TY - JOUR
T1 - Epigenetic-age acceleration in the emerging burden of cardiometabolic diseases among migrant and non-migrant African populations: a population-based cross-sectional RODAM substudy
AU - Chilunga, Felix P.
AU - Henneman, Peter
AU - Elliott, Hannah R.
AU - Cronjé, H. Toinét
AU - Walia, Gagandeep K.
AU - Meeks, Karlijn A. C.
AU - Requena-Mendez, Ana
AU - Venema, Andrea
AU - Bahendeka, Silver
AU - Danquah, Ina
AU - Adeyemo, Adebowale
AU - Klipstein-Grobusch, Kerstin
AU - Pieters, Marlien
AU - Mannens, Marcels M. A. M.
AU - Agyemang, Charles
N1 - Funding Information: The authors are grateful to the volunteers participating in the RODAM, IMS, and PURE-SA-NW studies. We also thank all research staff who were involved in these studies. This work was supported by the European Commission under the Framework Programme (grant number 278901) and European Research Council Consolidation (grant number 772244). FPC is supported by the Erasmus Mundus Joint Doctorate Programme of the European Union through the Amsterdam Institute of Global Health and Development (grant agreement 2015?1595). KACM and AA are supported by the Intramural Research Programme of the National Institutes of Health in the Centre for Research on Genomics and Global Health (CRGGH). The CRGGH is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Centre for Information Technology, and the Office of the Director at the National Institutes of Health (1ZIAHG200362). HRE works in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol, which is financially supported by the Medical Research Council and the University of Bristol (MC_UU_00011/5). HTC is supported by a grant from the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Ageing (NNF17OC0027812). Funding Information: The authors are grateful to the volunteers participating in the RODAM, IMS, and PURE-SA-NW studies. We also thank all research staff who were involved in these studies. This work was supported by the European Commission under the Framework Programme (grant number 278901) and European Research Council Consolidation (grant number 772244). FPC is supported by the Erasmus Mundus Joint Doctorate Programme of the European Union through the Amsterdam Institute of Global Health and Development (grant agreement 2015–1595). KACM and AA are supported by the Intramural Research Programme of the National Institutes of Health in the Centre for Research on Genomics and Global Health (CRGGH). The CRGGH is supported by the National Human Genome Research Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Centre for Information Technology, and the Office of the Director at the National Institutes of Health (1ZIAHG200362). HRE works in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol, which is financially supported by the Medical Research Council and the University of Bristol (MC_UU_00011/5). HTC is supported by a grant from the Novo Nordisk Foundation Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Ageing (NNF17OC0027812). Publisher Copyright: © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2021/6/1
Y1 - 2021/6/1
N2 - Background: African populations are going through health transitions due to rapid urbanisation and international migration. However, the role of biological ageing in the emerging burden of cardiometabolic diseases among migrant and non-migrant Africans is unknown. We aimed to examine differences in epigenetic-age acceleration (EAA) as measured by four clocks (Horvath, Hannum, PhenoAge, and GrimAge) and their associations with cardiometabolic factors among migrant Ghanaians residing in Europe and non-migrant Ghanaians residing in Ghana using cross‑sectional data. Methods: In this population-based cross-sectional RODAM substudy, recruitment of urban participants in Ghana was done in two cities (Kumasi and Obuasi), whereas recruitment in rural areas was done in 15 villages in the Ashanti region. In Europe, participants were recruited from the cities of Amsterdam (Netherlands), Berlin (Germany), and London (UK). The method and location of participant recruitment varied according to country and city. Participants were included in the RODAM study if they were older than 25 years, had completed the RODAM study questionnaire, were physically examined, and had blood samples taken. In the present subsample, data for DNA-methylation (DNAm) had to be available for the participants. We did not specify any exclusion criteria. We used genome-wide DNAm data from Ghanaians to quantify EAA. We assessed the correlation between DNAm-based age measures and chronological age, and then we did linear regressions to investigate the associations between EAA and body-mass index (BMI), fasting blood glucose (FBG), blood pressure, alcohol consumption, smoking status, physical activity, and one-carbon metabolism nutrients among migrant and non-migrant populations. We replicated our findings among rural–urban sibling pairs from the India Migration Study and among indigenous South Africans from the PURE-SA-NW study. Findings: Between Feb 2, 2012, and Sept 30, 2014, 736 individuals participated in the RODAM epigenetics substudy, of which 12 (2%) were excluded during DNAm quality control, and a further 12 (2%) were excluded because of genotypic and phenotypic sex discordance. 712 (97%) of 736 participants were included in the analysis; 365 (51%) of these 712 participants were migrants and 347 (49%) were non-migrants. We found that migrant Ghanaians had lower EAA than non-migrant Ghanaians (intrinsic EAA Horvath –0·34 years vs 0·35 years; extrinsic EAA Hannum –0·86 years vs 0·90 years; PhenoAge acceleration –1·68 years vs 1·77 years; and GrimAge acceleration –0·18 years vs 0·19 years). Within migrant Ghanaians, higher FBG was positively associated with EAA measures, with the adjusted regression β for intrinsic EAA being 0·30 (95% CI 0·01 to 0·59) for migrants and 0·12 (−0·04 to 0·28) for non-migrants, for extrinsic EAA being 0·31 (0·05 to 0·56) for migrants and 0·08 (−0·06 to 0·22) for non-migrants, for PhenoAge acceleration being 0·39 (0·07 to 0·71) for migrants and 0·14 (−0·01 to 0·32) for non-migrants, and for GrimAge acceleration being 0·18 (0·01 to 0·34) for migrants and 0·12 (0·03 to 0·21) for non-migrants. Within non-migrant Ghanaians, higher BMI and vitamin-B9 (folate) intake were negatively associated with EAA measures. Our findings on FBG, BMI, and folate were replicated in the independent cohorts. Interpretation: Our study shows that migration is negatively associated with EAA among Ghanaians. Moreover, cardiometabolic factors are differentially associated with EAA within migrant and non-migrant subgroups. Our results call for context-based interventions for cardiometabolic diseases among transitioning populations that account for the effects of biological ageing. Funding: European Commission under the Framework Programme and European Research Council Consolidation.
