Risk Of Diabetes In Individuals Research Articles

Higher risk of incident diabetes among patients with primary hyperparathyroidism.

There is relatively scarce data regarding the association between primary hyperparathyroidism (PHPT) and incident diabetes in large population-based longitudinal studies. We aimed to evaluate the risk of incident diabetes in individuals with and without PHPT and investigate the association between serum calcium concentrations and the risk of incident diabetes in patients with PHPT. We included 2749 PHPT patients and 13,745 age, sex and index year matched non-PHPT individuals during 2000-2019. We used Cox regression models to compare the risk of incident diabetes in individuals with and without PHPT, and the risk of incident diabetes in PHPT patients with serum calcium concentration above and below the median value. The association between serum calcium concentrations and the risk of incident diabetes was examined by restricted cubic spline analyses in patients with PHPT. During a median follow-up time of 5.17 years (IQR 2.17, 9.58), 433 patients (15.75%) with PHPT and 2110 individuals (15.35%) without PHPT developed diabetes, respectively. Patients with PHPT had a higher incidence rate of diabetes compared to non-PHPT individuals (27.60 [95% CI 25.00, 30.30] vs. 23.90 [95% CI 22.80, 24.90] per 1000 person-years, log-rank test p = .007]. Crude Cox regression model showed PHPT was associated with a 15% higher risk of incident diabetes (HR 1.15, 95%CI 1.04, 1.28). In patients with PHPT, a 44% higher risk of incident diabetes was found in patients with serum calcium concentrations above the median value (2.63 mmol/L), compared to those below the median value (HR 1.44, 95%CI 1.08, 1.90). Restricted cubic spline analyses confirmed a positive linear association between serum calcium concentrations and the risk of incident diabetes in those with PHPT (p-value for nonlinear = .751) CONCLUSIONS: Patients with PHPT had a higher risk of incident diabetes compared to non-PHPT individuals. A positive linear association was found between serum calcium concentrations and the risk of incident diabetes in patients with PHPT.

391 Value estimation of the Diabetes Prevention Program: How well does clinical trial-based cost-effectiveness apply to the real world?

OBJECTIVES/GOALS: Many economic evaluations rely on clinical trial data that may not represent real world populations and intervention effectiveness. We compare risk and cost-effectiveness for the Diabetes Prevention Program (DPP) clinical trial cohort and a real world population eligible for the national DPP to assess the impact of using real world data. METHODS/STUDY POPULATION: To produce real world (US population) representative results, we identified National Health and Nutrition Examination Survey (NHANES) subjects eligible for the national DPP and adjusted projections using survey weights. We used clinical predictive models to estimate individual diabetes risk, and microsimulation to estimate lifetime costs, benefits, and net monetary benefits (NMB) for lifestyle intervention and metformin. We compared results across the DPP clinical trial and NHANES populations. RESULTS/ANTICIPATED RESULTS: Three-year risk of diabetes onset for the DPP trial population (mean of 19.7%, median of 10.3%) exceeded corresponding risk for the NHANES population (mean of 14.6%, median of 4.8%). The proportion of individuals with a three-year diabetes risk < 10% for the DPP trial population (49%) was less than the corresponding proportion for NHANES (67%). Mean NMB for metformin for the DPP trial population ($9,749) exceeded the corresponding value for NHANES ($5,391). The proportion of subjects with negative NMB was 49% for the DPP trial population and 67% for NHANES. Lifestyle intervention had a mean NMB of $34,889 for the DPP trial population and $28,652 for NHANES. Only 20% of the NHANES population eligible for national DPP met inclusion/exclusion criteria for the DPP trial. DISCUSSION/SIGNIFICANCE: Real world populations eligible for the national DPP include a greater proportion of low-risk individuals, and for these people, prevention programs may confer smaller benefits. Technology assessments based on clinical trial data should be revised using real world population and treatment effect data.

Metabolically healthy obese individuals are still at high risk for diabetes: Application of the marginal structural model.

