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

Albrechtsen, A.; Grarup, N.; Li, Y.; Sparso, T.; Tian, G.; Cao, H.; Jiang, T.; Kim, S. Y.; Korneliussen, T. and Li, Q., et al. (2013) In Diabetologia 56(2). p.298-310
Abstract
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... (More)
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. (Less)
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keywords
Exome sequencing, Genetic epidemiology, Genetics, Lipids, Next-generation sequencing, Obesity, Type 2 diabetes
in
Diabetologia
volume
56
issue
2
pages
298 - 310
publisher
Springer
external identifiers
  • wos:000313075500010
  • scopus:84876276050
ISSN
1432-0428
DOI
10.1007/s00125-012-2756-1
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English
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yes
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56523986-819a-47dd-8322-bd05ce5e7b7d (old id 3476925)
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2013-03-01 07:47:47
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2019-01-20 03:40:02
@article{56523986-819a-47dd-8322-bd05ce5e7b7d,
  abstract     = {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) &gt; 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 &gt; 27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p &lt; 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 &gt; 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.},
  author       = {Albrechtsen, A. and Grarup, N. and Li, Y. and Sparso, T. and Tian, G. and Cao, H. and Jiang, T. and Kim, S. Y. and Korneliussen, T. and Li, Q. and Nie, C. and Wu, R. and Skotte, L. and Morris, A. P. and Ladenvall, Claes and Cauchi, S. and Stancakova, A. and Andersen, G. and Astrup, A. and Banasik, K. and Bennett, A. J. and Bolund, L. and Charpentier, G. and Chen, Y. and Dekker, J. M. and Doney, A. S. F. and Dorkhan, Mozhgan and Forsen, T. and Frayling, T. M. and Groves, C. J. and Gui, Y. and Hallmans, G. and Hattersley, A. T. and He, K. and Hitman, G. A. and Holmkvist, J. and Huang, S. and Jiang, H. and Jin, X. and Justesen, J. M. and Kristiansen, K. and Kuusisto, J. and Lajer, M. and Lantieri, O. and Li, W. and Liang, H. and Liao, Q. and Liu, X. and Ma, T. and Ma, X. and Manijak, M. P. and Marre, M. and Mokrosinski, J. and Morris, A. D. and Mu, B. and Nielsen, A. A. and Nijpels, G. and Nilsson, Peter and Palmer, C. N. A. and Rayner, N. W. and Renstrom, F. and Ribel-Madsen, R. and Robertson, N. and Rolandsson, O. and Rossing, P. and Schwartz, T. W. and Slagboom, P. E. and Sterner, Maria and Tang, M. and Tarnow, L. and Tuomi, T. and van't Riet, E. and van Leeuwen, N. and Varga, T. V. and Vestmar, M. A. and Walker, M. and Wang, B. and Wang, Y. and Wu, H. and Xi, F. and Yengo, L. and Yu, C. and Zhang, X. and Zhang, J. and Zhang, Q. and Zhang, W. and Zheng, H. and Zhou, Y. and Altshuler, D. and 't Hart, L. M. and Franks, P. W. and Balkau, B. and Froguel, P. and McCarthy, M. I. and Laakso, M. and Groop, Leif and Christensen, C. and Brandslund, I. and Lauritzen, T. and Witte, D. R. and Linneberg, A. and Jorgensen, T. and Hansen, T. and Wang, J. and Nielsen, R. and Pedersen, O.},
  issn         = {1432-0428},
  keyword      = {Exome sequencing,Genetic epidemiology,Genetics,Lipids,Next-generation sequencing,Obesity,Type 2 diabetes},
  language     = {eng},
  number       = {2},
  pages        = {298--310},
  publisher    = {Springer},
  series       = {Diabetologia},
  title        = {Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes},
  url          = {http://dx.doi.org/10.1007/s00125-012-2756-1},
  volume       = {56},
  year         = {2013},
}