Rare variant associations with plasma protein levels in the UK Biobank.

Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.

Genetic associations of protein-coding variants in human disease.

Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have so far remained largely underpowered in relation to identifying associations in the rare and low-frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes1. Here we combined whole-exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third being previously unreported. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks enabled us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Genome-Wide Association Study Identifies 4 Novel Risk Loci for Small Intestinal Neuroendocrine Tumors Including a Missense Mutation in LGR5.

BACKGROUND & AIMS: Small intestinal neuroendocrine tumor (SI-NET) is a rare disease, but its incidence has increased over the past 4 decades. Understanding the genetic risk factors underlying SI-NETs can help in disease prevention and may provide clinically beneficial markers for diagnosis. Here the results of the largest genome-wide association study of SI-NETs performed to date with 405 cases and 614,666 controls are reported. METHODS: Samples from 307 patients with SI-NETs and 287,137 controls in the FinnGen study were used for the identification of SI-NET risk-associated genetic variants. The results were also meta-analyzed with summary statistics from the UK Biobank (n = 98 patients with SI-NET and n = 327,529 controls). RESULTS: We identified 6 genome-wide significant (P < 5 × 10-8) loci associated with SI-NET risk, of which 4 (near SEMA6A, LGR5, CDKAL1, and FERMT2) are novel and 2 (near LTA4H-ELK and in KIF16B) have been reported previously. Interestingly, the top hit (rs200138614; P = 1.80 × 10-19) was a missense variant (p.Cys712Phe) in the LGR5 gene, a bona-fide marker of adult intestinal stem cells and a potentiator of canonical WNT signaling. The association was validated in an independent Finnish collection of 70 patients with SI-NETs, as well as in the UK Biobank exome sequence data (n = 92 cases and n = 392,814 controls). Overexpression of LGR5 p.Cys712Phe in intestinal organoids abolished the ability of R-Spondin1 to support organoid growth, indicating that the mutation perturbed R-Spondin-LGR5 signaling. CONCLUSIONS: Our study is the largest genome-wide association study to date on SI-NETs and reported 4 new associated genome-wide association study loci, including a novel missense mutation (rs200138614, p.Cys712Phe) in LGR5, a canonical marker of adult intestinal stem cells.

Genomic atlas of the human plasma proteome.

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

The Parkinson's disease-associated gene ITPKB protects against α-synuclein aggregation by regulating ER-to-mitochondria calcium release.

Inositol-1,4,5-triphosphate (IP3) kinase B (ITPKB) is a ubiquitously expressed lipid kinase that inactivates IP3, a secondary messenger that stimulates calcium release from the endoplasmic reticulum (ER). Genome-wide association studies have identified common variants in the ITPKB gene locus associated with reduced risk of sporadic Parkinson's disease (PD). Here, we investigate whether ITPKB activity or expression level impacts PD phenotypes in cellular and animal models. In primary neurons, knockdown or pharmacological inhibition of ITPKB increased levels of phosphorylated, insoluble α-synuclein pathology following treatment with α-synuclein preformed fibrils (PFFs). Conversely, ITPKB overexpression reduced PFF-induced α-synuclein aggregation. We also demonstrate that ITPKB inhibition or knockdown increases intracellular calcium levels in neurons, leading to an accumulation of calcium in mitochondria that increases respiration and inhibits the initiation of autophagy, suggesting that ITPKB regulates α-synuclein pathology by inhibiting ER-to-mitochondria calcium transport. Furthermore, the effects of ITPKB on mitochondrial calcium and respiration were prevented by pretreatment with pharmacological inhibitors of the mitochondrial calcium uniporter complex, which was also sufficient to reduce α-synuclein pathology in PFF-treated neurons. Taken together, these results identify ITPKB as a negative regulator of α-synuclein aggregation and highlight modulation of ER-to-mitochondria calcium flux as a therapeutic strategy for the treatment of sporadic PD.

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome.

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer's Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer's disease, 6 genes with Parkinson's disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.

Phase 1-2 Trial of Antisense Oligonucleotide Tofersen for SOD1 ALS.

