Prediabetic Individuals Research Articles

Endothelial dysfunction in prediabetes and diabetes mellitus in patients with normal coronary arteries

BackgroundDiabetes mellitus (DM) is a global health issue associated with increased cardiovascular disease risk. Endothelial dysfunction is a known precursor to atherosclerosis and cardiovascular disease, and its role in the pathogenesis of DM complications is well-documented. There is limited information in the evaluation of endothelial function in prediabetic patients using flow-mediated dilation (FMD), and studies have not excluded patients with known atherosclerosis or coronary artery disease. Thus, in this study, we aimed to evaluate the endothelial functions using FMD from the brachial artery of DM and prediabetes patients who had normal coronary arteries.MethodsThis study included 73 participants: 25 with DM, 25 with prediabetes, and 23 normoglycemic controls, all with normal coronary arteries on angiography. FMD measurements were conducted following established protocols, and statistical analysis was performed using standard methods to compare FMD levels among groups.ResultsThe groups were comparable in clinical and demographic characteristics, except for fasting plasma glucose levels. Significant differences in FMD levels were observed: 10.1% in the DM group, 16.5% in the prediabetes group, and 14.8% in the control group (P = 0.004). Diabetic patients had significantly lower FMD levels than both prediabetic and normoglycemic individuals. No significant difference in FMD was found between prediabetic and control groups.ConclusionsDiabetic patients exhibited significant endothelial dysfunction compared to normoglycemic individuals, while prediabetic patients did not show similar dysfunction. These findings suggest a window of opportunity in the prediabetic stage for early intervention to prevent advanced endothelial dysfunction.Trial registration numberISRCTN Registry ISRCTN15351014. Registry date: 23/09/2024. Retrospectively registered.

Pioneering diabetes screening tool: machine learning driven optical vascular signal analysis

The escalating prevalence of diabetes mellitus underscores the critical need for non-invasive screening tools capable of early disease detection. Present diagnostic techniques depend on invasive procedures, which highlights the need for advancement of non-invasive alternatives for initial disease detection. Machine learning in integration with the optical sensing technology can effectively analyze the signal patterns associated with diabetes. The objective of this research is to develop and evaluate a non-invasive optical-based method combined with machine learning algorithms for the classification of individuals into normal, prediabetic, and diabetic categories. A novel device was engineered to capture real-time optical vascular signals from participants representing the three glycemic states. The signals were then subjected to quality assessment and preprocessing to ensure data reliability. Subsequently, feature extraction was performed using time-domain analysis and wavelet scattering techniques to derive meaningful characteristics from the optical signals. The extracted features were subsequently employed to train and validate a suite of machine learning algorithms. An ensemble bagged trees classifier with wavelet scattering features and random forest classifier with time-domain features demonstrated superior performance, achieving an overall accuracy of 86.6% and 80.0% in differentiating between normal, prediabetic, and diabetic individuals based on the optical vascular signals. The proposed non-invasive optical-based approach, coupled with advanced machine learning techniques, holds promise as a potential screening tool for diabetes mellitus. The classification accuracy achieved in this study warrants further investigation and validation in larger and more diverse populations.

Elevated 1-Hour Post Load Glucose as a Predictor for Telomere Attrition: a study based on a Chinese Community population.

1-hour post-load glucose (1h-PG) detects dysglycemia-related disorders more effectively than traditional glycemic parameters. Hyperglycemia accelerates aging, whether 1h-PG outperforms in predicting aging remains unclear. To Compare the effectiveness of 1h-PG with other glycemic parameters in identifying and predicting telomere attrition. We conducted a cross-sectional and longitudinal study based on a Chinese community cohort. Multivariate linear regression and logistic regression were used to analyze the associations between glycemic parameters and telomere length. The area under the receiver operating characteristic (AUROC) curve were used to compare the differentiating and predictive ability. Populations were regrouped by glucose tolerance status and 1h-PG to compare telomere length. Analyses were separately conducted in non-diabetic and diabetic populations. The cross-sectional study included 715 participants. Only 1h-PG was significantly negatively associated with RTL in both non-diabetic (β = -0.106, 95%CI -0.068 to -0.007, P = 0.017) (odds ratio [OR] = 1.151, 95% CI 1.069 to 1.239, P = 0.005) and diabetic (β = -0.222, 95%CI -0.032 to -0.007, P = 0.002) (OR = 1.144, 95% CI 1.041 to 1.258, P = 0.035) populations. The longitudinal study recruited 437 populations and 112 remained in 7-years follow-up. 1h-PG was associated with telomere shortening in the non-diabetic group (β = -0.314, 95%CI -0.276 to -0.032, P = 0.016) (OR = 2.659, 95% CI 1.158 to 6.274, P = 0.021). AUROC analysis showed that 1h-PG outperformed other glycemic parameters in identifying and predicting telomere attrition. Reclassification revealed that normal glucose tolerance and prediabetic individuals with elevated 1h-PG had telomere lengths comparable to prediabetic and diabetic populations, respectively. 1h-PG outperforms other glycemic parameters in predicting telomere attrition and can be a valuable marker for early aging detection.

