US20130345287A1 - Methods of analysis of polymorphisms and uses thereof

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US20130345287A1

Publication number: US20130345287A1
Application number: US13/903,913
Authority: US
Inventors: Robert Peter Young
Original assignee: Synergenz Bioscience Ltd
Current assignee: Synergenz Bioscience Ltd
Priority date: 2005-05-20
Filing date: 2013-05-28
Publication date: 2013-12-26
Also published as: AU2006248189A1; US20110182872A1; WO2006123943A1; EP1888779A1; US7933722B2; US20060275808A1; EP1888779A4

The present invention provides methods for the assessment of diseases that result from the combined or interactive effects of two or more genetic variants, and in particular for diagnosing risk of developing such diseases in subjects using an analysis of genetic polymorphisms. Methods for the derivation of a net score indicative of a subject's risk of developing a disease are provided.

RELATED APPLICATION

This application claims priority to New Zealand Application Nos. 540249, filed May 20, 2005 and 514842, filed Aug. 15, 2005, both of which are incorporated by reference in their entireties.

FIELD OF THE INVENTION

The present invention is concerned with methods for the assessment of diseases that result from the combined or interactive results of two or more genetic variants, and in particular for diagnosing risk developing such diseases in subjects using an analysis of genetic polymorphisms.

BACKGROUND OF THE INVENTION

Diseases that results from the combined or interactive effects of two or more genetic variants, with or without environmental factors, are called complex diseases and include cancer, coronary artery disease, diabetes, stroke, and chronic obstructive pulmonary disease (COPD). Although combining non-genetic risk factors to determine a risk level of outcome has been in applied to coronary artery disease, (by combining individual factors such as blood pressure, gender, fasting cholesterol, and smoking status), there are no such methods in combining the effects of multiple genetic factors with non-genetic factors. There is a growing realization that the complex diseases, for which examples are given above, may result from the combined effects of common genetic variants or polymorphisms rather than mutations which are rare (believed to be present in less than 1% of the general population). Moreover, these relatively common polymorphisms can confer with susceptibility and/or protective effects on the development of these diseases. In addition, the likelihood that these polymorphisms are actually expressed (termed penetrance) as a disease or clinical manifestation requires a quantum of environmental exposure before such a genetic tendency can be clinically detected.

SUMMARY OF THE INVENTION

Recent studies have identified a number of genetic variants or polymorphisms that confer susceptibility to protection from COPD, occupational COPD (OCODP), and lung cancer. The biological basis of just how these polymorphisms interact or combined to determine risk remains unclear.
Surprisingly, it has now been found that an assessment approach which determines a subject's net score following the balancing of the number of polymorphisms associated with protection from a disease against the number of polymorphisms associated with susceptibility to that disease present in the subject is indicative of that subject's risk quotient. Furthermore, it has presently been determined that this approach is widely applicable, on a disease-by-disease basis.
It is broadly to this approach to risk assessment that the present invention is directed.
Accordingly, in a first aspect, the present invention provides a method of assessing a subject's risk of developing a disease which includes:

- analysing a biological sample from said subject for the presence or absence of protective polymorphisms and for the presence or absence of susceptibility polymorphisms, wherein said protective and susceptibility polymorphisms are associated with said disease;
- assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;
- calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;
- wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.

The value assigned to each protective polymorphism can be the same or can be different. The value assigned to each susceptibility polymorphism can be the same or can be different, with either each protective polymorphism having a negative value and each susceptibility polymorphism having a positive value, or vice versa. When the disease is a lung disease, the protective polymorphisms analysed can be selected from one or more of the group consisting of: +760GG or +760CG within the gene encoding superoxide dismutase 3 (SOD3); −1296TT within the promoter of the gene encoding tissue inhibitor of metalloproteinase 3 (TIMP3); CC (homozygous P allele) within codon 10 of the gene encoding transforming growth factor beta (TGFβ); 2G2G within the promoter of the gene encoding metalloproteinase 1 (MMP1); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.
Linkage disequilibrium is a phenomenon in genetics whereby two or more mutations or polymorphisms are in such close genetic proximit that they are co-inherited. This means that in genotyping, detection of one polymorphism as present implies the presence of the other. (Reich, D. E. et al. Linkage disequilibrium in the human genome. Nature 411:199-204. (2001), herein incorporated by reference in its entirety).
Preferably, all polymorphisms of the group are analysed.
Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of: −82AA within the promoter of the gene encoding human macrophase elastase (MMP12); −1562CT or −1562TT within the promoter of the gene encoding metalloproteinase 9 (MMP9); 1237AG or 1237AA (Tt or tt allele genotypes) within the 3′ region of the gene encoding a1-antitrypsin (a1AT); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
In one embodiment each protective polymorphism is assigned a value of −1 and each susceptibility polymorphism is assigned a value of +1.
In another embodiment each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of −1.
When the disease is COPD, the protective polymorphisms analysed can be selected from one or more of the group consisting of: −765 CC or CG in the promoter of the gene encoding cyclooxygenase 2 (COX2); Arg 130 Gln AA in the gene encoding Interleukin-13 (IL-13) Asp 298 Glu TT in the gene encoding nitric oxide synthase 3 (NOS3); Lys 420 Thr AA or AC in the gene encoding vitamin binding protein (VDBP); Glu 416 Asp TT or TG in the gene encoding VDBP; Ile 105 Val AA in the gene encoding glutathione S-transferase (GSTP1); MS in the gene encoding a1-antitrypsin (a1AT); the +489 GG geneotpye in the gene encoding Tissue Necrosis factor a (TNFa); the −308 GG geneotype in the gene encoding TNFa; the C89Y AA or AG geneotype in the gene encoding SMAD3; the 161 GG genotype in the gene encoding Mannose binding lectin 2 (MBL2); the −1903 AA genotype in the gene encoding Chymase 1 (CMA1); the Arg 197 Gln AA genotype in the gene encoding N-Acetyl transferase 2 (NAT2); the His 139 Arg GG genotype in the gene encoding Microsomal epoxide hydrolase (MEH); the −366 AA or AG genotype in the gene encoding 5 Lipo-oxgenase (ALOX5); the HOM T2437C TT genotype in the gene encoding Heat Shock Protein 70 (HPS 70); the exon 1+49 CT or TT genotype in the gene encoding Elafin; the Gln 27 Glu GG genotype in the gene encoding β2 Adrenergic receptor (ADBR); the −1607 1G1G or 1G2G genotype in the promoter of the gene encoding Matrix Metalloproteinase 1 (MMP1); or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms. Preferably, all polymorphisms of the group are analysed.
Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of: Arg 16 Gly GG in the gene encoding β2-adrenoreceptor (ADRB2); 105 AA in the gene encoding Interleukin-18 (IL-18); −133 CC in the promoter of the gene encoding IL-18; −675 5G5G in the promoter of the gene encoding plasminogen activator inhibitor 1 (PAI-1); −1055 TT in the promoter of the gene encoding IL-13; 874 TT in the gene encoding interferon gamma (IFN?); the +489 AA or AG genotype in the gene encoding TNFa; the −308 AA or AG genotype in the gene encoding TNFa; the C89Y GG genotype in the gene encoding SMAD3; the E469K GG genotype in the gene encoding Intracellular Adhesion molecule 1 (ICAM1); the Gly 881 Arg GC or CC genotype in the gene encoding Capase (NOD2); the −511 GG genotype in the gene encoding IL1B; the Tyr 113 His TT genotype in the gene encoding MEH; the −366 GG genotype in the gene encoding ALOX5; the HOM T2437C CC or CT genotype in the gene encoding HSP 70; the +13924 AA genotype in the gene encoding Chloride Channel Calcium-activated 1 (CLCA1); the −159 CC genotype in the gene encoding Monocyte differentiation antigen CD-14 (CD-14); or one or polymorphisms in linkage disequilibrium with one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
In one embodiment each protective polymorphism is assigned a value of −1 and each susceptibility polymorphism is assigned a value of +1.
In one embodiment each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of −1.
When the disease is OCOPD, the protective polymorphisms analysed can be selected from one or more of the group consisting of: −765 CC or CG in the promoter of the gene encoding COX2; −251 AA In the Promoter of the gene encoding interleukin-8 (IL-8); Lys 420 Thr AA in the gene encoding VDBP; Glu 416 Asp TT or TG in the gene encoding VDBP; exon 3 T/C RR in the gene encoding microsomal epoxide hydrolase (MEH); Arg 312 Gln AG or GG in the gene encoding SOD3; MS or SS in the gene encoding a1AT; Asp 299 AG or GG in the gene encoding toll-like receptor 4 (TLR4); Gln 27 Glu CC in the gene encoding ADRB2; −518 AA in the gene encoding IL-11; Asp 298 Glu TT in the gene encoding NOS3; or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of: −765 GG in the promoter of the gene encoding COX2; 105 AA in the gene encoding IL-18; −133 CC in the promoter of the gene encoding IL-18; −675 5G5G in the promoter of the gene encoding PAI-1; Lys 420 Thr CC in the gene encoding VDBP; Glu 416 Asp GG in the gene encoding VDBP; Ile 105 Val GG in the gene encoding GSTP1; Arg 312 Gln AA in the gene encoding SOD3; −1055 TT in the promoter of the gene encoding IL-13; 3′ 1237 Tt or tt in the gene encoding a1AT; −1607 2G2G in the promoter of the gene encoding MMP1; or one or more polymorphisms in linkage disequilibrium with one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
In one embodiment each protective polymorphism is assigned a value of −1 and each susceptibility polymorphism is assigned a value of +1.
In one embodiment each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of −1.
When the disease is lung cancer, the protective polymorphisms analysed can be selected from one or more of the group consisting of: the Asp 298 Glu TT genotype in the gene encoding NOS3; the Arg 312 Gln CG or GG genotype in the gene encoding SOD3; the Asn 357 Ser AG or GG genotype in the gene encoding MMP12; the 105 AC or CC genotype in the gene encoding IL-18; the −133 CG or GG genotype in the gene encoding IL-18; the −765 CC or CG genotype in the promoter of the gene encoding COX2; the −221 TT genotype in the gene encoding Mucin 5AC (MUC5AC); the intron 1 C/T TT genotype in the gene encoding Arginase 1 (Arg1); the Leu252Val GG genotype in the gene encoding Insulin-like growth factor II receptor (IGF2R); the −1082 genotype in the gene encoding Interleukin 10 (IL-10); the −251 AA genotype in the gene encoding Interleukin 8 (IL-8); the Arg 399 Gln AA genotype in the X-ray repair complementing defective in Chinese hamster 1 (XRCC1) gene; the A870G GG genotype in the gene encoding cyclin D (CCND1); the −751 GG genotype in the promoter of the xeroderma pigmentosum complementation group D (XPD) gene; the Ile 462 Val AG or GG genotype in the gene encoding cytochrome P450 1A1 (CYP1A1); the Ser 326 Cys GG genotype in the gene encoding 8-Oxoguanine DNA glycolase (OGG1); the Phe 257 Ser CC genotype in the gene encoding REV1; or one or more polymorphisms in linkage disequilibrium with any one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
Preferably, the susceptibility polymorphisms analysed are selected from one or more of the group consisting of: the −786 TT genotype in the promoter of the gene encoding NOS3; the Ala 15 Thr GG genotype in the gene encoding anti-chymotrypsin (ACT); the 105 AA genotype in the gene encoding IL-18; the −133 CC genotype in the promoter of the gene encoding IL-18; the 874 AA genotype in the gene encoding IFN?; the −765 GG genotype in the promoter of the gene encoding COX2; the −447 CC or GC genotype in the gene encoding Connective tissue growth factor (CTFG); and the +161 AA or AG genotype in the gene encoding MBL2; −511 GG genotype in the gene encoding IL-1B; the A-670G AA genotype in the gene encoding FAS (Apo-1/CD95); the Arg 197 Gln GG genotype in the gene encoding N-acetyltransferase 2 (NAT2); the Ile462 Val AA genotype in the gene encoding CYP1A1; the 1019 G/C Pst I CC or CG genotype in the gene encoding cytochrome P450 2E1 (CYP2E1); the C/T Rsa I TT or TC genotype in the gene encoding CYP2E1; the GSTM null genotype in the gene encoding GSTM; the −1607 2G/2G genotype in the promoter of the gene encoding MMP1; the Gln 185 Glu CC genotype in the gene encoding Nibrin (NBS1); the Asp 148 Glu GG genotype in the gene encoding Apex nuclease (APE1); or one or more polymorphisms in linkage disequilibrium with any one or more of these polymorphisms.
Preferably, all polymorphisms of the group are analysed.
In one embodiment each protective polymorphism is assigned a value of −1 and each susceptibility polymorphism is assigned a value of +1.
In one embodiment each protective polymorphism is assigned a value of +1 and each susceptibility polymorphism is assigned a value of −1.
In various embodiments the subject is or has been a smoker.
Preferably, the methods of the invention are performed in conjunction with an analysis of one or more risk factors, including one or more epidemiological risk factors, associated with the risk of developing a lung disease including COPD, emphysema, OCOPD, and lung cancer. Such epidemiological risk factors include but are not limited to smoking or exposure to tobacco smoke, age, sex, and familial history.
In another aspect, the invention provides a method of determining a subject's risk of developing a disease, said method comprising:

- obtaining the result of one or more analyses of a sample from said subject to determine the presence or absence of protective polymorphisms and the presence or absence of susceptibility polymorphisms, and wherein said protective and susceptibility polymorphisms are associated with the disease;
- assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;
- calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;
- wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.

In a further aspect the present invention provides a method for assessing the risk of a subject developing a disease which includes

- determining a net score for said subject in accordance with the methods of the invention described above, in combination with a score based on the presence or absence of one or more epidemiological risk factors,
- wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased predisposition and/or susceptibility to said disease.

In another aspect, the present invention provides a kit for assessing a subject's risk of developing a disease, said kit comprising a means of analysing a sample from said subject for the presence or absence of one or more protective polymorphisms and one or more susceptibility polymorphisms as described herein.
In yet a further aspect, the present invention provides a method of prophylactic or therapeutic intervention in relation to a subject having a net susceptibility score for a disease as determined by a method as defined above which includes the steps of communicating to said subject said net susceptibility score, and advising on changes to the subject's lifestyle that could reduce the risk of developing said disease.
In still a further aspect, the present invention provides a method of treatment of a subject to decrease the risk of developing a disease through alteration of the net score for said subject as determined by a method as defined above, wherein said method of treatment includes reversing, genotypically or phenotypically, the presence and/or functional effect of one or more susceptibility polymorphisms associated with said disease; and/or replicating and/or mimicking, genotypically or phenotypically, the presence and/or functional effect of one or more protective polymorphisms associated with said disease.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1: depicts a graph showing combined frequencies of the presence or absence of selected protective genotypes in the COPD subjects and in resistant smokers.

FIG. 2: depicts a graph showing net scores for protective and susceptibility polymorphisms in COPD subjects.

FIG. 3: depicts a graph showing net scores for protective and susceptibility polymorphisms in OCOPD subjects.

FIG. 4: depicts a graph showing net scores for protective and susceptibility polymorphisms in subjects with lung cancer.

FIG. 5: depicts a graph showing net scored for protective and susceptibility polymorphisms in subject with lung cancer.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

There is a need for a method for assessing a subject's risk of developing a disease using genetic (and optionally non-genetic) risk factors. In some embodiments, it is an object of the present invention to go some way towards meeting this need and/or to provide the public with a useful choice.
The present invention is directed to methods for the assessment of the genetic risk quotient of a particular subject with respect to a particular disease. The methods rely upon the recognition that for many (if not all) diseases there exist genetic polymorphisms which fall into two categories—namely those indicative of a reduced risk of developing a particular disease (which can be termed “protective polymorphisms” or “protective SNPs”) and those indicative of an increased risk of developing a particular disease (which can be termed “susceptibility polymorphisms” or “susceptibility SNPs”).
As used herein, the phase “risk of developing [a] disease” means the likelihood that a subject to which the risk applies will develop the disease, and includes predisposition to, and potential onset of the disease. Accordingly, the phase “increased risk of developing [a] disease” means that a subject having such an increased risk possesses an hereditary inclination or tendency to develop the disease. This does not mean that such a person will actually develop the disease at any time, merely that he or she has a greater likelihood of developing the disease compared to the general population of individuals that either does not possess a polymorphism associated with increased disease risk, or does possess a polymorphism associated with decreased disease risk. Subjects with an increased risk of developing the disease include those with a predisposition to the disease, for example in the case of COPD, a tendency or prediliction regardless of their lung function at the time of assessment, for example, a subject who is genetically inclined to COPD but who has normal lung function, those at potential risk, for example in the case of COPD, subjects with a tendency to mildly reduced lung function who are likely to go on to suffer COPD if they keep smoking, and subjects with potential onset of the disease, for example in the case of COPD, subjects who have a tendency to poor lung function on spirometry etc., consistent with COPD at the time of assessment.
Similarly, the phrase “decreased risk of developing [a] disease” means that a subject having such a decreased risk possesses an hereditary disinclination or reduced tendency to develop the disease. This does not mean that such a person will not develop the disease at any time, merely that he or she has a decreased likelihood of developing the disease compared to the general population of individuals that either does not possess one or more polymorphisms associated with increased disease risk, or does not possess a polymorphism associated with decreased disease risk.
It will be understood that in the context of the present invention the term “polymorphism” means the occurrence together in the same population at a rate greater than that attributable to random mutation (usually greater than 1%) of two or more alternate forms (such as alleles or genetic markers) of a chromosomal locus that differ in nucleotide sequence or have variable numbers of repeated nucleotide units. See www.ornl.gov/sci/techresources/Human_Genome/publicat/97pr/09gloss.html#p. Accordingly, the term “polymorphisms” is used herein contemplates genetic variations, including single nucleotide substitutions, insertions and deletions of nucleotides, repetitive sequences (such as microsatellites), and the total or partial absence of genes (eg. null mutations). As used herein, the term “polymorphisms” also includes genotypes and haplotypes. A genotype is the genetic composition at a specific locus or set of loci. A haplotype is a set of closely linked genetic markers present on one chromosome which are not easily separable by recombination, tend to be inherited together, and can be in linkage disequilibrium. A haplotype can be identified by patterns of polymorphisms such as SNPs. Similarly, the term “single nucleotide polymorphism” or “SNP” in the context of the present invention includes single base nucleotide substitutions and short deletion and insertion polymorphisms. It will further be understood that the term “disease” is used herein in its widest possible sense, and includes conditions which can be considered disorders and/or illnesses which have a genetic basis or to which the genetic makeup of the subject contributes.
Using case-control studies, the frequencies of several genetic variants (polymorphisms) of candidate genes have been compared in disease sufferers, for example, in chronic obstructive pulmonary disease (COPD) sufferers, in occupational chronic obstructive pulmonary disease (OCOPD) sufferers, and in lung cancer sufferers, and in control subjects not suffering from the relevant disease, for example smokers without lung cancer and with normal lung function. The majority of these candidate genes have confirmed (or likely) functional effects on gene expression or protein function.
In various specific embodiments, the frequencies of polymorphisms between blood donor controls, resistant subjects and those with COPD, the frequencies of polymorphisms between blood donor controls, resistant subjects and those with OCOPD, and the frequencies of polymorphisms between blood donor controls, resistant subjects and those with lung cancer, have been compared. This has resulted in both protective and susceptibility polymorphisms being identified for each disease.
The surprising finding relevant to this invention is that a combined analysis of protective and susceptibility polymorphisms discriminatory for a given disease yields a result that is indicative of that subject's risk quotient for that disease. This approach is widely applicable, on a disease-by-disease basis.
The present invention identifies methods of assessing the risk of a subject developing a disease which includes determining in said subject the presence or absence of protective and susceptibility polymorphisms associated with said disease. A net score for said subject is derived, said score representing the balance between the combined value of the protective polymorphisms present in said subject and the combined value of the susceptibility polymorphisms present in said subject. A net protective score is predictive of a reduced risk of developing said disease, and a net susceptibility score is predictive of an increased risk of developing said disease.
Within each category (protective polymorphisms, susceptibility polymorphisms, respectively) the polymorphisms can each be assigned the same value. For example, in the analyses presented in the Examples herein, each protective polymorphism associated with a given disease is assigned a value of +1, and each susceptibility polymorphism is assigned a value of −1. Alternatively, polymorphisms discriminatory for a disease within the same category can each be assigned a different value to reflect their discriminatory value for said disease. For example, a polymorphism highly discriminatory of risk of developing a disease can be assigned a high weighting, for example a polymorphism with a high Odd's ratio can be considered highly discriminatory of disease, and can be assigned a high weighting.
Accordingly, in a first aspect, the present invention provides a method of assessing a subject's risk of developing a disease which includes:
analsying a biological sample from said subject for the presence or absence of protective polymorphisms and for the presence or absence of susceptibility polymorphisms, wherein said protective and susceptibility polymorphisms are associated with said disease;
assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;
calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphism present in the subject sample;
wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.
The subject sample can have already been analysed for the presence or absence of one or more protective or susceptibility polymorphisms, and the method includes the step of

- assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;

calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphisms and the combined value of the susceptibility polymorphisms present in the subject sample;
wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.
In one embodiment described in Example 1, 17 susceptibility genetic polymorphisms and 19 protective genetic polymorphisms identified as discriminatory for COPD were analysed using methods of the invention. These analyses can be used to determined the risk quotient of any subject for COPD, and in particular to identify subjects at greater risk of developing lung cancer.
In another embodiment described herein in Example 2, 11 susceptibility genetic polymorphisms and 11 protective genetic polymorphisms identified as discriminatory for OCOPD are analysed using methods of the invention. These analyses can be determined the risk quotient of any subject for OCOPD, and in particular to identify subjects at greater risk of developing OCOPD.
In a further embodiment described herein in Example 3, 19 susceptibility genetic polymorphisms and 17 protective genetic polymorphisms identified as discriminatory for lung cancer are analysed using methods of the invention. These analyses can be used to determine the risk quotient of any subject for lung cancer, and in particular to identify subjects at greater risk of developing lung cancer.
Susceptibility and protective polymorphisms can readily be identified for other diseases using approaches similar to those described in the Examples, as well as in PCT International Application No. PCT/NZ02/00106 (published as WO 02/099134 and herein incorporated by reference in its entirety) via which four susceptibility and three protective polymorphisms discriminatory for lung disease were identified.
The one or more polymorphisms can be detected directly or by detection of one or more polymorphisms which are in linkage disequilibrium with said one or more polymorphisms. As discussed above, linkage disequilibrium is a phenomenon in genetics whereby two or more mutations or polymorphisms are in such close genetic proximity that they are co-inherited. This means that in genotyping, detection of one polymorphism as present implies the presence of the other. (Reich D E et al; Linkage disequilibrium in the human genome, Nature 2001, 411:199-204.)
Examples of polymorphisms reported to be in linkage disequilibrium are presented herein, and include the Interleukin-18 −133 C/G and 105 A/C polymorphisms, and the Vitamin D binding protein Glu 416 Asp and Lys 420 Thr polymorphisms, as shown below.


		rs	Alleles	LD between	Phenotype
Gene	SNPs	numbers	in LD	alleles	in COPD

Interleukin-18	IL18 −133 C/G	rs360721	C allele	Strong LD	CC susceptible
	IL18 105 A/C	rs549908	A allele		AA susceptible
Vitamin D	VDBP Lys 420 Thr	rs4588	A allele	Strong LD	AA/AC protective
binding protein	VDBP Glu 416 Asp	rs7041	T allele		TT/TG protective