BACKGROUND: Tofersen is an antisense oligonucleotide that mediates the degradation of superoxide dismutase 1 (SOD1) messenger RNA to reduce SOD1 protein synthesis. Intrathecal administration of tofersen is being studied for the treatment of amyotrophic lateral sclerosis (ALS) due to SOD1 mutations. METHODS: We conducted a phase 1-2 ascending-dose trial evaluating tofersen in adults with ALS due to SOD1 mutations. In each dose cohort (20, 40, 60, or 100 mg), participants were randomly assigned in a 3:1 ratio to receive five doses of tofersen or placebo, administered intrathecally for 12 weeks. The primary outcomes were safety and pharmacokinetics. The secondary outcome was the change from baseline in the cerebrospinal fluid (CSF) SOD1 concentration at day 85. Clinical function and vital capacity were measured. RESULTS: A total of 50 participants underwent randomization and were included in the analyses; 48 participants received all five planned doses. Lumbar puncture-related adverse events were observed in most participants. Elevations in CSF white-cell count and protein were reported as adverse events in 4 and 5 participants, respectively, who received tofersen. Among participants who received tofersen, one died from pulmonary embolus on day 137, and one from respiratory failure on day 152; one participant in the placebo group died from respiratory failure on day 52. The difference at day 85 in the change from baseline in the CSF SOD1 concentration between the tofersen groups and the placebo group was 2 percentage points (95% confidence interval [CI], -18 to 27) for the 20-mg dose, -25 percentage points (95% CI, -40 to -5) for the 40-mg dose, -19 percentage points (95% CI, -35 to 2) for the 60-mg dose, and -33 percentage points (95% CI, -47 to -16) for the 100-mg dose. CONCLUSIONS: In adults with ALS due to SOD1 mutations, CSF SOD1 concentrations decreased at the highest concentration of tofersen administered intrathecally over a period of 12 weeks. CSF pleocytosis occurred in some participants receiving tofersen. Lumbar puncture-related adverse events were observed in most participants. (Funded by Biogen; ClinicalTrials.gov number, NCT02623699; EudraCT number, 2015-004098-33.).

Reduction of TMEM97 increases NPC1 protein levels and restores cholesterol trafficking in Niemann-pick type C1 disease cells.

Niemann-Pick type C disease (NP-C) is a progressive lysosomal lipid storage disease caused by mutations in the NPC1 and NPC2 genes. NPC1 is essential for transporting cholesterol and other lipids out of lysosomes, but little is known about the mechanisms that control its cellular abundance and localization. Here we show that a reduction of TMEM97, a cholesterol-responsive NPC1-binding protein, increases NPC1 levels in cells through a post-transcriptional mechanism. Reducing TMEM97 through RNA-interference reduces lysosomal lipid storage and restores cholesterol trafficking to the endoplasmic reticulum in cell models of NP-C. In TMEM97 knockdown cells, NPC1 levels can be reinstated with wild type TMEM97, but not TMEM97 missing an ER-retention signal suggesting that TMEM97 contributes to controlling the availability of NPC1 to the cell. Importantly, knockdown of TMEM97 also increases levels of residual NPC1 in NPC1-mutant patient fibroblasts and reduces cholesterol storage in an NPC1-dependent manner. Our findings propose TMEM97 inhibition as a novel strategy to increase residual NPC1 levels in cells and a potential therapeutic target for NP-C.

Systematic cell-based phenotyping of missense alleles empowers rare variant association studies: a case for LDLR and myocardial infarction.

A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.

Impaired antibacterial autophagy links granulomatous intestinal inflammation in Niemann-Pick disease type C1 and XIAP deficiency with NOD2 variants in Crohn's disease.

