| Title: | Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort |
| Journal: | Journal of Medical Genetics |
| Published: | 30 Aug 2018 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/30166351/ |
| DOI: | https://doi.org/10.1136/jmedgenet-2018-105437 |
| URL: | https://jmg.bmj.com/content/jmedgenet/55/11/765.full.pdf |
Publication 13745
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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.</p>
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).</p>
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 LINC01432 (p=1.9×10-9) variants associated with male baldness, LDLR variants with hyperlipidaemia (ICD-9:272) (p=9.4×10-10) and variants in IRF4 (p=2.8×10-57), SLC45A2 (p=2.2×10-130), HERC2 (p=2.8×10-176), OCA2 (p=2.4×10-121) and MC1R (p=7.7×10-22) 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 <5×10-9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, CACUL1 and MAP3K9.</p>
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.</p>
15 Keywords
- Anthropometry
- Biological Variation, Individual
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Genotype
- Humans
- Inheritance Patterns
- Male
- Phenotype
- Polymorphism, Single Nucleotide
- Public Health Surveillance
- Quantitative Trait Loci
- Quantitative Trait, Heritable
- Risk Assessment
17 Authors
- Iván Galván-Femenía
- Mireia Obón-Santacana
- David Piñeyro
- Marta Guindo-Martinez
- Xavier Duran
- Anna Carreras
- Raquel Pluvinet
- Juan Velasco
- Laia Ramos
- Susanna Aussó
- J M Mercader
- Lluis Puig
- Manuel Perucho
- David Torrents
- Victor Moreno
- Lauro Sumoy
- Rafael de Cid
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