Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis.

OBJECTIVE: This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC). DESIGN: In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients. METHODS: The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes. RESULTS: Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups. CONCLUSIONS: These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.

The association between the triglyceride-glucose index and the risk of cardiovascular disease in US population aged ≤ 65 years with prediabetes or diabetes: a population-based study.

BACKGROUND: The relationship between the triglyceride-glucose (TyG) index and the risk of cardiovascular disease (CVD) in the U.S. population under 65 years of age with diabetes or prediabetes is unknown. The purpose of this study was to investigate the relationship between baseline TyG index and CVD risk in U.S. patients under 65 years of age with diabetes or prediabetes. METHODS: We used data from the 2003-2018 National Health and Nutrition Examination Survey (NHANES). Multivariate regression analysis models were constructed to explore the relationship between baseline TyG index and CVD risk. Nonlinear correlations were explored using restricted cubic splines. Subgroup analysis and interaction tests were also conducted. RESULTS: The study enrolled a total of 4340 participants with diabetes or pre-diabetes, with a mean TyG index of 9.02 ± 0.02. The overall average prevalence of CVD was 10.38%. Participants in the higher TyG quartiles showed high rates of CVD (Quartile 1: 7.35%; Quartile 2: 10.04%; Quartile 3: 10.71%; Quartile 4: 13.65%). For CVD, a possible association between the TyG index and the risk of CVD was observed. Our findings suggested a linear association between the TyG index and the risk of CVD. The results revealed a U-shaped relationship between the TyG index and both the risk of CVD (P nonlinear = 0.02583) and CHF (P nonlinear = 0.0208) in individuals with diabetes. Subgroup analysis and the interaction term indicated that there was no significant difference among different stratifications. Our study also revealed a positive association between the TyG index and comorbid MetS in the U.S. population under 65 years of age with prediabetes or diabetes. CONCLUSIONS: A higher TyG index was linked to an increased likelihood of CVD in the U.S. population aged ≤ 65 years with prediabetes and diabetes. Besides, TyG index assessment will contribute to more convenient and effective screening of high-risk individuals in patients with MetS. Future studies should explore whether interventions targeting the TyG index may improve clinical outcomes in these patients.

Evidence-based screening, clinical care and health education recommendations for Alaska Native peoples with prediabetes living in southcentral Alaska: findings from the Alaska EARTH follow-up study.

Pre-diabetes (pre-DM) is a strong predictor of diabetes (DM) over time. This study investigated how much of the recent increase in pre-DM identified among Alaska Native (AN) peoples living in urban southcentral Alaska may be due to changes in diagnostic methods. We used clinical and demographic data collected at baseline between 2004 and 2006 and at follow-up collected between 2015 and 2017 from the urban southcentral Alaska Education and Research Towards Health (EARTH) cohort. We used descriptive statistics and logistic regression to explore differences in demographic and clinical variables among the identified pre-DM groups. Of 388 participants in the follow-up study, 243 had A1c levels indicating pre-DM with only 20 demonstrating pre-DM also by fasting blood glucose (FBG). Current smoking was the sole predictor for pre-DM by A1c alone while abdominal obesity and elevated FBG-predicted pre-DM by A1c+FBG. No participants had an elevated FBG without an A1c elevation. A substantial portion of the rise in pre-DM found among urban southcentral AN peoples in the EARTH follow-up study was due to the addition of A1c testing. Pre-DM by A1c alone should be used to motivate behavioural changes that address modifiable risk factors, including smoking cessation, physical activity and weight management.

Association of prediabetes with clinical outcomes in patients with chronic coronary syndrome: a post hoc analysis of the ISCHEMIA and ISCHEMIA-CKD trials.