Efficacy Of Family Participatory Intervention Strategies On Prevention Of Diabetes Among Prediabetic Individuals In Selected Rural Communities In Chennai

Efficacy Of Family Participatory Intervention Strategies On Prevention Of Diabetes Among Prediabetic Individuals In Selected Rural Communities In Chennai

12474 Demographic Characteristics Of Patients With Prediabetes Who Reverted To Normoglycemia Or Progressed To Diabetes At 1 Year Follow Up

Abstract Disclosure: E.M. Niedzialkowska: None. F. El Sayed: None. M. Townsend: None. U. Bhatia: None. S. Roy: None. R. Homayouni: None. A. Halalau: None. Background: Pre-diabetes (PD), characterized by hyperglycemia influenced by lifestyle factors, genetics, age, and ethnicity, is considered a risk factor for development of diabetes. However, only a small proportion of PD individuals progress to type-2 diabetes (T2D) each year. More refined diabetes risk prediction tools are needed to direct proactive health management strategies for at-risk populations. Question and Significance: Our study explored the associations between age, race, gender and BMI in PD individuals who either progressed to T2D or reverted to normoglycemia (NG) over a one-year follow-up period. Methods and Design: This is a retrospective observational study of 38,228 patients with PD, based on having two consecutive years of hemoglobin A1c (HbA1c) between 5.7% and 6.5%. We compared the demographic characteristics of individuals who progressed to T2D or regressed to NG within one year using bivariate (Kruskal-Wallis or Chi-squared) or multivariate logistic regression analysis. Results: The study cohort included 57.36% females, 66.13% Whites, 19.41% Blacks and 4.36% Asians with a median age of 69. Bivariate analysis revealed significant age differences between PD patients who reverted to NG with median age of 67 in those who reverted vs 70 in those who did not revert (p< 0.0001). In addition, the proportion of males who progressed to T2D was significantly higher and the proportion of Blacks who reverted to NG was significantly lower.Using multivariate regression (adjusting for age, gender, race and BMI), we found that each year in age significantly lowered the odds of reversion from PD to NG (OR 0.98, p<0.0001) but was not associated with progression to T2D. PD males had significantly higher odds of progression to T2D (OR 1.28, p<0.0001). Both Asians (OR 0.62, p<0.0007) and Blacks (OR 0.68, p<0.0004) had significantly lower odds of reversion to NG from PD compared to Whites. Surprisingly, BMI was not associated with neither reversion to NG nor progression to T2D, after adjusting for age, gender, and race. Discussion: Our findings underscore significant racial disparities and gender differences in regression to normoglycemia and progression to diabetes. This emphasizes the need for personalized interventions and targeted strategies for prediabetic populations to mitigate progression to T2D and to achieve normoglycemia. Presentation: 6/1/2024

Oxidative stress and inflammation on metabolic abnormalities and renal involvement in prediabetic subjects across Europe

Background: Studying the mechanisms involved in the transition from prediabetes to diabetes and its associated complications, such as kidney disease, is a growing challenge. This study focuses on identifying valuable biomarkers for the early detection of kidney damage, evaluating molecules associated with oxidative stress and inflammation in prediabetic individuals across Europe.Methods: In plasma samples from individuals with prediabetes included in the ePREDICE study, we determined molecules related to oxidative stress (Advance oxidative protein products-AOPP) and inflammatory biomarkers (C-reactive protein-CRP; Interleukin 6-IL-6), and correlated them with anthropometric and biochemical data, assessing their potential for the early diagnosis of renal involvement.Results: Among the 967 people with prediabetes, 94 presented some sign of renal impairment such as albuminuria, hyperfiltration or hypofiltration. Significant variations were identified between oxidative stress and inflammatory biomarkers (upper and lower quartiles of AOPP, CRP and IL6), and parameters associated with blood pressure, glucose metabolism, lipid profile, and fatty liver index. In particular, both types of biomarkers were associated with components of the metabolic syndrome. There were significant associations between AOPP and CRP, and the presence of albuminuria, but not with renal function. Overall, CRP was a better biomarker than IL-6 for most of the parameters studied.Conclusion: These results highlight the important associations of oxidative stress and inflammation with metabolic abnormalities linked to the prediabetic state and its complications such as fatty liver and renal involvement. Although these results need to be confirmed, our study suggest that AOPP and CRP could be simple biomarkers of interest in predicting the risk of loss of renal function in people with prediabetes.

