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.
The human proteome is a crucial intermediate between complex diseases and their genetic and environmental components, and an important source of drug development targets and biomarkers. Here, we ...comprehensively assess the genetic architecture of 257 circulating protein biomarkers of cardiometabolic relevance through high-depth (22.5×) whole-genome sequencing (WGS) in 1328 individuals. We discover 131 independent sequence variant associations (P < 7.45 × 10
) across the allele frequency spectrum, all of which replicate in an independent cohort (n = 1605, 18.4x WGS). We identify for the first time replicating evidence for rare-variant cis-acting protein quantitative trait loci for five genes, involving both coding and noncoding variation. We construct and validate polygenic scores that explain up to 45% of protein level variation. We find causal links between protein levels and disease risk, identifying high-value biomarkers and drug development targets.
Deep sequencing offers unparalleled access to rare variants in human populations. Understanding their role in disease is a priority, yet prohibitive sequencing costs mean that many cohorts lack the ...sample size to discover these effects on their own. Meta-analysis of individual variant scores allows the combination of rare variants across cohorts and study of their aggregated effect at the gene level, boosting discovery power. However, the methods involved have largely not been field-tested. In this study, we aim to perform the first meta-analysis of gene-based rare variant aggregation optimal tests, applied to the human cardiometabolic proteome.
Here, we carry out this analysis across MANOLIS, Pomak and ORCADES, three isolated European cohorts with whole-genome sequencing (total N = 4,422). We examine the genetic architecture of 250 proteomic traits of cardiometabolic relevance. We use a containerised pipeline to harmonise variant lists across cohorts and define four sets of qualifying variants. For every gene, we interrogate protein-damaging variants, exonic variants, exonic and regulatory variants, and regulatory only variants, using the CADD and Eigen scores to weigh variants according to their predicted functional consequence. We perform single-cohort rare variant analysis and meta-analyse variant scores using the SMMAT package.
We describe 5 rare variant pQTLs (RV-pQTL) which pass our stringent significance threshold (7.45 × 10−11) and quality control procedure. These were split between four cis signals for MARCO, TEK, MMP2 and MPO, and one trans association for GDF2 in the SERPINA11 gene. We show that the cis-MPO association, which was not detectable using the single-point data alone, is driven by 5 missense and frameshift variants. These include rs140636390 and rs119468010, which are specific to MANOLIS and ORCADES, respectively. We show how this kind of signal could improve the predictive accuracy of genetic factors in common complex disease such as stroke and cardiovascular disease.
Our proof-of-concept study demonstrates the power of gene-based meta-analyses for discovering disease-relevant associations complementing common-variant signals by incorporating population-specific rare variation.
•Meta-analysis of gene-based variant scores leverages population-specific allelic heterogeneity.•We study rare variants influencing 250 circulating serum proteins in two Greek population isolates.•4 cis and 1 trans coding variant signals are study-wide significant and pass quality control.•Five rare coding variants influence protein expression of myeloperoxidase (MPO).•Different isolates are enriched for different rare coding MPO variants.
SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the ...coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.
We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data.
We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 95% CI, 1.10-2.42;
=0.01), hospitalization (odds ratio, 1.52 95% CI, 1.05-2.21;
=0.03), and infection (odds ratio, 1.60 95% CI, 1.08-2.37;
=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells.
Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.
Abstract
Cardiometabolic diseases, such as type 2 diabetes and cardiovascular disease, have a high public health burden. Understanding the genetically determined regulation of proteins that are ...dysregulated in disease can help to dissect the complex biology underpinning them. Here, we perform a protein quantitative trait locus (pQTL) analysis of 248 serum proteins relevant to cardiometabolic processes in 2893 individuals. Meta-analyzing whole-genome sequencing (WGS) data from two Greek cohorts, MANOLIS (n = 1356; 22.5× WGS) and Pomak (n = 1537; 18.4× WGS), we detect 301 independently associated pQTL variants for 170 proteins, including 12 rare variants (minor allele frequency < 1%). We additionally find 15 pQTL variants that are rare in non-Finnish European populations but have drifted up in the frequency in the discovery cohorts here. We identify proteins causally associated with cardiometabolic traits, including Mep1b for high-density lipoprotein (HDL) levels, and describe a knock-out (KO) Mep1b mouse model. Our findings furnish insights into the genetic architecture of the serum proteome, identify new protein–disease relationships and demonstrate the importance of isolated populations in pQTL analysis.
Cover Image Png, Grace; Suveges, Daniel; Park, Young‐Chan ...
Genetic epidemiology,
January 2020, Letnik:
44, Številka:
1
Journal Article
Recenzirano
Front Cover Caption: The cover image is based on the Original Article Population‐wide copy number variation calling using variant call format files from 6,898 individuals by Arthur Gilly et al., ...https://doi.org/10.1002/gepi.22260.
Copy number variants (CNVs) play an important role in a number of human diseases, but the accurate calling of CNVs remains challenging. Most current approaches to CNV detection use raw read ...alignments, which are computationally intensive to process. We use a regression tree‐based approach to call germline CNVs from whole‐genome sequencing (WGS, >18x) variant call sets in 6,898 samples across four European cohorts, and describe a rich large variation landscape comprising 1,320 CNVs. Eighty‐one percent of detected events have been previously reported in the Database of Genomic Variants. Twenty‐three percent of high‐quality deletions affect entire genes, and we recapitulate known events such as the GSTM1 and RHD gene deletions. We test for association between the detected deletions and 275 protein levels in 1,457 individuals to assess the potential clinical impact of the detected CNVs. We describe complex CNV patterns underlying an association with levels of the CCL3 protein (MAF = 0.15, p = 3.6x10−12) at the CCL3L3 locus, and a novel cis‐association between a low‐frequency NOMO1 deletion and NOMO1 protein levels (MAF = 0.02, p = 2.2x10−7). This study demonstrates that existing population‐wide WGS call sets can be mined for germline CNVs with minimal computational overhead, delivering insight into a less well‐studied, yet potentially impactful class of genetic variant.
Human plasma contains a wide variety of circulating proteins. These proteins can be important clinical biomarkers in disease and also possible drug targets. Large scale genomics studies of ...circulating proteins can identify genetic variants that lead to relative protein abundance.
We conducted a meta-analysis on genome-wide association studies of autosomal chromosomes in 22,997 individuals of primarily European ancestry across 12 cohorts to identify protein quantitative trait loci (pQTL) for 92 cardiometabolic associated plasma proteins.
We identified 503 (337 cis and 166 trans) conditionally independent pQTLs, including several novel variants not reported in the literature. We conducted a sex-stratified analysis and found that 118 (23.5%) of pQTLs demonstrated heterogeneity between sexes. The direction of effect was preserved but there were differences in effect size and significance. Additionally, we annotate trans-pQTLs with nearest genes and report plausible biological relationships. Using Mendelian randomization, we identified causal associations for 18 proteins across 19 phenotypes, of which 10 have additional genetic colocalization evidence. We highlight proteins associated with a constellation of cardiometabolic traits including angiopoietin-related protein 7 (ANGPTL7) and Semaphorin 3F (SEMA3F).
Through large-scale analysis of protein quantitative trait loci, we provide a comprehensive overview of common variants associated with plasma proteins. We highlight possible biological relationships which may serve as a basis for further investigation into possible causal roles in cardiometabolic diseases.
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