6 research outputs found

    A genome-wide association search for type 2 diabetes genes in African Americans.

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    African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations

    Oral mucosal injury caused by mammalian target of rapamycin inhibitors: emerging perspectives on pathobiology and impact on clinical practice

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    In recent years oral mucosal injury has been increasingly recognized as an important toxicity associated with mammalian target of rapamycin (mTOR) inhibitors, including in patients with breast cancer who are receiving everolimus. This review addresses the state‐of‐the‐science regarding mTOR inhibitor‐associated stomatitis (mIAS), and delineates its clinical characteristics and management. Given the clinically impactful pain associated with mIAS, this review also specifically highlights new research focusing on the study of the molecular basis of pain. The incidence of mIAS varies widely (2–78%). As reported across multiple mTOR inhibitor clinical trials, grade 3/4 toxicity occurs in up to 9% of patients. Managing mTOR‐associated oral lesions with topical oral, intralesional, and/or systemic steroids can be beneficial, in contrast to the lack of evidence supporting steroid treatment of oral mucositis caused by high‐dose chemotherapy or radiation. However, steroid management is not uniformly efficacious in all patients receiving mTOR inhibitors. Furthermore, technology does not presently exist to permit clinicians to predict a priori which of their patients will develop these lesions. There thus remains a strategic need to define the pathobiology of mIAS, the molecular basis of pain, and risk prediction relative to development of the clinical lesion. This knowledge could lead to novel future interventions designed to more effectively prevent mIAS and improve pain management if clinically significant mIAS lesions develop

    The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

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    Abstract Aims/hypothesis The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. Methods We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. Results Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p =3.4 × 10 −9 ). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. Conclusions/interpretation Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. Data availability Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ ,accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org ,publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445). Graphical abstractinfo:eu-repo/semantics/publishe
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