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PubMed2024

Genomic variants associated with type 2 diabetes mellitus among Filipinos.

Type 2 diabetes mellitus leads to debilitating complications that affect the quality of life of many Filipinos. Genetic variability contributes to 30% to 70% of T2DM risk. Determining genomic variants related to type 2 diabetes mellitus susceptibility can lead to early detection to prevent complications. However, interethnic variability in risk and genetic susceptibility exists. This study aimed to identify variants associated with type 2 diabetes mellitus among Filipinos using a case-control design frequency matched for age and sex. A comparison was made between 66 unrelated Filipino adults with type 2 diabetes mellitus and 121 without. Genotyping was done using a candidate gene approach on genetic variants of type 2 diabetes mellitus and its complications involving allelic association and genotypic association studies with correction for multiple testing. Nine (9) significant variants, mostly involved in glucose and energy metabolism, associated with type 2 diabetes mellitus in Filipinos were found. Notably, a CDKAL1 variant (rs7766070) confers the highest level of risk while rs7119 (HMG20A) and rs708272 (CETP) have high risk allele frequencies in this population at 0.77 and 0.66, respectively, making them potentially good markers for type 2 diabetes mellitus screening. The data generated can be valuable in developing genetic risk prediction models for type 2 diabetes mellitus to diagnose and prevent the condition among Filipinos.

Humans↗

PubMed2026

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.  Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans↗

PubMed2026

Genetic and Lifestyle Factors Influence High 1-Hour Plasma Glucose, a Predictor of Type 2 Diabetes Mellitus.

BACKGRUOUND: High 1-hour plasma glucose (1-h PG) level has been proposed by the International Diabetes Federation to identify high-risk individuals and diagnose type 2 diabetes mellitus (T2DM). In a longitudinal cohort, we examined T2DM risk, β-cell function, and the effects of genetic and lifestyle factors on high 1-h PG. METHODS: We analyzed 7,464 participants without T2D at baseline from a community-based prospective cohort in Korea, who underwent biennial 2-h 75-g oral glucose tolerance tests over 14 years. Incident T2D risk were assessed across 1-h PG groups: < 155, 155-208, and ≥ 209 mg/dL. In 6,588 participants with at least two 1-h PG measurements, we analyzed 1-h PG trajectories by T2D polygenic risk score (PRS; low, 1st quintile; intermediate, 2nd-4th quintiles; high, 5th quintile) and lifestyle, assessed using Life's Essential 8. RESULTS: Compared to the <155 mg/dL group, hazard ratios for T2DM were 3.34 (95% confidence interval [CI], 2.99 to 3.74; P<0.001) for 155-208 mg/dL, and 6.81 (95% CI, 5.81 to 7.98; P<0.001) for ≥209 mg/dL. Both groups had lower baseline disposition index compared to the <155 mg/dL group (57.3% and 72.7%, respectively; both P<0.001). Higher T2DM PRS was associated with elevated baseline 1-h PG (low: 131 mg/dL, intermediate: 141 mg/dL, high: 151 mg/dL) and faster increase in 1-h PG (1.36 vs. 1.85 vs. 2.21 mg/dL/year; all P<0.001). Importantly, healthy lifestyle attenuated the rate of increase across all PRS groups. CONCLUSION: High 1-h PG predicts T2DM risk and is associated with β-cell dysfunction. The 1-h PG level is influenced by genetic risk and can be modified with a healthy lifestyle.

Humans↗

PubMed2025

Screening of the key single nucleotide polymorphisms in type 2 diabetes mellitus complicated with lower extremity arterial disease by machine learning.

