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

Zheng, Jie; Haberland, Valeriia; Baird, Denis; Walker, Venexia; Haycock, Philip; Hurle, Mark R.; Gutteridge, Alex; Erola, Pau; Liu, Yi; Luo, Shan; Robinson, Jamie; Richardson, Tom G; Staley, James R; Elsworth, Benjamin; Burgess, Stephen; Sun, Benjamin B.; Danesh, John; Runz, Heiko; Maranville, Joseph C.; Martin, Hannah M.; Yarmolinsky, James; Laurin, Charles; Holmes, Michael V.; Liu, Jiang; Estrada, Karol; Santos, Rita; McCarthy, Linda; Waterworth, Dawn; Nelson, Matthew R.; Hemani, Gibran; Smith, George Davey; Butterworth, Adam S.; Scott, Robert A.; Gaunt, Tom R.

doi:10.1101/627398

Cited by 62 publications

(90 citation statements)

References 92 publications

(111 reference statements)

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“…We also found genetic evidence that selected protein targets, such as for MARK3 and monocyte count, have potential for adverse effects on other health outcomes, but note that this was not a general characteristic of all tested 'druggable' targets. Further, in-depth characterization of the targets identified will be required as a first step in gauging the likely success of any new or repurposed drugs identified via this analysis 33 .…”

Section: A Variant At the Abo Locus Links Susceptibility Of Respiratomentioning

confidence: 99%

Genetic architecture of host proteins interacting with SARS-CoV-2

Pietzner

Wheeler

Carrasco-Zanini

et al. 2020

Preprint

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ABSTRACTStrategies to develop therapeutics for SARS-CoV-2 infection may be informed by experimental identification of viral-host protein interactions in cellular assays and measurement of host response proteins in COVID-19 patients. Identification of genetic variants that influence the level or activity of these proteins in the host could enable rapid ‘in silico’ assessment in human genetic studies of their causal relevance as molecular targets for new or repurposed drugs to treat COVID-19. We integrated large-scale genomic and aptamer-based plasma proteomic data from 10,708 individuals to characterize the genetic architecture of 179 host proteins reported to interact with SARS-CoV-2 proteins or to participate in the host response to COVID-19. We identified 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links, evidence that putative viral interaction partners such as MARK3 affect immune response, and establish the first link between a recently reported variant for respiratory failure of COVID-19 patients at the ABO locus and hypercoagulation, i.e. maladaptive host response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and dynamic and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).

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Section: A Variant At the Abo Locus Links Susceptibility Of Respiratomentioning

confidence: 99%

Genetic architecture of host proteins interacting with SARS-CoV-2

Pietzner

Wheeler

Carrasco-Zanini

et al. 2020

Preprint

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“…Understanding which proteins influence which diseases is a fundamental problem in biomedical science since proteins are the major biological effector molecules. Proteins are also the targets of most medicines, so interest has emerged in the use of MR approaches to identify and validate drug targets [21][22][23][24] . Moreover, recent technological developments enable measurement of hundreds or thousands of proteins on an -omics scale in a single biological sample 8 .…”

Section: Introductionmentioning

confidence: 99%

“…The Ensembl 97 GRCh38 human genome assembly contains an estimated 20,454 protein coding genes, encoding an estimated 24,700 protein coding transcripts (merged Ensembl/Havana annotation). Of these transcripts,21,869 have a support level of ≤ 2, meaning that there is some level of experimental support for the presence of these transcripts. In addition, UniProt (version 2019_06, combining SwissProt and TrEMBL) reports 20,416 high quality manually annotated proteins.…”

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confidence: 99%

Genetic drug target validation using Mendelian randomization

Schmidt

Finan

Gordillo-Marañón

et al. 2019

Preprint

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Mendelian randomisation analysis has emerged as an important tool to elucidate the causal relevance of a range of environmental and biological risk factors for human disease. However, inference on cause is undermined if the genetic variants used to instrument a risk factor of interest also associate with other traits that open alternative pathways to the disease (horizontal pleiotropy). We show how the 'no horizontal pleiotropy assumption' in MR analysis is strengthened when proteins are the risk factors of interest. Proteins are the proximal effectors of biological processes encoded in the genome, and are becoming assayable on an -omics scale.Moreover, proteins are the targets of most medicines, so Mendelian randomization (MR) studies of drug targets are becoming a fundamental tool in drug development. To enable such studies we introduce a formal mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. Finally, we illustrate key model decisions and introduce an analytical framework for maximizing power and elucidating the robustness of drug target MR analyses.

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“…In addition, protein coding variants may cause technical artifacts in both affinity proteomics and mass spectrometry 43,44 . However, systematic conditional and colocalization analyses in causality testing using the aptamer-based technology have shown that pQTLs driven by common missense variants being artefactual is an unlikely event 11,45 .…”

Section: Figure 2bmentioning

confidence: 99%

Coding and regulatory variants affect serum protein levels and common disease

Emilsson

Guðmundsdóttir

Guðjónsson

et al. 2020

Preprint

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Circulating proteins are prognostic for human outcomes including cancer, heart failure, brain trauma and brain amyloid plaque burden. A deep serum proteome survey recently revealed close associations of serum protein networks and common diseases. The present study reveals unprecedented number of individual serum proteins that overlap genetic signatures of diseases emanating from different tissues of the body. Here, 55,932 low-frequency and common exome-array variants were compared with 4782 protein measurements in the serum of 5457 individuals of the deeply annotated AGES Reykjavik cohort. At a Bonferroni adjusted P-value threshold < 2.1610 -10 , 5553 variants affecting levels of 1931 serum proteins were detected. These associated variants overlapped genetic loci for hundreds of complex disease traits, emphasizing the emerging role for serum proteins as biomarkers of and potential causative agents of multiple diseases.Large-scale genome-wide association studies (GWASs) have expanded our knowledge of the genetic basis of complex disease. As of 2018, approximately 5687 GWASs have been published revealing 71,673 DNA variants to phenotype associations 1 . More recently, exomewide genotyping arrays have linked rare and common variants to many complex traits. For example, 444 independent risk variants were identified for lipoprotein fractions across 250 genes 2 . Despite the overall success of GWAS, the common lead SNPs rarely point directly to a clear causative polymorphism, making determination of the underlying disease mechanism difficult 3-6 . Regulatory variants affecting mRNA and/or protein levels and structural variants like missense mutations can point directly to the causal candidate. Alteration of the amino acid sequence may affect protein activity and/or influence transcription, translation, stability, processing and secretion of the protein in question 7-9 . Thus, by integrating intermediate traits

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

Cited by 62 publications

References 92 publications

Genetic architecture of host proteins interacting with SARS-CoV-2

Genetic architecture of host proteins interacting with SARS-CoV-2

Genetic drug target validation using Mendelian randomization

Coding and regulatory variants affect serum protein levels and common disease

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