Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes

Publikation

Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes

Wissenschaftlicher Artikel/Review - 19.11.2012

Mu B, Sterner M, Tang M, Tarnow L, Tuomi T, van't Riet E, van Leeuwen N, Varga T V, Vestmar M A, Walker M, Wang B, Wang Y, Slagboom P E, Nielsen A A, Nijpels G, Nilsson P, Palmer C N A, Rayner N W, Renström Frida, Ribel-Madsen R, Robertson N, Rolandsson O, Rossing P, Schwartz T W, Wu H, Xi F, Yengo L, Laakso M, Groop L, Christensen C, Brandslund I, Lauritzen T, Witte D R, Linneberg A, Jørgensen T, Hansen T, Wang J, Nielsen R, McCarthy M I, Froguel P, Yu C, Zhang X, Zhang J, Zhang Q, Zhang W, Zheng H, Zhou Y, Altshuler D, 't Hart L M, Franks P W, Balkau B, Pedersen O, Morris A D, Albrechtsen A, Ladenvall C, Cauchi S, Stančáková A, Andersen G, Astrup A, Banasik K, Bennett A J, Bolund L, Charpentier G, Chen Y, Dekker J M, Morris A P, Skotte L, Grarup N, Li Y, Sparsø T, Tian G, Cao H, Jiang T, Kim S Y, Korneliussen T, Li Q, Nie C, Wu R, Doney A S F, Dorkhan M, Forsen T, Kuusisto J, Lajer M, Lantieri O, Li W, Liang H, Liao Q, Liu X, Ma T, Ma X, Manijak M P, Marre M, Kristiansen K, Justesen J M, Frayling T M, Groves C J, Gui Y, Hallmans G, Hattersley A T, He K, Hitman G A, Holmkvist J, Huang S, Jiang H, Jin X, Mokrosiński J

Zitation

Mu B, Sterner M, Tang M, Tarnow L, Tuomi T, van't Riet E, van Leeuwen N, Varga T, Vestmar M, Walker M, Wang B, Wang Y, Slagboom P, Nielsen A, Nijpels G, Nilsson P, Palmer C, Rayner N, Renström F, Ribel-Madsen R, Robertson N, Rolandsson O, Rossing P, Schwartz T, Wu H, Xi F, Yengo L, Laakso M, Groop L, Christensen C, Brandslund I, Lauritzen T, Witte D, Linneberg A, Jørgensen T, Hansen T, Wang J, Nielsen R, McCarthy M, Froguel P, Yu C, Zhang X, Zhang J, Zhang Q, Zhang W, Zheng H, Zhou Y, Altshuler D, 't Hart L, Franks P, Balkau B, Pedersen O, Morris A, Albrechtsen A, Ladenvall C, Cauchi S, Stančáková A, Andersen G, Astrup A, Banasik K, Bennett A, Bolund L, Charpentier G, Chen Y, Dekker J, Morris A, Skotte L, Grarup N, Li Y, Sparsø T, Tian G, Cao H, Jiang T, Kim S, Korneliussen T, Li Q, Nie C, Wu R, Doney A, Dorkhan M, Forsen T, Kuusisto J, Lajer M, Lantieri O, Li W, Liang H, Liao Q, Liu X, Ma T, Ma X, Manijak M, Marre M, Kristiansen K, Justesen J, Frayling T, Groves C, Gui Y, Hallmans G, Hattersley A, He K, Hitman G, Holmkvist J, Huang S, Jiang H, Jin X, Mokrosiński J. Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes. Diabetologia 2012; 56:298-310.

Art

Wissenschaftlicher Artikel/Review (Englisch)

Zeitschrift

Diabetologia 2012; 56

Veröffentlichungsdatum

19.11.2012

eISSN (Online)

1432-0428

Seiten

298-310

Kurzbeschreibung/Zielsetzung

AIMS/HYPOTHESIS
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.

METHODS
The study comprised three stages. We performed medium-depth (8×) 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.

RESULTS
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 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)).

CONCLUSIONS/INTERPRETATION
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.