Comparison of the Concordance of Cardiometabolic Diseases and Physical and Laboratory Examination Findings between Monozygotic and Dizygotic Korean Adult Twins: A Cross-Sectional Study Using KoGES HTS Data.
Ho Suk KangSo Young KimHyo Geun ChoiHyun LimJoo-Hee KimJi Hee KimSeong-Jin ChoEun Sook NamKyueng Whan MinHa Young ParkNan Young KimYounghee ChoiMi Jung KwonPublished in: Nutrients (2022)
This study investigated the contribution of genetic and environmental factors to cardiometabolic diseases (CMDs) by comparing disease concordance in monozygotic and dizygotic twins. This cross-sectional study analyzed 1294 (1040 monozygotic and 254 dizygotic) twin pairs (>20 years) based on the Korean Genome and Epidemiology Study data (2005-2014). The odds ratios of disease concordance were calculated using binomial and multinomial logistic regression models. The occurrence of CMDs (hypertension, hyperlipidemia, type 2 diabetes, cerebral stroke, transient ischemic attack, and ischemic heart disease) and related physical and laboratory levels did not differ between the monozygotic and dizygotic twin groups. The odds for concordance of the presence/absence of CMDs and the likelihood of incident CMD within monozygotic twins were comparable to that of dizygotic twins. The absolute differences in hemoglobin A1c, insulin, low- and high-density lipoprotein cholesterol, total cholesterol, triglycerides, and systolic blood pressure were lower in monozygotic twins than in dizygotic twins. Absolute differences in fasting glucose and diastolic blood pressure did not differ between groups. Although baseline levels of several laboratory parameters related to CMD showed a strong likelihood of heritability in monozygotic twins, CMD phenotype appears to be largely affected by environmental factors.
Keyphrases
- blood pressure
- gestational age
- type diabetes
- hypertensive patients
- blood glucose
- physical activity
- left ventricular
- cerebral ischemia
- heart rate
- mental health
- cardiovascular disease
- electronic health record
- heart failure
- risk assessment
- genome wide
- subarachnoid hemorrhage
- preterm birth
- atrial fibrillation
- brain injury
- mass spectrometry
- skeletal muscle
- risk factors
- atomic force microscopy
- dna methylation
- artificial intelligence
- machine learning
- high resolution
- red blood cell
- low density lipoprotein