Karlijn A C Meeks1, Peter Henneman2, Andrea Venema2, Juliet Addo3, Silver Bahendeka4, Tom Burr5, Ina Danquah6,7, Cecilia Galbete6, Marcel M A M Mannens2, Frank P Mockenhaupt8, Ellis Owusu-Dabo9, Charles N Rotimi10, Matthias B Schulze6, Liam Smeeth3, Joachim Spranger11,12,13, Mohammad H Zafarmand1,14, Adebowale Adeyemo10, Charles Agyemang1. 1. Department of Public Health, Amsterdam Public Health Research Institute, Academic Medical Center, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands. 2. Department of Clinical Genetics, Research Institute for Reproduction and Development, Academic Medical Center, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands. 3. Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK. 4. Mother Kevin Postgraduate Medical School (MKPGMS), Uganda Martyrs University, Kampala, Uganda. 5. Genomics Department, Source BioScience, Nottingham, UK. 6. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. 7. Institute for Social Medicine, Epidemiology and Health Economics, Charité - Universitaetsmedizin Berlin, Berlin, Germany. 8. Institute of Tropical Medicine and International Health, Charité - University Medicine Berlin, Berlin, Germany. 9. School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. 10. Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD, USA. 11. Department of Endocrinology and Metabolism, Charité - University Medicine Berlin, Berlin, Germany. 12. Partner site Berlin, German Centre for Cardiovascular Research (DZHK), Berlin, Germany. 13. Center for Cardiovascular Research (CCR), Charité - University Medicine Berlin, Berlin, Germany. 14. Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Academic Medical Center, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Abstract
BACKGROUND: Type 2 diabetes (T2D) results from a complex interplay between genetics and the environment. Several epigenome-wide association studies (EWAS) have found DNA methylation loci associated with T2D in European populations. However, data from African populations are lacking. We undertook the first EWAS for T2D among sub-Saharan Africans, aiming at identifying ubiquitous and novel DNA methylation loci associated with T2D. METHODS: The Illumina 450k DNA-methylation array was used on whole blood samples of 713 Ghanaian participants (256 with T2D, 457 controls) from the cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) study. Differentially methylated positions (DMPs) for T2D and HbA1c were identified through linear regression analysis adjusted for age, sex, estimated cell counts, hybridization batch, array position and body mass index (BMI). We also did a candidate analysis of previously reported EWAS loci for T2D in non-African populations, identified through a systematic literature search. RESULTS: Four DMPs [cg19693031 (TXNIP), cg04816311 (C7orf50), cg00574958 (CPT1A), cg07988171 (TPM4)] were associated with T2D after correction for inflation by possible systematic biases. The most strongly associated DMP-cg19693031, TXNIP (P = 2.6E-19) -showed hypomethylation in T2D cases compared with controls. Two out of the four DMPs [cg19693031 (TXNIP), cg04816311 (C7orf50)] remained associated with T2D after adjustment for BMI, and one locus [cg07988171 (TPM4)] that has not been reported previously. CONCLUSIONS: In this first EWAS for T2D in sub-Saharan Africans, we have identified four DMPs at epigenome-wide level, one of which is novel. These findings provide insight into the epigenetic loci that underlie the burden of T2D in sub-Saharan Africans.
BACKGROUND:Type 2 diabetes (T2D) results from a complex interplay between genetics and the environment. Several epigenome-wide association studies (EWAS) have found DNA methylation loci associated with T2D in European populations. However, data from African populations are lacking. We undertook the first EWAS for T2D among sub-Saharan Africans, aiming at identifying ubiquitous and novel DNA methylation loci associated with T2D. METHODS: The Illumina 450k DNA-methylation array was used on whole blood samples of 713 Ghanaian participants (256 with T2D, 457 controls) from the cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) study. Differentially methylated positions (DMPs) for T2D and HbA1c were identified through linear regression analysis adjusted for age, sex, estimated cell counts, hybridization batch, array position and body mass index (BMI). We also did a candidate analysis of previously reported EWAS loci for T2D in non-African populations, identified through a systematic literature search. RESULTS: Four DMPs [cg19693031 (TXNIP), cg04816311 (C7orf50), cg00574958 (CPT1A), cg07988171 (TPM4)] were associated with T2D after correction for inflation by possible systematic biases. The most strongly associated DMP-cg19693031, TXNIP (P = 2.6E-19) -showed hypomethylation in T2D cases compared with controls. Two out of the four DMPs [cg19693031 (TXNIP), cg04816311 (C7orf50)] remained associated with T2D after adjustment for BMI, and one locus [cg07988171 (TPM4)] that has not been reported previously. CONCLUSIONS: In this first EWAS for T2D in sub-Saharan Africans, we have identified four DMPs at epigenome-wide level, one of which is novel. These findings provide insight into the epigenetic loci that underlie the burden of T2D in sub-Saharan Africans.
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