Literature DB >> 15829249

Approaches to determine clinical significance of genetic variants.

Alasdair MacAuley1, Warren C Ladiges.   

Abstract

The clinical significance of genetic variants (single nucleotide polymorphisms, SNPs) has implications for risk assessment and also for predicting the outcome of a disease process, especially in response to intervention. Approaches to determine the clinical significance of genetic polymorphisms are now beginning to be developed. The technology tools and procedures currently available have significant potential in identifying and validating polymorphisms associated with environmentally sensitive phenotypes. Numerous concepts can now provide the methodology to selectively identify SNPs with the potential for impacting gene function. These include computational algorithms, biochemical assays, yeast mutagenicity assays, and epidemiological studies, either as a stand-alone screen, or in various combinations depending on the gene of interest. Proof of principle will ultimately depend on large-scale epidemiological and clinical studies, but will require intensive resources. Therefore, the use of the mouse as a preclinical biological model is paramount in helping screen valid SNPs or combinations of SNPs for human studies. But more importantly, mouse modeling will help answer the question of what role gene variants play in sensitivity or resistance to a wide variety of environmental insults ranging from toxic chemicals and carcinogens to more mundane and routine exposure items, such as dietary factors, air quality, over the counter and prescription medications, and ultraviolet light. Our focus on SNPs that result in an amino acid change is a matter of expediency because these variants are more amenable to the prescreening approaches currently available that are expected to help identify SNPs that affect protein function. The mouse models generated to evaluate the environmental relevance of selected SNPs will be extremely valuable biological tools to validate gene variant and environment interaction in a variety of settings. Informative mouse models will also provide the basis of pursuing relevant SNPs in epidemiological and clinical investigations.

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Year:  2005        PMID: 15829249     DOI: 10.1016/j.mrfmmm.2005.01.009

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  2 in total

1.  Tumor growth is suppressed in mice expressing a truncated XRCC1 protein.

Authors:  Christina Pettan-Brewer; John Morton; Sarah Cullen; Linda Enns; Keffy Rm Kehrli; Julia Sidorova; Jorming Goh; Rebecca Coil; Warren C Ladiges
Journal:  Am J Cancer Res       Date:  2012-02-15       Impact factor: 6.166

2.  Allelic spectrum of the natural variation in CRP.

Authors:  Dana C Crawford; Qian Yi; Joshua D Smith; Cynthia Shephard; Michelle Wong; Laura Witrak; Robert J Livingston; Mark J Rieder; Deborah A Nickerson
Journal:  Hum Genet       Date:  2006-03-21       Impact factor: 4.132

  2 in total

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