Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity

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Standard

Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. / Hägg, Sara; Ganna, Andrea; Van Der Laan, Sander W; Esko, Tonu; Pers, Tune H; Locke, Adam E; Berndt, Sonja I; Justice, Anne E; Kahali, Bratati; Siemelink, Marten A; Pasterkamp, Gerard; Strachan, David P; Speliotes, Elizabeth K; North, Kari E; Loos, Ruth J F; Hirschhorn, Joel N; Pawitan, Yudi; Ingelsson, Erik; GIANT Consortium.

In: Human Molecular Genetics, Vol. 24, No. 23, 01.12.2015, p. 6849-60.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Hägg, S, Ganna, A, Van Der Laan, SW, Esko, T, Pers, TH, Locke, AE, Berndt, SI, Justice, AE, Kahali, B, Siemelink, MA, Pasterkamp, G, Strachan, DP, Speliotes, EK, North, KE, Loos, RJF, Hirschhorn, JN, Pawitan, Y, Ingelsson, E & GIANT Consortium 2015, 'Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity', Human Molecular Genetics, vol. 24, no. 23, pp. 6849-60. https://doi.org/10.1093/hmg/ddv379

APA

Hägg, S., Ganna, A., Van Der Laan, S. W., Esko, T., Pers, T. H., Locke, A. E., Berndt, S. I., Justice, A. E., Kahali, B., Siemelink, M. A., Pasterkamp, G., Strachan, D. P., Speliotes, E. K., North, K. E., Loos, R. J. F., Hirschhorn, J. N., Pawitan, Y., Ingelsson, E., & GIANT Consortium (2015). Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. Human Molecular Genetics, 24(23), 6849-60. https://doi.org/10.1093/hmg/ddv379

Vancouver

Hägg S, Ganna A, Van Der Laan SW, Esko T, Pers TH, Locke AE et al. Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. Human Molecular Genetics. 2015 Dec 1;24(23):6849-60. https://doi.org/10.1093/hmg/ddv379

Author

Hägg, Sara ; Ganna, Andrea ; Van Der Laan, Sander W ; Esko, Tonu ; Pers, Tune H ; Locke, Adam E ; Berndt, Sonja I ; Justice, Anne E ; Kahali, Bratati ; Siemelink, Marten A ; Pasterkamp, Gerard ; Strachan, David P ; Speliotes, Elizabeth K ; North, Kari E ; Loos, Ruth J F ; Hirschhorn, Joel N ; Pawitan, Yudi ; Ingelsson, Erik ; GIANT Consortium. / Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity. In: Human Molecular Genetics. 2015 ; Vol. 24, No. 23. pp. 6849-60.

Bibtex

@article{99683cf3b4604910a2b0d75895ce1e72,
title = "Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity",
abstract = "To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the {\textquoteleft}VErsatile Gene-based Association Study{\textquoteright} (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P < 2.8 × 10−6 for 17 941 gene tests). We confirmed all loci, and six of them were gene-wide significant in Stage 2 alone. We provide biological support for the loci by pathway, expression and methylation analyses. Our results indicate that gene-based meta-analysis of GWAS provides a useful strategy to find loci of interest that were not identified in standard single-marker analyses due to high allelic heterogeneity. ",
author = "Sara H{\"a}gg and Andrea Ganna and {Van Der Laan}, {Sander W} and Tonu Esko and Pers, {Tune H} and Locke, {Adam E} and Berndt, {Sonja I} and Justice, {Anne E} and Bratati Kahali and Siemelink, {Marten A} and Gerard Pasterkamp and Strachan, {David P} and Speliotes, {Elizabeth K} and North, {Kari E} and Loos, {Ruth J F} and Hirschhorn, {Joel N} and Yudi Pawitan and Erik Ingelsson and {GIANT Consortium}",
note = "{\textcopyright} The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.",
year = "2015",
month = dec,
day = "1",
doi = "10.1093/hmg/ddv379",
language = "English",
volume = "24",
pages = "6849--60",
journal = "Human Molecular Genetics",
issn = "0964-6906",
publisher = "Oxford University Press",
number = "23",

}

RIS

TY - JOUR

T1 - Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity

AU - Hägg, Sara

AU - Ganna, Andrea

AU - Van Der Laan, Sander W

AU - Esko, Tonu

AU - Pers, Tune H

AU - Locke, Adam E

AU - Berndt, Sonja I

AU - Justice, Anne E

AU - Kahali, Bratati

AU - Siemelink, Marten A

AU - Pasterkamp, Gerard

AU - Strachan, David P

AU - Speliotes, Elizabeth K

AU - North, Kari E

AU - Loos, Ruth J F

AU - Hirschhorn, Joel N

AU - Pawitan, Yudi

AU - Ingelsson, Erik

AU - GIANT Consortium

N1 - © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the ‘VErsatile Gene-based Association Study’ (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P < 2.8 × 10−6 for 17 941 gene tests). We confirmed all loci, and six of them were gene-wide significant in Stage 2 alone. We provide biological support for the loci by pathway, expression and methylation analyses. Our results indicate that gene-based meta-analysis of GWAS provides a useful strategy to find loci of interest that were not identified in standard single-marker analyses due to high allelic heterogeneity.

AB - To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the ‘VErsatile Gene-based Association Study’ (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P < 2.8 × 10−6 for 17 941 gene tests). We confirmed all loci, and six of them were gene-wide significant in Stage 2 alone. We provide biological support for the loci by pathway, expression and methylation analyses. Our results indicate that gene-based meta-analysis of GWAS provides a useful strategy to find loci of interest that were not identified in standard single-marker analyses due to high allelic heterogeneity.

U2 - 10.1093/hmg/ddv379

DO - 10.1093/hmg/ddv379

M3 - Journal article

C2 - 26376864

VL - 24

SP - 6849

EP - 6860

JO - Human Molecular Genetics

JF - Human Molecular Genetics

SN - 0964-6906

IS - 23

ER -

ID: 150707993