Dataset Information

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

ABSTRACT: Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

SUBMITTER: Astle WJ

PROVIDER: S-EPMC5300907 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Astle William J WJ Elding Heather H Jiang Tao T Allen Dave D Ruklisa Dace D Mann Alice L AL Mead Daniel D Bouman Heleen H Riveros-Mckay Fernando F Kostadima Myrto A MA Lambourne John J JJ Sivapalaratnam Suthesh S Downes Kate K Kundu Kousik K Bomba Lorenzo L Berentsen Kim K Bradley John R JR Daugherty Louise C LC Delaneau Olivier O Freson Kathleen K Garner Stephen F SF Grassi Luigi L Guerrero Jose J Haimel Matthias M Janssen-Megens Eva M EM Kaan Anita A Kamat Mihir M Kim Bowon B Mandoli Amit A Marchini Jonathan J Martens Joost H A JHA Meacham Stuart S Megy Karyn K O'Connell Jared J Petersen Romina R Sharifi Nilofar N Sheard Simon M SM Staley James R JR Tuna Salih S van der Ent Martijn M Walter Klaudia K Wang Shuang-Yin SY Wheeler Eleanor E Wilder Steven P SP Iotchkova Valentina V Moore Carmel C Sambrook Jennifer J Stunnenberg Hendrik G HG Di Angelantonio Emanuele E Kaptoge Stephen S Kuijpers Taco W TW Carrillo-de-Santa-Pau Enrique E Juan David D Rico Daniel D Valencia Alfonso A Chen Lu L Ge Bing B Vasquez Louella L Kwan Tony T Garrido-Martín Diego D Watt Stephen S Yang Ying Y Guigo Roderic R Beck Stephan S Paul Dirk S DS Pastinen Tomi T Bujold David D Bourque Guillaume G Frontini Mattia M Danesh John J Roberts David J DJ Ouwehand Willem H WH Butterworth Adam S AS Soranzo Nicole N

Cell 20161101 5

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotype ...[more]

PMID: 27863252

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Project description:BACKGROUND:There are now over 2000 loci in the human genome where genome wide association studies (GWAS) have found one or more SNPs to be associated with altered risk of a complex trait disease. At each of these loci, there must be some molecular level mechanism relevant to the disease. What are these mechanisms and how do they contribute to disease? RESULTS:Here we consider the roles of three primary mechanism classes: changes that directly alter protein function (missense SNPs), changes that alter transcript abundance as a consequence of variants close-by in sequence, and changes that affect splicing. Missense SNPs are divided into those predicted to have a high impact on in vivo protein function, and those with a low impact. Splicing is divided into SNPs with a direct impact on splice sites, and those with a predicted effect on auxiliary splicing signals. The analysis was based on associations found for seven complex trait diseases in the classic Wellcome Trust Case Control Consortium (WTCCC1) GWA study and subsequent studies and meta-analyses, collected from the GWAS catalog. Linkage disequilibrium information was used to identify possible candidate SNPs for involvement in disease mechanism in each of the 356 loci associated with these seven diseases. With the parameters used, we find that 76% of loci have at least of these mechanisms. Overall, except for the low incidence of direct impact on splice sites, the mechanisms are found at similar frequencies, with changes in transcript abundance the most common. But the distribution of mechanisms over diseases varies markedly, as does the fraction of loci with assigned mechanisms. Many of the implicated proteins have previously been suggested as relevant, but the specific mechanism assignments are new. In addition, a number of new disease relevant proteins are proposed. CONCLUSIONS:The high fraction of GWAS loci with proposed mechanisms suggests that these classes of mechanism play a major role. Other mechanism types, such as variants affecting expression of genes remote in the DNA sequence, will contribute in other loci. Each of the identified putative mechanisms provides a hypothesis for further investigation.

Dataset Information

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Publications

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

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