Literature DB >> 21909187

Statistical Analysis in Genetic Studies of Mental Illnesses.

Heping Zhang1.   

Abstract

Identifying the risk factors for mental illnesses is of significant public health importance. Diagnosis, stigma associated with mental illnesses, comorbidity, and complex etiologies, among others, make it very challenging to study mental disorders. Genetic studies of mental illnesses date back at least a century ago, beginning with descriptive studies based on Mendelian laws of inheritance. A variety of study designs including twin studies, family studies, linkage analysis, and more recently, genomewide association studies have been employed to study the genetics of mental illnesses, or complex diseases in general. In this paper, I will present the challenges and methods from a statistical perspective and focus on genetic association studies.

Entities:  

Year:  2011        PMID: 21909187      PMCID: PMC3169093          DOI: 10.1214/11-STS353

Source DB:  PubMed          Journal:  Stat Sci        ISSN: 0883-4237            Impact factor:   2.901


  69 in total

1.  Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions.

Authors:  K L Lunetta; S V Faraone; J Biederman; N M Laird
Journal:  Am J Hum Genet       Date:  2000-02       Impact factor: 11.025

2.  A genome-wide association study identifies IL23R as an inflammatory bowel disease gene.

Authors:  Richard H Duerr; Kent D Taylor; Steven R Brant; John D Rioux; Mark S Silverberg; Mark J Daly; A Hillary Steinhart; Clara Abraham; Miguel Regueiro; Anne Griffiths; Themistocles Dassopoulos; Alain Bitton; Huiying Yang; Stephan Targan; Lisa Wu Datta; Emily O Kistner; L Philip Schumm; Annette T Lee; Peter K Gregersen; M Michael Barmada; Jerome I Rotter; Dan L Nicolae; Judy H Cho
Journal:  Science       Date:  2006-10-26       Impact factor: 47.728

3.  Family-based association tests for ordinal traits adjusting for covariates.

Authors:  Xueqin Wang; Yuanqing Ye; Heping Zhang
Journal:  Genet Epidemiol       Date:  2006-12       Impact factor: 2.135

4.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits.

Authors:  Lucia A Hindorff; Praveen Sethupathy; Heather A Junkins; Erin M Ramos; Jayashri P Mehta; Francis S Collins; Teri A Manolio
Journal:  Proc Natl Acad Sci U S A       Date:  2009-05-27       Impact factor: 11.205

5.  Lack of association between SLITRK1var321 and Tourette syndrome in a large family-based sample.

Authors:  J M Scharf; P Moorjani; J Fagerness; J V Platko; C Illmann; B Galloway; E Jenike; S E Stewart; D L Pauls
Journal:  Neurology       Date:  2008-04-15       Impact factor: 9.910

6.  Parametric and nonparametric linkage analysis: a unified multipoint approach.

Authors:  L Kruglyak; M J Daly; M P Reeve-Daly; E S Lander
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

7.  Estimation of the recombination fraction in human pedigrees: efficient computation of the likelihood for human linkage studies.

Authors:  J Ott
Journal:  Am J Hum Genet       Date:  1974-09       Impact factor: 11.025

8.  A general model for the genetic analysis of pedigree data.

Authors:  R C Elston; J Stewart
Journal:  Hum Hered       Date:  1971       Impact factor: 0.444

9.  A discordant-sibship test for disequilibrium and linkage: no need for parental data.

Authors:  S Horvath; N M Laird
Journal:  Am J Hum Genet       Date:  1998-12       Impact factor: 11.025

10.  A genome-wide linkage and association study using COGA data.

Authors:  Xiaofeng Zhu; Richard Cooper; Donghui Kan; Guichan Cao; Xiaodong Wu
Journal:  BMC Genet       Date:  2005-12-30       Impact factor: 2.797

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  5 in total

1.  FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data.

Authors:  Meiyan Huang; Thomas Nichols; Chao Huang; Yang Yu; Zhaohua Lu; Rebecca C Knickmeyer; Qianjin Feng; Hongtu Zhu
Journal:  Neuroimage       Date:  2015-05-27       Impact factor: 6.556

Review 2.  Gene × Environment Determinants of Stress- and Anxiety-Related Disorders.

Authors:  Sumeet Sharma; Abigail Powers; Bekh Bradley; Kerry J Ressler
Journal:  Annu Rev Psychol       Date:  2015-10-06       Impact factor: 24.137

3.  Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing.

Authors:  Jiwei Zhao; Heping Zhang
Journal:  Stat Interface       Date:  2016       Impact factor: 0.582

4.  Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence.

Authors:  Heping Zhang; Dungang Liu; Jiwei Zhao; Xuan Bi
Journal:  Ann Appl Stat       Date:  2018-11-13       Impact factor: 2.083

5.  Residuals and Diagnostics for Ordinal Regression Models: A Surrogate Approach.

Authors:  Dungang Liu; Heping Zhang
Journal:  J Am Stat Assoc       Date:  2018-06-06       Impact factor: 5.033

  5 in total

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