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Frontiers in Endocrinology 2024Diabetic retinopathy (DR) stands as a prevalent complication in the eye resulting from diabetes mellitus, predominantly associated with high blood sugar levels and... (Review)
Review
Diabetic retinopathy (DR) stands as a prevalent complication in the eye resulting from diabetes mellitus, predominantly associated with high blood sugar levels and hypertension as individuals age. DR is a severe microvascular complication of both type I and type II diabetes mellitus and the leading cause of vision impairment. The critical approach to combatting and halting the advancement of DR lies in effectively managing blood glucose and blood pressure levels in diabetic patients; however, this is seldom achieved. Both human and animal studies have revealed the intricate nature of this condition involving various cell types and molecules. Aside from photocoagulation, the sole therapy targeting VEGF molecules in the retina to prevent abnormal blood vessel growth is intravitreal anti-VEGF therapy. However, a substantial portion of cases, approximately 30-40%, do not respond to this treatment. This review explores distinctive pathophysiological phenomena of DR and identifiable cell types and molecules that could be targeted to mitigate the chronic changes occurring in the retina due to diabetes mellitus. Addressing the significant research gap in this domain is imperative to broaden the treatment options available for managing DR effectively.
Topics: Humans; Diabetic Retinopathy; Animals; Molecular Targeted Therapy; Cell- and Tissue-Based Therapy; Vascular Endothelial Growth Factor A
PubMed: 38948520
DOI: 10.3389/fendo.2024.1416668 -
Frontiers in Endocrinology 2024The concept of the gut-retinal axis proposed by previous scholars primarily focused on the relationship between intestinal microbiota and retinal diseases, and few...
Mendelian randomization study and mediation analysis about the relation of inflammatory bowel disease and diabetic retinopathy: the further exploration of gut-retina axis.
BACKGROUND
The concept of the gut-retinal axis proposed by previous scholars primarily focused on the relationship between intestinal microbiota and retinal diseases, and few further expanded the relationship between intestinal diseases and retinal diseases. To further substantiate the concept of the gut-retinal axis, we analyzed inflammatory bowel disease (IBD) and diabetic retinopathy (DR) using Mendelian randomization (MR), and use mediation analysis to further explore the potential substances that influence this causal relationship.
METHODS
The genome-wide association study's (GWAS) summary statistics for genetic variations were utilized in a Mendelian randomization (MR) investigation. GWAS data on IBD (including ulcerative colitis (UC), Crohn's disease (CD), and IBD) for non-Finnish Europeans (NFE) were sourced from published articles. In contrast, data on DR (including DR and diabetic maculopathy (DMP)) were obtained from FinnGen R9. The causal relationship has been investigated using inverse variance weighted (IVW), MR-Egger, and weighted median and sensitivity analysis was applied to verify the stability of the results. In addition, we applied mediation analysis to investigate whether circulating inflammatory proteins and plasma lipids played a mediating role, and calculated its effect ratio.
RESULTS
The causal relationship between IBD and DR was discovered by employing the inverse variance weighted (IVW) method and weighted median method. In forward MR, UC was significantly associated with lower risk of DR (IVW: OR=0.874; 95%CI= 0.835-0.916; P value= 1.28E-08) (Weighted median: OR=0.893; 95%CI= 0.837-0.954; P value= 7.40E-04). In reverse MR, it was shown that DR (IVW: OR=0.870; 95%CI= 0.828-0.914; P value= 2.79E-08)(Weighted median: OR=0.857; 95%CI= 0.801-0.916; P value= 6.40E-06) and DMP (IVW: OR=0.900; 95%CI= 0.865-0.937; P value= 3.34E-07)(Weighted median: OR=0.882; 95%CI= 0.841-0.924; P value= 1.82E-07) could reduce the risk of CD. What's more, DR is associated with a lower risk of IBD according to genetic prediction (IVW: OR=0.922; 95%CI= 0.873-0.972; P value= 0.002) (Weighted median: OR=0.924; 95%CI= 0.861-0.992; P value= 0.029). Fibroblast growth factor 21 (FGF21), phosphatidylcholine (PC), and triacylglycerol (TG) serve as mediators in these relationships.
