -01
DNAJB9 DnaJ (Hsp40) homolog, subfamily B, member 9 1.227 5.43E- -03
DNAJB11 DnaJ (Hsp40) homolog, subfamily B, member 1 1 1.034 6.07E- -01
DNAJB12 DnaJ (Hsp40) homolog, subfamily B, member 12 1.023 5.86E- -01 DNAJB14 DnaJ (Hsp40) homolog, subfamily B, member 14 1.135 2.18E- -03
DNAJC9 DnaJ (Hsp40) homolog, subfamily C, member 9 1.074 1.60E- -01
DNAJC10 DnaJ (Hsp40) homolog, subfamily C, member 10 1.101 1.20E- -01
DNAJC12 DnaJ (Hsp40) homolog, subfamily C, member 12 1.067 . 4.88E- -01
DNAJC14 DnaJ (Hsp40) homolog, subfamily C, member 14 1.006 8.84E- -01
DNAJC15 DnaJ (Hsp40) homolog, subfamily C, member 15 1.068 3.70E- -01
DNAJC18 DnaJ (Hsp40) homolog, subfamily C, member 18 1.076 1.29E- -01
DNAJC19 DnaJ (Hsp40) homolog, subfamily C, member 19 1.026 5.38E- -01
DNAJC24 DnaJ (Hsp40) homolog, subfamily C, member 24 1.056 3.50E- -01
DNAJC25 DnaJ (Hsp40) homolog, subfamily C , member 25 1.079 6.65E- -02
FBXW7 F-box and WD repeat domain containing 7 1.085 5.26E- -02
HLA-A major histocompatibility complex, class I, A 1.033 6.01 E- -01
HLA-B major histocompatibility complex, class I, B 1.042 4.95E- -01
HSP90AA1 heat shock protein 90kDa alpha (cytosolic), class A member 1 1.033 7.53E- -01
HSP90B1 heat shock protein 90kDa beta (Grp94), member 1 1.011 8.43E- -01
HSPA4 heat shock 70kDa protein 4 1.014 8.73E- -01
HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E- -02
HSPA6 heat shock 70kDa protein 6 (HSP70B') 1122 3.85E- -01
HSPA9 heat shock 70kDa protein 9 (mortalin) 1.006 9.28Ε- 1
HSPA13 heat shock protein 70kDa family, member 13 1.079 8.66E- -02
HSPA14 heat shock 70kDa protein 14 1.164 2.19E- -03
HSPA1A/ heat shock 70kDa protein 1 A 1.145 1.35E- -01
HSPA1 B
HSPA1 L heat shock 70kDa protein 1 -like 1.035 5.25E- -01
HSPB1 heat shock 27kDa protein 1 1.116 2.01 E- -01
HSPB11 heat shock protein family B (small), member 11 1.088 2.90E- -01
HSPD1 heat shock 60kDa protein 1 (chaperonin) 1.127 1.79E- -01
HSPE1 heat shock 10kDa protein 1 (chaperonin 10) 1.154 2.61 E- -01
HSPH1 heat shock 105kDa/110kDa protein 1 1.027 7.52E- -01
IFNG . interferon, gamma 1.508 1.97E- -01
LOC728622/ S-phase kinase-associated protein 1 1.088 4.31 E- -02 r\r I
PSMA1 proteasome (prosome, macropain) subunit, alpha type, 1 1.063 9.34E- -02
PSMA2 proteasome (prosome, macropain) subunit, alpha type, 2 1.119 8.59E- -02
PSMA3 proteasome (prosome, macropain) subunit, alpha type, 3 1.134 1.22E- -01
PSMA4 proteasome (prosome, macropain) subunit, alpha type, 4 1.105 8.02E- -02
PSMA5 proteasome (prosome, macropain) subunit, alpha type, 5 1.074 7.85E- -02
PSMA6 proteasome (prosome, macropain) subunit, alpha type, 6 1.098 1.13E- -01
PSMB1 proteasome (prosome, macropain) subunit, beta type, 1 1.035 4.01 E- -01
PSMB2 proteasome (prosome, macropain) subunit, beta type, 2 1.001 9.89E- -01
PSMB3 proteasome (prosome, macropain) subunit, beta type, 3 1.082 1.30E- -01
PSMB4 proteasome (prosome, macropain) subunit, beta type, 4 1.024 4.61 E- -01
PSMB5 proteasome (prosome, macropain) subunit, beta type, 5 1.006 9.21 E- -01
PSMB6 proteasome (prosome, macropain) subunit, beta type, 6 1.058 2.70E- -01
PSMB7 proteasome (prosome, macropain) subunit, beta type, 7 1.027 4.71 E- -01
PSMB8 proteasome (prosome, macropain) subunit, beta type, 8 (large 1.056 4.75E- -01 multifunctional peptidase 7)
PSMB9 proteasome (prosome, macropain) subunit, beta type, 9 (large 1.078 2.48E- -01 multifunctional peptidase 2)
PSMC1 proteasome (prosome, macropain) 26S subunit, ATPase, 1 1.052 2.11 E- -01
PSMC2 proteasome (prosome, macropain) 26S subunit, ATPase, 2 1.136 1.78E- -02
PSMC4 proteasome (prosome, macropain) 26S subunit, ATPase, 4 1.040 3.05E- -01
PSMC6 proteasome (prosome, macropain) 26S subunit, ATPase, 6 1.051 2.44E- -01
PSMD1 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1 1.022 7.05E- -01
PSMD6 proteasome (prosome, macropain) 26S subunit, non-ATPase, 6 1.079 1.18E- -01
PSMD7 proteasome (prosome, macropain) 26S subunit, non-ATPase, 7 1.022 4.48E- -01
PSMD9 proteasome (prosome, macropain) 26S subunit, non-ATPase, 9 1.049 1.77E- -01
PSMD10 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1.046 3.68E- -01 PSMD12 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1.111 4.14E-■02
19
PSMD13 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1.005 9.11 E- -01
1 "¾
PSMD14 proteasome (prosome, macropain) 26S subunit, non-ATPase, 1.147 3.16E- -02
Λ Α
PSME1 proteasome (prosome, macropain) activator subunit 1 (PA28 1.030 5.81 E- -01 alpha)
PSME2 proteasome (prosome, macropain) activator subunit 2 (PA28 1.040 5.84E- -01 beta)
RBX1 ring-box 1 , E3 ubiquitin protein ligase 1.156 8.09E- -02
SACS spastic ataxia of Charlevoix-Saguenay (sacsin) 1.018 8.03E- -01
SKP2 S-phase kinase-associated protein 2 (p45) 1.032 5.78E- -01
TAP1 transporter 1, ATP-binding cassette, sub-family B (MDR/TAP) 1.051 3.59E- -01
TAP2 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) 1.174 1.42E- -02
TCEB1 transcription elongation factor B (Sill), polypeptide 1 (15kDa, 1.145 3.85E- -02 elongin C)
TCEB2 transcription elongation factor B (Sill), polypeptide 2 (18kDa, 1.073 2.11 E- -01 elongin B)
TRAF6 TNF receptor-associated factor 6 1.039 5.19E- -01
UBD ubiquitin D 1.205 2.22E- -01
UBE2A ubiquitin-conjugating enzyme E2A (RAD6 homoiog) 1.036 5.11 E- -01
UBE2D2 ubiquitin-conjugating enzyme E2D 2 (UBC4/5 homoiog, yeast) 1.010 7.98E- -01
UBE2D3 ubiquitin-conjugating enzyme E2D 3 (UBC4/5 homoiog, yeast) 1.053 1.65E- -01
UBE2D4 ubiquitin-conjugating enzyme E2D 4 (putative) 1.067 2.27E- -01
UBE2E1 ubiquitin-conjugating enzyme E2E 1 (UBC4/5 homoiog, yeast) 1.063 3.09E- -01
UBE2E3 ubiquitin-conjugating enzyme E2E 3 (UBC4/5 homoiog, yeast) 1.135 2.36E- -02
UBE2F ubiquitin-conjugating enzyme E2F (putative) 1.070 3.52E- -01
UBE2G1 ubiquitin-conjugating enzyme E2G 1 (UBC7 homoiog, yeast) 1.028 5.31 E- -01
UBE2H ubiquitin-conjugating enzyme E2H (UBC8 homoiog, yeast) 1.025 4.92E- -01
UBE2J1 ubiquitin-conjugating enzyme E2, J1 (UBC6 homoiog, yeast) 1.120 6.47E- -02
UBE2L6 ubiquitin-conjugating enzyme E2L 6 1.022 7.18E- -01
UBE2N ubiquitin-conjugating enzyme E2N (UBC13 homoiog, yeast) 1.048 2.13E- -01
UBE2Q1 ubiquitin-conjugating enzyme E2Q family member 1 1.103 7.75E- -02
UBE2V1 ubiquitin-conjugating enzyme E2 variant 1 1.009 8.97E- -01
UBE2V2 ubiquitin-conjugating enzyme E2 variant 2 1.140 2.26E- -02
UBE3A ubiquitin protein ligase E3A 1.056 1.84E- -01
UBE4A ubiquitination factor E4A (UFD2 homoiog, yeast) 1.052 4.43E- -01
UBE4B ubiquitination factor E4B (UFD2 homoiog, yeast) 1.080 8.18E- -02
UCHL3 ubiquitin carboxyl-terminal esterase L3 (ubiquitin thiolesterase) 1.070 1.35E- -01
UCHL5 ubiquitin carboxyl-terminal hydrolase L5 1.049 3.32Ε-Ό1
US01 US01 vesicle docking protein homoiog (yeast) 1.054 3.64E- -01
USP1 ubiquitin specific peptidase 1 1.140 1.15E- -01
USP3 ubiquitin specific peptidase 3 1.050 3.01E- -01
USP8 ubiquitin specific peptidase 8 1.084 2.13E- -01
USP10 ubiquitin specific peptidase 10 1.019 6.53E- -01
USP13 ubiquitin specific peptidase 13 (isopeptidase T-3) 1.099 1.47E- -01
USP14 ubiquitin specific peptidase 14 (tRNA-guanine transglycosylase) 1.100 4.61 E- -02
USP15 ubiquitin specific peptidase 15 1.017 7.01 E- -01
USP16 ubiquitin specific peptidase 16 1.071 9.78E- -02
USP33 ubiquitin specific peptidase 33 1.049 2.78E- -01
USP36 ubiquitin specific peptidase 36 1.013 8.51 E- -01
USP37 ubiquitin specific peptidase 37 1.071 1.28E- -01
USP38 ubiquitin specific peptidase 38 1.066 1.45E- -01
USP42 ubiquitin specific peptidase 42 1.136 2.79E- -02
USP48 ubiquitin specific peptidase 48 1.098 1.26E- -01
USP49 ubiquitin specific peptidase 49 1.058 5.55E- -01 USP54 ubiquitin specific peptidase 54 1.104 2.85E-01
USP9X ubiquitin specific peptidase 9, X-linked 1.014 7.85E-01
VHL von Hippel-Lindau tumor suppressor 1.063 1.86E-01
Table 5: list of genes belonging to the Oxidative Phosphorylation pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (67 observed genes out of 148 total genes; P value=2.23E-10).
