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Aims/Introduction: Research has suggested that vitamin D deficiency is associated with diabetic retinopathy (DR). Our study aimed to determine whether vitamin D deficiency is the cause of diabetic retinopathy or if diabetic retinopathy reduces vitamin D levels. Materials and Methods: Participants with type‐2 diabetes were recruited for this prospective observational clinical study and were divided into a diabetic group without retinopathy and a diabetic group with retinopathy, with additional healthy volunteers serving as a control group. The differences in clinical characteristics among the three groups were also compared. Patients without retinopathy were then followed for 1 year to monitor the incidence of diabetic retinopathy. After follow‐up, participants were divided into subgroups based on whether diabetic retinopathy occurred. The baseline data of the subgroups were compared, and the independent risk factors were analyzed. Results: Vitamin D levels were generally low. Participants with diabetic retinopathy had significantly lower vitamin D levels than did those without retinopathy (P < 0.01). A comparison of the two subgroups revealed lower baseline vitamin D concentrations in the new‐DR subgroup than in the non‐DR subgroup (P < 0.01). Vitamin D deficiency and elevated HbA1c levels were found to be independent risk factors for diabetic retinopathy (OR = 0.935, 95% CI: 0.867–0.981, P = 0.006; OR = 2.208, 95% CI: 1.764–2.764, P < 0.01). The limit of vitamin D intake according to the receiver‐operating characteristic (ROC) curve was 26.01 ng/mL, and the area under the ROC curve was 0.603 (95% CI: 0.559–0.706, P = 0.002). Conclusions: Vitamin D levels were significantly lower in patients diagnosed with diabetic retinopathy. More importantly, vitamin D deficiency may accelerate the onset of diabetic retinopathy. [ABSTRACT FROM AUTHOR]

Obesity and its related metabolic complications represent a significant global health challenge. Central to this is the dysregulation of glucolipid metabolism, with a predominant focus on glucose metabolic dysfunction in the current research, whereas adipose metabolism impairment garners less attention. Exosomes (EXs), small extracellular vesicles (EVs) secreted by various cells, have emerged as important mediators of intercellular communication and have the potential to be biomarkers, targets, and therapeutic tools for diverse diseases. In particular, EXs have been found to play a role in adipose metabolism by transporting cargoes such as noncoding RNAs (ncRNA), proteins, and other factors. This review article summarizes the current understanding of the role of EXs in mediating adipose metabolism disorders in obesity. It highlights their roles in adipogenesis (encompassing adipogenic differentiation and lipid synthesis), lipid catabolism, lipid transport, and white adipose browning. The insights provided by this review offer new avenues for developing exosome-based therapies to treat obesity and its associated comorbidities. [ABSTRACT FROM AUTHOR]

Background: Diabetic peripheral neuropathy (DPN) is a common complication of Type 2 diabetes mellitus (T2DM), which frequently results in disabling neuropathic pain and lower‐limb amputation. The identification of noninvasive biomarkers for DPN may help early detection and individualized treatment of DPN. Methods: In this study, we identified differentially expressed genes (DEGs) between DPN and the control based on blood‐source (GSE95849) and tissue‐source gene expression profiles (GSE143979) from the Gene Expression Omnibus (GEO) database using limma, edgeR, and DESeq2 approaches. KEGGG and GO functional enrichments were performed. Hub genes and their correlation with infiltrating immune cells were analyzed. Real‐time quantitative polymerase chain reaction (RT‐qPCR) was used to quantify hub gene expression. Results: In total, 144 DEGs between DPN and the control were identified. Functional enrichment revealed that the DEGs were mainly enriched in immune‐related pathways like the Fc epsilon receptor Ig signaling pathway. By protein–protein interaction (PPI) network analysis, FCER1G, SYK, ITGA4, F13A1, MS4A2, and PTK2B were screened as hub genes with higher expression in DPN patients, among which half were immune genes (FCER1G, PTK2B, and SYK). RT‐qPCR demonstrated that mRNA expression of FCER1G, PTK2B, and SYK was significantly increased in patients with DPN compared with both diabetic nonperipheral neuropathy (DNN) and normal subjects. The area under the receiver operating characteristic (ROC) curve of FCER1G, PTK2B, and SYK was 0.84, 0.81, and 0.73, respectively, suggesting their great advantages as diagnostic biomarkers to predict the progression of neuropathy in T2DM. Further analysis indicated that the expression of FCER1G, PTK2B, and SYK was negatively correlated with the cell proportion of significantly altered resting natural killer cells, T follicular helper cells, and activated mast cells, but positively correlated with monocytes. Conclusions: Our findings demonstrated FCER1G, PTK2B, and SYK are potential diagnostic biomarkers and therapeutic targets for DPN, which provides new insight into DPN pathogenesis and therapies. [ABSTRACT FROM AUTHOR]

Aims: Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We aimed to synthesize the available data to assess the diagnostic utility of lncRNAs for identification of type 2 diabetes mellitus and its consequences. Materials and Methods: We performed a systematic review and meta‐analysis, searching PubMed, Embase, and Web of Science for articles published from September 11, 2015 to December 27, 2022. We evaluated human case–control or cohort studies on differential lncRNA expression in type 2 diabetes mellitus or its associated comorbidities. We excluded studies if they were non‐peer reviewed or published in languages other than English. From 2387 identified studies, we included 17 (4685 participants). Results: Analysis of the pooled data showed that lncRNAs had a diagnostic area under the curve (AUC) of 0.84 (95% CI: 0.80–0.87), with a sensitivity of 0.79 (95% CI: 0.74–0.83) and a specificity of 0.75 (95% CI: 0.69–0.80). LncRNAs had an AUC of 0.65 for the diagnosis of prediabetes, with 82% sensitivity and 65% specificity. Conclusions: LncRNAs may be promising diagnostic markers for type 2 diabetes mellitus and its complications. [ABSTRACT FROM AUTHOR]