Endoplasmic reticulum stress-induced apoptosis in the development of diabetes: is there a role for adipose tissue and liver?

Diabetes mellitus (DM) is a multifactorial chronic metabolic disease characterized by hyperglycaemia. Several different mechanisms have been implicated in the development of the disease, including endoplasmic reticulum (ER) stress. ER stress is increasingly acknowledged as an important mechanism in the development of DM, not only for β-cell loss but also for insulin resistance. Accumulating evidence suggests that ER stress-induced apoptosis may be an important mode of β-cell loss and therefore important in the development of diabetes. Recent data also suggest a role of ER stress-induced apoptosis in liver and adipose tissue in relation to diabetes, but more extensive studies on human adipocyte and hepatocyte (patho)physiology and ER stress are needed to identify the exact interactions between environmental signals, ER stress and apoptosis in these organs

Glucose Variability Assessed with Continuous Glucose Monitoring:Reliability, Reference Values, and Correlations with Established Glycemic Indices-The Maastricht Study

Background: Glucose variability (GV) measured by continuous glucose monitoring (CGM) has become an accepted marker of glycemic control. Nevertheless, several methodological aspects of GV assessment require further study. We, therefore, investigated the minimum number of days needed to reliably measure GV, assessed GV reference values, and studied the correlation of GV with established glycemic indices (i.e., HbA(1c), seven-point oral glucose tolerance test [OGTT]-derived indices). Methods: We used cross-sectional data from The Maastricht Study, an observational population-based cohort enriched with type 2 diabetes. Participants with more than 48 h of CGM (iPro2; Medtronic) were included for analysis (n = 851; age: 60 +/- 9years; 49% women; 23% type 2 diabetes). We used mean sensor glucose (MSG), standard deviation (SD), and coefficient of variation (CV) as CGM-derived indices (the latter two for GV quantification). We calculated reliability using the Spearman-Brown prophecy formula, established reference values by calculating 2.5th-97.5th percentiles, and studied correlations using Spearman's rho. Results: Sufficient reliability (R > 0.80) was achieved with two (MSG and SD), or three monitoring days (CV). The reference ranges, assessed in individuals with normal glucose metabolism (n = 470), were 90.5-120.6 mg/dL (MSG), 7.9-24.8 mg/dL (SD), and 7.74%-22.45% (CV). For MSG, the strongest correlation was found with fasting plasma glucose (rho = 0.65 [0.61; 0.69]); for SD, with the 1-h OGTT value (rho = 0.61 [0.56; 0.65]); and for CV, with both the incremental glucose peak (IGP) during the OGTT (rho = 0.50 [0.45; 0.55]) and the 1-h OGTT value (rho = 0.50 [0.45; 0.55]). Conclusions: The reliability findings and reference values are relevant for studies that aim to investigate CGM-measured GV. One-hour OGTT and IGP values can be used as GV indices when CGM is unavailable

Upstream transcription factor 1 (USF1) in risk of type 2 diabetes:Association study in 2000 Dutch Caucasians

Type 2 diabetes shares substantial genetic and phenotypic overlap with familial combined hyperlipidemia. Upstream stimulatory factor 1 (USF7), a well-established susceptibility gene for familial combined hyperlipidemia, is postulated to be such a shared genetic determinant. We evaluated two established variants in familial combined hyperlipidemia (rs2073658 and rs3737787) for association with type 2 diabetes in two Dutch case-control samples (N=2011). The first case-control sample comprised 501 subjects with type 2 diabetes from the Breda cohort and 920 healthy blood bank donors of Dutch Caucasian origin. The second case-control sample included 211 subjects with type 2 diabetes, and 379 normoglycemic controls. SNP rs2073658 and SNP rs3737787 were in perfect linkage disequilibrium. In the first case-control sample, prevalence of the major allele was higher in patients than in controls (75% versus 71%, OR=1.25, p=0.018). A similar effect-size and -direction was observed in the second case-control sample (76% versus 72%, OR=1.22, p=0.16). A combined analysis strengthened the evidence for association (OR=1.23, p=0.006). Notably, the increased risk for type 2 diabetes could be ascribed to the major allele, and its high frequency translated to a substantial population attributable risk of 14.5%. In conclusion, the major allele of rs2073658 in the USF1 gene is associated with a modestly increased risk to develop type 2 diabetes in Dutch Caucasians, with considerable impact at the population level. (c) 2008 Elsevier Inc. All rights reserved

Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study

Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to blindness and cardiovascular disease. Information about early stage T2D might be present in retinal fundus images, but to what extent these images can be used for a screening setting is still unknown. In this study, deep neural networks were employed to differentiate between fundus images from individuals with and without T2D. We investigated three methods to achieve high classification performance, measured by the area under the receiver operating curve (ROC-AUC). A multi-target learning approach to simultaneously output retinal biomarkers as well as T2D works best (AUC = 0.746 [$\pm$0.001]). Furthermore, the classification performance can be improved when images with high prediction uncertainty are referred to a specialist. We also show that the combination of images of the left and right eye per individual can further improve the classification performance (AUC = 0.758 [$\pm$0.003]), using a simple averaging approach. The results are promising, suggesting the feasibility of screening for T2D from retinal fundus images.Comment: to be published in the proceeding of SPIE - Medical Imaging 2020, 6 pages, 1 figur