AB - Background: African populations are going through health transitions due to rapid urbanisation and international migration. However, the role of biological ageing in the emerging burden of cardiometabolic diseases among migrant and non-migrant Africans is unknown. We aimed to examine differences in epigenetic-age acceleration (EAA) as measured by four clocks (Horvath, Hannum, PhenoAge, and GrimAge) and their associations with cardiometabolic factors among migrant Ghanaians residing in Europe and non-migrant Ghanaians residing in Ghana using cross‑sectional data. Methods: In this population-based cross-sectional RODAM substudy, recruitment of urban participants in Ghana was done in two cities (Kumasi and Obuasi), whereas recruitment in rural areas was done in 15 villages in the Ashanti region. In Europe, participants were recruited from the cities of Amsterdam (Netherlands), Berlin (Germany), and London (UK). The method and location of participant recruitment varied according to country and city. Participants were included in the RODAM study if they were older than 25 years, had completed the RODAM study questionnaire, were physically examined, and had blood samples taken. In the present subsample, data for DNA-methylation (DNAm) had to be available for the participants. We did not specify any exclusion criteria. We used genome-wide DNAm data from Ghanaians to quantify EAA. We assessed the correlation between DNAm-based age measures and chronological age, and then we did linear regressions to investigate the associations between EAA and body-mass index (BMI), fasting blood glucose (FBG), blood pressure, alcohol consumption, smoking status, physical activity, and one-carbon metabolism nutrients among migrant and non-migrant populations. We replicated our findings among rural–urban sibling pairs from the India Migration Study and among indigenous South Africans from the PURE-SA-NW study. Findings: Between Feb 2, 2012, and Sept 30, 2014, 736 individuals participated in the RODAM epigenetics substudy, of which 12 (2%) were excluded during DNAm quality control, and a further 12 (2%) were excluded because of genotypic and phenotypic sex discordance. 712 (97%) of 736 participants were included in the analysis; 365 (51%) of these 712 participants were migrants and 347 (49%) were non-migrants. We found that migrant Ghanaians had lower EAA than non-migrant Ghanaians (intrinsic EAA Horvath –0·34 years vs 0·35 years; extrinsic EAA Hannum –0·86 years vs 0·90 years; PhenoAge acceleration –1·68 years vs 1·77 years; and GrimAge acceleration –0·18 years vs 0·19 years). Within migrant Ghanaians, higher FBG was positively associated with EAA measures, with the adjusted regression β for intrinsic EAA being 0·30 (95% CI 0·01 to 0·59) for migrants and 0·12 (−0·04 to 0·28) for non-migrants, for extrinsic EAA being 0·31 (0·05 to 0·56) for migrants and 0·08 (−0·06 to 0·22) for non-migrants, for PhenoAge acceleration being 0·39 (0·07 to 0·71) for migrants and 0·14 (−0·01 to 0·32) for non-migrants, and for GrimAge acceleration being 0·18 (0·01 to 0·34) for migrants and 0·12 (0·03 to 0·21) for non-migrants. Within non-migrant Ghanaians, higher BMI and vitamin-B9 (folate) intake were negatively associated with EAA measures. Our findings on FBG, BMI, and folate were replicated in the independent cohorts. Interpretation: Our study shows that migration is negatively associated with EAA among Ghanaians. Moreover, cardiometabolic factors are differentially associated with EAA within migrant and non-migrant subgroups. Our results call for context-based interventions for cardiometabolic diseases among transitioning populations that account for the effects of biological ageing. Funding: European Commission under the Framework Programme and European Research Council Consolidation.
UR - http://www.scopus.com/inward/record.url?scp=85107340431&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/S2666-7568(21)00087-8
DO - https://doi.org/10.1016/S2666-7568(21)00087-8
M3 - Article
C2 - 35146471
SN - 2666-7568
VL - 2
SP - e327-e339
JO - The Lancet Healthy Longevity
JF - The Lancet Healthy Longevity
IS - 6
ER -