Metformin Attenuates Post-exercise Heart Rate Recovery In Prediabetic And Diabetic Individuals.

Metformin Attenuates Post-exercise Heart Rate Recovery In Prediabetic And Diabetic Individuals.

Exercise intensities and metabolic health: Targeting blood glucose, insulin, and C-peptide levels in adults with prediabetes in the postprandial state

ObjectiveExercise improves postprandial glycemia and insulin sensitivity in individuals with prediabetes, but the optimal intensity for this metabolic regulation remains unclear. The current study explored the impact of various exercise intensities on blood glucose, insulin, and C-peptide levels in prediabetic individuals to identify the optimal intensity for improving these metabolic indicators. MethodsIn this crossover study, 25 individuals with prediabetes participated in exercise sessions at four different intensities 50 %, 60 %, 70 %, and 80 % of their predicted maximum heart rate using a treadmill. Each session lasted 30 min, including a 5-min warm-up and 5-min cool-down period. Blood samples were collected at four time points: during fasting, immediately before exercise, and 30 and 60 min post-exercise. These samples were analyzed for glucose, insulin, and C-peptide levels. The effects of exercise intensity on these parameters were evaluated using repeated measures analysis of variance (ANOVA), with post hoc tests conducted to determine specific differences between the intensities. ResultsThe participants had an average age of 34.88 years, mean height of 170 cm, and body mass index of 30.34 kg/m2. A significant reduction in insulin and glucose levels post-exercise was observed at 70 % intensity (p ≤ 0.001). Despite high fasting blood glucose levels (110–115 mg/dL), significant reductions were noted at 30 and 60 min post-exercise (p ≤ 0.001). Insulin levels approached near baseline at 70 % intensity, from fasting (26.74 ± 20.83) to 60 min post-exercise (28.47 ± 20.79), indicating a positive response at this intensity. C-peptide levels also showed significant changes, with 70 % intensity exercise bringing them closest to fasting levels by 60 min post-exercise. ConclusionThis study highlights the importance of exercise intensities in enhancing metabolic parameters in individuals with prediabetes. Specifically, 70 % of the predicted maximum heart rate was beneficial, optimizing insulin sensitivity and potentially reducing the risk of progressing from prediabetes to diabetes.

The Silent Threat: A Retrospective Cohort Study on the Impact of Prediabetes on ST-Elevation Myocardial Infarction Survival-A Call to Action!

Background: Prediabetes is frequently underdiagnosed and undertreated, yet it poses significant cardiovascular risks. This study investigates the impact of prediabetes on short- and long-term survival outcomes in patients who experienced ST-elevation myocardial infarction (STEMI). Methods: In this retrospective, single-center cohort study, we evaluated 725 STEMI patients stratified into non-diabetic, prediabetic, and diabetic groups based on HbA1c levels at presentation. A Kaplan-Meier survival analysis was employed to compare long-term outcomes over a three-year follow-up period. Cardiovascular risk factors, including hypertension and dyslipidemia, were analyzed across the groups. The discriminatory power of HbA1c for predicting all-cause mortality was assessed using an Area Under the Receiver Operating Characteristic (AUROC) analysis. Results: Of the 725 patients, 407 (56.1%) were non-diabetic, 184 (25.4%) were prediabetic, and 134 (18.5%) were diabetic. Prediabetic patients exhibited significant additional cardiovascular risk factors, such as arterial hypertension (67.4%) and dyslipidemia (78.3%), with prevalence rates between those of non-diabetic and diabetic patients. The Kaplan-Meier analysis revealed that at a three-year follow-up, prediabetic patients faced a survival disadvantage, with a significant decrease in survival rates compared to non-diabetic patients (log-rank p = 0.016); their survival outcomes approached those of diabetic patients (p = 0.125). The AUROC analysis demonstrated that HbA1c was a significant predictor of short- and long-term mortality, with a cut-off value of 5.75% and an Area Under the Curve (AUC) of 0.580-0.617 (95% CI: 0.458-0.721), indicating a moderate ability to predict survival in patients with STEMI. Conclusions: Prediabetes significantly worsens survival outcomes following STEMI, nearly approaching the risk level of diabetes. Integrating rigorous cardiovascular risk management strategies for prediabetic individuals, including lifestyle interventions and potentially pharmacological treatments, could prevent the progression to diabetes and mitigate associated cardiovascular risks.