To assess the effect of obesity phenotype on the incidence of diabetes, considering phenotype as a time-varying exposure. We used community-based cohort data from the Korean Genome and Epidemiology Study, with a 16-year follow-up period. Obesity phenotype was determined using body mass index and metabolic syndrome criteria. The influence of obesity phenotype on the occurrence of diabetes was evaluated using a Cox proportional hazard model and a marginal structural model (MSM). Obesity phenotypes were defined in 6265 individuals, with diabetes identified in 903 (14.4%) during the follow-up period. Individuals with metabolically healthy obesity (MHO) exhibited a higher risk of diabetes compared to those with metabolically healthy normal weight (MHNW), with a hazard ratio (HR) of 1.48 (95% confidence interval [CI] 1.15-1.90). This association remained significant after applying the MSM (HR 1.49, 95% CI 1.01-2.20). Moreover, various sensitivity analyses consistently demonstrated a higher risk of diabetes in individuals with MHO compared to those with MHNW. Even when obesity phenotype was treated as a time-varying exposure, individuals with MHO were still at higher risk for developing diabetes than those with MHNW. Consequently, such individuals should aim to avoid transitioning to a metabolically unfavourable state and strive to reduce their body weight to a normal range.

Association of Spousal Diabetes Status and Ideal Cardiovascular Health Metrics With Risk of Incident Diabetes Among Chinese Adults

ImportanceSpouses share common socioeconomic, environmental, and lifestyle factors, and multiple studies have found that spousal diabetes status was associated with diabetes prevalence. But the association of spousal diabetes status and ideal cardiovascular health metrics (ICVHMs) assessed by the American Heart Association’s Life’s Essential 8 measures with incident diabetes has not been comprehensively characterized, especially in large-scale cohort studies.ObjectiveTo explore the association of spousal diabetes status and cardiovascular health metrics with risk of incident diabetes in Chinese adults.Design, Setting, and ParticipantsThis cohort study included individuals in the China Cardiovascular Disease and Cancer Cohort without diabetes who underwent baseline and follow-up glucose measurements and had spouses with baseline glucose measurements. The data were collected in January 2011 to December 2012 and March 2014 to December 2016. The spousal study had a mean (SD) follow-up of 3.6 (0.9) years (median [IQR], 3.2 [2.9-4.5] years). Statistical analysis was performed from July to November 2022.ExposureSpousal diabetes status was diagnosed according to the 2010 American Diabetes Association (ADA) criteria. All participants provided detailed clinical, sociodemographic, and lifestyle information included in cardiovascular health metrics.Main Outcomes and MeasuresIncident diabetes, diagnosed according to 2010 ADA criteria.ResultsOverall, 34 821 individuals were included, with a mean (SD) age of 56.4 (8.3) years and 16 699 (48.0%) male participants. Spousal diabetes diagnosis was associated with an increased risk of incident diabetes (hazard ratio [HR], 1.15; 95% CI, 1.03-1.30). Furthermore, participants whose spouses had uncontrolled glycated hemoglobin (HbA1c) had a higher risk of diabetes (HR, 1.20; 95% CI, 1.04-1.39) but the risk of diabetes in participants whose spouses had controlled HbA1c did not increase significantly (HR, 1.10; 95% CI, 0.92-1.30). Moreover, this association varied with composite cardiovascular health status. Diabetes risk in individuals who had poor cardiovascular health status (<4 ICVHMs) was associated with spousal diabetes status (3 ICVHMs: HR, 1.50; 95% CI, 1.15-1.97), while diabetes risk in individuals who had intermediate to ideal cardiovascular health status (≥4 ICVHMs) was not associated with it (4 ICVHMs: HR, 1.01; 95% CI, 0.69-1.50).Conclusions and RelevanceIn this study, spousal diabetes diagnosis with uncontrolled HbA1c level was associated with increased risk of incident diabetes, but strict management of spousal HbA1c level and improving ICVHM profiles may attenuate the association of spousal diabetes status with diabetes risk. These findings suggest the potential benefit of couple-based lifestyle or pharmaceutical interventions for diabetes.

Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response

Aims/hypothesisAlthough insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the probability of successful prevention and intervention. Moreover, treatment efficacy is affected by the genetics of the individual. We used gene expression profiles from a cross-sectional study to identify potential candidate genes for the prediction of diabetes risk and intervention response.MethodsUsing a multivariate regression model, we linked gene expression profiles of human skeletal muscle and intermuscular adipose tissue (IMAT) to fasting glucose levels and glucose infusion rate. Based on the expression patterns of the top predictive genes, we characterised and compared individual gene expression with clinical classifications using k-nearest neighbour clustering. The predictive potential of the candidate genes identified was validated using muscle gene expression data from a longitudinal intervention study.ResultsWe found that genes with a strong association with clinical measures clustered into three distinct expression patterns. Their predictive values for insulin resistance varied substantially between skeletal muscle and IMAT. Moreover, we discovered that individual gene expression-based classifications may differ from classifications based predominantly on clinical variables, indicating that participant stratification may be imprecise if only clinical variables are used for classification. Of the 15 top candidate genes, ST3GAL2, AASS, ARF1 and the transcription factor SIN3A are novel candidates for predicting a refined diabetes risk and intervention response.Conclusion/interpretationOur results confirm that disease progression and successful intervention depend on individual gene expression states. We anticipate that our findings may lead to a better understanding and prediction of individual diabetes risk and may help to develop individualised intervention strategies.Graphical abstract

Serum Mac-2 Binding Protein Glycosylation Isomer Concentrations Are Associated With Incidence of Type 2 Diabetes.

Serum Mac-2 binding protein glycosylation isomer (M2BPGi) concentrations are known to be an indicator of chronic liver injury and fibrosis. This study aimed to investigate the association between serum M2BPGi concentrations and the development of type 2 diabetes in a Japanese community. A total of 2143 community-dwelling Japanese individuals aged 40-79 years without diabetes at baseline were followed up for 7 years. Serum M2BPGi concentrations were divided into quintiles: Q1, ≤0.37 cutoff index (COI); Q2, 0.38-0.49 COI; Q3, 0.50-0.62 COI; Q4, 0.62-0.80 COI; and Q5, ≥0.81 COI. Cox proportional hazards models were used to estimate hazard ratios and 95% CIs for the development of type 2 diabetes. During the follow-up period, 219 individuals developed type 2 diabetes. The age- and sex-adjusted cumulative incidence of type 2 diabetes significantly increased with elevating serum M2BPGi levels (P for trend < .01). This association remained significant after adjustment for potential confounders (P for trend = .04). This significant association attenuated to a nonsignificant level after additionally adjusting for serum high-sensitivity C-reactive protein or homeostasis model assessment of insulin resistance. The present study demonstrated that higher serum M2BPGi concentrations were significantly associated with higher risk of diabetes in a Japanese community. Moreover, inflammation and insulin resistance were suggested to contribute to the excess risk of diabetes in individuals with higher serum M2BPGi levels. These findings shed light on the importance of inflammation and insulin resistance when considering the pathogenesis of diabetes.

Gestational Glucose Intolerance and Risk of Future Diabetes.

Pregnant individuals are universally screened for gestational diabetes mellitus (GDM). Gestational glucose intolerance (GGI) (an abnormal initial GDM screening test without a GDM diagnosis) is not a recognized diabetes risk factor. We tested for an association between GGI and diabetes after pregnancy. We conducted a retrospective cohort study of individuals followed for prenatal and primary care. We defined GGI as an abnormal screening glucose-loading test result at ≥24 weeks' gestation with an oral glucose tolerance test (OGTT) that did not meet GDM criteria. The primary outcome was incident diabetes. We used Cox proportional hazards models with time-varying exposures and covariates to compare incident diabetes risk in individuals with GGI and normal glucose tolerance. Among 16,836 individuals, there were 20,359 pregnancies with normal glucose tolerance, 2,943 with GGI, and 909 with GDM. Over a median of 8.4 years of follow-up, 428 individuals developed diabetes. Individuals with GGI had increased diabetes risk compared to those with normal glucose tolerance in pregnancy (adjusted hazard ratio [aHR] 2.01 [95% CI 1.54-2.62], P < 0.001). Diabetes risk increased with the number of abnormal OGTT values (zero, aHR 1.54 [1.09-2.16], P = 0.01; one, aHR 2.97 [2.07-4.27], P < 0.001; GDM, aHR 8.26 [6.49-10.51], P < 0.001 for each compared with normal glucose tolerance). The fraction of cases of diabetes 10 years after delivery attributable to GGI and GDM was 8.5% and 28.1%, respectively. GGI confers an increased risk of future diabetes. Routinely available clinical data identify an unrecognized group who may benefit from enhanced diabetes screening and prevention.

