TY - JOUR
T1 - Epigenome-wide meta-analysis of BMI in nine cohorts
T2 - Examining the utility of epigenetically predicted BMI
AU - Do, Whitney L.
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.
N1 - Funding Information:
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-13–100-01-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.
Funding Information:
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-13–100-01-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 .
Publisher Copyright:
© 2022 American Society of Human Genetics
PY - 2023/2/2
Y1 - 2023/2/2
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 - adiposity
KW - BMI
KW - DNA methylation
KW - epigenome-wide association study
KW - epigenomics
KW - metabolic disease
KW - obesity
KW - prediction
UR - http://www.scopus.com/inward/record.url?scp=85147457765&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147457765&partnerID=8YFLogxK
U2 - 10.1016/j.ajhg.2022.12.014
DO - 10.1016/j.ajhg.2022.12.014
M3 - Article
C2 - 36649705
AN - SCOPUS:85147457765
SN - 0002-9297
VL - 110
SP - 273
EP - 283
JO - American Journal of Human Genetics
JF - American Journal of Human Genetics
IS - 2
ER -