OBJECTIVES: Diabetic lower extremity arterial disease (LEAD) is a manifestation of diabetic lower extremity vascular complications. This study aimed to screen the key single nucleotide polymorphism (SNP) gene signature in patients with type 2 diabetes mellitus (T2DM) and LEAD. METHODS: A total of 147 patients with T2DM complicated by LEAD and 144 patients with T2DM without LEAD were enrolled for transcriptome sequencing. The Plink software was used to preprocess the data. Five machine learning methods were adopted to build the SNP diagnosis models. The receiver operating characteristic (ROC) curve was used to quantify the predicted probabilities of the model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the cluster Profiler package. Finally, regression statistical analysis was used to correlate the key SNPs with clinical information and biochemical indicators. RESULTS: A total of 24 SNPs were retained and 10 SNPs were risk allele genes. Nine SNPs (rs7412, rs1800629, rs699947, rs3918242, rs668, rs1800470, rs1800449, rs1800469, and rs1024611) were identified as the key SNPs sites. GO and KEGG pathway analyses revealed that these genes are mainly enriched in fluid shear stress and atherosclerosis. Finally, rs1800449 was associated with low-density lipoprotein cholesterol (LDL-C). With high density lipoprotein cholesterol (HDL-C), related site was rs1024611. The sites associated with total cholesterol (CHOL) were rs1800449 and rs7412.The site associated with apolipoprotein B (APOB) and apolipoprotein A1 (APOA1) were rs1800470 and rs1800469. CONCLUSION: This study authenticated nine SNPs for the diagnosis of T2DM patients with LEAD, which will be of great significance in the development of diagnostic molecular biomarkers for T2DM patients.

Humans↗

PubMed2003

Genetics and functional genomics of type 2 diabetes mellitus.

Genome-wide studies of transcription in the skeletal muscle of type 2 diabetic patients have identified coordinated changes in the expression of genes involved in oxidative phosphorylation, and have underlined the central role of the oxidative-phosphorylation regulator, PCG1alpha. These findings help unravel the complex pathogenesis and inheritance of polygenic type 2 diabetes mellitus.

Animals↗

PubMed2025

Meta-evolutionary exome analysis identifies novel type 2 diabetes mellitus genes in the UK Biobank and all of us.

Type 2 diabetes mellitus (T2DM) risk is heavily influenced by genetics, yet current association tests have explained only parts of its heritability. We developed MEVA (Meta-Evolutionary Action), a meta-analytic framework that integrates three complementary methods-EAML, Sigma-Diff, and GeneEMBED-to assess the functional burden of protein-coding variants using evolutionary data. MEVA was applied to exome data from 28,115 T2DM cases and 28,115 controls in the UK Biobank (UKB), identifying 101 genes (p < 1e-5). MEVA outperformed its component methods, each of which substantially outperformed a conventional burden test (MAGMA), in recovering known T2DM genes (AUROC = 0.925) and maintaining robustness in progressively smaller cohorts (AUROC = 0.917). MEVA showed significant enrichment for T2DM-related loci (p = 6.8e-10, p = 2.0e-34), protein interactions (z = 4.6, z = 4.2), pathways (p = 1.3e-6, z = 2.0), phenotypes (p = 1.3e-21, z = 9.1), and literature mentions (z = 7.2). Replication in 16,915 T2DM cases and 16,915 controls from All of Us (AoU) yielded 99 genes (p < 1e-5), 23 of which were also recovered in the UKB cohort - far exceeding random chance. These included established genes (SLC30A8, WFS1, HNF1A) and less-characterized candidates (NRIP1, ADAM30, CALCOCO2, TUBB1, ZFP36L2, WDR90). Notably, NRIP1 loss-of-function variants were associated with increased T2DM risk in both the UKB (OR = 1.09, FDR = 5.4e-4) and AoU (OR = 1.09, FDR = 0.046), and TUBB1 and CALCOCO2 gain-of-function variants showed consistent risk effects (FDR < 0.05). Pathway analyses revealed convergence on endoplasmic reticulum chaperone complexes (FDR = 0.02) and Hippo signaling (FDR = 8.5e-4). Finally, all 177 candidate genes were functionally prioritized using ten orthogonal criteria to guide experimental follow-up. These results demonstrate that combining complementary, impact-aware association tests increases sensitivity, improves replication, and expands the catalog of genetic risk factors for T2DM.

