Literature DB >> 16194763

Genetic association studies in mood disorders: issues and promise.

Sevilla D Detera-Wadleigh1, Francis J McMahon.   

Abstract

Genetic association is a powerful method for identifying genetic variants that contribute to the molecular basis of complex diseases. There is now a wealth of informative, validated and densely-spaced single nucleotide polymorphism (SNP) markers for use in association studies, and the delineation of the genome-wide haplotype architecture will greatly enhance our ability to conduct whole genome association screens, fine mapping of linkage regions, and systematic screening of functional candidate genes. Single nucleotide polymorphism-based genotyping technology has progressed dramatically to the point of high-throughput methods that can assay up to thousands of SNPs on many samples in one experiment. Genotyping cost remains a limiting factor in complex disease studies, where numerous SNPs and large sample sets are needed to maximize statistical power. Strategies designed to reduce cost include DNA pooling and analysis with tagSNPs. As larger clinical samples become available, it will be increasingly important to test for hidden stratification in case-control studies, as well as transmission distortion in family-based studies, either of which can lead to spurious association findings. As yet, there is no widely-accepted genetic association finding in mood disorders, but functional candidate genes, such as the serotonin transporter, and positional candidates, such as G72/G30 on chromosome 13q, are beginning to be identified in several studies. Relating associated variants to the phenotype represents the next critical step toward establishing the pathogenic role of gene variants in mood disorders.

Entities:  

Mesh:

Year:  2004        PMID: 16194763     DOI: 10.1080/09540260400014377

Source DB:  PubMed          Journal:  Int Rev Psychiatry        ISSN: 0954-0261


  5 in total

1.  A high-density single nucleotide polymorphism map for Neurospora crassa.

Authors:  Randy Lambreghts; Mi Shi; William J Belden; David Decaprio; Danny Park; Matthew R Henn; James E Galagan; Meray Bastürkmen; Bruce W Birren; Matthew S Sachs; Jay C Dunlap; Jennifer J Loros
Journal:  Genetics       Date:  2008-11-17       Impact factor: 4.562

Review 2.  Genetic research into bipolar disorder: the need for a research framework that integrates sophisticated molecular biology and clinically informed phenotype characterization.

Authors:  Thomas G Schulze
Journal:  Psychiatr Clin North Am       Date:  2010-03

3.  Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine.

Authors:  Huijie Zhang; Xianglu Li; Jianyue Pang; Xiaofeng Zhao; Suxia Cao; Xinyou Wang; Xingbang Wang; Hengfen Li
Journal:  Front Psychiatry       Date:  2020-06-03       Impact factor: 4.157

Review 4.  Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression.

Authors:  Wayne C Drevets; Joseph L Price; Maura L Furey
Journal:  Brain Struct Funct       Date:  2008-08-13       Impact factor: 3.270

5.  A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder.

Authors:  A E Baum; N Akula; M Cabanero; I Cardona; W Corona; B Klemens; T G Schulze; S Cichon; M Rietschel; M M Nöthen; A Georgi; J Schumacher; M Schwarz; R Abou Jamra; S Höfels; P Propping; J Satagopan; S D Detera-Wadleigh; J Hardy; F J McMahon
Journal:  Mol Psychiatry       Date:  2007-05-08       Impact factor: 15.992

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.