BACKGROUND: There is conflicting evidence whether prediabetes is associated with adverse clinical outcomes in patients with chronic coronary syndrome. We aimed to assess the effect of prediabetes in patients with chronic coronary syndrome on clinical outcomes. METHODS: This is a secondary analysis of data from the ISCHEMIA and ISCHEMIA-CKD trials, including patients with chronic coronary syndrome determined by coronary computed tomography angiography or exercise-stress testing. Participants were assigned to the normoglycemia group (HbA1c < 5.7% [< 39 mmol/mol]), prediabetes group (HbA1c 5.7-6.4% [40-47 mmol/mol]), or diabetes group (HbA1c ≥ 6.5% [≥ 48 mmol/mol]). The primary end point of this study was all-cause mortality. Secondary endpoints included major adverse cardiovascular events and composites thereof. RESULTS: Overall, the primary endpoint all-cause mortality occurred in 330 (8.4%) of 3910 patients over a median follow-up time of 3.1 years (IQR 2.1-4.1). The primary endpoint all-cause mortality occurred in 37 (5.2%) of 716 patients in the normoglycemia group, in 63 (6.9%) of 911 in the prediabetes group, and in 230 (10.1%) of 2283 in the diabetes group. In the covariate-adjusted Cox model analysis, the estimated adjusted HR (aHR) in the prediabetes group as compared with the normoglycemia group was 1.45 (95%CI, 0.95-2.20). The aHR in the diabetes group as compared with the normoglycemia group was 1.84 (95%CI, 1.29-2.65). Prediabetes, compared with normoglycemia, was associated with an increased risk of stroke (aHR, 3.44, 95%CI, 1.15-10.25). Subgroup analyses suggested an increased risk of all-cause death associated with prediabetes in males and patients under 65 years. CONCLUSIONS: In patients with chronic coronary syndrome, diabetes but not prediabetes was associated with significantly increased risk of all-cause death within a median follow-up period of 3.1 years. Trial Registration NCT01471522, BioLINCC ID 13936.

Do WHO criteria for gestational diabetes fit a rural population in Tanzania? - A follow-up study assessing mother and child health six years after a pregnancy diagnosed with gestational diabetes.

AIMS AND METHODS: In low- and middle- income countries (LMICs) consequences of gestational diabetes (GDM) is understudied. Using a prospective cohort of mothers (n = 197)and children (n = 251), from rural north-eastern Tanzania, we assessed prediabetes and type 2 diabetes (T2D) prevalence six years after a pregnancy with/without GDM. RESULTS: The prevalence of prediabetes (49.4 % vs. 46.4 %) orT2D (20.0 % vs. 16.1 %), p ≥ 0.36, based on fasting plasma glucose (FPG) or HbA1clevels (prediabetes: 16.9 % vs. 13.8 % and T2D 1.2 % vs. 0 %, p = 0.47), andcardio-metabolic health parameters,weresimilar between women with/without previous GDM. These results were supported by similar perinatal outcomes and child health at follow-up.The overall prevalence ofprediabetes/T2D was high, but no differences in other cardio-metabolic risk markers were observed in women with prediabetes/T2D compared to women with normal glucose tolerance. CONCLUSIONS: Despite high prevalence of GDM amongTanzanian women, the diagnosis was not associated with adverse pregnancy outcomes, nor with increased risk of prediabetes or T2D at follow-up. FPG and HbA1c may be poor markers for diabetes in this population, and further follow-up studies with longer time intervals are warranted to evaluate which GDM diagnostic criteria are most optimal for women in rural Tanzania and similar LMIC settings.

Reframing prediabetes: A call for better risk stratification and intervention.

Prediabetes is an intermediate state of glucose homeostasis whereby plasma glucose concentrations are above normal but below the threshold of diagnosis for diabetes. Over the last several decades, criteria for prediabetes have changed as the cut points for normal glucose concentration and diagnosis of diabetes have shifted. Global consensus does not exist for prediabetes criteria; as a result, the clinical course and risk for type 2 diabetes vary. At present, we can identify individuals with prediabetes based on three glycemic tests (hemoglobin A1c, fasting plasma glucose, and 2-h plasma glucose during an oral glucose tolerance test). The majority of individuals diagnosed with prediabetes meet only one of these criteria. Meeting one, two, or all glycemic criteria changes risk for type 2 diabetes, but this information is not widely known and does not currently guide intervention strategies for individuals with prediabetes. This review summarizes current epidemiology, prognosis, and intervention strategies for individuals diagnosed with prediabetes and suggests a call for more precise risk stratification of individuals with prediabetes as elevated (one prediabetes criterion), high risk (two prediabetes criteria), and very high risk (three prediabetes criteria). In addition, the roles of oral glucose tolerance testing and continuous glucose monitoring in the diagnostic criteria for prediabetes need reassessment. Finally, we must reframe our goals for prediabetes and prioritize intensive interventions for those at high and very high risk for type 2 diabetes.

Continuous glucose monitoring and intrapersonal variability in fasting glucose.

