Literature DB >> 17661717

Genome-wide association studies of cancer.

Eric Jorgenson1, John S Witte.   

Abstract

Genome-wide association studies provide a new and powerful approach to investigate the effect of inherited genetic variation on the risk of human disease. These studies rely on high throughput DNA microarray technology to genotype hundreds of thousands of genetic variants across the human genome. The first genome-wide association studies have identified previously unknown genetic risk factors that influence a range of diseases, including prostate cancer, breast cancer, myocardial infarction, age-related macular degeneration, diabetes, Crohn's disease and obesity. Many more studies are currently underway, including a number that will focus on other cancers (e.g., colorectal). Here we discuss the major issues involved in conducting genome-wide association studies and how these studies can be used to examine cancer phenotypes.

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Year:  2007        PMID: 17661717     DOI: 10.2217/14796694.3.4.419

Source DB:  PubMed          Journal:  Future Oncol        ISSN: 1479-6694            Impact factor:   3.404


  6 in total

1.  Genome-wide association studies and beyond.

Authors:  John S Witte
Journal:  Annu Rev Public Health       Date:  2010       Impact factor: 21.981

Review 2.  Molecular alterations in prostate cancer as diagnostic, prognostic, and therapeutic targets.

Authors:  Bora Gurel; Tsuyoshi Iwata; Cheryl M Koh; Srinivasan Yegnasubramanian; William G Nelson; Angelo M De Marzo
Journal:  Adv Anat Pathol       Date:  2008-11       Impact factor: 3.875

3.  Unraveling the genetic basis of asthma and allergic diseases.

Authors:  Jian-Feng Meng; Lanny J Rosenwasser
Journal:  Allergy Asthma Immunol Res       Date:  2010-06-11       Impact factor: 5.764

Review 4.  Prostate cancer genomics: towards a new understanding.

Authors:  John S Witte
Journal:  Nat Rev Genet       Date:  2008-12-23       Impact factor: 53.242

Review 5.  New tools for functional genomic analysis.

Authors:  Xin Chen; Eric Jorgenson; Siu Tim Cheung
Journal:  Drug Discov Today       Date:  2009-05-27       Impact factor: 7.851

6.  Genome-wide association analysis identifies genetic variations in subjects with myalgic encephalomyelitis/chronic fatigue syndrome.

Authors:  K A Schlauch; S F Khaiboullina; K L De Meirleir; S Rawat; J Petereit; A A Rizvanov; N Blatt; T Mijatovic; D Kulick; A Palotás; V C Lombardi
Journal:  Transl Psychiatry       Date:  2016-02-09       Impact factor: 6.222

  6 in total

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