Humans↗

PubMed2025

Network pharmacology-based study on the mechanism of Tangfukang formula against type 2 diabetes mellitus.

OBJECTIVE: To explore the mechanism of Tangfukang formula (, TFK) in treating type 2 diabetes mellitus (T2DM). METHODS: We employed network pharmacology combined with experimental validation to explore the potential mechanism of TFK against T2DM. Initially, we filtered bioactive compounds with the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Symptom Mapping (SymMap), and gathered targets of TFK and T2DM. Subsequently, we constructed a protein-protein interaction (PPI) network, enriched core targets through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and adopted molecular docking to study the binding mode of compounds and the signaling pathway. Finally, we employed a KKAy mice model to investigate the effect and mechanism of TFK against T2DM. Biochemical assay, histology assay, and Western blot (WB) were used to assess the mechanism. RESULTS: There were 492 bioactive compounds of TFK screened, and 1226 overlapping targets of TFK against T2DM identified. A compound-T2DM-related target network with 997 nodes and 4439 edges was constructed. KEGG enrichment analysis identified some core pathways related to T2DM, including adenosine 5-monophosphate-activated protein kinase (AMPK) signaling pathway. Molecular docking study revealed that compounds of TFK, including citric acid, could bind to the active pocket of AMPK crystal structure with free binding energy of －4.8, －8 and －7.9, respectively. Animal experiments indicated that TFK decreased body weight, fasting blood glucose, fasting serum insulin, homeostasis model of insulin resistance, glycosylated serum protein, total cholesterol, triglyceride, and low-density lipoprotein cholesterol, and improve oral glucose tolerance test results. TFK reduced steatosis in liver tissue, and infiltration of inflammatory cells, and protected liver cells to a certain extent. WB analysis revealed that, TFK upregulated the phosphorylation of AMPK and branched-chain α-ketoacid dehydrogenase proteins. CONCLUSION: TFK has the potential to effectively manage T2DM, possibly by regulating the AMPK signaling pathway. The present study lays a new foundation for the therapeutic application of TFK in the treatment of T2DM.

Diabetes Mellitus, Type 2↗

PubMed2026

Apoptosis protein markers in comorbid type 2 diabetes mellitus and depression; relationships with cognitive performance, incident dementia, and white matter hyperintensities.

Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) are reciprocal risk factors, and both elevate dementia risk. Dysregulation of programmed cell death is implicated in T2DM, MDD, and neurodegeneration, but proteomic markers of apoptosis have yet to be studied as dementia predictors in people with T2DM and/or MDD. This study examines apoptosis markers in comorbid T2DM and MDD, and their associations with cognitive, dementia, and neuroimaging outcomes. The retrospective sample (n = 15,765) consisted of UK Biobank participants (MDD only n = 1230; T2DM only n = 3644; comorbid T2DM + MDD n = 721). Individuals with T2DM + MDD comorbidity had poorer cognitive performance, and a higher 15-year dementia incidence (HR = 4.44, 95% CI = [3.23,6.11]). Among 60 apoptosis-related proteins identified by Kyoto Encyclopedia of Genes and Genomes pathway enrichment, 41 were significantly up-regulated in comorbid T2DM + MDD relative to controls, and 4 were higher in the comorbid group than both T2DM alone and MDD alone. Tumor necrosis factor ligand superfamily member 10 (TNFSF10), growth arrest and DNA damage-inducible protein GADD45 beta, tumor necrosis factor ligand superfamily member 6, and RAC-gamma serine/threonine-protein kinase were associated with dementia risk. Nine proteins (e.g. apoptosis-inducing factor 1, mitochondrial, caspase-2, mitogen-activated protein kinase kinase kinase 5, TNFSF10), were associated with white matter hyperintensity volumes in comorbid T2DM + MDD after FDR correction, but none were associated with cognitive performance, atrophy, or white matter microstructural changes. These findings identify peripheral apoptosis markers that were further elevated in comorbid T2DM + MDD compared to either alone, pointing to an important pathophysiological element underlying adverse outcomes in the context of mood and metabolic comorbidity.

