76 research outputs found
Contribution of type 2 diabetes associated loci in the Arabic population from Tunisia: a case-control study
<p>Abstract</p> <p>Background</p> <p>Candidate gene and genome-wide association studies have both reproducibly identified several common Single Nucleotide Polymorphisms (SNPs) that confer type 2 diabetes (T2D) risk in European populations. Our aim was to evaluate the contribution to T2D of five of these established T2D-associated loci in the Arabic population from Tunisia.</p> <p>Methods</p> <p>A case-control design comprising 884 type 2 diabetic patients and 513 control subjects living in the East-Center of Tunisia was used to analyze the contribution to T2D of the following SNPs: E23K in <it>KCNJ11/Kir6.2</it>, K121Q in <it>ENPP1</it>, the -30G/A variant in the pancreatic β-cell specific promoter of Glucokinase, rs7903146 in <it>TCF7L2 </it>encoding transcription factor 7-like2, and rs7923837 in <it>HHEX </it>encoding the homeobox, hematopoietically expressed transcription factor.</p> <p>Results</p> <p><it>TCF7L2</it>-rs7903146 T allele increased susceptibility to T2D (OR = 1.25 [1.06–1.47], <it>P </it>= 0.006) in our study population. This risk was 56% higher among subjects carrying the TT genotype in comparison to those carrying the CC genotype (OR = 1.56 [1.13–2.16], <it>P </it>= 0.002). No allelic or genotypic association with T2D was detected for the other studied polymorphisms.</p> <p>Conclusion</p> <p>In the Tunisian population, <it>TCF7L2</it>-rs7903146 T allele confers an increased risk of developing T2D as previously reported in the European population and many other ethnic groups. In contrast, none of the other tested SNPs that influence T2D risk in the European population was associated with T2D in the Tunisian Arabic population. An insufficient power to detect minor allelic contributions or genetic heterogeneity of T2D between different ethnic groups can explain these findings.</p
The transcription factor 7-like 2 (TCF7L2) polymorphism may be associated with focal arteriolar narrowing in Caucasians with hypertension or without diabetes: the ARIC Study
<p>Abstract</p> <p>Background</p> <p>Transcription factor 7-like 2 (<it>TCF7L2</it>) has emerged as a consistently replicated susceptibility gene for type 2 diabetes, however, whether the <it>TCF7L2 </it>gene also has similar effects on the retinal microvasculature is less clear. We therefore aimed to investigate the association between the transcription factor 7-like 2 (<it>TCF7L2</it>) rs7903146 polymorphism and retinal microvascular phenotypes in the Atherosclerosis Risk in Communities (ARIC) Study (1993-1995).</p> <p>Methods</p> <p>This was a population-based, cross-sectional study of 10,320 middle-aged African American (n = 2,199) and Caucasian (n = 8,121) men and women selected from four United States communities to examine the association between <it>TCF7L2 </it>rs7903146 polymorphism and retinal microvascular signs (retinopathy, focal arteriolar narrowing, arteriovenous nicking, arteriolar and venular calibers). Photographs on one randomly selected eye were graded for presence of retinal microvascular signs and used to measure retinal vessel calibres.</p> <p>Results</p> <p>After adjusting for age, sex, study center, mean arterial blood pressure, total serum cholesterol, triglycerides, and other covariates, few associations of <it>TCF7L2 </it>rs7903146 and retinal microvascular signs were noted. <it>TCF7L2 </it>rs7903146 T risk allele was significantly associated with focal arteriolar narrowing in Caucasians with hypertension [odds ratio (OR)<sub>CT vs. CC </sub>(95% CI) = 1.25 (1.09-1.44); OR<sub>TT vs. CC </sub>= 1.56 (1.18-2.06); <it>P </it>= 0.002] and in Caucasians without diabetes [OR <sub>CT vs. CC </sub>= 1.18 (1.06-1.32); OR <sub>TT vs. CC </sub>= 1.40 (1.12, 1.75); <it>P </it>= 0.003]. No significant association of the <it>TCF7L2 </it>rs7903146 polymorphism and retinal vascular signs was noted among African American individuals.</p> <p>Conclusions</p> <p><it>TCF7L2 </it>rs7903146 is not consistently associated with retinal microvascular signs. However, we report an association between the <it>TCF7L2 </it>rs7903146 polymorphism and focal arteriolar narrowing in Caucasians with hypertension or without diabetes. Further research in other large, population-based studies is needed to replicate these findings.</p
