Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers

Höglund, Julia; Rafati, Nima; Rask‐Andersen, Mathias; Enroth, Stefan; Karlsson, Torgny; Ek, Weronica E.; Johansson, Åsa

doi:10.1038/s41598-019-53111-7

Cited by 52 publications

(69 citation statements)

References 49 publications

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“…When such a variant was found, conditional analysis was performed and the novelty status updated accordingly. We further incorporated evidence from three association studies with signals that were not reported in the GWAS catalog [40][41][42] . Using this method, there were thirty-nine proteins measured in this study for which we were not able to find evidence of previous studies of genetic associations.…”

Section: Methodsmentioning

confidence: 99%

Whole-genome sequencing analysis of the cardiometabolic proteome

et al. 2020

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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.

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Section: Methodsmentioning

confidence: 99%

Whole-genome sequencing analysis of the cardiometabolic proteome

et al. 2020

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“…Instead of using imputed genotype data, Höglund et al used whole genome sequencing data to carry out genome-wide association studies (GWAS) on the levels of 72 inflammatory proteins. This led to the identification of 18 novel loci that were not identified using genotyped or imputed SNPs [36]. A number of studies have also carried out epigenome-wide association studies (EWAS) on the levels of a small set of inflammatory proteins, including C-reactive protein, interleukins-(1β, 4, 6, 9 and 10), interferon-gamma, transforming growth factor-beta and tumour necrosis factor [37][38][39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults

et al. 2020

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Background: The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear modelbased methods which may fail to account for complex structure and interrelationships within molecular datasets. Methods: In this study, we perform genome-and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares-(OLS) and mixed model-based approaches). Results: We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixedmodel and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease. Conclusions: Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

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“…In a study published by Hoglund et al 72 inflammatory biomarkers were analyzed and 18 novel associations were identified when using GWAS approach on WGS data, that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. This study suggests that we can enhance the power and accuracy of GWAS when using WGS data by having the ability to identify quantitative trait loci and nucleotides (QTNs) [ 31 , 32 ]. A few programs, including the Consortium of Asthma in African Populations of the Americas (CAAPA) and the Trans-Omics for Precision Medicine program (TOPMed) have begun using WGS, and several CNVs, structural variants, and rare coding variants have already been identified [ 33 , 34 , 35 ].…”

Section: Genetics In Asthmamentioning

confidence: 99%

Genetics and Epigenetics in Asthma

Ntontsi

Photiades

Ζervas

et al. 2021

IJMS

104

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Asthma is one of the most common respiratory disease that affects both children and adults worldwide, with diverse phenotypes and underlying pathogenetic mechanisms poorly understood. As technology in genome sequencing progressed, scientific efforts were made to explain and predict asthma’s complexity and heterogeneity, and genome-wide association studies (GWAS) quickly became the preferred study method. Several gene markers and loci associated with asthma susceptibility, atopic and childhood-onset asthma were identified during the last few decades. Markers near the ORMDL3/GSDMB genes were associated with childhood-onset asthma, interleukin (IL)33 and IL1RL1 SNPs were associated with atopic asthma, and the Thymic Stromal Lymphopoietin (TSLP) gene was identified as protective against the risk to TH2-asthma. The latest efforts and advances in identifying and decoding asthma susceptibility are focused on epigenetics, heritable characteristics that affect gene expression without altering DNA sequence, with DNA methylation being the most described mechanism. Other less studied epigenetic mechanisms include histone modifications and alterations of miR expression. Recent findings suggest that the DNA methylation pattern is tissue and cell-specific. Several studies attempt to describe DNA methylation of different types of cells and tissues of asthmatic patients that regulate airway remodeling, phagocytosis, and other lung functions in asthma. In this review, we attempt to briefly present the latest advancements in the field of genetics and mainly epigenetics concerning asthma susceptibility.

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Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers

Cited by 52 publications

References 49 publications

Whole-genome sequencing analysis of the cardiometabolic proteome

Whole-genome sequencing analysis of the cardiometabolic proteome

Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults

Genetics and Epigenetics in Asthma

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