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

Symptoms and quality of life before, during, and after a SARS-CoV-2 PCR positive or negative test:data from Lifelines

This study evaluates to what extent symptoms are present before, during, and after a positive SARS-CoV-2 polymerase chain reaction (PCR) test, and to evaluate how the symptom burden and quality of Life (QoL) compares to those with a negative PCR test. Participants from the Dutch Lifelines COVID-19 Cohort Study filled-out as of March 2020 weekly, later bi-weekly and monthly, questions about demographics, COVID-19 diagnosis and severity, QoL, and symptoms. The study population included those with one positive or negative PCR test who filled out two questionnaires before and after the test, resulting in 996 SARS-CoV-2 PCR positive and 3978 negative participants. Nearly all symptoms were more often reported after a positive test versus the period before the test (p &lt; 0.05), except fever. A higher symptom prevalence after versus before a test was also found for nearly all symptoms in negatives (p &lt; 0.05). Before the test, symptoms were already partly present and reporting of nearly all symptoms before did not differ between positives and negatives (p &gt; 0.05). QoL decreased around the test for positives and negatives, with a larger deterioration for positives. Not all symptoms after a positive SARS-CoV-2 PCR test might be attributable to the infection and symptoms were also common in negatives.</p

Blood pressure variability in individuals with and without (pre)diabetes:the Maastricht Study

Objective: The mechanisms associating (pre)diabetes and cardiovascular disease (CVD) are incompletely understood. We hypothesize that greater blood pressure variability (BPV) may underlie this association, due to its association with (incident) CVD. Therefore, we investigated the association between (pre)diabetes and very short-term to mid-term BPV, that is within-visit, 24-h and 7-day BPV. Methods: Cross-sectional data from The Maastricht Study [normal glucose metabolism (NGM), n¼1924; prediabetes, n¼511; type 2 diabetes mellitus (T2DM), n¼975; 51% men, aged 608 years]. We determined SD for within visit BPV (n¼3244), average real variability for 24-h BPV (n¼2699) day (0900–2100 h) and night (0100–0600 h) separately, and SD for 7-day BPV (n¼2259). Differences in BPV as compared with NGM were assessed by multiple linear regressions with adjustment for potential confounders. Results: In T2DM, the average systolic/diastolic values of within-visit, 24-h and 7-day BPV were 4.8/2.6, 10.5/7.3 and 10.4/6.5 mmHg, respectively, and in prediabetes 4.9/ 2.6, 10.3/7.0 and 9.4/5.9 mmHg, respectively. T2DM was associated with greater nocturnal systolic BPV [0.42mmHg (95% confidence interval: 0.05–0.80)], and greater 7-day systolic [0.76mmHg (0.32–1.19)] and diastolic BPV [0.65mmHg (0.29–1.01)], whereas prediabetes was associated with greater within-visit systolic BPV only [0.35mmHg (0.06–0.65)], as compared with NGM. Conclusion: Both T2DM and prediabetes are associated with slightly greater very short-term to mid-term BPV, which may, according to previous literature, explain a small part of the increased CVD risk seen in (pre)diabetes. Nevertheless, these findings do not detract from the fact that very short-term to mid-term BPV is substantial and important in individuals with and without (pre)diabetes

Analyzing Partitioned FAIR Health Data Responsibly

It is widely anticipated that the use of health-related big data will enable further understanding and improvements in human health and wellbeing. Our current project, funded through the Dutch National Research Agenda, aims to explore the relationship between the development of diabetes and socio-economic factors such as lifestyle and health care utilization. The analysis involves combining data from the Maastricht Study (DMS), a prospective clinical study, and data collected by Statistics Netherlands (CBS) as part of its routine operations. However, a wide array of social, legal, technical, and scientific issues hinder the analysis. In this paper, we describe these challenges and our progress towards addressing them.Comment: 6 pages, 1 figure, preliminary result, project repor

Association Between Employment Status and Objectively Measured Physical Activity and Sedentary BehaviorThe Maastricht Study

Objective:To examine the association between employment status and physical activity and sedentary behavior.Methods:We included 2045 participants from The Maastricht Study, who used a thigh-worn accelerometer. We compared time spent sedentary, standing, stepping, and higher intensity physical activity between participants with different employment status (non-employed or low-, intermediate- or high-level occupation) with analysis of variance.Results:Participants in low-level occupations were less sedentary and standing and stepping more than those in other occupational categories and non-employed participants. Among the employed, the differences were mostly observed on weekdays, whereas the differences in sedentary time and standing between those in low-level occupations and non-employed participants were evident both on weekdays and weekend days.Conclusions:Those in low-level occupational category were less sedentary and more active than non-employed and those in other occupational categories, especially on weekdays

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

White Matter Connectivity Abnormalities in Prediabetes and Type 2 Diabetes:The Maastricht Study

OBJECTIVE: Prediabetes and type 2 diabetes are associated with structural brain abnormalities, often observed in cognitive disorders. Besides visible lesions, (pre)diabetes might also be associated with alterations of the intrinsic organization of the white matter. In this population-based cohort study, the association of prediabetes and type 2 diabetes with white matter network organization was assessed. RESEARCH DESIGN AND METHODS: In the Maastricht Study, a type 2 diabetes-enriched population-based cohort study (1,361 normal glucose metabolism, 348 prediabetes, and 510 type 2 diabetes assessed by oral glucose tolerance test; 52% men; aged 59 ± 8 years), 3 Tesla structural and diffusion MRI was performed. Whole-brain white matter tractography was used to assess the number of connections (node degree) between 94 brain regions and the topology (graph measures). Multivariable linear regression analyses were used to investigate the associations of glucose metabolism status with network measures. Associations were adjusted for age, sex, education, and cardiovascular risk factors. RESULTS: Prediabetes and type 2 diabetes were associated with lower node degree after full adjustment (standardized [st]βPrediabetes = -0.055 [95% CI -0.172, -0.062], stβType2diabetes = -0.256 [-0.379, -0.133], Ptrend < 0.001). Prediabetes was associated with lower local efficiency (stβ = -0.084 [95% CI -0.159, -0.008], P = 0.033) and lower clustering coefficient (stβ = -0.097 [95% CI -0.189, -0.005], P = 0.049), whereas type 2 diabetes was not. Type 2 diabetes was associated with higher communicability (stβ = 0.148 [95% CI 0.042, 0.253], P = 0.008). CONCLUSIONS: These findings indicate that prediabetes and type 2 diabetes are associated with fewer white matter connections and weaker organization of white matter networks. Type 2 diabetes was associated with higher communicability, which was not yet observed in prediabetes and may reflect the use of alternative white matter connections