SYMBOL DEFINITION FOLD P ALUE
CHANGE
ATP5C1 ATP synthase, H+ transporting, mitochondrial F1 complex, 1.105 1.74E- ■01 gamma polypeptide 1
ATP5D ATP synthase, H+ transporting, mitochondrial F1 complex, delta 1.007 8.75E- ■01 subunit
ATP5G1 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.050 4.61 E- -01 subunit C1 (subunit 9)
ATP5G2 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.026 7.49E- -01 subunit C2 (subunit 9)
ATP5G3 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.052 2.20E- -01 subunit C3 (subunit 9)
ATP5H ATP synthase, H+ transporting, mitochondrial Fo complex, 1.125 5.76E- -02 subunit d
ATP5I ATP synthase, H+ transporting, mitochondrial Fo complex, 1.034 5.59E- -01 subunit E
ATP5J ATP synthase, H+ transporting, mitochondrial Fo complex, 1.078 2.25E- -01 subunit F6
ATP5J2 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.086 1.62E- -01 subunit F2
ATP5L ATP synthase, H+ transporting, mitochondrial Fo complex, 1.098 1.01 E- -01 subunit G
ATP50 ATP synthase, H+ transporting, mitochondrial F1 complex, 0 1.059 3.51 E- -01 subunit
ATP6V0A2 ATPase, H+ transporting, lysosomal V0 subunit a2 1.121 5.72E- -03
ATP6V0B ATPase, H+ transporting, lysosomal 21 kDa, V0 subunit b 1.066 1.42E- -01
ATP6V0C ATPase, H+ transporting, lysosomal 16kDa, V0 subunit c 1.015 7.83E- -01
ATP6V0E1 ATPase, H+ transporting, lysosomal 9kDa, V0 subunit e1 1.149 1.94E- -02
ATP6V1A ATPase, H+ transporting, lysosomal 70kDa, V1 subunit A 1.020 6.31 E- -01
ATP6V1 B2 ATPase, H+ transporting, lysosomal 56/58kDa, V1 subunit B2 1.114 2.47E- -02
ATP6V1 C1 ATPase, H+ transporting, lysosomal 42kDa, V1 subunit C1 1.057 3.35E- -01
ATP6V1 E1 ATPase, H+ transporting, lysosomal 31 kDa, V1 subunit E1 1.018 6.60E- -01
ATP6V1 F ATPase, H+ transporting, lysosomal 14kDa, V1 subunit F 1.052 4.18E- -01
ATP6V1 G1 ATPase, H+ transporting, lysosomal 13kDa, V1 subunit G1 1.069 1.66E- -01
COX 10 COX10 homolog, cytochrome c oxidase assembly protein, 1.034 5.05E- -01 heme A: farnesyltransferase (yeast)
COX1 1 COX11 cytochrome c oxidase assembly homolog (yeast) 1.033 4.56E- -01
COX17 COX17 cytochrome c oxidase assembly homolog (S. 1.066 3.44E- -01 cerevisiae)
COX5A cytochrome c oxidase subunit Va 1.050 4.37E- -01
COX6A1 cytochrome c oxidase subunit Via polypeptide 1 1.049 4.49E- -01
COX6B1 cytochrome c oxidase subunit Vlb polypeptide 1 (ubiquitous) 1.073 2.64E- -01
COX6C cytochrome c oxidase subunit Vic 1.026 5.21 E- -01
COX7A2 cytochrome c oxidase subunit Vila polypeptide 2 (liver) 1.106 9.80E- -02
COX7B cytochrome c oxidase subunit Vllb 1.164 9.25E- -02
COX7C cytochrome c oxidase subunit Vile 1.093 1.07E- -01
CYC1 cytochrome c-1 1.003 9.38E- -01
NDUFA1 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 1 , 1.091 1.80E- -01
7.5kDa
NDUFA3 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 3, 1.073 2.29E- -01
9kDa
NDUFA4 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4, 1.152 1.34E- -02
9kDa NDUFA7 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 7, 1.041 3.62E- -01
14.5kDa
NDUFA8 NADH dehydrogenase (ubiquinone) 1 aipha subcomplex, 8, 1.053 4.40E- -01
19kDa -
NDUFA9 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 9, 1.023 5.10E- -01
39kDa
NDUFA11 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 11 , 1.048 4.20E- -01
14.7kDa
NDUFA12 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 12 1.017 8.66E- -01
NDUFA13 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 13 1.044 4.15E- -01
NDUFAB1 NADH dehydrogenase (ubiquinone) 1 , alpha/beta subcomplex, 1.140 5.07E- -02
1 , 8kDa
NDUFB2 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 2, 1.014 8.40E- -01
8kDa
NDUFB3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 1.119 1.39E- -01
12kDa
NDUFB5 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 1.015 6.94E- -01
16kDa
NDUFB6 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 6, 1.095 1.04E- -01
17kDa
NDUFB7 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 7, 1.045 4.80E- -01
18kDa
NDUFB8 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 8, 1.028 5.52E- -01
19kDa
NDUFB10 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 10, 1.061 5.00E- -01
22kDa
NDUFB11 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 11 , 1.019 7.52E- -01
17.3kDa
NDUFC1 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1 , 1.087 9.10E- -02
6kDa
NDUFS3 NADH dehydrogenase (ubiquinone) Fe-S protein 3, 30kDa 1.019 6.92E- -01
(NADH-coenzyme Q reductase)
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4, 8kDa 1.110 8.37E- -02
(NADH-coenzyme Q reductase)
NDUFS5 NADH dehydrogenase (ubiquinone) Fe-S protein 5, 15kDa 1.171 4.43E- -02
(NADH-coenzyme Q reductase)
NDUFS8 NADH dehydrogenase (ubiquinone) Fe-S protein 8, 23kDa 1.006 9.12E- -01
(NADH-coenzyme Q reductase)
NDUFV2 NADH dehydrogenase (ubiquinone) flavoprotein 2, 24kDa 1.085 5.20E- -02
PPA1 pyrophosphatase (inorganic) 1 1.048 3.51 E- -01
PPA2 pyrophosphatase (inorganic) 2 1.090 2.66E- -01
SDHB succinate dehydrogenase complex, subunit B, iron sulfur (Ip) 1.000 9.95E- -01
SDHC succinate dehydrogenase complex, subunit C, integral 1.016 6.96E- -01 membrane protein, 15kDa
SDHD succinate dehydrogenase complex, subunit D, integral 1.107 9.55E- -02 membrane protein
uacR-io ubiquinol-cytochrome c reductase, complex III subunit X 1.062 2.42E- -01
UQCRB ubiquinol-cytochrome c reductase binding protein 1.168 4.96E- -02
UQCRC2 ubiquinol-cytochrome c reductase core protein II 1.016 8.24E- -01
UQCRH ubiquinol-cytochrome c reductase hinge protein 1.138 1.84E- -01
UQCRHL ubiquinol-cytochrome c reductase hinge protein-like 1.094 2.09E- -01
UQCRQ ubiquinol-cytochrome c reductase, complex III subunit VII, 1.084 1.73E- -01
9.5kDa Table 6: list of genes belonging to the Mitochondrial Dysfunction pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (66 observed genes out of 172 total genes; P value=6.9E-10).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
AIFM1 apoptosis-inducing factor, mitochondrion-associated, 1 1.032 3.75E- -01
APH1A anterior pharynx defective 1 homolog A (C. elegans) 1.015 8.34E- -01
APH1 B anterior pharynx defective 1 homolog B (C. elegans) 1.029 4.24E- -01
APP amyloid beta (A4) precursor protein 1.126 1.79E- -01
ATP5C1 ATP synthase, H+ transporting, mitochondrial F1 complex, 1.105 1.74E- -01 gamma polypeptide 1
ATP5J ATP synthase, H+ transporting, mitochondrial Fo complex, 1.078 2.25E- -01 subunit F6
CASP3 caspase 3, apoptosis-related cysteine peptidase 1.114 1.39E- -01
CASP8 caspase 8, apoptosis-related cysteine peptidase 1.189 5.83E- -02
CASP9 caspase 9, apoptosis-related cysteine peptidase 1.029 5.86E- -01
CAT catalase 1.047 5.96E- -01
COX10 COX10 homolog, cytochrome c oxidase assembly protein, 1.034 5.05E- -01 heme A: farnesyltransferase (yeast)
COX11 COX11 cytochrome c oxidase assembly homolog (yeast) 1.033 4.56E- -01
COX17 COX17 cytochrome c oxidase assembly homolog (S. 1.066 3.44E- -01 cerevisiae)
COX5A cytochrome c oxidase subunit Va 1.050 4.37E- -01
COX6A1 cytochrome c oxidase subunit Via polypeptide 1 1.049 4.49E- -01
COX6B1 cytochrome c oxidase subunit Vlb polypeptide 1 (ubiquitous) 1.073 2.64E- -01
COX6C cytochrome c oxidase subunit Vic 1.026 5.21 E- -01
COX7A2 cytochrome c oxidase subunit Vila polypeptide 2 (liver) 1.106 9.80E- -02
COX7B cytochrome c oxidase subunit Vllb 1.164 9.25E- -02
COX7C cytochrome c oxidase subunit Vile 1.093 1.07E- -01
CYC1 cytochrome c-1 1.003 9.38E- -01
CYCS cytochrome c, somatic 1.005 9.23E- -01
FIS1 fission 1 (mitochondrial outer membrane) homolog (S. 1.006 9.02E- -01 cerevisiae)
FURIN furin (paired basic amino acid cleaving enzyme) 1.212 2.09E- -02
GLRX2 glutaredoxin 2 1.132 1.69E- -01