Pancreatic Cancer Risk in Prediabetes: A Systematic Meta-Analysis Approach.

Pancreatic cancer and Prediabetes pose significant public health challenges. Given the lack of strong evidence and inconsistencies, we performed a meta-analysis to assess the risk of pancreatic cancer in prediabetes. We performed a thorough search of the major databases over the last 10 years to identify relevant articles. The Pooled odds ratio(OR) and Hazard Ratio(HR) were combined to calculate the effect size(ES). We analyzed 5 studies including 5,425,111 prediabetic individuals and 16,096,467 normoglycemic population across five countries with a median follow-up of 8.5 years. We identified a noteworthy association between prediabetes and pancreatic cancer, reporting an unadjusted effect size (ES) of 1.36 (95% CI 1.05-1.77, P = 0.02) and an adjusted ES of 1.40 (1.23-1.59, P < 0.01). Subgroup analyses by age revealed variations in risk, with studies involving participants aged 60 and above exhibiting a higher effect size (ES 1.83, 95% CI 1.28-2.62, P < 0.01). Geographical differences were also observed, with Japanese studies reporting a higher risk (ES 1.89, 95% CI 1.15-3.10, P < 0.01) compared to those from the USA (ES 1.32, 95% CI 1.13-1.53, P < 0.01). We identified 40% higher risk of pancreatic cancer in patients with prediabetes than those with normal blood glucose necessitating urgent attention for further research and policy change.

Patterns of Lipid Abnormalities in Obesity: A Comparative Analysis in Normoglycemic and Prediabetic Obese Individuals.

Background: Obesity is a growing global health concern, often accompanied by dyslipidemia, contributing to cardiovascular risk. Understanding the patterns of dyslipidemia in different glycemic states is crucial for targeted interventions. This study compares dyslipidemia patterns in normoglycemic and prediabetic obesity to improve clinical management strategies. Methods: The study analyzed the complete lipid profiles of 138 subjects, comparing the medians, prevalence, diagnostic performance, and risk assessment of each lipid parameter across 54 non-obese (NO), 44 normoglycemic obese (NG-OB), and 40 pre-diabetic obese (PreDM-OB) groups. Results: Elevated total cholesterol (TC) and low-density lipoprotein (LDL) were the most prevalent forms of dyslipidemia observed in obesity (45.35% and 43.53%, respectively). Stratification by glycemic status revealed that triglyceride (TG) levels were elevated in both the NG-OB and PreDM-OB groups, with a more marked increase in the latter group (73.07 mg/dL vs. 97.87 mg/dL vs. 121.8 mg/dL, respectively). Elevated LDL showed better diagnostic performance and higher odds ratios (OR) in the NG-OB group (AUC = 0.660, p = 0.006; OR = 2.78, p = 0.022). Conversely, low high-density lipoprotein (HDL) was more common and exhibited significant diagnostic performance, with higher OR values in the PreDM-OB group (AUC = 0.687, p = 0.002; OR = 3.69, p = 0.018). Importantly, all lipid ratios were elevated in obesity, with TC/HDL showing the highest predictive ability for prediabetes (AUC = 0.7491, p < 0.001). Conclusions: These findings revealed unique and common lipid abnormalities in normoglycemic and prediabetic obesity. Future research should explore the effects of targeted lipid management on obesity-associated complications.

Independent association of metabolic syndrome severity score and risk of diabetes: findings from 18 years of follow-up in the Tehran Lipid and Glucose Study

ObjectivesThis study aimed to investigate the association between age-specific and sex-specific continuous metabolic syndrome severity score (cMetS-S) and the risk of developing type 2 diabetes mellitus (T2DM). Additionally, the study...

