Literature DB >> 17317968

Exploiting Hardy-Weinberg equilibrium for efficient screening of single SNP associations from case-control studies.

Jinbo Chen1, Nilanjan Chatterjee.   

Abstract

In case-control studies, the assessment of the association between a binary disease outcome and a single nucleotide polymorphism (SNP) is often based on comparing the observed genotype distribution for the cases against that for the controls. In this article, we investigate an alternative analytic strategy in which the observed genotype frequencies of cases are compared against the expected genotype frequencies of controls assuming Hardy-Weinberg Equilibrium (HWE). Assuming HWE for controls, we derive closed-form expressions for maximum likelihood estimates of the genotype-specific disease odds ratio (OR) parameters and related variance-covariances. Based on these estimates and their variance-covariance structure, we then propose a two-degree-of-freedom test for disease-SNP association. We show that the proposed test can have substantially higher power than a variety of existing methods, especially when the true effect of the SNP is recessive. We also obtain analytic expressions for the bias of the OR estimates when the underlying HWE assumption is violated. We conclude that the novel test would be particularly useful for analyzing data from the initial 'screening' stages of contemporary multi-stage association studies.

Mesh:

Year:  2007        PMID: 17317968     DOI: 10.1159/000099996

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  24 in total

1.  Testing gene-environment interaction in large-scale case-control association studies: possible choices and comparisons.

Authors:  Bhramar Mukherjee; Jaeil Ahn; Stephen B Gruber; Nilanjan Chatterjee
Journal:  Am J Epidemiol       Date:  2011-12-22       Impact factor: 4.897

2.  Using family members to augment genetic case-control studies of a life-threatening disease.

Authors:  Lu Chen; Clarice R Weinberg; Jinbo Chen
Journal:  Stat Med       Date:  2016-02-11       Impact factor: 2.373

3.  Powerful multi-marker association tests: unifying genomic distance-based regression and logistic regression.

Authors:  Fang Han; Wei Pan
Journal:  Genet Epidemiol       Date:  2010-11       Impact factor: 2.135

4.  Efficient designs of gene-environment interaction studies: implications of Hardy-Weinberg equilibrium and gene-environment independence.

Authors:  Jinbo Chen; Guolian Kang; Tyler Vanderweele; Cuilin Zhang; Bhramar Mukherjee
Journal:  Stat Med       Date:  2012-02-24       Impact factor: 2.373

5.  Exploiting population samples to enhance genome-wide association studies of disease.

Authors:  Shachar Kaufman; Saharon Rosset
Journal:  Genetics       Date:  2014-03-10       Impact factor: 4.562

6.  Correlation between single-nucleotide polymorphisms and statin-induced myopathy: a mixed-effects model meta-analysis.

Authors:  Qian Xiang; Xiao-Dan Zhang; Guang-Yan Mu; Zhe Wang; Zhi-Yan Liu; Qiu-Fen Xie; Kun Hu; Zhuo Zhang; Ling-Yue Ma; Jie Jiang; Yi-Min Cui
Journal:  Eur J Clin Pharmacol       Date:  2020-11-04       Impact factor: 2.953

7.  Analysis of Case-Control Association Studies: SNPs, Imputation and Haplotypes.

Authors:  Nilanjan Chatterjee; Yi-Hau Chen; Sheng Luo; Raymond J Carroll
Journal:  Stat Sci       Date:  2009-11-01       Impact factor: 2.901

Review 8.  Associations between single-nucleotide polymorphisms and inflammatory bowel disease-associated colorectal cancers in inflammatory bowel disease patients: a meta-analysis.

Authors:  H Li; Z Jin; X Li; L Wu; J Jin
Journal:  Clin Transl Oncol       Date:  2017-02-27       Impact factor: 3.405

9.  Genetic variation in insulin-like growth factors and brain tumor risk.

Authors:  Stefan Lönn; Nathaniel Rothman; William R Shapiro; Howard A Fine; Robert G Selker; Peter M Black; Jay S Loeffler; Amy A Hutchinson; Peter D Inskip
Journal:  Neuro Oncol       Date:  2008-06-18       Impact factor: 12.300

10.  A new system identification approach to identify genetic variants in sequencing studies for a binary phenotype.

Authors:  Guolian Kang; Wenjian Bi; Yanlong Zhao; Ji-Feng Zhang; Jun J Yang; Heng Xu; Mignon L Loh; Stephen P Hunger; Mary V Relling; Stanley Pounds; Cheng Cheng
Journal:  Hum Hered       Date:  2014-07-30       Impact factor: 0.444

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.