Nondiabetic Subjects Research Articles

Human Gut Microbiome Before and After Bariatric Surgery in Obese Patients with and Without Type 2 Diabetes.

Bariatric surgery, a significant intervention for obesity, may influence weight loss through changes in gut microbiota, particularly the Firmicutes and Bacteroidetes. This study explores these potential shifts and their metabolic implications. We conducted a cross-sectional study involving patients who had undergone bariatric surgery. Stool samples were collected at baseline, 3 months, and 6 months post-operation. We performed DNA extraction and quantified the bacterial phyla Firmicutes and Bacteroidetes to assess changes in the gut microbiota over time. Our research revealed a significant alteration in the gut microbiota following bariatric surgery. In diabetic individuals, there was a marked increase in the average number of Firmicutes bacteria at both 3 and 6 months post-operation, compared to pre-surgery levels. In contrast, non-diabetic subjects experienced a notable decrease in Firmicutes during the same timeframe. Regarding Bacteroidetes bacteria, the trend was reversed; diabetic patients showed a significant reduction, while non-diabetics exhibited an increase after the surgery. These findings highlight the dynamic changes in gut microbiota composition associated with bariatric surgery and its potential link to metabolic changes post-operation. These findings suggest that obesity alters the gut's microbial composition. The observed bacterial fluctuations, particularly in the dominant Firmicutes and Bacteroidetes groups, are likely contributors to the weight loss experienced post-surgery. This alteration in gut bacteria underscores the complex interplay between microbiota and metabolic health, highlighting potential avenues for therapeutic intervention.

Type 1 diabetes mellitus and sperm quality: A case-control study.

The potential impact of diabetes mellitus type 1 (DM1) on male fertility is currently poorly defined. Hyperglycaemia and insulin deficiency may affect spermatogenesis. Some evidence suggests that men with DM1 have a significant reduction in progressive sperm motility, sperm morphology and semen volume, without significant changes in sperm concentration and count, but definite data are lacking. To evaluate the impact of DM1 on clinical parameters related to male fertility and semen analysis. We compared a court of 42 male DM1 patients with 43 nondiabetic subjects overlapping in age and remaining clinical data in an observational case-control study. All subjects underwent a comprehensive andrological reproductive evaluation, including medical history, physical examination, and semen analysis. We collected biochemical data in all patients with DM1, while diabetic patients with any alteration in semen parameters underwent sperm culture and scrotal ultrasound. In addition, all men completed the IIEF-5 questionnaire (International Index of Erectile Function-5) and the AMS (Aging Male Symptom score) questionnaire. Patients with DM1 had a higher prevalence of infertility, erectile dysfunction and worse semen parameters compared with controls. In particular, semen volume, total sperm count, and total and progressive sperm motility were significantly lower (p<0.001, p=0.003, p=0.048, and p=0.022 respectively). In addition, the rate of semen anti-sperm antibody positivity, the AMS score and FSH levels were higher. Several mechanisms may contribute to these semen alterations in DM1 patients, such as oxidative damage to spermatogenesis, seminal infections and pelvic neurological changes. These data suggest that patients with DM1 should be counselled from an andrological-reproductive point of view.

Iron Status in Male Type 2 Diabetic Patients and Its Association with Their Glycemic Status