Activating transcription factor 6 polymorphisms and haplotypes are associated with impaired glucose homeostasis and type 2 diabetes in dutch Caucasians

Context: Activating transcription factor 6 (ATF6) is critical for initiation and full activation of the unfolded protein response. An association between genetic variation in ATF6 and type 2 diabetes (DM2) was recently reported in Pima Indians. Objectives: To investigate the broader significance of this association for DM2, replication studies in distinct ethic populations are required. We investigated ATF6 for its association with DM2 in Dutch Caucasians. Design/Setting: A genetic association study was conducted at an academic research laboratory. Study Participants: Two independent Dutch cohorts were studied. Cohort 1 (n = 154) was used to evaluate genetic variation in the ATF6 gene in relation to glucose homeostasis in the general population. Cohort 2 (n = 798) consisted of patients with DM2, impaired glucose tolerance, impaired fasting glucose, and normoglycemic control subjects, and was used to investigate ATF6 polymorphisms for their contribution to disturbed glucose homeostasis and DM2. Main Outcome Measures: There were 16 tag single nucleotide polymorphisms genotyped in all subjects of both cohorts. Those single nucleotide polymorphisms included three nonsynonymous coding variants and captured all common allelic variation of ATF6. Results: Our data show that common ATF6 variants are associated with elevated glucose levels in the general population (cohort 1, P = 0.005-0.05). Furthermore, the majority of these variants, and haplotypes thereof, were significantly associated with impaired fasting glucose, impaired glucose tolerance, and DM2 ( cohort 2, P = 0.006-0.05). Associated variants differ from those identified in Pima Indians. Conclusions: Our results strengthen the evidence that one or more variants in ATF6 are associated with disturbed glucose homeostasis and DM2

Association of Type 2 Diabetes, According to the Number of Risk Factors Within Target Range, With Structural Brain Abnormalities, Cognitive Performance, and Risk of Dementia

OBJECTIVE: Type 2 diabetes is associated with increased risks of cognitive dysfunction and brain abnormalities. The extent to which risk factor modification can mitigate these risks is unclear. We investigated the associations between incident dementia, cognitive performance, and brain abnormalities among individuals with type 2 diabetes, according to the number of risk factors on target, compared with control subjects without diabetes. RESEARCH DESIGN AND METHODS: Prospective data were from UK Biobank of 87,856 individuals (n = 10,663 diabetes, n = 77,193 control subjects; baseline 2006-2010), with dementia follow-up until February 2018. Individuals with diabetes were categorized according to the number of seven selected risk factors within the guideline-recommended target range (nonsmoking; guideline-recommended levels of glycated hemoglobin, blood pressure, BMI, albuminuria, physical activity, and diet). Outcomes were incident dementia, domain-specific cognitive performance, white matter hyperintensities, and total brain volume. RESULTS: After a mean follow-up of 9.0 years, 147 individuals (1.4%) with diabetes and 412 control subjects (0.5%) had incident dementia. Among individuals with diabetes, excess dementia risk decreased stepwise for a higher number of risk factors on target. Compared with control subjects (incidence rate per 1,000 person-years 0.62 [95% CI 0.56; 0.68]), individuals with diabetes who had five to seven risk factors on target had no significant excess dementia risk (absolute rate difference per 1,000 person-years 0.20 [-0.11; 0.52]; hazard ratio 1.32 [0.89; 1.95]). Similarly, differences in processing speed, executive function, and brain volumes were progressively smaller for a higher number of risk factors on target. These results were replicated in the Maastricht Study. CONCLUSIONS: Among individuals with diabetes, excess dementia risk, lower cognitive performance, and brain abnormalities decreased stepwise for a higher number of risk factors on target

Impaired HDL cholesterol efflux in metabolic syndrome is unrelated to glucose tolerance status:the CODAM study

Type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) increase atherosclerotic cardiovascular disease risk. Cholesterol efflux capacity (CEC) is a key metric of the anti-atherosclerotic functionality of high-density lipoproteins (HDL). The present study aimed to delineate if T2DM and MetS cross-sectionally associate with altered CEC in a large high cardiometabolic risk population. CEC was determined from THP-1 macrophage foam cells towards apolipoprotein B-depleted plasma from 552 subjects of the CODAM cohort (288 controls, 126 impaired glucose metabolism [IGM], 138 T2DM). MetS was present in 297 participants. CEC was not different between different glucose tolerance categories but was lower in MetS (P <0.001), at least partly attributable to lower HDL cholesterol (HDL-C) and apoA-I levels (P <0.001 for each). Low grade inflammation was increased in IGM, T2DM and MetS as determined by a score comprising 8 different biomarkers (P <0.05-<0.001; n = 547). CEC inversely associated with low-grade inflammation taking account of HDL-C or apoA-I in MetS (P <0.02), but not in subjects without MetS (interaction: P = 0.015). This study demonstrates that IGM and T2DM do not impact the HDL CEC function, while efflux is lower in MetS, partly dependent on plasma HDL-C levels. Enhanced low-grade inflammation in MetS may conceivably impair CEC even independent of HDL-C and apoA-I

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

BACKGROUND: DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. RESULTS: By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g., NFKBIE, CDCA7(L), and NLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. CONCLUSION: We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation