Literature DB >> 28132020

Simultaneous Modeling of Disease Status and Clinical Phenotypes To Increase Power in Genome-Wide Association Studies.

Michael Bilow1, Fernando Crespo2,3, Zhicheng Pan4, Eleazar Eskin1,5, Susana Eyheramendy6.   

Abstract

Genome-wide association studies have identified thousands of variants implicated in dozens of complex diseases. Most studies collect individuals with and without disease and search for variants with different frequencies between the groups. For many of these studies, additional disease traits are also collected. Jointly modeling clinical phenotype and disease status is a promising way to increase power to detect true associations between genetics and disease. In particular, this approach increases the potential for discovering genetic variants that are associated with both a clinical phenotype and a disease. Standard multivariate techniques fail to effectively solve this problem, because their case-control status is discrete and not continuous. Standard approaches to estimate model parameters are biased due to the ascertainment in case-control studies. We present a novel method that resolves both of these issues for simultaneous association testing of genetic variants that have both case status and a clinical covariate. We demonstrate the utility of our method using both simulated data and the Northern Finland Birth Cohort data.
Copyright © 2017 by the Genetics Society of America.

Keywords:  covariates; multivariate analysis

Mesh:

Year:  2017        PMID: 28132020      PMCID: PMC5340321          DOI: 10.1534/genetics.116.198473

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  20 in total

1.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

2.  Characterizing learning by simultaneous analysis of continuous and binary measures of performance.

Authors:  M J Prerau; A C Smith; Uri T Eden; Y Kubota; M Yanike; W Suzuki; A M Graybiel; E N Brown
Journal:  J Neurophysiol       Date:  2009-08-19       Impact factor: 2.714

3.  Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1.

Authors:  Christopher I Amos; Xifeng Wu; Peter Broderick; Ivan P Gorlov; Jian Gu; Timothy Eisen; Qiong Dong; Qing Zhang; Xiangjun Gu; Jayaram Vijayakrishnan; Kate Sullivan; Athena Matakidou; Yufei Wang; Gordon Mills; Kimberly Doheny; Ya-Yu Tsai; Wei Vivien Chen; Sanjay Shete; Margaret R Spitz; Richard S Houlston
Journal:  Nat Genet       Date:  2008-04-02       Impact factor: 38.330

4.  What's the best statistic for a simple test of genetic association in a case-control study?

Authors:  Chia-Ling Kuo; Eleanor Feingold
Journal:  Genet Epidemiol       Date:  2010-04       Impact factor: 2.135

5.  A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25.

Authors:  Rayjean J Hung; James D McKay; Valerie Gaborieau; Paolo Boffetta; Mia Hashibe; David Zaridze; Anush Mukeria; Neonilia Szeszenia-Dabrowska; Jolanta Lissowska; Peter Rudnai; Eleonora Fabianova; Dana Mates; Vladimir Bencko; Lenka Foretova; Vladimir Janout; Chu Chen; Gary Goodman; John K Field; Triantafillos Liloglou; George Xinarianos; Adrian Cassidy; John McLaughlin; Geoffrey Liu; Steven Narod; Hans E Krokan; Frank Skorpen; Maiken Bratt Elvestad; Kristian Hveem; Lars Vatten; Jakob Linseisen; Françoise Clavel-Chapelon; Paolo Vineis; H Bas Bueno-de-Mesquita; Eiliv Lund; Carmen Martinez; Sheila Bingham; Torgny Rasmuson; Pierre Hainaut; Elio Riboli; Wolfgang Ahrens; Simone Benhamou; Pagona Lagiou; Dimitrios Trichopoulos; Ivana Holcátová; Franco Merletti; Kristina Kjaerheim; Antonio Agudo; Gary Macfarlane; Renato Talamini; Lorenzo Simonato; Ray Lowry; David I Conway; Ariana Znaor; Claire Healy; Diana Zelenika; Anne Boland; Marc Delepine; Mario Foglio; Doris Lechner; Fumihiko Matsuda; Helene Blanche; Ivo Gut; Simon Heath; Mark Lathrop; Paul Brennan
Journal:  Nature       Date:  2008-04-03       Impact factor: 49.962

Review 6.  Genome-wide association studies provide new insights into type 2 diabetes aetiology.

Authors:  Timothy M Frayling
Journal:  Nat Rev Genet       Date:  2007-09       Impact factor: 53.242

7.  Informed conditioning on clinical covariates increases power in case-control association studies.

Authors:  Noah Zaitlen; Sara Lindström; Bogdan Pasaniuc; Marilyn Cornelis; Giulio Genovese; Samuela Pollack; Anne Barton; Heike Bickeböller; Donald W Bowden; Steve Eyre; Barry I Freedman; David J Friedman; John K Field; Leif Groop; Aage Haugen; Joachim Heinrich; Brian E Henderson; Pamela J Hicks; Lynne J Hocking; Laurence N Kolonel; Maria Teresa Landi; Carl D Langefeld; Loic Le Marchand; Michael Meister; Ann W Morgan; Olaide Y Raji; Angela Risch; Albert Rosenberger; David Scherf; Sophia Steer; Martin Walshaw; Kevin M Waters; Anthony G Wilson; Paul Wordsworth; Shanbeh Zienolddiny; Eric Tchetgen Tchetgen; Christopher Haiman; David J Hunter; Robert M Plenge; Jane Worthington; David C Christiani; Debra A Schaumberg; Daniel I Chasman; David Altshuler; Benjamin Voight; Peter Kraft; Nick Patterson; Alkes L Price
Journal:  PLoS Genet       Date:  2012-11-08       Impact factor: 5.917

8.  The NHGRI GWAS Catalog, a curated resource of SNP-trait associations.

Authors:  Danielle Welter; Jacqueline MacArthur; Joannella Morales; Tony Burdett; Peggy Hall; Heather Junkins; Alan Klemm; Paul Flicek; Teri Manolio; Lucia Hindorff; Helen Parkinson
Journal:  Nucleic Acids Res       Date:  2013-12-06       Impact factor: 16.971

9.  Designing genome-wide association studies: sample size, power, imputation, and the choice of genotyping chip.

Authors:  Chris C A Spencer; Zhan Su; Peter Donnelly; Jonathan Marchini
Journal:  PLoS Genet       Date:  2009-05-15       Impact factor: 5.917

10.  The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys.

Authors:  H E Bays; R H Chapman; S Grandy
Journal:  Int J Clin Pract       Date:  2007-05       Impact factor: 2.503

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