It will be apparent that polymorphisms in linkage disequilibrium with one or more other polymorphism associated with increased or decreased risk of developing COPD, emphysema, or both COPD and emphysema will also provide utility as biomarkers for risk of developing COPD, emphysema, or both COPD and emphysema. The data presented herein shows that the frequency for SNPs in linkage disequilibrium is very similar. Accordingly, these genetically linked SNPs can be utilized in combined polymorphism analyses to derive a level of risk comparable to that calculated from the original SNP.
It will therefore be apparent that one or more polymorphisms in linkage disequilibrium with the polymorphisms specified herein can be identified, for example, using public data bases. Examples of such polymorphisms reported to be in linkage disequilibrium with the polymorphisms specified herein are presented herein in Table 21.
The methods of the invention are primarily reliant on genetic information such as that derived from methods suitable to the detection and identification of single nucleotide polymorphisms (SNPs) associated with the specific disease for which a risk assessment is desired. In some embodiments, a SNP is a single base change or point mutation resulting in genetic variation between individuals. SNPs occur in the human genome approximately once every 100 to 300 bases, and can occur in coding or non-coding regions. Due to the redundancy of the genetic code, a SNP in the coding region may or may not change the amino acid sequence of a protein product. A SNP in a non-coding region can, for example, alter gene expression by, for example, modifying control regions such as promoters, transcription factor binding sites, processing sites, ribosomal binding sites, and affect gene transcription, processing, and translation.
SNPs can facilitate large-scale association genetics studies, and there has recently been great interest in SNP discovery and detection. SNPs show great promise as markers for a number of phenotypic traits (including latent traits), such as for example, disease propensity and severity, wellness propensity, and drug responsiveness including, for example, susceptibility to adverse drug reactions. Knowledge of the association of a particular SNP with a phenotpyic trait, coupled with the knowledge of whether an individual has said particular SNP, can enable the targeting of diagnostic, preventative and therapeutic applications to allow better disease management, to enhance understanding of disease states and to ultimately facilitate the discovery of more effective treatments, such as personalised treatment regimens.
Indeed, a number of databases have been constructed of known SNPs, and for some such SNPs, the biological effect associated with a SNP. For example, the NCBI SNP database “dbSNP” is incorporated into NCBI's Entrez system and can be queried using the same approach as the other Entrez databases such as PubMed and GenBank. This database has records for over 1.5 million SNPs mapped onto the human genome sequence. Each dbSNP entry includes the sequence context of the polymorphism (i.e., the surrounding sequence), the occurrence frequency of the polymorphism (by population or individual), and the experimental method(s), protocols, and conditions used to assay the variation, and can include information associating a SNP with a particular phenotypic trait.
At least in part because of the potential impact on health and wellness, there has been and continues to be a great deal of effort to develop methods that reliably and rapidly identify SNPs. This is no trivial task, at least in part because of the complexity of human genomic DNA, with a haploid genome of 3×10⁹base pairs, and the associated sensitivity and discriminatory requirements.
Genotyping approaches to detect SNPs well-known in the art include DNA sequencing, methods that require allele specific hybridization of primers or problems, allele specific incorporation of nucleotides to primers bound close to or adjacent to the polymorphisms (often referred to as “single base extension”, or “minisequencing”), allele-specific ligation (joining) of oligonucleotides (ligation chain reaction or ligation padlock probes), allele-specific cleavage or oligonucleotides or PCR products by restriction enzymes (restriction fragment length polymorphisms analysis or RFLP) or chemical or other agents, resolution of allele-dependent differences in electrophoretic or chromatographic mobilities, by structure specific enzymes including invasive structure specific enzymes, or mass spectrometry. Analysis of amino acid variation is also possible where the SNP lies in a coding region and results in an amino acid change.
DNA sequencing allows the direct determination and identification of SNPs. The benefits in specificity and accuracy are generally outweighed for screening purposes by the difficulties inherent in whole genome, or even targeted subgenome, sequencing.
Mini-sequencing involves allowing a primer to hybridize to the DNA sequence adjacent to the SNP site on the test sample under investigation. The primer is extended by one nucleotide using all four differentially tagged fluorescent dideoxynucleotides (A, C, G, or T), and a DNA polymerase. Only one of the four nucleotides (homozygous case) or two of the four nucleotides (heterozygous case) is incorporated. The base that is incorporated is complementary to the nucleotide at the SNP position.
A number of methods currently used for SNP detection involve site-specific and/or allele-specific hybridisation (Matsuzaki, H. et al. Genome Res. 14:414-425 (2004); Matsuzaki, H. et al. Nat. Methods 1:109-111 (2004); Sethi, A. A. et al. Clin. Chem. 50(2):443-446 (2004), each of the foregoing which is herein incorporated by reference in its entirety). These methods are largely reliant on the discriminatory binding of oligonucleotides to target sequences containing the SNP of interest. The techniques of Affymetrix (Santa Clara, Calif.) and Nanogen Inc. (San Diego, Calif.) are particularly well-known, and utilize the fact that DNA duplexes containing single base mismatches are much less stable than duplexes that are perfectly base-paired. The presence of a matched duplex is detected by fluorescence.
The majority of methods to detect or identify SNPs by site-specific hybridisation require target amplification by methods such as PCR to increase sensitivity and specificity (see, for example U.S. Pat. No. 5,679,524, PCT publication WO 98/59066, PCT publication WO 95/12607, each of the foregoing which is herein incorporated by reference in its entirety). US Application 20050059030 (incorporated herein in its entirety) describes a method for detecting a single nucleotide polymorphism in total human DNA without prior amplification or complexity reduction to selectively enrich for the target sequence, and without the aid of any enzymatic reaction. The method utilises a single-step hybridization involving two hybridization events: hybridization of a first portion of the target sequence to a capture probe, and hybridization of a second portion of said target sequence to a detection probe. Both hybridization events happen in the same reaction, and the order in which hybridisation occurs is not critical.
US Application 20050042608 (herein incorporated by reference in its entirety) describes a modification of the method of electrochemical detection of nucleic acid hybridization of Thorp et al. (U.S. Pat. No. 5,871,918, herein incorporated by reference in its entirety). Briefly, capture probes are designed, each of which has a different SNP base and a sequence of probe bases on each side of the SNP base. The probe bases are complementary to the corresponding target sequence adjacent to the SNP site. Each capture probe is immobilized on a different electrode having a non-conductive outer layer on a conductive working surface of a substrate. The extent of hybridization between each capture probe and the nucleic acid target is detected by detecting the oxidation-reduction reaction at each electrode, utilizing a transition metal complex. These differences in the oxidation rates at the different electrodes are used to determine whether the selected nucleic acid target has a single nucleotide polymorphism at the selected SNP site.
The technique of Lynx Therapeutics (Hayward, Calif.) using MEGATYPE™ technology can genotype very large numbers of SNPs simultaneously from small or large pools of genomic material. This technology uses fluorescently labeled probes and compared the collected genomes of two populations, enabling detection and recovery of DNA fragments spanning SNPs that distinguish the two populations, without requiring prior SNP mapping or knowledge.
A number of other methods for detecting and identifying SNPs exist. These include the use of mass spectrometry, for example, to measure probes that hybridize to the SNP (Ross, P. L. et al. Discrimination of single-nucleotide polymorphisms in human DNA using peptide nucleic acid probes detected by MALDI-TOF mass spectrometry. Anal. Chem. 69, 4197-4202 (1997), herein incorporated by reference in its entirety). This technique varies in how rapidly it can be performed, from a few samples per day to a high throughput of 40,000 SNPs per day, using mass code tags. A preferred example is the use of mass spectrometric determination of a nucleic acid sequence which includes the polymorphisms of the invention, for example, which includes the promoter of the COX2 gene of a complementary sequence. Such mass spectrometric methods are known to those skilled in the art, and the genotyping methods of the invention are amenable to adaptations for the mass spectrometric detection of the polymorphisms of the invention, for example, the COX2 promoter polymorphisms of the invention.
SNPs can also be determined by ligation-bit analysis. This analysis requires two primers that hybridize to a target with a one nucleotide gap between the primers. Each of the four nucleotides is added to a separate reaction mixture containing DNA polymerase, ligase, target DNA and the primers. The polymerase adds a nucleotide to the 3′end of the first primer that is complementary to the SNP, and the ligase then ligates the two adjacent primers together. Upon heating of the sample, if ligation has occurred, the now larger primer will remain hybridized and a signal, for example, fluorescence, can be detected. A further discussion of these methods can be found in U.S. Pat. Nos. 5,919,626; 5,945,283; 5,242,794; and 5,952,174 (each of the foregoing which is herein incorporated by reference in its entirety).
U.S. Pat. No. 6,821,733 (herein incorporated by reference in its entirety) described methods to detect differences in the sequence of two nucleic acid molecules that includes the steps of: contacting two nucleic acids under conditions that allow the formation of a four-way complex and branch migration; contacting the four-way complex with a tracer molecule an a detection molecule under conditions in which the detection molecule is capable of binding the tracer molecule or the four-way complex; and determining binding of the tracer molecule to the detection molecule before and after exposure to the four-way complex. Competition of the four-way complex with the tracer molecule for binding to the detection molecule indicates a difference between the two nucleic acids.
Protein- and proteomics-based approaches are also suitable for polymorphism detection and analysis. Polymorphisms which result in or are associated with variation in expressed proteins can be detected directly by analysing said proteins. This typically requires separation of the various proteins within a sample, by, for example, gel electrophoresis or HPLC, and identification of said proteins or peptides derived therefrom, for example by NMR or protein sequencing such as chemical sequencing or more prevalently mass spectrometry. Proteomic methodologies are well known in the art, and have great potential for automation. For example, integrated systems, such as the ProteomIQ™ system for Proteome Systems, provide high throughput platforms for proteome analysis combining sample preparation, protein separation, image acquisition and analysis, protein processing, mass spectrometry and bioinformatics technologies.
The majority of proteomic methods of protein identification utilise mass spectrometry, including ion trap mass spectrometry, liquid chromatography (LC) and LC/MSn mass spectrometry, gas chromatography (GC) mass spectroscopy, Fourier transform-ion cyclotron resonance-mass spectrometer (FT-MS), MALDI-TOF mass spectrometry, and ESI mass spectrometry, and their derivatives. Mass spectrometric methods are also useful in the determination of post-translational modification of proteins, such as phosphorylation or glycosylation, an thus have utility in determining polymorphisms that result in or are associated with variation in post-translational modifications of proteins.
Associated technologies are also well known, and include, for example, protein processing devices such as the “Chemical Inkjet Printer” comprising piezoelectric printing technology that allows in situ enzymatic or chemical digestions of protein samples electroblotted from 2-D PAGE gels to membranes by jetting the enzyme or chemical directly onto the selected protein spots (Sloane, A. J. et al. High throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies. Mol Cell Proteomics 1(7):490-9 (2002), herein incorporated by reference in its entirety). After in-situ digestion and incubation of the proteins, the membrane can be placed directly into the mass spectrometer for peptide analysis.
A large number of methods reliant on the conformational variability of nucleic acids have been developed to detect SNPs.
For example, Single Strand Conformational Polymorphism (SSCP, Orita et al., PNAS 86:2766-2770 (1989), herein incorporated by reference in its entirety) is a method reliant on the ability of single-stranded nucleic acids to form secondary structure in solution under certain conditions. The secondary structure depends on the base composition and can be altered by a single nucleotide substitution, causing differences in electrophoretic mobility under nondenaturing conditions. The various polymorphs are typically detected by autoradiography when radioactively labelled, by silver staining of bands, by hybridisation with detectably labelled probe fragments or the use of fluorescent PCR primers which are subsequently detected, for example by an automated DNA sequencer.
Modifications of SSCP are well known in the art, and include the use of differing gel running conditions, such as for example temperature, or the addition of additives, and different gel matrices. Other variations on SSCP are well known to the skilled artisan, including, RNA-SSCP (Gasparini, P. et al. Scanning the first part of the neurofibromatosis type 1 gene by RNA-SSCP: identification of three novel mutations and of two new polymorphisms. Hum Genet. 97(4):492-5 (1996), been incorporated by reference in its entirety), restriction endonuclease fingerprinting-SSCP (Liu, Q. et al. Restriction endonuclease fingerprinting (REF): a sensitive method for screening mutations in long, contiguous segments of DNA. Biotechniques 18(3):470-7 (1995), herein incorporated by reference in its entirety), dideoxy fingerprinting (a hybrid between dideoxy sequencing and SSCP) (Sarkar, G. et al. Dideoxy fingerprinting (ddF): a rapid and efficient screen for the presence of mutations. Genomics 13:441-443 (1992), herein incorporated by reference in its entirety), bi-directional dideoxy fingerprinting (in which the dideoxy termination reaction is performed simultaneously with two opposing primers) (Liu, Q. et al. Bi-directional dideoxy fingerprinting (Bi-ddF): a rapid method for quantitative detection of mutations in genomic regions of 300-600 bp. Hum Mol Genet 5(1):107-14 (1996), herein incorporated by reference in its entirety), and Fluorescent PCR-SSCP (in which PCR products are internally labeled with multiple fluorescent dyes, can be digested with restriction enzymes, followed by SSCP, and analysed on an automated DNA sequencer able to detect the fluorescent dyes) (Makino, R. et al. F-SSCP: fluorescence-based polymerase chain reaction-single-strand conformation polymorphism (PCR-SSCP) analysis. PCR Methods Appl. 2(1)10-13 (1992), herein incorporated by reference in its entirety).
Other methods which utilise the varying mobility of different nucleic acid structures include Denaturing Gradient Gel Electrophoresis (DGGE) (Cariello, N. F. et al. Resolution of a missense mutant in human genomic DNA by denaturing gradient gel electrophoresis and direct sequencing using in vitro DNA amplification: HPRT Munich. Am J Hum Genet. 42(5):726-34 (1988), herein incorporated by reference in its entirety), Temperature Gradient Gel Electrophoresis (TGGE) (Riesner, D. et al. Temperature-gradient gel electrophoresis or the detection of polymorphic DNA and for quantitative polymerase chain reaction. Electrophoresis. 13:632-6 (1992), herein incorporated by reference in is entirety), and Heteroduplex Analysis (HET) (Keen, J. et al. Rapid detection of single base mismatches as heteroduplexes on Hydrolink gels. Trends Genet. 7(1):5 (1991), herein, incorporated by reference in its entirety). Here, variation in the dissociation of double stranded DNA (for example, due to base-pair mismatches) results in a change in electrophoretic mobility. These mobility shifts are used to detect nucleotide variations.
Denaturing High Pressure Liquid Chromatography (HPLC) is yet a further method utilised to detect SNPs, using HPLC methods well-known in the art as an alternative to the separation methods described above (such as gel electrophoresis) to detect, for example, homoduplexes and heteroduplexes which elute from the HPLC column at different rates, thereby enabling detection of mismatch nucleotides and thus SNPs (Giordano, M. et al. Identification by denaturing high-performance liquid chromatography of numerous polymorphisms in a candidate region for multiple sclerosis susceptibility. Genomics 56(3):247-53 (1999), herein incorporated by reference in its entirety).
Yet further methods to detect SNPs rely on the differing susceptibility of single stranded and double stranded nucleic acids to cleavage by various agents, including chemical cleavage agents and nucleolytic enzymes. For example, cleavage of mismatches within RNA:DNA heteroduplexes by RNase A, of heteroduplexes by, for example bacteriophase T4 endonuclease YII or T7 endonuclease I, of the 5′ end of the hairpin loops at the junction between single stranded and double stranded DNA by cleavase I, and the modification of mispaired nucleotides within heteroduplexes by chemical agents commonly used in Maxam-Gilbert sequencing chemistry, are all well known in the art.
Further examples include the Protein Translation Test (PTT), used to resolves stop codons generated by variations which lead to a premature termination of translation and to protein products of reduced size, and the use of mismatch binding proteins (Moore, W. et al. Mutation detection in the breast cancer gene BRCA1 using the protein truncation test. Mol Biotechnol. 14(2):89-97 (2000), herein incorporated by reference in its entirety). Variations are detected by binding of, for example, the MutS protein, a component of Escherichia coli DNA mismatch repair system, or the human hMSH2 and GTBP proteins, to double stranded DNA heteroduplexes containing mismatched bases. DNA duplexes are then incubated with the mistmatch binding protein, and variations are detected by mobility shift assay. For example, a simple assay is based on the fact that the binding of the mismatch binding protein to the heteroduplex protects the heteroduplex from exonuclease degradation.
Those skilled in the art will know that a particular SNP, particularly when it occurs in a regulatory region of a gene such as a promoter, can be associated with altered expression of a gene. Altered expression of a gene can also result when the SNP is located in the coding region of a protein-encoding gene, for example where the SNP is associated with codons of varying usage and thus with tRNAs of differing abundance. Such altered expression can be determined by methods well known in the art, and can thereby be employed to detect such SNPs. Similarly, where a SNP occurs in the coding region of a gene and results in a non-synonymous amino acid substitution, such substitution can result in a change in the function of the gene product. Similarly, in cases where the gene product is an RNA, such SNPs can result in a change of function in the RNA gene product. Any such change in function, for example as assessed in an activity or functionality assay, can be employed to detect such SNPs.
The above methods of detecting and identifying SNPs are amenable to use in the methods of the invention.
In practicing the present invention to assess the risk a particular subject faces with respect to a particular disease, that subject will be assessed to determine the presence or absence of polymorphisms (preferably SNPs) which are either associated with protection from the disease or susceptibility to the disease.
In order to detect and identify SNPs in accordance with the invention, a sample containing material to be tested is obtained from the subject. The sample can be any sample potentially containing the target SNPs (or target polypeptides, as the case may be) and obtained from any bodily fluid (blood, urine, saliva, etc) biopsies or other tissue preparations.
DNA or RNA can be isolated from the sample according to any of a number of methods well known in the art. For example, methods of purification of nucleic acids are described in Tijssen; Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization with nucleic acid probes Part 1: Theory and Nucleic acid preparation, Elsevier, New York, N.Y. 1993, as well as in Maniatis, T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual 1989 (each of the foregoing which is herein incorporated by reference in its entirety).
Upon detection of the presence or absence of the polymorphisms tested for, the critical step is to determine a net susceptibility score for the subject. This score will represent the balance between the combined value of the protective polymorphisms present and the total value of the susceptibility polymorphisms present, with a net protective score (i.e., a greater weight of protective polymorphisms present than susceptibility polymorphisms) being predictive of a reduced risk of developing the disease in question. The reverse is true where there is a net susceptibility score. To calculate where the balance lies, the individual polymorphisms are assigned a value. In the simplest embodiment, each polymorphisms within a category (i.e. protective or susceptibility) is assigned an equal value, with each protective polymorphism being −1 and each susceptibility polymorphism being +1 (or vice versa). It is however contemplated that the values assigned to individual polymorphisms within a category can differ, with some polymorphisms being assigned a value that reflects their predictive or discriminatory value. For example, one particularly strong protective polymorphism can have a value of −2, whereas another more weakly protective polymorphism can have a value of −0.75.
The net score, and the associated predictive outcome in terms of the risk of the subject developing a particular disease, can be represented in a number of ways. One example is as a graph as more particularly exemplified herein.
Another example is a simple numerical score (eg +2 to represent a subject with a net susceptibility score or −2 to represent with a net protective score). In each case, the result is communicated to the subject with an explanation of what that result means to that subject. Preferably, advice on ways the subject can change their lifestyle so as to reduce the risk of developing the disease is also communicated to the subject.
It will be appreciated that the methods of the invention can be performed in conjunction with an analysis of other risk factors known to be associated with a disease, such as COPD, emphysema, OCOPD, or lung cancer. Such risk factors include epidemiological risk factors associated with an increased risk of developing the disease. Such risk factors include, but are not limited to smoking and/or exposure to tobacco smoke, age, sex and familial history. These risk factors can be used to augment an analysis of one or more polymorphisms as herein described when assessing a subject's risk of developing a disease such as COPD, emphysema, OCOPD, or lung cancer.
The predictive methods of the invention allow a number of therapeutic interventions and/or treatment regimens to be assessed for suitability and implemented for a given subject, depending upon the disease and the overall risk quotient. The simplest of these can be the provision to a subject with a net susceptibility score of motivation to implement a lifestyle change, for example, in the case of OCOPD, to reduce exposure to aero-pollutants, for example, by an occupational change or by the use of safety equipment in the work place. Similarly where the subject is a current smoker, the methods of the invention can provide motivation to quit smoking. In this latter case, a “quit smoking” program can be followed, which can include the use of anti-smoking medicaments (such as nicotine patches and the like) as well as anti-addiction medicaments.
Other therapeutic interventions can involve altering the balance between protective and susceptibility polymorphisms toward a protective state (such as by neutralizing or reversing a susceptibility polymorphism). The manner of therapeutic intervention or treatment will be predicated by the nature of the polymorphism(s) and the biological effect of said polymorphism(s). For example, where a susceptibility polymorphism is associated with a change in the expression of a gene, intervention or treatment is preferably directed to the restoration of normal expression of said gene, by, for example, administration of an agent capable of modulating the expression of said gene. Where a polymorphism, such as a SNP allele or genotype, is associated with decreased expression of a gene, therapy can involve administration of an agent capable of increasing the expression of said gene, and conversely, where a polymorphism is associated with increased expression of a gene, therapy can involve administration of an agent capable of decreasing the expression of said gene. Methods useful for the modulation of gene expression are well known in the art. For example, in situations were a polymorphism is associated with upregulated expression of a gene, therapy utilising, for example, RNAi or antisense methodologies can be implemented to decrease the abundance of mRNA and so decrease the expression of said gene. Alternatively, therapy can involve methods directed to, for example, modulating the activity of the product of said gene, thereby compensating for the abnormal expression of said gene.
Where a susceptibility polymorphism is associated with decreased gene produce function or decreased levels of expression of a gene product, therapeutic intervention or treatment can involve augmenting or replacing of said function, or supplementing the amount of gene produce within the subject for example, by administration of said gene product or a functional analogue thereof. For example, where a polymorphism is associated with decreased enzyme function, therapy can involve administration of active enzyme or an enzyme analogue to the subject. Similarly, where a polymorphism is associated with increased gene product function, therapeutic intervention or treatment can involve reduction of said function, for example, by administration of an inhibitor of said gene product or an agent capable of decreasing the level of said gene product in the subject. For example, where a polymorphism is associated with increased enzyme function, therapy can involve administration of an enzyme inhibitor to the subject.
Likewise, when a protective polymorphism is associated with upregulation of a particular gene or expression of an enzyme or other protein, therapies can be directed to mimic such upregulation or expression in an individual lacking the resistive genotype, and/or delivery of such enzyme or other protein to such individual Further, when a protective polymorphism is associated with downregulation of a particular gene, or with diminished or eliminated expression of an enzyme or other protein, desirable therapies can be directed to mimicking such conditions in an individual that lacks the protective genotype.

EXAMPLES

The invention will now be described in more detail, with reference to non-limiting examples.

Example 1

Case Association Study—COPD

Methods

Subject Recruitment

Subjects of European descent who had smoked a minimum of fifteen pack years and diagnosed by a physician with chronic obstructive pulmonary disease (COPD) were recruited. Subjects met the following criteria were over 50 years old and had developed symptoms of breathlessness after 40 years of age, had a Forced expiratory volume in one second (FEV1) as a percentage of predicted <70% and a FEV1/FVC ratio (Forced expiratory volume in one second/Forced vital capacity) of <79% (measuring using American Thoracic Society criteria). Two hundred and ninety-four subjects were recruited, of these 58% were male, the mean FEV1/FVC (±95% confidence limits) was 51% (49-53), mean FEV1 as a percentage of predicted was 43 (41-45). Mean age, cigarettes per day and pack year history was 65 yrs (64-66), 24 cigarettes/day (22-25) and 50 pack years (41-55) respectively. Two hundred and seventeen European subjects who had smoked a minimum of twenty pack years and who had never suffered breathlessness and had not been diagnosed with an obstructive lung disease in the past, in particular childhood asthma or chronic obstructive lung disease, were also studied. This control group was recruited through clubs for the elderly and consisted of 63% male, the mean FEV1/FVC (95% CI) was 82% (81-83), mean FEV1 as a percentage or predicted was 96 (95-97). Mean age, cigarettes per day and pack year history was 59 yrs (57-61), 24 cigarettes/day (22-26) and 42 pack years (39-45) respectively. Using a PCR based method [1, incorporated herein in its entirety by reference], all subjects were genotyped for the α1-antitrypsin mutations (S and Z alleles) and those with the ZZ allele were excluded. The COPD and resistant smoker cohorts were matched for subjects with the MZ genotype (5% in each cohort). 190 European blood donors (smoking status unknown) were recruited consecutively through local blood donor services. Sixty-three percent were men and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between COPY sufferers and resistant smokers was found not to determine FEV or COPD.
This study shows that polymorphisms found in greater frequency in COPD patients compared to controls (and/or resistant smokers) can reflect an increased susceptibility to the development of impaired lung function and COPD. Similarly, polymorphisms found in greater frequency in resistant smokers compared to susceptible smokers (COPD patients and/or controls) can reflect a protective role.
Summary of Characteristics for the COPD, Resistant Smoker and Healthy Blood Donors


Parameter	COPD	Resistant smokers
Median (IQR)	N = 294	N = 217	Differences

% male	58%	63%	ns
Age (yrs)	65 (64-66)	59 (57-61)	P < 0.05
Pack years	50 (46-53)	42 (39-45)	P < 0.05
Cigarettes/day	24 (22-25)	24 (22-26)	ns
FEV1 (L)	1.6 (0.7-2.5)	2.9 (2.8-3.0)	P < 0.05
FEV1 % predict	43 (41-45)	96% (95-97)	P < 0.05
FEV1/FVC	51 (49-53)	82 (81-83)	P < 0.05

Means and 95% confidence limits

Cyclo-oxgenase 2 (COX2) −765 G/C Promoter Polymorphism and a1-Antitrypsin Genotyping

Genomic DNA was extracted from whole blood samples [2, herein incorporated by reference in its entirety]. The Cyclo-oxygenase 2 −765 polymorphism was determined by minor modifications of a previously published method [3, herein incorporated by reference in its entirety]. The PCR reaction was carried out in a total volume of 25 ul and contained 20 ng genomic DNA, 500 pmol forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C., 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 3% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (Roche Diagnostics, New Zealand) at 37° C. Digested products were separated on a 2.5% agarose gel run for 2.0 hours at 80 mV with TBE buffer. The products were visualised against a 123 bp ladder using ultraviolet transillumination after ethidium bromide staining. Using a PCR based method referenced above [1, herein incorporated by reference in its entirety], all COPD and resistant smoker subjects were genotyped for the α1-antitrypsin S and Z alleles.
Other Polymorphism Genotyping
Genomic DNA was extracted from whole blood samples [2]. Purified genomic DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a Sequenom™ system (Sequenom™ Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the following sequences, amplification conditions and methods.
The following conditions were used for the PCR multiplex reaction: final concentrations were for 10× Buffer 15 mM MgCl₂1.25×, 25 mM MgCl₂1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Qiagen hot start) 0.15 U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 min, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. Shrimp alkaline phosphotase (SAP) treatment was used (2 ul to 5 ul per PCT reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of: water, 0.76 ul; hME 10× termination buffer, 0.2 ul; hME primer (10 uM), 1 ul; MassEXTEND enzyme, 0.04 ul.

