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Multitrait Genome Association Analysis Identifies New Susceptibility Genes Complex traits J Med Genet: first published as 10.1136/jmedgenet-2018-105437 on 30 August 2018. Downloaded from ORIGINAL ARTICLE Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort Iván Galván-Femenía,1 Mireia Obón-Santacana,1,2 David Piñeyro,3 Marta Guindo-Martinez,4 Xavier Duran,1 Anna Carreras,1 Raquel Pluvinet,3 Juan Velasco,1 Laia Ramos,3 Susanna Aussó,3 J M Mercader,5,6 Lluis Puig,7 Manuel Perucho,8 David Torrents,4,9 Victor Moreno,2,10 Lauro Sumoy,3 Rafael de Cid1 ► Additional material is ABSTRact INTRODUCTION published online only. To view, Background Heritability estimates have revealed an Common disorders cause 85% of deaths in the please visit the journal online 1 (http:// dx. doi. org/ 10. 1136/ important contribution of SNP variants for most common European Union (EU). The increasing incidence jmedgenet- 2018- 105437). traits; however, SNP analysis by single-trait genome- and prevalence of cancer, cardiovascular diseases, wide association studies (GWAS) has failed to uncover chronic respiratory diseases, diabetes and mental For numbered affiliations see their impact. In this study, we applied a multitrait GWAS illness represent a challenge that leads to extra costs end of article. approach to discover additional factor of the missing for the healthcare system. Moreover, as European population is getting older, this scenario will be Correspondence to heritability of human anthropometric variation. Dr Rafael de Cid, GCAT lab Methods We analysed 205 traits, including diseases heightened in the next few years. Like complex Group, Program of Predictive identified at baseline in the GCAT cohort (Genomes For traits, many common diseases are complex inher- and Personalized Medicine of Life- Cohort study of the Genomes of Catalonia) (n=4988), ited conditions with genetic and environmental Cancer (PMPPC), Germans Trias determinants. Advancing in their understanding i Pujol Research Institute (IGTP), a Mediterranean adult population-based cohort study Crta. de Can Ruti, Badalona from the south of Europe. We estimated SNP heritability requires the use of multifaceted and long-term 08916, Spain; rdecid@ igtp. cat contribution and single-trait GWAS for all traits from prospective approaches. Cohort analyses provide 15 million SNP variants. Then, we applied a multitrait- an exceptional tool for dissecting the architecture Received 24 April 2018 of complex diseases by contributing knowledge Revised 19 July 2018 related approach to study genome-wide association to Accepted 21 July 2018 anthropometric measures in a two-stage meta-analysis for evidence-based prevention, as exemplified by with the UK Biobank cohort (n=336 107). the Framingham Heart Study2 or the European Results Heritability estimates (eg, skin colour, Prospective Investigation into Cancer and Nutrition alcohol consumption, smoking habit, body mass cohort study.3 index, educational level or height) revealed an In the last decades, high performance DNA geno- http://jmg.bmj.com/ important contribution of SNP variants, ranging from typing technology has fuelled genomic research 18% to 77%. Single-trait analysis identified 1785 in large cohorts, having been the most promising SNPs with genome-wide significance threshold. line in research on the aetiology of most common From these, several previously reported single-trait diseases. Genome-wide association studies (GWAS) hits were confirmed in our sample with LINC01432 have provided valuable information for many single (p=1.9×10−9) variants associated with male baldness, conditions.4 Despite the perception of the limitations on September 24, 2021 by guest. Protected copyright. LDLR variants with hyperlipidaemia (ICD-9:272) of the GWAS analyses, efforts combining massive (p=9.4×10−10) and variants in IRF4 (p=2.8×10−57), data deriving from whole-genome sequencing at SLC45A2 (p=2.2×10−130), HERC2 (p=2.8×10−176), population scale with novel conceptual and meth- OCA2 (p=2.4×10−121) and MC1R (p=7.7×10−22) odological analysis frameworks have been set forth associated with hair, eye and skin colour, freckling, to explore the last frontier of the missing herita- tanning capacity and sun burning sensitivity and the bility issue,5 driving the field of genomic research Fitzpatrick phototype score, all highly correlated cross- on complex diseases to a new age.6Pritchard and phenotypes. Multitrait meta-analysis of anthropometric colleagues recently proposed the breakthrough idea variation validated 27 loci in a two-stage meta- of the omnigenic character of genetic architecture © Author(s) (or their 7 employer(s)) 2018. Re-use analysis with a large British ancestry cohort, six of of diseases and complex traits. They suggested that permitted under