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Fine mapping genetic associations between the HLA region and extremely high intelligence.

ABSTRACT: General cognitive ability (intelligence) is one of the most heritable behavioural traits and most predictive of socially important outcomes and health. We hypothesized that some of the missing heritability of IQ might lie hidden in the human leukocyte antigen (HLA) region, which plays a critical role in many diseases and traits but is not well tagged in conventional GWAS. Using a uniquely powered design, we investigated whether fine-mapping of the HLA region could narrow the missing heritability gap. Our case-control design included 1,393 cases with extremely high intelligence scores (top 0.0003 of the population equivalent to IQ?>?147) and 3,253 unselected population controls. We imputed variants in 200 genes across the HLA region, one SNP (rs444921) reached our criterion for study-wide significance. SNP-based heritability of the HLA variants was small and not significant (h2?=?0.3%, SE?=?0.2%). A polygenic score from the case-control genetic association analysis of SNPs in the HLA region did not significantly predict individual differences in intelligence in an independent unselected sample. We conclude that although genetic variation in the HLA region is important to the aetiology of many disorders, it does not appear to be hiding much of the missing heritability of intelligence.

SUBMITTER: Zabaneh D

PROVIDER: S-EPMC5259706 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Fine mapping genetic associations between the HLA region and extremely high intelligence.

Zabaneh Delilah D Krapohl Eva E Simpson Michael A MA Miller Mike B MB Iacono William G WG McGue Matt M Putallaz Martha M Lubinski David D Plomin Robert R Breen Gerome G

Scientific reports 20170124

General cognitive ability (intelligence) is one of the most heritable behavioural traits and most predictive of socially important outcomes and health. We hypothesized that some of the missing heritability of IQ might lie hidden in the human leukocyte antigen (HLA) region, which plays a critical role in many diseases and traits but is not well tagged in conventional GWAS. Using a uniquely powered design, we investigated whether fine-mapping of the HLA region could narrow the missing heritability ...[more]

PMID: 28117369

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Project description:BackgroundGenome-wide association studies of asthma have revealed robust associations with variation across the human leukocyte antigen (HLA) complex with independent associations in the HLA class I and class II regions for both childhood-onset asthma (COA) and adult-onset asthma (AOA). However, the specific variants and genes contributing to risk are unknown.MethodsWe used Bayesian approaches to perform genetic fine-mapping for COA and AOA (n=9432 and 21,556, respectively; n=318,167 shared controls) in White British individuals from the UK Biobank and to perform expression quantitative trait locus (eQTL) fine-mapping in immune (lymphoblastoid cell lines, n=398; peripheral blood mononuclear cells, n=132) and airway (nasal epithelial cells, n=188) cells from ethnically diverse individuals. We also examined putatively causal protein coding variation from protein crystal structures and conducted replication studies in independent multi-ethnic cohorts from the UK Biobank (COA n=1686; AOA n=3666; controls n=56,063).ResultsGenetic fine-mapping revealed both shared and distinct causal variation between COA and AOA in the class I region but only distinct causal variation in the class II region. Both gene expression levels and amino acid variation contributed to risk. Our results from eQTL fine-mapping and amino acid visualization suggested that the HLA-DQA1*03:01 allele and variation associated with expression of the nonclassical HLA-DQA2 and HLA-DQB2 genes accounted entirely for the most significant association with AOA in GWAS. Our studies also suggested a potentially prominent role for HLA-C protein coding variation in the class I region in COA. We replicated putatively causal variant associations in a multi-ethnic cohort.ConclusionsWe highlight roles for both gene expression and protein coding variation in asthma risk and identified putatively causal variation and genes in the HLA region. A convergence of genomic, transcriptional, and protein coding evidence implicates the HLA-DQA2 and HLA-DQB2 genes and HLA-DQA1*03:01 allele in AOA.

Project description:Background & aimsAssociation studies have greatly refined the important role of the major histocompatibility complex (MHC) region in autoimmune hepatitis (AIH). However, the effects of human leucocyte antigen (HLA) polymorphisms on AIH are not well established. The aim of this study is to systematically characterise the association of MHC variants with AIH in our well-defined cohort of patients.MethodsWe performed an imputation-based analysis on the extensive association observed within the MHC region using the Han-MHC reference panel, and tested the comprehensive associations of HLA polymorphisms with AIH in 1622 Chinese AIH type 1 patients and 10,466 population controls.ResultsA total of 588 HLA variants were significantly associated with AIH, with HLA-B∗35:01 (p = 8.17 × 10-304; odds ratio [OR] = 7.32) contributing the strongest signal. Stepwise conditional analysis revealed additional independent signals at HLA-B∗08:01 (p = 1.35 × 10-33; OR = 4.26) and rs7765379 (p = 5.08 × 10-18; OR = 1.66). A strong link between the lead HLA variant and clinical phenotypes of AIH was observed: patients with HLA-B∗35:01 were less frequently positive for ANA and tended to have higher serum AST and ALT levels at diagnosis, but lower serum IgG levels.ConclusionsOur study reveals three novel and independent variants at HLA-B∗35:01, HLA-B∗08:01, and rs7765379 associated with AIH across the whole MHC region in the Han Chinese population. The findings illustrate the value of the MHC region in AIH and provide a new perspective for the immunogenetics of AIH.Impact and implicationsThis study revealed three novel and independent variants associated with autoimmune hepatitis across the whole major histocompatibility complex region in the Han Chinese population. These findings are significant in identifying autoantigens, providing insights into the activation of the autoimmune processes, and further advancing our understanding of the immunogenetic basis underlying autoimmune hepatitis.

Project description:In searching for genetic variants for complex diseases with deep sequencing data, genomic marker sets of high-dimensional genotypic data and sparse functional variants are quite common. Existing sequence association tests are incapable of identifying such marker sets or individual causal loci, although they appeared powerful to identify small marker sets with dense functional variants. In sequence association studies of admixed individuals, cryptic relatedness and population structure are known to confound the association analyses.We here propose a unified marker wise test (uFineMap) to accurately localize causal loci and a unified high-dimensional set based test (uHDSet) to identify high-dimensional sparse associations in deep sequencing genomic data of multi-ethnic individuals with random relatedness. These two novel tests are based on scaled sparse linear mixed regressions with Lp (0?<?p?<?1) norm regularization. They jointly adjust for cryptic relatedness, population structure and other confounders to prevent false discoveries and improve statistical power for identifying promising individual markers and marker sets that harbor functional genetic variants of a complex trait.With large scale simulation data and real data analyses, the proposed tests appropriately controlled Type I error rates and appeared to be more powerful than several prominent methods. We illustrated their practical utilities by the applications to DNA sequence data of Framingham Heart Study for osteoporosis. The proposed tests identified 11 novel significant genes that were missed by the prominent famSKAT and GEMMA. In particular, four out of six most significant pathways identified by the uHDSet but missed by famSKAT have been reported to be related to BMD or osteoporosis in the literature.The computational toolkit is available for academic use: https://sites.google.com/site/shaolongscode/home/uhdsetwyp@tulane.eduSupplementary data are available at Bioinformatics online.

Dataset Information

Fine mapping genetic associations between the HLA region and extremely high intelligence.

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Fine mapping genetic associations between the HLA region and extremely high intelligence.

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