Sequenom conditions for the polymorphisms genotyping-1

SNP_ID	TERM	WELL	2nd-PCRP	1st-PCRP

Vitamin	ACT	W1	ACGTTGGATGGCTTGTTAACCAGCTTTGCC	ACGTTGGATGTTTTTCAGACTGGCAGAGCG
DPB - 420			[SEQ. ID. NO. 1]	[SEQ. ID. NO. 2]

Vitamin	ACT	W1	ACGTTGGATGTTTTTCAGACTGGCAGAGCG	ACGTTGGATGGCTTGTTAACCAGCTTTGCC
DBP-416			[SEQ. ID. NO. 3]	[SEQ. ID. NO. 4]

IL13 C-	ACT	W2	ACGTTGGATGCATGTCGCCTTTTCCTGCTC	ACGTTGGATGCAACACCCAACAGGCAAATG
1055T			[SEQ. ID. NO. 5]	[SEQ. ID. NO. 6]

GSTP1 -	ACT	W2	ACGTTGGATGTGGTGGACATGGTGAATGAC	ACGTTGGATGTGGTGCAGATGCTCACATAG
105			[SEQ. ID. NO. 7]	[SEQ. ID. NO. 8]

PAI1 G-	ACT	W2	ACGTTGGATGCACAGAGAGAGTCTGGACAC	ACGTTGGATGCTCTTGGTCTTTCCCTCATC
675G			[SEQ. ID. NO. 9]	[SEQ. ID. NO. 10]

NOS3 -	ACT	W3	ACGTTGGATGACAGCTCTGCATTCAGCACG	ACGTTGGATGAGTCAATCCCTTTGGTGCTC
296			[SEQ. ID. NO. 11]	[SEQ. ID. NO. 12]

IL13-	ACT	W3	ACGTTGGATGGTTTTCCAGCTTGCATGTCC	ACGTTGGATGCAATAGTCAGGTCCTGTCTC
Arg130Gln			[SEQ. ID. NO. 13]	[SEQ. ID. NO. 14]

ADRB2-	ACT	W3	ACGTTGGATGGAACGGCAGCGCCTTCTTG	ACGTTGGATGACTTGGCAATGGCTGTGATG
Arg16Gly			[SEQ. ID. NO. 15]	[SEQ. ID. NO. 16]

IFNG -	CGT	W5	ACGTTGGATGCAGACATTCACAATTGATTT	ACGTTGGATGGATAGTTCCAAACATGTGCG
A874T			[SEQ. ID. NO. 17]	[SEQ. ID. NO. 18]

IL18- C-	ACT	W6	ACGTTGGATGGGGTATTCATAAGCTGAAAC	ACGTTGGATGCCTTCAAGTTCAGTGGTCAG
133G			[SEQ. ID. NO. 19]	[SEQ. ID. NO. 20]

IL18-	ACT	W8	ACGTTGGATGGGTCAATGAAGAGAACTTGG	ACGTTGGATGAATGTTTATTGTAGAAAACC
A105C			[SEQ. ID. NO. 21]	[SEQ. ID. NO. 22]

Sequenom conditions for the polymorphisms genotyping-2

SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR

Vitamin DBP-420	99	99.7	99.7	46.2	53.3	ML	R
Vitamin DBP-416	99	99.7	99.7	45.5	33.3	M	F
IL13 C-1055T	112	97.5	80	48.2	60	L	R
GSTP1-105	107	99.4	80	49.9	52.9		F
PAl1 G-875G	109	97.6	80	59.3	66.7	g	F
NOS3-298	186	98.1	65	61.2	63.2		F
IL13-Arg130Gln	171	99.3	65	55.1	47.6		F
ADRB2-Arg16Gly	187	88.2	65	65.1	58.3		F
IFNG-A874T	112	75.3	81.2	45.6	27.3		F
IL18-C-133G	112	93.5	74.3	41.8	46.7	L	F
IL18-A105C	121	67.2	74.3	48.6	40		R

Sequenom conditions for the polymorphisms genotyping-3

SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

Vitamin DBP - 420	4518.9	AGCTTTGCCAGTTCC[SEQ. ID. NO. 23]	A	4807.1

Vitamin DBP - 416	5524.6	AAAAGCAAAATTGCCTGA[SEQ. ID. NO. 24]	T	5812.8

IL13 C-1055T	4405.9	TCCTGCTCTTCCCTC[SEQ. ID. NO. 25]	T	4703.1

GSTP1 - 105	5099.3	ACCTCCGCTGCAAATAC[SEQ. ID. NO. 26]	A	5396.5

PAI1 G-675G	5620.6	GAGTCTGGACACGTGGGG[SEQ. ID. NO. 27]	DEL	5917.9

NOS3 -298	5813.8	TGCTGCAGGCCCCAGATGA[SEQ. ID. NO. 28]	T	6102

IL13-Arg130Gln	5470.2	AGAAACTTTTTCGCGAGGGAC[SEQ. ID. NO. 29]	A	6767.4

ADRB2- Arg16Gly	7264.7	AGCGCCTTCTTGCTGGCACCCAAT[SEQ. ID. NO. 30]	A	7561.9

IFNG - A874T	6639.4	TCTTACAACACAAAATCAAATC[SEQ. ID. NO. 31]	T	5927.6

IL18- C-133G	4592	AGCTGAAACTTCTGG[SEQ. ID. NO. 32]	C	4865.2

IL18- A105C	6085	TCAAGCTTGCCAAAGTAATC[SEQ. ID. NO. 33]	A	6373.2

Sequenom conditions for the polymorphisms genotyping-4

		EXT2_	EXT2_
SNP_ID	EXT1_SEQ	CALL	MASS	EXT2_SEQ	1stPAUSE

Vitamin	AGCTTTGCCAGTTCCT[SEQ. ID. NO. 34]	C	5136.4	AGCTTTGCCAGTTCCGT	4848.2
DBP - 420				[SEQ. ID. NO. 35]

Vitamin	AAAAGCAAAATTGCCTGAT[SEQ. ID. NO. 36]	G	6456.2	AAAAGCAAAATTGCCTGAGGC	5853.9
DBP - 416				[SEQ. ID. NO. 37]

IL13 C-	TCCTGCTCTTCCCTCA[SEQ. ID. NO. 38]	C	5023.3	TCCTGCTCTTCCCTCGT	4735.1
1055T				[SEQ. ID. NO. 39]

GSTP1 -	ACCTCCGCTGCAAATACA[SEQ. ID. NO. 40]	G	5716.7	ACCTCCGCTGCAAATACGT	5428.5
105				[SEQ. ID. NO. 41]

PAI1 G-	GAGTCTGGACACGTGGGGA[SEQ. ID. NO. 42]	G	5247.1	GAGTCTGGACACGTGGGGGA	5949.9
675G				[SEQ. ID. NO. 43]

NOS3 -	TGCTGCAGGCCCCAGATGAT[SEQ. ID. NO. 44]	G	6416.2	TGCTGCAGGCCCCAGATGAGC	6143
298				[SEQ. ID. NO. 45]

IL13-	AGAAACTTTTTCGCGAGGGACA[SEQ. ID. NO. 46]	G	7416.8	AGAAACTTTTTCGCGAGGGACGGT	6799.4
Arg130Gln				[SEQ. ID. NO. 47]

ADRB2-	AGCGCCTTCTTGCTGGCACCCAATA[SEQ. ID. NO. 48]	G	8220.3	AGCGCCTTCTTGCTGGCACCCAATGGA	7593.9
Arg16Gly				[SEQ. ID. NO. 49]

IFNG -	TCTTACAACACAAAATCAAATCT[SEQ. ID. NO. 50]	A	7225.8	TCTTACAACACAAAATCAAATCAC	6952.6
A874T				[SEQ. ID. NO. 51]

IL18- C-	AGCTGAAACTTCTGGC[SEQ. ID. NO. 52]	G	5218.4	AGCTGAAACTTCTGGGA	4921/2
133G				[SEQ. ID. NO. 53]

IL18-	TCAAGCTTGCCAAAGTATCT[SEQ. ID. NO. 54]	C	7040.6	TCAAGCTTGCCAAAGTAATCGGA	6414.2
A105C				[SEQ. ID. NO. 55]

Sequenom conditions for the polymorphisms genotyping-5

SNP_ID	2nd-PCRP	1st-PCRP

Lipoxygenase5-	ACGTTGGATGGAAGTCAGAGATGATGGCAG	ACGTTGGATGATGAATCCTGGACCCAAGAC
366G/A	[SEQ. ID. NO. 56]	[SEQ. ID. NO. 57]

TNFalpha + 489G/A	ACGTTGGATGGAAAGATGTGCGCTGATAGG	ACGTTGGATGGCCACATCTCTTTCTGCATC
	[SEQ. ID. NO. 58]	[SEQ. ID. NO. 59]

SMAD3C89Y	ACGTTGGATGTTGCAGGTGTCCCATCGGAA [SEQ. ID. NO. 60]	ACGTTGGATGTAGCTCGTGGTGGCTGTGCCA
		[SEQ. ID. NO. 61]

CaspaseGly881ArgG/C	ACGTTGGATGGTGATCACCCAAGGCTTCAG [SEQ. ID. NO. 62]	ACGTTGGATGGTCTGTTGACTCTTTTGGCC
		[SEQ. ID. NO. 63]

MBL2-161G/A	ACGTTGGATGGTAGCTCTCCAGGCATCAAC [SEQ. ID. NO. 64]	ACGTTGGATGGTACCTGGTTCCCCCTTTTC
		[SEQ. ID. NO. 65]

HSP70-HOM2437T/C	ACGTTGGATGTGATCTTGTTCACCTTGCCG [SEQ. ID. NO. 66]	ACGTTGGATGAGATCGAGGTGACGTTTGAC
		[SEQ. ID. NO. 67]

CD14-159C/T	ACGTTGGATGAGACACAGAACCCTAGATGC [SEQ. ID. NO. 68]	ACGTTGGATGGCAATGAAGGATGTTTCAGG
		[SEQ. ID. NO. 69]

Chymase1-1903G/A	ACGTTGGATGTAAGACAGCTCCACAGCATC [SEQ. ID. NO. 70]	ACGTTGGATGTTCCATTTCCTCACCCTCAG
		[SEQ. ID. NO. 71]

TNFalpha-308G/A	ACGTTGGATGGATTTGTGTGTAGGACCCTG [SEQ. ID. NO. 72]	ACGTTGGATGGGTCCCCAAAAGAAATGGAG
		[SEQ. ID. NO. 73]

CLCA1 + 13924T/A	ACGTTGGATGGGATTGGAGAACAAACTCAC [SEQ. ID. NO. 74]	ACGTTGGATGGGCAGCTGTTACACCAAAAG
		[SEQ. ID. NO. 75]

MEHTyr113HisT/C	ACGTTGGATGCTGGCGTTTTGCAAACATAC [SEQ. ID. NO. 76]	ACGTTGGATGTTGACTGGAAGAAGCAGGTG
		[SEQ. ID. NO. 77]

NAT2Arg197GlnG/A	ACGTTGGATGCCTGCCAAAGAAGAAACACC [SEQ. ID. NO. 78]	ACGTTGGATGACGTCTGCAGGTATGTATTC
		[SEQ. ID. NO. 79]

MEHHis139ArgG/A	ACGTTGGATGACTTCATCCACGTGAAGCCC [SEQ. ID. NO. 80]	ACGTTGGATGAAACTCGTAGAAAGAGCCGG
		[SEQ. ID. NO. 81]

IL-1B-511A/G	ACGTTGGATGATTTTCTCCTCAGAGGCTCC [SEQ. ID. NO. 82]	ACGTTGGATGTGTCTGTATTGAGGGTGTGG
		[SEQ. ID. NO. 83]

ADRB2Gln27GluC/G	ACGTTGGATGTTGCTGGCACCCAATGGAAG [SEQ. ID. NO. 84]	ACGTTGGATGATGAGAGACATGACGATGCC
		[SEQ. ID. NO. 85]

ICAM1E469KA/G	ACGTTGGATGACTCACAGAGCACATTCACG [SEQ. ID. NO. 86]	ACGTTGGATGTGTCACTCGAGATCTTGAGG
		[SEQ. ID. NO. 87]

Sequenom conditions for the polymorphisms genotyping-6

SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	UEP_DIR

Lipoxygenase5-366G/A	104	99.6	73.4	59	70.6	F
TNF alpha + 489G/A	96	99.6	73.4	45.5	38.9	F
SMAD3C89Y	107	87.3	71.7	45.7	47.1	F
CaspaseGly881ArgG/C	111	97.2	81	52.9	58.8	R
MBL2 + 161G/A	99	96.8	81	50.3	52.9	F
HSP70-HOM2437T/C	107	99.3	81	62.2	65	R
CD14-159C/T	92	98	76.7	53.3	50	F
Chymase1-1903G/A	105	99.6	78.7	53.6	39.1	R
TNFalpha-308G/A	100	99.7	81.6	59.9	70.6	R
CLCA1 + 13924T/A	101	98	98	45.3	36.8	R
MEHTyr113HisT/C	103	97.7	82.2	48.7	42.1	R
NAT2Arg197GlnG/A	115	97.4	70	48.5	36.4	F
MeHHis139ArgG/a	115	96.7	77.8	66	82.4	F
IL-1B-511A/G	111	99.2	83	46	47.1	R
ADRB2Gln27GluC/G	118	96.6	80	52.2	66.7	F
ICAM1E469KA/G	115	98.8	95.8	51.5	52.9	R

Sequenom conditions for the polymorphisms genotyping-7

SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

Lipoxygenase5-366G/A	5209.4	GTGCCTGTGCTGGGCTC [SEQ. ID. NO. 88]	A	5506.6

TNFalpha + 489G/A	5638.7	GGATGGAGAGAAAAAAAC [SEQ. ID. NO. 89]	A	5935.9

SMAD3C89Y	5056.3	CCCTCATGTCATCTACT [SEQ. ID. NO. 90]	A	5353.5

CaspaseGly881ArgG/C	5097.3	GTCACCCACTCTGTTGC [SEQ. ID. NO. 91]	G	5370.5

MBL2 + 161G/A	5299.5	CAAAGATGGGCGTGATG [SEQ. ID. NO. 92]	A	5596.7

HSP70-HOM2437T/C	6026.9	CCTTGCCGGTGCTCTTGTCC [SEQ. ID. NO. 93]	T	6324.1

CD14-159C/T	6068	CAGAATCCTTCCTGTTACGG [SEQ. ID. NO. 94]	C	6341.1

Chymase1-1903G/A	6973.6	TCCACCAAGACTTAAGTTTTGCT [SEQ. ID. NO. 95]	G	7246.7

TNFalpha-308G/A	5156.4	GAGGCXTGAACCCCGTCC [SEQ. ID. NO. 96]	G	5429.5

CLCA1 + 13924T/A	5759.8	CTTTTTCATAGAGTCCTGT [SEQ. ID. NO. 97]	A	6048

MEHTyr113HisT/C	5913.9	TTAGTCTTGAAGTGAGGGT [SEQ. ID. NO. 98]	T	6211.1

NAT2Arg197GlnG/A	6635.3	TACTTATTTACGCTTGAACCTC [SEQ. ID. NO. 99]	A	6932.5

MEHHis139ArgG/A	5117.3	CCAGCTGCCCGCAGGCC [SEQ. ID. NO. 100]	A	5414.5

IL-1B-511A/G	5203.4	AATTGACAGAGAGCTCC [SEQ. ID. NO. 101]	G	5476.6

ADRB2Gln27GlyC/G	4547	CACGACGTCACGCAG [SEQ. ID. NO. 102]	C	4820.2

ICAM1E489KA/G	5090.3	CACATTCACGGTCACCT [SEQ. ID. NO. 103]	G	5363.5

Sequenom conditions for the polymorphisms genotyping-8

		EXT2	EXT2			1^st
SNP_ID	EXT1_SEQ	CALL	MASS	EXT2_SEQ	PAUSE

Lipoxygenase5-	GTGCCTGTGCTGGGCTCA	G	5826.8	GTGCCTGTGCTGGGCTCGT	5538.6
3668G/A	[SEQ. ID. NO. 104]			[SEQ. ID. NO. 105]

TNFalpha + 489G/A	GGATGGAGAGAAAAAAACA	G	6256.1	GGATGGAGAGAAAAAAACGT	5967.9
	[SEQ. ID. NO. 106]			[SEQ. ID. NO. 107]

SMAD3C89Y	CCCTCATGTCATCTACTA	G	5658.7	CCCTCATGTCATCTACTGC	5385.5
	[SEQ. ID. NO. 108]			[SEQ. ID. NO. 109]

CaspaseGly881ArgG/C	GTCACCCACTCTGTTGCC	C	5699.7	GTCACCCACTCTGTTGCGC	5426.5
	[SEQ. ID. NO. 110]			[SEQ. ID. NO. 111]

MBL2 + 161G/A	CAAAGATGGGCGTGATGA	G	5901.9	CAAAGATGGGCGTGATGGC	5628.7
	[SEQ. ID. NO. 112]			[SEQ. ID. NO. 113]

HSP70-HOM2437T/C	CCTTGCCGGTGCTCTTGTCCA	C	6644.3	CCTTGCCGGTGCTCTTGTCCGT	6356.1
	[SEQ. ID. NO. 114]			[SEQ. ID. NO. 115]

CD14-159C/T	CAGAATCCTTCCTGTTACGGC	T	6645.3	CAGAATCCTTCCTGTTACGGTC	6372.2
	[SEQ. ID. NO. 116]			[SEQ. ID. NO. 117]

Chymase1-1903G/A	TCCACCAAGACTTAAGTTTTGCTC	A	7550.9	TCCACCAAGACTTAAGTTTTGCTTC	7277.8
	[SEQ. ID. NO. 118]			[SEQ. ID. NO. 119]

TNFalpha-308G/A	GAGGCTGAACCCCGTCCC	A	5733.7	GAGGCTGAACCCCGTCCTC	5480.6
	[SEQ. ID. NO. 120]			[SEQ. ID. NO. 121]

CLCA1 + 13924T/A	CTTTTTCATAGAGTCCTGTT	T	6659.4	CTTTTTCATAGAGTCCTGTAAC	6073
	[SEQ. ID. NO. 122]			[SEQ. ID. NO. 123]

MEHTyr113HisT/G	TTAGTCTTGAAGTGAGGGTA	C	6531.3	TTAGTCTTGAAGTGAGGGTGT	6243.1
	[SEQ. ID. NO. 124]			[SEQ. ID. NO. 125]

NAT2Arg197GlnG/A	TACTTATTTACGCTTGAACCTCA	G	7261.8	TACTTATTTACGCTTGAACCTCGA	6964.5
	[SEQ. ID. NO. 126]			[SEQ. ID. NO. 127]

MEHHis139ArgG/A	CCAGCTGCCCGCAGGCCA	G	5734.7	CCAGCTGCCCGCAGGCCGT	5446.5
	[SEQ. ID. NO. 128]			[SEQ. ID. NO. 129]

IL-1B-511A/G	AATTGACAGAGAGCTCCC	A	5820.8	AATTGACAGAGAGCTCCTG	5507.6
	[SEQ. ID. NO. 130]			[SEQ. ID. NO. 131]

ADRB2Gln27GluC/G	CACGACGTCACGCAGC	G	5173.4	CACGACGTCACGCAGGA	4876.2
	[SEQ. ID. NO. 132]			[SEQ. ID. NO. 133]

ICAM1E469KA/G	CACATTCACGGTCACCTC	A	5707.7	CACATTCACGGTCACCTTG	5394.5
	[SEQ. ID. NO. 134]			[SEQ. ID. NO. 135]

Results

Frequencies of individual polymorphisms are as follows:

TABLE 1

Polymorphism allele and genotype frequencies in the COPD patients and resistant smokers.

Cyclo-oxygenase 2 −765 G/C

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Controls n = 94 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
COPD n = 202 (%)	59 (15%)	345 (85%)	6 (3%)	47 (23%)	149 (74%)
Resistant n = 172 (%)	85²(25%)	259 (75%)	14¹(8%)	57 (33%)	101 (59%)

Beta2-adrenoreceptor Arg 16 Gly

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 182 (%)	152 (42%)	212 (58%)	26 (14%)	100 (55%)	56 (31%)
COPD n = 236 (%)	164 (34%)	308 (66%)	34 (14%)	96 (41%)	106³(45%)
Resistant n = 190 (%)	135 (46%)	245 (64%)	34 (18%)	67 (35%)	89²(47%)

Interleukin 18 105 A/C

Frequency

Allele*

Genotype

	C	A	CC	AC	AA

Controls n = 184 (%)	118 (32%)	250 (68%)	22 (12%)	74 (40%)	88 (48%)
COPD n = 240 (%)	122 (25%)	377⁶(75%)	21 (9%)	80 (33%)	139^5,7(58%)
Resistant n = 196 (%)	113 (29%)	277 (71%)	16 (8%)	81 (41%)	99 (50%)

Interleukin 18 −133 C/G

Frequency

Allele*

Genotype

	G	C	GG	GC	CC

Controls n = 187 (%)	120 (32%)	254 (68%)	23 (12%)	74 (40%)	90 (48%)
COPD n = 238	123 (26%)	353⁹(74%)	21 (9%)	81 (34%)	136⁸(57%)
Resistant n = 195 (%)	113 (29%)	277 (71%)	16 (8%)	81 (42%)	98 (50%)

Plasminogen activator inhibitor 1 −675 4G/5G

Frequency

Allele*

Genotype

	5G	4G	5G5G	5G4G	4G4G

Controls n = 186 (%)	158 (42%)	214 (58%)	31 (17%)	96 (52%)	59 (32%)
COPD n = 237 (%)	219¹²(46%)	255 (54%)	54^10,11(23%)	111 (47%)	72 (30%)
Resistant n = 194 (%)	152 (39%)	236 (61%)	31 (16%)	90 (46%)	73^10,11(38%)

Nitric oxide synthase 3 Asp 298 Glu (T/G)

Frequency

Allele*

Genotype

	T	G	TT	TG	GG

Controls n = 183 (%)	108 (30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
COPD n = 238 (%)	159 (42%)	317 (58%)	25 (10%)	109 (47%)	104 (43%)
Resistant n = 194 (%)	136 (35%)	252 (65%)	28¹³(15%)	80 (41%)	86 (44%)

Vitamin D Binding Protein Lys 420 Thr (A/C)

Frequency

Allele*

Genotype

	A	C	AA	AC	CC

Controls n = 189 (%)	113 (30%)	265 (70%)	17 (9%)	79 (42%)	93 (49%)
COPD n = 250 (%)	147 (29%)	353 (71%)	24 (10%)	99 (40%)	127 (50%)
Resistant n = 195 (%)	140¹⁵(36%)	250 (64%)	25¹⁴(13%)	90¹⁴(46%)	80 (41%)

Vitamin D Binding Protein Glu 416 Asp (T/G)

Frequency

Allele*

Genotype

	T	G	TT	TG	GG

Controls n = 188 (%)	162 (43%)	214 (57%)	35 (19%)	92 (49%)	61 (32%)
COPD n = 240 (%)	230 (48%)	250 (52%)	57 (24%)	116 (48%)	67 (28%)
Resistant n = 197 (%)	193¹⁷(49%)	201 (51%)	43¹⁶(22%)	107¹⁶(54%)	47 (24%)

Glutathione S Transferase P1 Ile 105 Val (A/G)

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 185 (%)	232 (63%)	138 (37%)	70 (38%)	92 (50%)	23 (12%)
COPD n = 238 (%)	310 (65%)	166 (35%)	96 (40%)	118 (50%)	24 (10%)
Resistant n = 194 (%)	269¹⁹(69%)	119 (31%)	91¹⁸(47%)	87 (45%)	16 (8%)

Interferon-gamma 874 A/T

Frequency

Allele*

Genotype

	A	T	AA	AT	TT

Controls n = 186 (%)	183 (49%)	189 (51%)	37 (20%)	109 (58%)	40 (22%)
COPD n = 235 (%)	244 (52%)	226 (48%)	64²⁰(27%)	116 (49%)	55 (24%)
Resistant n = 193 (%)	208 (54%)	178 (46%)	51 (27%)	106 (55%)	36 (18%)

Interleukin-13 Arg 130 Gln (G/A)

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 184 (%)	67 (18%)	301 (82%)	3 (2%)	61 (33%)	120 (65%)
COPD n = 237 (%)	86 (18%)	388 (82%)	8 (3%)	70 (30%)	159 (67%)
Resistant n = 194 (%)	74 (19%)	314 (81%)	9²¹(5%)	56 (28%)	129 (67%)

Interleukin-13 −1055 C/T

Frequency

Allele*

Genotype

	T	C	TT	TC	CC

Controls n = 182 (%)	65 (18%)	299 (82%)	5 (3%)	55 (30%)	122 (67%)
COPD n = 234 (%)	94 (20%)	374 (80%)	8²²(4%)	78 (33%)	148 (63%)
Resistant n = 192 (%)	72 (19%)	312 (81%)	2 (1%)	68 (35%)	122 (64%)

a1-antitrypsin S

Frequency

Allele*

Genotype

		M	S	MM	MS	SS

	COPD n = 202 (%)	391 (97%)	13 (3%)	189 (94%)	13 (6%)	0 (0%)
	Resistant n = 189 (%)	350 (93%)	28 (7%)	162 (85%)	26²³(14%)	1²³(1%)

*number of chromosomes (2n)Genotype

1. Genotype. CC/CG vs GG for resistant vs COPD, Odds ratio (OR)=1.98, 95% confidence limits 1.3-3.1, χ²(Yates corrected)=8.82, p=0.003, CC/CG=protective for COPD
2. Allele. C vs G for resistant vs COPD, Odds ratio (OR)=1.92, 95% confidence limits 1.3-2.8, χ²(Yates corrected)=11.56, p<0.001, C=protective for COPD
3. Genotype. GG vs AG/AA for COPD vs controls, Odds ratio (OR)=1.83, 95% confidence limits 1.2-2.8, χ2 (Yates corrected)=8.1, p=0.004, GG=susceptible to COPD (depending on the presence of other snps)
4. Genotype. GG vs AG/AA for resistant vs controls, Odds ratio (OR)=1.98, 95% confidence limits 1.3-3.1, χ2 (Yates corrected)=9.43, p=0.002 GG=resistance (depending on the presence of other snps)
5. Genotype. AA vs AC/CC for COPD vs controls, Odds ratio (OR)=1.50, 95% confidence limits 1.0-2.3, χ2 (Yates uncorrected)=4.26, p=0.04, AA=susceptible to COPD
6. Allele. A vs C for COPD vs control, Odds ratio (OR)=1.46, 95% confidence limits 1.1-2.0, χ2 (Yates corrected)=5.76, p=0.02
7. Genotype. AA vs AC/CC for COPD vs resistant, Odds ratio (OR)=1.35, 95% confidence limits 0.9-2.0, χ2 (Yates uncorrected)=2.39, p=0.12 (trend), AA=susceptible to COPD
8. Genotype. CC vs CG/GG for COPD vs controls, Odds ratio (OR)=1.44, 95% confidence limits 1.0-2.2, χ2 (Yates corrected)=3.4, p=0.06, CC=susceptible to COPD
9. Allele. C vs G for COPD vs control, Odds ratio (OR)=1.36, 95% confidence limits 1.0-1.9, χ2 (Yates corrected)=53.7, p=0.05, C=susceptible to COPD
10. Genotype. 5G5G vs rest for COPD vs resistant, Odds ratio (OR)=1.55, 95% confidence limits 0.9-2.6, χ2 (Yates uncorrected)=3.12, p=0.08, 5G5G=susceptible to COPD
11. Genotype. 5G5G vs rest for COPD vs control, Odds ratio (OR)=1.48, 95% confidence limits 0.9-2.5, χ2 (Yates uncorrected)=2.43, p=0.12, 5G5G=susceptible to COPD
12. Allele. 5G vs 4G for COPD vs resistant, Odds ratio (OR)=1.33, 95% confidence limits 1.0-1.8, χ2 (Yates corrected)=4.02, p=0.05, 5G=susceptible to COPD
13. Genotype. TT vs TG/GG for resistant vs controls, Odds ratio (OR)=2.2, 95% confidence limits 1.0-4.7, χ2 (Yates corrected)=4.49, p=0.03, TT genotype=protective for COPD
14. Genotype. AA/AC vs CC for resistant vs COPD, Odds ratio (OR)=1.39, 95% confidence limits 0.9-2.1, χ2 (Yates uncorrected)=2.59, p=0.10, AA/AC genotype=protective for COPD
15. Allele. A vs C for resistant vs COPD, Odds ratio (OR)=1.34, 95% confidence limits 1.0-1.8, χ2 (Yates corrected)=3.94, p=0.05, A allele=protective for COPD
16. Genotype. TT/TG vs GG for resistant vs controls, Odds ratio (OR)=1.53, 95% confidence limits 1.0-2.5, χ2 (Yates uncorrected)=3.52, p=0.06, TT/TG genotype=protective for COPD
17. Allele. T vs G for resistant vs control, Odds ratio (OR)=1.27, 95% confidence limits 1.0-1.7, χ2 (Yates corrected)=2.69, p=0.1, T allele=protective for COPD
18. Genotype. AA vs AG/GG for resistant vs controls, Odds ratio (OR)=1.45, 95% confidence limits 0.9-2.2, χ2 (Yates uncorrected)=3.19, p=0.07, AA genotype=protective for COPD
19. Allele. A vs G for resistant vs control, Odds ratio (OR)=1.34, 95% confidence limits 1.0-1.8, χ2 (Yates uncorrected)=3.71, p=0.05, A allele=protective for COPD
20. Genotype. AA vs AT/TT for COPD vs controls, Odds ratio (OR)=1.51, 95% confidence limits 0.9-2.5, χ2 (Yates uncorrected)=3.07, p=0.08, AA genotype=susceptible to COPD
21. Genotype. AA vs AG/GG for resistant vs controls, Odds ratio (OR)=2.94, 95% confidence limits 0.7-14.0, χ2 (Yates uncorrected)=2.78, p=0.09, AA genotype=protective for COPD
22. Genotype. TT vs TC/CC for COPD vs resistant, Odds ratio (OR)=6.03, 95% confidence limits 1.1-42, χ2 (Yates corrected)=4.9, p=0.03, TT=susceptible to COPD
23. Genotype. MS/SS vs MM for Resistant vs COPD, Odds ratio (OR)=2.42, 95% confidence limits 1.2-5.1, χ2 (Yates corrected)=5.7, p=0.01, S=protective for COPD

Tissue Necrosis Factor α +489 G/A polymorphism allele and

genotype frequency in the COPD patients and resistant smokers.