GPX4 glutathione peroxidase 4 (phospholipid hydroperoxidase) 1.078 8.09E- -02
GPX7 glutathione peroxidase 7 1.059 4.28E- -01
HTRA2 HtrA serine peptidase 2 1.003 9.44E- -01
MAOA monoamine oxidase A 1.144 2.14E- -01
MAP2K4 mitogen-activated protein kinase kinase 4 1.008 8.85E- -01
MAPK9 mitogen-activated protein kinase 9 1.028 6.41 E- -01
NDUFA3 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 3, 1.073 2.29E- -01
9kDa
NDUFA4 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4, 1.152 1.34E- -02
9kDa
NDUFA7 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 7, 1.041 3.62E- -01
14.5kDa
NDUFA8 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 8, 1.053 4.40E- -01
19kDa
NDUFA9 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 9, 1.023 5.10E- -01
39kDa
NDUFA1 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 11 , 1.048 4.20E- -01
14.7kDa
NDUFA12 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 12 1.017 8.66E- -01
NDUFA13 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 13 1.044 4.15E- -01
NDUFAB1 NADH dehydrogenase (ubiquinone) 1 , alpha/beta subcomplex, 1.140 5.07E- -02 1 , 8kDa
NDUFB2 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 2, 1.014 8.40E- -01
8kDa - - "
NDUFB3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 1.119 1.39E- -01
12kDa
NDUFB5 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, " 1.015 6.94E- -01
16kDa
NDUFB6 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 6, 1.095 1.04E- -01
17kDa
NDUFB7 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 7, 1.045 4.80E- -01
18kDa
NDUFB8 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 8, 1.028 5.52E- -01
19kDa
NDUFB10 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 10, 1.061 5.00E- -01
22kDa
NDUFB11 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 11 , 1.019 7.52E- -01
17.3kDa
NDUFS3 NADH dehydrogenase (ubiquinone) Fe-S protein 3, 30kDa 1.019 6.92E- -01
(NADH-coenzyme Q reductase)
NDUFS4 NADH dehydrogenase (ubiquinone) Fe-S protein 4, 18kDa 1.110 8.37E- -02
(NADH-coenzyme Q reductase)
NDUFS5 NADH dehydrogenase (ubiquinone) Fe-S protein 5, 15kDa 1.171 4.43E- -02
(NADH-coenzyme Q reductase)
NDUFS8 NADH dehydrogenase (ubiquinone) Fe-S protein 8, 23kDa 1.006 9.12E- -01
(NADH-coenzyme Q reductase)
NDUFV2 NADH dehydrogenase (ubiquinone) flavoprotein 2, 24kDa 1.085 5.20E- -02
PARK7 Parkinson disease (autosomal recessive, early onset) 7 1.008 8.76E- -01
PRDX3 peroxiredoxin 3 1.079 3.03E- -01
PRDX5 peroxiredoxin 5 1.173 2.62E- -03
PSEN1 presenilin 1 1.007 8.93E- -01
PSEN2 presenilin 2 (Alzheimer disease 4) 1.118 7.73E- -02
PSENEN presenilin enhancer 2 homolog (C. elegans) 1.002 9.46E- -01
SDHB succinate dehydrogenase complex, subunit B, iron sulfur (Ip) 1.000 9.95E- -01
SDHC succinate dehydrogenase complex, subunit C, integral 1.016 6.96E- -01 membrane protein, 15kDa
SDHD succinate dehydrogenase complex, subunit D, integral 1.107 9.55E- -02 membrane protein
S0D2 superoxide dismutase 2, mitochondrial 1.097 2.98E- -01
UQCRB ubiquinol-cytochrome c reductase binding protein 1.168 4.96E- -02
UQCRC2 ubiquinol-cytochrome c reductase core protein II 1.016 8.24E- -01
UQCRH ubiquinol-cytochrome c reductase hinge protein 1.138 1.84E- -01
Table 7: list of genes belonging to the Glucocorticoid Receptor Signaling pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (104 observed genes out of 291 total genes; P value=7.12E- 8).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
ADRB2 adrenergic, beta-2-, receptor, surface 1.032 7.71 E- -01
ANXA1 annexin A1 1.230 1.95E- -02
ATM ataxia telangiectasia mutated 1.01 1 8.91 E- -01
CCL3 chemokine (C-C motif) ligand 3 2.012 8.27E- -02
CCL5 chemokine (C-C motif) ligand 5 1.235 1.83E- -01
CCNH cyclin H 1.154 5.90E- -02
CD3D CD3d molecule, delta (CD3-TCR complex) 1.101 6.06E- -02
CD3G CD3g molecule, gamma (CD3-TCR complex) 1.016 7.89E- -01
CEBPB CCAAT/enhancer binding protein (C/EBP), beta 1.079 1.40E- -01
CHUK conserved helix-loop-helix ubiquitous kinase 1.040 4.30E- -01
CREB1 cAMP responsive element binding protein 1 1.092 3.01 E- -01
CREBBP CREB binding protein 1.045 2.98E- -01
CREBZF CREB/ATF bZIP transcription factor 1.030 6. 1 E- -01
CSF2 colony stimulating factor 2 (granulocyte-macrophage) 1.493 1.01 E- -01
DUSP1 dual specificity phosphatase 1 1.073 6.81 E- -01
ELK1 ELK1 , member of ETS oncogene family 1.006 9.34E- -01
EP300 E1 A binding protein p300 1.054 4.08E- -01
FKBP5 FK506 binding protein 5 1.068 3.76E- -01
GTF2A2 general transcription factor IIA, 2, 12kDa 1.092 2.24E- -01
GTF2B general transcription factor IIB 1.037 3.44E- -01
GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E- -02
GTF2E2 general transcription factor HE, polypeptide 2, beta 34kDa 1.017 6.26E- -01
GTF2F2 general transcription factor IIF, polypeptide 2, 30kDa 1.083 7.47E- -02
GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E- -02
GTF2H5 general transcription factor IIH, polypeptide 5 1.185 1.55E- -02
HLTF helicase-like transcription factor 1.149 6.54E- -03
HMGB1 high-mobility group box 1 1.198 1.35E- -02
HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 1.040 2.98E- -01
HSP90AA1 heat shock protein 90kDa alpha (cytosolic), class A member 1 1.033 7.53E- -01
HSP90B1 heat shock protein 90kDa beta (Grp94), member 1 1.01 1 8.43E- -01
HSPA4 heat shock 70kDa protein 4 1.014 8.73E- -01
HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E- -02
HSPA6 heat shock 70kDa protein 6 (HSP70B') 1.122 3.85E- -01
HSPA9 heat shock 70kDa protein 9 (mortalin) 1.006 9.28E- -01
HSPA14 heat shock 70kDa protein 14 1.164 2.19E- -03 heat shock 70kDa protein 1A 1.145 1.35E- -01
HSPA1A/HS
PA B
HSPA1 L heat shock 70kDa protein 1-like 1.035 5.25E- -01
IFNG interferon, gamma 1.508 1.97E- -01
IL4 interleukin 4 1.025 8.37E- -01
IL5 interleukin 5 (colony-stimulating factor, eosinophil) 1.083 5.66E- -01
JAK2 Janus kinase 2 1.338 3.59E- -04
JUN jun proto-oncogene 1.119 2.32E- -01
MAP2K1 mitogen-activated protein kinase kinase 1 1.005 9.21 E- -01
MAP2K4 mitogen-activated protein kinase kinase 4 1.008 8.85E- -01
MAP3K1 mitogen-activated protein kinase kinase kinase 1 1.136 1.72E- -01
MAP3K7 mitogen-activated protein kinase kinase kinase 7 1.035 4.72E- -01
MAPK1 mitogen-activated protein kinase 1 1.042 4.45E- -01 APK9 mitogen-activated protein kinase 9 1.028 6.41 E- -01
MAPK14 mitogen-activated protein kinase 14 1.006 8.97E- -01
MED1 mediator complex subunit 1 1.068 1.98E- -01
MNAT1 menage a trois homolog- 1 , cyclin H assembly factor (Xenopus 1.016 7.81 E- -01 laevis)
NCOA1 nuclear receptor coactivator 1 1.051 3.70E- -01
NCOA2 nuclear receptor coactivator 2 1.010 8.62E- -01
NCOA3 nuclear receptor coactivator 3 1.030 5.51 E- -01
NFAT5 nuclear factor of activated T-cells 5, tonicity-responsive 1.056 4.46E- -01
NFKBIA nuclear factor of kappa light polypeptide gene enhancer in B- 1.142 1.84E- -01 cells inhibitor, alpha
NFKBIB nuclear factor of kappa light polypeptide gene enhancer in B- 1.054 3.14E- -01 cells inhibitor, beta
NFKBIE nuclear factor of kappa light polypeptide gene enhancer in B- 1.042 4.59E- -01 cells inhibitor, epsilon
NR3C1 nuclear receptor subfamily 3, group C, member 1 1.017 7.32E- -01
(glucocorticoid receptor)
NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 1.068 1.30E- -01
NRIP1 nuclear receptor interacting protein 1 1.007 9.20E- -01
PCK2 phosphoenolpyruvate carboxykinase 2 (mitochondrial) 1.009 8.64E- -01
PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1.040 3.60E- -01
PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 1.059 3.11 E- -01
PLAU plasminogen activator, urokinase 1.273 3.78E- -02
P0LR2A polymerase (RNA) II (DNA directed) polypeptide A, 220kDa 1.011 8.32E- -01
POLR2C polymerase (RNA) II (DNA directed) polypeptide C, 33kDa 1.005 9.29E- -01
