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Complex traits
Original article
Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort
  1. Iván Galván-Femenía1,
  2. Mireia Obón-Santacana1,2,
  3. David Piñeyro3,
  4. Marta Guindo-Martinez4,
  5. Xavier Duran1,
  6. Anna Carreras1,
  7. Raquel Pluvinet3,
  8. Juan Velasco1,
  9. Laia Ramos3,
  10. Susanna Aussó3,
  11. J M Mercader5,6,
  12. Lluis Puig7,
  13. Manuel Perucho8,
  14. David Torrents4,9,
  15. Victor Moreno2,10,
  16. Lauro Sumoy3,
  17. Rafael de Cid1
  1. 1 GenomesForLife-GCAT Lab Group, Program of Predictive and Personalized Medicine of Cancer (PMPPC), Germans Trias i Pujol Research Institute (IGTP), Crta. de Can Ruti, Badalona, Catalunya, Spain
  2. 2 Unit of Biomarkers and Susceptibility, Cancer Prevention and Control Program, Catalan Institute of Oncology (ICO), IDIBELL and CIBERESP, Barcelona, Spain
  3. 3 High Content Genomics and Bioinformatics Unit, Program of Predictive and Personalized Medicine of Cancer (PMPPC), Germans Trias i Pujol Research Institute (IGTP), Badalona, Catalunya, Spain
  4. 4 Life Sciences - Computational Genomics, Barcelona Supercomputing Center (BSC-CNS), Joint BSC-CRG-IRB Research Program in Computational Biology, Barcelona, Spain
  5. 5 Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, US
  6. 6 Diabetes Unit and Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, US
  7. 7 Blood Division, Banc de Sang i Teixits, Barcelona, Spain
  8. 8 Cancer Genetics and Epigenetics Group, Program of Predictive and Personalized Medicine of Cancer (PMPPC), Germans Trias i Pujol Research Institute (IGTP), Badalona, Catalunya, Spain
  9. 9 ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Catalunya, Spain
  10. 10 Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
  1. Correspondence to Dr Rafael de Cid, GCAT lab Group, Program of Predictive and Personalized Medicine of Cancer (PMPPC), Germans Trias i Pujol Research Institute (IGTP), Crta. de Can Ruti, Badalona 08916, Spain; rdecid{at}igtp.cat

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 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.

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.

  • gwas
  • cohort
  • complex traits
  • multitrait
  • phenome

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jmedgenet-2018-105437

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    Footnotes

    • Contributors All authors contributed to the feedback of the manuscript and played an important role in implementing the study. IG-F, MP, VM and RdC conceived the study. IG-F and RdC planned the study. LP coordinated the cohort recruitment. AC, JV and XD prepared the samples. MO-S and XD curated the epidemiological data variables. DP, RP, LR, SA and LS conducted the genotyping. IG-F, DP and LS analysed the clustering analysis. IG-F, MG-M, JMM and DT conducted the imputation analysis. IG-F and RdC conducted and supervised the genetic analysis. IG-F, MO-S and RdC wrote the manuscript. RdC submitted and supervised the study.

    • Funding This work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) project ADE 10/00026, by the Catalan Departament de Salut and by the Departament d’Empresa i Coneixement de la Generalitat de Catalunya, the Agència de Gestió d’Estudis Universitaris i de Recerca (AGAUR) (SGR 1269, SGR 1589 and SGR 647). RdC is the recipient of a Ramon y Cajal grant (RYC-2011-07822). The Project GCAT is coordinated by the Germans Trias i Pujol Research Institute (IGTP), in collaboration with the Catalan Institute of Oncology (ICO), and in partnership with the Blood and Tissue Bank of Catalonia (BST). IGTP is part of the CERCA Programme/Generalitat de Catalunya.

    • Competing interests None declared.

    • Patient consent Obtained.

    • Ethics approval http://www.ceicgermanstrias.cat/.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Correction notice This article has been corrected since it was published online first. JMM has been added to the authors list and to the ’Contributors' section.