Discovery of 318 novel loci for type-2 diabetes and related micro- and macrovascular outcomes among 1.4 million participants in a multi-ethnic meta-analysis

Vujkovic, Marijana; Keaton, Jacob M.; Lynch, Julie; Miller, Donald R.; Zhou, Jin; Tcheandjieu, Catherine; Huffman, Jennifer E.; Assimes, Themistocles L.; Judy, Renae; Huang, Jie; Lee, Kyung Min; Klarin, Derek; Pyarajan, Saiju; Danesh, John; Melander, Olle; Rasheed, Awais; Qamar, Nadeem; Sheikh, Saqib Shafi; Hameed, Shahid; Qureshi, Irshad Hussain; Afzal, Muhammad; Jahazaib, Uzma; Jalal, Anjum; Abbas, Shahid; Sheng, Xin; Gao, Long; Kaestner, Klaus H.; Suszták, Katalin; Sun, Yan V.; DuVall, Scott L.; Cho, Kelly; Lee, Jennifer S.; Gaziano, J. Michael; Philips, Lawrence S.; Meigs, James B.; Reaven, Peter D.; Wilson, Peter W.F.; Edwards, Todd L.; Rader, Daniel J.; Damrauer, Scott M.; O’Donnell, Christopher J.; Tsao, Philip S.; Chang, Kyong–Mi; Voight, Benjamin F.; Saleheen, Danish

doi:10.1101/19012690

Cited by 50 publications

(73 citation statements)

References 78 publications

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“…In more complex and common diseases such as T2D, clues to the genetic and physiological mechanisms may be inferred from large-scale GWAS. To date, >400 genetic loci have been associated with T2D risk (22). Some of these are in proximity of UPR genes such as the well-established WFS1 risk variants (23) that are associated with reduced insulin secretion (24).…”

Section: Gwas Of T2d Identify Variants In Genes Essential For Er Stress Regulationmentioning

confidence: 99%

Pathological β-Cell Endoplasmic Reticulum Stress in Type 2 Diabetes: Current Evidence

et al. 2021

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The notion that in diabetes pancreatic β-cells express endoplasmic reticulum (ER) stress markers indicative of increased unfolded protein response (UPR) signaling is no longer in doubt. However, what remains controversial is whether this increase in ER stress response actually contributes importantly to the β-cell failure of type 2 diabetes (akin to ‘terminal UPR’), or whether it represents a coping mechanism that represents the best attempt of β-cells to adapt to changes in metabolic demands as presented by disease progression. Here an intercontinental group of experts review evidence for the role of ER stress in monogenic and type 2 diabetes in an attempt to reconcile these disparate views. Current evidence implies that pancreatic β-cells require a regulated UPR for their development, function and survival, as well as to maintain cellular homeostasis in response to protein misfolding stress. Prolonged ER stress signaling, however, can be detrimental to β-cells, highlighting the importance of “optimal” UPR for ER homeostasis, β-cell function and survival.

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Section: Gwas Of T2d Identify Variants In Genes Essential For Er Stress Regulationmentioning

confidence: 99%

Pathological β-Cell Endoplasmic Reticulum Stress in Type 2 Diabetes: Current Evidence

et al. 2021

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“…However, it is important to notice that single nucleotide polymorphisms (SNPs) primarily associated with obesity tend to have a positive correlation between the effect size on BMI and the effect of the same SNP on T2D, yet SNPs primarily associated with T2D have no impact on BMI per se (15). Importantly, both GWAS and gene candidate approaches have led to the identification of genes implicated in the pathogenesis of obesity and/or T2D (14,16), which are involved in critical pathways for glucose regulatory processes, such as insulin signaling (INSR, IRS1, IRS2) (16)(17)(18)(19)(20), beta-cell differentiation and insulin secretion (PDX1, HNF4A, TCF7L2, SLC2A4, GLP1R, KCNQ1) (16,17,(21)(22)(23)(24), adipocyte differentiation (PPARG, PPARGC1A, LEP, ADIPOQ) (17,19,20,25,26), mitochondrial biogenesis and function (PGC1) (27), lipid and glucose homeostasis (SREBF1) (28) and cytokine signaling and inflammation (ADIPOQ) (29).…”

