Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort.

J Med Genet
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Abstract

BACKGROUND: Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation.

METHODS: We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-wide association to anthropometric measures in a two-stage meta-analysis with the UK Biobank cohort (n=336 107).

RESULTS: Heritability estimates (eg, skin colour, alcohol consumption, smoking habit, body mass index, educational level or height) revealed an important contribution of SNP variants, ranging from 18% to 77%. Single-trait analysis identified 1785 SNPs with genome-wide significance threshold. From these, several previously reported single-trait hits were confirmed in our sample with (p=1.9×10) variants associated with male baldness, variants with hyperlipidaemia (ICD-9:272) (p=9.4×10) and variants in (p=2.8×10) (p=2.2×10) (p=2.8×10) (p=2.4×10) and (p=7.7×10) associated with hair, eye and skin colour, freckling, tanning capacity and sun burning sensitivity and the Fitzpatrick phototype score, all highly correlated cross-phenotypes. Multitrait meta-analysis of anthropometric variation validated 27 loci in a two-stage meta-analysis with a large British ancestry cohort, six of which are newly reported here (p value threshold

CONCLUSION: Considering multiple-related genetic phenotypes improve associated genome signal detection. These results indicate the potential value of data-driven multivariate phenotyping for genetic studies in large population-based cohorts to contribute to knowledge of complex traits.

Year of Publication
2018
Journal
J Med Genet
Volume
55
Issue
11
Pages
765-778
Date Published
2018 11
ISSN
1468-6244
DOI
10.1136/jmedgenet-2018-105437
PubMed ID
30166351
PubMed Central ID
PMC6252362
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