Abstract
Background and Objectives: Analyzing the association between multiple SNPs and the disease outcomes will provide new insight into the disease's etiology. However, this presents an analytic difficulty due to the large number of SNPs and the complex relationships among them. We proposed using the mixed model approach to identify the significant multi-locus genotypes and the high-order gene-to-gene interactions. Subjects and Methods: We described the mixed effects model and applied this approach to real world data. For the purpose of these analyses, we examine the association of four types of SNPs (AGT5, APOB, CETP3 and ACE6) with the lipid profiles and the measures related with cardiovascular disease. We used data from 672 healthy individuals (283 males and 389 females) who were without cardiovascular diseases. Results: The results of our analysis suggested that there were significant random genotype patterns and genotype groups according to the gender effect on the lipid profiles. In other words, there was significant variability across the genotype groups because of the effect of gender on the lipid profiles. Conclusion: The mixed model approach provided a flexible statistical framework for controlling potential confounding variables and for identifying a significant genetic contributions that may come about through the effects of multi-locus genotypes or through an interaction between the genotype and environmental variables (e.g. gender) with the variations in quantitative traits (e.g. lipid profiles). There were significant genetic contributions to the variability in the lipid profiles, and these were explained by the 4 SNPs described in our real data.
| Original language | English |
|---|---|
| Pages (from-to) | 229-235 |
| Number of pages | 7 |
| Journal | Korean Circulation Journal |
| Volume | 36 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2006 Mar |
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All Science Journal Classification (ASJC) codes
- Internal Medicine
- Cardiology and Cardiovascular Medicine
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Genetic association analysis of lipid profiles using linear mixed model. / Song, Kijun; Park, Chan Mi; Lim, Kil Seob; Jang, Yang Soo; Kim, Dong Kee.
In: Korean Circulation Journal, Vol. 36, No. 3, 03.2006, p. 229-235.Research output: Contribution to journal › Article
TY - JOUR
T1 - Genetic association analysis of lipid profiles using linear mixed model
AU - Song, Kijun
AU - Park, Chan Mi
AU - Lim, Kil Seob
AU - Jang, Yang Soo
AU - Kim, Dong Kee
PY - 2006/3
Y1 - 2006/3
N2 - Background and Objectives: Analyzing the association between multiple SNPs and the disease outcomes will provide new insight into the disease's etiology. However, this presents an analytic difficulty due to the large number of SNPs and the complex relationships among them. We proposed using the mixed model approach to identify the significant multi-locus genotypes and the high-order gene-to-gene interactions. Subjects and Methods: We described the mixed effects model and applied this approach to real world data. For the purpose of these analyses, we examine the association of four types of SNPs (AGT5, APOB, CETP3 and ACE6) with the lipid profiles and the measures related with cardiovascular disease. We used data from 672 healthy individuals (283 males and 389 females) who were without cardiovascular diseases. Results: The results of our analysis suggested that there were significant random genotype patterns and genotype groups according to the gender effect on the lipid profiles. In other words, there was significant variability across the genotype groups because of the effect of gender on the lipid profiles. Conclusion: The mixed model approach provided a flexible statistical framework for controlling potential confounding variables and for identifying a significant genetic contributions that may come about through the effects of multi-locus genotypes or through an interaction between the genotype and environmental variables (e.g. gender) with the variations in quantitative traits (e.g. lipid profiles). There were significant genetic contributions to the variability in the lipid profiles, and these were explained by the 4 SNPs described in our real data.
AB - Background and Objectives: Analyzing the association between multiple SNPs and the disease outcomes will provide new insight into the disease's etiology. However, this presents an analytic difficulty due to the large number of SNPs and the complex relationships among them. We proposed using the mixed model approach to identify the significant multi-locus genotypes and the high-order gene-to-gene interactions. Subjects and Methods: We described the mixed effects model and applied this approach to real world data. For the purpose of these analyses, we examine the association of four types of SNPs (AGT5, APOB, CETP3 and ACE6) with the lipid profiles and the measures related with cardiovascular disease. We used data from 672 healthy individuals (283 males and 389 females) who were without cardiovascular diseases. Results: The results of our analysis suggested that there were significant random genotype patterns and genotype groups according to the gender effect on the lipid profiles. In other words, there was significant variability across the genotype groups because of the effect of gender on the lipid profiles. Conclusion: The mixed model approach provided a flexible statistical framework for controlling potential confounding variables and for identifying a significant genetic contributions that may come about through the effects of multi-locus genotypes or through an interaction between the genotype and environmental variables (e.g. gender) with the variations in quantitative traits (e.g. lipid profiles). There were significant genetic contributions to the variability in the lipid profiles, and these were explained by the 4 SNPs described in our real data.
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UR - http://www.scopus.com/inward/citedby.url?scp=33645749937&partnerID=8YFLogxK
U2 - 10.4070/kcj.2006.36.3.229
DO - 10.4070/kcj.2006.36.3.229
M3 - Article
AN - SCOPUS:33645749937
VL - 36
SP - 229
EP - 235
JO - Korean Circulation Journal
JF - Korean Circulation Journal
SN - 1738-5520
IS - 3
ER -