Genome-wide population-based association study of extremely overweight young adults--the GOYA study

Lavinia Paternoster; David M Evans; Ellen Aagaard Nohr; Claus Holst; Valerie Gaborieau; Paul Brennan; Anette Prior Gjesing; Niels Grarup; Daniel R Witte; Torben Jørgensen; Allan René Linneberg; Torsten Lauritzen; Anelli Sandbaek; Torben Hansen; Oluf Borbye Pedersen; Katherine S Elliott; John P Kemp; Beate St Pourcain; George McMahon; Diana Zelenika; Jörg Hager; Mark Lathrop; Nicholas J Timpson; George Davey Smith; Thorkild I A Sørensen

doi:10.1371/journal.pone.0024303

Genome-wide population-based association study of extremely overweight young adults--the GOYA study

Lavinia Paternoster, David M Evans, Ellen Aagaard Nohr, Claus Holst, Valerie Gaborieau, Paul Brennan, Anette Prior Gjesing, Niels Grarup, Daniel R Witte, Torben Jørgensen, Allan René Linneberg, Torsten Lauritzen, Anelli Sandbaek, Torben Hansen, Oluf Borbye Pedersen, Katherine S Elliott, John P Kemp, Beate St Pourcain, George McMahon, Diana ZelenikaJörg Hager, Mark Lathrop, Nicholas J Timpson, George Davey Smith, Thorkild I A Sørensen

78 Citations (Scopus)

Abstract

Background: Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ~1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. Methodology/Principal Findings: From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ~212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10 ^-8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Significance: Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.

Original language	English
Article number	e24303
Journal	P L o S One
Volume	6
Issue number	9
ISSN	1932-6203
DOIs	https://doi.org/10.1371/journal.pone.0024303
Publication status	Published - 15 Sept 2011

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Paternoster, L., Evans, D. M., Nohr, E. A., Holst, C., Gaborieau, V., Brennan, P., Gjesing, A. P., Grarup, N., Witte, D. R., Jørgensen, T., Linneberg, A. R., Lauritzen, T., Sandbaek, A., Hansen, T., Pedersen, O. B., Elliott, K. S., Kemp, J. P., St Pourcain, B., McMahon, G., ... Sørensen, T. I. A. (2011). Genome-wide population-based association study of extremely overweight young adults--the GOYA study. P L o S One, 6(9), [e24303]. https://doi.org/10.1371/journal.pone.0024303

Paternoster, L, Evans, DM, Nohr, EA, Holst, C, Gaborieau, V, Brennan, P, Gjesing, AP, Grarup, N, Witte, DR, Jørgensen, T, Linneberg, AR, Lauritzen, T, Sandbaek, A, Hansen, T, Pedersen, OB, Elliott, KS, Kemp, JP, St Pourcain, B, McMahon, G, Zelenika, D, Hager, J, Lathrop, M, Timpson, NJ, Smith, GD & Sørensen, TIA 2011, 'Genome-wide population-based association study of extremely overweight young adults--the GOYA study', P L o S One, vol. 6, no. 9, e24303. https://doi.org/10.1371/journal.pone.0024303

@article{9a26bd9954844f3a8c6c34ee155f67e4,

title = "Genome-wide population-based association study of extremely overweight young adults--the GOYA study",

abstract = "Background: Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ~1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. Methodology/Principal Findings: From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ~212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10 -8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Significance: Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.",

author = "Lavinia Paternoster and Evans, {David M} and Nohr, {Ellen Aagaard} and Claus Holst and Valerie Gaborieau and Paul Brennan and Gjesing, {Anette Prior} and Niels Grarup and Witte, {Daniel R} and Torben J{\o}rgensen and Linneberg, {Allan Ren{\'e}} and Torsten Lauritzen and Anelli Sandbaek and Torben Hansen and Pedersen, {Oluf Borbye} and Elliott, {Katherine S} and Kemp, {John P} and {St Pourcain}, Beate and George McMahon and Diana Zelenika and J{\"o}rg Hager and Mark Lathrop and Timpson, {Nicholas J} and Smith, {George Davey} and S{\o}rensen, {Thorkild I A}",

year = "2011",

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day = "15",

doi = "10.1371/journal.pone.0024303",

language = "English",

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issn = "1932-6203",

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TY - JOUR

T1 - Genome-wide population-based association study of extremely overweight young adults--the GOYA study

AU - Paternoster, Lavinia

AU - Evans, David M

AU - Nohr, Ellen Aagaard

AU - Holst, Claus

AU - Gaborieau, Valerie

AU - Brennan, Paul

AU - Gjesing, Anette Prior

AU - Grarup, Niels

AU - Witte, Daniel R

AU - Jørgensen, Torben

AU - Linneberg, Allan René

AU - Lauritzen, Torsten

AU - Sandbaek, Anelli

AU - Hansen, Torben

AU - Pedersen, Oluf Borbye

AU - Elliott, Katherine S

AU - Kemp, John P

AU - St Pourcain, Beate

AU - McMahon, George

AU - Zelenika, Diana

AU - Hager, Jörg

AU - Lathrop, Mark

AU - Timpson, Nicholas J

AU - Smith, George Davey

AU - Sørensen, Thorkild I A

PY - 2011/9/15

Y1 - 2011/9/15

N2 - Background: Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ~1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. Methodology/Principal Findings: From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ~212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10 -8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Significance: Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.

AB - Background: Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ~1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. Methodology/Principal Findings: From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ~212,000 individuals). We followed up novel (at the time of the study) association signals (p<0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P<5×10 -8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p<0.001), and nominal association (p<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Significance: Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.

U2 - 10.1371/journal.pone.0024303

DO - 10.1371/journal.pone.0024303

M3 - Journal article

C2 - 21935397

SN - 1932-6203

VL - 6

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 9

M1 - e24303

ER -

Genome-wide population-based association study of extremely overweight young adults--the GOYA study

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