No Indices of Increased Type 2 Diabetes Risk in Individuals with Reactive Postprandial Hypoglycemia.

Reactive postprandial hypoglycemia (RPH) is an understudied condition that lacks clinical definition, knowledge of future health implications, and an understanding of precise underlying mechanisms. Therefore, our study aimed to assess the glycemic response after glucose ingestion in individuals several years after the initial evaluation of RPH and to compare glucose regulation in individuals with RPH vs. healthy volunteers. We assessed the inter- and intra-individual differences in glucose, insulin, and C-peptide concentrations during 5-h oral glucose tolerance tests (OGTTs); the surrogate markers of insulin resistance (HOMA-IR and Matsuda index); and beta-cell function (distribution index and insulinogenic index). The study included 29 subjects with RPH (all females, aged 39 (28, 46) years) and 11 sex-, age-, and body mass index (BMI)-matched controls. No biochemical deterioration of beta-cell secretory capacity and no progression to dysglycemia after 6.4 ± 4.2 years of follow-up were detected. RPH subjects were not insulin resistant, and their insulin sensitivity did not deteriorate. RPH subjects exhibited no differences in concentrations or in the shape of the glucose-insulin curves during the 5-h OGTTs compared to age- and BMI-matched controls. No increased incident type 2 diabetes risk indices were evident in individuals with RPH. This dictates the need for further research to investigate the magnitude of future diabetes risk in individuals experiencing RPH.

G protein-coupled receptor 151 regulates glucose metabolism and hepatic gluconeogenesis

Human genetics has been instrumental in identification of genetic variants linked to type 2 diabetes. Recently a rare, putative loss-of-function mutation in the orphan G-protein coupled receptor 151 (GPR151) was found to be associated with lower odds ratio for type 2 diabetes, but the mechanism behind this association has remained elusive. Here we show that Gpr151 is a fasting- and glucagon-responsive hepatic gene which regulates hepatic gluconeogenesis. Gpr151 ablation in mice leads to suppression of hepatic gluconeogenesis genes and reduced hepatic glucose production in response to pyruvate. Importantly, the restoration of hepatic Gpr151 levels in the Gpr151 knockout mice reverses the reduced hepatic glucose production. In this work, we establish a previously unknown role of Gpr151 in the liver that provides an explanation to the lowered type 2 diabetes risk in individuals with nonsynonymous mutations in GPR151.

Determining Diabetes Risk and Health Literacy Levels in Individuals Aged 45 and Above: A Descriptive Correlational Study

Purpose: The aim of this study is to determine actual and perceived diabetes risk in individuals aged ≥45 and their health literacy levels.&#x0D; Methods and Materials: The study is of descriptive, correlational design and was conducted with 82 university staff members of ages ≥45 years. Along with Finnish Diabetes Risk Score (FINDRISC), was used to collect data of the question, “Please comment on your diabetes risk?” and the Health Literacy Scale for Turkey (HLST-32).&#x0D; Results: About of twenty-six percent for the participants exhibited a high/very high actual diabetes mellitus risk. A positive and significant correlation was found between the participants’ actual and perceived risk of diabetes mellitus (r=0.771, p

Impact of applying a diabetes risk score in primary care on change in physical activity: a pragmatic cluster randomised trial

AimThere is little evidence of the impact of diabetes risk scores on individual diabetes risk factors, motivation for behaviour changes and mental health. The aim of this study was to investigate the effect of applying a noninvasive diabetes risk score in primary care as component of routine health checks on physical activity and secondary outcomes.MethodsCluster randomised trial, in which primary care physicians (PCPs), randomised (1:1) by minimisation, enrolled participants with statutory health insurance without known diabetes, ≥ 35 years of age with a body mass index ≥ 27.0 kg/m2. The German Diabetes Risk Score was applied as add-on to the standard routine health check, conducted in the controls. Primary outcome was the difference in participants’ physical activity (International Physical Activity Questionnaire) after 12 months. Secondary outcomes included body mass index, perceived health, anxiety, depression, and motivation for lifestyle change. Analysis was by intention-to-treat principle using mixed models.Results36 PCPs were randomised; remaining 30 PCPs (intervention: n = 16; control: n = 14) recruited 315 participants (intervention: n = 153; controls: n = 162). A slight increase in physical activity was observed in the intervention group with an adjusted mean change of 388 (95% confidence interval: − 235; 1011) metabolic equivalents minutes per week. There were no relevant changes in secondary outcomes.ConclusionsThe application of a noninvasive diabetes risk score alone is not effective in promoting physical activity in primary care.Clinical Trial Registration: ClinicalTrials.gov (NCT03234322, registration date: July 31, 2017).

