Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome

• Published in: BMC bioinformatics Vol. 18; no. 1; p. 156
• Main Authors: Yoon, Grace, Zheng, Yinan, Zhang, Zhou, Zhang, Haixiang, Gao, Tao, Joyce, Brian, Zhang, Wei, Guan, Weihua, Baccarelli, Andrea A., Jiang, Wenxin, Schwartz, Joel, Vokonas, Pantel S., Hou, Lifang, Liu, Lei
• Format: Journal Article
• Language: English
• Published: England BioMed Central 07.03.2017
• Subjects: Aging; Bioinformatics; Blood pressure; Cardiovascular disease; Cell division; Cholesterol; CpG Islands; Deoxyribonucleic acid; Diabetes; DNA; DNA Methylation; Epigenetics; Gene expression; Genetic testing; Humans; Hypertension; Iterative methods; Lipids; Male; Markers; Mens health; Metabolic disorders; Metabolic syndrome; Metabolic Syndrome - genetics; Methodology; Models, Statistical; Obesity; Public health; Screening; Studies; Bootstrap; Ultra-high dimensional variable selection; Metabolic syndrome; elastic net; ISIS; methylation
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-017-1568-1

Metabolic syndrome has become a major public health challenge worldwide. The association between metabolic syndrome and DNA methylation is of great research interest. We constructed a binomial model to investigate the association between a metabolic syndrome index and DNA methylation in the Normative Aging Study. We applied the Iterative Sure Independence Screening (ISIS) method with elastic net penalty to DNA methylation levels at 484,548 CpG markers from 659 human subjects, and demonstrated that the screening step in ISIS can significantly improve the performance of the elastic net. The proposed method identifies four CpGs which can be mapped to two biologically relevant and functional genes. Identification of significant CpG markers may potentially have practical implications for disease prevention and treatment.