Background &amp; objective: Alteration in iron metabolism may occur in diabetic patients especially those who have poor glycemic control. Serum iron is involved in free radical formation associated with hyperglycemia and causes diabetic complications. The present study was undertaken to observe the iron status and its relation with glycemic control in male type 2 diabetic patients. Methods: This cross-sectional analytical study was carried out in the Department of Physiology, Sir Salimullah Medical College (SSMC), Dhaka from July 2017 to June 2018. A total of 48 diagnosed male type 2 diabetic patients (cases) were recruited from the Out-patient Department (OPD) of Endocrinology based on predefined eligibility criteria. Of them, 24 had good glycemic control (HbA1c level &lt; 7%) (Group B1) and 24 had poor glycemic control (HbA1c level ≥ 7%) (Group B2). To compare the outcome (serum iron status) of these diabetic patients, another 48 age- and BMI-matched healthy non-diabetic male subjects were selected from personal contact as control. While diabetes and glycemic status (fasting blood glucose level, and HbA1c) of the diabetic patients were exposure variables, serum iron, serum total iron binding capacity (TIBC), transferrin saturation, and serum ferritin were the outcome variables. Results: The mean age of the subjects of either study group was around 43 and there was no significant difference between the groups concerning age (p = 0.610). The distribution of BMI and serum creatinine between groups was also similar (p = 0.135 and p = 0.134 respectively). The cases had a significantly higher level of serum iron, transferrin saturation, and an insignificantly lower total iron binding capacity (TIBC) than their non-diabetic peers (p = 0.045, p = 0.036, and p = 0.061 respectively). A comparison of outcome variables among the three groups shows that the groups were significantly heterogeneous in terms of serum iron, TIBC, transferrin saturation, haemoglobin level (p = 0.032, p = 0.012, p = 0.008 and p = 0.018 respectively). The associations were more conspicuous in patients with poor glycemic status. Correlation analyses revealed that while there was a significant linear correlation between serum iron and HbA1c (r = + 0.376, p &lt; 0.01), it was negatively correlated with serum TIBC (r = -0.478, p &lt; 0.001). The glycemic status (HbA1c) was also found to be linearly correlated with serum ferritin and transferrin saturation (r = + 0.354, p = 0.013 and r = + 0.462, p &lt; 0.001 respectively). Conclusion: The study concluded that type 2 diabetic patients have a significantly higher level of serum iron, transferrin saturation, and a lower total iron binding capacity (TIBC) than the non-diabetic healthy subjects, all of which may lead to reduced synthesis of hemoglobin. The compromised iron metabolism is even more evident as the hyperglycemia aggravates. Ibrahim Card Med J 2023; 13 (1&amp;2): 32-39

A collectanea of food insulinaemic index: 2023

Background and AimsTo systematically update and publish the lnsulinaemic Index (II) value compilation of food/beverages. MethodsA literature search identified around 400 scholarly articles published between inception and December 2023. II values were pooled according to the selection criteria of at least 10 healthy, non-diabetic subjects with normal BMI. In addition, the II reported should have been derived from incremental area under the curve (iAUC) calculation of the insulin concentration over time. The reference food used from the pooled articles were either glucose or bread. ResultsThe II of 629 food / beverage items were found from 80 distinct articles. This is almost a five-fold increase in the number of entries from a previous compilation in 2011. Furthermore, these articles originated from 32 different countries, and were cleaved into 25 food categories. The II values ranged from 1 to 209. The highest overall recorded II was for a soy milk-based infant formula while the lowest was for both acacia fibre and gin. Upon clustering to single food, the infant formula retained the highest II while both acacia fibre and gin maintained the lowest recording. As for mixed meal, a potato dish served with a beverage recorded the highest II while a type of taco served with a sweetener, vegetable and fruit had the lowest II. Our minimum and maximum II data values replace the entries reported by previous compilations. ConclusionAcknowledging some limitations, these data would facilitate clinical usage of II for various applications in research, clinical nutrition, clinical medicine, diabetology and precision medicine. Future studies concerning II should investigate standardisation of reference food, including glucose and the test food portion. Although this collectanea adds up new food/beverages II values, priority should be given to populate this database.

The Lipidomic Profile Is Associated with the Dietary Pattern in Subjects with and without Diabetes Mellitus from a Mediterranean Area.

