Identification of Common and Rare Genetic Variation Associated With Plasma Protein Levels Using Whole-Exome Sequencing and Mass Spectrometry

The genetic landscape of neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.

Genetic determinants of plasma protein levels in the Estonian population

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

The functional impact of rare variation across the regulatory cascade

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

High plasma levels of C1-inhibitor are associated with lower risk of future venous thromboembolism

BACKGROUND

C1-inhibitor (C1INH) is a broad-acting serine protease inhibitor with anticoagulant activity. The impact of C1INH plasma levels within the normal physiological range on risk of venous thromboembolism (VTE) is unknown. We assessed the association of plasma C1INH levels and VTE risk and evaluated the impact of C1INH on thrombin and plasmin generation in ex vivo assays.

METHODS

A nested case-control study with 405 patients with VTE and 829 age- and sex-matched controls was derived from the Tromsø Study. Odds ratios (ORs) with 95% confidence intervals (95% CI) for VTE were estimated across plasma C1INH quartiles. Genetic regulation of C1INH was explored using quantitative trait loci analysis of whole exome sequencing data. The effect of plasma C1INH levels on coagulation was evaluated ex vivo by calibrated automated thrombography.

RESULTS

Individuals with C1INH levels in the highest quartile had a lower risk of VTE (OR 0.68, 95% CI: 0.49-0.96) compared with those with C1INH in the lowest quartile. In subgroup analysis, the corresponding ORs were 0.60 (95% CI: 0.39-0.89) for deep vein thrombosis and 0.85 (95% CI: 0.52-1.38) for pulmonary embolism, respectively. No significant genetic determinants of plasma C1INH levels were identified. Addition of exogenous C1INH to normal human plasma reduced thrombin generation triggered by an activator of the intrinsic coagulation pathway, but not when triggered by an activator of the extrinsic coagulation pathway.

CONCLUSIONS

High plasma levels of C1INH were associated with lower risk of VTE, and C1INH inhibited thrombin generation initiated by the intrinsic coagulation pathway ex vivo.

Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

Differences and commonalities in the genetic architecture of protein quantitative trait loci in European and Arab populations

Polygenic scores (PGS) can identify individuals at risk of adverse health events and guide genetics-based personalized medicine. However, it is not clear how well PGS translate between different populations, limiting their application to well-studied ethnicities. Proteins are intermediate traits linking genetic predisposition and environmental factors to disease, with numerous blood circulating protein levels representing functional readouts of disease-related processes. We hypothesized that studying the genetic architecture of a comprehensive set of blood-circulating proteins between a European and an Arab population could shed fresh light on the translatability of PGS to understudied populations. We therefore conducted a genome-wide association study with whole-genome sequencing data using 1301 proteins measured on the SOMAscan aptamer-based affinity proteomics platform in 2935 samples of Qatar Biobank and evaluated the replication of protein quantitative traits (pQTLs) from European studies in an Arab population. Then, we investigated the colocalization of shared pQTL signals between the two populations. Finally, we compared the performance of protein PGS derived from a Caucasian population in a European and an Arab cohort. We found that the majority of shared pQTL signals (81.8%) colocalized between both populations. About one-third of the genetic protein heritability was explained by protein PGS derived from a European cohort, with protein PGS performing ~20% better in Europeans when compared to Arabs. Our results are relevant for the translation of PGS to non-Caucasian populations, as well as for future efforts to extend genetic research to understudied populations.

Genetic mechanisms of 184 neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-reiated proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-reiated traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.

The genetic regulation of protein expression in cerebrospinal fluid

Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10-10 , 117 cis-pQTLs and 59 trans-pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF-specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP-10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP-10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.

Coding and regulatory variants are associated with serum protein levels and disease

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.

Soluble Urokinase Plasminogen Activator Receptor: Genetic Variation and Cardiovascular Disease Risk in Black Adults

BACKGROUND

suPAR (Soluble urokinase plasminogen activator receptor) has emerged as an important biomarker of coagulation, inflammation, and cardiovascular disease (CVD) risk. The contribution of suPAR to CVD risk and its genetic influence in Black populations have not been evaluated.

