Genetic and epigenetic architectures of neurological protein biomarkers in the Lothian Birth Cohort 1936

Abstract

Although plasma proteins may serve as important markers of disease risk in neurological conditions, the molecular mechanisms responsible for inter-individual variation in plasma protein levels are poorly understood. In this study, we conducted genome-and epigenome-wide association studies on the levels of 92 neurological proteins to identify genetic and epigenetic loci associated with their plasma concentrations (n = 750). We identified 62 independent genome-wide significant loci for 37 proteins (P < 5.4 x 10 -10 ) and 68 epigenome-wide significant sites associated with the levels of 7 proteins (P < 3.9 x 10 -10 ). Using this information, we identified biological pathways in which putative neurological biomarkers are implicated as well as molecular mechanisms through which genetic variation may perturb plasma protein levels. Additionally, we found evidence that poliovirus receptor is causally associated with Alzheimer's disease. In conclusion, we identified many novel genetic and epigenetic factors that are associated with neurological protein levels which may inform disease biology and establish causal relationships between biomarkers and neurological diseases. Conception and design: RFH and REM. Data analysis: RFH, DLMcC, DCL and REM. Drafting the article: RFH and REM. Revision of the article: all authors.

A large-scale plasma proteome Mendelian randomization study identifies novel causal plasma proteins related to primary biliary cholangitis

“…We extracted summary statistics of pQTLs for plasma proteins from nine different proteomic GWASs and pooled them together using METAL. (10)(11)(12)(13)(14)(15)(16)(17)(18)21) In total, 51,799 individuals were included in our analysis. All of the participating individuals are of European ancestry.…”

“…Therefore, they could serve as an important source of biomarkers (8). Recently, several genome-wide association studies (GWASs) of plasma proteins have identified protein quantitative trait loci (pQTLs) for thousands of plasma proteins (10)(11)(12)(13)(14)(15)(16)(17)(18). A pQTL is an association of protein levels at a genetic locus and is represented by the strongest associating single-nucleotide polymorphism (SNP) (8).…”

“…Furthermore, the high efficiency and low cost make MR more suitable for large-scale screening for causal relationships. As a result, we conducted two-sample MR analyses for the plasma proteome using pQTLs extracted from nine different GWASs (10)(11)(12)(13)(14)(15)(16)(17)(18). In this study, to eliminate bias, MR analyses were conducted using different types of pQTLs.…”

Genetics’ Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome‐Wide Protein–Protein Interaction Dynamics

“…Advances in proteomics have since opened up the possibility to investigate the association of genomic variants with protein abundances . Studies using aptamer‐, immunoassay‐, or mass‐spectrometry‐based proteomics have shown how changes in protein abundance can be associated with variants both in cis and in trans. Notably, such proteome‐wide screens of pQTL have been conducted in yeast, mice, maize, human cell lines, and primary cell lines .…”

Integrated multiple-microarray analysis and mendelian randomization to identify novel targets involved in diabetic nephropathy

“…Compared with observational studies, MR can avoid environmental confounders and reverse causality because the genetic variants used in MR cannot be easily changed by the external environment (8). Several genome-wide association studies (GWASs) of plasma proteins have recently identified the cis-variant in the protein-encoding gene (known as the protein quantitative trait loci, pQTL) for thousands of plasma proteins (9)(10)(11)(12)(13)(14)(15). Consequently, cis-pQTLs have been widely used as genetic instruments to estimate the causal effects of plasma proteins on complex diseases, satisfying three key assumptions of MR (relevance, independence, and exclusion assumptions) (16).…”