CONCLUSIONS
Our research offers novel insights and sources for investigating the gut-retina axis in the genetic relationship between IBD and DR. We discover four mediators and more about the association between the intestine and retinal disorders and provide more evidence for the gut-retinal axis theory.
Topics: Humans; Mendelian Randomization Analysis; Diabetic Retinopathy; Genome-Wide Association Study; Inflammatory Bowel Diseases; Mediation Analysis; Retina; Polymorphism, Single Nucleotide; Gastrointestinal Microbiome
PubMed: 38948518
DOI: 10.3389/fendo.2024.1382777 -
Frontiers in Pharmacology 2024The escalation of global population aging has accentuated the prominence of senile diabetes mellitus (SDM) as a consequential public health concern. Oxidative stress and...
Network analysis combined with experimental assessment to explore the therapeutic mechanisms of New Shenqi Pills formula targeting mitochondria on senile diabetes mellitus.
BACKGROUND
The escalation of global population aging has accentuated the prominence of senile diabetes mellitus (SDM) as a consequential public health concern. Oxidative stress and chronic inflammatory cascades prevalent in individuals with senile diabetes significantly amplify disease progression and complication rates. Traditional Chinese Medicine (TCM) emerges as a pivotal player in enhancing blood sugar homeostasis and retarding complication onset in the clinical management of senile diabetes. Nonetheless, an evident research gap persists regarding the integration of TCM's renal tonification pharmacological mechanisms with experimental validation within the realm of senile diabetes therapeutics.
AIMS
The objective of this study was to investigate the mechanisms of action of New Shenqi Pills (SQP) in the treatment of SDM and make an experimental assessment.
METHODS
Network analysis is used to evaluate target pathways related to SQP and SDM. Mitochondrial-related genes were obtained from the MitoCarta3.0 database and intersected with the common target genes of the disease and drugs, then constructing a protein-protein interaction (PPI) network making use of the GeneMANIA database. Representative compounds in the SQP were quantitatively measured using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) to ensure quality control and quantitative analysis of the compounds. A type 2 diabetes mice (C57BL/6) model was used to investigate the pharmacodynamics of SQP. The glucose lowering efficacy of SQP was assessed through various metrics including body weight and fasting blood glucose (FBG). To elucidate the modulatory effects of SQP on pancreatic beta cell function, we measured oral glucose tolerance test (OGTT), insulin histochemical staining and tunel apoptosis detection, then assessed the insulin-mediated phosphoinositide 3-kinase (PI3K)/protein kinase A (Akt)/glycogen synthase kinase-3β (GSK-3β) pathway in diabetic mice via Western blotting. Additionally, we observe the structural changes of the nucleus, cytoplasmic granules and mitochondria of pancreatic islet β cells.
RESULTS
In this investigation, we identified a total of 1876 genes associated with senile diabetes, 278 targets of SQP, and 166 overlapping target genes, primarily enriched in pathways pertinent to oxidative stress response, peptide response, and oxygen level modulation. Moreover, an intersection analysis involving 1,136 human mitochondrial genes and comorbidity targets yielded 15 mitochondria-related therapeutic targets. Quality control assessments and quantitative analyses of SQP revealed the predominant presence of five compounds with elevated concentrations: Catalpol, Cinnamon Aldehyde, Rehmanthin D, Trigonelline, and Paeonol Phenol. Vivo experiments demonstrated notable findings. Relative to the control group, mice in the model group exhibited significant increases in body weight and fasting blood glucose levels, alongside decreased insulin secretion and heightened islet cell apoptosis. Moreover, β-cells nuclear condensation and mitochondrial cristae disappearance were observed, accompanied by reduced expression levels of p-GSK-3β protein in islet cells ( < 0.05 or < 0.01). Conversely, treatment groups administered SQP and Rg displayed augmented expressions of the aforementioned protein markers ( < 0.05 or < 0.01), alongside preserved mitochondrial cristae structure in islet β cells.