Higher docosahexaenoic acid proportions in blood are inversely associated with the prevalence of prediabetes: Evidence from the UK Biobank

Prediabetes and type 2 diabetes mellitus are growing global health concerns, predisposing individuals to various vascular complications. Lifestyle modifications, including dietary interventions, offer promising avenues for prevention and management. Using a multivariable-adjusted model, we analyzed the cross-sectional associations between plasma proportions (% of total fatty acids) of omega-3 polyunsaturated fatty acids (n3 PUFA, including total n3 PUFA, docosahexaenoic acid [DHA], non-DHA n3 PUFA), and glycated hemoglobin A1c (HbA1c) as well as the prevalence of prediabetes in a sample from the UK Biobank cohort. Our hypothesis was that proportions of n3 PUFA, especially DHA, would by inversely associated with the prediabetes prevalence. The sample (n = 92,762; 54.5% females) had an average age of 56 years and was overweight (mean body mass index = 27). The mean plasma DHA proportion in the sample was 2.03% (standard deviation [SD] = 0.67%), non-DHA n3 PUFA was 2.41% (SD = 1.02%) and total n3 PUFA was 4.43% (SD = 1.56%). Prediabetic individuals were identified by blood HbA1c proportions between 5.7% and 6.4% (39-46 mmol/mol) according to American Diabetes Association criteria. Each of the three n3 PUFA biomarkers was inversely associated with HbA1c proportions. In particular, DHA showed the strongest inverse association, with an OR of 0.62 (95% confidence intervals: 0.58, 0.67; P < .001) when comparing quintiles 5 to 1 in a fully adjusted model. These findings suggest a potential protective role of n3 PUFA, particularly DHA, in mitigating the risk of having prediabetes. Further prospective investigations are needed to clarify whether long-chain n3 PUFA could function as modifiable factors for prediabetes.

A longitudinal study on the impact of the TyG Index and TG/HDL-C ratio on the risk of type 2 diabetes in Chinese patients with prediabetes

ObjectiveTo elucidate the impact and predictive value of the Triglyceride Glucose Index (TyG) and the ratio of Triglycerides to High-Density Lipoprotein Cholesterol (TG/HDL-C) in identifying the risk of diabetes progression in Chinese individuals with prediabetes.MethodsThis longitudinal study enrolled 15,012 prediabetic adults from the Rich Healthcare Group between 2010 and 2016. Diabetes was defined as self-reported diabetes or a fasting glucose level ≥ 7.0 mmol/L. The Cox proportional hazards models was utilized to assess the relationship between the two indices and the risk of developing diabetes. The predictive efficacy of the two markers was gauged by the area under the curve (AUC).ResultsOver a median follow-up period of 2.87 years, 1,730 (11.5%) prediabetic participants developed diabetes. The adjusted hazard ratios for the top quartile of the TyG index and the TG/HDL-C ratio were 2.03 (95% confidence interval [CI]: 1.71–2.40) and 2.59 (95% CI: 2.20–3.05), respectively, compared to the lowest quartile. A significant trend of increasing diabetes risk with higher quartiles of both indices was observed. The AUC for the adjusted prediction model for prediabetes-to-diabetes transition was 0.726 for the TyG index and 0.710 for the TG/HDL-C ratio. The difference in AUCs was statistically significant (P = 0.03).ConclusionsThe baseline TyG index or TG/HDL-C ratio was significantly associated with an increased risk of diabetes in prediabetic individuals. The TyG index demonstrated superior predictive accuracy, underscoring its importance in preventing diabetes in prediabetic individuals.

Anthropometric indicators and cardiovascular diseases risk in pre-diabetic and diabetic adults: NHANES 1999–2018 cross-sectional analysis

