Change search
ReferencesLink to record
Permanent link

Direct link
Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes
Show others and affiliations
2013 (English)In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 56, no 2, 298-310 p.Article in journal (Refereed) Published
Abstract [en]

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) > 1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8x) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI > 27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF > 1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 x 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 x 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 x 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits.

Place, publisher, year, edition, pages
2013. Vol. 56, no 2, 298-310 p.
Keyword [en]
Exome sequencing, Genetic epidemiology, Genetics, Lipids, Next-generation sequencing, Obesity, Type 2 diabetes
National Category
Medical and Health Sciences
URN: urn:nbn:se:umu:diva-64936DOI: 10.1007/s00125-012-2756-1ISI: 000313075500010OAI: diva2:609973
Available from: 2013-03-08 Created: 2013-02-04 Last updated: 2015-04-22Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Hallmans, GöranRolandsson, OlovFranks, Paul W.
By organisation
Nutritional ResearchDepartment of Biobank ResearchFamily MedicineMedicine
In the same journal
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 133 hits
ReferencesLink to record
Permanent link

Direct link