CONCLUSION
Our findings suggest that SQP can ameliorate diabetes by reducing islet cell apoptosis and resist oxidative stress. These insulin-mediated PI3K/AKT/GSK-3β pathway plays an important regulatory role in this process.
PubMed: 38948458
DOI: 10.3389/fphar.2024.1339758 -
Data in Brief Aug 2024This dataset provides a collection of Continuous Glucose Monitoring (CGM) data, insulin dose administration, meal ingestion counted in carbohydrate grams, steps,...
This dataset provides a collection of Continuous Glucose Monitoring (CGM) data, insulin dose administration, meal ingestion counted in carbohydrate grams, steps, calories burned, heart rate, and sleep quality and quantity assessment ac- quired from 25 people with type 1 diabetes mellitus (T1DM). CGM data was acquired by FreeStyle Libre 2 CGMs, and Fitbit Ionic smartwatches were used to obtain steps, calories, heart rate, and sleep data for at least 14 days. This dataset could be utilized to obtain glucose prediction models, hypoglycemia and hyperglycemia prediction models, and research on the relationships among sleep, CGM values, and the rest of the mentioned variables. This dataset could be used directly from the preprocessed version or customized from raw data. The data set has been used previously with different machine learning algorithms to predict glucose values, hypo, and hyperglycemia and to analyze influences among the features and the quality and quantity of sleep in people with T1DM.
PubMed: 38948410
DOI: 10.1016/j.dib.2024.110559 -
Sichuan Da Xue Xue Bao. Yi Xue Ban =... May 2024To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results...
[Construction of a Predictive Model for Diabetes Mellitus Type 2 in Middle-Aged and Elderly Populations Based on the Medical Checkup Data of National Basic Public Health Service].
OBJECTIVE
To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2 (T2DM) in the middle-aged and elderly populations based on the results of a Meta-analysis, and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.
METHODS
Cohort studies evaluating T2DM risks were identified in Chinese and English databases. The logistic model utilized Meta-combined effect values such as the odds ratio (OR) to derive , the partial regression coefficient, of the logistic model. The Meta-combined incidence rate of T2DM was used to obtain the parameter of the logistic model. Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service. The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7602 individuals who did not have T2DM at their baseline medical checkups done at the community health center. This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.
RESULTS
A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM, including age, central obesity, smoking, physical inactivity, impaired fasting glucose, a reduced level of high-density lipoprotein cholesterol (HDL-C), hypertension, body mass index (BMI), triglyceride glucose (TYG) index, and a family history of diabetes, with the OR values and 95% confidence interval (CI) being 1.04 (1.03, 1.05), 1.55 (1.29, 1.88), 1.36 (1.11, 1.66), 1.26 (1.07, 1.49), 3.93 (2.94, 5.24), 1.14 (1.06, 1.23), 1.47 (1.34, 1.61), 1.11 (1.05, 1.18), 2.15 (1.75, 2.62), and 1.66 (1.55, 1.78), respectively, and the combined values being 0.039, 0.438, 0.307, 0.231, 1.369, 0.131, 0.385, 0.104, 0.765, and 0.507, respectively. A total of 37 studies reported the incidence rate, with the combined incidence being 0.08 (0.07, 0.09) and the parameter being -2.442 for the logistic model. The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7602 individuals who had medical checkups and were followed up for at least once. External validation results showed that the predictive model had an area under curve (AUC) of 0.794 (0.771, 0.816), accuracy of 74.5%, sensitivity of 71.0%, and specificity of 74.7% in the 7602 individuals.
CONCLUSION
The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.
Topics: Humans; Diabetes Mellitus, Type 2; Middle Aged; Aged; Risk Factors; Logistic Models; Female; Male; China; Cohort Studies; Public Health; Incidence
PubMed: 38948267
DOI: 10.12182/20240560502 -
PeerJ 2024Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder with systemic implications, potentially affecting musculoskeletal health. This study aimed to assess...