Plasma fasting glucose (FG) levels play a pivotal role in the diagnosis of prediabetes and diabetes worldwide. Here we investigated FG values using continuous glucose monitoring (CGM) devices in nondiabetic adults aged 40-70 years. FG was measured during 59,565 morning windows of 8,315 individuals (7.16 ± 3.17 days per participant). Mean FG was 96.2 ± 12.87 mg dl-1, rising by 0.234 mg dl-1 per year with age. Intraperson, day-to-day variability expressed as FG standard deviation was 7.52 ± 4.31 mg dl-1. As there are currently no CGM-based criteria for diabetes diagnosis, we analyzed the potential implications of this variability on the classification of glycemic status based on current plasma FG-based diagnostic guidelines. Among 5,328 individuals who would have been considered to have normal FG based on the first FG measurement, 40% and 3% would have been reclassified as having glucose in the prediabetes and diabetes ranges, respectively, based on sequential measurements throughout the study. Finally, we revealed associations between mean FG and various clinical measures. Our findings suggest that careful consideration is necessary when interpreting FG as substantial intraperson variability exists and highlight the potential impact of using CGM data to refine glycemic status assessment.

Prediabetes and major adverse cardiac events after acute coronary syndrome: An overestimated concept.

BACKGROUND: Unlike diabetes, the effect of prediabetes on outcomes in patients with acute coronary syndrome (ACS) who underwent percutaneous coronary intervention (PCI) is not much investigated. We investigated the association between fasting glycemic status and major adverse cardiovascular and cerebrovascular events (MACCE) in patients with ACS undergoing PCI and had mid to long-term follow-up after coronary stenting. METHODS: Registry-based retrospective cohort study included ACS patients who underwent PCI at the Tehran Heart Center from 2015 to 2021 with a median follow-up of 378 days. Patients were allocated into normoglycemic, prediabetic, and diabetic groups. The primary and secondary outcomes were MACCE and its components, respectively. Unadjusted and adjusted Cox models were used to evaluate the association between glycemic status and outcomes. RESULTS: Among 13 682 patients, 3151 (23%) were prediabetic, and 5834 (42.6%) were diabetic. MACCE risk was significantly higher for diabetic versus normoglycemic (adjusted hazard ratio [aHR]: 1.22, 95% confidence interval [CI]: 1.06-1.41), but nonsignificantly higher for prediabetic versus normoglycemic (aHR: 0.95, 95% CI: 0.78-1.10). All-cause mortality risk was significantly higher in diabetic versus normoglycemic (aHR: 1.42, 95% CI: 1.08-1.86), but nonsignificantly higher for prediabetic versus normoglycemic (aHR: 1.15, 95% CI: 0.84-1.59). Among other components of MACCE, only coronary artery bypass grafting was significantly higher in diabetic patients, and not prediabetic, compared with normoglycemic. CONCLUSIONS: Prediabetic ACS patients undergoing PCI, unlike diabetics, are not at increased risk of MACCE and all-cause mortality. While prediabetic patients could be regarded as having the same risk as nondiabetics, careful consideration to provide more intensive pre- and post-PCI care in diabetic patients is mandatory.

Liraglutide and not lifestyle intervention reduces soluble CD163 after comparable weight loss in obese participants with prediabetes or type 2 diabetes mellitus.