P0LR2D polymerase (RNA) II (DNA directed) polypeptide D 1.040 2.99E- -01
P0LR2F polymerase (RNA) II (DNA directed) polypeptide F 1.056 3.20E- -01
P0LR2G polymerase (RNA) II (DNA directed) polypeptide G 1.066 2.79E- -01
P0LR2H polymerase (RNA) II (DNA directed) polypeptide H 1.027 5.75E- -01
P0LR2I polymerase (RNA) II (DNA directed) polypeptide I, 14.5kDa 1.000 9.96E- -01
P0LR2J polymerase (RNA) II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E- -01 polymerase (RNA) II (DNA directed) polypeptide J2 1.035 7.06E- -01
POLR2J2/P
OLR2J3
POU2F1 POU class 2 homeobox 1 1.029 4.76E- -01
PPP3CA protein. phosphatase 3, catalytic subunit, alpha isozyme 1.017 7.37E- -01
PPP3CB protein phosphatase 3, catalytic subunit, beta isozyme 1.012 7.64E- -01
PPP3CC protein phosphatase 3, catalytic subunit, gamma isozyme 1.153 3.69E- -03
PPP3R1 protein phosphatase 3, regulatory subunit B, alpha 1.047 3.19E- -01
PRKAB2 protein kinase, AMP-activated, beta 2 non-catalytic subunit 1.009 8.49E- -01
PRKACB protein kinase, cAMP-dependent, catalytic, beta 1.015 8.11 E- -01
PTGES3 prostaglandin E synthase 3 (cytosolic) 1.147 2.43E- -01
PTGS2 prostaglandin-endoperoxide synthase 2 (prostaglandin G/H 1.150 3.14E- -01 synthase and cyclooxygenase)
RAC1 ras-related C3 botulinum toxin substrate 1 (rho family, small 1.032 3.09E- -01
GTP binding protein Rac1)
RRAS related RAS viral (r-ras) oncogene homolog 1.008 8.86E- -01
RRAS2 related RAS viral (r-ras) oncogene homolog 2 1.074 2.66E- -01
SMAD3 SMAD family member 3 1.273 1.00E- -02
SMAD4 S AD family member 4 1.065 1.80E- -01
STAT signal transducer and activator of transcription 1 , 91kDa 1.205 7.85E- -02
STAT5A signal transducer and activator of transcription 5A 1.046 4.89E- -01
TAF2 TAF2 RNA polymerase II, TATA box binding protein (TBP)- 1.051 3.70E- -01 associated factor, 150kDa
TAF5 TAF5 RNA polymerase II, TATA box binding protein (TBP)- 1.049 3.01 E- -01 associated factor, 10OkDa
TAF9 TAF9 RNA polymerase II, TATA box binding protein (TBP)- 1.116 1.27E- -01 associated factor, 32kDa
TAF10 TAF10 RNA polymerase II, TATA box binding protein (TBP)- 1.007 8.82E- -01 associated factor, 30kDa
TAF12 TAF12 RNA polymerase II, TATA box binding protein (TBP)- 1.073 1.05E- -01 associated factor, 20kDa
TAF13 TAF13 RNA polymerase II, TATA box binding protein (TBP)- 1.033 6.37E- -01 associated factor, 18kDa
TAF15 TAF15 RNA polymerase II, TATA box binding protein (TBP)- 1.064 1.93E- -01 associated factor, 68kDa
TAF1 L TAF1 RNA polymerase II, TATA box binding protein (TBP)- 1.006 8.59E- -01 associated factor, 21 OkDa-like
TAF4B TAF4b RNA polymerase II, TATA box binding protein (TBP)- 1.036 4.90E- -01 associated factor, 105kDa
TAF9B TAF9B RNA polymerase II, TATA box binding protein (TBP)- 1.036 5.25E- -01 associated factor, 31kDa
TBP TATA box binding protein 1.017 5.40E- -01
TGFBR2 transforming growth factor, beta receptor II (7 /80kDa) 1.068 2.53E- -01
TRAF6 TNF receptor-associated factor 6 1.039 5.19E- -01
YWHAH tyrosine 3-monooxygenase/tryptophan 5-monooxygenase 1.016 6.76E- -01 activation protein, eta polypeptide
Table 8: list of genes belonging to the Antigen Presentation pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (26 observed genes out of 43 total genes; P value=1.26E-7).
SYMBOL DEFINITION FOLD P ALUE
CHANGE
B2M beta-2-microglobulin 1.024 5.18E-01
CALR calreticulin 1.089 6.26E-02
CANX calnexin 1.090 6.46E-02
CD74 CD74 molecule, major histocompatibility complex, class II 1.1 13 2.19E-01 invariant chain
HLA-A major histocompatibility complex, class I, A 1.033 6.01 E-01
HLA-B major histocompatibility complex, class I, B 1.042 4.95E-01
H LA-DMA major histocompatibility complex, class II, DM alpha 1.117 2.38E-01
HLA-DMB major histocompatibility complex, class II, DM beta 1.079 4.13E-01
HLA-DOA major histocompatibility complex, class II, DO alpha 1.083 2.97E-01
HLA-DPA1 major histocompatibility complex, class II, DP alpha 1 1.193 2.41 E-01
HLA-DPB1 major histocompatibility complex, class II, DP beta 1 1.141 2.37Έ-01
HLA-DQA1 major histocompatibility complex, class II, DQ alpha 1 1.204 2.98E-01
HLA-DRA major histocompatibility complex, class II, DR alpha 1.236 9.41 E-02
HLA-DRB4 major histocompatibility complex, class II, DR beta 4 1.255 3.36E-01
HLA-DRB3 major histocompatibility complex, class II, DR beta 3 1.039 7.78E-01
(includes
others)
HLA-F major histocompatibility complex, class I, F 1.148 1.27E-01
HLA-G major histocompatibility complex, class I, G 1.055 6.14E-01
IFNG interferon, gamma 1.508 1.97E-01
(includes
EG: 15978)
MR1 major histocompatibility complex, class l-related 1.009 9.12E-01
PSMB5 proteasome (prosome, macropain) subunit, beta type, 5 1.006 9.21 E-01
PSMB6 proteasome (prosome, macropain) subunit, beta type, 6 1.058 2.70E-01
PSMB8 proteasome (prosome, macropain) subunit, beta type, 8 (large 1.056 4.75E-01 multifunctional peptidase 7)
PSMB9 proteasome (prosome, macropain) subunit, beta type, 9 (large 1.078 2.48E-01 multifunctional peptidase 2)
TAP1 transporter 1 , ATP-binding cassette, sub-family B (MDR/TAP) 1.051 3.59E-01-
TAP2 transporter 2, ATP-binding cassette, sub-family B (MDR/TAP) 1.174 1.42 E-02
TAPBP TAP binding protein (tapasin) 1.002 9.84E-01
Table 9: list of genes belonging to the Purine Metabolism pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (102 observed genes out of 386 total genes; P value=3.61 E-7).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
ADCY3 adenylate cyclase 3 1.133 5.47E-02
ADK adenosine kinase 1.067 3.68E-01
ADSS adenylosuccinate synthase 1.136 5.35E-05
ADSSL1 adenylosuccinate synthase like 1 1.015 7.49E-01
AK2 adenylate kinase 2 1.053 3.27E-01
AK4 adenylate kinase 4 1.209 2.40E-02
ATIC 5-aminoimidazole-4-carboxamide ribonucleotide 1.025 7.04E-01 formyltransferase/I P cyclohydrolase
ATP5C1 ATP synthase, H+ transporting, mitochondrial F1 complex, 1.105 1.74E-01 gamma polypeptide 1
ATP5D ATP synthase, H+ transporting, mitochondrial F1 complex, delta 1.007 8.75E-01 subunit
ATP5G1 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.05 4.61 E-01 subunit C1 (subunit 9)
ATP5G2 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.026 7.49E-01 subunit C2 (subunit 9)
ATP5G3 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.052 2.20E-01 subunit C3 (subunit 9)
ATP5H ATP synthase, H+ transporting, mitochondrial Fo complex, 1.125 5.76E-02 subunit d
ATP5I ATP synthase, H+ transporting, mitochondrial Fo complex, 1.034 5.59E-01 subunit E
ATP5J2 ATP synthase, H+ transporting, mitochondrial Fo complex, 1.086 1.62E-01 subunit F2
ATP5J ATP synthase, H+ transporting, mitochondrial Fo complex, 1.078 2.25E-01 subunit F6
ATP5L ATP synthase, H+ transporting, mitochondrial Fo complex, 1.098 1.01 E-01 subunit G
ATP5S ATP synthase, H+ transporting, mitochondrial Fo complex, 1.101 8.46E-02 subunit s (factor B)
ATP6V1 G1 ATPase, H+ transporting, lysosomal 13kDa, V1 subunit G1 1.069 1.66E-01
BCKDHB branched chain keto acid dehydrogenase E1 , beta polypeptide 1.023 6.11 E-01
BLM Bloom syndrome, RecQ helicase-like 1.097 8.80E-02
CHD1 L chromodomain helicase DNA binding protein 1 -like 1.026 5.52E-01
CLPX ClpX caseinolytic peptidase X homolog (E. coli) 1.043 3.71 E-01
DCK deoxycytidine kinase 1.019 7.74E-01
DCTPP1 dCTP pyrophosphatase 1 1.051 4.57E-01
DGUOK deoxyguanosine kinase 1.073 4.01 E-02
DNA2 DNA replication helicase 2 homolog (yeast) 1.068 2.46E-01
ENPP3 ectonucleotide pyrophosphatase/phosphodiesterase 3 1.019 8.55 E-01
ENTPD1 ectonucleoside triphosphate diphosphohydrolase 1 1.759 1.60E-02
GART phosphoribosylglycinamide formyltransferase, 1.046 4.80E-01 phosphoribosylglycinamide synthetase,
phosphoribosylaminoimidazole synthetase
