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Abstract
Despite the increasing global burden of neurological disorders, there is a lack of effective diagnostic and therapeutic biomarkers. Proteins are often dysregulated in disease and have a strong genetic component. Here, we carry out a protein quantitative trait locus analysis of 184 neurologically-relevant proteins, using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In doing so, we elucidate the genetic landscape of the circulating proteome and its connection to neurological disorders. We detect 214 independently-associated variants for 107 proteins, the majority of which (76%) are cis-acting, including 114 variants that have not been previously identified. Using two-sample Mendelian randomisation, we identify causal associations between serum CD33 and Alzheimer’s disease, GPNMB and Parkinson’s disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting drug repurposing opportunities.
Serum proteins are easily accessible biomarkers and drug targets. Here, the authors use whole genome sequencing data to describe the genetic architecture of neurologically-relevant serum proteins and establish causal protein-neurological disease relationships.
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1 Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Translational Genomics, Neuherberg, Germany (GRID:grid.4567.0) (ISNI:0000 0004 0483 2525); Technical University of Munich and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany (GRID:grid.6936.a) (ISNI:0000000123222966)
2 Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Translational Genomics, Neuherberg, Germany (GRID:grid.4567.0) (ISNI:0000 0004 0483 2525)
3 University of Edinburgh, Centre for Global Health Research, Usher Institute, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
4 University of Edinburgh, MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
5 University of Edinburgh, Centre for Global Health Research, Usher Institute, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988); Fudan University, Greater Bay Area Institute of Precision Medicine (Guangzhou), Guangzhou, China (GRID:grid.8547.e) (ISNI:0000 0001 0125 2443); Karolinska Institute, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626)
6 University of Cambridge, MRC Epidemiology Unit, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000000121885934)
7 University of Cambridge, MRC Epidemiology Unit, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000000121885934); Computational Medicine, Berlin Institute of Health (BIH), Charité University Medicine, Berlin, Germany (GRID:grid.484013.a)
8 Anogia Medical Centre, Anogia, Greece (GRID:grid.484013.a)
9 Echinos Medical Centre, Echinos, Greece (GRID:grid.484013.a)
10 School of Health Science and Education, Harokopio University of Athens, Department of Nutrition and Dietetics, Athens, Greece (GRID:grid.15823.3d) (ISNI:0000 0004 0622 2843)
11 Karolinska Institute, Department of Medicine, Solna, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626); Emerging Science & Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, USA (GRID:grid.4714.6)
12 University of Edinburgh, Centre for Global Health Research, Usher Institute, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988); University of Edinburgh, MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)