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題名 結合家庭、病例及病例-對照分析中疾病遺傳訊息的統計方法
Statistical Methods for Combining Genetic Association Information from Family, Case-Only and Case-Control Analyses
作者 林惠文
Lin, Hui Wen
貢獻者 劉惠美<br>程毅豪
林惠文
Lin,Hui Wen
關鍵詞 病例對照研究
病例研究
病例父母研究
基因與環境交互作用
TDT
結合家庭資料與無相關控制組資料
結合病例對照和單純病例分析
結合病例父母對照和單純病例分析
日期 2008
上傳時間 9-五月-2016 11:37:54 (UTC+8)
摘要 近年來，基因與疾病之關聯分析 (association analysis)
     越來越受到研究學者重視，因為在複雜性疾病與易感性基因之探討中
     傳統的連鎖方法 (linkage method)
     已不適用，所以複雜性疾病與易感性基因的關聯分析也蓬勃發展起來。在本文中我們主要是在探討
     關聯分析中以家庭為研究資料與以群體為研究資料之間的優缺點，進而取長補短提出結合兩種資料之新的關聯分析方法
     來增加估計與檢定之效力。我們同時考慮環境因素，探討基因因素與環境因素之交互作用。
     
     本研究共分為三部份。第一部份探討如何整合病例-父母/病例-同胞
     (case-parent/case-sibling) 與病例-對照 (case-control)
     研究。我們提出一個加權最小平方 (Weighted Least Squares)
     的方法將病例-父母/病例-同胞與病例-對照分析之估計式加以結合，以增進統計檢定之效力。
     
     第二部分旨在探討基因-環境之交互作用。我們提出一個二階段研究設計法。在第一階段研究中，先收集病例資料;
     在第二階段研究中，再收集其相對應之控制組資料。我們提出一個迴歸估計式以結合第一階段之單純病例分析(case-only
     analysis)
     與第二階段之病例-對照分析。此建議之估計式即使在基因因子與環境因子
     獨立之條件 (此條件為單純病例分析所必需)
     不成立的情形下，依然可得出正確之統計推論。
     
     第三部份旨在探討群體分層 (population stratification) 存在
     之情形下，基因-環境之交互作用。我們提出一個二階段研究設計，以病例資料為第一階段資料，
     再從病例資料中隨機抽取一部份病例患者之父母資料為第二階段資料。我們提出一個迴歸估計式結合單純病例研分析與病例-父母分析之估計式。
     此新估計式即可整合單純病例分析與病例-父母分析，同時在群體分層存在之情形下，仍可得出有效之統計推論。
In recent years, there are increasing attention to association
     studies, because linkage method will not be suitable under complex
     disease and susceptible genes. In the thesis, we are probing into
     association of family study and population study. And we combine
     family study and population study for increased efficiency of
     association method. We also consider interesting studies about
     gene-environment interactions. The thesis contains three projects.
     
     The first project focuses on examining when and how the two sources
     of information offered by such studies, one from the
     case-parent/case-sibling analysis, and the other from the
     case-control analysis with data from affected subjects and unrelated
     controls, can be integrated to enhance statistical power. We propose
     a weighted least-squares approach to linearly and optimally combine
     separate estimators from the case-parent/case-sibling and the
     logistic regression analysis for the association parameters.
     
     In the second project, we focus on examining the situation of
     gene-environment interaction. We propose a two-stage design. In the
     first stage, we collect patient data, and we seek out control data
     with respect to cases in the second stage. We propose regression
     analysis estimation in order to combine the case-only analysis in
     the first stage and the case-control analysis in the second stage.
     This estimation earns the correct statistical inference when genes
     and environment factors are not independent.
     
     In the third project, we explore gene-environment interactions under
     population stratification. We propose a two-stage design. In the
     first stage, we collect patient data, and we randomly collect a
     partial data of patient`s parent from the cases in the second stage.
     We propose regression analysis estimation in order to combine the
     case-only analysis and the case-parent analysis. This estimation can
     combine the case-only analysis and the case-parent analysis, and
     attains effective statistical inference under population
     stratification.
參考文獻 Albert PS, Ratnaasinghe D, Tangrea J, et al. (2001) Limitations of the case-only designfor identifying gene-environment interactions. Am J Epidemiol, 154(8):687-693
     
     Allen AS, Rathouz, PJ, Satten GA. (2003) Informative missingness in genetic association studies: case-parent designs. Am J Hum Genet 72:671-680
     