BACKGROUND: The GLP-1 receptor agonist liraglutide is used to treat hyperglycemia in type 2 diabetes but is also known to induce weight loss, preserve the beta cell and reduce cardiovascular risk. The mechanisms underlying these effects are however still not completely known. Herein we explore the effect of liraglutide on markers of immune cell activity in a population of obese individuals with prediabetes or newly diagnosed type 2 diabetes mellitus. METHOD: Plasma levels of the monocyte/macrophage markers, soluble (s)CD163 and sCD14, the neutrophil markers myeloperoxidase (MPO) and neutrophil gelatinase-associated lipocalin (NGAL),the T-cell markers sCD25 and T-cell immunoglobulin mucin domain-3 (sTIM-3) and the inflammatory marker TNF superfamily (TNFSF) member 14 (LIGHT/TNFSF14) were measured by enzyme-linked immunosorbent assays in obese individuals with prediabetes or diabetes diagnosed within the last 12 months, prior to and after comparable weight loss achieved with lifestyle changes (n = 20) or liraglutide treatment (n = 20), and in healthy subjects (n = 13). RESULTS: At baseline, plasma levels of the macrophage marker sCD163, and the inflammatory marker LIGHT were higher in cases as compared to controls. Plasma levels of sCD14, NGAL, sTIM-3 and sCD25 did not differ at baseline between patients and controls. After weight reduction following lifestyle intervention or liraglutide treatment, sCD163 decreased significantly in the liraglutide group vs. lifestyle (between-group difference p = 0.023, adjusted for visceral adipose tissue and triglycerides basal values). MPO and LIGHT decreased significantly only in the liraglutide group (between group difference not significant). Plasma levels of MPO and in particular sCD163 correlated with markers of metabolic dysfunction and inflammation. After weight loss, only sCD163 showed a trend for decreased levels during OGTT, both in the whole cohort as in those of liraglutide vs lifestyle group. CONCLUSION: Weight loss following treatment with liraglutide was associated with reduced circulating levels of sCD163 when compared to the same extent of weight loss after lifestyle changes. This might contribute to reduced cardiometabolic risk in individuals receiving treatment with liraglutide.

Frail hypertensive older adults with prediabetes and chronic kidney disease: insights on organ damage and cognitive performance - preliminary results from the CARYATID study.

BACKGROUND: Hypertension and chronic kidney disease (CKD) pose significant public health challenges, sharing intertwined pathophysiological mechanisms. Prediabetes is recognized as a precursor to diabetes and is often accompanied by cardiovascular comorbidities such as hypertension, elevating the risk of pre-frailty and frailty. Albuminuria is a hallmark of organ damage in hypertension amplifying the risk of pre-frailty, frailty, and cognitive decline in older adults. We explored the association between albuminuria and cognitive impairment in frail older adults with prediabetes and CKD, assessing cognitive levels based on estimated glomerular filtration rate (eGFR). METHODS: We conducted a study involving consecutive frail older patients with hypertension recruited from March 2021 to March 2023 at the ASL (local health unit of the Italian Ministry of Health) of Avellino, Italy, followed up after three months. Inclusion criteria comprised age over 65 years, prior diagnosis of hypertension without secondary causes, prediabetes, frailty status, Montreal Cognitive Assessment (MoCA) score < 26, and CKD with eGFR > 15 ml/min. RESULTS: 237 patients completed the study. We examined the association between albuminuria and MoCA Score, revealing a significant inverse correlation (r: 0.8846; p < 0.0001). Subsequently, we compared MoCA Score based on eGFR, observing a significant difference (p < 0.0001). These findings were further supported by a multivariable regression analysis, with albuminuria as the dependent variable. CONCLUSIONS: Our study represents the pioneering effort to establish a significant correlation between albuminuria and eGFR with cognitive function in frail hypertensive older adults afflicted with prediabetes and CKD.

Evaluation of prediabetes patients in terms of metabolic syndrome.

OBJECTIVE: Prediabetes accompanied by metabolic syndrome accelerates the process leading to diabetes and causes an increase in complications. The current study aimed to investigate the clinical conditions accompanying prediabetes and the effect of the association of metabolic syndrome on clinical outcomes in prediabetics. SUBJECTS AND METHODS: This cross-sectional study was conducted with 88 prediabetic individuals between November 2022 and January 2023. Prediabetes was diagnosed using the American Diabetes Association (ADA) criteria, and metabolic syndrome was diagnosed using the International Diabetes Federation criteria. Clinical history, physical examination and laboratory tests of the participants were recorded. RESULTS: Metabolic syndrome (MetS) was present in 69 of 88 prediabetic patients included in the study (78.4%). Hypertension (p=0.019), abdominal obesity (p<0.001), low-density lipoprotein (LDL) elevation (p=0.006), and dyslipidemia (p=0.020) were detected more frequently in prediabetic individuals accompanied by MetS. Median values of waist circumference (p=0.020), systolic blood pressure (p=0.021), triglyceride (p<0.001), LDL (p=0.003) and postprandial blood sugar (p=0.049) in prediabetics accompanied by MetS were statistically significant. It was higher than those without MetS. The median Vit-D level of prediabetics without MetS was higher than those with MetS (p=0.049). The median creatinine value of prediabetics without MetS was higher than that of prediabetics with MetS (p=0.049). CONCLUSIONS: Hypertension, dyslipidemia, abdominal obesity, and metabolic obesity increased in the coexistence of prediabetes and MetS. At the same time, the coexistence of prediabetes and MetS was associated with higher systolic blood pressure, postprandial blood sugar, and LDL levels. Prediabetic individuals accompanied by MetS are at greater metabolic risk.