Lipid functions can be influenced by genetics, age, disease states, and lifestyle factors, particularly dietary patterns, which are crucial in diabetes management. Lipidomics is an expanding field involving the comprehensive exploration of lipids from biological samples. In this cross-sectional study, 396 participants from a Mediterranean region, including individuals with type 1 diabetes (T1D), type 2 diabetes (T2D), and non-diabetic individuals, underwent lipidomic profiling and dietary assessment. Participants completed validated food frequency questionnaires, and lipid analysis was conducted using ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC/MS). Multiple linear regression models were used to determine the association between lipid features and dietary patterns. Across all subjects, acylcarnitines (AcCa) and triglycerides (TG) displayed negative associations with the alternate Healthy Eating Index (aHEI), indicating a link between lipidomic profiles and dietary habits. Various lipid species (LS) showed positive and negative associations with dietary carbohydrates, fats, and proteins. Notably, in the interaction analysis between diabetes and the aHEI, we found some lysophosphatidylcholines (LPC) that showed a similar direction with respect to aHEI in non-diabetic individuals and T2D subjects, while an opposite direction was observed in T1D subjects. The study highlights the significant association between lipidomic profiles and dietary habits in people with and without diabetes, particularly emphasizing the role of healthy dietary choices, as reflected by the aHEI, in modulating lipid concentrations. These findings underscore the importance of dietary interventions to improve metabolic health outcomes, especially in the context of diabetes management.

Non-diabetic elderly populations: the MHR as a protective factor against bone abnormalities.

In China, osteoporosis has become a major health concern among elderly population, imposing significant burden on the country's social and economic systems. The monocyte to high-density lipoprotein ratio (MHR) has been currently recommended as a novel marker of inflammation and oxidative stress associated with osteoporosis in type 2 diabetes mellitus (T2DM). However, its reliability in non-diabetic elderly populations remains unclear. The present study was to evaluate the association between MHR and osteoporosis in a non-diabetic elderly population. The clinical data of 240 non-diabetic elderly subjects (115 in the osteoporosis group and 125 in the normal bone group) were retrospectively analyzed and all statistical analyses were performed by using SPSS 26.0. Differences in age, neutrophils, lymphocytes, monocytes, MHR, uric acid, creatinine, triglycerides,and high-density lipoprotein cholesterol were found to be statistically significant between the two groups. A binary logistic regression model was conducted by including age, MHR, UA and Cr as variables. The results showed that age was an independent risk factor and MHR was an independent protective factor for bone abnormality in the non-diabetic elderly population. The ROC analysis showed that the area under the curve for the predictive effect of MHR, age and their combined test on osteoporosis in non-diabetic elderly populations was 0.623, 0.728 and 0.761, respectively; the correlation analysis showed that MHR was positively correlated with lumbar and hip BMD, and negatively associated with femoral neck stress ratio, femoral intertrochanteric stress ratio, and femoral stem stress ratio, showing statistically significant differences (P<0.05). For the non-diabetic elderly population: the MHR is a protective factor against bone abnormalities and was significantly higher in the normal bone group than in the abnormal bone group.

Associations between Serum Kallistatin Levels and Markers of Glucose Homeostasis, Inflammation, and Lipoprotein Metabolism in Patients with Type 2 Diabetes and Nondiabetic Obesity.

Kallistatin is an endogenous serine proteinase inhibitor with various functions, including antioxidative, anti-inflammatory, and anti-atherosclerotic properties. To date, associations between kallistatin and lipoprotein subfractions are poorly investigated. In this study, we enrolled 62 obese patients with type 2 diabetes (T2D), 106 nondiabetic obese (NDO) subjects matched in gender, age, and body mass index, as well as 49 gender- and age-matched healthy, normal-weight controls. Serum kallistatin levels were measured with ELISA, and lipoprotein subfractions were analyzed using Lipoprint® (Quantimetrix Corp., Redondo Beach, CA, USA) gel electrophoresis. Kallistatin concentrations were significantly higher in T2D patients compared to NDO and control groups. We found significant positive correlations between very-low-density lipoprotein (VLDL), small high-density lipoprotein (HDL) subfractions, glucose, hemoglobin A1c (HbA1c), betatrophin, and kallistatin, while negative correlations were detected between mean low-density lipoprotein (LDL) size, large and intermediate HDL subfractions, and kallistatin in the whole study population. The best predictor of kallistatin was HbA1c in T2D patients, high-sensitivity C-reactive protein (hsCRP) and betatrophin in NDO patients, and hsCRP in controls. Our results indicate that kallistatin expression might be induced by persistent hyperglycemia in T2D, while in nondiabetic subjects, its production might be associated with systemic inflammation. The correlation of kallistatin with lipid subfractions may suggest its putative role in atherogenesis.