OBJECTIVE: Patients with Niemann-Pick disease type C1 (NPC1), a lysosomal lipid storage disorder that causes neurodegeneration and liver damage, can present with IBD, but neither the significance nor the functional mechanism of this association is clear. We studied bacterial handling and antibacterial autophagy in patients with NPC1. DESIGN: We characterised intestinal inflammation in 14 patients with NPC1 who developed IBD. We investigated bacterial handling and cytokine production of NPC1 monocytes or macrophages in vitro and compared NPC1-associated functional defects to those caused by IBD-associated nucleotide-binding oligomerization domain-containing protein 2 (NOD2) variants or mutations in X-linked inhibitor of apoptosis (XIAP). RESULTS: Patients with the lysosomal lipid storage disorder NPC1 have increased susceptibility to early-onset fistulising colitis with granuloma formation, reminiscent of Crohn's disease (CD). Mutations in NPC1 cause impaired autophagy due to defective autophagosome function that abolishes NOD2-mediated bacterial handling in vitro similar to variants in NOD2 or XIAP deficiency. In contrast to genetic NOD2 and XIAP variants, NPC1 mutations do not impair NOD2-receptor-interacting kinase 2 (RIPK2)-XIAP-dependent cytokine production. Pharmacological activation of autophagy can rescue bacterial clearance in macrophages in vitro by increasing the autophagic flux and bypassing defects in NPC1. CONCLUSIONS: NPC1 confers increased risk of early-onset severe CD. Our data support the concept that genetic defects at different checkpoints of selective autophagy cause a shared outcome of CD-like immunopathology linking monogenic and polygenic forms of IBD. Muramyl dipeptide-driven cytokine responses and antibacterial autophagy induction are parallel and independent signalling cascades downstream of the NOD2-RIPK2-XIAP complex.

Altered distribution and function of natural killer cells in murine and human Niemann-Pick disease type C1.

Niemann-Pick type C (NPC) is a neurodegenerative lysosomal storage disorder caused by defects in the lysosomal proteins NPC1 or NPC2. NPC cells are characterized by reduced lysosomal calcium levels and impaired sphingosine transport from lysosomes. Natural killer (NK) cells kill virally infected/transformed cells via degranulation of lysosome-related organelles. Their trafficking from lymphoid tissues into the circulation is dependent on sphingosine-1-phosphate (S1P) gradients, sensed by S1P receptor 5 (S1P5). We hypothesized that NK-cell function and trafficking could be affected in NPC disease due to the combined effects of the lysosomal calcium defect and sphingosine storage. In an NPC1 mouse model, we found the frequency of NK cells was altered and phenocopied S1P5-deficient mice, consistent with defects in S1P levels. NK cells from NPC1 mice also had a defect in cytotoxicity due to a failure in degranulation of cytotoxic granules, which was associated with reduced lysosomal calcium levels. Affected NPC1 patients and NPC1 heterozygote carriers had reduced NK-cell numbers in their blood and showed similar phenotypic and developmental changes to those observed in the NPC1 mouse. These findings highlight the effects of lysosomal storage on the peripheral immune system.

RNAi-based functional profiling of loci from blood lipid genome-wide association studies identifies genes with cholesterol-regulatory function.

Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL-receptor levels and/or that overexpression as GFP-tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.

Transmembrane protein 55B is a novel regulator of cellular cholesterol metabolism.

OBJECTIVE: Interindividual variation in pathways affecting cellular cholesterol metabolism can influence levels of plasma cholesterol, a well-established risk factor for cardiovascular disease. Inherent variation among immortalized lymphoblastoid cell lines from different donors can be leveraged to discover novel genes that modulate cellular cholesterol metabolism. The objective of this study was to identify novel genes that regulate cholesterol metabolism by testing for evidence of correlated gene expression with cellular levels of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) mRNA, a marker for cellular cholesterol homeostasis, in a large panel of lymphoblastoid cell lines. APPROACH AND RESULTS: Expression array profiling was performed on 480 lymphoblastoid cell lines established from participants of the Cholesterol and Pharmacogenetics (CAP) statin clinical trial, and transcripts were tested for evidence of correlated expression with HMGCR as a marker of intracellular cholesterol homeostasis. Of these, transmembrane protein 55b (TMEM55B) showed the strongest correlation (r=0.29; P=4.0E-08) of all genes not previously implicated in cholesterol metabolism and was found to be sterol regulated. TMEM55B knockdown in human hepatoma cell lines promoted the decay rate of the low-density lipoprotein receptor, reduced cell surface low-density lipoprotein receptor protein, impaired low-density lipoprotein uptake, and reduced intracellular cholesterol. CONCLUSIONS: Here, we report identification of TMEM55B as a novel regulator of cellular cholesterol metabolism through the combination of gene expression profiling and functional studies. The findings highlight the value of an integrated genomic approach for identifying genes that influence cholesterol homeostasis.

Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding.

In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug-induced transcriptional modules from genome-wide microarray data of drug-treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell-type-specific drug-induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α-adrenergic receptor, peroxisome proliferator-activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology.

Genome-wide association analysis in primary sclerosing cholangitis and ulcerative colitis identifies risk loci at GPR35 and TCF4.