Frequency

1. Allele*

2. Genotype

	A	G	AA	AG	GG

COPD	54 (11%)	430 (89%)	5 (2%)	44 (18%)	193 (80%)
n = 242 (%)
Resistant	27 (7%)	347 (93%)	1 (1%)	25 (13%)	161 (86%)
n = 187 (%)

*number of chromosomes (2n)

1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR)=1.57, 95% confidence limits 0.9-2.7, χ²(Yates corrected)=2.52, p=0.11, AA/AG=susceptible (GG=protective)
2. Allele. A vs G for COPD vs resistant, Odds ratio (OR)=1.61, 95% confidence limits 1.0-2.7, χ²(Yates corrected)=3.38, p=0.07, A=susceptible

Tissue Necrosis Factor α −308 G/A polymorphism allele and

genotype frequency in the COPD patients and resistant smokers.

Frequency

3. Allele*

4. Genotype

	A	G	AA	AG	GG

COPD	90 (19%)	394 (81%)	6 (2%)	78 (32%)	158 (65%)
n = 242 (%)
Resistant	58 (15%)	322 (85%)	3 (2%)	52 (27%)	135 (71%)
n = 190 (%)

*number of chromosomes (2n)

1. Genotype. GG vs AG/AA for COPD vs resistant, Odds ratio (OR)=0.77, 95% confidence limits 0.5-1.2, χ²(Yates uncorrected)=1.62, p=0.20, GG=protective (AA/AG=susceptible) trend
2. Allele. A vs G for COPD vs resistant, Odds ratio (OR)=1.3, 95% confidence limits 0.9-1.9, χ²(Yates uncorrected)=1.7, p=0.20, A=susceptible trend

SMAD3 C89Y polymorphism allele and genotype frequency

in the COPD patients and resistant smokers.

Frequency

5. Allele*

6. Genotype

	A	G	AA	AG	GG

COPD	2 (1%)	498 (99%)	0 (0%)	2 (1%)	248 (99%)
n = 250 (%)
Resistant	6 (2%)	386 (98%)	0 (0%)	6 (3%)	190 (97%)
n = 196 (%)

*number of chromosomes (2n)

1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR)=0.26, 95% confidence limits 0.04-1.4, χ²(Yates uncorrected)=3.19, p=0.07, AA/AG=protective (GG susceptible)

Intracellular Adhesion molecule 1 (ICAM1) A/G E469K

(rs5498) polymorphism allele and genotype frequency

in COPD patients and resistant smokers.

Frequency

7. Allele*

8. Genotype

	A	G	AA	AG	GG

COPD	259 (54%)	225 (46%)	73 (30%)	113 (47%)	56 (23%)
n = 242 (%)
Resistant	217 (60%)	147 (40%)	64 (35%)	89 (49%)	29 (16%)
n = 182 (%)

*number of chromosomes (2n)

1. Genotype. GG vs AG/GG for COPD vs resistant, Odds ratio (OR)=1.60, 95% confidence limits 0.9-2.7, χ²(Yates corrected)=3.37, p=0.07, GG=susceptibility
2. Allele. G vs A for COPD vs resistant, Odds ratio (OR)=1.3, 95% confidence limits 1.0-1.7, χ²(Yates corrected)=2.90, p=0.09

Caspase (NOD2) Gly881Arg polymorphism allele and genotype

frequencies in the COPD patients and resistant smokers.

Frequency

9. Allele*

10. Genotype

	G	C	GG	GC	CC

COPD	486 (98%)	8 (2%)	239 (97%)	8 (3%)	0 (0%)
n = 247 (%)
Resistant	388 (99.5%)	2 0.5%)	193 (99%)	2 (1%)	0 (0%)
n = 195 (%)

*number of chromosomes (2n)

1. Genotype. CC/CG vs GG for COPD vs resistant, Odds ratio (OR)=3.2, 95% confidence limits 0.6-22, χ²(Yates uncorrected)=2.41, p=0.11 (1-tailed), GC/CC=susceptibility (trend)

Mannose binding lectin 2(MBL2) +161 G/A polymorphism allele and

genotype frequencies in the COPD patients and resistant smokers.

Frequency

11. Allele*

12. Genotype

	A	G	AA	AG	GG

COPD	110 (25%)	326 (75%)	6 (3%)	98 (45%)	114 (52%)
n = 218 (%)
Resistant	66 (18%)	300 (82%)	6 (3%)	54 (30%)	123 (67%)
n = 183 (%)

*number of chromosomes (2n)

1. Genotype. GG vs rest for COPD vs resistant, Odds ratio (OR)=0.53, 95% confidence limits 0.4-0.80, χ²(Yates uncorrected)=8.55, p=0.003, GG=protective

Chymase 1 (CMA1) −1903 G/A promoter polymorphism allele and

genotype frequencies in the COPD patients and resistant smokers.

Frequency

13. Allele*

14. Genotype

	A	G	AA	AG	GG

COPD	259 (54%)	219 (46%)	67 (28%)	125 (52%)	47 (20%)
n = 239 (%)
Resistant	209 (58%)	153 (42%)	63 (35%)	83 (46%)	35 (19%)
n = 181 (%)

*number of chromosomes (2n)

1. Genotype. AA vs AG/GG for COPD vs resistant, Odds ratio (OR)=0.73, 95% confidence limits 0.5-1.1, χ²(Yates corrected)=1.91, p=0.17, AA genotype=protective trend

N-acetyltransferase 2 Arg 197 Gln G/A polymorphism allele

and genotype frequencies in COPD and resistant smokers.

Frequency

15. Allele*

16. Genotype

	A	G	AA	AG	GG

COPD	136 (28%)	358 (72%)	14 (6%)	108 (44%)	125 (50%)
n = 247 (%)
Resistant	125 (32%)	267 (68%)	21 (11%)	83 (42%)	92 (47%)
n = 196 (%)

*number of chromosomes (2n)

1. Genotype. AA vs AG/GG for COPD vs resistant, Odds ratio (OR)=0.50, 95% confidence limits 0.2-1.0, χ²(Yates uncorrected)=3.82, p=0.05, AA genotype=protective

Interleukin 1B (IL-1b) −511 A/G polymorphism allele

and genotype frequencies in COPD and resistant smokers.

Frequency

17. Allele*

18. Genotype

	A	G	AA	AG	GG

COPD	160 (32%)	336 (68%)	31 (13%)	98 (40%)	119 (48%)
n = 248 (%)
Resistant	142 (36%)	248 (64%)	27 (14%)	88 (45%)	80 (41%)
n = 195 (%)

*number of chromosomes (2n)

1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR)=1.3, 95% confidence limits 0.9-2.0, χ²(Yates corrected)=1.86, p=0.17, GG genotype=susceptible trend

Microsomal epoxide hydrolase (MEH) Tyr 113 His

T/C (exon 3) polymorphism allele and genotype

frequency in COPD and resistant smokers.

Frequency

19. Allele*

20. Genotype

	C	T	CC	CT	TT

COPD	137 (28%)	361 (72%)	18 (7%)	101 (41%)	130 (52%)
n = 249 (%)
Resistant	130 (34%)	258 (66%)	19 (10%)	92 (47%)	83 (43%)
n = 194 (%)

*number of chromosomes (2n)

1. Genotype. TT vs CT/CC for COPD vs resistant, Odds ratio (OR)=1.5, 95% confidence limits 1.0-2.2, χ²(Yates corrected)=3.51, p=0.06, TT genotype=susceptible

Microsomal epoxide hydrolase (MEH) His 139 Arg

A/G (exon 4) polymorphism allele and genotype

frequency in COPD and resistant smokers.

Frequency

21. Allele*

22. Genotype

	A	G	AA	AG	GG

COPD	372 (78%)	104 (22%)	148 (62%)	76 (32%)	14 (6%)
n = 238 (%)
Resistant	277 (77%)	81 (23%)	114 (64%)	49 (27%)	16 (9%)
n = 179 (%)

*number of chromosomes (2n)

1. Genotype. GG vs AA/AG for COPD vs resistant, Odds ratio (OR)=0.64, 95% confidence limits 0.3-1.4, χ²(Yates uncorrected)=1.43, p=0.23, GG genotype=protective (trend)

Lipo-oxygenase −366 G/A polymorphism allele and genotype

frequencies in the COPD patients and resistant smokers.

Frequency

23. Allele*

24. Genotype

	A	G	AA	AG	GG

COPD	21 (4%)	473 (96%)	1 (0.5%)	19 (7.5%)	227 (92%)
n = 247 (%)
Resistant	25 (7%)	359 (93%)	0 (0%)	25 (13%)	167 (87%)
n = 192 (%)

*number of chromosomes (2n)

1. Genotype. AA/AG vs GG for COPD vs resistant, Odds ratio (OR)=0.60, 95% confidence limits 0.3-1.1, χ²(Yates corrected)=2.34, p=0.12, AA/AG genotype=protective (GG susceptible) trend

Heat Shock Protein 70 (HSP 70) HOM T2437C polymorphism

allele and genotype frequencies in the COPD

patients and resistant smokers.

Frequency

25. Allele*

26. Genotype

	C	T	CC	CT	TT

COPD	127 (32%)	271 (68%)	5 (3%)	117 (59%)	77 (39%)
n = 199 (%)
Resistant	78 (23%)	254 (77%)	4 (2%)	70 (42%)	92 (56%)
n = 166 (%)

*number of chromosomes (2n)

1. Genotype. CC/CT vs TT for COPD vs resistant, Odds ratio (OR)=2.0, 95% confidence limits 1.3-3.1, χ²(Yates uncorrected)=9.52, p=0.002, CC/CT genotype=susceptible (TT=protective)

Chloride Channel Calcium-activated 1 (CLCA1) +13924

T/A polymorphism allele and genotype frequencies

in the COPD patients and resistant smokers.

Frequency

27. Allele*

28. Genotype

	A	T	AA	AT	TT

COPD	282 (63%)	166 (37%)	84 (38%)	114 (51%)	26 (12%)
n = 224 (%)
Resistant	178 (56%)	138 (44%)	42 (27%)	94 (59%)	22 (14%)
n = 158 (%)

*number of chromosomes (2n)

1. Genotype. AA vs AT/TT for COPD vs resistant, Odds ratio (OR)=1.7, 95% confidence limits 1.0-2.7, χ²(Yates corrected)=4.51, p=0.03, AA=susceptible

Monocyte differentiation antigen CD-14 −159

promoter polymorphism allele and genotype frequencies

in the COPD patients and resistant smokers.

Frequency

29. Allele*

30. Genotype

	C	T	CC	CT	TT

COPD	268 (56%)	212 (44%)	77 (32%)	114 (48%)	49 (20%)
n = 240 (%)
Resistant	182 (51%)	178 (49%)	46 (25%)	90 (50%)	44 (24%)
n = 180 (%)

*number of chromosomes (2n)

1. Genotype. CC vs CT/TT for COPD vs Resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.9-2.2, χ²(Yates uncorrected)=2.12, p=0.15, CC=susceptible (trend)

Elafin +49 C/T polymorphism allele and genotype frequencies

in the COPD patients, resistant smokers and controls.

Frequency

31. Allele*

32. Genotype

	C	T	CC	CT	TT

COPD n =	247 (86%)	41 (14%)	105 (73%)	37 (26%)	2 (1%)
144 (%)
Resistant n =	121 (81%)	29 (19%)	49 (65%)	23 (31%)	3 (4%)
75 (%)

*number of chromosomes (2n)

1. Genotype. CT/TT vs CC for COPD vs resistant, Odds ratio (OR)=0.70, 95% confidence limits=0.4-1.2, χ²(Yates uncorrected)=1.36, p=0.24, CT/TT genotype=protective (trend only)
2. Allele: T vs C for COPD vs resistant, Odds ratio (OR)=0.69, 95% confidence limits=0.4-1.2, χ²(Yates uncorrected)=1.91, p=0.17, T genotype=protective (trend only)

Beta2-adrenoreceptor Gln 27 Glu polymorphism allele and genotype

frequency in the COPD patients, resistant smokers and controls.

Frequency

33. Allele*

34. Genotype

	C	G	CC	CG	GG

Controls n =	204 (55%)	168 (45%)	57 (31%)	89 (48%)	39 (21%)
185 (%)
COPD n =	268 (56%)	208 (44%)	67 (28%)	134 (56%)	37 (16%)
238 (%)
Resistant n =	220 (56%)	170 (44%)	64 (33%)	92 (47%)	39 (20%)
195 (%)

*number of chromosomes (2n)

1. Genotype. GG vs CG/CC for COPD vs resistant, Odds ratio (OR)=0.74, 95% confidence limits=0.4-1.2, χ²(Yates uncorrected)=1.47, p=0.23, GG=protective (trend)
2. Genotype. GG vs CG/CC for COPD vs controls, Odds ratio (OR)=0.69, 95% confidence limits=0.4-1.2, χ²(Yates uncorrected)=2.16, p=0.14, GG=protective (trend)

Matrix metalloproteinase 1 (MMP1) −1607 1G/2G

polymorphism allele and genotype frequencies in

COPD patients, resistant smokers and controls.

Frequency

35. Allele*

36. Genotype

	1G	2G	1G1G	1G2G	2G2G

Controls n =	214 (61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
174 (%)
COPD n =	182 (42%)	252 (58%)	47 (22%)	88 (41%)	82 (38%)
217 (%)
Resistant n =	186 (50%)	188 (50%)	46 (25%)	94 (50%)	47 (25%)
187 (%)

*number of chromosomes (2n)

1. Genotype. 1G1G vs rest for COPD vs controls, Odds ratio (OR)=0.43, 95% confidence limits 0.3-0.7, ?²(Yates uncorrected)=13.3, p=0.0003 1G1G genotype=protective
2. Allele. 1G vs 2G for COPD vs controls, Odds ratio (OR)=0.45, 95% confidence limits 0.3-0.6, ?2 (Yates corrected)=28.8, p<0.0001, 1G=protective
3. Genotype. 1G1G/1G2G vs rest for COPD vs resistant smokers, Odds ratio (OR)=0.55, 95% confidence limits 0.4-0.9, ?²(Yates uncorrected)=6.83, p=0.009 1G1G/162G genotypes=protective
4. Allele. 1G vs 2G for COPD vs resistant smokers, Odds ratio (OR)=0.73, 95% confidence limits 0.6-1.0, ?2 (Yates corrected)=4.61, p=0.03, 1G=protective
5. Genotype. 2G2G vs 1G1G/1G2G for COPD vs controls, Odds ratio (OR)=3.17, 95% confidence limits 1.9-5.3, ?2 (Yates uncorrected)=21.4, p<0.0001 2G2G genotype=susceptible
6. Allele. 2G vs 1G for COPD vs controls, Odds ratio (OR)=2.2, 95% confidence limits 1.6-3.0, ?2 (Yates corrected)=28.8, p<0.00001, 2G=susceptible
7. Genotype. 2G2G vs 1G1G/1G2G for COPD vs resistant, Odds ratio (OR)=1.81, 95% confidence limits 1.2-2.9, ?2 (Yates uncorrected)=6.83, p=0.009 2G2G genotype=susceptible
8. Allele. 2G vs 1G for COPD vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 1.0-1.8, ?2 (Yates corrected)=4.61, p=0.0.03, 2G=susceptible
Table 2 below provides a summary of the protective and susceptibility polymorphisms determined for COPD.

TABLE 2

Summary of protective and susceptibility polymorphisms for COPD

Gene	Polymorphism	Role

Cyclo-oxygenase 2 (COX2)	COX2 −765 G/C	CC/CG protective
β2-adrenoreceptor (ADBR)	ADBR Arg16Gly	GG susceptible
Interleukin -18 (IL18)	IL18 −133 C/G	CC susceptible
Interleukin -18 (IL18)	IL18 105 A/C	AA susceptible
Plasminogen activator inhibitor 1 (PAI-1)	PAI-1 −675 4G/5G	5G5G susceptible
Nitric Oxide synthase 3 (NOS3)	NOS3 298 Asp/Glu	TT protective
Vitamin D Binding Protein (VDBP)	VDBP Lys 420 Thr	AA/AC protective
Vitamin D Binding Protein (VDBP)	VDBP Glu 416 Asp	TT/TG protective
Glutathione S Transferase (GSTP-1)	GSTP1 Ile105Val	AA protective
Interferon ? (IFN-?)	IFN-? 874 A/T	AA susceptible
Interleukin-13 (IL13)	IL13 Arg 130 Gln	AA protective
Interleukin-13 (IL13)	Il13 −1055C/T	TT susceptible
a1-antitrypsin (a1-AT)	a1-AT S allele	MS protective
Tissue Necrosis Factor α TNFa	TNFa +489 G/A	AA/AG susceptible
		GG protective
Tissue Necrosis Factor α TNFa	TNFa −308 G/A	GG protective
		AA/AG susceptible
SMAD3	SMAD3 C89Y AG	AA/AG protective
		GG susceptible
Intracellular adhesion molecule 1 (ICAM1)	ICAM1 E469K A/G	GG susceptible
Caspase (NOD2)	NOD2 Gly 881Arg G/C	GC/CC susceptible
Mannose binding lectin 2 (MBL2)	MBL2 161 G/A	GG protective
Chymase 1 (CMA1)	CMA1 −1903 G/A	AA protective
N- Acetyl transferase 2 (NAT2)	NAT2 Arg 197 Gln	AA protective
	G/A
Interleukin 1B (IL1B)	(IL1B) −511 A/G	GG susceptible
Microsomal epoxide hydrolase (MEH)	MEH Tyr 113 His T/C	TT susceptible
Microsomal epoxide hydrolase (MEH)	MEH His 139 Arg G/A	GG protective
5 Lipo-oxygenase (ALOX5)	ALOX5 −366 G/A	AA/AG protective
		GG susceptible
Heat Shock Protein 70 (HSP 70)	HSP 70 HOM T2437C	CC/CT susceptible
		TT protective
Chloride Channel Calcium-activated 1 (CLCA1)	CLCA1 +13924 T/A	AA susceptible
Monocyte differentiation antigen CD-14	CD-14 −159 C/T	CC susceptible
Elafin	Elafin Exon 1 +49 C/T	CT/TT protective
B2-adrenergic receptor (ADBR)	ADBR Gln 27 Glu C/G	GG protective
Matrix metalloproteinase 1 (MMP1)	MMP1 −1607 1G/2G	1G1G/1G2G
		protective

The combined frequencies of the presence or absence of the selected protective genotypes COX2 (−765) CC/CG, β2 adreno-receptor AA, Interleukin-13 AA, Nitic Oxide Synthase 3 TT, and Vitamin D Binding Protein AA observed in the COPD subjects and in resistant smokers is presented below in Table 3.

TABLE 3

Combined frequencies of the presence or absence of selected protective
genotypes in COPD subjects and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

COPD	136 (54%)	100 (40%)	16 (7%)	252
Resistant smokers	79 (40%)	83 (42%)	34 (17%)	196
% of smokers with	136/215	100/183	16/50
COPD	(63%)	(55%)	(32%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist vs COPD	—	—	16.43	0.0003
2+ vs 0-1, Resist vs COPD	3.1	1.6-6.1	12.36	0.0004
1+ vs 0, Resist vs COPD	1.74	1.2-2.6	7.71	0.006

The combined frequencies of the presence or absence of the selected susceptibility genotypes Interleukin-18 105 AA, PAI-1 −675 5G5G, Interleukin-13 −1055 TT, and Interferon-? −874 AA observed in the COPD subjects and in resistant smokers is presented below in Table 4.

TABLE 4

Combined frequencies of the presence or absence
of selected susceptibility genotypes in the
COPD subjects and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

COPD	66 (26%)	113 (45%)	73 (29%)	252
Resistant smokers	69 (35%)	92 (47%)	35 (18%)	196
% of smokers with	66/135	113/205	73/108
COPD	(49%)	(55%)	(68%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, COPD vs Resist	—	—	8.72	0.01
2+ vs 0-1, COPD vs Resist	1.9	1.2-3.0	6.84	0.009
1+ vs 0, COPD vs Resist	1.5	1.0-3.5	3.84	0.05

The combined frequencies of the presence of absence of the protective genotypes COX3 (−765) CC/CG, Interleukin 13 AA, Nitic Oxide Synthase 3 TT, Vitamin D Binding Protein AA/AC GSTP1 AA, and a1-antitrypsin MS/SS, observed in the COPD subjects and in resistant smokers is presented below in Table 5 and in FIG. 1.

TABLE 5

Combined frequencies of the presence or absence of selected protective
genotypes in the COPD subjects and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

COPD	51 (19%)	64 (24%)	150 (57%)	265
Resistant smokers	16 (8%)	56 (27%)	133 (65%)	205
% of smokers with	51/76	64/120	150/283
COPD	(76%)	(53%)	(53%)

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist vs COPD	—	—	12.14	0.0005
1+vs 0, Resist vs COPD	2.82	1.5-5.3	11.46	0.0004

Protective polymorphisms were assigned a score of +1 while susceptibility polymorphisms were assigned a score of −1. For each subject, a net score was then calculated according to the presence of susceptibility an protective genotypes. This produced a linear spread of values. When assessed as a range between −3 to +3, a linear relationship as depicted in FIG. 2 was observed. This analysis indicates that for subjects with a net score of −2 or less, there was a 70% or greater risk of having COPD. In contrast, for subjects with a net score of 2+ or greater the risk was approximately 40% (see FIG. 2).
In an analysis in which the value of a given polymorphism was weighted based on the Odd's ratio for that polymorphism (generated by comparing its frequency between resistant and COPD subjects), a linear relationship was again observed. This analysis allowed for the distinction of smokers at high or low risk of having COPD.

Example 2

Case Association Study—OCOPD

Methods

Subject Recruitment

Subjects of European descent who had been exposed to chronic smoking (minimum 15 pack years) and aero-pollutants in the work place (noxious dusts or fumes) were identified from respiratory clinics. After spirometric testing those with occupational chronic obstructive pulmonary disease (OCOPD) with forced expiratory volume in one second (FEV1) as a percentage of predicted <70% and a FEV1/FVC ratio (Forced expiratory volume in one second/Forced vital capacity) of <79% (measured using American Thoracic Society criteria) were recruited. One hundred and thirty-nine subjects were recruited, of these 70% were male, the mean FEV1/FVC (±Standard Deviation) was 54% (SD 15), mean FEV1 as a percentage of predicted was 46 (SD 19). Mean age, cigarettes per day, and pack year history was 62 years (SD 9), 25 cigarettes/day (SD 16) and 53 pack years (SD 31), respectively. One hundred and twelve European subjects who had smoked a minimum of fifteen pack years and similarly had been exposed in the work place to potentially noxious dusts or fumes were also studied. This control group was recruited through community studies of lung function and were 81% male; the mean FEV1/FVC (SD) was 81% (SD 8), and mean FEV1 as a percentage of predicted was 95 (SD 10). Mean age, cigarettes per day and pack year history was 58 yrs (SD 11), 26 cigarettes/day (SD 14) and 45 pack years (SD 28), respectively. Using a PCR based method [1], all subjects were genotyped for the α1-antitrypsin mutations (M, S and Z alleles) and those with the ZZ allele were excluded. The OCOPD and resistant smoker cohorts were matched for subjected with the MZ genotype (6% in each cohort). They were also matched for age started smoking (mean 16 yr) and aged stopped smoking (mid fifties). 190 European blood donors (smoking and occupational exposure status unknown) were recruited consecutively through local blood donor services. Sixty-three percent were men and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between OCOPD sufferers and resistant smokers was found not to determine FEV or OCOPD.

Summary of Characteristics for the OCOPD and Exposed Resistant Smoker Cohorts.


		Exposed
Parameter	OCOPD	resistant smokers
Mean (SD)	N = 139	N = 112	Differences

% male	70%	81%	P < 0.05
Age (yrs)	62 (9)	59 (11)	ns
Pack years	53 (31)	42 (28)	P < 0.05
Cigarettes/day	25 (16)	24 (14)	ns
FEV1 (L)	1.3 (0.7)	3.0 (0.7)	P < 0.05
FEV1 % predict	46 (19)	96% (10)	P < 0.05
FEV1/FVC	54 (15)	81 (8)	P < 0.05

Means and 1SD

Cyclooxygenase 2 (COX2) −765 G/C Promoter Polymorphism and a1-Antitrypsin Genotyping

Genomic DNA was extracted from whole blood samples [2]. The COX2 −765 polymorphism was determined by minor modifications of a previously published method [3]. The PCR reaction was carried out in a total volume of 25 ul and contained 20 ng genomic DNA, 500 pmol forward and reverse primers, 0.2 mM dNTPS, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of Taq polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C., 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 6% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (Roche Diagnostics, New Zealand) at 37° C. Digested products were separated on a 2.5% agarose gel run for 2.0 hrs at 80 mV with TBE buffer and visualised using ultraviolet transillumination after ethidium bromide staining against a 123 bp ladder. Using a PCR based method discussed above [3], all smoking subjects were genotyped for the α1-antitrypsin M, S and Z alleles.

Genotyping of the Superoxide Dismutase 3 Arg 312 Gln Polymorphism

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [4, herein incorporated by reference in its entirety]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions. The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 10 pmol forward an reverse primers, 0.1 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 0.5 unit of Taq polymerase (Qiagen). Aliquots of amplification product were digested for 4 hrs with 5 U of the relevant restriction enzymes (Roche Diagnostics, New Zealand) at designated temperatures and conditions. Digested products were separated on 8% polyacrylamide gels (49:1, Sigma). The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the Microsomal Hydrolase Exon 3 TC Polymorphism

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [5, herein incorporated by reference in its entirety]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions. The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Cycling conditions consisted of 94° C. 60 s, 56° C. 20 s, 72° C. 20 s for 38 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 5 U of the relevant restriction enzymes Eco RV (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 8% polyacrylamide gels (49:1, Sigma). The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.
Genotyping of the 3′ 1237 G/A (T/t) Polymorphism of the a1-Antitrypsin Gene
Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [Sandford A J et al., [6], each of which is herein incorporated by reference in its entirety]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 5′-CTACCAGGAATGGCCTTGTCC-3′ [SEQ. ID. NO.136] and 5′-CTCTCAGGTCTGGTGTCATCC-3′ [SEQ. ID. NO. 137]. Cycling conditions consisted of 94 C 60 s, 56 C 20 s, 72 C 20 s for 38 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 2 Units of the restriction enzymes Taq I (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 3% agarose. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the Asp 299 Gly Polymorphism of the Toll-Like Receptor 4 Gene

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [6]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 100 mg forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 5′-GATTAGCATACTTAGACTACTACCTCCATG-3′ [SEQ. ID. NO.138] and 5′-GATCAACTTCTGAAAAAGCATTCCCAC-3′ [SEQ. ID. NO.139]. Cycling conditions consisted of 94° C. 30 s, 55° C. 30 s, 72° C. 30 s for 30 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 2 U of the restriction enzyme Nco I (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 3% agarose gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Genotyping of the −1607 1G2G Polymorphism of the Matrix Metalloproteinase 1 Gene

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [Dunleavey L, et al]. Genotyping was done using minor modifications of the above protocol optimised for laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HCL (pH 8.4), 50 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 3′TCGTGAGAATGTCTTCCCATT-3′ [SEQ. ID. NO. 140] and 5′-TCTTGGATTGATTTGAGATAAGTGAAATC-3′ [SEQ. ID. NO.141]. Cycling conditions consisted of 94 C 60 s, 55 C 30 s, 72 C 30 s for 35 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested for 4 hrs with 6 Units of the restriction enzymes XmnI (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 6% polyacrylamide gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Other Polymorphism Genotyping

Genomic DNA was extracted from whole blood samples [4]. Purified genomic DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a Sequenom™ system (Sequenom™ Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the sequences, amplification conditions and methods described below.
The following conditions were used for the PCR multiplex reaction: final concentrations were for 10× Buffer 15 mM MgCl2 1.25×, 25 mM MgCl2 1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Qiagen hot start) 0.15 u/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 min, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2 ul to 5 ul PCR reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of water 0.76 ul, hME 10× termination buffer 0.2 ul, hME primer (10 uM) 1 ul, MassEXTEND enzyme 0.04 ul.

Sequenom conditions for the polymorphisms genotyping-1

SNP_ID	TERM	WELL	2nd-PCRP	1st-PCRP

VDBP - 420	ACT	W1	ACGTTGGATGGCTTGTTAACCAGCTT	ACGTTGGATGTTTTTTCAGACTGGCAG
			TGCC [SEQ. ID. NO. 142]	AGCG [SEQ. ID. NO. 143]

VDBP - 416	ACT	W1	ACGTTGGATGTTTTTTCAGACTGGCAG	ACGTTGGATGGCTTGTTAACCAGCTTT
			AGCG [SEQ. ID. NO. 144]	GCC [SEQ. ID. NO. 145]

ADRB2-	ACT	W2	ACGTTGGATGTTGCTGGCACCCAATG	ACGTTGGATGATGAGAGACATGACGA
Gln27Glu			GAAG [SEQ. ID. NO. 146]	TGCC [SEQ. ID. NO. 147]

GSTP1 -105	ACT	W2	ACGTTGGATGTGGTGGACATGGTGAA	ACGTTGGATGTGGTGCAGATGCTCAC
			TGAC [SEQ. ID. NO. 148]	ATAG [SEQ. ID. NO. 149]

PAI1 G-675G	ACT	W2	ACGTTGGATGCACAGAGAGAGTCTGG	ACGTTGGATGCTCTTGGTCTTTCCCTC
			ACAC [SEQ. ID. NO. 150]	ATC
				[SEQ. ID. NO. 151]

IL-11 G518A	ACT	W3	ACGTTGGATGCCTCTGATCCTCTTTGC	ACGTTGGATGAAGAGGGAGTGGAAG
			TTC [SEQ. ID. NO. 152]	GGAAG [SEQ. ID. NO. 153]

NOS3 - 298	ACT	WC	ACGTTGGATGACAGCTCTGCATTCAG	ACGTTGGATGAGTCAATCCCTTTGGT
			CACG [SEQ. ID. NO. 154]	GCTC [SEQ. ID. NO. 155]

IL-8 A-251T	CGT	W5	ACGTTGGATGACTGAAGCTCCACAAT	ACGTTGGATGGCCACTCTAGTACTAT
			TTGG [SEQ. ID. NO. 156]	ATCTG [SEQ. ID. NO. 157]

IL-18 C-133G	ACT	W6	ACGTTGGATGGGGTATTCATAAGCTG	ACGTTGGATGCCTTCAAGTTCAGTGG
			AAAC [SEQ. ID. NO. 158]	TCAG [SEQ. ID. NO. 159]

IL-18 A105C	ACT	W8	ACGTTGGATGGGTCAATGAAGAGAA	ACGTTGGATGAATGTTTATTGTAGAA
			CTTGG [SEQ. ID. NO. 160]	AACC [SEQ. ID. NO. 161]

Sequenom conditions for the polymorphisms genotyping-2

SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR

VDBP-420	99	99.7	99.7	46.2	53.3	ML	R
VDBP-416	99	99.7	99.7	45.5	33.3	M	F
ADRB2-Gln27Glu	118	96.6	80	52.2	66.7	L	F
GSTP1-105	107	99.4	80	49.9	52.9		F
PAI1 G-675G	109	97.9	80	59.3	66.7	g	F
IL-11 G518A	169	97.5	65	52.9	52.6	s	F
NOS3-298	186	98.1	65	61.2	63.2		F
IL-8 A-251T	119	92.6	81.2	45.9	28.6		R
IL-18 C-133G	112	93.5	74.3	41.8	46.7	L	F
IL-18 A105C	121	67.2	74.3	48.9	40		R

Sequenom conditions for the polymorphisms genotyping-3

SNP_ID	UEP_MASS	UEP_SEQ	EXT1_CALL	EXT1_MASS

VDBP - 420	4518.9	AGCTTTGCCAGTTCC[SEQ. ID. NO. 162]	A	4807.1

VDBP - 416	5524.6	AAAAGCAAAATTGCCTGA[SEQ. ID. NO.	T	5812.8
		163]

ADRB2-	4547	CACGACGTCACGCAG[SEQ. ID. NO. 164]	C	4820.2
Gln27Glu

GSTP1-105	5099.3	ACCTCCGCTGCAAATAC[SEQ. ID. NO.	A	5396.5
		165]

PAI1 G-675G	5620.6	GAGTCTGGACACGTGGGG[SEQ. ID. NO.	DEL	5917.9
		166]

IL-11 G518A	5705.7	TCCATCTCTGTGGATCTCC[SEQ. ID. NO.	A	6002.9
		167]

NOS3 - 298	5813.8	TGCTGCAGGCCCCAGATGA[SEQ. ID. NO.	T	6102
		168]

IL-8 A-251T	6428.2	CACAATTTGGTGAATTATCAA[SEQ. ID.	A	6716.4
		NO. 169]

IL-18 C-133G	4592	AGCTGAAACTTCTGG[SEQ. ID. NO. 170]	C	4865.2

IL-18 A105C	6085	TCAAGCTTGCCAAAGTAATC[SEQ. ID.	A	6373.2
		NO. 171]

Sequenom conditions for the polymorphisms genotyping-4

SNP_ID	EXT1_SEQ	EXT2_CALL	EXT2_MASS	EXT2_SEQ	1stPAUSE

VDBP - 420	AGCTTTGCCAGTTCCT	C	5136.4	AGCTTTGCCAGTTCCGT	4848.2
	[SEQ. ID. NO. 172]			[SEQ. ID. NO. 173]

VDBP - 416	AAAAGCAAAATTGCCTGA	G	6456.2	AAAAGCAAAATTGCCTGAG	5853.9
	T [SEQ. ID. NO. 174]			GC [SEQ. ID. NO. 175]

ADRB2-	CACGACGTCACGCAGC	G	5173/4	CACGACGTCACGCAGGA	4876.2
Gln27Glu	[SEQ. ID. NO. 176]			[SEQ. ID. NO. 177]

GSTP1-105	ACCTCCGCTGCAAATACA	G	5716.7	ACCTCCGCTGCAAATACGT	5428.5
	[SEQ. ID. NO. 178]			[SEQ. ID. NO. 179]

PAI1 G-675G	GAGTCTGGACACGTGGGG	G	6247.1	GAGTCTGGACACGTGGGGG	5949.9
	A [SEQ. ID. NO. 180]			A [SEQ. ID. NO. 181]

IL-11 G518A	TCCATCTCTGTGGATCTCC	G	6323.1	TCCATCTCTGTGGATCTCC	6034.9
	A [SEQ. ID. NO. 182]			GT [SEQ. ID. NO. 183]

NOS3 - 298	TGCTGCAGGCCCCAGATG	G	6416.2	TGCTGCAGGCCCCAGATGA	6143
	AT [SEQ. ID. NO. 184]			GC [SEQ. ID. NO. 185]

IL-8 A-251T	CACAATTTGGTGAATTAT	T	7029.6	CACAATTTGGTGAATTATC	6741.4
	CAAT [SEQ. ID. NO. 186]			AAAT [SEQ. ID. NO. 187]

IL-18 C-133G	AGCTGAAACTTCTGGC	G	5218.4	AGCTGAAACTTCTGGGA	4921.2
	[SEQ. ID. NO. 188]			[SEQ. ID. NO. 189]

IL-18 A105C	TCAAGCTTGCCAAAGTAA	C	7040.6	TCAAGCTTGCCAAAGTAAT	6414.2
	TCT [SEQ. ID. NO. 190]			CGGA[SEQ. ID. NO. 191]

Results

Frequencies of individual polymorphisms are as follows:

TABLE 6

Polymorphism allele and genotype frequency in the OCOPD
patients, exposed resistant smokers and controls.

Cyclo-oxygenase 2 −765 G/C

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Controls n = 95 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
OCOPD n = 82 (%)	22 (13%)	142⁴(87%)	2 (2%)	18 (22%)	62³(76%)
Resistant n = 87 (%)	42²(24%)	132 (76%)	6¹(7%)	30¹(34%)	51 (59%)

Glutathione S Transferase P1 Ile 105 Val (A/G)

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 186 (%)	234 (63%)	138 (37%)	71 (38%)	92 (50%)	23 (12%)
OCOPD n = 123 (%)	159 (65%)	87 (36%)	52 (42%)	55 (45%)	16⁵(13%)
Resistant n = 98 (%)	136 (69%)	60 (31%)	44 (45%)	48 (49%)	6 (6%)

Interleukin 18 105 C/A

Frequency

Allele*

Genotype

	C	A	CC	AC	AA

Controls n = 185 (%)	119 (32%)	251 (68%)	22 (12%)	75 (40%)	88 (48%)
OCOPD n = 122 (%)	62 (25%)	182 (75%)	12 (10%)	38 (31%)	72^6,7(59%)
Resistant n = 98 (%)	60 (31%)	136 (69%)	6 (6%)	48 (49%)	44 (45%)

Interleukin 18 −133 G/C

Frequency

Allele*

Genotype

	G	C	GG	GC	CC

Controls n = 188 (%)	121 (32%)	255 (68%)	23 (12%)	75 (40%)	90 (48%)
OCOPD n = 122	62 (25%)	182 (75%)	12 (10%)	38 (31%)	72^8,9(59%)
Resistant n = 97 (%)	60 (31%)	134 (69%)	6 (6%)	48 (50%)	43 (44%)

Interleukin 8 −251 A/T

Frequency

Allele*

Genotype

	A	T	AA	AT	TT

Controls n = 188 (%)	175 (47%)	201 (53%)	39 (21%)	97 (52%)	52 (28%)
OCOPD n = 116	101 (44%)	131 (56%)	21 (18%)	59 (51%)	36 (31%)
Resistant n = 93 (%)	94¹¹(50%)	92 (49%)	26¹⁰(28%)	42 (45%)	25 (27%)

Vitamin D Binding Protein Lys 420 Thr (A/C)

Frequency

Allele*

Genotype

	A	C	AA	AC	CC

Controls n = 189 (%)	113 (30%)	265 (70%)	17 (9%)	79 (42%)	93 (49%)
OCOPD n = 122 (%)	62 (25%)	182 (75%)	5 (4%)	52 (43%)	65¹⁴(53%)
Resistant n = 99 (%)	73¹³(37%)	125 (63%)	12¹²(12%)	49 (50%)	38 (38%)

Vitamin D Binding Protein Glu 416 Asp (T/G)

Frequency

Allele*

Genotype

	T	G	TT	TG	GG

Controls n = 189 (%)	163 (43%)	215 (57%)	35 (19%)	93 (49%)	61 (32%)
OCOPD n = 122 (%)	109 (45%)	135 (55%)	25 (21%)	59 (48%)	38¹⁷(31%)
Resistant n = 99 (%)	103¹⁶(52%)	95 (48%)	23¹⁵(23%)	57¹⁵(58%)	19 (19%)

Microsomal epxoide hydrolase R/r Exon 3 T/C

Frequency

Allele*

Genotype

	r	R	rr	Rr	RR

Controls n = 184 (%)	228 (62%)	140 (38%)	77 (42%)	74 (40%)	33 (18%)
OCOPD n = 98 (%)	144 (74%)	52 (26%)	55 (56%)	34 (35%)	9 (9%)
Resistant n = 102 (%)	135 (66%)	69 (34%)	52 (51%)	31 (30%)	19¹⁸(19%)

Super oxide dismutase 3 Arg 312 Gln

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 190 (%)	371 (98%)	9 (2%)	183 (96%)	5 (3%)	2 (1%)
OCOPD n = 100 (%)	199²⁰(99%)	1 (1%)	99 (99%)	1 (1%)	0 (0%)
Resistant n = 102 (%)	193 (95%)	11²⁰(5%)	92 (90%)	9¹⁹(55%)	1¹⁹(1%)

a1-antitrypsin S

Frequency

Allele*

Genotype

	M	S	MM	MS	SS

OCOPD n = 88 (%)	171 (97%)	5 (3%)	83 (94%)	5 (6%)	0 (0%)
Resistant n = 94 (%)	175 (93%)	13²²(7%)	81 (86%)	13²¹(14%)	0 (0%)

Toll-like receptor 4 Asp 299 Gly A/G

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

OCOPD n = 60 (%)	117 (98%)	1 (2%)	58 (98%)	1 (2%)	0 (0%)
Resistant n = 34 (%)	65 (96%)	3 (4%)	31 (91%)	3²³(9%)	0 (0%)

Beta2-adrenoreceptor Gln 27 Glu

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Controls n = 186 (%)	204 (55%)	168 (45%)	57 (31%)	90 (48%)	39 (21%)
OCOPD n = 122 (%)	129 (53%)	115 (47%)	32 (26%)	65 (53%)	25 (21%)
Resistant n = 99 (%)	117 (59%)	81 (41%)	38²⁴(38%)	41 (41%)	20 (20%)

Interleukin 11 (IL-11) −518 G/A

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

OCOPD n = 119 (%)	110 (46%)	128 (54%)	22 (19%)	66 (55%)	31 (26%)
Resistant n = 98 (%)	103 (53%)	93 (47%)	26²⁵(27%)	51 (52%)	21 (21%)

Interleukin-13 −1055 C/T

Frequency

Allele*

Genotype

	T	C	TT	TC	CC

Controls n = 182 (%)	65 (18%)	299 (82%)	5 (3%)	55 (30%)	122 (67%)
OCOPD n = 121 (%)	53 (22%)	189 (78%)	5²⁶(4%)	43 (36%)	73 (60%)
Resistant n = 97 (%)	31 (16%)	163 (84%)	1 (1%)	29 (30%)	67 (69%)

Plasminogen activator inhibitor 1 −675 4G/5G

Frequency

Allele*

Genotype

	5G	4G	5G5G	5G4G	4G4G

Controls n = 186 (%)	158 (42%)	214 (58%)	31 (17%)	96 (52%)	59 (32%)
OCOPD n = 122 (%)	115²⁸(47%)	129 (53%)	29²⁷(24%)	57 (47%)	36 (30%)
Resistant n = 98 (%)	76 (39%)	120 (61%)	14 (14%)	48 (49%)	36 (37%)

Nitric oxide synthase 3 Asp 298 Glu (T/G)

Frequency

Allele*

Genotype

	T	G	TT	TG	GG

Controls n = 183 (%)	108 (30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
OCOPD n = 120 (%)	71 (30%)	169 (70%)	10 (8%)	51 (43%)	59 (49%)
Resistant n = 99 (%)	71 (36%)	127 (64%)	15^29,30(15%)	41 (41%)	43 (43%)

a1-antitrypsin 3* 1237 G/A (T/t)

Frequency

Allele*

Genotype

	T	t	TT	Tt	tt

Controls n = 178 (%)	345 (97%)	11 (3%)	167 (94%)	11 (6%)	0 (0%)
COPD n = 61 (%)	109 (89%)	13 (11%)³²	50 (82%)	9 (15%)³¹	2 (3%)³¹
Resistant n = 35 (%)	67 (96%)	3 (4%)	32 (91%)	3 (9%)	0 (0%)

Matrix metalloproteinase 1 −1607 1G/2G

Frequency

Allele*

Genotype

	1G	2G	1G1G	1G2G	2G2G

Controls n = 174 (%)	214 (61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
COPD n = 93 (%)	90 (48%)	96 (52%)³⁴	24 (26%)	42 (45%)	27 (29%)³³
Resistant n = 94 (%)	99 (53%)	89 (47%)	25 (27%)	49 (52%)	20 (21%)

*number of chromosomes (2n)

1. Genotype. CC/CG vs GG for resistant vs OCOPD, Odds ratio (OR)=2.2, 95% confidence limits=1.1-4.8, χ²(Yates corrected)=4.76, P=0.03, CC/CG=protective
2. Allele. C vs G for resistant vs OCOPD, Odds ratio (OR)=2.1, 95% confidence limits 1.1-3.8, χ²(Yates corrected)=5.65, p=0.02. C=protective
3. Genotype. GG vs CG/CC for OCOPD vs resistant, Odds ratio (OR)=0.5, 95% confidence limits=0.2-0.9, χ²(Yates corrected)=4.76, P=0.03. GG=susceptible
4. Allele. G vs C for OCOPD vs resistant, Odds radio (OR)=0.5, 95% confidence limits 0.3-0.9, χ²(Yates corrected)=5.65, p=0.02. G=susceptible
5. Genotype. GG vs AG/AA for OCOPD vs resistant, Odds ratio (OR)=2.3, 95% confidence limits=0.8-6.9, χ²(Yates uncorrected)=2.88, p=0.09. GG genotype =susceptible
6. Genotype. AA vs AC/CC for OCOPD vs resistant, Odds ratio (OR)=1.8, 95% confidence limits=1.0-3.1, χ²(Yates corrected)=3.8, p=0.05. AA=susceptibility
7. Genotype. AA vs AC/CC for OCOPD vs controls, Odds ratio (OR)=1.6, 95% confidence limits 1.0-2.6, χ²(Yates uncorrected)=3.86, p=0.05. AA =susceptibility
8. Genotype. CC vs CG/GG for OCOPD vs controls, Odds ratio (OR)=1.6, 95% confidence limits=1.0-2.6, χ²(Yates uncorrected)=3.68, p=0.05. CC =susceptibility
9. Genotype. CC vs CG/GG for OCOPD vs resistant, Odds ratio (OR)=1.8, 95% confidence limits 1.0-3.2, χ²(Yates corrected)=4.10, p=0.04. CC =susceptibility
10. Genotype. AA vs AT/TT for OCODP vs resistant, Odds ratio (OR)=1.8, 95% confidence limits=0.9-3.6, χ²(Yates uncorrected)=2.88, p=0.09. AA=protective
11. Allele. A vs T for OCOPD vs resistant, Odds ratio (OR)=1.3, 95% confidence limits=0.9-2.0, χ²(Yates uncorrected)=2.3, p=0.15, A=protective
12. Genotype. AA vs AC/CC for resistant vs OCOPD, Odds ratio (OR)=3.2, 95% confidence limits=1.0-11.0, χ²(Yates corrected)=3.89, p=0.05. AA genotype =protective
13. Allele. A vs C for resistant vs OCOPD, Odds ratio (OR)=1.7, 95% confidence limits 1.1-2.6, χ²(Yates corrected)=6.24, p=0.01. A allele=protective
14. Genotype. CC vs AC/AA for OCOPD vs resistant, Odds ratio (OR)=1.8, 95% confidence limits=1.0-3.3, χ²(Yates corrected)=4.29, p=0.04. CC genotype =susceptibility
15. Genotype. TT/TG vs GG for resistant vs OCOPD, Odds ratio (OR)=1.9, 95% confidence limits=1.0-38, χ²(Yates uncorrected)=4.08, p=0.04. TT/TG genotype=protective
16. Allele. T vs G for resistant vs OCOPD, Odds ratio (OR)=1.3, 95% confidence limits 0.9-2.0, χ²(Yates uncorrected)=2.36, p=0.12. A allele=protective
17. Genotype. GG vs TT/TG for OCOPD vs resistant, Odds ratio (OR)=0.5, 95% confidence limits=0.3-1.0, χ²(Yates uncorrected)=4.1, p=0.04. GG genotype =susceptible
18. Genotype. RR vs Rr/rr for resistant vs OCOPD, Odds ratio (OR)=2.3, 95% confidence limits=0.9-5.8, χ²(Yates uncorrected)=3.7, p=0.05. RR genotype =protective
19. Genotype. AG/GG vs AA for resistant vs OCOPD, Odds ratio (OR)=10.8, 95% confidence limits=1.4-229, χ²(Yates corrected)=5.99 p=0.01. AG/GG genotype=protective, AA susceptible
20. Allele. G vs A for resistant vs OCOPD, Odds ratio (OR)=11.3, 95% confidence limits 1.5-237, χ²(Yates corrected)=6.77, p=0.001. G allele=protective, A susceptible
21. Genotype. MS vs MM for Resistant vs OCOPD, Odds ratio (OR)=2.7, 95% confidence limits 0.8-9.0, χ²(Yates uncorrected)=3.4, p=0.07. MS=protective
22. Allele: S vs M for resistant vs OCOPD, Odds ratio (OR)=2.5, 95% confidence limits 0.8-8.4, χ²(Yates uncorrected)=3.24, p=0.07.
23. Genotype. AG vs AA in resistant vs OCOPD, Odd's ratio (OR)=5.61, 95% confidence limits 0.5-146, χ²(Yates uncorrected)=2.66, p=0.10. AG=protective
24. Genotype. CC vs CG/GG for resistant vs OOCOPD, Odds ratio (OR)=1.75, 95% confidence limits=1.0-3.2, χ²(Yates uncorrected)=3.73, p=0.05. CC =protective
25. Genotype: AA vs AG/GG fore resistant vs OCOPD, Odd's ratio (OR)=1.6, 95% confidence limits 0.8-32, χ²(Yates uncorrected)=2.02, p=0.16. AA=protective
26. Genotype. TT vs TC/CC for OCOPD vs resistant, Odds ratio (OR)=6.03, 95% confidence limits 1.1-42, χ²(Yates corrected)=4.9, p=0.03. TT=susceptible
27. Genotype. 5G5G vs rest for OCOPD vs resistant, Odds ratio (OR)=1.9, 95% confidence limits 0.9-4.0, χ²(Yates uncorrected)=3.11, p=0.08. 5G5G=susceptible
28. Allele. 5G vs 4G for OCOPD vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.9-2.1, χ²(Yates corrected)=3.1, p=0.08. 5G=susceptible
29. Genotype. TT vs TG/GG for resistant vs controls, Odds ratio (OR)=2.3, 95% confidence limits 1.0-5.5, χ²(Yates corrected)=3.80, p=0.05. TT genotype =protective
30. Genotype. Tt vs TG/GG for resistant vs OCOPD, Odds ratio (OR)=1.9, 95% confidence limits 0.8-5.0, χ²(Yates uncorrected)=2.49, p=0.11. TT genotype =protective
31. Genotype Tt/tt vs TT for COPD vs controls, Odd's ratio (OR)=3.34, 95% confidence limits 1.3-8.9, χ²(Yates corrected)=6.28, p=0.01. Tt/tt=susceptible to OCOPD
32. Allele: t vs T for COPD vs controls, Odd's Ratio (OR)=2.5, 95% confidence limits 1.0-6.3, χ²(Yates corrected)=4.1, p=0.04. t=susceptible to OCOPD
33. Genotype. 2G2G vs 1G1G/1G2G for COPD vs controls, Odds ratio (OR)=2.1, 95% confidence limits 1.1-4.1, χ²(Yates corrected)=5.44, p=0.02. 2G2G genotype=susceptible to OCOPD
34. Allele. 2G vs 1G for COPD vs controls, Odds ratio (OR)=1.7, 95% confidence limits 1.2-2.5, χ²(Yates corrected)=7.97, p=0.005. 2G=susceptible for OCOPD
Table 7 below provides a summary of the protective and susceptibility polymorphisms determined for OCOPD.

