Linkage and genome-wide association analysis of obesity-related phenotypes: association of weight with the MGAT1 gene

EUROSPAN Consortium, Asa Johansson, Fabio Marroni, Caroline Hayward, Christopher S Franklin, Anatoly V Kirichenko, Inger Jonasson, Andrew A Hicks, Veronique Vitart, Aaron Isaacs, Tatiana Axenovich, Susan Campbell, Jamie Floyd, Nick Hastie, Sara Knott, Gordan Lauc, Irene Pichler, Kresimir Rotim, Sarah H Wild, Irina V ZorkoltsevaJames F Wilson, Igor Rudan, Harry Campbell, Cristian Pattaro, Peter Pramstaller, Ben A Oostra, Alan F Wright, Cornelia M van Duijn, Yurii S Aulchenko, Ulf Gyllensten

Research output: Contribution to journalArticlepeer-review


As major risk-factors for diabetes and cardiovascular diseases, the genetic contribution to obesity-related traits has been of interest for decades. Recently, a limited number of common genetic variants, which have replicated in different populations, have been identified. One approach to increase the statistical power in genetic mapping studies is to focus on populations with increased levels of linkage disequilibrium (LD) and reduced genetic diversity. We have performed joint linkage and genome-wide association analyses for weight and BMI in 3,448 (linkage) and 3,925 (association) partly overlapping healthy individuals from five European populations. A total of four chromosomal regions (two for weight and two for BMI) showed suggestive linkage (lod >2.69) either in one of the populations or in the joint data. At the genome-wide level (nominal P <1.6 x 10(-7), Bonferroni-adjusted P <0.05) one single-nucleotide polymorphism (SNP) (rs12517906) (nominal P = 7.3 x 10(-8)) was associated with weight, whereas none with BMI. The SNP associated with weight is located close to MGAT1. The monoacylglycerol acyltransferase (MGAT) enzyme family is known to be involved in dietary fat absorption. There was no overlap between the linkage regions and the associated SNPs. Our results show that genetic effects influencing weight and BMI are shared across diverse European populations, even though some of these populations have experienced recent population bottlenecks and/or been affected by genetic drift. The analysis enabled us to identify a new candidate gene, MGAT1, associated with weight in women.
Original languageEnglish
Pages (from-to)803-8
Number of pages6
Issue number4
Publication statusPublished - 6 Sep 2012


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