Humans↗

PubMed2026

Lifestyle Combination Patterns as Key Modifiable Factors for Type 2 Diabetes Mellitus Risk among Middle-Aged Korean Men.

BACKGRUOUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) worldwide highlights the need to understand risk factors and effective prevention strategies. Although individual lifestyle factors associated with diabetes risk have been identified, research on their collective interactions is limited. This study aimed to identify lifestyle combination patterns in middle-aged Korean men and evaluate their impact on T2DM risk. METHODS: A total of 2,332 middle-aged men without T2DM at baseline (2001-2002) from the Korean Genome and Epidemiology Study (KoGES) cohort were included. T2DM incidence was tracked through the 8th follow-up survey (2017-2018). Lifestyle combination patterns were identified using factor analysis based on sociodemographic, lifestyle, and dietary data. Cox regression was used to assess T2DM incidence across patterns. RESULTS: Four lifestyle combination patterns were identified: 'Healthy Lifestyle,' 'Low Carb & High Protein,' 'High SES & Irregular Lifestyle,' and 'Bad Eating Habits.' The risk of developing T2DM varied across patterns. The 'Healthy Lifestyle' and 'Low Carb & High Protein' patterns showed a slight decrease in risk in T3, but the differences were not significant. The 'High SES & Irregular Lifestyle' pattern was associated with a higher T2DM risk in T3 than in T1 (hazard ratio [HR], 1.25; 95% confidence interval [CI], 1.05 to 1.55), but the association was attenuated after adjustment for family history. The 'Bad Eating Habits' pattern showed a 1.21-fold higher risk in T3 (HR, 1.21; 95% CI, 1.01 to 1.47). CONCLUSION: This study underscores the existence of distinct lifestyle combination patterns and their differential implications for T2DM risk. These findings support the need for tailored preventive strategies based on lifestyle patterns.

Humans↗

PubMed2025

Association of Calpain-10 gene polymorphisms with Type 2 diabetes mellitus: a case-control study from a tertiary care hospital in Pakistan.

INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a major public health challenge, with rising prevalence in low- and middle-income countries such as Pakistan. Genetic susceptibility plays a critical role in its pathogenesis. Calpain-10 (CAPN-10), a gene implicated in insulin secretion and glucose homeostasis, has been studied for its potential involvement in T2DM. This study aimed to evaluate the association of CAPN-10 polymorphisms-SNP44 (rs2975760) and SNP43 (rs3792267)-with T2DM in a Pakistani cohort. METHODS: This case-control study included 164 T2DM patients and 164 healthy controls (mean age ± SD: 57.2 ± 8.2 vs. 53.9 ± 6.3 years; age range: 41-82 years). The male-to-female ratio was 41.4-58.6% in cases and 37.2-62.8% in controls. Participants were enrolled using non-probability convenience sampling. Genomic DNA was extracted from whole blood, and genotyping of CAPN-10 SNPs (rs3792267 and rs2975760) was performed using PCR-RFLP. Genotype distributions were assessed for Hardy-Weinberg equilibrium. Associations with T2DM were evaluated using odds ratios (ORs) and 95% confidence intervals (CIs) via logistic regression. Chi-square tests were used for categorical comparisons, with p < 0.05 considered statistically significant. Analyses were conducted using SPSS version 26. RESULTS: For SNP44, no significant association with T2DM was observed under dominant, heterozygous, or recessive models after Bonferroni correction (adjusted p > 0.05). Similarly, SNP43 showed no statistically significant association with T2DM in either dominant or recessive models (adjusted p > 0.05), although the AA genotype appeared more frequently among T2DM cases. These findings suggest no significant role of CAPN-10 polymorphisms in T2DM susceptibility in this population. CONCLUSION: CAPN-10 polymorphisms SNP44 and SNP43 showed no significant association with T2DM in this population, suggesting limited predictive value for disease susceptibility.