GMPR2 guanosine monophosphate reductase 2 1.015 7.95E-01
HLTF helicase-like transcription factor 1.149 6.54E-03
HPRT1 hypoxanthine phosphoribosyltransferase 1 1.12 4.43E-02
HSPA5 heat shock 70kDa protein 5 (glucose-regulated protein, 78kDa) 1.107 4.28E-02
HSPD1 heat shock 60kDa protein 1 (chaperonin) 1.127 1.79E-01
IDE insulin-degrading enzyme 1.064 2.57E-01
IMPAD1 inositol monophosphatase domain containing 1 1.092 2.80E-02 KATNA1 katanin p60 (ATPase containing) subunit A 1 1.004 9.13E-01
KIF1 B kinesin family member 1 B 1.267 7.86E-05
KIF20B kinesin family member 20B 1.029 6.53E-01
LOC1001328 postmeiotic segregation increased 2 pseudogene 5 1.016 7.57E-01
32/PMS2P5
MPP6 membrane protein, palmitoylated 6 (MAGUK p55 subfamily 1.047 4.61 E-01 member 6)
MSH2 mutS homolog 2, colon cancer, nonpolyposis type 1 (E. coli) 1.073 3.05E-01
MYH9 myosin, heavy chain 9, non-muscle 1.016 7.27E-01
NME7 non-metastatic cells 7, protein expressed in (nucleoside- 1.062 2.42E-01 diphosphate kinase)
NME1 non-metastatic cells 1 , protein (NM23A) expressed in 1.123 1.41Έ-01
(includes
EG:18102)
NT5C2 5'-nucleotidase, cytosolic II 1.067 1.74E-01
NT5C3 5'-nucleotidase, cytosolic III 1.098 7.03E-02
NT5E 5'-nucleotidase, ecto (CD73) 1.088 1.87E-01
NUDT5 nudix (nucleoside diphosphate linked moiety X)-type motif 5 1.085 1.06ΕΞτ01
NUDT9 nudix (nucleoside diphosphate linked moiety X)-type motif 9 1,022 6.26E-01
PAICS phosphoribosylaminoimidazole carboxylase, 1.075 2.03E-01 phosphoribosylaminoimidazole succinocarboxamide synthetase
PAPD5 PAP associated domain containing 5 1.028 6.01 E-01
PAPD7 PAP associated domain containing 7 1.069 9.88E-02
PAPSS1 3'-phosphoadenosine 5'-phosphosulfate synthase 1 1.081 4.17E-01
PDE7B phosphodiesterase 7B 1.135 3.54E-01
PDE9A phosphodiesterase 9A 1.058 5.30E-01
PFAS phosphoribosylformylglycinamidine synthase 1.026 7.01 E-01
PKM2 pyruvate kinase, muscle 1.124 8.98E-02
PMS1 PMS1 postmeiotic segregation increased 1 (S. cerevisiae) 1.03 4.57E-01
PNP purine nucleoside phosphorylase 1.052 4.72E-01
PNPT1 polyribonucleotide nucleotidyltransferase 1 1.12 3.82E-02
POLB polymerase (DNA directed), beta 1.016 6.28E-01
POLE2 polymerase (DNA directed), epsilon 2 (p59 subunit) 1.139 8.74E-02
POLE3 polymerase (DNA directed), epsilon 3 (p17 subunit) 1.024 6.19E-01
POLE4 polymerase (DNA-directed), epsilon 4 (p12 subunit) 1.136 3.60E-02
POLQ polymerase (DNA directed), theta 1.004 9.65E-01
POLR1C polymerase (RNA) I polypeptide C, 30kDa 1.122 9.19E-03
POLR1 D polymerase (RNA) I polypeptide D, 16kDa 1.064 2.77 E-01
POLR2A polymerase (RNA) II (DNA directed) polypeptide A, 220kDa 1.011 8.32E-01
POLR2C . polymerase (RNA) II (DNA directed) polypeptide C, 33kDa 1.005 9.29E-01
POLR2D polymerase (RNA) II (DNA directed) polypeptide D 1.04 2.99E-01
POLR2F polymerase (RNA) II (DNA directed) polypeptide F 1.056 3.20E-01
POLR2G polymerase (RNA) II (DNA directed) polypeptide G 1.066 2.79E-01
POLR2H polymerase (RNA) II (DNA directed) polypeptide H 1.027 5.75E-01
POLR2I polymerase (RNA) II (DNA directed) polypeptide I, 14.5kDa 1 9.96E-01
POLR2J polymerase (RNA) II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E-01
POLR3A polymerase (RNA) III (DNA directed) polypeptide A, 155kDa 1.011 8.72E-01
POLR3B polymerase (RNA) III (DNA directed) polypeptide B 1.037 5.06E-01
POLR3C polymerase (RNA) III (DNA directed) polypeptide C (62kD) 1.068 1.05E-01
POLR3H polymerase (RNA) III (DNA directed) polypeptide H (22.9kD) 1.036 3.59E-01
POLR3K polymerase (RNA) III (DNA directed) polypeptide K, 12.3 kDa 1.105 1.14E-01
PPAT phosphoribosyl pyrophosphate amidotransferase 1.088 5.21 E-02
PRIM1 primase, DNA, polypeptide 1 (49kDa) 1.056 3.94E-01
PRPS1 phosphoribosyl pyrophosphate synthetase 1 1.053 2.51 E-01
PRPS2 phosphoribosyl pyrophosphate synthetase 2 1.16 4.62E-03
PSMC1 proteasome (prosome, macropain) 26S subunit, ATPase, 1 1.052 2.11 E-01
PSMC2 proteasome (prosome, macropain) 26S subunit, ATPase, 2 1.136 1.78E-02
PSMC4 proteasome (prosome, macropain) 26S subunit, ATPase, 4 1.04 3.05E-01 PSMC6 proteasome (prosome, macropain) 26S subunit, ATPase, 6 1.051 2.44E-01
RALBP1 ralA binding protein 1 1.024 6.35E-01
RFC5 replication factor C (activator 1) 5, 36.5kDa 1.043 5.25E-01
RRM1 ribonucleotide reductase M1 1.125 9.34E-02
RRM2 ribonucleotide reductase M2 1.107 3.31 E-01
RRM2B ribonucleotide reductase M2 B (TP53 inducible) 1.052 3.80E-01
SMARCA5 SWI/SNF related, matrix associated, actin dependent regulator 1.142 8.58E-02 of chromatin, subfamily a, member 5
TAF9 TAF9 RNA polymerase II, TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
TYMP thymidine phosphorylase 1.044 6.86E-01
VCP valosin containing protein 1.006 9.23E-01
VPS4B vacuolar protein sorting 4 homolog B (S. cerevisiae) 1.026 6.24E-01
WRN Werner syndrome, RecQ helicase-like 1.098 3.85E-02
WRNIP1 Werner helicase interacting protein 1 1.017 7.51 E-01
Table 10: list of genes belonging to the Assembly of RNA Polymerase II Complex pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (29 observed genes out of 56 total genes; P value=8.25E-7).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
CCNH cyclin H 1.154 5.90E-02
DR1 down-regulator of transcription 1 , TBP-binding (negative cofactor 1.068 2.83E-01
GTF2A2 general transcription factor IIA, 2, 12kDa 1.092 2.24E-01
GTF2B general transcription factor IIB 1.037 3.44E-01
GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E-02
GTF2E2 general transcription factor HE, polypeptide 2, beta 34kDa 1.017 6.26E-01
GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E-02
GTF2H5 general transcription factor IIH, polypeptide 5 1.185 1.55E-02
MNAT1 menage a trois homolog 1 , cyclin H assembly factor (Xenopus 1.016 7.81 E-01 laevis)
POLR2A polymerase (RNA) II (D A directed) polypeptide A, 220kDa 1.01 1 8.32E-01
POLR2C polymerase (RNA) II (DNA directed) polypeptide C, 33kDa 1 .005 9.29E-01
POLR2D polymerase (RNA) II (DNA directed) polypeptide D 1.04 2.99E-01
POLR2F polymerase (RNA) II (DNA directed) polypeptide F 1.056 3.20E-01
POLR2G polymerase (RNA) II (DNA directed) polypeptide G 1.066 2.79E-01
POLR2H polymerase (RNA) II (DNA directed) polypeptide H 1.027 5.75E-01
POLR2I polymerase (RNA) II (DNA directed) polypeptide I, 14.5kDa 1 9.96E-01
POLR2J polymerase (RNA) II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E-01
POLR2J2/P polymerase (RNA) II (DNA directed) polypeptide J2 1.035 7.06E-01
OLR2J3
TAF2 TAF2 RNA polymerase II, TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor, 150kDa
TAF5 TAF5 RNA polymerase II, TATA box binding protein (TBP)- 1.049 3.01 E-01 associated factor, 100kDa
TAF9 TAF9 RNA polymerase II, TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
TAF12 TAF12 RNA polymerase II, TATA box binding protein (TBP)- 1.073 1.05E-01 associated factor, 20kDa
TAF13 TAF13 RNA polymerase II, TATA box binding protein (TBP)- 1.033 6.37E-01 associated factor, 18kDa
TAF15 TAF15 RNA polymerase II, TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor, 68kDa
TAF10 TAF10 RNA polymerase II, TATA box binding protein (TBP)- 1.007 8.82E-01
(includes associated factor, 30kDa
EG:216185)
TAF1 L TAF1 RNA polymerase II, TATA box binding protein (TBP)- 1.006 8.59E-01 associated factor, 210kDa-like
TAF4B TAF4b RNA polymerase II, TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor, 105kDa
TAF9B TAF9B RNA polymerase II, TATA box binding protein (TBP)- 1.036 5.25E-01 associated factor, 31 kDa
TBP TATA box binding protein 1.017 5.40E-01 Table 11 : list of genes belonging to the Cytotoxic T Lymphocyte-mediated Apoptosis of Target Cells pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (28 observed genes out of 53 total genes; P value=1.93E-6).
