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

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

doi:10.1007/s00125-012-2756-1

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

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

Research output: Contribution to journal › Article › peer-review

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 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.

Original language	English
Pages (from-to)	298-310
Journal	Diabetologia
Volume	56
Issue number	2
DOIs	https://doi.org/10.1007/s00125-012-2756-1
Publication status	Published - 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Subject classification (UKÄ)

Endocrinology and Diabetes

Free keywords

Exome sequencing
Genetic epidemiology
Genetics
Lipids
Next-generation sequencing
Obesity
Type 2 diabetes

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10.1007/s00125-012-2756-1

Cite this

Albrechtsen, A., Grarup, N., Li, Y., Sparso, T., Tian, G., Cao, H., Jiang, T., Kim, S. Y., Korneliussen, T., Li, Q., Nie, C., Wu, R., Skotte, L., Morris, A. P., Ladenvall, C., Cauchi, S., Stancakova, A., Andersen, G., Astrup, A., ... Pedersen, O. (2013). Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes. Diabetologia, 56(2), 298-310. https://doi.org/10.1007/s00125-012-2756-1

@article{56523986819a47dd8322bd05ce5e7b7d,

title = "Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes",

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 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.",

keywords = "Exome sequencing, Genetic epidemiology, Genetics, Lipids, Next-generation sequencing, Obesity, Type 2 diabetes",

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

year = "2013",

doi = "10.1007/s00125-012-2756-1",

language = "English",

volume = "56",

pages = "298--310",

journal = "Diabetologia",

issn = "1432-0428",

publisher = "Springer",

number = "2",

}

Albrechtsen, A, Grarup, N, Li, Y, Sparso, T, Tian, G, Cao, H, Jiang, T, Kim, SY, Korneliussen, T, Li, Q, Nie, C, Wu, R, Skotte, L, Morris, AP, Ladenvall, C, Cauchi, S, Stancakova, A, Andersen, G, Astrup, A, Banasik, K, Bennett, AJ, Bolund, L, Charpentier, G, Chen, Y, Dekker, JM, Doney, ASF, Dorkhan, M, Forsen, T, Frayling, TM, Groves, CJ, Gui, Y, Hallmans, G, Hattersley, AT, He, K, Hitman, GA, Holmkvist, J, Huang, S, Jiang, H, Jin, X, Justesen, JM, Kristiansen, K, Kuusisto, J, Lajer, M, Lantieri, O, Li, W, Liang, H, Liao, Q, Liu, X, Ma, T, Ma, X, Manijak, MP, Marre, M, Mokrosinski, J, Morris, AD, Mu, B, Nielsen, AA, Nijpels, G, Nilsson, P, Palmer, CNA, Rayner, NW, Renstrom, F, Ribel-Madsen, R, Robertson, N, Rolandsson, O, Rossing, P, Schwartz, TW, Slagboom, PE, Sterner, M, Tang, M, Tarnow, L, Tuomi, T, van't Riet, E, van Leeuwen, N, Varga, TV, Vestmar, MA, Walker, M, Wang, B, Wang, Y, Wu, H, Xi, F, Yengo, L, Yu, C, Zhang, X, Zhang, J, Zhang, Q, Zhang, W, Zheng, H, Zhou, Y, Altshuler, D, 't Hart, LM, Franks, PW, Balkau, B, Froguel, P, McCarthy, MI, Laakso, M, Groop, L, Christensen, C, Brandslund, I, Lauritzen, T, Witte, DR, Linneberg, A, Jorgensen, T, Hansen, T, Wang, J, Nielsen, R & Pedersen, O 2013, 'Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes', Diabetologia, vol. 56, no. 2, pp. 298-310. https://doi.org/10.1007/s00125-012-2756-1

TY - JOUR

T1 - Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes

AU - Albrechtsen, A.

AU - Grarup, N.

AU - Li, Y.

AU - Sparso, T.

AU - Tian, G.

AU - Cao, H.

AU - Jiang, T.

AU - Kim, S. Y.

AU - Korneliussen, T.

AU - Li, Q.

AU - Nie, C.

AU - Wu, R.

AU - Skotte, L.

AU - Morris, A. P.

AU - Ladenvall, Claes

AU - Cauchi, S.

AU - Stancakova, A.

AU - Andersen, G.

AU - Astrup, A.

AU - Banasik, K.

AU - Bennett, A. J.

AU - Bolund, L.

AU - Charpentier, G.

AU - Chen, Y.

AU - Dekker, J. M.

AU - Doney, A. S. F.

AU - Dorkhan, Mozhgan

AU - Forsen, T.

AU - Frayling, T. M.

AU - Groves, C. J.

AU - Gui, Y.

AU - Hallmans, G.

AU - Hattersley, A. T.

AU - He, K.

AU - Hitman, G. A.

AU - Holmkvist, J.

AU - Huang, S.

AU - Jiang, H.

AU - Jin, X.

AU - Justesen, J. M.

AU - Kristiansen, K.

AU - Kuusisto, J.

AU - Lajer, M.

AU - Lantieri, O.

AU - Li, W.

AU - Liang, H.

AU - Liao, Q.

AU - Liu, X.

AU - Ma, T.

AU - Ma, X.

AU - Manijak, M. P.

AU - Marre, M.

AU - Mokrosinski, J.

AU - Morris, A. D.

AU - Mu, B.

AU - Nielsen, A. A.

AU - Nijpels, G.

AU - Nilsson, Peter

AU - Palmer, C. N. A.

AU - Rayner, N. W.

AU - Renstrom, F.

AU - Ribel-Madsen, R.

AU - Robertson, N.

AU - Rolandsson, O.

AU - Rossing, P.

AU - Schwartz, T. W.

AU - Slagboom, P. E.

AU - Sterner, Maria

AU - Tang, M.

AU - Tarnow, L.

AU - Tuomi, T.

AU - van't Riet, E.

AU - van Leeuwen, N.

AU - Varga, T. V.

AU - Vestmar, M. A.

AU - Walker, M.

AU - Wang, B.

AU - Wang, Y.

AU - Wu, H.

AU - Xi, F.

AU - Yengo, L.

AU - Yu, C.

AU - Zhang, X.

AU - Zhang, J.

AU - Zhang, Q.

AU - Zhang, W.

AU - Zheng, H.

AU - Zhou, Y.

AU - Altshuler, D.

AU - 't Hart, L. M.

AU - Franks, P. W.

AU - Balkau, B.

AU - Froguel, P.

AU - McCarthy, M. I.

AU - Laakso, M.

AU - Groop, Leif

AU - Christensen, C.

AU - Brandslund, I.

AU - Lauritzen, T.

AU - Witte, D. R.

AU - Linneberg, A.

AU - Jorgensen, T.

AU - Hansen, T.

AU - Wang, J.

AU - Nielsen, R.

AU - Pedersen, O.

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - Exome sequencing

KW - Genetic epidemiology

KW - Genetics

KW - Lipids

KW - Next-generation sequencing

KW - Obesity

KW - Type 2 diabetes

UR - https://www.scopus.com/pages/publications/84876276050

U2 - 10.1007/s00125-012-2756-1

DO - 10.1007/s00125-012-2756-1

M3 - Article

C2 - 23160641

SN - 1432-0428

VL - 56

SP - 298

EP - 310

JO - Diabetologia

JF - Diabetologia

IS - 2

ER -

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

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