CC BY-NC. No which are newly reported here (p value threshold beyond a handful of driver genes (ie, core genes) commercial re-use. See rights <5×10−9) at ZRANB2-AS2, PIK3R1, EPHA7, MAD1L1, directly connected to an illness, the missing herita- and permissions. Published bility could be accounted for by multiple genes (ie, by BMJ. CACUL1 and MAP3K9. Conclusion Considering multiple-related genetic peripheral genes) not clustered in functional path- To cite: Galván-Femenía I, phenotypes improve associated genome signal ways, but dispersed along the genome, explaining Obón-Santacana M, the pleiotropy frequently seen in most complex Piñeyro D, et al. J Med Genet detection. These results indicate the potential value Epub ahead of print: [please of data-driven multivariate phenotyping for genetic traits. Core genes have been already outlined by the include Day Month Year]. studies in large population-based cohorts to contribute GWAS approach, but most of the possible contrib- doi:10.1136/ to knowledge of complex traits. uting genes have been disregarded based on meth- jmedgenet-2018-105437 odological issues such as p value or lower minor Galván-Femenía I, et al. J Med Genet 2018;0:1–14. doi:10.1136/jmedgenet-2018-105437 1 Complex traits J Med Genet: first published as 10.1136/jmedgenet-2018-105437 on 30 August 2018. Downloaded from allele frequency (MAF). Pathway disturbances have also been a Phenome landmark in the search for genetic associations,8 but not always Baseline variables were obtained from a self-reported epidemi- appear to the root of the mechanism of inheritance of complex ological questionnaire and included biological traits, medical diseases, at least for peripheral genes.7 With this challenging diagnoses, drug use, lifestyle habits and sociodemographic vision, a multitrait genome association analysis of the whole and socioeconomic variables.18 Description of GCAT variables phenome9 becomes a more appropriate way to detect peripheral dataset is available at GCAT (see the URLs section). To keep gene variation effects and new network disturbances affecting as many as possible of the genotyped samples in the study, we core genes. Multitrait analysis approaches are developed for imputed anthropometric missing values (<1%) from the overall research of genetically complex conditions using raw or summa- distribution values using statistical approaches. Missing values ry-level data statistics from GWAS in order to explain the largest (<1%) for biological and anthropometric measures (height, possible amount of the covariation between SNPs and traits.10–15 weight, waist and hip circumference, systolic and diastolic blood The contribution of total genetic variation, known as heri- pressure and heart rate) were imputed by stratifying the whole tability (broad-sense heritability, h2), is estimated now from GCAT cohort by gender and age and using multiple imputa- genome-wide studies in large cohorts directly from SNP data tion by the fully conditional specification method, implemented (known as h2SNP). However, even if most disease conditions in the R mice package.19 For GWAS analysis, we retained all have a strong genetic basis, it is well known that our capacity to variables with at least five observations (n=205). For herita- find genetic effects depends on the overall genetic contribution of bility estimates, only variables with at least 500 individuals per the trait. Overall estimations differed depending on the ancestry, class were retained (n=96) for robustness. The description of sample ascertainment, gender and age of the population under the traits and measures included in this study is summarised in study. Recently, data from the UK Biobank determined genetic online supplementary table S1. contributions with a phenome-based approach16 and identi- fied a shared familial environment as a significant important Genotyping, relatedness and population structure factor besides genetic heritability values in 12 common diseases 17 Genotyping of the 5459 GCAT participants (GCATcore) was analysed. done using the Infinium Expanded Multi-Ethnic Genotyping In this study, we present new data on phenotype-wide estima- Array (MEGAEx) (ILLUMINA, San Diego, California, USA). A tion of the heritability of 205 complex traits (including diseases) customised cluster file was produced from the entire sample and new insights into the genetics of anthropometric traits dataset and used for joint calling. We applied PCA to detect any in a Mediterranean Caucasian population using a two-stage hidden substructure and the method of moments for the estima- meta-analysis approach with multiple-related phenotypes tion of identity by descent probabilities to exclude cases with (MRPs). cryptic relatedness. The extensive QC protocol used for
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