Genomewide Association Studies and Human Disease

Institute of Neurology, University College London, London, United Kingdom. at
New England Journal of Medicine (Impact Factor: 55.87). 05/2009; 360(17):1759-68. DOI: 10.1056/NEJMra0808700
Source: PubMed

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    • "Genetic investigation of individuals who have had a stroke is a promising approach for identification of novel biological mechanisms that underlie the development of cerebrovascular disease. Thanks to modern advances in the field of stroke genetics, many cases of cryptogenic stroke have been clarified; the discovery of new pathogenetic pathways might lead in the future to the development of preventive strategies and acute treatments [14] [15]. "
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    ABSTRACT: Background: Stroke may be a clinical expression of several inherited disorders in humans. Recognition of the underlined genetic disorders causing stroke is important for a correct diagnosis, for genetic counselling and, even if rarely, for a correct therapeutic management. Moreover, the genetics of complex diseases such the stroke, in which multiple genes interact with environmental risk factors to increase risk, has been revolutionized by the Genome-Wide Association Study (GWAS) approach. Scope of review: Here we review the single-gene causes of ischemic stroke, bringing the reader from the candidate gene method toward the exciting new horizons of genetic technology. Major conclusions: The aetiological diagnosis of ischemic stroke in young adults is more complex than in the elderly. The identification of a genetic cause is important to provide appropriate counseling and to start a correct therapy, when available. The advent of GWAS technology, such as for other complex pathological conditions, has contributed enormously to the understanding of many of these genetic bases. For success large, well phenotyped case cohorts are required, and international collaborations are essential. General significance: This review focuses on the main causes of genetically-based ischemic stroke in young adults, often classified as indeterminate, investigating also the recent findings of the GWAS, in order to improve diagnostic and therapeutic management.
    Biochimica et Biophysica Acta - Clinical 12/2014; 349. DOI:10.1016/j.bbacli.2014.12.004
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    • "However, existing main-effect-centered methodologies and techniques that depend on fundamental assumptions about a simple genetic architecture can only find very limited individual associations with disease risks. Genome-wide association studies (GWAS) [18] [19] [39] and the next generation sequencing [33] make millions single nucleotide polymorphisms (SNPs) in human genome available for testing associations with phenotypic traits. These developments call for new methodologies that embrace the complex genetic architecture of diseases [10] [25]. "
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    ABSTRACT: We analyzed two West African samples (Guinea-Bissau: n=289 cases and 322 controls; The Gambia: n=240 cases and 248 controls) to evaluate single-nucleotide polymorphisms (SNPs) in Epiregulin (EREG) and V-ATPase (T-cell immune regulator 1 (TCIRG1)) using single and multilocus analyses to determine whether previously described associations with pulmonary tuberculosis (PTB) in Vietnamese and Italians would replicate in African populations. We did not detect any significant single locus or haplotype associations in either sample. We also performed exploratory pairwise interaction analyses using Visualization of Statistical Epistasis Networks (ViSEN), a novel method to detect only interactions among multiple variables, to elucidate possible interaction effects between SNPs and demographic factors. Although we found no strong evidence of marginal effects, there were several significant pairwise interactions that were identified in either the Guinea-Bissau or the Gambian samples, two of which replicated across populations. Our results indicate that the effects of EREG and TCIRG1 variants on PTB susceptibility, to the extent that they exist, are dependent on gene-gene interactions in West African populations as detected with ViSEN. In addition, epistatic effects are likely to be influenced by inter- and intra-population differences in genetic or environmental context and/or the mycobacterial lineages causing disease.Genes and Immunity advance online publication, 5 June 2014; doi:10.1038/gene.2014.28.
    Genes and Immunity 06/2014; 15(6). DOI:10.1038/gene.2014.28 · 2.91 Impact Factor
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    • "These data and those of others (Waterland et al. 2010; Dominguez-Salas et al. 2013) are examples for genetic association and metabolomics studies: using metabolite levels without knowledge of usual dietary intakes may result in misclassification of individuals, thereby affecting association analysis. Lack of dietary intake data (and the genetic heterogeneity added in large sample sizes) may be among many reasons for the ''missing heritability'' (Hardy and Singleton 2009; Manolio et al. 2009; Hebebrand et al. 2010; Ober and Vercelli 2011) in genetic association studies. The interpretation of the differences in metabolite levels was made possible by assessing nutrient intakes, in this case by using 24-h dietary recalls. "
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    ABSTRACT: Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6-14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.
    Genes & Nutrition 05/2014; 9(3):403. DOI:10.1007/s12263-014-0403-9 · 2.79 Impact Factor
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