Barefoot pressure distribution of diabetic patients and non-diabetic volunteer subjects after sensorimotor training with an unstable shoe construction

BackgroundForty-three percent of all diabetic foot ulcers occur under the medial forefoot due to a medial deviation of elevated pressures and premature forefoot ground contact in neuropathic diabetic patients. A 6-week sensorimotor training period with an unstable shoe construction reduces in-shoe peak pressures and contact times under the medial aspect of the forefoot. MethodsThe study was designed as a Randomised Control Trial with two diabetic groups (one served as intervention group and one as control group) and one non-diabetic intervention group. Measurements for barefoot pressure distribution and contact times were taken by means of an Emed® pressure measurement platform (Novel GmbH, Munich) before and after 6 weeks. During this time the diabetic and the non-diabetic intervention groups were required to wear an unstable shoe construction (Masai Barefoot Technology, MBT®) for at least four hours per day. FindingsResults for the non-diabetic intervention group showed significantly later contact times for the medial portion of the forefoot, resulting in shorter contact times. Peak pressure was also reduced under the medial aspect of the foot while it was increased under the lateral aspect of the foot. Changes for the diabetic intervention group followed the same pattern while the values of the diabetic control group shifted away from the reference values. InterpretationA 6-week sensorimotor training period with an unstable shoe construction can change barefoot peak pressures and contact times in non-diabetic subjects and in diabetic patients in the most endangered area, i.e. the medial forefoot.

Effects of tumor necrosis factor-α rs1800629 and interleukin-10 rs1800872 genetic variants on type 2 diabetes mellitus susceptibility and metabolic parameters among Jordanians.

Diabetes mellitus (DM) is a complex chronic illness with diverse pathogenesis and associations with health complications. Genetic factors significantly contribute to DM development, and tumor necrosis factor alpha (TNF-α) and interleukin-10 (IL-10) genes play major roles. This study aims to explore the influence of TNF-α rs1800629 and IL-10 rs1800872 genetic variants on T2DM development in Jordanian patients at Jordan University Hospital. One-hundred and 60 diabetic and 159 non-diabetic subjects were genotyped for TNF-α rs1800629. Additionally, 181 diabetic and 191 non-diabetic subjects were genotyped for IL-10 rs1800872 using PCR-RFLP genotyping method. The demographic, lipid, and glycemic parameters of the patients were obtained from the computer records in the hospital. TNF-α rs1800629 and IL-10 rs1800872 genetic variants exhibited significant different frequencies in non-T2DM subjects and T2DM patients. The difference in TNF-α rs1800629 genotype frequency between non-T2DM and T2DM participants was significant under the dominant model, while the IL-10 rs1800872 genotype frequency was significant under the recessive model. A significant association (p<0.05) was observed between TNF-α rs1800629 and total cholesterol levels, and between IL-10 rs1800872 polymorphism and glycosylated hemoglobin (HbA1c) and creatinine levels among T2DM patients. TNF-α rs1800629 and IL-10 rs1800872 are identified as genetic risk factors for T2DM. These variants also correlate with variations in cholesterol, HbA1c, and creatinine levels among T2DM patients. Larger clinical studies are warranted to validate these findings.

Correlation between HOMA-IR value and urinary albumin excretion rate in nondiabetic young adult subjects

Correlation between HOMA-IR value and urinary albumin excretion rate in nondiabetic young adult subjects

#771 Estimating glomerular filtration rate: does the diabetic status influence the performances of current equations?