BackgroundSince cardiovascular disease (CVD) stands as the primary cause of death in those with diabetes, and given the substantial influence of obesity as a common risk factor for both diabetes and atherosclerotic conditions, this investigation sought to find the relationship between anthropometric indicators and CVD risk within these populations. MethodsOur study examined 36,329 adults, including those with diagnosed diabetes, pre-diabetes, and without diabetes from National Health and Nutrition Examination Survey (NHANES) data spanning 1999 to 2018. Various anthropometric indicators such as body mass index (BMI), waist circumference, weight-adjusted waist index (WWI), waist-to-height ratio (WHtR), weight, and height were assessed. Baseline characteristics were compared among the three groups after weighting. Participants were then grouped based on anthropometric indicators, and logistic regression models were used to analyze the association between these indicators and CVD risk in the total diabetes group (including diabetic and pre-diabetic individuals). Threshold effect analysis was conducted to explore nonlinear relationships, and mediation analyses assessed whether serum parameters influenced these relationships. ResultsThis cross-sectional study involved 36,329 participants, weighted to a count of approximately 160.9 million, including over 45.9 million pre-diabetic individuals and around 16.6 million diabetic individuals. Baseline analysis showed significant associations between all six anthropometric indicators and CVD risk across patients with different diabetes statuses. Weighted restricted cubic spline (RCS) curve analysis highlighted increased CVD risk among the total diabetes group for each anthropometric indicator compared to the non-diabetic group. Anthropometric indicators were then divided into quartiles, and after adjusting for confounders, Model 3 revealed that the highest BMI group had a heightened risk of CVD compared to the lowest BMI group. Similar trends were observed in the WWI and WHtR subgroups. Threshold effect analysis of anthropometric indicators unveiled nonlinear associations between waist circumference, height, WWI and CVD risk. Mediation analysis suggested that lipid parameters, especially HDL, significantly mediated these relationships. ConclusionIn individuals with diabetes and pre-diabetes, BMI, weight, and WHtR displayed a consistent, linear increase correlation with CVD risk. Conversely, the link between waist circumference, height, and WWI and CVD risk showcased a more complex, nonlinear pattern. Moreover, HDL level emerged as notable mediator in the association between anthropometric indicators and the risk of CVD.

Evaluation of circulating plasma miR-9, miR-29a, miR-192, and miR-375 as potential biomarkers for predicting prediabetes and type 2 diabetes in Nepali adult population

Circulating plasma miRNAs have emerged as potential early predictors of glucometabolic disorders. However, their biomarker potential remains unvalidated in populations with diverse genetic backgrounds, races, and ethnicities. This study aims to validate the biomarker potential of plasma miR-9, miR-29a, miR-192, and miR-375 for early detection of prediabetes and type 2 diabetes mellitus (T2DM) in Nepali populations that represent distinct genetic backgrounds, races, and ethnicities. A total of 46 adults, categorized into healthy controls (n = 25), prediabetes (n = 9), and T2DM (n = 12) groups, were enrolled. Baseline sociodemographic, anthropometric, and clinical characteristics were collected. Fold change in plasma expression of all four miRNAs was quantified using RT-qPCR against the RNU6B reference gene. Their biomarker potential was determined by receiver operating characteristic (ROC) curve analysis. Multivariate discriminant function and hierarchical cluster analyses were used to evaluate the effectiveness of the miRNA panel in reclassifying study participants who were initially categorized according to their glucose tolerance status. Plasma expression of all four miRNAs was significantly upregulated in T2DM patients compared to normoglycemic controls. Furthermore, the expression of only miR-29a and miR-375 was upregulated in T2DM patients than in prediabetic individuals. Notably, only miR-192 expression was significantly upregulated in prediabetic individuals than in the normoglycemic controls. The miRNA expression profiles had the potential of reclassifying the participants into three original groups with an accuracy of 69.6 %. ROC curve analysis identified miR-192 as the predictor for both prediabetes and T2DM, while miR-9, miR-29a, miR-192, and miR-375 were predictive only for T2DM. The specific set of miRNA combinations significantly improved their predictive accuracy. This study validates the early predictive biomarker potential of plasma miR-9, miR-29a, miR-192, and miR-375 also in the Nepali population and paves the way for future translational studies to validate their utility in clinical laboratories.

Serum Afamin in Prediabetic Individuals in Association with Insulin Resistance and Glycemic Indices: A Case-Control Study

