The MR-Base platform supports systematic causal inference across the human phenome

eLife, Journal Year: 2018, Volume and Issue: 7

Published: May 30, 2018

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly GWAS results often insufficiently curated, undermining efficient implementation of approach. We therefore developed MR-Base ( http://www.mrbase.org ): platform that integrates curated database complete (no restrictions according statistical significance) with an application programming interface, web app R packages automate 2SMR. The software includes several sensitivity analyses assessing impact horizontal pleiotropy other violations assumptions. currently comprises 11 billion single nucleotide polymorphism-trait associations 1673 is updated on regular basis. Integrating data ensures more rigorous hypothesis-driven allows millions potential efficiently evaluated in phenome-wide studies.

Language: Английский

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The GTEx Consortium atlas of genetic regulatory effects across human tissues

Science, Journal Year: 2020, Volume and Issue: 369(6509), P. 1318 - 1330

Published: Sept. 10, 2020

The Genotype-Tissue Expression (GTEx) project dissects how genetic variation affects gene expression and splicing.

Language: Английский

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Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Nature Genetics, Journal Year: 2021, Volume and Issue: 53(9), P. 1300 - 1310

Published: Sept. 1, 2021

Language: Английский

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LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

Bioinformatics, Journal Year: 2016, Volume and Issue: 33(2), P. 272 - 279

Published: Sept. 22, 2016

LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability complex traits diseases, partition this into functional categories, genetic correlation between different phenotypes. Because relies on summary level data, computationally tractable even for very large sample sizes. However, publicly available GWAS are typically stored in databases have formats, making it difficult apply correlations across many simultaneously.

Language: Английский

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The MRC IEU OpenGWAS data infrastructure

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: Aug. 10, 2020

Abstract Data generated by genome-wide association studies (GWAS) are growing fast with the linkage of biobank samples to health records, and expanding capture high-dimensional molecular phenotypes. However utility these efforts can only be fully realised if their complete results collected from heterogeneous sources formats, harmonised made programmatically accessible. Here we present OpenGWAS database, an open source, access, scalable high-performance cloud-based data infrastructure that imports publishes GWAS summary datasets metadata for scientific community. Our import pipeline harmonises against dbSNP human genome reference sequence, generates reports standardises format metadata. Users access via a website, application programming interface, R Python packages, also as downloadable files rapidly queried in high performance computing environments. currently contains 126 billion genetic associations 14,582 representing range different phenotypes disease outcomes across populations. We developed packages serve conduits between available analytical tools, enabling Mendelian randomization, colocalisation analysis, fine mapping, correlation locus visualisation. is freely accessible at https://gwas.mrcieu.ac.uk , has been designed facilitate integration third party tools.

Language: Английский

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Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

PLoS Medicine, Journal Year: 2020, Volume and Issue: 17(3), P. e1003062 - e1003062

Published: March 23, 2020

Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipid-related entities account for this relationship remains unclear. Using genetic instruments lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles aetiology of CHD. Methods and findings We conducted a genome-wide association study (GWAS) circulating non-fasted UK Biobank (UKBB) low-density (LDL) cholesterol, triglycerides, apolipoprotein B identify lipid-associated single nucleotide polymorphisms (SNPs). data from CARDIoGRAMplusC4D CHD (consisting 60,801 cases 123,504 controls), performed univariable MR analyses. Similar GWAS analyses were high-density (HDL) cholesterol A-I. The apolipoproteins UKBB included between 393,193 441,016 individuals whom mean age was 56.9 y (range 39–73 y) 54.2% women. (standard deviation) concentrations LDL 3.57 (0.87) mmol/L HDL 1.45 (0.38) mmol/L, median triglycerides 1.50 (IQR = 1.11) mmol/L. values A-I 1.03 (0.24) g/L 1.54 (0.27) g/L, respectively. identified multiple independent SNPs associated at P < 5 × 10−8 (220), (n 255), (440), (534), (440). Between 56%–93% each trait had not been previously reported large-scale GWASs. Almost half (46%) these with than trait. Assessed individually using MR, (odds ratio [OR] 1.66 per 1-standard-deviation–higher trait; 95% CI: 1.49–1.86; 0.001), (OR 1.34; 1.25–1.44; 0.001) 1.73; 1.56–1.91; effect estimates consistent higher risk In only 1.92; 1.31–2.81; retained robust effect, estimate 0.85; 0.57–1.27; 0.44) reversing that 1.12; 1.02–1.23; 0.01) becoming weaker. Individual showed 0.80; 0.75–0.86; 0.83; 0.77–0.89; lower CHD, but attenuated substantially null on accounting B. A limitation is that, owing nature metabolism, measures related composition particles are highly correlated, creating challenge making exclusive interpretations causation individual components. Conclusions These suggest predominant accounts aetiological

Language: Английский

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Genetics of 35 blood and urine biomarkers in the UK Biobank

Nature Genetics, Journal Year: 2021, Volume and Issue: 53(2), P. 185 - 194

Published: Jan. 18, 2021

Language: Английский

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Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2018, Volume and Issue: unknown

Published: Oct. 19, 2018

Summary While many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear. To identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals the eQTLGen Consortium. We observed that cis -eQTLs can be detected for 88% of studied genes, but they a different genetic architecture compared to variants, limiting our ability use pinpoint causal genes within susceptibility loci. In contrast, trans-eQTLs (detected 37% 10,317 trait-associated variants) were more informative. Multiple unlinked associated same complex trait, often converged on trans-genes are known play central roles disease etiology. when ascertaining effect polygenic scores calculated 1,263 study (GWAS) traits. Expression levels 13% correlated with scores, resulting drive

Language: Английский

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Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

American Journal of Epidemiology, Journal Year: 2017, Volume and Issue: 186(9), P. 1084 - 1096

Published: Jan. 30, 2017

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy found widespread use, already over 400,000 blood samples. Over 200 measures are quantified per sample; addition to many routinely used epidemiology, method simultaneously provides fine-grained lipoprotein subclass quantification circulating fatty acids, amino gluconeogenesis-related metabolites, other molecules from multiple pathways. Here we focus applications quantifying epidemiology. We highlight characterization factors, use Mendelian randomization, key issues study design analyses also detail how integration data with genetics can enhance drug development. discuss why is becoming epidemiology biobanking. Although still novel, it seems likely that comprehensive biomarker will contribute etiologic understanding various abilities predict disease risks, potential translate into clinical settings.

Language: Английский

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Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases

Nature Genetics, Journal Year: 2023, Volume and Issue: 55(1), P. 44 - 53

Published: Jan. 1, 2023

Language: Английский

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