1. University of Science and Technology of China, Hefei 230026, China.
2. CAS Key Laboratory of Bio-medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
3. ImmuFucell Biotechnology Co., Ltd., Beijing 100102, China.
4. CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
5. Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom.
6. Department of Medical Molecular Biology, Beijing Institute of Biotechnology, Beijing 100850, China.
7. Medical College, Guizhou University, Guiyang 550025, China.
Cancer incidence and mortality increase with increasing body mass index (BMI), but BMI-associated epigenetic alterations in cancer remain elusive. We hypothesized that BMI would be associated with DNA methylation alterations in cancers. To test this hypothesis, here, we estimated the associations between DNA methylation and BMI through two different methods across 15 cancer types, at approximately 485,000 CpG sites and 2415 samples using data from The Cancer Genome Atlas. After comparing the DNA methylation levels in control BMI and high BMI individuals, we found differentially methylated CpG sites (DMSs) in cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), and uterine corpus endometrial carcinoma (UCEC) (False Discovery Rate < 0.05). The DMSs of COAD or UCEC were enriched in several obesity-induced and cancer-related pathways. Next, when BMI was used as a continuous variable, we identified BMI-associated methylated CpG sites (BMS) (P (Bonferroni) < 0.05) in CHOL (BMS = 1), COAD (BMS = 1), and UCEC (BMS = 4) using multivariable linear regression. In UCEC, three of the BMSs can predict the clinical outcomes and survival of patients with the tumors. Overall, we observed associations between DNA methylation and high BMI in CHOL, COAD, and UCEC. Furthermore, three BMI-associated CpGs were identified as potential biomarkers for UCEC prognosis.
Keywords: Association analysis, Body mass index, Cancer, DNA methylation, Epigenetics