Background: Prediabetes is a metabolic disorder characterized by higher serum glucose levels than normal and below the diagnostic threshold for diabetes mellitus. Afamin is a glycoprotein mainly excreted from the liver and facilitates vitamin E transport. Afamin is one of the albumin gene family that includes albumin, α-Fetoprotein, and vitamin D-binding protein. Aim: This study aimed to evaluate serum afamin levels in prediabetic individuals and ascertain the association of serum afamin with insulin resistance and glycemic indices. Material and Methods: A case-control study was performed at Azadi Teaching Hospital, Kurdistan Region, Iraq, consisted of 88 participants, 44 prediabetic individuals and 44 apparently healthy individuals as a control group. Prediabetic individuals were obtained from relatives of patients with diabetes mellitus visiting Azadi Teaching Hospital, whereas, healthy individuals were chosen from the medical staff and college employees. The diagnosis of prediabetes was made according to the American Diabetes Association criteria. Serum afamin were assessed by Enzyme-Linked Immunosorbent Assay, while other biochemical parameters such as HbA1c, glucose and insulin were analyzed by Cobas 6000 (Roche, Hitachi/ Germany). Results: Mean level of serum afamin was higher in prediabetic individuals (115.31±62.74) compared to their level in the control group (91.57±43.46), with a statistically significant difference (p = 0.042). The mean age of prediabetics was (44.05±10.56) with males predominant (63.6%) and 70.5% of them were more than 40 years and 88.6% were obese. Conclusion: The study concluded the presence of higher mean serum afamin levels among prediabetic individuals compared to the healthy control.

A Comparative Study on Levels of hs-CRP and Lipid Profile in Prediabetic and Normal Population.

This study aimed to compare high-sensitivity C-reactive protein (hs-CRP) and lipid profile levels between prediabetic and normal populations and explore correlations between hs-CRP and lipid profile in prediabetic individuals. The study was conducted among Group A comprising 75 prediabetic individuals, and Group B, which included 75 non-diabetic controls from the general population. Results showed that the mean hs-CRP level in Group A (1.717) significantly exceeded that of Group B (0.917) (p = 0.001). Pearson correlation analysis revealed significant positive linear relationships between hs-CRP and lipid profile parameters, indicating that as total cholesterol, triglycerides (TGs), high-density lipoprotein (HDL), and very low-density lipoprotein (VLDL) increased, hs-CRP also increased. A significant negative linear relationship was observed between hs-CRP and HDL. Moreover, a positive linear relationship existed between hs-CRP and glycemic parameters (fasting blood sugar (FBS), postprandial blood sugar (PPBS), and Glycated haemoglobin (HbA1c)). It is concluded that elevated hs-CRP, an inflammatory marker, correlated with dysregulated lipid profiles, and glycemic parameters, indicating its potential role in assessing inflammation in prediabetic individuals and its association with dyslipidemia and glucose metabolism.

Gut Microbial Composition, but Not Diversity, Changed With High-Astaxanthin Salmon Consumption in Obese, Prediabetic Individuals

Gut Microbial Composition, but Not Diversity, Changed With High-Astaxanthin Salmon Consumption in Obese, Prediabetic Individuals

Association of Lipoprotein and Apolipoprotein Ratios With Glycemic Levels in Individuals With Prediabetes: A Case-Control Study.

Prediabetes is defined as a hyperglycemic state between normal glucose metabolism and diabetes mellitus. It is also recognized as a predisposing factor for cardiovascular disease. Apolipoprotein is a constituent of lipoproteins, and its ratio levels (ApoB/ApoA1 ratio) are considered an independent risk factor for cardiovascular diseases. This study aimed to evaluate the apolipoprotein ratio (ApoB/ApoA1 ratio) and lipoprotein ratio (low-density lipoprotein cholesterol/high-density lipoproteincholesterol (LDL-C/HDL-C) ratio) in prediabetes in relation to glycemic levels and establish the association between apolipoprotein and lipoprotein ratios in prediabetic individuals and their glycemic levels. A case-control study was conducted among 150 participants, 75 with prediabetes and 75 apparently healthy individuals (with no prediabetes or diabetes), from January 1, 2023 to December 30, 2023. The parameters involved are fasting serumglucose, insulin, blood HbA1c%, HDL-C, LDL-C, apolipoprotein A, apolipoprotein B, and lipoprotein(a) (Lp(a)), measured using different principles. Prediabetes was more predominant in males (58.7%), particularly those aged over 40 years (74.7%). The mean Lp(a) (46.18±11.66 mg/dl), LDL-C/HDL-C ratio (1.74±0.96), and ApoB/ApoA ratio (1.10±0.62) were significantly higher among prediabetic individuals. Moreover, these ratios were insignificantly higher in prediabetic individuals with HbA1c level (5.8-6.4%) and fasting glucose level (100-125 mg/dl) than those with lower levels. Prediabetic individuals exhibited a notably elevated average level of Lp(a), as well as increased mean ApoB/ApoA1 ratio and mean LDL-C/HDL-C ratio compared to individuals who were apparently healthy.