title: Application of the back-error propagation artificial neural network (BPANN) on genetic variants in the PPAR-γ and RXR-α gene and risk of metabolic syndrome in a Chinese Han population.
abstract: This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propagation artificial neural network (BPANN). We established the model based on data gathered from metabolic syndrome patients (n = 1012) and normal controls (n = 1069) by BPANN. Mean impact value (MIV) for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction (GMDR) confirmed a joint effect of PPAR-γ and RXR-α based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk factors were in the order of body mass index (BMI), serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 (rs4240711, rs4842194, rs2920502 and rs3856806) models were the best models (cross-validation consistency 10/10, P = 0.0107) with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Xu
authors.initials: X
authors.lastname: Zhao
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Kang
authors.initials: K
authors.lastname: Xu
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Hui
authors.initials: H
authors.lastname: Shi
authors.affiliation: Department of Endocrinology, the Affiliated Changzhou Second Hospital, Nanjing Medical University, Changzhou, Jiangsu 213003, China;
authors.forename: Jinluo
authors.initials: J
authors.lastname: Cheng
authors.affiliation: Department of Endocrinology, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China;
authors.forename: Jianhua
authors.initials: J
authors.lastname: Ma
authors.affiliation: Department of Endocrinology, the Third Affiliated Hospital, Nanjing Medical University, Yizheng, Jiangsu 211400, China.
authors.forename: Yanqin
authors.initials: Y
authors.lastname: Gao
authors.affiliation: Department of Endocrinology, the First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210029, China;
authors.forename: Qian
authors.initials: Q
authors.lastname: Li
authors.affiliation: Department of Endocrinology, the Affiliated Changzhou Second Hospital, Nanjing Medical University, Changzhou, Jiangsu 213003, China;
authors.forename: Xinhua
authors.initials: X
authors.lastname: Ye
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Ying
authors.initials: Y
authors.lastname: Lu
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Xiaofang
authors.initials: X
authors.lastname: Yu
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Juan
authors.initials: J
authors.lastname: Du
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Wencong
authors.initials: W
authors.lastname: Du
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Qing
authors.initials: Q
authors.lastname: Ye
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
authors.forename: Ling
authors.initials: L
authors.lastname: Zhou
keywords: adiponectin; back-error propagation artificial neural network (BPANN); metabolic syndrome; peroxisome proliferators activated receptor-γ (PPAR) gene; retinoid X receptor-α (RXR-α) gene