Do biomarkers of COVID-19 severity simply reflect a stress response in type 2 diabetes: Biomarker response to hypoglycemia.
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ABSTRACT:
SUBMITTER: Moin ASM
PROVIDER: S-EPMC7609242 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
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Do biomarkers of COVID-19 severity simply reflect a stress response in type 2 diabetes: Biomarker response to hypoglycemia.
Moin Abu Saleh Md ASM Al-Qaissi Ahmed A Sathyapalan Thozhukat T Atkin Stephen L SL Butler Alexandra E AE
Metabolism: clinical and experimental 20201104
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Project description:ObjectivesHypoglycemia is a common side effect of insulin therapy in type 1 and type 2 diabetes. Limited data exist on the frequency of hypoglycemic events in type 2 diabetic patients in Turkey. Our study investigated self-reported hypoglycemic events and awareness of hypoglycemia in Turkish patients with type 2 diabetes.MethodsPeople with type 2 diabetes older than 18 years of age were recruited from the two university hospital diabetes clinics. The frequency and severity of hypoglycemia and awareness of hypoglycemia during the preceding year were determinated using questionnaires by the face-to-face interview method.ResultsIn this study of 187 patients with type 2 diabetes, 83.4% had impaired awareness of their hypoglycemia, and 62% reported that they had missed some of the symptoms of hypoglycemia. Of the patients reporting hypoglycemic symptoms and severity level, 84.1% experienced mild hypoglycemia, 60% moderate, and 15.5% severe hypoglycemia in the past year. No significant association was made between hypoglycemia awareness and age, body-mass index (BMI), years of diabetes, dose of insulin, duration of insulin use, number of meals, or amount of snacking. A significant correlation was found between A1c levels and hypoglycemia awareness and severity of hypoglycemia. A significant correlation was found between dose of insulin, amount of snacking, and severity of hypoglycemia. No significant association was made between severity of hypoglycemia and age, BMI, years of diabetes, duration of insulin use, or the number of meals. However, the group with severe hypoglycemia had diabetes longer, and the average daily dose of insulin use was higher than in other groups.ConclusionsAccording to the study results, the percentage of patients with impaired awareness of hypoglycemia is high, and 62% of patients reported that they had missed some of the symptoms of hypoglycemia in type 2 diabetes. In addition, the percentage of severe hypoglycemic events is not low. Impaired awareness of hypoglycemia is a major risk factor for severe hypoglycemic events. Patients should be educated about the danger of hypoglycemia. Education should be improved, and a determined attempt should be made to eradicate the problem.
| S-EPMC5157194 | biostudies-literature
Project description:In this project, using discovery-based mass spectrometry approach and adopting data-dependent LC-MS/MS, we detected and identified modified peptides in complex clinical plasma samples and developed first-level biomarker verification strategy. Further, using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS) based targeted approach which virtually quantifies irreversible oxidation at any targeted cysteine, we quantified cysteine tri-oxidation in HSA in diabetes patients. Site-specific tri-oxidized HSA could be a potential biomarker of diabetes and provide directive of disease mechanism.
2020-05-26 | PXD012667 | Pride
Project description:IntroductionPatients with severe COVID-19 infections have coagulation abnormalities indicative of a hypercoagulable state, with thromboembolic complications and increased mortality. Platelets are recognized as mediators of inflammation, releasing proinflammatory and prothrombotic factors, and are hyperactivated in COVID-19 infected patients. Activated platelets have also been reported in type 2 diabetes (T2D) patients, putting these patients at higher risk for thromboembolic complications of COVID-19 infection.MethodsA case-control study of T2D (n=33) and control subjects (n=30) who underwent a hyperinsulinemic clamp to induce normoglycemia in T2D subjects: T2D: baseline glucose 7.5 ± 0.3mmol/l (135.1 ± 5.4mg/dl), reduced to 4.5 ± 0.07mmol/l (81 ± 1.2mg/dl) with 1-hour clamp; Controls: maintained at 5.1 ± 0.1mmol/l (91.9 ± 1.8mg/dl). Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement was used to determine a panel of platelet proteins.ResultsProthrombotic platelet proteins were elevated in T2D versus controls: platelet factor 4 (PF4, p<0.05); platelet glycoprotein VI (PGVI p<0.05); P-selectin (p<0.01) and plasminogen activator inhibitor I (PAI-1, p<0.01). In addition, the antithrombotic platelet-related proteins, plasmin (p<0.05) and heparin cofactor II (HCFII, p<0.05), were increased in T2D. Normalization of glucose in the T2D cohort had no effect on platelet protein levels.ConclusionT2D patients have platelet hyperactivation, placing them at higher risk for thromboembolic events. When infected with COVID-19, this risk may be compounded, and their propensity for a more severe COVID-19 disease course increased.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03102801, identifier NCT03102801.