METHODS

We measured suPAR in 3492 Black adults from the prospective, community-based JHS (Jackson Heart Study). Cross-sectional associations of suPAR with lifestyle and CVD risk factors were assessed, whole-genome sequence data were used to evaluate genetic associations of suPAR, and relationships of suPAR with incident CVD outcomes and overall mortality were estimated over follow-up.

RESULTS

In Cox models adjusted for traditional CVD risk factors, estimated glomerular filtration rate, and CRP (C-reactive protein), each 1-SD higher suPAR was associated with a 21% to 31% increased risk of incident coronary heart disease, heart failure, stroke, and mortality. In the genome-wide association study, 2 missense (rs399145 encoding p.Thr86Ala, rs4760 encoding p.Phe272Leu) and 2 noncoding regulatory variants (rs73935023 within an enhancer element and rs4251805 within the promoter) of PLAUR on chromosome 19 were each independently associated with suPAR and together explained 14% of suPAR phenotypic variation. The allele frequencies of each of the four suPAR-associated genetic variants differ considerably across African and European populations. We further show that PLAUR rs73935023 can alter transcriptional activity in vitro. We did not find any association between genetically determined suPAR and CVD in JHS or a larger electronic medical record-based analyses of Blacks or Whites.

CONCLUSIONS

Our results demonstrate the importance of ancestry-differentiated genetic variation on suPAR levels and indicate suPAR is a CVD biomarker in Black adults.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Proteome-wide Systems Genetics to Identify Functional Regulators of Complex Traits

Proteomic technologies now enable the rapid quantification of thousands of proteins across genetically diverse samples. Integration of these data with systems-genetics analyses is a powerful approach to identify new regulators of economically important or disease-relevant phenotypes in various populations. In this review, we summarize the latest proteomic technologies and discuss technical challenges for their use in population studies. We demonstrate how the analysis of correlation structure and loci mapping can be used to identify genetic factors regulating functional protein networks and complex traits. Finally, we provide an extensive summary of the use of proteome-wide systems genetics throughout fungi, plant, and animal kingdoms and discuss the power of this approach to identify candidate regulators and drug targets in large human consortium studies.

Whole-genome sequencing analysis of the cardiometabolic proteome

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 × 10⁻¹¹) 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.

The human proteome represents a crucial link between complex disease and genetic/environmental factors. Here, the authors investigate 257 cardiometabolic-relevant protein biomarkers in whole genome sequencing data from 1328 individuals, revealing the genetic architecture underlying biomarker variation.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Whole-genome sequence association analysis of blood proteins in a longitudinal wellness cohort

BACKGROUND

The human plasma proteome is important for many biological processes and targets for diagnostics and therapy. It is therefore of great interest to understand the interplay of genetic and environmental factors to determine the specific protein levels in individuals and to gain a deeper insight of the importance of genetic architecture related to the individual variability of plasma levels of proteins during adult life.

METHODS

We have combined whole-genome sequencing, multiplex plasma protein profiling, and extensive clinical phenotyping in a longitudinal 2-year wellness study of 101 healthy individuals with repeated sampling. Analyses of genetic and non-genetic associations related to the variability of blood levels of proteins in these individuals were performed.

RESULTS

The analyses showed that each individual has a unique protein profile, and we report on the intra-individual as well as inter-individual variation for 794 plasma proteins. A genome-wide association study (GWAS) using 7.3 million genetic variants identified by whole-genome sequencing revealed 144 independent variants across 107 proteins that showed strong association (P < 6 × 10-11) between genetics and the inter-individual variability on protein levels. Many proteins not reported before were identified (67 out of 107) with individual plasma level affected by genetics. Our longitudinal analysis further demonstrates that these levels are stable during the 2-year study period. The variability of protein profiles as a consequence of environmental factors was also analyzed with focus on the effects of weight loss and infections.

CONCLUSIONS

We show that the adult blood levels of many proteins are determined at birth by genetics, which is important for efforts aimed to understand the relationship between plasma proteome profiles and human biology and disease.