Mediterranean diet and diabetes risk in a cohort study of individuals with prediabetes: propensity score analyses.

Randomized controlled trials have demonstrated the efficacy of several dietary patterns plus physical activity to reduce diabetes onset in people with prediabetes. However, there is no evidence on the effect from the Mediterranean diet on the progression from prediabetes to diabetes. We aimed to evaluate the effect from high adherence to Mediterranean diet on the risk of diabetes in individuals with prediabetes. Prospective cohort study in Spanish Primary Care setting. A total of 1184 participants with prediabetes based on levels of fasting plasma glucose and/or glycated hemoglobin were followed up for a mean of 4.2years. A total of 210 participants developed diabetes type 2 during the follow up. Hazard ratios of diabetes onset were estimated by Cox proportional regression models associated to high versus low/medium adherence to Mediterranean diet. Different propensity score methods were used to control for potential confounders. Incidence rate of diabetes in participants with high versus low/medium adherence to Mediterranean diet was 2.9 versus 4.8 per 100 persons-years. The hazard ratios adjusted for propensity score and by inverse probability weighting (IPW) had identical magnitude: 0.63 (95% confidence interval, 0.43-0.93). The hazard ratio in the adjusted model using propensity score matching 1:2 was 0.56 (95% confidence interval, 0.37-0.84). These propensity score analyses suggest that high adherence to Mediterranean diet reduces diabetes risk in people with prediabetes.

Machine Learning Refutes Loss of Smell as a Risk Indicator of Diabetes Mellitus.

Because it is associated with central nervous changes, and olfactory dysfunction has been reported with increased prevalence among persons with diabetes, this study addressed the question of whether the risk of developing diabetes in the next 10 years is reflected in olfactory symptoms. In a cross-sectional study, in 164 individuals seeking medical consulting for possible diabetes, olfactory function was evaluated using a standardized clinical test assessing olfactory threshold, odor discrimination, and odor identification. Metabolomics parameters were assessed via blood concentrations. The individual diabetes risk was quantified according to the validated German version of the “FINDRISK” diabetes risk score. Machine learning algorithms trained with metabolomics patterns predicted low or high diabetes risk with a balanced accuracy of 63–75%. Similarly, olfactory subtest results predicted the olfactory dysfunction category with a balanced accuracy of 85–94%, occasionally reaching 100%. However, olfactory subtest results failed to improve the prediction of diabetes risk based on metabolomics data, and metabolomics data did not improve the prediction of the olfactory dysfunction category based on olfactory subtest results. Results of the present study suggest that olfactory function is not a useful predictor of diabetes.

Effect of lifestyle intervention on the risk of incident diabetes in individuals with impaired fasting glucose and low or high genetic risk for the development of type 2 diabetes in men: a T2D-GENE trial.

PurposeGenetic and lifestyle/environmental factors as well as their interplay contribute to the pathogenesis of type 2 diabetes (T2D). Several trials have shown that lifestyle intervention is effective in the prevention of T2D, but there are no trials that have taken into account the genetic risk of the participants. The aim of our T2D-GENE trial (ClinicalTrials.gov ID: NCT02709057) is to investigate the effects of lifestyle intervention on the prevention of T2D in participants with a high genetic risk of T2D compared with participants with a low genetic risk of T2D.MethodsBoth intervention and control groups include 300 participants with low and 300 participants with high genetic risk for T2D. Genetic risk was evaluated by genetic risk score, and these two groups were matched additionally for fasting plasma glucose concentration, age, and body mass index. Corresponding control groups (300 participants each) do not have lifestyle intervention. The inclusion criteria are impaired fasting glucose at entry with or without impaired glucose tolerance, age 50–75 years, and body mass index ≥25 kg/m2. The primary outcome is incident T2D and the intervention lasts for 3 years.ConclusionIf the effects of the lifestyle intervention are independent from the genetic risk of the participants, our study will be of great importance for the entire T2D research community, health care providers, and individuals at high risk for T2D. In this case, lifestyle intervention is beneficial for all individuals at risk for developing T2D, independently of genetic risk.ClinicalTrials.gov IDNCT02709057 March 15, 2016