Undiagnosed type 2 diabetes is common - intensified screening of established risk groups is imperative in Sweden: the SDPP cohort.

BACKGROUND: Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection. METHODS: We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D. RESULTS: At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare. CONCLUSIONS: Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.

Recalibration of a Non-Laboratory-Based Risk Model to Estimate Pre-Diabetes/Diabetes Mellitus Risk in Primary Care in Hong Kong.

INTRODUCTION/OBJECTIVES: A non-laboratory-based pre-diabetes/diabetes mellitus (pre-DM/DM) risk prediction model developed from the Hong Kong Chinese population showed good external discrimination in a primary care (PC) population, but the estimated risk level was significantly lower than the observed incidence, indicating poor calibration. This study explored whether recalibrating/updating methods could improve the model's accuracy in estimating individuals' risks in PC. METHODS: We performed a secondary analysis on the model's predictors and blood test results of 919 Chinese adults with no prior DM diagnosis recruited from PC clinics from April 2021 to January 2022 in HK. The dataset was randomly split in half into a training set and a test set. The model was recalibrated/updated based on a seven-step methodology, including model recalibrating, revising and extending methods. The primary outcome was the calibration of the recalibrated/updated models, indicated by calibration plots. The models' discrimination, indicated by the area under the receiver operating characteristic curves (AUC-ROC), was also evaluated. RESULTS: Recalibrating the model's regression constant, with no change to the predictors' coefficients, improved the model's accuracy (calibration plot intercept: -0.01, slope: 0.69). More extensive methods could not improve any further. All recalibrated/updated models had similar AUC-ROCs to the original model. CONCLUSION: The simple recalibration method can adapt the HK Chinese pre-DM/DM model to PC populations with different pre-test probabilities. The recalibrated model can be used as a first-step screening tool and as a measure to monitor changes in pre-DM/DM risks over time or after interventions.

Sex-specific differences in myocardial glucose metabolic rate in non-diabetic, pre-diabetic and type 2 diabetic subjects.

BACKGROUND: Evidence has shown that women with type 2 diabetes (T2DM) have a higher excess risk for cardiovascular disease (CVD) than men with T2DM. Subjects with either T2DM or prediabetes exhibit myocardial insulin resistance, but it is still unsettled whether sex-related differences in myocardial insulin resistance occur in diabetic and prediabetic subjects. METHODS: We aimed to evaluate sex-related differences in myocardial glucose metabolic rate (MRGlu), assessed using dynamic PET with 18F-FDG combined with euglycemic-hyperinsulinemic clamp, in subjects with normal glucose tolerance (NGT; n = 20), prediabetes (n = 11), and T2DM (n = 26). RESULTS: Women with prediabetes or T2DM exhibited greater relative differences in myocardial MRGlu than men with prediabetes or T2DM when compared with their NGT counterparts. As compared with women with NGT, those with prediabetes exhibited an age-adjusted 35% lower myocardial MRGlu value (P = 0.04) and women with T2DM a 74% lower value (P = 0.006), respectively. Conversely, as compared with men with NGT, men with T2DM exhibited a 40% lower myocardial MRGlu value (P = 0.004), while no significant difference was observed between men with NGT and prediabetes. The statistical test for interaction between sex and glucose tolerance on myocardial MRGlu (P < 0.0001) was significant suggesting a sex-specific association. CONCLUSIONS: Our data suggest that deterioration of glucose homeostasis in women is associated with a greater impairment in myocardial glucose metabolism as compared with men. The sex-specific myocardial insulin resistance could be an important factor responsible for the greater effect of T2DM on the excess risk of cardiovascular disease in women than in men.

Is pre-diabetes a predictor of events in patients with atrial fibrillation?

