scholarly journals Emerging roles of GLIS3 in neonatal diabetes, type 1 and type 2 diabetes

2017 ◽  
Vol 58 (2) ◽  
pp. R73-R85 ◽  
Author(s):  
Xianjie Wen ◽  
Yisheng Yang
Keyword(s):  
Type 2 Diabetes ◽  
Zinc Finger Protein ◽  
Association Studies ◽  
Protein A ◽  
Neonatal Diabetes ◽  
Genome Wide Association Studies ◽  
Β Cell ◽  
Ductal Cells

GLI-similar 3 (GLIS3), a member of the Krüppel-like zinc finger protein subfamily, is predominantly expressed in the pancreas, thyroid and kidney. Glis3 mRNA can be initially detected in mouse pancreas at embryonic day 11.5 and is largely restricted to β cells, pancreatic polypeptide-expressing cells, as well as ductal cells at later stage of pancreas development. Mutations in GLIS3 cause a neonatal diabetes syndrome, characterized by neonatal diabetes, congenital hypothyroidism and polycystic kidney. Importantly, genome-wide association studies showed that variations of GLIS3 are strongly associated with both type 1 diabetes (T1D) and type 2 diabetes (T2D) in multiple populations. GLIS3 cooperates with pancreatic and duodenal homeobox 1 (PDX1), v-maf musculoaponeurotic fibrosarcoma oncogene family, protein A (MAFA), as well as neurogenic differentiation 1 (NEUROD1) and potently controls insulin gene transcription. GLIS3 also plays a role in β cell survival and likely in insulin secretion. Any perturbation of these functions may underlie all three forms of diabetes. GLIS3, synergistically with hepatocyte nuclear factor 6 (HNF6) and forkhead box A2 (FOXA2), controls fetal islet differentiation via transactivating neurogenin 3 (NGN3) and impairment of this function leads to neonatal diabetes. In addition, GLIS3 is also required for the compensatory β cell proliferation and mass expansion in response to insulin resistance, which if disrupted may predispose to T2D. The increasing understanding of the mechanisms of GLIS3 in β cell development, survival and function maintenance will provide new insights into disease pathogenesis and potential therapeutic target identification to combat diabetes.

scholarly journals RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

2021 ◽  
Author(s):  
John T Walker ◽  
Diane C Saunders ◽  
Vivek Rai ◽  
Chunhua Dai ◽  
Peter Orchard ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Secretion ◽  
Association Studies ◽  
Critical Role ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Β Cells ◽  
Β Cell ◽  
Gene Regulatory

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet β cells. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping β cell regulatory elements, but translating these into biological mechanisms has been challenging. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D β cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected β cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in β cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the β cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

scholarly journals Associations among circulating sphingolipids, β-cell function, and risk of developing type 2 diabetes: A population-based cohort study in China

PLoS Medicine ◽  
2020 ◽  
Vol 17 (12) ◽  
pp. e1003451
Author(s):  
Huan Yun ◽  
Liang Sun ◽  
Qingqing Wu ◽  
Geng Zong ◽  
Qibin Qi ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cell Function ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Β Cell ◽  
Nutrition Survey ◽  
Cell Dysfunction ◽  
Independent Population

Background Animal studies suggest vital roles of sphingolipids, especially ceramides, in the pathogenesis of type 2 diabetes (T2D) via pathways involved in insulin resistance, β-cell dysfunction, and inflammation, but human studies are limited. We aimed to evaluate the associations of circulating sphingolipids with incident T2D and to explore underlying mechanisms. Methods and findings The current study included 826 men and 1,148 women who were aged 50–70 years, from Beijing and Shanghai, and without T2D in 2005 and who were resurveyed in 2011. Cardiometabolic traits were measured at baseline and follow-up surveys. A total of 76 sphingolipids were quantified using high-coverage targeted lipidomics. Summary data for 2-sample Mendelian randomization were obtained from genome-wide association studies of circulating sphingolipids and the China Health and Nutrition Survey (n = 5,731). During the 6-year period, 529 participants developed T2D. Eleven novel and 3 reported sphingolipids, namely ceramides (d18:1/18:1, d18:1/20:0, d18:1/20:1, d18:1/22:1), saturated sphingomyelins (C34:0, C36:0, C38:0, C40:0), unsaturated sphingomyelins (C34:1, C36:1, C42:3), hydroxyl-sphingomyelins (C34:1, C38:3), and a hexosylceramide (d18:1/20:1), were positively associated with incident T2D (relative risks [RRs]: 1.14–1.21; all P < 0.001), after multivariate adjustment including lifestyle characteristics and BMI. Network analysis further identified 5 modules, and 2 modules containing saturated sphingomyelins showed the strongest associations with increased T2D risk (RRQ4 versus Q1 = 1.59 and 1.43; both Ptrend < 0.001). Mediation analysis suggested that the detrimental associations of 13 sphingolipids with T2D were largely mediated through β-cell dysfunction, as indicated by HOMA-B (mediation proportion: 11.19%–42.42%; all P < 0.001). Moreover, Mendelian randomization evidenced a positive association between a genetically instrumented ceramide (d18:1/20:1) and T2D (odds ratio: 1.15 [95% CI 1.05–1.26]; P = 0.002). Main limitations in the current study included potential undiagnosed cases and lack of an independent population for replication. Conclusions In this study, we observed that a panel of novel sphingolipids with unique structures were positively associated with incident T2D, largely mediated through β-cell dysfunction, in Chinese individuals.

Genome-Wide Association Studies Identify Two Novel Loci Conferring Susceptibility to Diabetic Retinopathy in Japanese Patients with Type 2 Diabetes

2021 ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Masatoshi Matsunami ◽  
Momoko Horikoshi ◽  
Minoru Iwata ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Association Studies ◽  
Meta Analysis ◽  
Japanese Patients ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Stage 1

Abstract Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases, and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (p &lt; 1.0 × 10−4) in an independent case–control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stage-1 and -2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, p = 1.62 × 10−9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11–1.23, and rs140508424 within PALM2 on chromosome 9, p = 4.19 × 10−8, OR = 1.61, 95% CI 1.36–1.91. However, the association of these two loci were not replicated in Korean, European, or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (p = 2.17 × 10−6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

scholarly journals Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Shiu Lun Au Yeung ◽  
Jie V Zhao ◽  
C Mary Schooling
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Predisposition ◽  
Mendelian Randomization ◽  
Fasting Glucose ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Wide Confidence Interval

Abstract Background Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases). Method We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method. Results We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval. Conclusion We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.

scholarly journals Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Toshimasa Yamauchi ◽  
Kazuo Hara ◽  
Kazuki Yasuda ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Japanese Population ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes

Genes ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 374 ◽  
Author(s):  
Anna Dziewulska ◽  
Aneta Dobosz ◽  
Agnieszka Dobrzyn
Keyword(s):  
Type 2 Diabetes ◽  
Pancreatic Islets ◽  
High Throughput ◽  
Target Genes ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genomic Landscape ◽  
A Genome ◽  
Next Generation Sequencing Ngs

Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.

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