BACKGROUND
Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder with systemic implications, potentially affecting musculoskeletal health. This study aimed to assess shoulder muscle strength and joint repositioning accuracy in individuals with T2DM, exploring potential correlations and shedding light on the musculoskeletal consequences of the condition. The objectives were two-fold: (1) to assess and compare shoulder strength and joint repositioning accuracy between individuals with T2DM and asymptomatic counterparts, and (2) to examine the correlation between shoulder strength and joint repositioning accuracy in individuals with T2DM.
METHODS
A cross-sectional study enrolled 172 participants using the convenience sampling method, including 86 individuals with T2DM and an age-matched asymptomatic group ( = 86). Shoulder strength was assessed using a handheld dynamometer, while joint repositioning accuracy was evaluated with an electronic digital inclinometer.
RESULTS
Individuals with T2DM exhibited reduced shoulder muscle strength compared to asymptomatic individuals ( < 0.001). Additionally, joint repositioning accuracy was significantly lower in the T2DM group ( < 0.001). Negative correlations were observed between shoulder strength and joint repositioning accuracy in various directions (ranging from -0.29 to -0.46, < 0.001), indicating that higher muscle strength was associated with improved joint repositioning accuracy in individuals with T2DM.
CONCLUSION
This study highlights the significant impact of T2DM on shoulder muscle strength and joint repositioning accuracy. Reduced strength and impaired accuracy are evident in individuals with T2DM, emphasizing the importance of addressing musculoskeletal aspects in diabetes management. The negative correlations suggest that enhancing shoulder muscle strength may lead to improved joint repositioning accuracy, potentially contributing to enhanced physical functioning in this population.
Topics: Humans; Diabetes Mellitus, Type 2; Male; Cross-Sectional Studies; Female; Middle Aged; Muscle Weakness; Muscle Strength; Shoulder; Proprioception; Shoulder Joint; Aged; Adult; Range of Motion, Articular
PubMed: 38948217
DOI: 10.7717/peerj.17630 -
PeerJ 2024Recent studies suggest that gut microbiota composition, abundance and diversity can influence many chronic diseases such as type 2 diabetes. Modulating gut microbiota... (Randomized Controlled Trial)
Randomized Controlled Trial Comparative Study
Microbiota based personalized nutrition improves hyperglycaemia and hypertension parameters and reduces inflammation: a prospective, open label, controlled, randomized, comparative, proof of concept study.
BACKGROUND
Recent studies suggest that gut microbiota composition, abundance and diversity can influence many chronic diseases such as type 2 diabetes. Modulating gut microbiota through targeted nutrition can provide beneficial effects leading to the concept of personalized nutrition for health improvement. In this prospective clinical trial, we evaluated the impact of a microbiome-based targeted personalized diet on hyperglycaemic and hyperlipidaemic individuals. Specifically, BugSpeaks-a microbiome profile test that profiles microbiota using next generation sequencing and provides personalized nutritional recommendation based on the individual microbiota profile was evaluated.
METHODS
A total of 30 participants with type 2 diabetes and hyperlipidaemia were recruited for this study. The microbiome profile of the 15 participants (test arm) was evaluated using whole genome shotgun metagenomics and personalized nutritional recommendations based on their microbiota profile were provided. The remaining 15 participants (control arm) were provided with diabetic nutritional guidance for 3 months. Clinical and anthropometric parameters such as HbA1c, systolic/diastolic pressure, c-reactive protein levels and microbiota composition were measured and compared during the study.
