Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits

Disruption of fasting and post-load glucose homeostasis are largely independent and sustained by distinct and early major beta-cell function defects: a cross-sectional and longitudinal analysis of the relationship between insulin sensitivity and cardiovascular risk (RISC) study cohort

Background/aims: Uncertainty still exists on the earliest beta-cell defects at the bases of the type 2 diabetes. We assume that this depends on the inaccurate distinction between fasting and post-load glucose homeostasis and aim at providing a description of major beta-cell functions across the full physiologic spectrum of each condition. Methods: In 1320 non-diabetic individuals we performed an OGTT with insulin secretion modeling and a euglycemic insulin clamp, coupled in subgroups to glucose tracers and IVGTT; 1038 subjects underwent another OGTT after 3.5 years. Post-load glucose homeostasis was defined as mean plasma glucose above fasting levels (δOGTT). The analysis was performed by two-way ANCOVA. Results: Fasting plasma glucose (FPG) and δOGTT were weakly related variables (stβ = 0.12) as were their changes over time (r = −0.08). Disruption of FPG control was associated with an isolated and progressive decline (approaching 60%) of the sensitivity of the beta-cell to glucose values within the normal fasting range. Disruption of post-load glucose control was characterized by a progressive decline (approaching 60%) of the slope of the full beta-cell vs glucose dose-response curve and an early minor (30%) decline of potentiation. The acute dynamic beta-cell responses, neither per se nor in relation to the degree of insulin resistance appeared to play a relevant role in disruption of fasting or post-load homeostasis. Follow-up data qualitatively and quantitatively confirmed the results of the cross-sectional analysis. Conclusion: In normal subjects fasting and post-load glucose homeostasis are largely independent, and their disruption is sustained by different and specific beta-cell defects

Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts

Aims/hypothesis: The euglycemic hyperinsulinemic clamp (EIC) is a direct measure and the reference-standard in the assessment of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-throughput plasma proteomic profiling in developing signatures correlating with the M-value derived from the EIC. Methods: We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M-value variance explained (R2 82 ). Results: A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M-value R2 85 from 0.237 (95% confidence interval: 0.178-0.303) to 0.456 (0.372-0.536) in RISC. A similar pattern was observed in ULSAM in which the M-value R2 increased from 0.443 (0.360-0.530) to 0.632 (0.569-0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R2 despite differences in baseline cohort characteristics and clamp methodology: RISC to ULSAM: 0.491 (0.433-0.539) for 51 proteins, ULSAM to RISC: 0.369 (0.331-0.416) for 67 proteins. A randomized LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins) which improved R2 92 but to a lesser degree than standard LASSO models: 0.352 (0.266-0.439) within RISC and 0.495 (0.404-0.585) within ULSAM. Differences in R2 93 explained between randomized and standard LASSO were notably reduced in the cross-cohort analyses despite the much smaller number of proteins selected: RISC to ULSAM range 0.444 (0.391-0.497) ULSAM to RISC range 0.348 (0.300-0.396). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomized LASSO. The single most consistently selected protein across all analyses and models was IGFBP2. Conclusions/interpretation: A plasma proteomic signature identified through a standard LASSO approach improves the cross-sectional estimation of the M-value over routine clinical variables. However, a small subset of these proteins identified using stability selection algorithm affords much of this improvement especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin resistant individuals at risk of IR-related adverse health consequences

Dynamics of disease characteristics and clinical management of critically ill COVID-19 patients over the time course of the pandemic: an analysis of the prospective, international, multicentre RISC-19-ICU registry.

BACKGROUND It remains elusive how the characteristics, the course of disease, the clinical management and the outcomes of critically ill COVID-19 patients admitted to intensive care units (ICU) worldwide have changed over the course of the pandemic. METHODS Prospective, observational registry constituted by 90 ICUs across 22 countries worldwide including patients with a laboratory-confirmed, critical presentation of COVID-19 requiring advanced organ support. Hierarchical, generalized linear mixed-effect models accounting for hospital and country variability were employed to analyse the continuous evolution of the studied variables over the pandemic. RESULTS Four thousand forty-one patients were included from March 2020 to September 2021. Over this period, the age of the admitted patients (62 [95% CI 60-63] years vs 64 [62-66] years, p < 0.001) and the severity of organ dysfunction at ICU admission decreased (Sequential Organ Failure Assessment 8.2 [7.6-9.0] vs 5.8 [5.3-6.4], p < 0.001) and increased, while more female patients (26 [23-29]% vs 41 [35-48]%, p < 0.001) were admitted. The time span between symptom onset and hospitalization as well as ICU admission became longer later in the pandemic (6.7 [6.2-7.2| days vs 9.7 [8.9-10.5] days, p < 0.001). The PaO2/FiO2 at admission was lower (132 [123-141] mmHg vs 101 [91-113] mmHg, p < 0.001) but showed faster improvements over the initial 5 days of ICU stay in late 2021 compared to early 2020 (34 [20-48] mmHg vs 70 [41-100] mmHg, p = 0.05). The number of patients treated with steroids and tocilizumab increased, while the use of therapeutic anticoagulation presented an inverse U-shaped behaviour over the course of the pandemic. The proportion of patients treated with high-flow oxygen (5 [4-7]% vs 20 [14-29], p < 0.001) and non-invasive mechanical ventilation (14 [11-18]% vs 24 [17-33]%, p < 0.001) throughout the pandemic increased concomitant to a decrease in invasive mechanical ventilation (82 [76-86]% vs 74 [64-82]%, p < 0.001). The ICU mortality (23 [19-26]% vs 17 [12-25]%, p < 0.001) and length of stay (14 [13-16] days vs 11 [10-13] days, p < 0.001) decreased over 19 months of the pandemic. CONCLUSION Characteristics and disease course of critically ill COVID-19 patients have continuously evolved, concomitant to the clinical management, throughout the pandemic leading to a younger, less severely ill ICU population with distinctly different clinical, pulmonary and inflammatory presentations than at the onset of the pandemic