TABLE 7

Summary of protective and susceptibility polymorphisms for OCOPD

Gene	Polymorphism	Role

Cyclo-oxygenase (Cox) 2	Cox 2 −765 G/C	CC/CG susceptible
		GG susceptible
β2-adrenoreceptor (ADRB2)	ADRB2 Gln 27Glu	CC protective
Interleukin -18 (IL-18)	IL-18 −133 C/G	CC susceptible
Interleukin -18 (IL-18)	IL-18 105 A/C	AA susceptible
Plasminogen activator inhibitor 1 (PAI-1)	PAI-1 −675 4G/5G	5G5G susceptible
Nitric oxide synthase 3 (NOS3)	NOS3 298 Asp/Glu	TT protective
Vitamin D Binding Protein (VDBR)	VDBR Lys 420 Thr	AA protective
		CC susceptible
Vitamin D Binding Protein (VDBR)	VDBR Glu 416 Asp	TT/TG protective
		GG susceptible
Glutathione S Transferase (GSTP1)	GSTP1 Ile105Val	GG susceptible
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gln	AG/GG protective
		AA susceptible
a1-antitrypsin (a1AT)	a1AT 3′ 1237 G/A (T/t)	Tt/tt susceptible
a1-antitrypsin (a1AT)	a1AT S allele	MS protective
Toll-like receptor 4 (TLR4)	TLR4 Asp 299 Gly A/G	AG/GG protective
Interleukin-8 (IL-8)	IL-8 −251 A/T	AA protective
Interleukin 11 (IL-11)	IL-11 −518 G/A	AA protective
Microsomal epoxide hydrolase (MEH)	MEH Exon 3 T/C (r/R)	RR protective
Interleukin 13 (IL-13)	IL-13 −1055 C/T	TT susceptible
Matrix Metalloproteinase 1 (MMP1)	MMP1 −1607 1G/2G	2G2G susceptible

The combined frequencies of the presence or absence of the selected protective genotypes COX2 −765 CC/CG, NOS3 298 TT, a1AT MS/SS, SOD3 AG/GG, MEH Exon 3 RR, and VDBP 420 AA observed in the OCOPD subjects and in resistant smokers is presented below in Table 8.

TABLE 8

Combined frequencies of the presence or absence of protective
genotypes in OCOPD subjects and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

OCOPD	34 (27%)	51 (41%)	39 (32%)	124
Resistant smokers	20 (19%)	31 (30%)	53 (51%)	104
% of smokers with	34/54	51/82	39/92
OCOPD	(63%)	(62%)	(42%)

Comparison	Odd’s ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist	—	—	16.2	0.003
vs OCOPD
2+ vs 0-1, Resist	2.3	1.3-4.0	8.15	0.004
vs OCOPD
0 vs 2+, OCOPD	2.3	1.1-4.9	4.97	0.03
vs Resist

The combined frequencies of the presence or absence of the selected susceptibility genotypes MMP1 −1607 2G2G, GSTP1 105 GG, PAI-1 −675 5G5G, IL-13 −1055 TT, and VDBP 416 GG, observed in the OCOPD subjects and in resistant smokers is present below in Table 9.

TABLE 9

Combined frequencies of the presence or absence
of selected susceptibility genotypes in OCOPD
subjects and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

OCOPD	45 (36%)	55 (44%)	24 (20%)	124
Resistant smokers	55 (54%)	37 (37%)	9 (9%)	101
% of smokers with	45/100	55/92	24/33
OCOPD	(45%)	(60%)	(73%)

Comparison	Odd’s ratio	95% CI	?2	P value

0 vs 1 vs 2+, OCOPD	—	—	9.1	0.01
vs Resist
2+ vs 0-1, OCOPD	2.5	1.0-6.0	4.05	0.04
vs Resist
0+ vs 1-2+, Resist	2.1	1.2-3.7	6.72	0.01
vs OCOPD

Protective polymorphisms were assigned a score of +1 while susceptibility polymorphisms were assigned a score of −1. For each subject, a net score was then calculated according to the presence of susceptibility and protective genotypes. This produced a linear spread of values, as shown in Table 10. When assessed as a range between −2 to +3, a linear relationship as depicted in FIG. 3 was observed. This analysis indicates that for subjects with a net score of −1 or less, there was an approximately 70% or greater risk of having OCOPD. In contrast, for subjects with a net score of 2+ or greater, the risk was approximately 25% (see FIG. 3). As a point of clarification, it is noted that FIG. 3 depicts the sum of the protective and susceptibility polymorphisms combined, rather than simply the sum of the protective polymorphisms in one graph and the sum of the susceptibility polymorphisms in another graph. Thus, the SNP score can be negative if there are only susceptibility polymorphisms, positive, if there are only protective polymorphisms, or either positive or negative, depending upon the relative numbers of protective to susceptibility polymorphisms.

TABLE 10

Combined presence or absence of protective and
susceptibility polymorphisms

	Score combining protective and
	susceptibility polymorphisms

Example 3

Case Association Study—Lung Cancer

Methods

Subject Recruitment

Subjects of European descent who had smoked a minimum of fifteen pack years and diagnosed with lung cancer were recruited. Subjects met the following criteria: diagnosed with lung cancer based on radiological and histological grounds, including primary lung cancers with histological types of small cell lung cancer, squamous cell lung cancer, adenocarcinoma of the lung, non-small cell cancer (where histological markers can not distinguish the subtype) an broncho-alveolar carcinoma. Subjects can be of any age and at any state of treatment after the diagnosis had been confirmed. One hundred and nine subjects were recruited, of these 58% were male, the mean FEV1/FVC (±95% confidence limits) was 51% (49-53), mean FEV1 as a percentage of predicted was 43 (41-45). Mean age, cigarettes per day and pack year history was 65 yrs (64-66), 24 cigarettes/day (22-25) and 50 pack years (41-55) respectively. Two hundred and seventeen European subjects who had smoked a minimum of twenty pack years and who had never suffered breathlessness and had not been diagnosed with an obstructive lung disease or lung cancer in the past were also studied. This control group was recruited through clubs for the elderly and consisted of 63% male, the mean FEV1/FVC (95% CI) was 82% (81-83), mean FEV1 as a percentage of predicted as 96 (95-97). Mean age, cigarettes per day and pack year history was 59 yrs (57-61), 24 cigarettes/day (22-26) and 42 pack years (39-45) respectively. Using a PCR based method [1], all subjects were genotyped for the α1-antitrypsin mutations (S and Z alleles) and those with the ZZ allele were excluded. 190 European blood donors (smoking status unknown) were recruited and their mean age was 50 years. On regression analysis, the age difference and pack years difference observed between lung cancer sufferers and resistant smokers was found not be determine FEV or lung cancer.
This study shows that polymorphisms found in greater frequency in lung cancer patients compared to resistant smokers can reflect an increased susceptibility to the development of lung cancer. Similarly, polymorphisms found in greater frequency in resistant smokers compared to lung cancer can reflect a protective role.
Summary of Characteristics.


Parameter	Lung Cancer	Resistant smokers
Mean (IQR)	N = 109	N = 200	Differences

% male	52%	64%	ns
Age (yrs)	68 (11)	60 (12)	P < 0.05
Pack years	40 (31)	43 (25)	P < 0.05
Cigarettes/day	18 (11)	24 (12)	ns
FEV1 (L)	1.7 (0.6)	2.8 (0.7)	P < 0.05
FEV1 % predict	67 (22)	96% (10)	P < 0.05
FEV1/FVC	59 (14)	82 (8)	P < 0.05

Means and 95% confidence limits

Glutathione S-Transferase Null Polymorphisms Genotyping

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described [7, herein incorporated by reference in its entirety]. Genotyping was done using minor modifications of the above protocol optimised for our own laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl an contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HLC (pH 8.4), 50 mM KCl, 2.5 mM MgCl2 and 1.0 unit of Taq polymerase (Qiagen). Forward, internal (GSTM4) and reverse prime sequences were 5′ CTGCCCTACTTGATTGATGG-3′ [SEQ. ID. NO.192], 5′ ATCTTCTCCTCTTCTGTCTC-3′ [SEQ. ID. NO.193] and 5′-TTCTGGATTGTAGCAGATCA-3′ [SEQ. ID. NO.194]. Cycling conditions consisting of 94 C 60 s, 59 C 30 s, 72 C 30 s for 35 cycles with an extended last extension of 3 min. Digested products were separated on 3% agarose gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 Kb plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Cyclooxygenase 2 Polymorphisms Genotyping

Genomic DNA was extracted from whole blood samples (Maniatis, T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual. 1989). The Cyclo-oxgenase 2 −765 polymorphism was determined by minor modifications of a previously published method (Papafili A, et al., 2002, incorporated in its entirety herein by reference)). The PCR reaction was carried out in a total volume of 25 ul and contained 20 ng genomic DNA, 400 pmol forward and reverse primers, 0.2 mM dNTPs, 10 mM Tris-HCL (pH 8.4), 150 mM KCl, 1.0 mM MgCl₂and 1 unit of polymerase (Life Technologies). Cycling times were incubations for 3 min at 95° C. followed by 33 cycles of 50 s at 94° C. 60 s at 66° C. and 60 s at 72° C. A final elongation of 10 min at 72° C. then followed. 4 ul of PCR products were visualised by ultraviolet trans-illumination of a 3% agarose gel stained with ethidium bromide. An aliquot of 3 ul of amplification product was digested for 1 hr with 4 units of AciI (Roche Diagnostics, New Zealand) at 37° C. Digested products were separated on a 2.5% agarose gel run for 2.0 hours at 80 mV with TBE buffer. The products were visualised against a 123 bp ladder using ultraviolet transillumination after ethidium bromide staining.

Matrix Metalloproteinase 1 −1607 1G/2G Polymorphisms Genotyping

Genomic DNA was extracted using standard phenol and chloroform methods. Cohorts of patients and controls were configured in to 96-well PCR format containing strategic negative controls. The assay primers, PCR conditions and RFLP assays details have been previously described (Dunleavey, L. et al. Rapid genotype analysis of the matrix metalloproteinase-1 gene 1G/2G polymorphism that is associated with risk of cancer. Matrix Biol. 19(2):175-7 (2000), herein incorporated by reference in its entirety). Genotyping was done using minor modifications of the above protocol optimised for our own laboratory conditions The PCR reactions were amplified in MJ Research thermocyclers in a total volume of 25 μl and contained 80 ng genomic DNA, 100 ng forward and reverse primers, 200 mM dNTPs, 20 mM Tris-HCL (pH 8.4, 50 mM KCl, 1.5 mM MgCl₂and 1.0 unit of Taq polymerase (Qiagen). Forward and reverse prime sequences were 3′ TCGTGAGAATGTCTTCCCATT-3′ [SEQ. ID. NO.195] and 5′-TCTTGGATTGATTTGAGATAAGTGAAATC-3′ [SEQ. ID. NO.196]. Cycling conditions consisted of 94 C 60 s, 55 C 30 s, 72 C 30 s for 35 cycles with an extended last extension of 3 min. Aliquots of amplification product were digested with 4 hrs with 6 Units of the restriction enzymes XmnI (Roche Diagnostics, New Zealand) at designated temperature conditions. Digested products were separated on 6% polyacrylamide gel. The products were visualised by ultraviolet transillumination following ethidium bromide staining and migration compared against a 1 kB plus ladder standard (Invitrogen). Genotypes were recorded in data spreadsheets and statistical analysis performed.

Polymorphism Genotyping Using the Sequenom Autoflex Mass Spectrometer

Genomic DNA was extracted from whole blood sample [2]. Purified genomic DNA was aliquoted (10 ng/ul concentration) into 96 well plates and genotyped on a Sequenom™ system (Sequenom™ Autoflex Mass Spectrometer and Samsung 24 pin nanodispenser) using the following sequences, amplification conditions and methods. The following conditions were used for the PCR multiplex reaction: final concentrations were for 10× Buffer 15 mM MgCl2 1.25×, 25 mM MgCl2 1.625 mM, dNTP mix 25 mM 500 uM, primers 4 uM 100 nM, Taq polymerase (Qiagen hot start) 0.15 U/reaction, Genomic DNA 10 ng/ul. Cycling times were 95° C. for 15 min, (5° C. for 15 s, 56° C. 30 s, 72° C. 30 s for 45 cycles with a prolonged extension time of 3 min to finish. We used shrimp alkaline phosphotase (SAP) treatment (2 ul to 5 ul per PCR reaction) incubated at 35° C. for 30 min and extension reaction (add 2 ul to 7 ul after SAP treatment) with the following volumes per reaction of water, 0.76 ul; hME 10× termination buffer, 0.2 ul; hME primer (10 mM), 1 ul; MassEXTEND enzyme, 0.04 ul.

Sequenom conditions for the polymorphisms genotyping-1

TERM	SNP_ID	2nd-PCRP	1st-PCRP

ACT	CYP2E1_1019G/CPst1	ACGTTGGATGAAACCAGAGGGAAGCAAAGG	ACGTTGGATGTCATTGGTTGTGCTGCACCT
		[SEQ. ID. NO. 197]	[SEQ. ID. NO. 198]

ACT	XPD-751 G/T	ACGTTGGATGCACCAGGAACCGTTTATGGC	ACGTTGGATGAGCAGCTAGAATCAGAGGAG
		[SEQ. ID. NO. 199]	[SEQ. ID. NO. 200]

ACT	IL-18 105 A/C	ACGTTGGATGGTCAATGAAGAGAACTTGGTC	ACGTTGGATGAATGTTTATTGTAGAAAACC
		[SEQ. ID. NO. 201]	[SEQ. ID. NO. 202]

ACT	IL-18-133G/C	ACGTTGGATGGGGTATTCATAAGCTGAAAC	ACGTTGGATGCCTTCAAGTTCAGTGGTCAG
		[SEQ. ID. NO. 203]	[SEQ. ID. NO. 204]

ACT	CYP 1A1 Ile462Val	ACGTTGGATGGTGATTATCTTTGGCATGGG	ACGTTGGATGGGATAGCCAGGAAGAGAAAG
		[SEQ. ID. NO. 205]	[SEQ. ID. NO. 206]

ACT	MMP12 Asn 357 Ser A/G	ACGTTGGATGCCCTATTTCTTTGTCTTCAC	ACGTTGGATGCTTGGGATAATTTGGCTCTG
		[SEQ. ID. NO. 207]	[SEQ. ID. NO. 208]

ACT	OGG1 Ser 326 Cys G/C	ACGTTGGATGGGAACCCTTTCTGCGCTTTG	ACGTTGGATGCCTACAGGTGCTGTTCAGTG
		[SEQ. ID. NO. 209]	[SEQ. ID. NO. 210]

ACT	NAT2 Arg	197 Gln A/G	ACGTTGGATGCCTGCCAAAGAAGAAACACC	ACGTTGGATGACGTCTGCAGGTATGTATTC
		[SEQ. ID. NO. 211]	[SEQ. ID. NO. 212]

ACT	CYP2E1_C/T Rsa1	ACGTTGGATGGTTCTTAATTCATAGGTTGC	ACGTTGGATGCTTCATTTCTCATCATATTTTC
		[SEQ. ID. NO. 213]	[SEQ. ID. NO. 214]

ACG	CCND1 A870G	ACGTTGGATGTAGGTGTCTCCCCCTGTAAG	ACGTTGGATGTCCTCTCCAGAGTGATCAAG
		[SEQ. ID. NO. 215]	[SEQ. ID. NO. 216]

ACG	ILB1-511 A/G	ACGTTGGATCATTTTCTCCTCAGAGGCTCC	ACGTTGGATGTGTCTGTATTGAGGGTGTGG
		[SEQ. ID. NO. 217]	[SEQ. ID. NO. 218]

ACG	FAS_A-670G	ACGTTGGATGTTGTGGCTGCAACATGAGAG	ACGTTGGATGCTATGGCGCAACATCTGTAC
		[SEQ. ID. NO. 219]	[SEQ. ID. NO. 220]

ACG	NOS3-789 T/C	ACGTTGGATGACTGTAGTTTCCCTAGTCCC	ACGTTGGATGAGTCAGCAGAGAGACTAGGG
		[SEQ. ID. NO. 221]	[SEQ. ID. NO. 222]

ACT	ACT_Ala15Thr	ACGTTGGATGGAGTTGAGAATGGAGAGAATG	ACGTTGGATGTCAAGTGGGCTGTTAGGGTG
		[SEQ. ID. NO. 223]	[SEQ. ID. NO. 224]

ACT	SOD3 Arg 312 Gln	ACGTTGGATGTGCTGCGTGGTGGGCGTGTG	ACGTTGGATGGGCCTTGCACTCGCTCTCG
		[SEQ. ID. NO. 225]	[SEQ. ID. NO. 226]

ACT	NOS3 Asp 298 Glu	ACGTTGGATGAAACGGTCGCTTCGACGTGC	ACGTTGGATGACCTCAAGGACCAGCTCGG
		[SEQ. ID. NO. 227]	[SEQ. ID. NO. 228]

CGT	IL-8-251 A/T	ACGTTGGATGACTGAAGCTCCACAATTTGG	ACGTTGGATGGCCACTCTAGTACTATATCTG
		[SEQ. ID. NO. 229]	[SEQ. ID. NO. 230]

CGT	IFN gamma 874 A/T	ACGTTGGATGCAGACATTCACAATTGATTT	ACGTTGGATGGATAGTTCCAAACATGTGCG
		[SEQ. ID. NO. 231]	[SEQ. ID. NO. 232]

ACT	XRCC1 Arg 399 Gln G/A	ACGTTGGATGTAAGGAGTGGGTGCTGGACT	ACGTTGGATGAGGATAAGGAGCAGGGTTGG
		[SEQ. ID. NO. 233]	[SEQ. ID. NO. 234]

Sequenom conditions for the polymorphisms genotyping-2

SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DIR	UEP_MASS

CYP2E1_1019G/CPst1	119	95.2	71.3	46.7	47.1	F	5256.4
XPD-751 G/T	113	97.6	71.3	49.8	47.4	F	5689.7
IL-18 105 A/C	120	65.6	71.3	49.8	36.4	R	6702.4
IL-18-133 G/C	112	93.5	81.3	47.1	42.1	F	5811.8
CYP 1A1 Ile462Val	102	98.2	81.3	55.6	55	F	6222.1
MMP12 Asn 357 Ser	95	92.6	81.3	48	30.4	F	7070.6
OGG1 Ser 326 Cys G/C	99	96.5	82.2	58.9	70.6	R	5227.4
NAT2 Arg 197 Gln A/G	115	97.4	70	48.5	36.4	F	6635.3
CYP2E1_C/T Rsa1	105	62.8	77.8	46.4	26.1	R	7018.6
CCND1 A870G	106	98.1	83	45.8	47.1	R	5034.3
ILB1-511 A/G	111	99.2	83	46	47.1	R	5203.4
FAS_A-670G	103	99.2	83	54.4	50	R	6166
NOS3-786 T/C	114	97.5	83	61.8	61.9	F	6358.1
ACT_Ala15Thr	118	93.4	68.2	45.2	47.1	F	5136.4
SOD3 Arg 312 Gln	119	63.2	68.2	55.5	57.9	F	5855.8
NOS3 Asp 298 Glu	113	82.2	68.2	65.4	66.7	F	6432.2
IL-8-251 A/T	119	92.6	75.8	45.9	28.6	R	6428.2
IFN gamma 874 A/T	112	75.3	75.8	46.4	26.1	F	6943.6
XRCC1 Arg 399 Gln G/A	109	93.6	93.6	66.8	82.4	F	5099.3

Sequenom conditions for the polymorphisms genotyping-3

		EXT1	EXT1		EXT2
SNP_ID	UEP_SEQ	CALL	MASS	EXT1_SEQ	CALL

CYP2E1_1019G/CPSt1	TTCTTGGTTCAGGAGAG	C	5529.6	TTCTTGGTTCAGGAGAGC	G
	[SEQ. ID. NO. 235]			[SEQ. ID. NO. 236]

XPD-751 G/T	GCAATCTGCTCTATCCTCT	T	5977.9	GCAATCTGCTCTATCCTCTT	G
	[SEQ. ID. NO. 237]			[SEQ. ID. NO. 238]

IL-18 105 A/C	ATTCAAGCTTGCCAAAGTAATC	A	6990.6	ATTCAAGCTTGCCAAAGTAAT	C
	[SEQ. ID. NO. 239]			CT [SEQ. ID. NO. 240]

IL-18-133 G/C	CATAAGCTGAAACTTCTGG	C	6085	CATAAGCTGAAACTTCTGGC	G
	[SEQ. ID. NO. 241]			[SEQ. ID. NO. 242]

CYP 1A1 Ile462Val	GGAAGTGTATCGGTGAGACC	A	6519.3	GGAAGTGTATCGGTGAGACC	G
	[SEQ. ID. NO. 243]			A [SEQ. ID. NO. 244]

MMP12 Asn 357 Ser	TGACAAATACTGGTTAATTAGCA	A	7367.8	TGACAAATACTGGTTAATTAG	G
A/G	[SEQ. ID. NO. 245]			CAA [SEQ. ID. NO. 246]

OGG1 Ser 326 Cys	GCTCCTGAGCATGGCGG	G	5500.6	GCTCCTGAGCATGGCGGC	C
G/C	[SEQ. ID. NO. 247]			[SEQ. ID. NO. 248]

NAT2 Arg 197 Gln	TACTTATTTACGCTTGAACCTC	A	6932.5	TACTTATTTACGCTTGAACCT	G
A/G	[SEQ. ID. NO. 249]			CA [SEQ. ID. NO. 250]

CYP2E1_C/T Rsa1	CTTAATTCATAGGTTGCAATTTT	T	7315.8	CTTAATTCATAGGTTGCAATT	C
	[SEQ. ID. NO. 251]			TTA [SEQ. ID. NO. 252]

CCND1 A870G	ACATCACCCTCACTTAC[SEQ. ID.	G	5307.5	ACATCACCCTCACTTACC	A
	NO. 253]			[SEQ. ID. NO. 254]

ILB1-511 A/G	AATTGACAGAGAGCTCC	G	5476.6	AATTGACAGAGAGCTCCC	A
	[SEQ. ID. NO. 255]			[SEQ. ID. NO. 256]

FAS_A-670G	ATGAGAGGCTCACAGACGTT	G	6439.2	ATGAGAGGCTCACAGACGTT	A
	[SEQ. ID. NO. 257]			C [SEQ. ID. NO. 258]

NOS3-786 T/C	GGCATCAAGCTCTTCCCTGGC	C	6631/3	GGCATCAAGCTCTTCCCTGG	T
	[SEQ. ID. NO. 259]			CC [SEQ. ID. NO. 260]

ACT_Ala15Thr	GAATGTTACCTCTCCTG[SEQ. ID.	A	5433/6	GAATGTTACCTCTCCTGA	G
	NO. 261]			[SEQ. ID. NO. 262]

SOD3 Arg 312 Gln	GCACTCAGAGCGCAAGAAG	C	6129	GCACTCAGAGCGCAAGAAGC	G
	[SEQ. ID. NO. 263]			[SEQ. ID. NO. 264]

NOS3 Asp 298 Glu	GCTGCTGCAGGCCCCAGATGA	T	6720.4	GCTGCTGCAGGCCCCAGATG	G
	[SEQ. ID. NO. 265]			AT [SEQ. ID. NO. 266]

IL-8-251 A/T	CACAATTTGGTGAATTATCAA	A	6716.4	CACAATTTGGTGAATTATCAA	T
	[SEQ. ID. NO. 267]			T [SEQ. ID. NO. 268]

IFN gamma 874 A/T	TTCTTACAACACAAAATCAAATC	T	7231.8	TTCTTACAACACAAAATCAAA	A
	[SEQ. ID. NO. 269]			TCT [SEQ. ID. NO. 270]

XRCC1 Arg 399 Gln	TCGGCGGCTGCCCTCCC	A	5396.5	TCGGCGGCTGCCCTCCCA	G
G/A	[SEQ. ID. NO. 271]			[SEQ. ID. NO. 272]

Sequenom conditions for the polymorphisms genotyping-4

SNP_ID	EXT2_MASS	EXT2_SEQ	1stPAUSE

CYP2E1_1019G/CPst1	5873.8	TTCTTGGTTCAGGAGAGGT[SEQ. ID. NO. 273]	5585.6

XPD-751 G/T	6292.1	GCAATCTGCTCTATCCTCTGC[SEQ. ID. NO. 274]	6018.9

IL-18 105 A/C	7658	ATTCAAGCTTGCCAAAGTAATCGGA[SEQ.	7031.6
		ID. NO. 275]

IL-18-133 G/C	6438.2	CATAAGCTGAAACTTCTGGGA[SEQ. ID. NO.	6141
		276]