Association between TCF7L2 gene polymorphisms and susceptibility to Type 2 Diabetes Mellitus: a large Human Genome Epidemiology (HuGE) review and meta-analysis
<p>Abstract</p> <p>Background</p> <p>Transcription factor 7-like 2 (<it>TCF7L2</it>) has been shown to be associated with type 2 diabetes mellitus (T2MD) in multiple ethnic groups in the past two years, but, contradictory results were reported for Chinese and Pima Indian populations. The authors then performed a large meta-analysis of 36 studies examining the association of type 2 diabetes mellitus (T2DM) with polymorphisms in the <it>TCF7L2 </it>gene in various ethnicities, containing rs7903146 C-to-T (IVS3C>T), rs7901695 T-to-C (IVS3T>C), a rs12255372 G-to-T (IVS4G>T), and rs11196205 G-to-C (IVS4G>C) polymorphisms and to evaluate the size of gene effect and the possible genetic mode of action.</p> <p>Methods</p> <p>Literature-based searching was conducted to collect data and three methods, that is, fixed-effects, random-effects and Bayesian multivariate mete-analysis, were performed to pool the odds ratio (<it>OR</it>). Publication bias and study-between heterogeneity were also examined.</p> <p>Results</p> <p>The studies included 35,843 cases of T2DM and 39,123 controls, using mainly primary data. For T2DM and IVS3C>T polymorphism, the Bayesian <it>OR </it>for TT homozygotes and TC heterozygotes versus CC homozygote was 1.968 (95% credible interval (<it>CrI</it>): 1.790, 2.157), 1.406 (95% <it>CrI</it>: 1.341, 1.476), respectively, and the population attributable risk (PAR) for the TT/TC genotypes of this variant is 16.9% for overall. For T2DM and IVS4G>T polymorphism, TT homozygotes and TG heterozygotes versus GG homozygote was 1.885 (95%<it>CrI</it>: 1.698, 2.088), 1.360 (95% <it>CrI</it>: 1.291, 1.433), respectively. Four <it>OR</it>s among these two polymorphisms all yielded significant between-study heterogeneity (P < 0.05) and the main source of heterogeneity was ethnic differences. Data also showed significant associations between T2DM and the other two polymorphisms, but with low heterogeneity (<it>P </it>> 0.10). Pooled <it>OR</it>s fit a codominant, multiplicative genetic model for all the four polymorphisms of <it>TCF7L2 </it>gene, and this model was also confirmed in different ethnic populations when stratification of IVS3C>T and IVS4G>T polymorphisms except for Africans, where a dominant, additive genetic mode is suggested for IVS3C>T polymorphism.</p> <p>Conclusion</p> <p>This meta-analysis demonstrates that four variants of <it>TCF7L2 </it>gene are all associated with T2DM, and indicates a multiplicative genetic model for all the four polymorphisms, as well as suggests the <it>TCF7L2 </it>gene involved in near 1/5 of all T2MD. Potential gene-gene and gene-environmental interactions by which common variants in the <it>TCF7L2 </it>gene influence the risk of T2MD need further exploration.</p
SLC30A3 Responds to Glucose- and Zinc Variations in ß-Cells and Is Critical for Insulin Production and In Vivo Glucose-Metabolism During ß-Cell Stress
BACKGROUND:Ion transporters of the Slc30A- (ZnT-) family regulate zinc fluxes into sub-cellular compartments. beta-cells depend on zinc for both insulin crystallization and regulation of cell mass. METHODOLOGY/PRINCIPAL FINDINGS:This study examined: the effect of glucose and zinc chelation on ZnT gene and protein levels and apoptosis in beta-cells and pancreatic islets, the effects of ZnT-3 knock-down on insulin secretion in a beta-cell line and ZnT-3 knock-out on glucose metabolism in mice during streptozotocin-induced beta-cell stress. In INS-1E cells 2 mM glucose down-regulated ZnT-3 and up-regulated ZnT-5 expression relative to 5 mM. 16 mM glucose increased ZnT-3 and decreased ZnT-8 expression. Zinc chelation by DEDTC lowered INS-1E insulin content and insulin expression. Furthermore, zinc depletion increased ZnT-3- and decreased ZnT-8 gene expression whereas the amount of ZnT-3 protein in the cells was decreased. Zinc depletion and high glucose induced apoptosis and necrosis in INS-1E cells. The most responsive zinc transporter, ZnT-3, was investigated further; by immunohistochemistry and western blotting ZnT-3 was demonstrated in INS-1E cells. 