     Allen AS, Satten GA (2007) Inference on haplotype/disease association using parentaffected-child data: the projection conditional on parental haplotypes method.Genet Epidemiol 31:211-223
     
     Andrieu N, Goldstein AM (1998) Epidemiologic and Genetic Approaches in the Study of Gene-Environment Interaction: an Overview of Available Methods. Epidemiol Rev 20:139-147
     
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     Campbell CD, Ogburn EL, Lunetta KL, Lyon HN, Freedman ML, Groop LC, Altshuler D, Ardlie KG, Hirschhorn JN (2005) Demonstrating stratification in a European American population. Nat Genet 37:868-872
     
     Cardon LR, Bell JI (2001) Association study designs for complex diseases. Nat Rev Genet 2:91-99
     
     Carlson CS, Eberle MA, Kruglyak L, Nickerson DA (2004) Mapping complex disease loci in whole-genome association studies. Nature 429:446-452
     
     Chen YH (2004) New Approach to Association Testing in Case-Parent Designs Under Informative Parental Missingness. Genetic Epidemiology 27: 131-140
     
     Chen YH, Chen H (2000) A unified approach to regression analysis under doublesampling designs. J R Statistic Soc B 62:449-460
     
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     Epstein MP, Satten GA (2003) Inference on haplotype effects in case-control studies using unphased genotype data. Am J Hum Genet 73:1316-1329
     
     Epstein MP, Veal CD, Trembath RC, Barker JN, Li C, Satten GA (2005) Genetic association analysis using data from triads and unrelated subjects. Am J Hum Genet 76:592-608
     
     Fahrmeir L, Tutz G (2001) Multivariate statistical modelling based on generalized linear models. Springer-Verlag New York.
     
     Falk CT, Rubinstein P (1987) Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations. Ann Hum Genet 51:227-233
     
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     Hamajima N, Yuasa H, Matsuo K, Kurobe Y (1999) Detection of Gene-Environment Interaction by Case-only Studies. Japanese Journal of Clinical Oncology 29:490-493
     
     Hoggart CJ, Parra EJ, Shriver MD, Bonilla C, Kittles RA, Clayton DG, McKeigue PM(2003) Control of confounding of genetic associations in stratified populations. Am J Hum Genet. 72(6):1492-1504.
     
     Hsu L (2003) Genetic association tests with age at onset. Genet Epidemiol 24:118-127.
     
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     Keavney B (2000) Genetic association studies in complex diseases. Journal of Human Hypertension (2000) 14, 361-367.
     
     Khoury MJ, Flanders WD (1996) Nontraditional Epidemiologic Approaches in the Anal-ysis of Gene Environment Interaction: Case-Control Studies with No Controls.
     American Journal of Epidemiology 144(3):207-213.
     
     Laird NM, Lange C (2006) Family-based designs in the age of large-scale gene-association studies. Nat Rev Genet 7:385-394.
     
     Lander ES, Schork NJ (1994) Genetic dissection of complex traits. Science 265:2037-2048.
     
     Lewontin RC (1988) On measures of gametic disequilibrium. Genetics 120:849-852.
     
     Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models.Biometrika 73:13-22.
     
     Martin ER, Kaplan NL (2000) A Nonte Carlo procedure for two-stage tests with correlated data. Genet Epidemiol 18:48-62.
     
     Mitchell LE (2000) Relationship between case-control studies and the transmission/disequilibrium test. Genet Epidemiol 19:193-201.
     
     Nagelkerke NJ, Hoebee B, Teunis P, Kimman TG (2004) Combining the transmission disequilibrium test and case-control methodology using generalized logistic regression.
     Eur J Hum Genet 12:964-970.
     
     Piegorsch WW, Weinberg CR, Taylor JA (1994) Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. Stat Med. 13(2):153-62.
     
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     Pritchard JK, Donnelly P (2001) Case-control studies of association in structured or admixtured populations. Theor Pop Biol 60:227-237.
     
     Pritchard JK, Stephens M, Rosenberg NA, Donnelly P (2000) Association mapping in structured population. Am J Hum Genet, 67:170-181.
     
     Reich DE, Goldstein DB. (2001) Detecting association in a case-control study while correcting for population stratification.Genet Epidemiol. 22(2):196-201.
     
     Risch NJ (2000) Searching for genetic determinants in the new millennium. Nature 405:847-856.
     
     Rosenberg NA, Pritchard JK,Weber JL, Cann HM, Kidd KK, Zhivotovsky L A, Feldman M W (2002) Genetic structure of human populations. Science 298:2381-2385.
     
