A Mendelian randomization study identifies proteins involved in neurodegenerative diseases

Proteins are involved in multiple biological functions. High-throughput technologies have allowed the measurement of thousands of proteins in population biobanks. In this study, we aimed to identify proteins related to Alzheimer's disease (AD), Parkinson's disease (PD), Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) using large-scale genetic and proteomic data. We performed a two-sample cis Mendelian randomization (MR) study by selecting instrumental variables for the abundance of over 2,700 proteins measured by either Olink or SomaScan platforms in plasma from UK Biobank and the deCODE Health Study. We also used the latest publicly-available GWAS for the diseases of interest. The potentially causal effect of proteins on neurodegenerative diseases was estimated based on the Wald ratio. We tested 10,244 protein-disease associations, identifying 122 associations which were statistically significant (5% false discovery rate). Out of 57 associations (58%) tested using an instrumental variable from both Olink and SomaScan platforms, 33 (58%) were statistically significant in both platforms. Evidence of co-localisation between plasma protein abundance and disease risk (posterior probability >0.80) was identified for 46 protein-disease pairs. Twenty-three out of 46 protein-disease associations correspond to genetic loci not previously reported by genome-wide association studies. The newly-associated proteins for AD are involved in complement (C1S, C1R), microglia (SIRPA, PRSS8) and lysosomal functions (CLN5). A protein newly-associated with PD (CTF1) is involved in the interleukin-6 pathway, two proteins for ALS (TPP1, TNFSF13) are involved in lysosomal and astrocyte function, respectively, and proteins associated with MS are involved in blood-brain barrier function (TYMP, VEGFB), the oligodendrocyte function (PARP1), the structure of the node of Ranvier and function of dorsal root ganglion (NCS1, FLRT3, CDH15), and the response to viral infections including Epstein-Barr virus (PVR, WARS1). Our study demonstrates how harnessing large-scale genomic and proteomic data can yield novel insights into the role of plasma proteome in the pathogenesis of neurodegenerative diseases. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Lazaros Belbasis is supported by an NDPH Early Career Research Fellowship. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The cis pQTLs that were used as IVs are publicly available in the relevant publications. Summary statistics for the GWAS on AD and ALS are available through GWAS Catalog (https://www.ebi.ac.uk/gwas/). Summary statistics for the GWAS on PD and MS are available through OpenGWAS project (https://gwas.mrcieu.ac.uk/). Summary statistics for the GWAS on brain volume traits are available upon request from the ENIGMA consortium (https://enigma.ini.usc.edu/). Summary statistics for the GWAS on white matter hyper-intensities are publicly available through CHARGE consortium. Summary statistics for the cis region of gene expression in plasma and brain regions are publicly available through the eQTLGen (https://www.eqtlgen.org/) and the MetaBrain (https://www.metabrain.nl/) consortia, respectively.