These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Toxicogenetics of antiretroviral therapy: genetic factors that contribute to metabolic complications. Author: Tarr PE, Telenti A. Journal: Antivir Ther; 2007; 12(7):999-1013. PubMed ID: 18018758. Abstract: Metabolic complications of antiretroviral therapy (ART) have emerged as a major concern for long-term, successful management of HIV infection. Variability in the response to ART between individuals has been increasingly linked to the genetic background of patients, as regards efficacy and susceptibility to adverse reactions (toxicogenetics). This review summarizes the biological and methodological background for the genetic prediction of metabolic toxicity of ART. Recent studies are discussed which suggest that single-nucleotide polymorphisms (SNPs) in several genes involved in lipid metabolism and lipid transport in the general population (ABCA1, APOA5, APOC3, APOE, CETP) might modulate plasma triglyceride and high-density lipoprotein cholesterol levels in HIV-infected patients. At present, genetic prediction of lipodystrophy is not possible. Lipodystrophy has been linked to an accumulation of mtDNA mutations, a finding causally associated with ageing phenotypes in animal models. No mutations in LMNA, a gene linked to rare, inherited forms of lipodystrophy, have been identified in small studies of patients with lipodystrophy, and a possible link to a TNF promoter SNP remains to be confirmed. With the rapidly decreasing cost of genetic testing, the main issues that need to be addressed prior to introduction of toxicogenetic prediction in HIV clinical practice include reproducibly high predictive values of SNP associations with clinically relevant and well defined metabolic outcomes, studies that evaluate the contribution of SNPs in the context of multi-SNP and haplotype analysis, and the validation of genetic markers in independent, large patient cohorts. Comprehensive, whole genome approaches are increasingly being used.[Abstract] [Full Text] [Related] [New Search]