Abstract Background and Aims Diabetes is the first cause of chronic kidney disease (CKD) worldwide. The estimation of glomerular filtration rate (GFR) is one main tool to detect CKD. The most used biomarker remains serum creatinine and the European Kidney Function Consortium (EKFCcrea) equations is the most validated in Europe. More recently, another renal biomarker, cystatin C, has been proposed. In the current analysis, we studied the performances of the EKFC equations in a large cohort of subjects according to their diabetic status. Method Four cohorts from the EKFC dataset were considered in which the diabetic status was available: Lund, Sweden (n = 2,780), Berlin, Germany (n = 654), Créteil, France (n = 466), and Paris, France (n = 2,258). Serum creatinine and cystatin C were measured with calibrated assays. GFR was measured by plasma clearances (mGFR) (iohexol in Lund, Berlin and Créteil and 51Cr-EDTA in Paris). The performance of the equations was assessed by calculating bias, precision (IQR) and P30 (percentage of eGFR-values within ±30% of mGFR). As the characteristics of diabetic patients were different, we matched diabetic and non-diabetic patients using the following matching criteria: age (±3 years), sex (equal), mGFR (±3 mL/min/1.73 m²), and BMI (±2.5 kg/m²). Results In the whole population (n = 6,158), median [IQR] age was 61 [47; 72] years, with 45.8% of women. Mean measured GFR (mGFR) was 60 [39; 82] mL/min/1.73 m². Compared to non-diabetic subjects (n = 5,124), diabetic patients (n = 1,034) were older, more frequently males, heavier, had lower mGFR (45 vs 64 mL/min/1.73 m²), and higher creatinine (1.44 vs 1.06 mg/dL; p &amp;lt; 0.0001) and cystatin C (1.67 vs 1.20 mg/L) concentrations. The performance of the EKFCcys equation was similar to EKFCcrea, but the EKFCcrea+cys had better P30 than single-biomarker equations. Globally, P30 were substantially lower in diabetic patients than in non-diabetic patients (Table). We could match data for 289 females and 546 males. The results in the matched cohorts were quite similar between diabetics and non-diabetics subjects, and this is true for every equation. Conclusion In conclusion, in a large dataset of patients including diabetics and non-diabetics, we showed that the EKFC equations are accurate in diabetic and non-diabetic patients. Combining the creatinine and cystatin C-based equations presents an added value. If accuracy of all equations seems better in non-diabetic than in diabetic subjects, it is probably more due to differences in age and (still more) in GFR levels than to the diabetic status.

Noninvasive Real-Time Glucose Monitoring Is in the Near Future.

Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n = 6; type 1 diabetes, n = 28; nondiabetic pregnant subjects, n = 10; and nondiabetic, n = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors (R2 = 0.95), with 100% of values within Zone A. In the hypoglycemia assessment, measurements from the Gen III sensor tightly followed the capillary glucose measurements down to 42 mg/dL (2.3 mmol/L), whereas the CGM measurements from two different CGM only converged with the GWave and capillary glucose readings after 90 min of decreasing glucose levels. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.

Additive Interaction Between Insulin Resistance, Chronic Low-Grade Inflammation and Vitamin D Deficiency on the Risk of Type 2 Diabetes Mellitus: A Cohort Study