180-LB: Effects of Proton Pump Inhibitors on Glycemic Control and Risk of Incident Diabetes: A Systematic Review and Meta-analysis

Background and Aims: Whether proton pump inhibitors (PPI) can improve glycemic control is unclear. Also, incident diabetes from PPI use has not been elucidated. We conducted a meta-analysis and systematic review to determine the impact of PPI on glycemic control in individuals with diabetes and the risk of diabetes in those without diabetes. Methods: PubMed, Embase, Scopus, and ClinicalTrials.gov were searched from inception to November 21, 2020. Studies reporting a change of glycemic indices, including glycosylated hemoglobin (HbA1c) or fasting blood glucose (FBG), in individuals with diabetes taking add-on PPI compared to standard therapy were included. Also, studies evaluating risk of incident diabetes in individuals taking PPI were assessed. We performed dual independent review, data extraction, and quality assessment. Weighted mean differences or relative risks were imputed using random-effects models. Results: Seven studies (n = 342) for glycemic control, and five studies (n = 244,439) for risk of incident diabetes were included. Compared to standard therapy, add-on PPI was associated with a significant decrease in HbA1c (WMD = −0.36 %; 95% CI: −0.68 to −0.05; p = 0.025), and FBG (WMD = −10.0 mg/dL; 95% CI: −19.4 to −0.6; p = 0.037). However, PPI use was not significantly associated with the risk of incident diabetes (pooled RR = 1.10; 95% CI: 0.89 to 1.34; p = 0.385). Conclusions: PPI along with standard care improved glycemic indices in individuals with diabetes but did not alter the risk of incident diabetes. The effects of PPI on glycemic control should be considered when treating upper gastrointestinal symptoms in patients with diabetes. Disclosure C. Peng: None. K. Bukhari: None. H. Huang: None. Y. Tu: None. G. Lee: None. H. Chang: None. Y. Huang: None. Y. Fu: None. K. M. Munir: None.

Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program

IntroductionAlthough various lipid and non-lipid analytes measured by nuclear magnetic resonance (NMR) spectroscopy have been associated with type 2 diabetes, a structured comparison of the ability of NMR-derived biomarkers and...

Assessing The Knowledge, Attitude And Practice (KAP) of Prediabetes Management Among Healthcare Providers in Four Tertiary Hospitals In Nigeria: An Observational-Based Cross-Sectional Study

Introduction: An estimated 6.3 million Nigerians were reported to have prediabetes in 2015 placing Nigeria in the 9th position in world ranking. This number is projected to become 12.9 million by 2040. One way of reversing this trend is early identification of individuals at risk. This study was carried out to assess the knowledge, attitudes and practice of health care providers toward prediabetes diagnosis and management. Methods: This was an observational-based cross-sectional study involving the use of self administered questionnaire to doctors from the departments of internal medicine, paediatrics, obstetrics and gynaecology, family medicine and others. Results: In all, 358 questionnaires out of 410 were selected. All 10 risk factors for prediabetes were correctly identified by 82/358 (22.9%) participants with 300/358 (83.8%) able to identify at least 5 risk factors. Laboratory reference interval of 5.6 – 6.9 mmol/L for diagnosing prediabetes using fasting plasma glucose were correctly identified by 70/358 (19.6%) (lower value) and 14.5% (upper value) respectively. American Diabetes Association guidelines for prediabetes screening was the most familiar to 272(76.0%) respondents even though 144/358(40.2%) do not consider prediabetes as a condition that requires specific management. Over half 186/358(52%) of respondents agreed that metformin use can reduce the risk of diabetes in individuals with prediabetes but only 6/358(1.7%) have ever discussed starting metformin with their patients. Conclusion: There is need to educate medical doctors about risk factors for prediabetes and its management to curb the rising diabetes epidemic in Nigeria.

The relative risk of developing type 2 diabetes among individuals with prediabetes compared with individuals with normoglycaemia: Meta-analysis and meta-regression.

