Browsing by Subject "Genetics of disease"

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    Genetic susceptibility to acute rheumatic fever: a systematic review and meta-analysis of twin studies
    (Public Library of Science, 2011) Engel, Mark E; Stander, Raphaella; Vogel, Jonathan; Adeyemo, Adebowale A; Mayosi, Bongani M
    BACKGROUND: Acute rheumatic fever is considered to be a heritable condition, but the magnitude of the genetic effect is unknown. The objective of this study was to conduct a systematic review and meta-analysis of twin studies of concordance of acute rheumatic fever in order to derive quantitative estimates of the size of the genetic effect. METHODS: We searched PubMed/MEDLINE, ISI Web of Science, EMBASE, and Google Scholar from their inception to 31 January 2011, and bibliographies of retrieved articles, for twin studies of the concordance for acute rheumatic fever or rheumatic heart disease in monozygotic versus dizygotic twins that used accepted diagnostic criteria for acute rheumatic fever and zygosity without age, gender or language restrictions. Twin similarity was measured by probandwise concordance rate and odds ratio (OR), and aggregate probandwise concordance risk was calculated by combining raw data from each study. ORs from separate studies were combined by random-effects meta-analysis to evaluate association between zygosity status and concordance. Heritability was estimated by fitting a variance components model to the data. RESULTS: 435 twin pairs from six independent studies met the inclusion criteria. The pooled probandwise concordance risk for acute rheumatic fever was 44% in monozygotic twins and 12% in dizygotic twins, and the association between zygosity and concordance was strong (OR 6.39; 95% confidence interval, 3.39 to 12.06; P<0.001), with no significant study heterogeneity (P = 0.768). The estimated heritability across all the studies was 60%. CONCLUSIONS: Acute rheumatic fever is an autoimmune disorder with a high heritability. The discovery of all genetic susceptibility loci through whole genome scanning may provide a clinically useful genetic risk prediction tool for acute rheumatic fever and its sequel, rheumatic heart disease.
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    Genetic variation in TLR genes in Ugandan and South African populations and comparison with HapMap data
    (Public Library of Science, 2012) Baker, Allison R; Qiu, Feiyou; Randhawa, April Kaur; Horne, David J; Adams, Mark D; Shey, Muki; Barnholtz-Sloan, Jill; Mayanja-Kizza, Harriet; Kaplan, Gilla; Hanekom, Willem A; Boom, W Henry; Hawn, Thomas R; Stein, Catherine M
    Genetic epidemiological studies of complex diseases often rely on data from the International HapMap Consortium for identification of single nucleotide polymorphisms (SNPs), particularly those that tag haplotypes. However, little is known about the relevance of the African populations used to collect HapMap data for study populations conducted elsewhere in Africa. Toll-like receptor (TLR) genes play a key role in susceptibility to various infectious diseases, including tuberculosis. We conducted full-exon sequencing in samples obtained from Uganda (n = 48) and South Africa (n = 48), in four genes in the TLR pathway: TLR2, TLR4, TLR6, and TIRAP. We identified one novel TIRAP SNP (with minor allele frequency [MAF] 3.2%) and a novel TLR6 SNP (MAF 8%) in the Ugandan population, and a TLR6 SNP that is unique to the South African population (MAF 14%). These SNPs were also not present in the 1000 Genomes data. Genotype and haplotype frequencies and linkage disequilibrium patterns in Uganda and South Africa were similar to African populations in the HapMap datasets. Multidimensional scaling analysis of polymorphisms in all four genes suggested broad overlap of all of the examined African populations. Based on these data, we propose that there is enough similarity among African populations represented in the HapMap database to justify initial SNP selection for genetic epidemiological studies in Uganda and South Africa. We also discovered three novel polymorphisms that appear to be population-specific and would only be detected by sequencing efforts.