     Schaid DJ (1996) General score tests for associations of genetic markers with disease using cases and their parents. Genet Epidemiol 13:423-429.
     
     Schaid DJ (1999) Case-Parents Design for Gene-Environment Interaction. Genetic Epidemiology 16:261-273.
     
     Schaid DJ, Rowland C (1998) Use of parents, sibs, and unrelated controls for detection of associations between genetic markers and disease. Am J Hum Genet 63:1492-1506.
     
     Schaid DJ, Sommer SS (1993) Genotype relative risks: methods for design and analysis of candidate-gene association studies. Am J Hum Genet 53:1114-1126.
     
     Schmidt S, Schaid DJ (1999) Potential misinterpretation of the case-only study to assess gene-environment interaction. American Journal of Epidemiology. 150(8):878-885.
     
     Seber GA (1997) Linear regression analysis. John Wiley and Sons, New York, pp 61-62.
     
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     Shih MC, Whittemore AS (2002) Tests for genetic association using family data. Genetic Epidemiology 22:128-145.
     
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     unrelated individuals. Hum Hered 55:179-190.
     
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     Weinberg CR,Umbach DM (2000) Choosing a retrospective design to assess joint genetic and environmental contributions to risk. Am J Epidemiology, 152(3):197-203.
     
     Yang Q, Khoury MJ, Flanders WD (1997) Sample Size Requirements in Case-Only De-signs to Detect Gene-Environment Interaction. American Journal of Epidemiology
     146(9):713-720.
     
     Zeger SL, Liang KY, Albert PS (1988) Models for longitudinal data: a generalized estimating equation approach. Biometrics 44:1049-1060.
     
     Zhao LP, Li SS, Khalid N (2003) A method for the assessment of disease associations with single-nucleotide polymorphism haplotypes and environmental variables in casecontrol
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描述 博士
國立政治大學
統計學系
92354505
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0923545051
資料類型 thesis
dc.contributor.advisor 劉惠美<br>程毅豪zh_TW
dc.contributor.author (作者) 林惠文zh_TW
dc.contributor.author (作者) Lin,Hui Wenen_US
dc.creator (作者) 林惠文zh_TW
dc.creator (作者) Lin, Hui Wenen_US
dc.date (日期) 2008en_US
dc.date.accessioned 9-五月-2016 11:37:54 (UTC+8)-
dc.date.available 9-五月-2016 11:37:54 (UTC+8)-
dc.date.issued (上傳時間) 9-五月-2016 11:37:54 (UTC+8)-
dc.identifier (其他 識別碼) G0923545051en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/94723-
dc.description (描述) 博士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 92354505zh_TW
dc.description.abstract (摘要) 近年來，基因與疾病之關聯分析 (association analysis)
     越來越受到研究學者重視，因為在複雜性疾病與易感性基因之探討中
     傳統的連鎖方法 (linkage method)
     已不適用，所以複雜性疾病與易感性基因的關聯分析也蓬勃發展起來。在本文中我們主要是在探討
     關聯分析中以家庭為研究資料與以群體為研究資料之間的優缺點，進而取長補短提出結合兩種資料之新的關聯分析方法
     來增加估計與檢定之效力。我們同時考慮環境因素，探討基因因素與環境因素之交互作用。
     
     本研究共分為三部份。第一部份探討如何整合病例-父母/病例-同胞
     (case-parent/case-sibling) 與病例-對照 (case-control)
     研究。我們提出一個加權最小平方 (Weighted Least Squares)
     的方法將病例-父母/病例-同胞與病例-對照分析之估計式加以結合，以增進統計檢定之效力。
     
     第二部分旨在探討基因-環境之交互作用。我們提出一個二階段研究設計法。在第一階段研究中，先收集病例資料;
     在第二階段研究中，再收集其相對應之控制組資料。我們提出一個迴歸估計式以結合第一階段之單純病例分析(case-only
     analysis)
     與第二階段之病例-對照分析。此建議之估計式即使在基因因子與環境因子
     獨立之條件 (此條件為單純病例分析所必需)
     不成立的情形下，依然可得出正確之統計推論。
     
     第三部份旨在探討群體分層 (population stratification) 存在
     之情形下，基因-環境之交互作用。我們提出一個二階段研究設計，以病例資料為第一階段資料，
     再從病例資料中隨機抽取一部份病例患者之父母資料為第二階段資料。我們提出一個迴歸估計式結合單純病例研分析與病例-父母分析之估計式。
     此新估計式即可整合單純病例分析與病例-父母分析，同時在群體分層存在之情形下，仍可得出有效之統計推論。		zh_TW
dc.description.abstract (摘要) In recent years, there are increasing attention to association
     studies, because linkage method will not be suitable under complex
     disease and susceptible genes. In the thesis, we are probing into
     association of family study and population study. And we combine
     family study and population study for increased efficiency of
     association method. We also consider interesting studies about
     gene-environment interactions. The thesis contains three projects.
     