To assess the overall relative risk of diabetes in individuals with prediabetes based on updated diagnostic criteria, as compared with individuals with normoglycaemia; and to identify the study characteristics associated with the heterogeneity between studies. Meta-analysis, meta-regression. PubMed, CINAHL, British Nursing Index. Search time frame: December 1998-December 2018. The pooled relative risk of developing diabetes among individuals with prediabetes compared with those with normoglycaemia was calculated under a random effects model. Studies reported the natural progression from prediabetes to diabetes were included in this review. Sources of study heterogeneity were examined by a meta-regression. Fifty-nine eligible studies were systematically identified. The pooled relative risk for diabetes among individuals with prediabetes as compared with normoglycaemia was 5.88 (95% CI: 5.02-6.89). The annualized incidence rate (per 1,000 person-year) for diabetes among individuals with prediabetes defined by different criteria varied from 2.20-212.15, with high heterogeneity between studies (I2 =96.64%, Q test: p<.001). In the multivariable meta-regression analysis, Asian population significantly increased RR compare to Caucasians. Besides, people with 'elevated glycated haemoglobin A1c or impaired fasting glucose' had highest relative risk compare to people with other types of prediabetes. Individuals with prediabetes had higher risk of developing diabetes than those with normoglycaemia. Races and diagnostic criteria of prediabetes were associated with the magnitude of the estimated risk. Prediabetes is a precursor of diabetes. To screen people with prediabetes as early as possible, practitioners could consider haemoglobin A1c test as an alternative to fasting plasma glucose test. Nurses should educate people especially Asians with prediabetes for the prevention of progression to diabetes.

TCF7L2 rs290487 C allele aberrantly enhances hepatic gluconeogenesis through allele-specific changes in transcription and chromatin binding.

In this study, we investigated the mechanisms underlying the altered hepatic glucose metabolism and enhanced diabetes risk in individuals with the TCF7L2 rs290487 C allele. Analysis of 195 cirrhotic patients revealed a higher insulin resistance index and incidence of hepatogenous diabetes in patients with the rs290487 C/C genotype compared to those with the C/T or T/T genotype. The in vitro experiments using targeted mutant PLC-PRF-5 cell line showed that cells with the rs290487 C/C genotype (C/C cells) had higher glucose production, lower glucose uptake, and lower TCF7L2 mRNA and protein levels than those with the C/T genotype (C/T cells). Integrated multi-omics analysis of ChIP-seq, ATAC-seq, RNA-seq, and metabolomics data showed genome-wide alterations in the DNA binding affinity of TCF7L2 in the C/C cells, including gain (e.g., PFKP and PPARGC1A) and loss (e.g., PGK1 and PGM1) of binding sites in several glucose metabolism-related genes. These allele-specific changes in transcriptional regulation lead to increased expression of gluconeogenesis-related genes (PCK1, G6PC and PPARGC1A) and their downstream metabolites (oxaloacetate and β-D-fructose 2,6-bisphosphate). These findings demonstrate that the TCF7L2 rs290487 C allele enhances gluconeogenesis through allele-specific changes in transcription and chromatin binding.

Prediction and Diagnosis of Diabetes Mellitus Using a Water Wave Optimization Algorithm

Data mining is an appropriate way to discover information and hidden patterns in large amounts of data, where the hidden patterns cannot be easily discovered in normal ways. One of the most interesting applications of data mining is the discovery of diseases and disease patterns through investigating patients' records. Early diagnosis of diabetes can reduce the effects of this devastating disease. A common way to diagnose this disease is performing a blood test, which, despite its high precision, has some disadvantages such as: pain, cost, patient stress, lack of access to a laboratory, and so on. Diabetic patients’ information has hidden patterns, which can help you investigate the risk of diabetes in individuals, without performing any blood tests. Use of neural networks, as powerful data mining tools, is an appropriate method to discover hidden patterns in diabetic patients’ information. In this paper, in order to discover the hidden patterns and diagnose diabetes, a water wave optimization(WWO) algorithm; as a precise metaheuristic algorithm, was used along with a neural network to increase the precision of diabetes prediction. The results of our implementation in the MATLAB programming environment, using the dataset related to diabetes, indicated that the proposed method diagnosed diabetes at a precision of 94.73%,sensitivity of 94.20%, specificity of 93.34%, and accuracy of 95.46%, and was more sensitive than methods such as: support vector machines, artificial neural networks, and decision trees.