SYMBOL DEFINITION FOLD P VALUE CHANGE
APAF1 apoptotic peptidase activating factor 1 1.036 4.74E-01
B2M beta-2 -microglobulin 1.024 5.18E-01
CASP3 caspase 3, apoptosis-related cysteine peptidase 1.114 1.39E-01
CASP6 caspase 6, apoptosis-related cysteine peptidase 1.033 6.85E-01
CASP8 caspase 8, apoptosis-related cysteine peptidase 1.189 5.83E-02
CASP9 caspase 9, apoptosis-related cysteine peptidase 1.029 5.86E-01
(includes
EG:1001409
45)
CD3D CD3d molecule, delta (CD3-TCR complex) 1.101 6.06E-02
CD3G CD3g molecule, gamma (CD3-TCR complex) 1.016 7.89E-01
CYCS cytochrome c, somatic 1.005 9.23E-01
FADD Fas (TNFRSF6)-associated via death domain 1.093 4.43E-02
FASLG Fas ligand (TNF superfamily, member 6) 1.291 1.39E-01
FCER1 G Fc fragment of IgE, high affinity I, receptor for; gamma 1.48 8.32E-02 polypeptide
GZMB granzyme B (granzyme 2, cytotoxic T-lymphocyte-associated 1.389 5.20E-03 serine esterase 1 )
HLA-A major histocompatibility complex, class I, A 1.033 6.01 E-01
HLA-B major histocompatibility complex, class I, B 1.042 4.95E-01
H LA-DMA major histocompatibility complex, class II, DM alpha 1.1 17 2.38E-01
HLA-DMB major histocompatibility complex, class II, DM beta 1.079 4.13E-01
HLA-DOA major histocompatibility complex, class II, DO alpha 1.083 2.97E-01
HLA-DPAT major histocompatibility complex, class II, DP alpha 1 1.193 2.41 E-01
HLA-DPB1 major histocompatibility complex, class II, DP beta 1 1.141 2.37E-01
HLA-DQA1 major histocompatibility complex, class II, DQ alpha 1 1.204 2.98E-01
HLA-DQB1 major histocompatibility complex, class II, DQ beta 1 1.054 7.36 E-01
HLA-DRA major histocompatibility complex, class II, DR alpha 1.236 9.41 E-02
HLA-DRB4 major histocompatibility complex, class II, DR beta 4 1.255 3.36E-01
HLA-DRB3 major histocompatibility complex, class II, DR beta 3 1.039 7.78E-01
(includes
others)
HLA-F major histocompatibility complex, class I, F 1.148 1.27E-01
HLA-G major histocompatibility complex, class I, G 1.055 6.14E-01
PRE1 perforin 1 (pore forming protein) 1.194 3.38E-01
Table 12: list of genes belonging to the Estrogen Receptor Signaling pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (56 observed genes out of 136 total genes; P value=2.57E- 5)·
SYMBOL DEFINITION FOLD P VALUE
CHANGE
CCNC cyclin C 1.082 1.42E-01
CCNH cyclin H 1.154 5.90E-02
CREBBP CREB binding protein 1.045 2.98E-01
CTBP1 C-terminal binding protein 1 1.007 8.92E-01
DDX5 DEAD (Asp-Glu-Ala-Asp) box helicase 5 1.04 3.77E-01
EP300 E1A binding protein p300 1.054 4.08E-01
GTF2B general transcription factor I IB 1.037 3.44E-01
GTF2E1 general transcription factor HE, polypeptide 1 , alpha 56kDa 1.077 5.60E-02
GTF2F2 general transcription factor IIF, polypeptide 2, 30kQa 1.083 7.47E-02
GTF2H1 general transcription factor IIH, polypeptide 1 , 62kDa 1.145 2.76E-02
GTF2H5 general transcription factor IIH, polypeptide 5 1.185 1.55E-02
H3F3A/H3F3 H3 histone, family 3B (H3.3B) 1.038 3.03E-01
R
D
HNRNPD heterogeneous nuclear ribonucleoprotein D (AU-rich element 1.015 7.86E-01
RNA binding protein 1 , 37kDa)
HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 1.04 2.98E-01
MAP2K1 mitogen -activated protein kinase kinase 1 1.005 9.21 E-01
MAPK1 mitogen-activated protein kinase 1 1.042 4.45E-01
MEDI O mediator complex subunit 10 1.028 5.23E-01
MED23 mediator complex subunit 23 1 9.99E-01
MED27 mediator complex subunit 27 1.014 7.42E-01
MED30 mediator complex subunit 30 1.053 2.89E-01
MED1 mediator complex subunit 1 1.068 1.98E-01
(includes
EG:19014)
MED4 mediator complex subunit 4 1.127 6.01 E-02
(includes
EG:29079)
MED6 mediator complex subunit 6 1.102 6.99E-03
(includes
EG: 10001 )
MNAT1 menage a trois homolog 1 , cyclin H assembly factor (Xenopus 1.016 7.81 E-01 laevis)
NCOA1 nuclear receptor coactivator 1 1.051 3.70E-01
NCOA2 nuclear receptor coactivator 2 1.01 8.62E-01
NCOA3 nuclear receptor coactivator 3 1.03 5.51 E-01
NR3C1 nuclear receptor subfamily 3, group C, member 1 (glucocorticoid 1.017 7.32E-01 receptor)
NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 1.068 1.30E-01
NRIP1 nuclear receptor interacting protein 1 1.007 9.20E-01
PCK2 phosphoenolpyruvate carboxykinase 2 (mitochondrial) 1.009 8.64E-01
POLR2A polymerase (RNA) II (DNA directed) polypeptide A, 220kDa 1.01 1 8.32E-01
POLR2C polymerase (RNA) II (DNA directed) polypeptide C, 33kDa 1.005 9.29E-01
POLR2D polymerase (RNA) II (DNA directed) polypeptide D 1.04 2.99E-01
POLR2F polymerase (RNA) II (DNA directed) polypeptide F 1.056 3.20E-01
POLR2G polymerase (RNA) II (DNA directed) polypeptide G 1.066 2.79E-01
POLR2H polymerase (RNA) II (DNA directed) polypeptide H 1.027 5.75E-01
POLR2I polymerase (RNA) II (DNA directed) polypeptide I, 14.5kDa 1 9.96 E-01
POLR2J polymerase (RNA) II (DNA directed) polypeptide J, 13.3kDa 1.062 3.99E-01 POLR2J2/P polymerase (RNA) II (DNA directed) polypeptide J2 1.035 7.06E-01
OLR2J3
PRKDC protein kinase, DNA-activated, catalytic polypeptide 1.025 -•5-.91 E-01
RRAS2 related RAS viral (r-ras) oncogene homolog 2 1.074 2.66E-01
RRAS related RAS viral (r-ras) oncogene homolog 1.008 8.86E-01
SPEN spen homolog, transcriptional regulator (Drosophila) 1.078 2.27E-01
TAF2 TAF2 RNA polymerase II, TATA box binding protein (TBP)- 1.051 3.70E-01 associated factor, 150kDa
TAF5 TAF5 RNA polymerase II, TATA box binding protein (TBP)- 1.049 3.01 E-01 associated factor, 10OkDa
TAF9 TAF9 RNA polymerase II, TATA box binding protein (TBP)- 1.116 1.27E-01 associated factor, 32kDa
TAF12 TAF12 RNA polymerase II, TATA box binding protein (TBP)- 1.073 1.05E-01 associated factor, 20kDa
TAF13 TAF13 RNA polymerase II, TATA box binding protein (TBP)- 1.033 6.37E-01 associated factor, 18kDa
TAF15 TAF15 RNA polymerase II, TATA box binding protein (TBP)- 1.064 1.93E-01 associated factor, 68kDa
TAF10 TAF10 RNA polymerase II, TATA box binding protein (TBP)- 1.007 8.82E-01
(includes associated factor, 30kDa
EG-.216185)
TAF1 L TAF1 RNA polymerase II, TATA box binding protein (TBP)- 1.006 8.59E-01 associated factor, 210kDa-like
TAF4B TAF4b RNA polymerase II, TATA box binding protein (TBP)- 1.036 4.90E-01 associated factor, 105kDa
TAF9B TAF9B RNA polymerase II, TATA box binding protein (TBP)- 1.036 5.25E-01 associated factor, 31 kDa
TBP TATA box binding protein 1.017 5.40E-01
TRRAP transformation/transcription domain-associated protein 1.089 2.24E-01
Table 13: list of genes belonging to the NRF2-mediated Oxidative Stress Response pathway, with the fold change and P value of the differential expression between MLD patients and controls, based on Ingenuity Pathway Analysis software (73 observed genes out of 191 total genes; P value=3.12E-6).