Humans↗

PubMed2025

Proteomics-enabled learning machine algorithms enhance the prediction of cardiovascular diseases in patients with type 2 diabetes mellitus.

BACKGROUND AND AIMS: Estimating the risk of cardiovascular disease (CVD) complications in type 2 diabetes mellitus (T2DM) patients is critical in the medical decision-making process. This study aimed to use a machine learning technique combined with proteomics to develop personalized models for predicting CVD in patients with T2DM. METHODS AND RESULTS: In total, 874 patients with T2DM and 2,920 Olink proteins obtained from the UK Biobank were used in this study. Proteins were screened using Cox regression and LASSO regression. A basic model containing clinical features and a full model combining proteome and clinical features were constructed using the random survival forest algorithm. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive performance of the models and compare them with other CVD predictive models. Compared with the basic model, the full model performed better in predicting CVD, with time-dependent AUCs of 0.81 (3 years), 0.74 (5 years) and 0.74 (10 years) (0.77, 0.69 and 0.67). We calculated the risk scores of the Framingham, ASCVD and Score2-Diabetes models. The results revealed that the prediction performance of the full model was also better than that of the abovementioned models. In terms of differentiation accuracy, the results of the net reclassification improvement index and integrated discrimination improvement index showed that the full model can identify high-risk individuals more accurately (accuracy rate: 79% vs. 69%). CONCLUSIONS: Proteomics can be used to predict cardiovascular complications in diabetic patients. It is also necessary to consider the applicability of the model due to the limitations of the sample size and the constraints of proteomics in clinical applications.

Humans↗

PubMed2026

Common Molecular Mechanisms and Candidate Drug Targets in Type 2 Diabetes Mellitus and Atherosclerotic Cardiovascular Disease.

This study examined the mechanisms underlying the comorbidity between type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD), while identifying potential therapeutic targets. Common differentially expressed genes (C-DEGs) between T2DM and ASCVD were extracted from the GSE78721 and GSE12288 datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, protein-protein interaction (PPI) network construction, hub gene identification, and Drug-Gene Interaction Database (DGIdb) analysis were conducted. The association between hub C-DEGs and immune-infiltrating cells was analyzed using the CIBERSORT method. Expression levels of hub C-DEGs were quantified through qRT-PCR and Western blot analyses. A total of 32 C-DEGs were identified, comprising 20 upregulated and 12 downregulated genes. C-DEGs were predominantly enriched in key pathways, including viral myocarditis, arrhythmogenic right ventricular cardiomyopathy, hypertrophic cardiomyopathy, and dilated cardiomyopathy. PPI analysis revealed 29 nodes and 39 edges, leading to the identification of eight hub C-DEGs (HSP90B1, PLAU, SLPI, TOP3A, NCF4, PRF1, TUBA1C, and CS) across both datasets. Furthermore, hub C-DEGs (TOP3A, SLPI, NCF4, PRF1, and PLAU) demonstrated significant correlations with immune-infiltrating cell levels. Drugs specifically targeting these hub C-DEGs present promising candidates for the treatment of T2DM and ASCVD. Additionally, the expression of hub C-DEGs at both mRNA and protein levels was validated in patients with T2DM and ASCVD. An integrated bioinformatics analysis facilitated the screening of candidate therapeutic targets, mechanisms, and drugs for T2DM and ASCVD, offering new insights into molecular therapies for these conditions.

