Analysis of the Relative Effects of SNPs within a Gene to Serum Lipid ProfilesUsing Stepwise Linear Regression

BACKGROUND AND OBJECTIVES: It is very important to distinguish between the primary and secondary genetic effects at different sites within a small genetic region. Therefore, we evaluated the relative effects of single nucleotide polymorphisms (SNPs) within a gene on the serum lipid profiles by using individual data. SUBJECTS AND METHODS: To evaluate the contributions of SNPs in a region to the serum lipid profiles (total cholesterol, triglyceride, low density lipoprotein, high density lipoprotein), we used data that consisted of 808 individuals (327 males and 481 females) who did not have cardiovascular disease. In this study, we used a stepwise regression procedure to analyze the relative effects of four single nucleotide polymorphisms (ACE6, ACE7, ACE8, ACE10) in a gene region on the development of the serum lipid profiles in each gender group. RESULTS: In the males, there were epistatic interaction effects between two loci (ACE6xACE7, ACE6xACE8, ACE6xACE10, ACE8xACE10 and ACE7xACE8) and among three loci (ACE6xACE7xACE8, ACE6xACE7xACE10 and ACE6xACE8xACE10). Also, there are interaction effects between two loci (ACE6xACE7, ACE6xACE8, ACE6xACE10, ACE7xACE10 and ACE8xACE10) and among three loci (ACE6xACE7xACE8, ACE6xACE7xACE10, ACE6xACE8xACE10 and ACE7xACE8xACE10) in the females. CONCLUSION: The results suggested that each of these loci is important in causing a relative change of the serum lipid profiles, even with simultaneously accounting for the effects at the other loci. In the results of the analysis, there existed the effects of individual loci and significant interaction between the loci on the serum lipid profiles in each gender group. It was confirmed that this stepwise regression method can be suitable for evaluating the relative effects of SNPs and it is easily performed.ope

Comparison of methods for linkage analysis of affected sibship data

의학전산통계학협동과정 의학통계학전공/석사[한글] 질적 형질에 대한 연관성 분석은 크게 두 가지로 구분 할 수 있는데, 전통적인 연관성 분석 방법으로 알려진 모형 기반 분석과 그렇지 않은 모형 무관 분석 방법이다. 당뇨나 심장병, 고혈압, 정신분열증등과 같은 복합질병의 경우 멘델의 유전법칙을 잘 따르지 않기 때문에 모형 기반 분석 방법을 사용하는 것보다 모형 무관 분석 방법을 사용하는 것이 효율적이라고 알려져 있다. 이러한 모형 무관 분석 방법 중 이환 형제 쌍 자료를 이용한 분석 방법은 형제 쌍 간의 유전적 일치 비율을 기준으로 공유하고 있는 대립유전자의 분포를 이용하는 것으로 크게 proportion test, mean test, minmax test로 구분 할 수 있다.본 연구에서는 이환 형제수가 3명 이상인 형제집단자료로 확장된 경우, 이환 형제 쌍 자료를 이용하는 분석 방법 중 유전 형식에 상관없이 로버스트한 방법으로 알려진 minmax test에 형제 쌍의 가중치를 고려할 수 있는 방법들 즉, 동일 가중 방법, Suarez의 방법, Hodge의 방법을 적용하여 그 성능을 비교하였다. 모의실험자료를 이용하여 비교한 결과 표식유전자의 빈도, 형질의 유전 형식, 형제수에 상관없이 Suarez의 방법이 가장 검정력이 높은 방법으로 드러났다. 또한, 동일 가중 방법을 제외하고는 표식유전자의 빈도가 높아질수록, 형제수가 많아질수록 더 높은 검정력을 보였고, 이러한 현상은 우성 유전 형식을 가정한 자료에서 더욱 두드러지게 나타났다. [영문]The classical model-based method of linkage analysis for qualitative trait has been successful in mapping Mendelian disease genes in humans. However, for complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. Of these model-free methods, linkage analysis using affected sib-pair is a powerful method based on an elegantly straightforward principle, that is, pairs of affected sibs will tend toward excess sharing of alleles at loci of some region of interest across the genome. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i. e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. These methods are originally designed for use on affected sib-pairs but, in practice, it is likely that the sample collected for a linkage study will contain a number of sibships including three or more affected siblings.In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. Those weighting schemes are that of regarding all possible affected sib-pairs from each sibships independently(called "all possible method"), and that of Suarez(1984) and Hodge(1979).In simulation result, we found that the method based on Suarez'' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especially.ope

Comparison of Methods for Linkage Analysis of Affected Sibship Data

For complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i.e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. In simulation result, we found that the method based on Suarez' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especiallyope