Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI

Whitney L. Do; Dianjianyi Sun; Karlijn Meeks; Pierre Antoine Dugué; Ellen Demerath; Weihua Guan; Shengxu Li; Wei Chen; Roger Milne; Abedowale Adeyemo; Charles Agyemang; Rami Nassir; Jo Ann E. Manson; Aladdin H. Shadyab; Lifang Hou; Steve Horvath; Themistocles L. Assimes; Parveen Bhatti; Kristina M. Jordahl; Andrea A. Baccarelli; Alicia K. Smith; Lisa R. Staimez; Aryeh D. Stein; Eric A. Whitsel; K. M.Venkat Narayan; Karen N. Conneely

doi:10.1016/j.ajhg.2022.12.014

Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI

Whitney L. Do, Dianjianyi Sun, Karlijn Meeks, Pierre Antoine Dugué, Ellen Demerath, Weihua Guan, Shengxu Li, Wei Chen, Roger Milne, Abedowale Adeyemo, Charles Agyemang, Rami Nassir, Jo Ann E. Manson, Aladdin H. Shadyab, Lifang Hou, Steve Horvath, Themistocles L. Assimes, Parveen Bhatti, Kristina M. Jordahl, Andrea A. BaccarelliAlicia K. Smith, Lisa R. Staimez, Aryeh D. Stein, Eric A. Whitsel, K. M.Venkat Narayan, Karen N. Conneely^*

^*Corresponding author for this work

Preventive Medicine

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

12 Scopus citations

Abstract

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E−7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

Original language	English (US)
Pages (from-to)	273-283
Number of pages	11
Journal	American journal of human genetics
Volume	110
Issue number	2
DOIs	https://doi.org/10.1016/j.ajhg.2022.12.014
State	Published - Feb 2 2023

Funding

We would like to acknowledge and thank Drs. Sonia Shah and Peter Visscher for sharing summary statistics which have been included in the discovery portion of this analysis. The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, and 75N92021D00005. WHI EMPC (AS315) was supported by NIEHS grant R01-ES020836 (L.H. A.A.B. E.A.W.). WHI AS311 was supported by American Cancer Society award 125299-RSG-13\u2013100-01-CCE (P.B.). WHI-BAA23 was supported by NHLBI Broad Agency Announcement contract HHSN268201300006C. The RODAM study was supported by the Intramural Research Program of the National Human Genome Research Institute of the National Institutes of Health (NIH) through the Center for Research on Genomics and Global Health (CRGGH) and by the European Commission under the Framework Programme (grant number 278901). The CRGGH is also supported by the National Institute of Diabetes and Digestive and Kidney Diseases and the Office of the Director at the NIH (Z01HG200362). The Atherosclerosis Risk in Communities study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). The authors thank the staff and participants of the ARIC study for their important contributions. Funding was also supported by NIH 5RC2HL102419 and R01NS087541. Additional acknowledgments can be found in the supplemental information. W.L.D. K.M.V.N. and K.N.C. conceived of the study. W.L.D. K.M.V.N. L.R.S. A.D.S. and A.K.S. developed the methods. E.D. W.G. S.L. W.C. D.S. R.M. P.-A.D. K.M. A.A. and C.A. computed and shared the summary statistics from the participating studies in the discovery analysis. L.H. S.H. T.L.A. P.B. K.M.J. E.A.W. and A.A.B. curated and processed the data used in the replication analyses. A.H.S. J.E.M. and R.N. provided cohort expertise for the replication data. W.L.D. performed all statistical analyses with support from K.N.C. W.L.D. drafted the manuscript with content expertise and review from all authors. All authors read and approved of the final manuscript. K.M.J. is an employee of Bristol Myers Squibb. We would like to acknowledge and thank Drs. Sonia Shah and Peter Visscher for sharing summary statistics which have been included in the discovery portion of this analysis. The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health , U.S. Department of Health and Human Services through 75N92021D00001 , 75N92021D00002 , 75N92021D00003 , 75N92021D00004 , and 75N92021D00005 . WHI EMPC (AS315) was supported by NIEHS grant R01-ES020836 (L.H., A.A.B., E.A.W.). WHI AS311 was supported by American Cancer Society award 125299-RSG-13\u2013100-01-CCE (P.B.). WHI-BAA23 was supported by NHLBI Broad Agency Announcement contract HHSN268201300006C. The RODAM study was supported by the Intramural Research Program of the National Human Genome Research Institute of the National Institutes of Health (NIH) through the Center for Research on Genomics and Global Health (CRGGH) and by the European Commission under the Framework Programme (grant number 278901 ). The CRGGH is also supported by the National Institute of Diabetes and Digestive and Kidney Diseases and the Office of the Director at the NIH ( Z01HG200362 ). The Atherosclerosis Risk in Communities study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health , Department of Health and Human Services (contract numbers HHSN268201700001I , HHSN268201700002I , HHSN268201700003I , HHSN268201700004I , and HHSN268201700005I ). The authors thank the staff and participants of the ARIC study for their important contributions. Funding was also supported by NIH 5RC2HL102419 and R01NS087541 . Additional acknowledgments can be found in the supplemental information .