| S-EPMC8043308 | biostudies-literature
Project description:Asprosin is a counter-regulatory hormone to insulin which plays a role in fasting. It may therefore also play a role in hypoglycaemia unawareness, which has been subsequently examined in this pilot study. Intravenous glucose tolerance test was used to induce controlled hyperglycemia whereas a hyperinsulinemic clamp test was used to induce a controlled hypoglycaemia in 15 patients with diabetes type 1, with and without hypoglycaemia unawareness. Changes in asprosin plasma levels did not differ between patients with and without hypoglycaemia unawareness. However, nine patients with insulin resistance as well as higher liver stiffness values and low-density lipoprotein but lower high-density lipoprotein levels did not show the expected increase in asprosin plasma levels during hypoglycemia. Therefore, insulin resistance and alterations in liver structure, most likely early stages of non-alcoholic fatty liver disease, seem to be relevant in type 1 diabetes and do not only lead to elevated plasma levels of asprosin, but also to a blunted asprosin response in hypoglycemia.
| S-EPMC6752946 | biostudies-literature
Project description:BackgroundAmong nondiabetic individuals, mild glucose decrements alter brain activity in regions linked to reward, motivation, and executive control. Whether these effects differ in type 1 diabetes mellitus (T1DM) patients with and without hypoglycemia awareness remains unclear.MethodsForty-two individuals (13 healthy control [HC] subjects, 16 T1DM individuals with hypoglycemia awareness [T1DM-Aware], and 13 T1DM individuals with hypoglycemia unawareness [T1DM-Unaware]) underwent blood oxygen level-dependent functional MRI brain imaging during a 2-step hyperinsulinemic euglycemic (90 mg/dl)-hypoglycemic (60 mg/dl) clamp for assessment of neural responses to mild hypoglycemia.ResultsMild hypoglycemia in HC subjects altered activity in the caudate, insula, prefrontal cortex, and angular gyrus, whereas T1DM-Aware subjects showed no caudate and insula changes, but showed altered activation patterns in the prefrontal cortex and angular gyrus. Most strikingly, in direct contrast to HC and T1DM-Aware subjects, T1DM-Unaware subjects failed to show any hypoglycemia-induced changes in brain activity. These findings were also associated with blunted hormonal counterregulatory responses and hypoglycemia symptom scores during mild hypoglycemia.ConclusionIn T1DM, and in particular T1DM-Unaware patients, there is a progressive blunting of brain responses in cortico-striatal and fronto-parietal neurocircuits in response to mild-moderate hypoglycemia. These findings have implications for understanding why individuals with impaired hypoglycemia awareness fail to respond appropriately to falling blood glucose levels.FundingThis study was supported in part by NIH grants R01DK020495, P30 DK045735, K23DK109284, K08AA023545. The Yale Center for Clinical Investigation is supported by an NIH Clinical Translational Science Award (UL1 RR024139).
| S-EPMC5873861 | biostudies-literature
Project description:IntroductionImmune system activation is involved in Huntington's disease (HD) pathogenesis and biomarkers for this process could be relevant to study the disease and characterise the therapeutic response to specific interventions. We aimed to study inflammatory cytokines and microglial markers in the CSF of HD patients.MethodsCSF TNF-α, IL-1β, IL-6, IL-8, YKL-40, chitotriosidase, total tau and neurofilament light chain (NFL) from 23 mutation carriers and 14 healthy controls were assayed.ResultsCSF TNF-α and IL-1β were below the limit of detection. Mutation carriers had higher YKL-40 (p = 0.003), chitotriosidase (p = 0.015) and IL-6 (p = 0.041) than controls. YKL-40 significantly correlated with disease stage (p = 0.007), UHDRS total functional capacity score (r = -0.46, p = 0.016), and UHDRS total motor score (r = 0.59, p = 4.5*10-4) after adjustment for age.ConclusionYKL-40 levels in CSF may, after further study, come to have a role as biomarkers for some aspects of HD. Further investigation is needed to support our exploratory findings.
| S-EPMC5033331 | biostudies-literature
Project description:ObjectiveTo assess the glucagon response to hypoglycemia and identify influencing factors in patients with type 1 diabetes compared with nondiabetic control subjects.Research design and methodsHyperinsulinemic hypoglycemic clamp studies were performed in all participants. The glucagon response to both hypoglycemia and arginine was measured, as well as epinephrine, cortisol, and growth hormone responses to hypoglycemia. Residual ?-cell function was assessed using fasting and stimulated C-peptide.ResultsTwenty-eight nonobese adolescents with type 1 diabetes (14 female, mean age 14.9 years [range 11.2-19.8]) and 12 healthy control subjects (6 female, 15.3 years [12.8-18.7]) participated in the study. Median duration of type 1 diabetes was 0.66 years (range 0.01-9.9). The glucagon peak to arginine stimulation was similar between groups (P = 0.27). In contrast, the glucagon peak to hypoglycemia was reduced in the group with diabetes (95% CI): 68 (62-74) vs. 96 (87-115) pg/mL (P < 0.001). This response was greater than 3 SDs from baseline for only 7% of subjects with type 1 diabetes in comparison with 83% of control subjects and was lost at a median duration of diabetes of 8 months and as early as 1 month after diagnosis (R = -0.41, P < 0.01). There was no correlation in response with height, weight, BMI, and HbA(1c). Epinephrine, cortisol, and growth hormone responses to hypoglycemia were present in both groups.ConclusionsThe glucagon response to hypoglycemia in adolescents with type 1 diabetes is influenced by the duration of diabetes and can be lost early in the course of the disease.