RESULTS
The test arm (microbiome-based nutrition) showed a statistically significant decrease in HbA1c level from 8.30 (95% confidence interval (CI), [7.74-8.85]) to 6.67 (95% CI [6.2-7.05]), < 0.001 after 90 days. The test arm also showed a 5% decline in the systolic pressure whereas the control arm showed a 7% increase. Incidentally, a sub-cohort of the test arm of patients with >130 mm Hg systolic pressure showed a statistically significant decrease of systolic pressure by 14%. Interestingly, CRP level was also found to drop by 19.5%. Alpha diversity measures showed a significant increase in Shannon diversity measure ( < 0.05), after the microbiome-based personalized dietary intervention. The intervention led to a minimum two-fold (Log2 fold change increase in species like and which might have a beneficial role in the current context and a similar decrease in species like and which have been earlier shown to have some negative effects in the host. Overall, the study indicated a net positive impact of the microbiota based personalized dietary regime on the gut microbiome and correlated clinical parameters.
Topics: Humans; Male; Hypertension; Female; Middle Aged; Gastrointestinal Microbiome; Prospective Studies; Diabetes Mellitus, Type 2; Hyperglycemia; Precision Medicine; Inflammation; Proof of Concept Study; Glycated Hemoglobin; Aged; Hyperlipidemias; Adult; C-Reactive Protein
PubMed: 38948211
DOI: 10.7717/peerj.17583 -
PeerJ 2024Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and...
BACKGROUND
Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and diabetes prevalence, little is known about disparities of DRMR in Florida. Understanding these disparities is important for guiding control programs and allocating health resources to communities most at need. Therefore, the objective of this study was to investigate geographic disparities and temporal changes of DRMR in Florida.
METHODS
Retrospective mortality data for deaths that occurred from 2010 to 2019 were obtained from the Florida Department of Health. Tenth International Classification of Disease codes E10-E14 were used to identify diabetes-related deaths. County-level mortality risks were computed and presented as number of deaths per 100,000 persons. Spatial Empirical Bayesian (SEB) smoothing was performed to adjust for spatial autocorrelation and the small number problem. High-risk spatial clusters of DRMR were identified using Tango's flexible spatial scan statistics. Geographic distribution and high-risk mortality clusters were displayed using ArcGIS, whereas seasonal patterns were visually represented in Excel.
RESULTS
A total of 54,684 deaths were reported during the study period. There was an increasing temporal trend as well as seasonal patterns in diabetes mortality risks with high risks occurring during the winter. The highest mortality risk (8.1 per 100,000 persons) was recorded during the winter of 2018, while the lowest (6.1 per 100,000 persons) was in the fall of 2010. County-level SEB smoothed mortality risks varied by geographic location, ranging from 12.6 to 81.1 deaths per 100,000 persons. Counties in the northern and central parts of the state tended to have high mortality risks, whereas southern counties consistently showed low mortality risks. Similar to the geographic distribution of DRMR, significant high-risk spatial clusters were also identified in the central and northern parts of Florida.
CONCLUSION
Geographic disparities of DRMR exist in Florida, with high-risk spatial clusters being observed in rural central and northern areas of the state. There is also evidence of both increasing temporal trends and Winter peaks of DRMR. These findings are helpful for guiding allocation of resources to control the disease, reduce disparities, and improve population health.
Topics: Humans; Florida; Retrospective Studies; Diabetes Mellitus; Female; Male; Bayes Theorem; Health Status Disparities; Middle Aged; Risk Factors; Seasons; Aged; Adult
PubMed: 38948203
DOI: 10.7717/peerj.17408 -
Avicenna Journal of Phytomedicine 2024The aim of this study was to investigate the effects of swimming (S) training in water at 5°C (S5C) and 35°C (S35C) along with cinnamon (Cin) supplementationon liver...
OBJECTIVE
The aim of this study was to investigate the effects of swimming (S) training in water at 5°C (S5C) and 35°C (S35C) along with cinnamon (Cin) supplementationon liver enzymes and thyroid hormones in streptozotocin (STZ(-induced diabetic rats.
