title: Genetic and environmental influences on serum lipid tracking: a population-based, longitudinal Chinese twin study.
abstract: We conducted cross-sectional and longitudinal twin analysis to explore genetic and environmental contribution to serum lipid tracking during childhood and adolescence. The study sample was part of a population-based twin cohort that was recruited in the rural areas of the Anhui Province of China. The baseline recruitment of twins was carried out from 1998 through 2000 and the follow-up from 2005 through 2007. Serum lipids showed significant tracking during childhood and adolescence. Participants with lipids at the highest tertile at the baseline tended to remain high at follow-up across ages and Tanner stages, whereas subjects with lipids at the lowest tertile at the baseline tended to remain low at follow-up. Using twin modeling, we showed that genetic and environmental factors contributed to individual variations in lipid levels and tracking from the baseline to the follow-up visit. The estimated tracking correlations for total cholesterol, triglyceride, and LDL cholesterol were in the range of 0.25-0.53 and were predominantly influenced by genetic factors. In contrast, the phenotypic tracking of HDL cholesterol was influenced by both genetic and environmental factors. Our study underscores the importance of considering both environmental and genetic factors in studying the etiology of dyslipidemia.
authors.affiliation: Department of Pediatrics, Children's Memorial Hospital, Children's Memorial Research Center, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60614, USA.
authors.forename: Shanchun
authors.initials: S
authors.lastname: Zhang
authors.forename: Xin
authors.initials: X
authors.lastname: Liu
authors.forename: Jonathan
authors.initials: J
authors.lastname: Necheles
authors.forename: Hui-Ju
authors.initials: HJ
authors.lastname: Tsai
authors.forename: Guoying
authors.initials: G
authors.lastname: Wang
authors.forename: Binyan
authors.initials: B
authors.lastname: Wang
authors.forename: Houxun
authors.initials: H
authors.lastname: Xing
authors.forename: Zhiping
authors.initials: Z
authors.lastname: Li
authors.forename: Xue
authors.initials: X
authors.lastname: Liu
authors.forename: Tonghua
authors.initials: T
authors.lastname: Zang
authors.forename: Xiping
authors.initials: X
authors.lastname: Xu
authors.forename: Xiaobin
authors.initials: X
authors.lastname: Wang
mesh_terms: D000293:Adolescent; D015415:Biomarkers; D016009:Chi-Square Distribution; D002648:Child; D002681:China; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D008078:Cholesterol, LDL / Q000097:blood; D003430:Cross-Sectional Studies; D050171:Dyslipidemias / Q000097:blood / Q000209:etiology* / Q000235:genetics; D004777:Environment; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D050356:Lipid Metabolism / Q000235:genetics*; D008055:Lipids / Q000097:blood*; D008137:Longitudinal Studies; D008297:Male; D016017:Odds Ratio; D010375:Pedigree; D010641:Phenotype; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014280:Triglycerides / Q000097:blood
chemical_list: D015415:Biomarkers; D008076:Cholesterol, HDL; D008078:Cholesterol, LDL; D008055:Lipids; D014280:Triglycerides; D002784:Cholesterol