Objectives The aim of this study was to explore, on an additive scale, the combined effect of the association between insulin resistance (IR), chronic low-grade inflammation (CLGI) and vitamin D deficiency (VDD) on the risk of type 2 Diabetes Mellitus (T2DM). Methods This is a cohort study, including 1484 non-diabetic subjects, followed for a period of four years. 25 hydroxy-vitamin D (25OHD), hypersensitive C-reactive protein (HsCRP) and triglyceride-glucose index were assessed. Based on VDD and CLGI, the population was subdivided into 4 exposure groups. Analysis was performed both in the case of IR and without IR. Cox proportional regression and additive interaction were applied to explore cumulative effects of exposure. Results At follow-up, 162 newly diagnosed cases of T2DM were identified. TYG index (RR = 4.0[2.8–5.6]), HsCRP (RR = 1.6 [1.4–1.7]) and 25OHD (RR = 0.96 [0.39–0.98]) were all significantly associated with the risk of T2DM (p < 0.01). The highest excess risk was recorded in patients cumulating simultaneously IR, CLGI and VDD (RR= 8.4[3.6–19.8], p < 0.0001). The additive interaction was significant, the excess risk linked to the interaction RERI = 10.5[1.43–19.7], the proportion attributable to the combined effect: AP = 0.61[0.37–0.85], and the interaction was synergistic: synergy index: 2.8[1.42–5.69]. Conclusion Baseline levels of TYG index, 25OHD and HsCRP are strongly predictive of future T2DM, and their joint effects are additive and synergistic. Interventional studies are therefore warranted in order to evaluate whether vitamin D supplementation, combined with appropriate anti-inflammatory therapies, is effective as a preventive strategy to reduce the risk of T2DM.

COMPARATIVE ANALYSIS OF RENAL PROFILE AND SERUM ELECTROLYTES AMONG DIABETIC AND NON DIABETIC GROUPS IN DISTRICT PESHAWAR KP

Diabetes mellitus is a prevalent non-communicable disease worldwide, contributing significantly to morbidity and mortality. Renal complications are a significant concern in diabetes, with hyperglycemia exacerbating renal dysfunction. Objective: This study aimed to assess renal function and electrolyte balance in diabetic and non-diabetic individuals, focusing on serum urea, creatinine levels, and electrolyte imbalances. Methods: This study was conducted at Al-Khidmat Hospital and processed at the MLT Skill Lab at Abasyn University, Peshawar. A total of 100 participants were enrolled, including diabetic and non-diabetic subjects. Blood samples were collected using a questionnaire design. Renal function tests (RFTs) were analysed using a biochemistry analyser, and serum electrolytes were assessed using an Electrolytes Analyzer. Data collection duration, methodology, and statistical analysis methods were employed. Results: Among the participants, individuals aged 40 to 70 in both genders exhibited a higher prevalence of elevated urea and creatinine levels, particularly in diabetic patients. Diabetic individuals showed a significant association with azotemia. Electrolyte imbalances, notably hypokalemia, were observed, indicating potential complications in diabetic patients. Conclusion: The study highlights the importance of proactive management strategies to mitigate renal complications in diabetic individuals. Comprehensive monitoring of renal function and electrolyte balance is essential in clinical practice.

Vitamin D status in Type 2 Diabetes Mellitus in a Tertiary Level Hospital

Background: There is increasing evidence of a relationship between vitamin D status and type 2 diabetes. Diabetes has also been found to be associated with 25(OH)D (vitamin D) deficiency and the role of vitamin D has recently emerged, especially in preventing cardiovascular diseases and cancer. and insulin resistance. Objective: This study aimed to compare vitamin D deficiency between healthy and Type 2 Diabetes Mellitus (T2DM) patients. Methods: This cross-sectional study was conducted from July 2021 to June 2022 in the Department of Physiology, Rangpur Medical College, Rangpur. For this study, a total number of 100 subjects were selected among them 50 non-diabetic healthy subjects were included as control and 50 Type 2 Diabetes Mellitus patients were included as cases. The subjects of control were selected from the surrounding community of Rangpur district and subjects of cases were selected from Diabetic Association and from Outdoor of Endocrinology Department, Rangpur Medical College and Hospital, Rangpur. For statistical analysis, an independent sample t-test was performed by computer-based software SPSS-23.0 version for windows. Results: The mean vitamin D level was lower in the diabetic patients than in non-diabetic participants (14.1±8.3 ng/ml and 37.3±11.3, p&lt;0.001). Conclusions: Early screening for serum vitamin D level is recommended for T2DM patients. Hence, it is crucial to promptly address any deficiencies in vitamin D levels. J Rang Med Col. March 2024; Vol. 9, No. 1: 77-81

Study of the Relationship Between Insulin Resistance, Iron Status Markers, and Body Weight in a Sample of Egyptian Population.