BACKGROUND: Diabetes mellitus (DM) increases the probability of presenting atrial fibrillation (AF) and it is a predictor of its ischemic stroke. There is limited information of the association between glycated hemoglobin (HbA1c) levels and ischemic, embolic or bleeding events in patients with pre-DM and AF. METHODS: To investigate whether the presence of pre-DM in patients with AF predicts ischemic or bleeding events, myocardial infarction or mortality, we performed a retrospective study with a final cohort of 2993 non-diabetic patients with AF and data of glycated hemoglobin (HbA1c). We divided the cohort in two groups: those with normal glucose (n = 1351) and those with pre-diabetes (n = 1642). Incidence rates were calculated as the number of events per 100 person-years and were then compared between groups. Competitive hazard regression analysis for non-fatal events(death as the competing event) and conventional Cox regression for mortality were performed. RESULTS: There was not difference between groups for incidence rates of the different events per 100 person-years. Even considering HbA1c as continuous variable, the unadjusted analysis showed no relation between levels of HbA1c and more risk of events. This association remained not significant after adjustment for CHA2DS2-VASc score, HAS-BLED score and anticoagulation therapy. CONCLUSION: In this study of 2993 non-diabetic patients with new-onset AF, we have not found an association between HbA1c and worse prognosis when it is in the range of pre-diabetes.

Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics.

BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics. MATERIALS AND METHODS: The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules. RESULTS: Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively. CONCLUSION: We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.

An interpretable predictive deep learning platform for pediatric metabolic diseases.

OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the development of these long-term complications. MATERIALS AND METHODS: No clinically available tools are currently in widespread use that can predict the onset of metabolic diseases in pediatric patients. Here, we use interpretable deep learning, leveraging longitudinal clinical measurements, demographical data, and diagnosis codes from electronic health record data from a large integrated health system to predict the onset of prediabetes, type 2 diabetes (T2D), and metabolic syndrome in pediatric cohorts. RESULTS: The cohort included 49 517 children with overweight or obesity aged 2-18 (54.9% male, 73% Caucasian), with a median follow-up time of 7.5 years and mean body mass index (BMI) percentile of 88.6%. Our model demonstrated area under receiver operating characteristic curve (AUC) accuracies up to 0.87, 0.79, and 0.79 for predicting T2D, metabolic syndrome, and prediabetes, respectively. Whereas most risk calculators use only recently available data, incorporating longitudinal data improved AUCs by 13.04%, 11.48%, and 11.67% for T2D, syndrome, and prediabetes, respectively, versus models using the most recent BMI (P < 2.2 × 10-16). DISCUSSION: Despite most risk calculators using only the most recent data, incorporating longitudinal data improved the model accuracies because utilizing trajectories provides a more comprehensive characterization of the patient's health history. Our interpretable model indicated that BMI trajectories were consistently identified as one of the most influential features for prediction, highlighting the advantages of incorporating longitudinal data when available.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus.

BACKGROUND: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state. METHODS: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D. RESULTS: A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D. CONCLUSIONS: Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study.

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70-110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Knowledge, attitude, and practice of pre-diabetic older people regarding pre-diabetes.

BACKGROUND: One of the risk factors of diabetes is the pre-diabetes stage which is significantly prevalent in older people. Knowledge, attitude, and practice of the pre-diabetic stage are of great importance and can decrease complications. The present study aimed to determine the knowledge, attitude, and practice of the pre-diabetic older people. METHODS: This cross-sectional study was conducted from April 2022 to August 2022 on 219 pre-diabetic older people referring to Sina Hospital in Tabriz, one of the most populated cities in the northwest of Iran. Data were collected using questionnaires of Knowledge, Attitude, Practice-Prediabetes Assessment Questionnaire (KAP-PAQ). The data were analyzed by SPSS 21. RESULTS: The mean scores of knowledge (in the range of 0-17), attitude (in the range of -10, + 10), and practice (in the range of 0-26) were 1.72 ± 1.0, 2.24 ± 1.92, and 5.76 ± 2.61, respectively. The older people's knowledge and practice levels in the pre-diabetes stage were low and about 50% of them had negative views. According to the Spearman correlation test, there was a positive significant relationship between the older people's knowledge and practice (p < 0.001, r = 0.234). CONCLUSIONS: The older people in the pre-diabetes stage had low knowledge and attitude and a negative viewpoint towards correcting lifestyle on diet, exercising and physical activity, weight control, diagnostic and screening methods. Increased knowledge about pre-diabetes and strengthened positive attitude towards correcting lifestyle through counseling as well as empowering the pre-diabetic older people can increase the efficiency of pre-diabetes prevention and control programs and prevent its progression to the diabetes stage.