| S-EPMC3402257 | biostudies-literature
Project description:IntroductionTo evaluate in an Italian real-world setting the safety and effectiveness of insulin degludec 100 units/mL, given once daily in patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) after switching from other basal insulins.MethodsReFLeCT was a multicenter, prospective, observational study conducted across seven European countries which involved adult patients whose physician planned to switch their medication from basal insulin to insulin degludec. The primary outcome was the change in the number of hypoglycemic episodes before and after the switch to insulin degludec. Results are expressed as 12-month follow-up/baseline incidence rate ratios (IRRs) with 95% confidence intervals (95% CIs).ResultsThe Italian cohort of the ReFLect study comprised 148 patients with T1DM and 311 patients with T2DM. In patients with T1DM, the switch to insulin degludec was associated with significantly lower rates of overall (IRR 0.69, 95% CI 0.57-0.82), non-severe (IRR 0.72, 95% CI 0.60-0.85), and nocturnal hypoglycemia (IRR 0.46, 95% CI 0.31-0.69). Following the switch, hemoglobin A1c (HbA1c) levels decreased significantly by 0.35% (95% CI - 0.50 to - 0.20), with no significant changes in fasting plasma glucose (FPG) and basal insulin dose. Body weight increased by 0.83 kg (95% CI 0.16-1.50). In patients with T2DM, significant reductions in the rates of overall (IRR 0.40, 95% CI 0.29-0.55), non-severe (IRR 0.47, 95% CI 0.34-0.63), and nocturnal hypoglycemia (IRR 0.27, 95% CI 0.09-0.86) were documented. HbA1c and FPG decreased significantly by 0.45% (95% CI - 0.58 to - 0.31) and 0.90 mmol/L (95% CI - 1.21 to - 0.59], respectively, with no significant changes in basal insulin dose or body weight. Treatment satisfaction significantly improved in both diabetes types.ConclusionIn Italian routine clinical practice, switching from other basal insulins to insulin degludec reduced the total episodes of hypoglycemia and improved glycemic control and treatment satisfaction in patients with T1DM and T2DM.Trial registrationClinicalTrials.gov NCT02392117.
| S-EPMC7644665 | biostudies-literature
Project description:Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r=0.56, p<0.0001, r=0.08 p=0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16-1.53) and 0.87 (0.76-0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease.
| S-EPMC5881904 | biostudies-literature
Project description:BackgroundDiabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occur because of a variety of causes, such as taking additional doses of insulin, skipping meals, or overexercising. Mainly, the symptoms of hypoglycemia range from mild dysphoria to more severe conditions, if not detected in a timely manner.ObjectiveIn this review, we aimed to report on innovative detection techniques and tactics for identifying and preventing hypoglycemic episodes, focusing on T1D.MethodsA systematic literature search following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed focusing on the PubMed, GoogleScholar, IEEEXplore, and ACM Digital Library to find articles on technologies related to hypoglycemia detection in patients with T1D.ResultsThe presented approaches have been used or devised to enhance blood glucose monitoring and boost its efficacy in forecasting future glucose levels, which could aid the prediction of future episodes of hypoglycemia. We detected 19 predictive models for hypoglycemia, specifically on T1D, using a wide range of algorithmic methodologies, spanning from statistics (1.9/19, 10%) to machine learning (9.88/19, 52%) and deep learning (7.22/19, 38%). The algorithms used most were the Kalman filtering and classification models (support vector machine, k-nearest neighbors, and random forests). The performance of the predictive models was found to be satisfactory overall, reaching accuracies between 70% and 99%, which proves that such technologies are capable of facilitating the prediction of T1D hypoglycemia.ConclusionsIt is evident that continuous glucose monitoring can improve glucose control in diabetes; however, predictive models for hypo- and hyperglycemia using only mainstream noninvasive sensors such as wristbands and smartwatches are foreseen to be the next step for mobile health in T1D. Prospective studies are required to demonstrate the value of such models in real-life mobile health interventions.
| S-EPMC9353679 | biostudies-literature