CYP 1A1 Ile462Val	6839.5	GGAAGTGTATCGGTGAGACCGT[SEQ. ID.	6551.3
		NO. 277]

MMP12 Asn 357 Ser A/G	7688	TGACAAATACTGGTTAATTAGCAGT[SEQ. ID.	7399.8
		NO. 278]

OGG1 Ser 326 Cys G/C	5853.8	GCTCCTGAGCATGGCGGGA[SEQ. ID. NO.	5556.6
		279]

NAT2 Arg 197 Gln A/G	7261.8	TACTTATTTACGCTTGAACCTCGA[SEQ. ID.	6964.5
		NO. 280]

CYP2E1_C/T Rsa1	7636	CTTAATTCATAGGTTGCAATTTTGT[SEQ. ID.	7347.8
		NO. 281]

CCND1 A870G	5651.7	ACATCACCCTCACTTACTG[SEQ. ID. NO. 282]	5338.5

ILB1-511 A/G	5820.8	AATTGACAGAGAGCTCCTG[SEQ. ID. NO. 283]	5507.6

FAS_A-670G	6743.4	ATGAGAGGCTCACAGACGTTTC[SEQ. ID.	6470.2
		NO. 284]

NOS3-786 T/C	6975.5	GGCATCAAGCTCTTCCCTGGCTG[SEQ. ID.	6662.3
		NO. 285]

ACT_Ala15Thr	5738.7	GAATGTTACCTCTCCTGGC[SEQ. ID. NO. 286]	5465.6

SOD3 Arg 312 Gln	7116.6	GCACTCAGAGCGCAAGAAGGGGC[SEQ. ID.	6185
		NO. 287]

NOS3 Asp 298 Glu	7034.6	GCTGCTGCAGGCCCCAGATGAGC[SEQ. ID.	6761.4
		NO. 288]

IL-8-251-A/T	7029.6	CACAATTTGGTGAATTATCAAAT[SEQ. ID.	6741.4
		NO. 289]

IFN gamma 874 A/T	7530	TTCTTACAACACAAAATCAAATCAC[SEQ. ID.	7256.8
		NO. 290]

XRCC1 Arg 399 Gln G/A	6054.9	TCGGCGGCTGCCCTCCCGGA[SEQ. ID. NO.	5428.5
		291]

Sequenom conditions for the polymorphisms genotyping-5

TERM	SNP_ID	2nd-PCRP	1st-PCRP

ACT	CTGF-447G/C	ACGTTGGATGAGGTAGCTGAAGAG	ACGTTGGATGGCCTATAGCCTCTAA
		GCAAAC [SEQ. ID. NO. 292]	AACGC [SEQ. ID. NO. 293]

ACT	NBS1 Gln185Glu	ACGTTGGATGCTTTCAATTTGTGGA	ACGTTGGATGTGTGCACTCATTTGT
	G/C	GGCTG [SEQ. ID. NO. 294]	GGACG [SEQ. ID. NO. 295]

ACT	MBL2 161 G/A	ACGTTGGATGGTAGCTCTCCAGGCA	ACGTTGGATGGTACCTGGTTCCCCC
		TCAAC [SEQ. ID. NO. 296]	TTTTC [SEQ. ID. NO. 297]

ACT	IGF24 Leu252Val	ACGTTGGATGACACCAGGCGTTTGA	ACGTTGGATGAAAAACGCCAACAGC
	C/G	TGTTG [SEQ. ID. NO. 298]	ATCGG [SEQ. ID. NO. 299]

ACT	MUC5AC-221 C/T	ACGTTGGATGAGGCGGAGATGGGT	ACGTTGGATGAGTCTAGGGTGGGG
		GTGTC [SEQ. ID. NO. 300]	TATGTG [SEQ. ID. NO. 301]

ACT	Arg1 intron1 C/T	ACGTTGGATGATGTGTGGATTCACA	ACGTTGGATGGGGTTGGCAACTCTA
		GCTCG [SEQ. ID. NO. 302]	AAAGG [SEQ. ID. NO. 303]

ACT	REV1 Phe257Ser	ACGTTGGATGCTCTGAAATCAGTGC	ACGTTGGATGATGGTCAACAGTGTT
	C/T	TGCTC [SEQ. ID. NO. 304]	GCCAG [SEQ. ID. NO. 305]

ACT	Apex1 Asp148Glu	ACGTTGGATGCACCTCTTGATTGCT	ACGTTGGATGACCCGGCCTTCCTGA
	G/T	TTCCC [SEQ. ID. NO. 306]	TCATG [SEQ. ID. NO. 307]

ACG	IL-10-1082 A/G	ACGTTGGATGATTCCATGGAGGCTG	ACGTTGGATGGACAACACTACTAAG
		GATAG [SEQ. ID. NO. 308]	GCTTC [SEQ. ID. NO. 309]

Sequenom conditions for the polymorphisms genotyping-6

SNP_ID	AMP_LEN	UP_CONF	MP_CONF	Tm(NN)	PcGC	PWARN	UEP_DI	UEP_MASS

CTGF-447G/C	119	98.2	65	52	52.9		R	5090.3
NBS1 Gln185Glu G/C	118	97	65	51	52.9		R	5192.4
MBL2 161 G/A	99	96.8	65	50.3	52.9		F	5299.5
IGF2R Leu252Val C/G	114	98.5	67.8	68.6	82.4		F	5206.4
MUC5AC-221 C/T	119	81.8	67.8	56.9	64.7	g	R	5273.4
Arg1 intron1 C/T	102	99.6	67.8	53.3	52.6		R	5932.9
REV1 Phe257Ser C/T	105	99.6	67.8	57.5	55		R	6003.9
Apex1 Asp148Glu G/T	114	92.9	67.8	46.8	35		F	6113
IL-10-1082 A/G	107	98	68.8	51.2	58.8		R	4977.2

Sequenom conditions for the polymorphisms genotyping-7

		EXT1_	EXT1_
SNP_ID	UEP_SEQ	CALL	MASS	EXT1_SEQ

CTGF-447G/C	AAAAGGTTTCTCCCCCC	G	5363.5	AAAAGGTTTCTCCCCCCC
	[SEQ. ID. NO. 310]			[SEQ. ID. NO. 311]

NBS1 Gln185Glu	AGGCTGCTTCTTGGACT	G	5465.6	AGGCTGCTTCTTGGACTC
G/C	[SEQ. ID. NO. 312]			[SEQ. ID. NO. 313]

MBL2 161 G/A	CAAAGATGGGCGTGATG	A	5596.7	CAAAGATGGGCGTGATGA
	[SEQ. ID. NO. 314]			[SEQ. ID. NO. 315]

IGF2R Leu252Val	GCCAGCCCCGGGACGGA	C	5479.6	GCCAGCCCCGGGACGGA
C/G	[SEQ. ID. NO. 316]			C [SEQ. ID. NO. 317]

MUC5AC-221	ATGGGTGTGTCTGCCGG	T	5570.6	ATGGGTGTGTCTGCCCGGA
C/T	[SEQ. ID. NO. 318]			[SEQ. ID. NO. 319]

Arg1 intron1 C/T	GGCTGTAAGGAAATCTGGG	T	6230.1	GGCTGTAAGGAAATCTGG
	[SEQ. ID. NO. 320]			GA [SEQ. ID. NO. 321]

REV1 Phe257Ser	CCTTATCCTCCTCCTGGGAA	T	6301.1	CCTTATCCTCCTCCTGGG
C/T	[SEQ. ID. NO. 322]			AAA [SEQ. ID. NO. 323]

Apex1 Asp148Glu	TGTTTCATTTCTATAGGCGA	T	6401.2	TGTTTCATTTCTATAGGCG
G/T	[SEQ. ID. NO. 324]			AT [SEQ. ID. NO. 325]

IL-10-1082 A/G	CCTATCCCTACTTCCCC	G	5250.4	CCTATCCCTACTTCCCCC
	[SEQ. ID. NO. 326]			[SEQ. ID. NO. 327]

Sequenom conditions for the polymorphisms genotyping-8

	EXT2_	EXT2_
SNP_ID	CALL	MASS	EXT2_SEQ	1stPAUSE

CTGF-447G/C	C	5716.7	AAAAGGTTTCTCCCCCCGA	5419.5
			[SEQ. ID. NO. 328]

NBS1 Gln185Glu	C	5818.8	AGGCTGCTTCTTGGACTGA	5521.6
G/C			[SEQ. ID. NO. 329]

MBL2 161 G/A	G	5901.9	CAAAGATGGGCGTGATGGC	5628.7
			[SEQ. ID. NO. 330]

IGF2R Leu252Val	G	5823.8	GCCAGCCCCGGGACGGAGT	5535.6
C/G			[SEQ. ID. NO. 331]

MUC5AC-221 C/T	C	5890.8	ATGGGTGTGTCTGCCGGGT	5602.6
			[SEQ. ID. NO. 332]

Arg1 intron1 C/T	C	6879.5	GGCTGTAAGGAAATCTGGGGGT	5262.1
			[SEQ. ID. NO. 333]

REV1 Phe257Ser	C	6630.3	CCTTATCCTCCTCCTGGGAAGA	6333.1
C/T			[SEQ. ID. NO. 334]

Apex1 Asp148Glu	G	7068.6	TGTTTCATTTCTATAGGCGAGGA	6442.2
G/T			[SEQ. ID. NO. 335]

IL-10-1082 A/G	A	5858.8	CCTATCCCTACTTCCCCTTC	5281.4
			[SEQ. ID. NO. 336]

Results

Frequencies of individual polymorphisms are as follows:

TABLE 11

Polymorphism allele and genotype frequencies in the
Lung cancer patients, resistant smokers and controls.

Nitric oxide synthase 3 Asp 298 Glu (T/G)

Frequency

Allele*

Genotype

	T	G	TT	TG	GG

Controls n = 183 (%)	108 (30%)	258 (70%)	13 (7%)	82 (45%)	88 (48%)
Lung Cancer n = 107 (%)	71 (33%)	143 (67%)	9 (8%)	53 (50%)	45 (42%)
Resistant n = 198 (%)	135 (34%)	261 (66%)	28^1,2(14%)	79 (40%)	91 (46%)

Nitric oxide synthase 3 −786 T/C

Frequency

Allele*

Genotype

	C	T	CC	CT	TT

Controls n = 183 (%)
Lung Cancer n = 107 (%)	82 (38%)	132 (62%)	16 (15%)	50 (47%)	41³(38%)
Resistant n = 198 (%)	166 (42%)	228 (58%)	31 (16%)	104 (53%)	62 (31%)

Super oxide dismutase 3 Arg 312 Gln C/G

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Controls n = 190 (%)	371 (98%)	9 (2%)	183 (96%)	5 (3%)	2 (1%)
Lung Cancer n = 104 (%)	208 (100%)	0 (0%)	104 (100%)	0 (0%)	0 (0%)
Resistant n = 182 (%)	390 (98%)	10 (3%)	191 (95%)	8⁴(4%)	1⁴(1%)

XRCC1 Arg 399 Gln A/G

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Controls n = 190 (%)
Lung Cancer n = 103 (%)	68 (33%)	138 (67%)	4 (4%)	60 (58%)	39 (38%)
Resistant n = 193 (%)	132 (34%)	254 (66%)	18⁵(9%)	96 (50%)	79 (41%)

Interleukin 8 −251 A/T

Frequency

Allele*

Genotype

	A	T	AA	AT	TT

Controls n = 188 (%)	175 (47%)	201 (53%)	39 (21%)	97 (52%)	52 (28%)
Lung Cancer n = 90	68 (38%)	112 (62%)	6 (7%)	56 (52%)	28 (31%)
Resistant n = 199 (%)	192⁷(48%)	206 (52%)	45⁶(23%)	102 (51%)	52 (26%)

Anti-chymotrypsin Ala −15 Thr

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Lung Cancer n = 108	99 (46%)	117⁹(54%)	24 (22%)	51 (47%)	33⁸(31%)
Resistant n = 196 (%)	207 (53%)	185 (47%)	52 (27%)	103 (53%)	41 (21%)

Cyclin D1 A 870 G

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Lung Cancer n = 107	109 (51%)	105 (49%)	25¹¹(23%)	59 (55%)	23 (21%)
Resistant n = 199 (%)	188 (47%)	210 (53%)	45 (23%)	98 (49%)	56¹⁰(28%)

Interleukin 1B −511 A/G

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Lung Cancer n = 107	64 (30%)	150 (70%)	12 (11%)	40 (37%)	55¹²(51%)
Resistant n = 198 (%)	143 (36%)	253 (64%)	23 (12%)	97 (49%)	78 (39%)

FAS (Apo-1/CD 95) A −670 G

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Lung Cancer n = 106	121¹⁴(57%)	91 (43%)	32¹³(30%)	57 (54%)	17 (16%)
Resistant n = 198 (%)	202 (51%)	194 (49%)	45 (23%)	112 (57%)	41 (21%)

XPD 751 T/G

Frequency

Allele*

Genotype

	G	T	GG	TG	TT

Lung Cancer n =108	72 (33%)	144 (66%)	11 (10%)	50 (46%)	47 (44%)
Resistant n = 197 (%)	147 (37%)	247 (63%)	31¹⁵(16%)	85 (43%)	81 (41%)

Cytochrome P450 1A1 Ile 462 Val G/A

Frequency

Allele*

Genotype

	G	A	GG	AG	AA

Lung Cancer n = 109	5 (2%)	213 (98%)	0 (0%)	5 (5%)	104¹⁶(95%)
Resistant n = 199 (%)	20 (5%)	378 (95%)	13¹⁶(1%)	18¹⁶(9%)	180²(90%)

MMP12 Asn 357 Ser

Frequency

Allele*

Genotype

	G	A	GG	AG	AA

Lung Cancer n = 109	8 (4%)	210 (96%)	1 (1%)	6 (5%)	102 (94%)
Resistant n = 199 (%)	21 (5%)	377 (95%)	0¹⁷(0%)	21¹⁷(11%)	178 (89%)

8-oxoguanine DNA glycosylase Ser 326 Cys C/G

Frequency

Allele*

Genotype

	G	C	GG	CG	CC

Lung Cancer n = 109	40 (18%)	178 (82%)	2 (2%)	36 (33%)	71 (55%)
Resistant n = 199 (%)	100 (25%)	298 (75%)	14¹⁸(7%)	72 (36%)	113 (57%)

N-Acetyltransferase 2 Arg 197 Gln G/A

Frequency

Allele*

Genotype

	A	G	AA	AG	GG

Lung Cancer n = 106	55 (26%)	157 (74%)	9 (8%)	37 (35%)	60¹⁹(57%)
Resistant n = 195 (%)	122 (31%)	268 (69%)	17 (9%)	88 (45%)	90 (46%)

Cytochrome P450 2E1 1019 G/C Pst1

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Lung Cancer n = 109	10 (5%)	208 (95%)	0 (0%)	10²⁰(9%)	99 (91%)
Resistant n = 197 (%)	11 (3%)	383 (97%)	0 (0%)	11 (6%)	186 (94%)

Cytochrome P450 2E1 C/T Rsa I

Frequency

Allele*

Genotype

	T	C	TT	TC	CC

Lung Cancer n = 108	11 (5%)	205 (95%)	0 (0%)	11²¹(10%)	97 (90%)
Resistant n = 198 (%)	11 (3%)	385 (97%)	0 (0%)	11 (6%)	187 (94%)

Interleukin 18 105 A/C

Frequency

Allele*

Genotype

	C	A	CC	AC	AA

Lung Cancer n = 107	50 (23%)	164 (77%)	8 (8%)	34 (33%)	65²²(61%)
Resistant n = 200 (%)	116 (29%)	284 (71%)	17²²(9%)	82²²(41%)	101 (50%)

Interleukin 18 −133 C/G

Frequency

Allele*

Genotype

	G	C	GG	CG	CC

Lung Cancer n = 109	52 (24%)	166 (76%)	8 (7%)	36 (33%)	65²³(60%)
Resistant n = 198 (%)	117 (30%)	279 (70%)	17²³(9%)	83²³(42%)	98 (49%)

Glutathione S-Transferase M null

		Frequency
		Allele*

	Null	Wild

Controls n = 178	75 (42%)	103 (58%)
Lung Cancer n = 107	67²⁴(58%)	48 (42%)
Resistant n = 182	100 (55%)	82 (45%)

Interferon-gamma 874 A/T

Frequency

Allele*

Genotype

	A	T	AA	AT	TT

Controls n = 186 (%)	183 (49%)	189 (51%)	37 (20%)	109 (58%)	40 (22%)
Lung cancer n = 106 (%)	116 (55%)	96 (45%)	34^25,26(32%)	48 (45%)	24 (23%)
Resistant n = 196 (%)	209 (53%)	183 (47%)	50 (26%)	109 (56%)	37 (19%)

Cyclooxygenase −765 C/G

Frequency

Allele*

Genotype

	C	G	CC	CG	GG

Controls n = 95 (%)	27 (14%)	161 (86%)	3 (3%)	21 (22%)	70 (75%)
Lung Cancer n = 109 (%)	34 (16%)	184 (84%)³⁰	5 (5%²⁷)	24 (22%)²⁷	80 (73%)²⁹
Resistant n = 158 (%)	75 (24%)²⁸	241 (76%)	11 (7%)	53 (34%)	94 (59%)

Matrix metalloproteinase 1 −1607 1G/2G

Frequency

Allele*

Genotype

	1G	2G	1G1G	1G2G	2G2G

Controls n = 174 (%)	214 (61%)	134 (39%)	68 (39%)	78 (45%)	28 (16%)
Lung Cancer n = 67 (%)	58 (43%)	76 (57%)³²	13 (19%)	32 (48%)	22 (33%)³¹
Resistant n = 171 (%)	167 (49%)	175 (51%)	41 (24%)	85 (50%)	45 (26%)

*number of chromosomes (2n)

1. Genotype. TT vs TG/GG for resistant vs lung cancer, Odds ratio (OR)=1.8, 95% confidence limits 0.8-4.3, χ²(Yates uncorrected)=2.14, p=0.14, TT genotype =protective
2. Genotype. TT vs TG/GG for resistant vs controls, Odd ratio (OR)=2.2, 95% confidence limits 1.0-4.6, χ²(Yates corrected)=4.2, p=0.04, TT genotype =protective
3. Genotype. TT vs CC/CT for Lung cancer vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.8-2.3, χ²(Yates uncorrected)=1.45, p=0.23, TT genotype =susceptible
4. Genotype CG/GG vs CC for resistant vs lung cancer, Yates uncorrected=3.38, P=0.07 and Fisher's Two tailed test, P=0.03. CG/GG=protective
5. Genotype. AA vs AG/GG for resistant vs lung cancer, Odds ratio (OR)=2.6, 95% confidence limits 0.8-9.2, χ²(Yates uncorrected)=2.89, p=0.09. AA genotype=protective
6. Genotype. A vs AT/TT for resistant vs lung cancer, Odds ratio (OR)=4.1, 95% confidence limits=1.6=11.2, χ²(Yates corrected)=9.8, p<0.002, AA=protective
7. Allele. A vs T for resistant smokers vs lung cancer, Odds ratio (OR)=1.5, 95% confidence limits 1.0-2.2, χ²(Yates corrected)=5.07, p=0.02, A=protective
8. Genotype. GG vs AA/AG for Lung cancer vs resistant, Odds ratio (OR)=1.7, 95% confidence limits=0.9-2.9, χ²(Yates uncorrected)=3.51, p=0.06, GG=susceptible
9. Allele. G vs A for lung cancer vs resistant smokers, Odds ratio (OR)=1.3, 95% confidence limits 0.9-1.9, χ²(Yates uncorrected)=2.71, p=0.10, G=susceptible
10. Genotype. GG vs AG/AA for Resistant vs lung cancer, Odds ratio (OR)=1.4, 95% confidence limits=0.8-2.6, χ²(Yates uncorrected)=1.6, p=0.20, GG=protective
11. Genotype. AG/AA vs GG for Lung cancer vs resistant, Odds ratio (OR)=1.4, 95% confidence limits=0.8-2.6, χ²(Yates uncorrected)=1.6, p=0.20, AA=susceptible
12. Genotype. GG vs AA/AG for Lung cancer vs resistant, Odds ratio (OR)=1.6, 95% confidence limits=1-2.7, χ²(Yates uncorrected)=4.07, p=0.04, GG=susceptible
13. Genotype. AA vs AG/GG for Lung cancer vs resistant, Odds ratio (OR)=1.5, 95% confidence limits=0.8-2.6, χ²(Yates uncorrected)=2.03, p=0.15, AA=susceptible
14. Allele. A vs G for Lung cancer vs resistant, Odds ratio (OR)=1.3, 95% confidence limits 0.9-1.8, χ²(Yates uncorrected)=2.04, p=0.15, A=susceptible
15. Genotype. GG vs TG/TT for Resistant vs lung cancer, Odds ratio (OR)=1.7, 95% confidence limits=0.8-3.7, χ²(Yates uncorrected)=1.81, p=0.18, GG=protective
16. Genotype. AG/GG vs AA for Resistant vs lung cancer, Odds ratio (OR)=2.2, 95% confidence limits=0.7-6.9, χ²(Yates uncorrected)=2.41, p=0.12, GG/AG =protective, AA=susceptible
17. Genotype. GG/AG vs AA for Resistant vs COPD, Odds ratio (OR)=1.7, 95% confidence limits=0.7-4.6, χ²(Yates uncorrected)=1.45, p=0.23, GG/AG =protective
18. Genotype. GG vs CG/CC for Resistant vs lung cancer, Odds ratio (OR)=4.0, 95% confidence limits=0.9-26.3, χ²(Yates uncorrected)=3.87, p=0.05, GG=protective
19. Genotype. GG vs AG/AA for Lung cancer vs resistant, Odds ratio (OR)=1.5, 95% confidence limits=0.9-2.5, χ²(Yates uncorrected)=3.0, p=0.08, GG=susceptible
20. Genotype. CG vs GG for Lung cancer and resistant, Odds ratio (OR)=1.7, 95% confidence limits=0.7-4.5, χ²(Yates uncorrected)=1.42, p=0.23, CG=susceptible
21. Genotype. TC vs CC for Lung cancer and resistant, Odds ratio (OR)=1.9, 95% confidence limits=0.8-5.0, χ²(Yates uncorrected)=2.24, p=0.13, TC=susceptible
22. Genotype. AA vs AC/CC for Lung cancer and resistant, Odds ratio (OR)=1.6, 95% confidence limits=1.0-2.6, χ²(Yates uncorrected)=3.51, p=0.06, AA =susceptible, AC/CC protective
23. Genotype. CC vs CG/GG for Lung cancer and resistant, Odds ratio (OR)=1.5, 95% confidence limits=0.9-2.5, χ²(Yates uncorrected)=2.90, p=0.09, CC =susceptible, CG/GG protective
24. Genotype. Null vs wild for Lung cancer and controls, Odds ratio (OR)=1.92, 95% confidence limits=1.2-3.2, χ²(Yates corrected)=6.64, p=0.01, Null =susceptible
25. Genotype. AA vs AT/TT for lung cancer vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.8-2.4, χ²(Yates uncorrected)=1.48, p=0.02, AA genotype=susceptible
26. Genotype. AA vs AT/TT for lung cancer vs controls, Odds ratio (OR)=1.9, 95% confidence limits 1.1-3.4, χ²(Yates corrected)=5.45, p=0.02, AA genotype=susceptible to lung cancer
27. Genotype. CC/CG vs GG for Lung cancer vs resistant, Odds ratio (OR)=0.53, 95% confidence limits=0.3-0.9, χ²(Yates corrected)=4.9, P=0.03 CC/CG=protective
28. Allele. C vs G for Lung cancer vs resistant, Odds ratio (OR)=0.59, 95% confidence limits 0.4-0.9, χ²(Yates corrected)=4.8, p=0.03, C=protective
29. Genotype. GG vs CG/CC for Lung cancer vs resistant, Odds ratio (OR)=1.88, 95% confidence limits=1.1-3.3, χ²(Yates corrected)=4.9, P=0.03 GG=susceptible (when compared against resistant smokers but not controls)
30. Allele. G vs C for Lung cancer vs resistant, Odds ratio (OR)=1.7, 95% confidence limits 1.1-2.7, χ²(Yates corrected)=4.8, p=0.03, G=susceptible (when compared against resistant smokers but not controls)
31. Genotype. 2G2G vs 1G1G/1G2G for Lung cancer vs controls, Odds ratio (OR) =2.55, 95% confidence limits 1.3-5.1, χ²(Yates corrected)=7.3, p=0.007 2G2G genotype=susceptible
32. Allele. 2G vs 1G for Lung cancer vs controls, Odds ratio (OR)=2.1, 95% confidence limits 1.4-3.2, χ²(Yates corrected)=12.3, p=0.0004, 2G=susceptible

Connective tissue growth factor (CTGF) −447

G/C polymorphism allele and genotype frequencies

in the lung cancer and resistant smokers.

Frequency

37. Allele*

38. Genotype

	G	C	GG	GC	CC

Lung cancer	201 (92%)	17 (8%)	92 (84%)	17 (16%)	0 (0%)
n = 109 (%)
Resistant	379 (95%)	21 (5%)	179 (90%)	21 (10%)	0 (0%)
n = 200 (%)

*number of chromosomes (2n)

1. Genotype. GC/CC vs GG for lung cancer vs resistant, Odds ratio (OR)=1.6, 95% confidence limits 0.8-3.3, χ²(Yates uncorrected)=1.70, p=0.19, GC/GG genotype=susceptibility (trend)

Mucin 5AC (Muc5AC) −221 C/T polymorphism allele and genotype

frequencies in the lung cancer and resistant smokers.

Frequency

39. Allele*

40. Genotype

	C	T	CC	CT	TT

Lung cancer n = 109	177	41	73	31	5
(%)	(81%)	(19%)	(67%)	(28%)	(5%)
Resistant n = 195	296	94	119	58	18
(%)	(76%)	(24%)	(61%)	(30%)	(9%)

*number of chromosomes (2n)

1. Genotype. TT vs CC/CT for lung cancer vs resistant, Odds ratio (OR)=0.47, 95% confidence limits 0.2-1.4, χ²(Yates uncorrected)=2.16, p=0.14, TT genotype=protective (trend)

Mannose binding lectin (MBL2) 161 G/A polymorphism allele and

genotype frequencies in the lung cancer and resistant smokers.

Frequency

41. Allele*

42. Genotype

	G	A	GG	AG	AA

Lung cancer n = 105	173	37	71	31	3
(%)	(82%)	(18%)	(67%)	(30%)	(3%)
Resistant n = 197	338	56	147	44	6
(%)	(86%)	(14%)	(75%)	(22%)	(3%)

*number of chromosomes (2n)

1. Genotype. AG/AA vs GG for lung cancer vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.8-2.4, χ²(Yates uncorrected)=1.67, p=0.20, AG/AA genotype=susceptibility (trend)

Nibrin (NBS1) Gln185Glu G/C polymorphism allele and genotype

frequencies in the lung cancer and resistant smokers.

Frequency

43. Allele*

44. Genotype

	G	C	GG	GC	CC

Lung cancer n = 109	150	68	54	42	13
(%)	(69%)	(31%)	(50%)	(39%)	(12%)
Resistant n = 199	295	103	107	81	11
(%)	(74%)	(26%)	(54%)	(41%)	(6%)

*number of chromosomes (2n)

1. Genotype. CC vs CG/GG for lung cancer vs resistant, Odds ratio (OR)=2.3, 95% confidence limits 0.9-5.8, χ²(Yates uncorrected)=4.01, p=0.05, CC genotype=susceptibility

Arginase 1 (Arg1) Intron 1 C/T polymorphism allele and genotype

frequencies in the lung cancer and resistant smokers.

Frequency

45. Allele*

46. Genotype

	C	T	CC	CT	TT

Lung cancer n = 105	137	73	45	47	13
(%)	(65%)	(35%)	(43%)	(45%)	(12%)
Resistant n = 180	203	157	65	73	42
(%)	(56%)	(44%)	(36%)	(41%)	(23%)

*number of chromosomes (2n)

1. Genotype. TT vs CC/CT for lung cancer vs resistant, Odds ratio (OR)=0.46, 95% confidence limits 0.2-0.95, χ²(Yates uncorrected)=5.11, p=0.02, TT genotype=protective
2. Allele. T vs C for lung cancer vs resistant, Odds ratio (OR)=0.69, 95% confidence limits 0.5-1.0, χ²(Yates corrected)=3.96, p=0.05, T allele=protective

REV1 Phe257Ser C/T polymorphism allele and genotype

frequencies in the lung cancer and resistant smokers.

Frequency

47. Allele*

48. Genotype

	C	T	CC	CT	TT

Lung cancer n = 109	129	89	39	51	19
(%)	(59%)	(41%)	(36%)	(47%)	(17%)
Resistant n = 192	242	142	83	76	33
(%)	(63%)	(37%)	(43%)	(40%)	(17%)

*number of chromosomes (2n)

1. Genotype. CC vs CT/TT for lung cancer vs resistant, Odds ratio (OR)=0.73, 95% confidence limits 0.4-1.2, χ²(Yates uncorrected)=1.6, p=0.20, CC genotype=protective (trend)

Insulin-like growth factor II receptor (IGF2R) Leu252Val

C/G polymorphism allele and genotype frequencies

in the lung cancer and resistant smokers.

Frequency

49. Allele*

50. Genotype

	C	G	CC	CG	GG

Lung cancer n = 109	190	28	82	26	1
(%)	(87%)	(13%)	(75%)	(24%)	(1%)
Resistant n = 198	342	54	150	42	6
(%)	(86%)	(14%)	(76%)	(21%)	(3%)

*number of chromosomes (2n)

1. Genotype. GG vs CC/CG for lung cancer vs resistant, Odds ratio (OR)=0.30, 95% confidence limits 0.01-2.5, χ²(Yates uncorrected)=1.41, p=0.22 (1-tailed t-test), GG genotype=protective (trend)

Apex nuclease (APE1) Asp148Glu T/G polymorphism

allele and genotype frequencies in the

lung cancer and resistant smokers.

Frequency

51. Allele*

52. Genotype

	T	G	TT	TG	GG

Lung cancer n = 109	124	94	39	46	24
(%)	(57%)	(43%)	(36%)	(42%)	(22%)
Resistant n = 192	229	155	69	91	32
(%)	(60%)	(40%)	(36%)	(47%)	(17%)

*number of chromosomes (2n)

1. Genotype. GG vs TT/Tg for lung cancer vs resistant, Odds ratio (OR)=1.4, 95% confidence limits 0.8-2.7, χ²(Yates uncorrected)=1.3, p=0.25, GG genotype=susceptibility (trend)

Interleukin 10 (IL-10) −1082 A/G polymorphism allele and

genotype frequencies in the lung cancer and resistant smokers.

Frequency

53. Allele*

54. Genotype

	G	C	GG	GC	CC

Lung cancer n = 98	91	105	16	59	23
(%)	(46%)	(54%)	(16%)	(60%)	(24%)
Resistant n = 196	174	218	40	94	62
(%)	(44%)	(56%)	(20%)	(48%)	(32%)

*number of chromosomes (2n)

1. Genotype. GG vs GC/CC for lung cancer vs resistant, Odds ratio (OR)=0.66, 95% confidence limits 0.4-1.2, χ²(Yates uncorrected)=2.12, p=0.15, GG genotype=protective (trend)
Table 12 below provides a summary of the protective and susceptibility polymorphisms determined for lung cancer.

TABLE 12

Summary of protective and susceptibility polymorphism in Lung Cancer
patients relative to resistant smokers (with normal lung function)

Gene	Polymorphism	Role

Nitric Oxide synthase 3 (NOS3)	NOS3 Asp 298 Glu	TT protective
Nitric Oxide synthase 3 (NOS3)	NOS3 −786 T/C	TT susceptible
Superoxide dismutase 3 (SOD3)	SOD3 Arg 312 Gln	CG/GG protective
XRCC1	XRCC1 Arg 399 Gln G/A	AA protective
Interleukin-8 (IL-8)	IL-8 −251 A/T	AA protective
Anti-chymotrypsin (ACT)	ACT Ala 15 Thr	GG susceptible
Cyclin D (CCND1)	CCND1 A870G	GG protective
		AA susceptible
Interleukin 1B (IL-1B)	IL-1B −511 A/G	GG susceptible
FAS (Apo-1/CD95)	FAS A-670G	AA susceptible
XPD	XPD −751 G/T	GG protective
CYP 1A1	CYP 1A1 Ile 462 Val	GG/AG protective
	A/G	AA susceptible
Matrix metalloproteinase 12	MMP12 Asn 357 Ser	GG/AG protective
(MMP12)	A/G
8-Oxoguanine DNA glycolase	OGG1 Ser 326 Cys G/C	GG protective
(OGG1)
N-acetyltransferase 2 (NAT2)	NAT2 Arg 197 Gln A/G	GG susceptible
CYP2E1	CYP2E1 1019 G/C Pst I	CC/CG
		susceptible
CYP2E1	CYP2E1 C/T Rsa I	TT/TC
		susceptible
Interleukin-18 (IL-18)	IL-18 105 A/C	AC/CC protective
		AA susceptible
Interleukin-18 (IL-18)	IL-18 −133 G/C	CG/GG protective
		CC susceptible
Glutathione S-transferase M	GSTM null	Null
		susceptible
Interferon gamma (IFN?)	IFN? 874 A/T	AA susceptible
Cyclo-oxygenase 2 (COX2)	COX2 −765 G/C	CC/CG protective
		GG susceptible
Matrix metalloproteinase 1 (MMP1)	MMP −1607 1G/2G	2G2G
		susceptible
Connective tissue growth factor	CTGF −447 G/C	GC/CC
(CTGF)		susceptible
Mucin 5AC (MUC5AC)	MUC5AC −221 C/T	TT protective
Mannose binding lectin 2 (MBL2)	MBL2 +161 G/A	AG/AA
		susceptible
Nibrin (NBS1)	NBS1 Gln185Glu G/C	CC susceptible
Arginase 1 (Arg1)	Arg1 intron 1 C/T	TT protective
REV1	REV1 Phe257Ser C/T	CC protective
Insulin-like growth factor II receptor	IGF2R Leu252Val C/G	GG protective
(IGF2R)
Apex nuclease (Apex or APE1))	Apex Asp148Glu G/T	GG susceptible
Interleukin 10 (IL-10)	IL-10 −1082 A/G	GG protective

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGG1 GG, CCND1 GG, NOS3 298 TT, IL-8 AA, and XRCC1 AA observed in the subjects with lung cancer and in resistant smokers is presented below in Table 13.

TABLE 13

Combined frequencies of the presence or absence of selected protective
genotypes in subjects with lung cancer and in resistant smokers.

Number of protective polymorphisms

Cohorts

	0	1	=2	Total

Lung Cancer	66 (61%)	37 (34%)	6 (6%)	109
Resistant smokers	71 (36%)	86 (43%)	42 (21%)	199
% of smokers with	66/137 (48%)	37/123 (30%)	6/42 (14%)
Lung cancer

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist	—	—	22.3	<0.0001
vs Lung cancer
2+ vs 0-1, Resist	4.6	1.8-12.5	11.87	0.0005
vs Lung cancer
0 vs 2+, Lung cancer	2.8	1.7-4.6	16.7	<0.0001
vs Resist

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA, IL-1B GG, and ACT 15 GG, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 14.

TABLE 14

Combined frequencies of the presence or absence of selected susceptibility
genotypes in subjects with lung cancer and in resistant smokers.

Number of susceptibility polymorphisms

Cohorts

	0	1	=2	Total

Lung Cancer	21 (19%)	52 (48%)	35 (33%)	108
Resistant smokers	71 (36%)	85 (43%)	42 (21%)	198
% of smokers with	21/92 (23%)	52/137 (38%)	35/77 (45%)
COPD

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Lung cancer	—	—	10.2	0.006
vs Resist
2+ vs 0-1, Lung cancer	1.8	1.0-3.1	4.1	0.04
vs Resist
0+ vs 1-2+, Resist	2.3	1.3-4.2	8.2	0.004
vs COPD

The combined frequencies of the presence or absence of the selected protective genotypes CYP1A1 GG/AG, OGG1 GG, CCND1 GG, NOS3 298 TT, SOD3 CG/GG, XPD GG, MMP12 GG/AG, and XRCC1 AA observed in the subjected with lung cancer and in resistant smokers is presented below in Table 15.

TABLE 15

Combined frequencies of the presence or absence of selected protective
genotypes in subjects with lung cancer and in resistant smokers.

Number of protective polymorphisms n = 8

Cohorts	0	1	=2	Total

Lung Cancer	54 (50%)	50 (46%)	5 (4%)	109
Resistant smokers	67 (34%)	83 (42%)	50 (25%)	199
% of smokers with	54/121 (45%)	50/133 (38%)	5/55 (9%)
Lung cancer

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist	—	—	21.5	<0.0001
vs Lung cancer
2+ vs 0-1, Resist	6.9	2.5-20.5	18.7	<0.0001
vs Lung cancer
0 vs 2+, Lung cancer	2.0	1.2-3.2	6.96	0.008
vs Resist

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA, IL-1B, ACT 15 GG, NAT2 GG, IL-18 105 AA, and IFN? AA, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 16.

TABLE 16

Combined frequencies of the presence or absence of selected susceptibility
genotypes in subjects with lung cancer and in resistant smokers.

Number of susceptibility polymorphisms n = 7

Cohorts	1	2	=3	Total

Lung Cancer	16 (15%)	35 (32%)	58 (53%)	109
Resistant smokers	65 (33%)	66 (33%)	69 (34%)	200
% of smokers with	16/81 (20%)	35/101 (35%)	58/127 (46%)
COPD

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Lung cancer	—	—	14.6	0.0007
vs Resist
3+ vs 1-2, Lung cancer	2.2	1.3-5.6	9.4	0.002
vs Resist
1 vs 2-3+, Resist	2.8	1.5-5.4	10.7	0.001
vs COPD

The combined frequencies of the presence or absence of the selected protective genotypes GYP1A1 GG/AG, OGG1 GG, CCND1 GG, NOS3 298 TT, IL-8 AA, XRCC1 AA, and Cox 2 −765 CC/CG, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 17.

TABLE 17

Combined frequencies of the presence or absence of protective genotypes in
the exposed smoking subjects (Lung cancer subjects and resistant smokers).

Number of protective genotypes

Cohorts

	0	1	=2	Total

Lung Cancer	45 (40%)	50 (43%)	19 (17%)	114
Resistant smokers	47 (23%)	79 (40%)	74 (37%)	200
% of smokers with	45/92 (49%)	50/129 (39%)	19/93 (20%)
Lung cancer

Comparison	Odd's ratio	95% CI	?2	P value

0 vs 1 vs 2+, Resist	—	—	16.8	0.0002
vs Lung cancer
2+ vs 0-1, Resist	2.94	1.6-5.4	13.44	0.0002
vs Lung cancer
0 vs 2+, Lung cancer	2.12	1.3-3.6	8.2	0.004
vs Resist

The combined frequencies of the presence or absence of the selected susceptibility genotypes CYP2E1 1019 CC/CG, FAS AA, IL-B1 GG, ACT 15 GG, and MMP1 2G2G, observed in the subjects with lung cancer and in resistant smokers is presented below in Table 18.

TABLE 18

Combined frequencies of the presence or absence of susceptibility genotypes
in the exposed smoking subjects (Lung cancer subjects and resistant smokers).

Number of suceptibility genotypes

Cohorts	0-1	2-3	4-6	Total

Lung Cancer	13 (12%)	66 (61%)	30 (28%)	109
Resistant smokers	54 (27%)	113 (56%)	33 (17%)	200
% of smokers with	13/67 (19%)	66/179 (37%)	30/63 (48%)
COPD

Comparison	Odd's ratio	95% CI	?2	P value

0-1 vs 2-3 vs 4-6, Lung cancer	—	—	11.8	0.003
vs Resist
4-6 vs rest, Lung cancer	1.9	1.0-3.5	4.6	0.03
vs Resist
0-1 vs rest, Resist	2.7	1.4-5.6	8.6	0.003
vs COPD

Protective polymorphisms were assigned a score of −1while susceptibility polymorphisms were assigned a score of +1. For each subject, a net score was then calculated according to the presence of susceptibility and protective genotypes. This produced a linear spread of values, as shown in Table 14. When assessed as a range between −2 to +4, a linear relationship as depicted in FIG. 4 was observed. This analysis indicates that for subjects with a net score of −2 or less, there was a minimal risk of having lung cancer. For subjects with a net score of −1, there was an approximately one in ten risk of having lung cancer. In contrast, for subjects with a net score of 4+ of greater, the risk was markedly increased to over 70% (see Table 19 and FIG. 4). It is noted that for FIG. 4, unlike the data presented in FIG. 3, the protective polymorphisms are assigned a negative value while the susceptibility polymorphisms are assigned a positive value. The precise value or sign given to each one is not critical, as long as it is consistent between the types of polymorphisms.

TABLE 19

Combined presence or absence of protective and
susceptibility polymorphisms

	Score combining protectuve (−1) and
	susceptibility (+1) polymorphisms

	−2	−1	0	1	2	3	4+

Lung cancer	0	2	10	21	38	23	15
N = 109 (%)	(0%)	(2%)	(9%)	(19%)	(35%)	(21%)	(14%)
Resistant smokers	6	21	39	51	52	25	6
N = 200 (%)	(3%)	(11%)	(20%)	(26%)	(26%)	(13%)	(3%)
% Lung cancer	0%	9%	20%	29%	42%	48%	71%

A further combined analysis was performed using a greater number of polymorphisms. Again, this produced a linear spread of values (Table 20). When assessed as a range between −3 to +5, a linear relationship as depicted in FIG. 5 was observed. This analysis indicates that for subjects with a net score of −2 or less, there was a minimal risk of having lung cancer. In contrast, for subjects with a net score of 5+ or greater, the risk was markedly increased to 80% (see Table 20 and FIG. 5).

TABLE 20

Combined presence or absence of protective and susceptibility polymorphisms

	SNP score for Lung cancer according to the presence of
	protective(−1) and susceptibility (+1) genotypes for all smokers

Cohorts	<−3	−2	−1	0	1	2	3	4	5+

Lung cancer	0	1	3	10	25	32	20	14	4
N = 109	(0%)	(1%)	(3%)	(9%)	(23%)	(29%)	(18%)	(13%)	(4%)
Resistand smokers	3	12	16	34	58	48	21	7	1
N = 200	(2%)	(6%)	(8%)	(17%)	(29%)	(24%)	(11%)	(4%)	(0.5%)
% Lung cancer	0%	7%	16%	23%	30%	40%	49%	67%	80%

Discussion

The methods of the invention allow the determination of risk of disease to be assessed. For example, a simple scoring system in which each polymorphism in a category (i.e. protective or susceptibility) is assigned the same value allows the combined effects of all potentially relevant polymorphisms to be factored into the analysis. In other embodiments, the methods of the invention utilize a scoring system with adjustment (weighting) for the magnitude of the effect of each individual polymorphism, and again allow all polymorphisms to be simultaneously analyzed.
In other embodiments, analyses can utilise path analysis and/or Monte-Carlo analysis where the non-genetic and genetic factors can be analyzed.
Similar results were observed in comparing the presence or absence of susceptibility and resistant polymorphisms in smokers with OCOPD, and in smokers with lung cancer and resistant smokers.
The benefit of a net susceptibility score, having been determined for a subject is that is provides the opportunity for early prophylactic and/or therapeutic intervention. Such intervention can be as simple as communicating the net susceptibility score to the subject together with an explanation of the implications of that score. This alone can cause a lifestyle or occupational change, with the resultant beneficial effect for the subject.
Other, more direct approaches to prophylaxis or therapy can also be followed. These can include pharmaceutical or other medicaments being administered directed at favorably altering the net score of the subject together with such approaches as discussed herein.
Table 21 below presents representative examples of polymorphisms in linkage disequilibrium with the polymorphisms specified herein. Examples of such polymorphisms can be located using public databases, such as that available online at world wide web dot hapmap dot org. Specified polymorphisms are indicated in the columns marked SNP NAME. Unique identifiers are indicated in the columns marked RS NUMBER.

TABLE 21

Polymorphisms reported to be in linkage disequilibrium (unless stated) with
examples of specified polymorphism.


























(1 = no other SNPs reported to be in LD,
2 = no other SNPS reported to be in LD)

INDUSTRIAL APPLICATION

The present invention is directed to methods for assessing a subject's risk of developing a disease. The methods include the analysis of polymorphisms herein shown to be associated with increased or decreased risk of developing a disease, or the analysis of results obtained from such an analysis, and the determination of a net risk score. Methods of treating subjects at risk of developing a disease herein described are also provided. Additional information regarding the above material, or subparts thereof, can be found in U.S. patent application Ser. No. 10/479,525, filed Jun. 16, 2004; and PCT Application No. PCT/NZ02/00106, filed Jun. 5, 2002, which further designates New Zealand Application No. 512169, filed Jun. 5, 2001; New Zealand Application No. 513016, filed Jul. 17, 2001, and New Zealand Application No. 514275, filed Sep. 18, 2001, all of which are incorporated by reference in their entireties. Additional information can also be found in PCT application Nos. ______ and ______, filed May 10, 2006, entitled “Methods and Compositions for Assessment of Pulmonary Function and Disorders” and “Methods of Analysis of Polymorphisms and Uses Thereof” respectively, having Agent Reference Nos. 542813JBM and 542814JBM respectively, both of whihc are incorporated in their entireties by reference. PCT Application Agent Reference No. 5428143JBM claims priority to: NZ application No. 539934, filed May 10, 2005; NZ application No. 541935, filed Aug. 19, 2005; and JP application No. 2005-360523, filed Dec. 14, 2005, all of which are incorporated by reference in their entireties. PCT Application Agent Reference No. 542814JBM claims priority to: NZ application No. 540249, filed May 20, 2005 and NZ application No. 541842, filed Aug. 15, 2005, all of which are incorporated in their entireties by reference. Additional information can also be found in U.S. patent application Ser. No. ______, filed concurrently with the instant application, entitled “Methods and Compositions for Assessment of Pulmonary Function and Disorders”, attorney docket No: SGENZ.013AUS, incorporated by reference in its entirety.

PUBLICATIONS

1. Sandford A J, et al., 1999, Z and S mutations of the α1-antitrypsin gene and the risk of chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol. 20; 287-291.
2. Maniatis T., Fritsch, E. F. and Sambrook, J., Molecular Cloning Manual. 1989.
3. Papafili A, et al., 2002. Common promoter variant in cyclooxygenase-2 represses gene expression. Arterioscler Thromb Vasc Biol. 20; 1631-1635.
4. Ukkola, O., Erkkilä, P. H. Savolainen, M. J. & Kesäniemi, Y. A. 2001. Lack of association between polymorphisms of catalase, copper zinc superoxide dismutase (SOD), extracellular SOD and endothelial nitric oxide synthase genes and macroangiopathy in patients with type 2 diabetes mellitus. J Int Med 249; 451-459.
5. Smith C A D & Harrison D J, 1997. Association between polymorphism in gene for microsomal epoxide hydrolase and susceptibility to emphysema. Lancet. 350; 630-633.
6. Lorenz E, et al., 2001. Determination of the TLR4 genotype using allele-specific PRC Biotechniques. 31; 22-24.
7. Cantlay A M, Smith C A, Wallace W A, Yap P L, Lamb D, Harrison D J. Heterogeneous expression and polymorphic genotype of glutathione S-transferases in human lung. Thorax. 1994, 49(10):1010-4.
All patents, publications, scientific articles, and other documents and materials referenced or mentioned herein are indicative of the levels of skill of those skilled in the art to which the invention pertains, and each such referenced document and material is hereby incorporated by reference to the same extent as if it had been incorporated by reference in its entirety individually or set forth herein in its entirety. Any and all materials and information from any such patents, publications, scientific articles, web sites, electronically available information, and other referenced materials or documents can be physically incorporated into this specification.
The specific methods and compositions described herein are representative of various embodiments or preferred embodiments and are exemplary only and not intended as limitations on the scope of the invention. Other objects, aspects, examples and embodiments will occur to those skilled in the art upon consideration of this specification, and are encompassed within the spirit of the invention as defined by the scope of the claims. It will be readily apparent to one skilled in the art that varying substitutions and modifications can be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably can be practiced in the absence of any element or elements, or limitation or limitations, which is not specifically disclosed herein as essential. Thus, for example, in each instance herein, in embodiments or examples of the present invention, any of the terms “comprising”, “consisting essentially of”, and “consisting of” can be replaced with either of the other two terms in the specification, thus indicating additional examples, having different scope, of various alternative embodiments of the invention. Also, the terms “comprising”, “including”, “containing”, etc. are to be read expansively and without limitation. The methods and processes illustratively described herein suitably can be practiced in different orders of steps, and that they are not necessarily restricted to the orders of steps indicated herein or in the claims. It is also that as used herein and in the appended claims, the singular forms “a”, “an,” and “the” include plural reference unless the context clearly dictates otherwise. Thus, for example, a reference to “a host cell” includes a plurality (for example, a culture or population) of such host cells, and so forth. Under no circumstances may the patent be interpreted to be limited to the specific examples or embodiments or methods specifically disclosed herein. Under no circumstances may the patent be interpreted to be limited by any statement made by any Examiner or any other official or employee of the Patent and Trademark Office unless such statement is specifically and without qualification or reservation expressly adopted in a responsive writing by the Applicant.
The terms and expressions that have been employed are used as terms of description and not of limitation, and there is no intent in the use of such terms and expressions to exclude any equivalent of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention as claimed. Thus, it will be understood that although the present invention has been specifically disclosed by preferred embodiments and optional features, modification and variation of the concepts herein disclosed can be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention as defined by the appended indicative claims.
The invention has been described broadly and generically herein. Each of the narrower species and subgeneric groupings falling within the generic disclosure also form part of the invention. This includes the generic description of the invention with a proviso or negative elimination removing any subject matter from the genus, regardless of whether or not the excised material is specifically recited herein.
Other embodiments are within the following indicative claims. In addition, where features or aspects of the invention are described in terms of Markush groups, those skilled in the art will recognize that the invention is also thereby described in terms of any individual member or subgroup of members of the Markush group.

OCOPD n = 124

Resistant n = 101

1. A method of assessing a subject's risk of developing a disease which comprises:

analysing a biological sample from said subject for the presence or absence of a protective polymorphism and for the presence or absence of a susceptibility polymorphism, wherein said protective polymorphism and said susceptibility polymorphism are associated with said disease;

assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa;

calculating a net score for said subject, said net score representing the balance between the combined value of the protective polymorphism and the combined value of the susceptibility polymorphism present in the subject sample;

wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of an increased risk of developing said disease.

2. A method according to claim 1 wherein the value assigned to each protective polymorphism is the same.

3-25. (canceled)

26. A method of determining a subject's risk of developing a disease, said method comprising:

obtaining the result of one or more analyses of a sample from said subject to determine a presence or absence of a protective polymorphism and a presence or absence of a susceptibility polymorphism, and wherein said protective susceptibility polymorphisms are associated with said disease;

assigning a positive score for each protective polymorphism and a negative score for each susceptibility polymorphism or vice versa; and

calculating a net score for said subject, said net score representing a balance between a combined value of the protective polymorphism and a combined value of the susceptibility polymorphism present in the subject sample,

wherein a net protective score is predictive of a reduced risk of developing said disease and a net susceptibility score is predictive of a increased risk of developing said disease.

27. (canceled)

28. A method of treatment of a subject to decrease a risk of developing a disease through alteration of the net score for said subject as determined by a method as defined above, wherein said method of treatment comprises:

reversing, genotypically or phenotypically, the presence and/or functional effect of one or more susceptibility polymorphisms associated with said disease; and or

replicating and/or mimicking, genotypically or phenotypically, the presence and/or functional effect of one or more protective polymorphisms associated with said disease

3) a) reversing, genotypically or phenotypically, the presence, functional effect, or presence and functional effect of one of more susceptibility polymorphisms associated with said disease and

b) replicating, mimicking, or replicating and mimicking, genotypically or phenotypically, the presence, functional effect, or presence an functional effect of one or more protective polymorphisms associated with said disease.

29. (canceled)