MATERIALS AND METHODS
In this experimental trial, 48 diabetic rats (55 mg/kg STZ) were divided into (1) diabetic control (CD), (2) S5C, (3) S5C+Cin, (4) S35C, (5) S35C+Cin and (6) Cin groups.Eight rats were placed in the healthy control (HC) group to evaluate the effects of diabetes induction on the research variables. Swimming training was performed at 5±2°C and 35±2°C for eight weeks, 3 days a week.For Cin supplementation, 200 mg/kg/day of the aqueous extract of cinnamon was dissolved in the animals drinking water. One-way analysis of variance with Tukey's test in Graphpad Prism software was used to analyze the findings.
RESULTS
S5C and S35C significantly increased thyroid-stimulating hormone (TSH), and decreased alkaline phosphatase (ALP) and alanine aminotransferase ALT)(p≤0.05). TSH levels in the S35C group were higher than the S5C group (p≥0.05); ALT levels in the S5C group were lower than the S35C group (p≥0.05). Also, Cin decreased AST and ALT levels (p≥0.05), while S35C+Cin decreased T3, ALP and ALT and S5C+Cin decreased ALP (p≥0.05).
CONCLUSION
It seems that training at different temperatures and consumption of cinnamon synergistically lead to improvement of liver enzymes and modulation of thyroid hormones. However, the effect of training in cold water and its impact on thyroid hormones is still unknown and needs further research.
PubMed: 38948171
DOI: 10.22038/AJP.2023.23248 -
Clinical Interventions in Aging 2024Serum trace elements and oxidative stress factors are related to diabetic microvascular complications. The study was to investigate the complex relationship between...
Malondialdehyde and Zinc May Relate to Severity of Microvascular Complications in Diabetes: A Preliminary Study on Older Adults with Type 2 Diabetes Mellitus in Northeast China.
BACKGROUND
Serum trace elements and oxidative stress factors are related to diabetic microvascular complications. The study was to investigate the complex relationship between trace elements, oxidative stress factors, and the severity of microvascular complications of diabetes in older adults.
METHODS
The present study included patients with or without type 2 diabetes, and blood glucose, blood lipids, trace elements (iron, magnesium, zinc), oxidative stress factors (malondialdehyde (MDA), nitric oxide (NO), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC)) were evaluated. Risk factors for the severity of diabetic microvascular complications in older adults with diabetes were also estimated.
RESULTS
There were statistically significant differences in fasting blood glucose (FBG), triglycerides (TG), low density lipoprotein (LDL), glycated hemoglobin (HbAlc), MDA, NO, SOD, T-AOC, magnesium, and zinc between the two groups (). Iron (r = 0.147, r = 0.180, r = 0.193, ) was positively correlated with zinc, SOD and T-AOC. Iron was negatively correlated with MDA (r = -0.146, ). Magnesium was positively correlated with SOD (r = 0.147, ). Zinc (r = 0.616, r = 0.575, ) was positively correlated with SOD and T-AOC. Zinc (r =-0.636, r=-0.616, ) was positively correlated with MDA and negatively correlated with NO. The course of disease (18.653, [5.726; 60.764], ), FBG (1.265, [1.059; 1.511], ), HbAlc (1.545, [1.431; 1.680], P <0.01), MDA (2.989, [1.900; 4.702], ) were risk factor for the severity of diabetic microvascular complications. Zinc (0.680, [0.503; 0.919], ) and SOD (0.820, [0.698; 0.964], ) were protective factors for the severity of diabetic microvascular complications.
CONCLUSION
Serum trace elements are related to oxidative stress levels in older adults with type 2 diabetes. The more stable trace element in older adults with diabetes, the lower the oxidative stress and the fewer microvascular complications of diabetes.
Topics: Humans; Diabetes Mellitus, Type 2; Male; Female; Aged; Zinc; China; Oxidative Stress; Malondialdehyde; Superoxide Dismutase; Middle Aged; Blood Glucose; Risk Factors; Diabetic Angiopathies; Glycated Hemoglobin; Nitric Oxide; Antioxidants; Magnesium; Lipids; Trace Elements; Severity of Illness Index
PubMed: 38948168
DOI: 10.2147/CIA.S464615