Section: Introductionmentioning

confidence: 99%

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

et al. 2021

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BackgroundObesity is a major risk factor for dysglycemic disorders, including type 2 diabetes (T2D). However, there is wide phenotypic variation in metabolic profiles. Tissue-specific epigenetic modifications could be partially accountable for the observed phenotypic variability.ScopeThe aim of this systematic review was to summarize the available data on epigenetic signatures in human adipose tissue (AT) that characterize overweight or obesity-related insulin resistance (IR) and dysglycemia states and to identify potential underlying mechanisms through the use of unbiased bioinformatics approaches.MethodsOriginal data published in the last decade concerning the comparison of epigenetic marks in human AT of individuals with metabolically unhealthy overweight/obesity (MUHO) versus normal weight individuals or individuals with metabolically healthy overweight/obesity (MHO) was assessed. Furthermore, association of these epigenetic marks with IR/dysglycemic traits, including T2D, was compiled.ResultsWe catalogued more than two thousand differentially methylated regions (DMRs; above the cut-off of 5%) in the AT of individuals with MUHO compared to individuals with MHO. These DNA methylation changes were less likely to occur around the promoter regions and were enriched at loci implicated in intracellular signaling (signal transduction mediated by small GTPases, ERK1/2 signaling and intracellular trafficking). We also identified a network of seven transcription factors that may play an important role in targeting DNA methylation changes to specific genes in the AT of subjects with MUHO, contributing to the pathogeny of obesity-related IR/T2D. Furthermore, we found differentially methylated CpG sites at 8 genes that were present in AT and whole blood, suggesting that DMRs in whole blood could be potentially used as accessible biomarkers of MUHO.ConclusionsThe overall evidence linking epigenetic alterations in key tissues such AT to metabolic complications in human obesity is still very limited, highlighting the need for further studies, particularly those focusing on epigenetic marks other than DNA methylation. Our initial analysis suggests that DNA methylation patterns can potentially discriminate between MUHO from MHO and provide new clues into why some people with obesity are less susceptible to dysglycemia. Identifying AT-specific epigenetic targets could also lead to novel approaches to modify the progression of individuals with obesity towards metabolic disease.Systematic Review RegistrationPROSPERO, identifier CRD42021227237.

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“…We did not replicate the finding that the chromosome regions near CENPW, GLIS3, BCL11A or THADA colocalised between type 1 and type 2 diabetes (H4PP CENPW=0.12, GLIS3=0.29, BCL11A=0.28, THADA not examined as no type 1 diabetes association existed in the region [FDR=0.07]). To investigate these discrepancies, we examined two other large type 2 diabetes meta-analyses: a trans-ethnic study including 1,407,282 individuals [8] and a study of 433,540 individuals of East Asian ancestry [9]. For the CENPW and BCL11A regions, the type 2 diabetes signal is consistent with at least one of the other GWAS studies (measured by linkage disequilibrium [LD] in Europeans to the other study index variants, ESM Table 4), and the type 1 diabetes index variant is not in strong LD (r 2 <0.41) with any of the index variants for type 2 diabetes across the three GWAS studies.…”

Section: Resultsmentioning

confidence: 99%

Analysis of overlapping genetic association in type 1 and type 2 diabetes

et al. 2021

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Aims/hypothesis Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal co-localises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. Methods Using publicly available type 2 diabetes summary statistics from a genome-wide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate <0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined co-localisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a co-localisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. Results Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals co-localised between both diseases (posterior probability ≥0.9): (1) chromosome 16q23.1, near CTRB1/BCAR1, which has been previously identified; (2) chromosome 11p15.5, near the INS gene; (3) chromosome 4p16.3, near TMEM129 and (4) chromosome 1p31.3, near PGM1. In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified co-localisation on chromosome 9p24.2, near the GLIS3 gene, in this case with a concordant direction of effect. Conclusions/interpretation Four of five association signals that co-localise between type 1 diabetes and type 2 diabetes are in opposite directions, suggesting a complex genetic relationship between the two diseases. Graphical abstract

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Discovery of 318 novel loci for type-2 diabetes and related micro- and macrovascular outcomes among 1.4 million participants in a multi-ethnic meta-analysis

Cited by 50 publications

References 78 publications

Pathological β-Cell Endoplasmic Reticulum Stress in Type 2 Diabetes: Current Evidence

Pathological β-Cell Endoplasmic Reticulum Stress in Type 2 Diabetes: Current Evidence

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

Analysis of overlapping genetic association in type 1 and type 2 diabetes

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