SYMBOL DEFINITION FOLD P VALUE
CHANGE
ABCC4 ATP-binding cassette, sub-family C (CFTR/MRP), member 4 1.057 1.94E- -01
AKR1A1 aldo-keto reductase family 1 , member A1 (aldehyde reductase) 1.009 8.80E- -01
ATM ataxia telangiectasia mutated 1.01 1 8.91 E- -01
CAT catalase 1.047 5.96E- -01
CCT7 chaperonin containing TCP1 , subunit 7 (eta) 1.015 7.32E- -01
CREBBP CREB binding protein 1.045 2.98E- -01
DNAJA1 DnaJ (Hsp40) homolog, subfamily A, member 1 1.036 5.28E- -01
DNAJA2 DnaJ (Hsp40) homolog, subfamily A, member 2 1.117 4.30E- -02
DNAJB1 DnaJ (Hsp40) homolog, subfamily B, member 1 1.015 6.95E- -01
DNAJB6 DnaJ (Hsp40) homolog, subfamily B, member 6 1.056 3.33E- -01
DNAJB9 DnaJ (Hsp40) homolog, subfamily B, member 9 1.227 5.43E- -03
DNAJB1 1 DnaJ (Hsp40) homolog, subfamily B, member 1 1 1.034 6.07E- -01
DNAJB12 DnaJ (Hsp40) homolog, subfamily B, member 12 1.023 5.86E- -01
DNAJB14 DnaJ (Hsp40) homolog, subfamily B, member 14 1.135 2.18E- -03
DNAJC9 DnaJ (Hsp40) homolog, subfamily C, member 9 1.074 1.60E- -01
DNAJC10 DnaJ (Hsp40) homolog, subfamily C, member 10 1.101 1.20E- -01
DNAJC14 DnaJ (Hsp40) homolog, subfamily C, member 14 1.006 8.84E- -01
DNAJC15 DnaJ (Hsp40) homolog, subfamily C, member 15 1.068 3.70E- -01
DNAJC18 DnaJ (Hsp40) homolog, subfamily C, member 18 1.076 1.29E- -01
DNAJC19 DnaJ (Hsp40) homolog, subfamily C, member 19 1.026 5.38E- -01
EIF2AK3 eukaryotic translation initiation factor 2-alpha kinase 3 1.047 3.23E- -01
EP300 E1A binding protein p300 1.054 4.08E- -01
ERP29 endoplasmic reticulum protein 29 1.025 6.21 E- -01
FKBP5 FK506 binding protein 5 1.068 3.76E- -01
FTH1 ferritin, heavy polypeptide 1 1.058 3.81 E- -01
FTL ferritin, light polypeptide 1.064 2.80E- -01
GCLC glutamate-cysteine ligase, catalytic subunit 1.043 4.53E- -01
GCLM glutamate-cysteine ligase, modifier subunit 1.125 9.16E- -02
GSTK1 glutathione S-transferase kappa 1 1.106 4.37E- -02
GST01 glutathione S-transferase omega 1 1.088 1.45E- -01
GSTP1 glutathione S-transferase pi 1 1.020 7.43E- -01
HERPUD1 homocysteine-inducible, endoplasmic reticulum stress- 1.092 7.29E- -02 inducible, ubiquitin-like domain member 1
HMOX1 heme oxygenase (decycling) 1 1.057 6.24E- -01
HRAS v-Ha-ras Harvey rat sarcoma viral oncogene homolog 1.040 2.98E- -01
JUN jun proto-oncogene 1.119 2.32E- -01
JUNB jun B proto-oncogene 1.040 6.06E- -01
JUND jun D proto-oncogene 1.043 2.98E- -01
KEAP1 kelch-like ECH-associated protein 1 1.055 3.64E- -01
MAF v-maf musculoaponeurotic fibrosarcoma oncogene homolog 1.221 2.26E- -01
(avian)
MAFF v-maf musculoaponeurotic fibrosarcoma oncogene homolog F 1.033 5.28E- -01
(avian)
MAFG v-maf musculoaponeurotic fibrosarcoma oncogene homolog G 1.014 6.95E- -01
(avian)
MAP2K1 mitogen-activated protein kinase kinase 1 1.005 9.21 E- -01
MAP2K3 mitogen-activated protein kinase kinase 3 1.013 8.03E- -01
MAP2K4 mitogen-activated protein kinase kinase 4 1.008 8.85E- -01
MAP3K1 mitogen-activated protein kinase kinase kinase 1 1.136 1.72E- -01 MAP3K5 mitogen-activated protein kinase kinase kinase 5 1.032 5.42E- -01
MAP3K7 mitogen-activated protein kinase kinase kinase 7 1.035 4.72E- -01
MAPK1 mitogen-activated protein kinase 1 1.042 4.45E- -01
MAPK9 mitogen-activated protein kinase 9 1.028 6.4iE- -01 APK14 mitogen-activated protein kinase 14 1.006 8.97E- -01
MGST3 microsomal glutathione S-transferase 3 1.245 3.37E- -02
NFE2L2 nuclear factor (erythroid-derived 2)-like 2 1.082 9.00E- -02
NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 1.068 1.30E- -01
PIK3CA phosphoinositide-3-kinase, catalytic, alpha polypeptide 1.040 3.60E- -01
PIK3R1 phosphoinositide-3-kinase, regulatory subunit 1 (alpha) 1.059 3.11 E- -01
PPIB peptidylprolyl isomerase B (cyclophilin B) 1.058 3.31 E- -01
PRDX1 peroxiredoxin 1 1.184 2.41 E- -02
PRKCA protein kinase C, alpha 1.002 9.69E- -01
PRKCB protein kinase C, beta 1.120 1.01 E- -01
PRKCQ protein kinase C, theta 1.070 4.52E- -02
PTPLAD1 protein tyrosine phosphatase-like A domain containing 1 1.087 1.91 E- -01
RBX1 ring-box 1 , E3 ubiquitin protein ligase 1.156 8.09E- -02
RRAS related RAS viral (r-ras) oncogene homolog 1.008 8.86E- -01
RRAS2 related RAS viral (r-ras) oncogene homolog 2 1.074 2.66E- -01
SLC35A2 solute carrier family 35 (UDP-galactose transporter), member 1.001 9.77E- -01
Δ
S0D1 superoxide dismutase 1 , soluble 1.119 3.86E- -02
S0D2 superoxide dismutase 2, mitochondrial 1.097 2.98E- -01
SQST 1 sequestosome 1 1.129 1.52E- -01
TXN thioredoxin 1.153 4.77E- -02
UBE2E3 ubiquitin-conjugating enzyme E2E 3 (UBC4/5 homolog, yeast) 1.135 2.36E- -02
UBE2K ubiquitin-conjugating enzyme E2K (UBC1 homolog, yeast) 1.078 5.13E- -02
USP14 ubiquitin specific peptidase 14 (tRNA-guanine transglycosylase) 1.100 4.61 E- -02
VCP valosin containing protein 1.006 9.23E- -01
ABBREVIATIONS
CNS: Central Nervous System
CSF: Cerebrospinal Fluid
GLD: Globoid Cell Leukodystrophy
IPA: Ingenuity Pathway Analysis
LSD: Lysosomal Storage Disorder
MLD: Metachromatic Leukodystrophy
MPSI: Mucopolysaccharidosis type I
MPSIII: Mucopolysaccharidosis type III
MSD: Multiple Sulfatase Deficiency
MT: Metallothionein
NCL: Neuronal Ceroid Lipofuscinosis NPC: Niemann-Pick disease type C
PAM: Prediction Analysis of Microarrays
SAM: Significance Analysis of Microarrays
SD: Sandhoff s Disease
All publications mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described methods and system of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention which are apparent to those skilled in molecular biology or related fields are intended to be within the scope of the following claims.

Claims

Claims
1. A method of diagnosis or prognosis of a lysosomal storage disorder in a subject, wherein said method comprises
(i) providing a sample from said subject,
(ii) determining the expression level of a metallothionein in said sample,
(iii) comparing the expression level of the metallothionein in said sample with the expression level of the metallothionein in a sample from a healthy subject or a previous sample from said subject.
2. A method for monitoring the progress of a lysosomal storage disorder in a subject comprising the steps of:
(i) providing a first sample from a subject,
(ii) determining the expression level of a metallothionein in said first sample,
(iii) providing a second sample from the subject wherein said second sample is obtained from the subject after said first sample,
(iv) comparing the expression level of the metallothionein in the second sample with the expression level of the metallothionein in the first sample wherein an increase in metallothionein expression in the second sample relative to the first sample indicates disease progression.
3. A method according to claim 2 wherein the second sample is obtained from the subject at least 10, 20, 50, 100, 200 or 300 days after the first sample.
4. A method according to claim 2 or 3 wherein the method is for monitoring the progress of a lysosomal storage disorder in response to treatment of the lysosomal storage disorder.
5. A method according to any one of claims 2 to 4 wherein the treatment is bone marrow transplantation, gene therapy and enzyme replacement therapy.
6. A method according to any preceding claim wherein the sample is nervous tissue, blood, blood cells, blood plasma, blood serum or cerebrospinal fluid.
7. A method according to claim 6 wherein the sample is cerebrospinal fluid.
8. A method according to any preceding claim wherein the metallothionein expression levels are determined by quantitative PCR or an immuoasssay.
9. A method according to claim 8 wherein the immunoassay is selected from the group consisting of enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunofluorescence assay (IF A), enzyme linked assay (EIA) and luminescence immunoassay (LIA), Western Blot assay (WB).
10. A method according to any preceding claim wherein the metallothionein is selected from the group consisting of MTl , MT2, MT3 and MT4.
11. A method according to any preceding claim wherein the metallothionein is selected from the group consisting of MTl A, MT1E, MT2A and MTE.
12. A method according to any preceding claim wherein the method comprises determining the expression level of more than one metallothionein.
13. A method according to claim 12 wherein the method comprises determining the expression levels of MTl A, MT1E, MT2A and/or MTE.
14. A method according to any preceding claim wherein the lysosomal storage disorder is selected from the group consisting of Metachromatic Leukodystrophy (MLD), Globoid Cell Leukodystrophy (GLD), Mucopolysaccharidois type I (MPS I), Mucopolysaccharidosis type III (MPS III), Neimann Pick disease (NPC), Neuronal Ceroidolipofuscinosis (NCL) and Sandhoff disease (SD).
15. A method according to claim 14 wherein the lysosomal storage disorder is MLD.
16. A method according to any preceding claim wherein the subject is a human subject.
17. An antibody directed against a metallothionein for use in a diagnostic for a lysosomal storage disorder.
18. Use of an antibody directed against a metallothionein for use in an in-vitro diagnostic for a lysosomal storage disorder.
19. An antibody or use according to claim 17 or 18 wherein the metallothionein is selected from the group consisting of MT1 and MT2.
20. An antibody or use according to any one of claims 1 to 19 wherein the lysosomal storage disorder is selected from the group consisting of Metachromatic leukodystrophy (MLD), Globoid Cell Leukodystrophy (GLD), Mucopolysaccharidois type I (MPS I), Mucopolysaccharidosis type III (MPS III), Neimann Pick disease (NPC), Neuronal Ceroidolipofuscinosis (NCL) and Sandhoff disease (SD).