Iron plays a key role in the regulation of body iron homeostasis and is used as a clinical marker for iron deficiency (ID) and hemochromatosis. The idea that iron dysregulation may contribute to various metabolic diseases, such as obesity, insulin resistance, MetS, and T2DM, is a hot topic of discussion. The aim of this study is to investigate the relationship insulin resistance, iron status markers, and body weight in a sample of Egyptian population. A case control study was conducted on 90 subjects with age ranging from 18 to 70 years old from a diabetes outpatient clinic, and they were divided to three groups: Group I, non-obese- non-diabetic as the control group; Group II, obese-non-diabetic; and Group III, obese-diabetic. In our study, there was no statistically significant difference between the three studied groups regarding the different iron parameters. Similarly, we found that neither HOMA-IR nor body weight had a significant correlation with iron status markers. On the contrary, we detected significant positive correlations between the TIBC and the fasting blood glucose, between the serum iron and the LDL, between the TSAT and the systolic blood pressure, and between the HOMA-IR and hematocrit. Our study demonstrated no direct statistical significant relationship between the different iron parameters, obesity, and insulin resistance, either in the diabetic or non-diabetic subjects. This may be due to the complex metabolic dysregulation and the small number of the sample for future investigations.

Helicobacter pylori Infection and Insulin Resistance in Diabetic and Nondiabetic Subjects

Helicobacter pylori Infection and Insulin Resistance in Diabetic and Nondiabetic Subjects

Effects of hypertriglyceridemia with or without NEFA elevation on β-cell function and insulin clearance and sensitivity.

Hypertriglyceridemia is a risk factor for developing type 2 diabetes (T2D) and might contribute to its pathogenesis either directly or through elevation of non-esterified fatty acids (NEFAs). This study aimed at comparing the glucometabolic effects of acute hypertriglyceridemia alone or combined with NEFA elevation in non-diabetic subjects. Twenty-two healthy lean volunteers underwent two 5-h intravenous infusions of either saline or Intralipid, without (n=12) or with heparin (I+H; n=10) to activate the release of NEFAs. Oral glucose tolerance tests (OGTTs) were performed during the last 3h of infusion. Insulin sensitivity, insulin secretion rate (ISR), model-derived β-cell function, and insulin clearance were measured after 2h of lipid infusion and during the OGTTs. In fasting conditions, both lipid infusions increased plasma insulin and ISR and reduced insulin clearance, without affecting plasma glucose and insulin sensitivity. These effects on insulin and ISR were more pronounced for I+H than Intralipid alone. During the OGTT, the lipid infusions markedly impaired glucose tolerance, increased plasma insulin and ISR, and decreased insulin sensitivity and clearance, without significant group differences. Intralipid alone inhibited glucose-stimulated insulin secretion (i.e. β-cell glucose sensitivity) and increased β-cell potentiation, whereas I+H had neutral effects on these β-cell functions. In healthy non-obese subjects, mild acute hypertriglyceridemia directly reduces glucose tolerance, insulin sensitivity and clearance, and has selective and opposite effects on β-cell function that are neutralized by NEFAs. These findings provide new insight into plausible biological signals that generate and sustain insulin resistance and chronic hyperinsulinemia in the development of T2D.

Bone canonical Wnt signaling is downregulated in type 2 diabetes and associates with higher advanced glycation end-products (AGEs) content and reduced bone strength.