Keywords

BMI
DNA methylation
adiposity
epigenome-wide association study
epigenomics
metabolic disease
obesity
prediction

ASJC Scopus subject areas

Genetics
Genetics(clinical)

UN SDGs

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

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10.1016/j.ajhg.2022.12.014

Cite this

Do, W. L., Sun, D., Meeks, K., Dugué, P. A., Demerath, E., Guan, W., Li, S., Chen, W., Milne, R., Adeyemo, A., Agyemang, C., Nassir, R., Manson, J. A. E., Shadyab, A. H., Hou, L., Horvath, S., Assimes, T. L., Bhatti, P., Jordahl, K. M., ... Conneely, K. N. (2023). Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI. American journal of human genetics, 110(2), 273-283. https://doi.org/10.1016/j.ajhg.2022.12.014

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title = "Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI",

abstract = "This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E−7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.",

keywords = "BMI, DNA methylation, adiposity, epigenome-wide association study, epigenomics, metabolic disease, obesity, prediction",

author = "Do, {Whitney L.} and Dianjianyi Sun and Karlijn Meeks and Dugu{\'e}, {Pierre Antoine} and Ellen Demerath and Weihua Guan and Shengxu Li and Wei Chen and Roger Milne and Abedowale Adeyemo and Charles Agyemang and Rami Nassir and Manson, {Jo Ann E.} and Shadyab, {Aladdin H.} and Lifang Hou and Steve Horvath and Assimes, {Themistocles L.} and Parveen Bhatti and Jordahl, {Kristina M.} and Baccarelli, {Andrea A.} and Smith, {Alicia K.} and Staimez, {Lisa R.} and Stein, {Aryeh D.} and Whitsel, {Eric A.} and Narayan, {K. M.Venkat} and Conneely, {Karen N.}",

note = "Publisher Copyright: {\textcopyright} 2022 American Society of Human Genetics",

year = "2023",

month = feb,

day = "2",

doi = "10.1016/j.ajhg.2022.12.014",

language = "English (US)",

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pages = "273--283",

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Do, WL, Sun, D, Meeks, K, Dugué, PA, Demerath, E, Guan, W, Li, S, Chen, W, Milne, R, Adeyemo, A, Agyemang, C, Nassir, R, Manson, JAE, Shadyab, AH, Hou, L, Horvath, S, Assimes, TL, Bhatti, P, Jordahl, KM, Baccarelli, AA, Smith, AK, Staimez, LR, Stein, AD, Whitsel, EA, Narayan, KMV & Conneely, KN 2023, 'Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI', American journal of human genetics, vol. 110, no. 2, pp. 273-283. https://doi.org/10.1016/j.ajhg.2022.12.014

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AU - Sun, Dianjianyi

AU - Meeks, Karlijn

AU - Dugué, Pierre Antoine

AU - Demerath, Ellen

AU - Guan, Weihua

AU - Li, Shengxu

AU - Chen, Wei

AU - Milne, Roger

AU - Adeyemo, Abedowale

AU - Agyemang, Charles

AU - Nassir, Rami

AU - Manson, Jo Ann E.

AU - Shadyab, Aladdin H.

AU - Hou, Lifang

AU - Horvath, Steve

AU - Assimes, Themistocles L.

AU - Bhatti, Parveen

AU - Jordahl, Kristina M.

AU - Baccarelli, Andrea A.

AU - Smith, Alicia K.

AU - Staimez, Lisa R.

AU - Stein, Aryeh D.

AU - Whitsel, Eric A.

AU - Narayan, K. M.Venkat

AU - Conneely, Karen N.

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N2 - This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E−7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

AB - This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E−7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

KW - BMI

KW - DNA methylation

KW - adiposity

KW - epigenome-wide association study

KW - epigenomics

KW - metabolic disease

KW - obesity

KW - prediction

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SN - 0002-9297

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EP - 283

JO - American journal of human genetics

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Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI

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UN SDGs

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