Investigate the Epigenetic Connections of Obesity Between Mother and Child With Machine Learning Methods

Title:Investigate the Epigenetic Connections of Obesity Between Mother and Child With Machine Learning Methods

Volume: 18 Issue: 9

Author(s): Liancheng Lu, Yixue Li*Tao Huang*

Affiliation:

• Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
• Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
• Guangzhou Laboratory, Guangzhou, 510005, China
• School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China
• Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200433, China

• Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China

Abstract:

Introduction: The prevalence of childhood obesity has been increasing in recent decades, and epigenetics is a great process to detect the relationship between children’s obesity and their mothers’ obesity. To investigate the epigenetic connections of obesity between mother and child, we analyzed the saliva DNA methylation profiles from 96 mother-child families. The BMI of both mother and child was measured.

Methods: MCFS (Monte Carlo Feature Selection) and IFS (Incremental Feature Selection) methods were used to select the obesity prediction biomarkers. MCFS analysis indicated that if the child's BMI was greater than 17.46, the mother was very likely to be obese. In other words, the obesity of child and mother were highly connected. 17 obesity marker probes corresponding to 18 genes: ADGRA1, CRYBA2, SRRM4, VIPR2, GRIK2, SLC27A1, CLUHP3, THNSL2, F10, PLEC, HTR3C, ESRRG, PTPRM, ANKRD11, ZFAND2A, RTN2/PPM1N, TEX101, were selected. Most of them were found to be related to obesity in literature.

Results: The results showed whether mothers are obese can be concluded through their children's BMI and methylation patterns. They can help understand the molecular mechanism of obesity.

Conclusion: Epigenetics is a great indicator of obesity. Our results suggested that the obesity status between child and mother was highly correlated. Obesity-related epigenetics changes from the mother remained in the DNA methylation profile of the child's salivary. DNA methylation can partially reflect the living environment and lifestyles.

Cite this article as:

Lu Liancheng, Li Yixue*, Huang Tao*, Investigate the Epigenetic Connections of Obesity Between Mother and Child With Machine Learning Methods, Current Bioinformatics 2023; 18 (9) . https://dx.doi.org/10.2174/1574893618666230526095702