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- Greenwald, WW, et al.
(författare)
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Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2078-
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Tidskriftsartikel (refereegranskat)abstract
- Genetic variants affecting pancreatic islet enhancers are central to T2D risk, but the gene targets of islet enhancer activity are largely unknown. We generate a high-resolution map of islet chromatin loops using Hi-C assays in three islet samples and use loops to annotate target genes of islet enhancers defined using ATAC-seq and published ChIP-seq data. We identify candidate target genes for thousands of islet enhancers, and find that enhancer looping is correlated with islet-specific gene expression. We fine-map T2D risk variants affecting islet enhancers, and find that candidate target genes of these variants defined using chromatin looping and eQTL mapping are enriched in protein transport and secretion pathways. At IGF2BP2, a fine-mapped T2D variant reduces islet enhancer activity and IGF2BP2 expression, and conditional inactivation of IGF2BP2 in mouse islets impairs glucose-stimulated insulin secretion. Our findings provide a resource for studying islet enhancer function and identifying genes involved in T2D risk.
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- Wang, HY, et al.
(författare)
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Profiling plasma microRNA in nasopharyngeal carcinoma with deep sequencing
- 2014
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Ingår i: Clinical chemistry. - : Oxford University Press (OUP). - 1530-8561 .- 0009-9147. ; 60:5, s. 773-782
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUNDThe goal of this study was to establish a plasma microRNA profile by use of next-generation sequencing that could aid in assessment of patient prognosis in nasopharyngeal carcinoma (NPC).METHODSTwo panels of NPC patients and healthy controls (HCs) were recruited for this study. We used deep sequencing to screen plasma microRNAs. Differentially expressed microRNAs were verified by quantitative real-time PCR (qPCR). Kaplan–Meier survival analysis with the log-rank test was used to compare overall survival (OS) and progression-free survival (PFS) between groups.RESULTSTwenty-three plasma miRNAs with differential expression levels were selected for qPCR analysis on an independent set including 100 NPC patients and 55 HCs. NPC patients with low concentrations of miR-483–5p and miR-103 had better prognosis for 5-year OS than those with high concentrations (87.5% vs 55.8%, P < 0.001; 80.9% vs 62.3%, P = 0.031). Those with low concentrations of miR-29a and let-7c had poorer prognosis (54.8% vs 82.8%, P = 0.002; 56.3% vs 84.6%, P = 0.001). A 3-signature miRNA integrated with clinical stage was further identified in an independent set. We calculated a prognostic index score and classified patients into low-, medium-, and high-risk groups. Five-year OS among the 3 groups was significantly different (90.9%, 66.7%, and 23.8%; P < 0.001). By multivariate analysis, a high-risk score was the most significantly unfavorable prognostic factor independent of other clinical variables (P < 0.001, hazard ratio = 15.1, 95% CI = 5.2–43.9).CONCLUSIONSDifferentially expressed plasma miRNAs as identified by next-generation sequencing can be helpful for predicting survival in NPC patients.
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- Zhang, L, et al.
(författare)
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Using human genetics to understand the epidemiological association between obesity, serum urate, and gout
- 2023
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Ingår i: Rheumatology (Oxford, England). - : Oxford University Press (OUP). - 1462-0332 .- 1462-0324. ; 62:10, s. 3280-3290
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Tidskriftsartikel (refereegranskat)abstract
- ObjectivesWe aimed to clarify the genetic overlaps underlying obesity-related traits, serum urate, and gout.MethodsWe conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci, and causal relationships between obesity (the exposure variable), gout (the primary outcome) and serum urate (the secondary outcome). Summary statistics were collected from the hitherto largest genome-wide association studies conducted for BMI (N = 806 834), waist-to-hip ratio (WHR; N = 697 734), WHR adjusted for BMI (WHRadjBMI; N = 694 649), serum urate (N = 288 649), and gout (Ncases = 13 179 and Ncontrols = 750 634).ResultsPositive overall genetic correlations were observed for BMI (rg = 0.27, P = 6.62 × 10−7), WHR (rg = 0.22, P = 6.26 × 10−7) and WHRadjBMI (rg = 0.07, P = 6.08 × 10−3) with gout. Partitioning the whole genome into 1703 LD (linkage disequilibrium)-independent regions, a significant local signal at 4q22 was identified for BMI and gout. The global and local shared genetic basis was further strengthened by the multiple pleiotropic loci identified in the cross-phenotype association study, multiple shared gene–tissue pairs observed by Transcriptome-wide association studies, as well as causal relationships demonstrated by Mendelian randomization [BMI–gout: OR (odds ratio) = 1.66, 95% CI = 1.45, 1.88; WHR–gout: OR = 1.57, 95% CI = 1.37, 1.81]. Replacing the binary disease status of gout with its latent pathological measure, serum urate, a similar pattern of correlation, pleiotropy and causality was observed with even more pronounced magnitude and significance.ConclusionOur comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis and pleiotropic loci, as well as a causal relationship between obesity, serum urate, and gout, highlighting an intrinsic link underlying these complex traits.
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