Diabetes Mellitus, Type 2↗

PubMed2025

Treatment preference for once-weekly versus once-daily DPP-4 inhibitors in patients with type 2 diabetes mellitus: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND/OBJECTIVE: Although once-weekly and once-daily DPP-4 inhibitors have gained widespread market recognition, patient preference differences remain a key focus. This meta-analysis compares treatment preferences for once-weekly versus once-daily DPP-4 inhibitors in T2DM, offering evidence to guide clinical decisions and healthcare policies. METHODS: PubMed, OVID, EBSCO, Web of Science, CNKI, Wanfang, and clinical trial registries were searched up to June 30, 2025. After screening literature against predefined criteria, a systematic review was conducted to compare the effects of once-weekly and once-daily DPP-4 inhibitors on the treatment preferences of patients with T2DM. RESULTS: 8 RCTs with 1,575 participants were analyzed. No significant difference in medication adherence and DTSQ total score between the once-weekly and once-daily groups (p > 0.05). HbA1c percentage (MD = -0.21, 95% CI [-0.42, -0.01], p < 0.05) decreased significantly with once-weekly dosing, while GA and FPG showed no change (p > 0.05), this suggests greater improvement in HbA1c percentage levels following a switch to once-weekly DPP-4 inhibitors. Once-weekly DPP-4 inhibitors showed higher musculoskeletal/connective tissue disorder risk (RR = 2.63; 95% CI [1.18, 5.83]), but no significant differences in other adverse events (p > 0.05). No significant differences in treatment burden between both groups (p > 0.05). CONCLUSION: No statistically significant association between treatment preferences for once-weekly versus once-daily DPP-4 inhibitors among T2DM patients and medication adherence, treatment satisfaction, glycemic level changes, safety, or treatment burden for these two dosing regimens. Further research is needed to elucidate the influence of physician prescribing behavior on these preferences.

Humans↗

PubMed2026

Comparative evaluation of oxidative stress biomarkers F2-isoprostanes and 8-OHdG in Parkinson's disease and Type 2 Diabetes Mellitus: a systematic review and meta-analysis of human studies.

BACKGROUND: Oxidative stress is central to type 2 diabetes mellitus (T2DM) and Parkinson's disease (PD). However, the utility of biomarkers for lipid peroxidation (F2-isoprostanes) and DNA damage (8-OHdG) in the comorbidity of PD and T2DM remains unclear. METHODS: We conducted a systematic review and meta-analysis of 54 unique studies of human subjects aged ≥ 50 years (n = 7,521: 3,522 with T2DM, 722 with PD, and 3,277 controls), measuring biomarkers in serum, plasma, or leukocytes. Mixed-effects models quantified standardized differences (Hedges' g) across subgroups. RESULTS: In T2DM, F2-isoprostanes (g = 1.60, 95% CI: 0.95-2.25) and 8-OHdG (g = 2.64, 95% CI: 2.13-3.14) were markedly elevated (p < 0.001). Stronger effects were observed in younger cohorts and serum/plasma samples, with complications like nephropathy exhibiting extreme oxidative stress (g = 5.24). In PD, 8-OHdG was moderately elevated (g = 0.78, 95% CI: 0.18-1.39; p = 0.011), particularly in randomized controlled trials and plasma samples, whereas F2-isoprostanes were not significantly elevated (g = 0.47, 95% CI: -0.43-1.38). High heterogeneity in T2DM (I2 > 90%) reflected methodological variability. CONCLUSION: Distinct profiles - both markers elevated in T2DM but only 8-OHdG in PD - underscore 8-OHdG's potential in PD-T2DM comorbidity. Future research should focus on standardized assays, multi-compartmental or multi-modal sampling, and longitudinal studies to clarify mechanisms and therapeutic targets.

Humans↗

PubMed2026

Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, andexperiments.

OBJECTIVE: To investigate the mechanism of action of Qinlian Jiangxia decoction (, QLJXD) in the treatment of type 2 diabetes mellitus (T2DM) complicated by hyperlipidemia using network pharmacology, molecular docking, molecular dynamics simulation and in vivo experiments. METHODS: Drug components, targets and disease targets were identified using databases such as TCM systems pharmacology database and analysis platform and GeneCards. The intersecting targets were subjected to protein-protein interaction analysis using the search tool for the retrieval of interacting genes/proteins database. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersecting targets were conducted using the Metascape platform to identify core components and targets. The results were validated using molecular docking, molecular dynamics simulations and in vivo experiments. RESULTS: QLJXD contains 76 active ingredients and 136 disease targets. The core ingredients are quercetin, β-sitosterol, wogonin and baicalein, while the core targets are fatty acid binding protein 4 (FABP4) and peroxisome proliferative activated receptor gamma (PPARG). Molecular docking and molecular dynamics simulations revealed that the core ingredients bound well to the core targets. Animal experiments demonstrated that QLJXD effectively inhibited the expression of FABP4 and increased the expression of PPARG, thereby enhancing disorders of glycolipid metabolism. CONCLUSION: The putative therapeutic efficacy of QLJXD in the management of T2DM complicated with hyperlipidemia may be ascribed to the synergistic actions of multiple components, such as quercetin, β-sitosterol, wogonin, and baicalein, which collectively modulate FABP4 and PPARG molecular targets.