Type 2 diabetes (T2D) is associated with higher fracture risk, despite normal or high bone mineral density. We reported that bone formation genes (SOST and RUNX2) and advanced glycation end-products (AGEs) were impaired in T2D. We investigated Wnt signaling regulation and its association with AGEs accumulation and bone strength in T2D from bone tissue of 15 T2D and 21 non-diabetic postmenopausal women undergoing hip arthroplasty. Bone histomorphometry revealed a trend of low mineralized volume in T2D (T2D 0.249% [0.156-0.366]) vs non-diabetic subjects 0.352% [0.269-0.454]; p=0.053, as well as reduced bone strength (T2D 21.60 MPa [13.46-30.10] vs non-diabetic subjects 76.24 MPa [26.81-132.9]; p=0.002). We also showed that gene expression of Wnt agonists LEF-1 (p=0.0136) and WNT10B (p=0.0302) were lower in T2D. Conversely, gene expression of WNT5A (p=0.0232), SOST (p<0.0001), and GSK3B (p=0.0456) were higher, while collagen (COL1A1) was lower in T2D (p=0.0482). AGEs content was associated with SOST and WNT5A (r=0.9231, p<0.0001; r=0.6751, p=0.0322), but inversely correlated with LEF-1 and COL1A1 (r=-0.7500, p=0.0255; r=-0.9762, p=0.0004). SOST was associated with glycemic control and disease duration (r=0.4846, p=0.0043; r=0.7107, p=0.00174), whereas WNT5A and GSK3B were only correlated with glycemic control (r=0.5589, p=0.0037; r=0.4901, p=0.0051). Finally, Young's modulus was negatively correlated with SOST (r=-0.5675, p=0.0011), AXIN2 (r=-0.5523, p=0.0042), and SFRP5 (r=-0.4442, p=0.0437), while positively correlated with LEF-1 (r=0.4116, p=0.0295) and WNT10B (r=0.6697, p=0.0001). These findings suggest that Wnt signaling and AGEs could be the main determinants of bone fragility in T2D.

Bone canonical Wnt signaling is downregulated in type 2 diabetes and associates with higher advanced glycation end-products (AGEs) content and reduced bone strength

Type 2 diabetes (T2D) is associated with higher fracture risk, despite normal or high bone mineral density. We reported that bone formation genes (SOST and RUNX2) and advanced glycation end-products (AGEs) were impaired in T2D. We investigated Wnt signaling regulation and its association with AGEs accumulation and bone strength in T2D from bone tissue of 15 T2D and 21 non-diabetic postmenopausal women undergoing hip arthroplasty. Bone histomorphometry revealed a trend of low mineralized volume in T2D (T2D 0.249% [0.156–0.366]) vs non-diabetic subjects 0.352% [0.269–0.454]; p=0.053, as well as reduced bone strength (T2D 21.60 MPa [13.46–30.10] vs non-diabetic subjects 76.24 MPa [26.81–132.9]; p=0.002). We also showed that gene expression of Wnt agonists LEF-1 (p=0.0136) and WNT10B (p=0.0302) were lower in T2D. Conversely, gene expression of WNT5A (p=0.0232), SOST (p&lt;0.0001), and GSK3B (p=0.0456) were higher, while collagen (COL1A1) was lower in T2D (p=0.0482). AGEs content was associated with SOST and WNT5A (r=0.9231, p&lt;0.0001; r=0.6751, p=0.0322), but inversely correlated with LEF-1 and COL1A1 (r=–0.7500, p=0.0255; r=–0.9762, p=0.0004). SOST was associated with glycemic control and disease duration (r=0.4846, p=0.0043; r=0.7107, p=0.00174), whereas WNT5A and GSK3B were only correlated with glycemic control (r=0.5589, p=0.0037; r=0.4901, p=0.0051). Finally, Young’s modulus was negatively correlated with SOST (r=−0.5675, p=0.0011), AXIN2 (r=−0.5523, p=0.0042), and SFRP5 (r=−0.4442, p=0.0437), while positively correlated with LEF-1 (r=0.4116, p=0.0295) and WNT10B (r=0.6697, p=0.0001). These findings suggest that Wnt signaling and AGEs could be the main determinants of bone fragility in T2D.