표현형 종단 자료에 대한 유전적 영향의 정량화

학위논문(박사)--서울대학교 대학원 :자연과학대학 협동과정 생물정보학전공,2020. 2. 원성호.The main goal is to identify the progressing effect of SNPs on the important health related phenotypic traits, and lung function specific traits by calculating SNP heritability with longitudinal data. The total 16 prominent health-related phenotypic traits were observed biennially for each subject during 10 years, and 12 spirometric measures were biennially observed for 14 years. SNP-based heritabilities for those phenotype averages and annual change were estimated. Since linear mixed models with two random effects are computationally very intensive, here, we proposed and applied two-stage model. First, the phenotypic average and annual change for each subject were estimated with a linear model, and then both regression coefficients were used as responses to estimate SNP heritability with GCTA software. This approach provides a reasonable and easy method to estimate heritability in longitudinal data and potentially assess both heritability of the phenotypic averages and changes through several periods. In the 16 health-related phenotypes analysis, results show that that significant SNP heritability is objectively confirmed for longitudinal changes in lung function decline including FEV1 in comparison with other health-related indices. In the 12 lung function specific analysis, SNP heritabilities of the annual change rate of FEV1 % predicted and FEV1/FVC were significantly high (hdecline2=0.105, p-value=0.004 for FEV1 % predicted; hdecline2=0.157, p-value=7.25×〖10〗^(-5)for FEV1/FVC). In subgroup analsysis, POST FEV1/FVC (hdecline2=0.399, p-value=0.009) were in never smokers significant high than in ever smokers.유전체 정보(SNP)의 대량생산이 가능해지며 질환의 원인을 규명하고자 질환 또는 위험요인에 대한 유전체 정보를 기반을 둔 전장 유전체 연관성 분석(GWAS)은 지속해서 활발히 진행됐고, 지역 또는 인종에 따라 다양하게 나타나고 있어 국내에서도 많은 결과가 발표되고 있다. 그러나, 실제 질환과 연관 있다고 보고된 SNP들의 설명력은 높지 않았다. 이러한 설명되지 않은 유전적 경향성(missing heritability)에 대한 문제점을 보완하기 위한 유전율 추정 방법들이 제안되고 있고, 최근에는 인구집단 기반(population-based)을 둔 유전율 추정이 많이 진행되고 있다. 현재까지 대부분 population-based 유전율 추정은 단면연구(cross-sectional study)에 집중되어 연구가 진행됐으나 반복측정자료(longitudinal data)를 이용한 유전율 추정 및 유전자-환경, 유전자-시간의 상호작용으로 인한 유전율 추정 분석은 많이 진행되지 않았다. 본 논문에서는 한국인 질병 관련 임상역학의 종단자료 및 유전체 자료를 기반 표현형에 대한 상염색체 공통변이(common variant) 유전적 영향의 추정에 목적을 두어 16가지의 표현형에 대하여 유전율 추정 및 GWAS를 진행하였고, 추가로 12가지의 폐기능관련 표현형에 대하여 유전율 추정을 진행 하였다. 또 표현형과 유전변이의 상호작용으로 인한 유전율에 대한 영향을 추정하였고 종단자료 특성상 분석이 어려운 것을 해결하기 위하여 two-stage 방법론을 제안하여 특정 표현형이 시간으로 인한 변화에 연관된 유전자들을 성공적으로 발굴하였다. 본 연구는 다량의 질병 관련 표현형 종단자료의 분석에 활용될 수 있을 것으로 기대된다.1 Introduction 1 1.1 The background on genetic association studies 1 1.1.1 Overview of genome-wide association studies 1 1.1.2 Single SNP-based analysis in GWAS 3 1.2 The background on heritability estimation 5 1.2.1 Overview of heritability estimation 5 1.2.2 Summary of heritability estimation methods 6 1.3 Overview of GxE analysis 7 1.4 Overview of longitudinal analysis 8 1.5 The purpose of this study 9 1.6 Outline of the thesis 10 2 An overview of genetic effect quantifying analysis with longitudinal data 11 2.1 Challenges of genetic effect quantifying analysis with longitudinal data 11 2.2 Review methods of longitudinal data analysis 13 2.3 Method applied in this paper with longitudinal data analysis 16 3 Identifying progressing effect of SNPs on 16 phenotypic traits with longitudinal data 19 3.1 Introduction 19 3.2 Methods 21 3.2.1 KARE cohort data 21 3.2.2 Genotype data 23 3.2.3 Calculation of phenotype averages and annual changes for each subject 25 3.2.4 Heritability estimation 26 3.2.5 GWAS analysis 26 3.3 Results 26 3.3.1 Estimation of heritability 26 3.3.2 Genome-wide association studies 40 3.4 Discussion 48 4 Heritability analysis reveal the significant effect of SNPs on lung function decline rate 53 4.1 Introduction 53 4.2 Methods 58 4.2.1 Study population and outcome definition 58 4.2.2 Lung functions 58 4.2.3 Genotyping, quality-control and imputation 59 4.2.4 Statistical analysis 60 4.3 Results 62 4.3.1 Characteristics of study subjects 64 4.3.2 The heritability of 12 pulmonary function traits 64 4.3.3 The heritability of smoking subgroups 73 4.4 Discussion 77 5 Summary and Conclusions 80 Bibliography 83 Abstract (Korean) 92Docto

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