Genetic and Environmental Regulation on Longitudinal Change of Metabolic Phenotypes in Danish and Chinese Adult Twins

Objective The rate of change in metabolic phenotypes can be highly indicative of metabolic disorders and disorder-related modifications. We analyzed data from longitudinal twin studies on multiple metabolic phenotypes in Danish and Chinese twins representing two populations of distinct ethnic, cultural, social-economic backgrounds and geographical environments. Materials and Methods The study covered a relatively large sample of 502 pairs of Danish adult twins followed up for a long period of 12 years with a mean age at intake of 38 years (range: 18-65) and a total of 181 Chinese adult twin pairs traced for about 7 years with a mean baseline age of 39.5 years (range: 23-64). The classical twin models were fitted to the longitudinal change in each phenotype (Delta phenotype) to estimate the genetic and environmental contributions to the variation in Xi phenotype. Results Moderate to high contributions by the unique environment were estimated for all phenotypes in both Danish (from 0.51 for low density lipoprotein cholesterol up to 0.72 for triglycerides) and Chinese (from 0.41 for triglycerides up to 0.73 for diastolic blood pressure) twins; low to moderate genetic components were estimated for long-term change in most of the phenotypes in Danish twins except for triglycerides and hip circumference. Compared with Danish twins, the Chinese twins tended to have higher genetic control over the longitudinal changes in lipids ( except high density lipoprotein cholesterol) and glucose, higher unique environmental contribution to blood pressure but no genetic contribution to longitudinal change in body mass traits. Conclusion Our results emphasize the major contribution of unique environment to the observed intraindividual variation in all metabolic phenotypes in both samples, and meanwhile reveal differential patterns of genetic and common environmental regulation on changes over time in metabolic phenotypes across the two samples.