44% knock-down of ZnT-3 by siRNA transfection in INS-1E cells decreased insulin expression and secretion. Streptozotocin-treated mice had higher glucose levels after ZnT-3 knock-out, particularly in overt diabetic animals. CONCLUSION/SIGNIFICANCE:Zinc transporting proteins in beta-cells respond to variations in glucose and zinc levels. ZnT-3, which is pivotal in the development of cellular changes as also seen in type 2 diabetes (e.g. amyloidosis in Alzheimer's disease) but not previously described in beta-cells, is present in this cell type, up-regulated by glucose in a concentration dependent manner and up-regulated by zinc depletion which by contrast decreased ZnT-3 protein levels. Knock-down of the ZnT-3 gene lowers insulin secretion in vitro and affects in vivo glucose metabolism after streptozotocin treatment
Accumulation of poly(A) RNA in nuclear granules enriched in Sam68 in motor neurons from the SMNA7 mouse model of SMA
Spinal muscular atrophy (SMA) is a severe motor neuron (MN) disease caused by the deletion or mutation of the survival motor neuron 1 (SMN1) gene, which results in reduced levels of the SMN protein and the selective degeneration of lower MNs. The best-known function of SMN is the biogenesis of spliceosomal snRNPs, the major components of the pre-mRNA splicing machinery. Therefore, SMN deficiency in SMA leads to widespread splicing abnormalities. We used the SMN?7 mouse model of SMA to investigate the cellular reorganization of polyadenylated mRNAs associated with the splicing dysfunction in MNs. We demonstrate that SMN deficiency induced the abnormal nuclear accumulation in euchromatin domains of poly(A) RNA granules (PARGs) enriched in the splicing regulator Sam68. However, these granules lacked other RNA-binding proteins, such as TDP43, PABPN1, hnRNPA12B, REF and Y14, which are essential for mRNA processing and nuclear export. These effects were accompanied by changes in the alternative splicing of the Sam68-dependent Bcl-x and Nrnx1 genes, as well as changes in the relative accumulation of the intron-containing Chat, Chodl, Myh9 and Myh14 mRNAs, which are all important for MN functions. PARG-containing MNs were observed at presymptomatic SMA stage, increasing their number during the symptomatic stage. Moreover, the massive accumulations of poly(A) RNA granules in MNs was accompanied by the cytoplasmic depletion of polyadenylated mRNAs for their translation. We suggest that the SMN-dependent abnormal accumulation of polyadenylated mRNAs and Sam68 in PARGs reflects a severe dysfunction of both mRNA processing and translation, which could contribute to SMA pathogenesis.This work was supported by grants from: “Dirección General de Investigación” of Spain (BFU2014-54754-P and SAF2015-70801-R, cofinanced by FEDER) and “Instituto de Investigación Marqués de Valdecilla-IDIVAL (NVAL17/22). Dr. Tapia is the recipient of a grant from SMA Europe and FundAME (Spain)
Association analysis of 31 common polymorphisms with type 2 diabetes and its related traits in Indian sib pairs
: AIMS/HYPOTHESIS: Evaluation of the association of 31 common single nucleotide polymorphisms (SNPs) with fasting glucose, fasting insulin, HOMA-beta cell function (HOMA-?), HOMA-insulin resistance (HOMA-IR) and type 2 diabetes in the Indian population. METHODS: We genotyped 3,089 sib pairs recruited in the Indian Migration Study from four cities in India (Lucknow, Nagpur, Hyderabad and Bangalore) for 31 SNPs in 24 genes previously associated with type 2 diabetes in European populations. We conducted within-sib-pair analysis for type 2 diabetes and its related quantitative traits. RESULTS: The risk-allele frequencies of all the SNPs were comparable with those reported in western populations. We demonstrated significant associations of CXCR4 (rs932206), CDKAL1 (rs7756992) and TCF7L2 (rs7903146, rs12255372) with fasting glucose, with ? values of 0.007 (p?=?0.05), 0.01 (p?=?0.01), 0.007 (p?=?0.05), 0.01 (p?=?0.003) and 0.08 (p?=?0.01), respectively. Variants in NOTCH2 (rs10923931), TCF-2 (also known as HNF1B) (rs757210), ADAM30 (rs2641348) and CDKN2A/B (rs10811661) significantly predicted fasting insulin, with ? values of -0.06 (p?=?0.04), 0.05 (p?=?0.05), -0.08 (p?=?0.01) and -0.08 (p?=?0.02), respectively. For HOMA-IR, we detected associations with TCF-2, ADAM30 and CDKN2A/B, with ? values of 0.05 (p?=?0.04), -0.07 (p?=?0.03) and -0.08 (p?=?0.02), respectively. We also found significant associations of ADAM30 (??=?-0.05; p?=?0.01) and CDKN2A/B (??=?-0.05; p?=?0.03) with HOMA-?. THADA variant (rs7578597) was associated with type 2 diabetes (OR 1.5; 95% CI 1.04, 2.22; p?=?0.03). CONCLUSIONS/INTERPRETATION: We validated the association of seven established loci with intermediate traits related to type 2 diabetes in an Indian population using a design resistant to population stratification
Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons
Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene
Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease. CAV1 and CAV2 organize membrane lipid rafts (MLRs) important for cell signaling and neuronal survival, and overexpression of CAV1 ameliorates ALS phenotypes in vivo. Genome-wide association studies localize a large proportion of ALS risk variants within the non-coding genome, but further characterization has been limited by lack of appropriate tools. By designing and applying a pipeline to identify pathogenic genetic variation within enhancer elements responsible for regulating gene expression, we identify disease-associated variation within CAV1/CAV2 enhancers, which replicate in an independent cohort. Discovered enhancer mutations reduce CAV1/CAV2 expression and disrupt MLRs in patient-derived cells, and CRISPR-Cas9 perturbation proximate to a patient mutation is sufficient to reduce CAV1/CAV2 expression in neurons. Additional enrichment of ALS-associated mutations within CAV1 exons positions CAV1 as an ALS risk gene. We propose CAV1/CAV2 overexpression as a personalized medicine target for ALS
Impact of population aging on future temperature-related mortality at different global warming levels
Data availability:
All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Data were collected within the MCC Collaborative Research Network under a data sharing agreement and cannot be made publicly available.Code availability:
A sample of the analysis code is available from https://github.com/CHENlab-Yale/MCC_ProjAging_Temp .Supplementary information is available online at: https://link-springer-com.ezproxytest.brunel.ac.uk/article/10.1038/s41467-024-45901-z#Sec15 .Older adults are generally amongst the most vulnerable to heat and cold. While temperature-related health impacts are projected to increase with global warming, the influence of population aging on these trends remains unclear. Here we show that at 1.5 °C, 2 °C, and 3 °C of global warming, heat-related mortality in 800 locations across 50 countries/areas will increase by 0.5%, 1.0%, and 2.5%, respectively; among which 1 in 5 to 1 in 4 heat-related deaths can be attributed to population aging. Despite a projected decrease in cold-related mortality due to progressive warming alone, population aging will mostly counteract this trend, leading to a net increase in cold-related mortality by 0.1%–0.4% at 1.5–3 °C global warming. Our findings indicate that population aging constitutes a crucial driver for future heat- and cold-related deaths, with increasing mortality burden for both heat and cold due to the aging population.We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modeling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. K.C. was supported by the Yale Planetary Solutions Project seed grant. A.G., A.S., and S.R. were supported by the European Union’s Horizon 2020 Project Exhaustion grant (820655). A.G. was also supported by the Medical Research Council UK grant (MR/V034162/1). J.M. received funding from the Fundação para a Ciência e a Tecnlogia Grant (SFRH/BPD/115112/2016). A.T. was supported by the MCIN/AEI/10.13039/501100011033 grant (CEX2018-000794-S). A.U. and J.K. were supported by the Czech Science Foundation (22-24920S). F.S. was supported by the Italian Ministry of University and Research (MUR), Department of Excellence project 2023-2027 ReDS ‘Rethinking Data Science’ - Department of Statistics, Computer Science and Applications - University of Florence. MNM. was supported by the European Commission (H2020-MSCA-IF-2020) under REA grant agreement no. 101022870. A.V.C. acknowledges the support of the Swiss National Foundation (TMSGI3_211626). V.H. received funding from the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie Grant Agreement No.: 101032087)
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