     The first project focuses on examining when and how the two sources
     of information offered by such studies, one from the
     case-parent/case-sibling analysis, and the other from the
     case-control analysis with data from affected subjects and unrelated
     controls, can be integrated to enhance statistical power. We propose
     a weighted least-squares approach to linearly and optimally combine
     separate estimators from the case-parent/case-sibling and the
     logistic regression analysis for the association parameters.
     
     In the second project, we focus on examining the situation of
     gene-environment interaction. We propose a two-stage design. In the
     first stage, we collect patient data, and we seek out control data
     with respect to cases in the second stage. We propose regression
     analysis estimation in order to combine the case-only analysis in
     the first stage and the case-control analysis in the second stage.
     This estimation earns the correct statistical inference when genes
     and environment factors are not independent.
     
     In the third project, we explore gene-environment interactions under
     population stratification. We propose a two-stage design. In the
     first stage, we collect patient data, and we randomly collect a
     partial data of patient`s parent from the cases in the second stage.
     We propose regression analysis estimation in order to combine the
     case-only analysis and the case-parent analysis. This estimation can
     combine the case-only analysis and the case-parent analysis, and
     attains effective statistical inference under population
     stratification.		en_US
dc.description.tableofcontents 第一章 緒論----------------------------------------------p.3
     第二章 結合病例父母/病例同胞和病例對照之新的關聯分析方法-------p.5
     2.1 簡介
     2.2 結合病例父母對照和無相關控制組群體之探討
     2.3 結合病例父母三元體和無相關控制組群體之理論方法
     2.4 檢查資料是否適合合併的檢定方法
     2.5 結合病例同胞對照資料和無相關控制組資料
     2.6 模擬研究
     2.7 結論與探討
     第三章 結合病例對照研究和單純病例研究來探討基因-環境交互作用之新的關聯分析方法-----------------------------------------------p.26
     3.1 簡介
     3.2 研究想法與架構
     3.3 基因因素與環境因素相互獨立的條件不成立時的情況
     3.3.1 離散的基因型資料
     3.3.2 連續的基因型資料
     3.4 結合病例對照與單純病例分析之方法理論
     3.5 模擬研究
     3.6 結論與探討
     第四章 結合家庭和病例資料之新的關聯分析方法------------------p.49
     4.1 簡介
     4.2 親本三元體(Trio) 基因因素和環境因素分析之理論
     4.3 父母資料有缺失時的分析方法
     4.3.1 分析方法理論
     4.3.2 核心家庭資料的估計和檢定
     4.4 結合家庭資料分析和單純病例分析之理論與方法
     4.5 模擬研究
     4.6 結論與探討
     附錄A1
     附錄A2
     附錄B
     附錄C
     參考文獻		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0923545051en_US
dc.subject (關鍵詞) 病例對照研究zh_TW
dc.subject (關鍵詞) 病例研究zh_TW
dc.subject (關鍵詞) 病例父母研究zh_TW
dc.subject (關鍵詞) 基因與環境交互作用zh_TW
dc.subject (關鍵詞) TDTzh_TW
dc.subject (關鍵詞) 結合家庭資料與無相關控制組資料zh_TW
dc.subject (關鍵詞) 結合病例對照和單純病例分析zh_TW
dc.subject (關鍵詞) 結合病例父母對照和單純病例分析zh_TW
dc.title (題名) 結合家庭、病例及病例-對照分析中疾病遺傳訊息的統計方法zh_TW
dc.title (題名) Statistical Methods for Combining Genetic Association Information from Family, Case-Only and Case-Control Analysesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Albert PS, Ratnaasinghe D, Tangrea J, et al. (2001) Limitations of the case-only designfor identifying gene-environment interactions. Am J Epidemiol, 154(8):687-693
     
     Allen AS, Rathouz, PJ, Satten GA. (2003) Informative missingness in genetic association studies: case-parent designs. Am J Hum Genet 72:671-680
     
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