Abstract
Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein’s heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.
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Data availability
The full genome-wide summary association statistics for the 184 proteins are publicly available at https://doi.org/10.7488/ds/7522; cis-eQTL summary-level data by eQTLGen, https://eqtlgen.org/cis-eqtls.html; GTEx data, https://gtexportal.org/home/datasets; 1000 Genomes phase 3 genotype data, https://www.cog-genomics.org/plink/2.0/resources#phase3_1kg; Neale’s lab UK Biobank round 2 GWAS summary-level data, http://www.nealelab.is/uk-biobank; Psychiatric Genomics Consortium (PGC) summary-level data, https://pgc.unc.edu/for-researchers/download-results/; DrugBank, https://www.drugbank.com; and Drugs.com, https://www.drugs.com. Source data are provided with this paper.
Code availability
Software used included METAL (https://genome.sph.umich.edu/wiki/METAL_Documentation), PLINK (https://www.cog-genomics.org/plink/), GenABEL (https://cran.r-project.org/src/contrib/Archive/GenABEL/), GCTA-GSMR (https://yanglab.westlake.edu.cn/software/gsmr/), PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk), MendelianRandomization (https://cran.r-project.org/web/packages/MendelianRandomization/index.html), coloc (https://chr1swallace.github.io/coloc/index.html), locuszoom (http://locuszoom.org/) and FUMA (https://fuma.ctglab.nl).
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Acknowledgements
X.S. was in receipt of a National Key Research and Development Program grant (numbers 2022YFF1202100 and 2022YFF1202105), a National Natural Science Foundation of China (NSFC) grant (number 12171495), a Natural Science Foundation of Guangdong Province grant (number 2021A1515010866) and Swedish Research Council (Vetenskapsrådet) grants (numbers 2017-02543 and 2022-01309). P.R.H.J.T. and J.F.W. acknowledge support from the Medical Research Council Human Genetics Unit Program grant ‘Quantitative Traits in Health and Disease’ (U. MC_UU_00007/10). The work of D.M., A.T., S.S. and Y.S.A. was supported by the Research Program at the Moscow State University (MSU) Institute for Artificial Intelligence. The work from X.F. was supported by the China Postdoctoral Science Foundation (number 2023M740690 and 2024T170174). The work from T.L. was supported by the China Postdoctoral Science Foundation (number 2023M740696). The work from C.K. and A.P.R. was supported in part by NIH grant R01-HL136574. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper. We thank the members of the SCALLOP Consortium of genome-wide association studies for making their data available. Cohort-specific acknowledgements are given in Supplementary Information.
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Contributions
X.S., P.N. and J.F.W. initiated and coordinated the study. L.R. performed the GWAS meta-analysis. J.C. conducted the colocalization analysis. Z.Y. conducted the Mendelian randomization analysis. R.Z. performed the drug target investigations. P.R.H.J.T., X.F., T.L., F.T., E.L.T., P.N. and X.S. contributed to the analysis pipeline. Y.Y. contributed to the cross-referencing prediction analysis. D.M. and A.T. contributed to the colocalization data processing and analysis. S.S. and Y.S.A. were involved in planning and supervising the work of D.M. and A.T. S.M.-W., M.D.M., B.P.P., A.J., R.F.H., E.W., S.K., S.A., L.P., Y.H., G.P., C.K., J.E.P., U.G., S.E.H., N.J.W., C. Lagging, M.A.I., A. Gilly, A. Göteson, M.K., E.T., J.H., A.P.R., G.D., E.Z., M.L., C.M.V.D., C.J., C. Langenberg, I.J.D., R.E.M., S.E., A.S.B. and A.M. contributed to the cohort-level analysis. L.R., J.C., Z.Y., R.Z., P.N. and X.S. wrote the paper. All authors approved the submitted version of the paper.
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Competing interests
P.R.H.J.T. is a salaried employee of BioAge Labs, Inc. R.E.M. has received a speaker fee from Illumina, is an advisor to the Epigenetic Clock Development Foundation and is a scientific consultant for Optima Partners. E.W. is now an employee of AstraZeneca. Y.S.A. is now an employee of GSK. A.S.B. has received grants from AstraZeneca, Bayer, Biogen, BioMarin and Sanofi. A.M. is an employee of Pfizer. X.S. is the founder of Quantix BioSciences and has received a speaker fee from Olink Proteomics. The remaining authors declare no competing interests.
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IRBs/Ethics Statement, cohort-specific acknowledgements, analysis plan for the GWAS meta-analysis, Supplementary tables descriptions 1–30 and Figs. 1–11.
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Repetto, L., Chen, J., Yang, Z. et al. The genetic landscape of neuro-related proteins in human plasma. Nat Hum Behav 8, 2222–2234 (2024). https://doi.org/10.1038/s41562-024-01963-z
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DOI: https://doi.org/10.1038/s41562-024-01963-z
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