62 research outputs found

    Impact of FTO genotypes on BMI and weight in polycystic ovary syndrome : a systematic review and meta-analysis

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    Aims/hypothesis FTO gene single nucleotide polymorphisms (SNPs) have been shown to be associated with obesity-related traits and type 2 diabetes. Several small studies have suggested a greater than expected effect of the FTO rs9939609 SNP on weight in polycystic ovary syndrome (PCOS). We therefore aimed to examine the impact of FTO genotype on BMI and weight in PCOS. Methods A systematic search of medical databases (PubMed, EMBASE and Cochrane CENTRAL) was conducted up to the end of April 2011. Seven studies describing eight distinct PCOS cohorts were retrieved; seven were genotyped for SNP rs9939609 and one for SNP rs1421085. The per allele effect on BMI and body weight increase was calculated and subjected to meta-analysis. Results A total of 2,548 women with PCOS were included in the study; 762 were TT homozygotes, 1,253 had an AT/CT genotype, and 533 were AA/CC homozygotes. Each additional copy of the effect allele (A/C) increased the BMI by a mean of 0.19 z score units (95% CI 0.13, 0.24; p = 2.26 × 10−11) and body weight by a mean of 0.20 z score units (95% CI 0.14, 0.26; p = 1.02 × 10−10). This translated into an approximately 3.3 kg/m2 increase in BMI and an approximately 9.6 kg gain in body weight between TT and AA/CC homozygotes. The association between FTO genotypes and BMI was stronger in the cohorts with PCOS than in the general female populations from large genome-wide association studies. Deviation from an additive genetic model was observed in heavier populations. Conclusions/interpretation The effect of FTO SNPs on obesity-related traits in PCOS seems to be more than two times greater than the effect found in large population-based studies. This suggests an interaction between FTO and the metabolic context or polygenic background of PCOS

    The CTGF -945GC polymorphism is not associated with plasma CTGF and does not predict nephropathy or outcome in type 1 diabetes

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    The -945GC polymorphism (rs6918698) in the connective tissue growth factor gene promoter (CTGF/CCN-2) has been associated with end organ damage in systemic sclerosis. Because CTGF is important in progression of diabetic kidney disease, we investigated whether the -945GC polymorphism is associated with plasma CTGF level and outcome in type 1 diabetes

    Detection of Molecular Paths Associated with Insulitis and Type 1 Diabetes in Non-Obese Diabetic Mouse

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    Recent clinical evidence suggests important role of lipid and amino acid metabolism in early pre-autoimmune stages of type 1 diabetes pathogenesis. We study the molecular paths associated with the incidence of insulitis and type 1 diabetes in the Non-Obese Diabetic (NOD) mouse model using available gene expression data from the pancreatic tissue from young pre-diabetic mice. We apply a graph-theoretic approach by using a modified color coding algorithm to detect optimal molecular paths associated with specific phenotypes in an integrated biological network encompassing heterogeneous interaction data types. In agreement with our recent clinical findings, we identified a path downregulated in early insulitis involving dihydroxyacetone phosphate acyltransferase (DHAPAT), a key regulator of ether phospholipid synthesis. The pathway involving serine/threonine-protein phosphatase (PP2A), an upstream regulator of lipid metabolism and insulin secretion, was found upregulated in early insulitis. Our findings provide further evidence for an important role of lipid metabolism in early stages of type 1 diabetes pathogenesis, as well as suggest that such dysregulation of lipids and related increased oxidative stress can be tracked to beta cells

    A Robust Statistical Method for Association-Based eQTL Analysis

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    Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions: The analyses show that the new method confers an improved statistical power for detecting genuin

    Clinical application of genetic testing for posterior uveal melanoma

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    Uveal melanoma is the most common primary intraocular tumor in adults, and it has a strong potential to metastasize. Traditionally, clinicopathological features of these tumors were used to provide a limited prediction of the metastatic risk. However, early genetic studies using karyotype analysis, fluorescence in situ hybridization, and comparative genetic hybridization of posterior uveal melanoma samples identified multiple chromosomal abnormalities associated with a higher risk of fatal metastasis. This correlation between specific genetic abnormalities in uveal melanoma and a patient’s risk for development of metastasis has recently been widely studied, and the development of new prognostic tests has allowed clinicians to predict this metastatic risk with increased accuracy. Such novel tests include gene expression profiling, which analyzes the RNA expression patterns of tumor cells, and multiplex ligation-dependent probe amplification, which detects deletions or and amplifications of DNA in tumor cells. This review discusses the current status of prognostic testing techniques available to clinicians and patients for posterior uveal melanomas

    Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus

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    <p>Abstract</p> <p>Background</p> <p>Hyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci.</p> <p>Methods</p> <p>Both Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]).</p> <p>Results</p> <p>Different patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations.</p> <p>Conclusion</p> <p>Combining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.</p

    Evidence for Hitchhiking of Deleterious Mutations within the Human Genome

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    Deleterious mutations present a significant obstacle to adaptive evolution. Deleterious mutations can inhibit the spread of linked adaptive mutations through a population; conversely, adaptive substitutions can increase the frequency of linked deleterious mutations and even result in their fixation. To assess the impact of adaptive mutations on linked deleterious mutations, we examined the distribution of deleterious and neutral amino acid polymorphism in the human genome. Within genomic regions that show evidence of recent hitchhiking, we find fewer neutral but a similar number of deleterious SNPs compared to other genomic regions. The higher ratio of deleterious to neutral SNPs is consistent with simulated hitchhiking events and implies that positive selection eliminates some deleterious alleles and increases the frequency of others. The distribution of disease-associated alleles is also altered in hitchhiking regions. Disease alleles within hitchhiking regions have been associated with auto-immune disorders, metabolic diseases, cancers, and mental disorders. Our results suggest that positive selection has had a significant impact on deleterious polymorphism and may be partly responsible for the high frequency of certain human disease alleles

    Polycystic ovary syndrome

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    The document attached has been archived with permission from the editor of the Medical Journal of Australia. An external link to the publisher’s copy is included.Polycystic ovary syndrome (PCOS) affects 5-20% of women of reproductive age worldwide. The condition is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology (PCOM) - with excessive androgen production by the ovaries being a key feature of PCOS. Metabolic dysfunction characterized by insulin resistance and compensatory hyperinsulinaemia is evident in the vast majority of affected individuals. PCOS increases the risk for type 2 diabetes mellitus, gestational diabetes and other pregnancy-related complications, venous thromboembolism, cerebrovascular and cardiovascular events and endometrial cancer. PCOS is a diagnosis of exclusion, based primarily on the presence of hyperandrogenism, ovulatory dysfunction and PCOM. Treatment should be tailored to the complaints and needs of the patient and involves targeting metabolic abnormalities through lifestyle changes, medication and potentially surgery for the prevention and management of excess weight, androgen suppression and/or blockade, endometrial protection, reproductive therapy and the detection and treatment of psychological features. This Primer summarizes the current state of knowledge regarding the epidemiology, mechanisms and pathophysiology, diagnosis, screening and prevention, management and future investigational directions of the disorder.Robert J Norman, Ruijin Wu and Marcin T Stankiewic
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