UNLABELLED: Approximately 60%-80% of patients with primary sclerosing cholangitis (PSC) have concurrent ulcerative colitis (UC). Previous genome-wide association studies (GWAS) in PSC have detected a number of susceptibility loci that also show associations in UC and other immune-mediated diseases. We aimed to systematically compare genetic associations in PSC with genotype data in UC patients with the aim of detecting new susceptibility loci for PSC. We performed combined analyses of GWAS for PSC and UC comprising 392 PSC cases, 987 UC cases, and 2,977 controls and followed up top association signals in an additional 1,012 PSC cases, 4,444 UC cases, and 11,659 controls. We discovered novel genome-wide significant associations with PSC at 2q37 [rs3749171 at G-protein-coupled receptor 35 (GPR35); P = 3.0 × 10(-9) in the overall study population, combined odds ratio [OR] and 95% confidence interval [CI] of 1.39 (1.24-1.55)] and at 18q21 [rs1452787 at transcription factor 4 (TCF4); P = 2.61 × 10(-8) , OR (95% CI) = 0.75 (0.68-0.83)]. In addition, several suggestive PSC associations were detected. The GPR35 rs3749171 is a missense single nucleotide polymorphism resulting in a shift from threonine to methionine. Structural modeling showed that rs3749171 is located in the third transmembrane helix of GPR35 and could possibly alter efficiency of signaling through the GPR35 receptor. CONCLUSION: By refining the analysis of a PSC GWAS by parallel assessments in a UC GWAS, we were able to detect two novel risk loci at genome-wide significance levels. GPR35 shows associations in both UC and PSC, whereas TCF4 represents a PSC risk locus not associated with UC. Both loci may represent previously unexplored aspects of PSC pathogenesis.

PICALO: principal interaction component analysis for the identification of discrete technical, cell-type, and environmental factors that mediate eQTLs.

Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait-associated variants, but their effects often rely on contexts that are unknown or unmeasured. We introduce PICALO, a method for hidden variable inference of eQTL contexts. PICALO identifies and disentangles technical from biological context in heterogeneous blood and brain bulk eQTL datasets. These contexts are biologically informative and reproducible, outperforming cell counts or expression-based principal components. Furthermore, we show that RNA quality and cell type proportions interact with thousands of eQTLs. Knowledge of hidden eQTL contexts may aid in the inference of functional mechanisms underlying disease variants.

Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression.

Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Blood protein assessment of leading incident diseases and mortality in the UK Biobank.

The circulating proteome offers insights into the biological pathways that underlie disease. Here, we test relationships between 1,468 Olink protein levels and the incidence of 23 age-related diseases and mortality in the UK Biobank (n = 47,600). We report 3,209 associations between 963 protein levels and 21 incident outcomes. Next, protein-based scores (ProteinScores) are developed using penalized Cox regression. When applied to test sets, six ProteinScores improve the area under the curve estimates for the 10-year onset of incident outcomes beyond age, sex and a comprehensive set of 24 lifestyle factors, clinically relevant biomarkers and physical measures. Furthermore, the ProteinScore for type 2 diabetes outperforms a polygenic risk score and HbA1c-a clinical marker used to monitor and diagnose type 2 diabetes. The performance of scores using metabolomic and proteomic features is also compared. These data characterize early proteomic contributions to major age-related diseases, demonstrating the value of the plasma proteome for risk stratification.

Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank.

Understanding how gene-environment interactions (GEIs) influence the circulating proteome could aid in biomarker discovery and validation. The presence of GEIs can be inferred from single nucleotide polymorphisms that associate with phenotypic variability - termed variance quantitative trait loci (vQTLs). Here, vQTL association studies are performed on plasma levels of 1463 proteins in 52,363 UK Biobank participants. A set of 677 independent vQTLs are identified across 568 proteins. They include 67 variants that lack conventional additive main effects on protein levels. Over 1100 GEIs are identified between 101 proteins and 153 environmental exposures. GEI analyses uncover possible mechanisms that explain why 13/67 vQTL-only sites lack corresponding main effects. Additional analyses also highlight how age, sex, epistatic interactions and statistical artefacts may underscore associations between genetic variation and variance heterogeneity. This study establishes the most comprehensive database yet of vQTLs and GEIs for the human proteome.