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018136435A1 (en) * 2017-01-17 2018-07-26 Children's Medical Center Corporation Compositions and methods for treating lysosomal storage diseases and disorders
WO2018136434A1 (en) * 2017-01-17 2018-07-26 Children's Medical Center Corporation Compositions and methods for diagnosing and treating peroxisomal diseases
WO2020123511A3 (en) * 2018-12-10 2020-07-23 Denali Therapeutics Inc. Lysosomal storage disorder biomarkers and methods of use thereof
CN113265461A (en) * 2021-07-02 2021-08-17 北京华诺奥美医学检验实验室有限公司 Primer group, probe group and kit for detecting high-frequency gene pathogenic variation
US11957713B2 (en) 2016-10-14 2024-04-16 Children's Medical Center Corporation Compositions and methods for treating diseases and disorders of the central nervous system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1997044668A1 (en) * 1996-05-17 1997-11-27 Women's And Children's Hospital Early detection of lysosomal storage disorders
WO2004088322A1 (en) * 2003-03-31 2004-10-14 Women's And Children's Hospital MULTIPLEX SCREENING FOR LYSOSOMAL STORAGE DISORDERS (LSDs)
WO2007136782A2 (en) * 2006-05-19 2007-11-29 Historx, Inc. Kits and methods for evaluating misfolded proteins
US7378231B1 (en) * 1999-03-17 2008-05-27 Women's And Children's Hospital Diagnosis of lysosomal storage disorders using saposins and other markers
WO2011028941A2 (en) * 2009-09-04 2011-03-10 The United States Of America, As Represented By The Secretary Department Of Health & Human Services Disabling autophagy as a treatment for lysosomal storage diseases

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1997044668A1 (en) * 1996-05-17 1997-11-27 Women's And Children's Hospital Early detection of lysosomal storage disorders
US7378231B1 (en) * 1999-03-17 2008-05-27 Women's And Children's Hospital Diagnosis of lysosomal storage disorders using saposins and other markers
WO2004088322A1 (en) * 2003-03-31 2004-10-14 Women's And Children's Hospital MULTIPLEX SCREENING FOR LYSOSOMAL STORAGE DISORDERS (LSDs)
WO2007136782A2 (en) * 2006-05-19 2007-11-29 Historx, Inc. Kits and methods for evaluating misfolded proteins
WO2011028941A2 (en) * 2009-09-04 2011-03-10 The United States Of America, As Represented By The Secretary Department Of Health & Human Services Disabling autophagy as a treatment for lysosomal storage diseases

Non-Patent Citations (63)

* Cited by examiner, † Cited by third party
Title
"Oligonucleotide Synthesis: A Practical Approach", IRL PRESS
ADAM V ET AL: "Vertebrate metallothioneins as target molecules for analytical techniques", TRAC, TRENDS IN ANALYTICAL CHEMISTRY, ELSEVIER, AMSTERDAM, NL, vol. 29, no. 5, 1 May 2010 (2010-05-01), pages 409 - 418, XP027006132, ISSN: 0165-9936, [retrieved on 20100220] *
AICARDI: "Disease of the nervous system in childhood.", 1998, CAMBRIDGE UNIVERSITY PRESS
ANDREWS, BIOCHEM. PHARMACOL., vol. 59, 2000, pages 95 - 104
AUSUBEL, F. M. ET AL.: "Current Protocols in Molecular Biology", 1995, JOHN WILEY & SONS
B. ROE; J. CRABTREE; A. KAHN: "DNA Isolation and Sequencing: Essential Techniques", 1996, JOHN WILEY & SONS
BAIRD ET AL., BIOCHEM J, vol. 394, 2006, pages 275 - 283
BAIRD ET AL., BIOCHEM J., vol. 394, 15 February 2006 (2006-02-15), pages 275 - 83
BAUM ET AL., CLIN CHIM ACTA, vol. 4, 1950, pages 4530
BIFFI ET AL., CLINICAL GENETICS, vol. 74, 2008, pages 349 - 357
BIFFI ET AL., J CLIN. INVEST., vol. 116, 2006, pages 3070 - 3082
BIFFI ET AL., J. CLIN. INVEST., vol. 113, 2004, pages 1118 - 1129
BIFFI. ET AL., CLINICAL GENETICS, vol. 74, 2008, pages 349 - 357
BOOT ET AL., EXPERT REV PROTEOMICS, vol. 6, 2009, pages 411 - 419
CAI ET AL., TOXICOL. LETT., vol. 146, 2004, pages 217 - 226
CAPDEVILA M ET AL: "State-of-the-art of metallothioneins at the beginning of the 21st century", COORDINATION CHEMISTRY REVIEWS, ELSEVIER SCIENCE, AMSTERDAM, NL, vol. 256, no. 1, 9 July 2011 (2011-07-09), pages 46 - 62, XP028124063, ISSN: 0010-8545, [retrieved on 20110719], DOI: 10.1016/J.CCR.2011.07.006 *
CESANI ET AL., HUM MUTAT, vol. 30, 2009, pages E936 - 945
CHIMIENTI ET AL., FREE RADICALS BIOL. MED., vol. 31, 2001, pages 1179 - 1190
CHUNG ET AL., JOURNAL OF NEUROCHEMISTRY, vol. 88, 2004, pages 454 - 461
CLARKE ET AL., MOLECULAR GENETICS AND METABOLISM, 2012
COMABELLA ET AL., JOURNAL OF NEUROIMMUNOLOGY, vol. 158, 2005, pages 231 - 239
CONSONNI ET AL., MOL CELL NEUROSCI, vol. 48, 2011, pages 151 - 160
D. M. J. LILLEY; J. E. DAHLBERG: "Methods of Enzymoiogy: DNA Structure Part A: Synthesis and Physical Analysis of DNA Methods in Enzymology", 1992, ACADEMIC PRESS
E. M. SHEVACH; W. STROBER: "Current Protocols in Immunology", 1992, JOHN WILEY & SONS
EBADI ET AL., BRAIN RESEARCH, vol. 134, 2005, pages 67 - 75
EDGAR ET AL., NUCLEIC ACIDS RESEARCH, vol. 30, 2002, pages 207 - 210
ESCOLAR ET AL., N. ENGL. J MED., vol. 352, 2005, pages 2069 - 2081
FELDMAN ET AL., BIOCHIM. BIOPHYS. ACTA, vol. 544, 1978, pages 638 - 646
GONG ET AL., EXPERIMENTAL NEUROLOGY, vol. 162, 2000, pages 27 - 36
GRABOWSKI, ADV HUM GENET, vol. 21, 1993, pages 377 - 441
GREGG ET AL., GENOMICS, vol. 91, 2008, pages 22 - 29
HAHN ET AL., EXP. MOL. MED., vol. 33, 2001, pages 32 - 36
HENNECKE; SCHERZER, BIOMARK MED, vol. 2, 2008, pages 41 - 53
HIDALGO ET AL., BRAIN RESEARCH BULLETIN, vol. 55, 2001, pages 133 - 145
IDA ET AL.: "Type 1 Gaucher Disease Patients: Phenotypic Expression and Natural History in Japanese Patients", BLOOD CELLS, MOLECULES AND DISEASES, vol. 24, no. 5, 1984, pages 73 - 81
J. M. POLAK; JAMES O'D. MCGEE: "Situ Hybridization: Principles and Practice", 1984, OXFORD UNIVERSITY PRESS
J. SAMBROOK; E. F. FRITSCH; T. MANIATIS: "Molecular Cloning: A Laboratory Manual", 1989, COL D SPRING HARBOR LABORATORY PRESS
JELLINGER ET AL., JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, vol. 12, 2008, pages 1094 - 1117
KOLODNY; NEUDORFER: "Metachromatic Leukodistrophy and Multiple Sulfatase Deficiency: Sulfatide Lipidosis.", 2003, HEINEMANN
LEE ET AL., GLIA, vol. 58, no. 10, August 2010 (2010-08-01), pages 186 - 96
LEE SOOK-JEONG ET AL: "Roles of zinc and metallothionein-3 in oxidative stress-induced lysosomal dysfunction, cell death, and autophagy in neurons and astrocytes", MOLECULAR BRAIN, BIOMED CENTRAL LTD, LONDON UK, vol. 3, no. 1, 26 October 2010 (2010-10-26), pages 30, XP021083321, ISSN: 1756-6606, DOI: 10.1186/1756-6606-3-30 *
LIPINSKI ET AL., PNAS, vol. 107, 2010, pages 14164 - 14169
MATZNER ET AL., HUM MOL GENET, vol. 14, 2005, pages 1139 - 1152
MATZNER ET AL., MOL THER, vol. 17, 2009, pages 600 - 606
MONICOU ET AL., ANAL CHEM, vol. 82, 2010, pages 6947 - 57
RANSOHOFF, NATURE REVIEWS, vol. 4, 2004, pages 309 - 314
SCHERZER ET AL., ARCH NEUROL, vol. 61, 2004, pages 1200 - 1205
SCHERZER ET AL., PNAS, vol. 104, 2007, pages 955 - 960
SCHERZER ET AL., PNAS, vol. 105, 2008, pages 10907 - 10912
SCHERZER ET AL., PROC NATL ACAD SCI USA, vol. 104, 2007, pages 955 - 960
SCHIFFMANN ET AL., CLIN JAM SOC NEPHROL, vol. 5, 2010, pages 360 - 364
SETTEMBRE ET AL., HUM MOL GENET, vol. 17, 2008, pages 119 - 129
SHI ET AL., NAT BIOTECHNOL, vol. 24, 2006, pages 1151 - 1161
SUMNER ET AL., NEUROLOGY, vol. 66, 2006, pages 1067 - 1073
TIBSHIRANI ET AL., DIAGNOSIS PROC NATL ACAD SCI USA, vol. 99, 2002, pages 6567 - 6572
TIBSHIRANI, PROC NATL ACAD SCI USA, vol. 99, 2002, pages 6567 - 6572
TUSHER ET AL., PNAS, vol. 98, 2001, pages 5116 - 5121
VISIGALLI ET AL., NEUROBIOLOGY OF DISEASE, vol. 34, 2009, pages 51 - 62
VISIGALLI ET AL., NEUROBIOLOGY OF THE DISEASE, vol. 34, 2009, pages 51 - 62
VOGT ET AL., ANNALS OF NEUROLOGY, vol. 53, 2003, pages 819 - 822
VON FIGURA; JAEKEN: "The Metabolic and Molecular Bases of Inherited Diseases", vol. 3, 2001, article "Metachromatic Leukodystrophy", pages: 3695 - 3724
WANG ET AL., J. PHARMACOL. EXP. THER., vol. 298, 2001, pages 461 - 468
ZHANG ET AL., HUMAN MOLECULAR GENETICS, vol. 3, no. 1, 1994, pages 139 - 145

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