Fatty liver is associated with insulin resistance, risk of coronary heart disease, and early atherosclerosis in a large European population

Udgivelsesdato: 2009-MayPatients with fatty liver (FL) disease have a high risk of developing diabetes and cardiovascular diseases. The aim was to evaluate the association between FL, insulin resistance (IR), coronary heart disease (CHD) risk, and early atherosclerosis in a large European population (RISC Study). In 1,307 nondiabetic subjects (age 30-60 years) recruited at 19 centers, we evaluated liver enzymes, lipids, insulin sensitivity (by euglycemic-hyperinsulinemic clamp), glucose tolerance (by 75 g oral glucose tolerance test), carotid atherosclerosis as intima media thickness (IMT), CHD risk by the Framingham Heart study prediction score, and physical activity (by accelerometer). The presence of FL was estimated using the fatty liver index (FLI; &gt;60, likelihood &gt;78% presence FL; FLI &lt;20 likelihood &gt;91% absence of FL). Subjects were divided into three groups: G1: FLI &lt;20 (n = 608); G3: FLI &gt;60 (n = 234), G2: intermediate group (n = 465). Compared to G1, G3 included more men (70% versus 24%) and people with impaired glucose tolerance (23% versus 5%). IMT increased with FLI (G3 = 0.64 +/- 0.08 versus G1 = 0.58 +/- 0.08 mm, P &lt; 0.0001). FLI was associated with increased CHD risk (r = 0.48), low-density lipoprotein cholesterol (r = 0.33), alanine aminotransferase (r = 0.48), aspartate aminotransferase (r = 0.25), systolic blood pressure (r = 0.39) and IMT (r = 0.30), and reduced insulin sensitivity (r = -0.43), high-density lipoprotein cholesterol (r = -0.50), adiponectin (r = -0.42), and physical activity (r = -0.16, all P &lt; 0.0001). The correlations hold also in multivariate analysis after adjusting for age, gender, and recruiting center. Conclusion: In middle-age nondiabetic subjects, increased IMT, CHD risk, and reduced insulin sensitivity are associated with high values of FLI

Prognostic factors associated with mortality risk and disease progression in 639 critically ill patients with COVID-19 in Europe: Initial report of the international RISC-19-ICU prospective observational cohort

Background Coronavirus disease 2019 (COVID-19) is associated with a high disease burden with 10% of confirmed cases progressing towards critical illness. Nevertheless, the disease course and predictors of mortality in critically ill patients are poorly understood. Methods Following the critical developments in ICUs in regions experiencing early inception of the pandemic, the European-based, international RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry was created to provide near real-time assessment of patients developing critical illness due to COVID-19. Findings As of April 22, 2020, 639 critically ill patients with confirmed SARS-CoV-2 infection were included in the RISC-19-ICU registry. Of these, 398 had deceased or been discharged from the ICU. ICU-mortality was 24%, median length of stay 12 (IQR, 5-21) days. ARDS was diagnosed in 74%, with a minimum P/F-ratio of 110 (IQR, 80-148). Prone positioning, ECCO2R, or ECMO were applied in 57%. Off-label therapies were prescribed in 265 (67%) patients, and 89% of all bloodstream infections were observed in this subgroup (n = 66; RR=3·2, 95% CI [1·7-6·0]). While PCT and IL-6 levels remained similar in ICU survivors and non-survivors throughout the ICU stay (p = 0·35, 0·34), CRP, creatinine, troponin, d-dimer, lactate, neutrophil count, P/F-ratio diverged within the first seven days (p<0·01). On a multivariable Cox proportional-hazard regression model at admission, creatinine, d-dimer, lactate, potassium, P/F-ratio, alveolar-arterial gradient, and ischemic heart disease were independently associated with ICU-mortality. Interpretation The European RISC-19-ICU cohort demonstrates a moderate mortality of 24% in critically ill patients with COVID-19. Despite high ARDS severity, mechanical ventilation incidence was low and associated with more rescue therapies. In contrast to risk factors in hospitalized patients reported in other studies, the main mortality predictors in these critically ill patients were markers of oxygenation deficit, renal and microvascular dysfunction, and coagulatory activation. Elevated risk of bloodstream infections underscores the need to exercise caution with off-label therapies

Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

BackgroundUncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates.MethodsSubanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups.ResultsInitially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016).ConclusionIn this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk