Estimation of heritability attributable to single-locus effects with a regression of offspring on mid-parent (ROMP) method for cardiovascular risk factors.
- Author:
Sun Ha JEE
1
;
Jung Yong PARK
;
Ji Eun YOON
;
Minji KIM
;
Eun Young CHO
;
Yang soo JANG
Author Information
1. Graduate School of Health Science and Management, Yonsei University. jsunha@yumc.yonsei.ac.kr
- Publication Type:Original Article
- Keywords:
Quantitative traits;
Heritability;
Cardiovascular;
Risk factor
- MeSH:
Apolipoproteins B;
Cholesterol;
Cholesterol, LDL;
Genome;
Humans;
Linear Models;
Risk Factors*;
Triglycerides
- From:Korean Journal of Epidemiology
2003;25(1):24-31
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: The objective of this study was to estimate the heritability attributable to single-locus effects with a regression of offspring on mid-parent (ROMP) method for cardiovascular risk factors. METHODS: The regression of offspring on mid-parent is determined with and without the inclusion of a single-locus effect, and the difference between the slopes of these two regression is an estimate of the heritability attributable to the single-locus effect. The study population included 1,550 family members of 295 patients, derived from cardiovascular genome center. The risk factors considered were total serum cholesterol, triglyceride, LDL cholesterol, apoAI and apoB. Heritability was estimated from the slope of the linear regression of offspring on mid-parents. RESULTS: Estimated heritability was 35 to 46% for total cholesterol with 6.2% attributable to polymorphism S128R. For triglyceride, the estimated heritability was 47.6% with 2% attributable to polymorphism G-217A. The heritability was 36-46% for LDL-cholesterol. For LDL cholesterol, S128R specific effect was 8.7%. Estimated heritability was 62.2% for apoAI with 3.2% attributable to polymorphism G-217A and 58 to 75% for apoB with 5.4% attributable to polymorphism S128R. CONCLUSIONS: These traits were significantly associated with polymorphism S128R. These results highlight the importance of considering genetic factors in studies of cardiovascular risk factors. Unlike traditional population-based tests of association, ROMP appears to be robust with respect to population stratification.