Molecular Docking Simulation↗

PubMed2026

Metformin Adherence and Risk of Polyneuropathy in Type 2 Diabetes Mellitus: An International Matched Cohort Study with Independent Validation.

BACKGROUND: Metformin is a popular first-line glucose-lowering medication for type 2 diabetes mellitus (T2DM). Although metformin reduces the risks of various complications of diabetes, its potential to cause polyneuropathy by depleting vitamin B12 levels is concerning. This study investigated whether the adherence or discontinuation of metformin after adding-on a second-line antiglycemic agent increases the risk of polyneuropathy in patients with T2DM. METHODS: Data from TriNetX were obtained, and patients with T2DM who were receiving second-line antiglycemic agents were divided into metformin-adherent and metformin-nonadherent groups based on prescription claims data. Neuropathy incidence was evaluated using diagnostic claims and nerve conduction examinations. For independent confirmation and external validation of the primary findings, we used data from the National Health Insurance Research Database (NHIRD) of Taiwan. RESULTS: After matching, 58,027 patients were included in each group. Compared with metformin adherent patients, metformin nonadherent patients had a higher risk of polyneuropathy (adjusted hazard ratios [aHR] 1.26; 95% confidence interval [CI] 1.23-1.29; P < 0.001). Risks of diabetic foot ulcer, amputation, neuropathy-related medication use, and bone fracture were also higher among nonadherent patients. Sensitivity analyses confirmed the robustness of findings. In the validation NHIRD cohort (31,384 matched pairs), metformin nonadherence remained associated with increased polyneuropathy risk (aHR 1.25; 95% CI 1.10-1.42; P < 0.001). CONCLUSIONS: Metformin adherence in patients with T2DM who require second-line treatment may reduce the risk of polyneuropathy; vitamin B supplementation may enhance this benefit.

Humans↗

PubMed2026

Mobile health apps improve Health-Related Quality of Life in Type 2 Diabetes Mellitus by enhancing medication adherence: A multicentre randomised controlled trial with mediation analysis.

AIMS: This study evaluated whether a gamified mHealth application (CareAide®) improves Health-Related Quality of Life (HRQoL) in Type 2 Diabetes Mellitus (T2DM) and whether this effect is mediated by medication adherence. METHODS: Prespecified secondary analysis of the T2DM cohort from a 6-month multicentre RCT (NCT06068309; N = 663; three Malaysian hospitals). Participants were randomised 1:1 to standard care or CareAide®. Adherence (MMAS-8), EQ-5D-5L utility (Malaysian value set), and AQoL-6D were assessed at baseline and 6 months. Simple mediation analysis (PROCESS Model 4; 5000 bootstraps) adjusted for baseline HRQoL. RESULTS: CareAide® significantly predicted higher MMAS-8 scores (mean difference +1.756; d = 1.638; p < 0.001). Higher MMAS-8 scores significantly predicted improved AQoL-6D utility (b = 0.024; p < 0.001). The direct effect on AQoL-6D was non-significant (p = 0.248). Bootstrapped indirect effect confirmed full mediation via AQoL-6D (0.042; 95% CI [0.024, 0.060]). A sensitivity analysis adjusting for baseline HbA1c confirmed full mediation (indirect = 0.034; 95% CI [0.015, 0.052]; n = 563). EQ-5D-5L utility showed a significant direct between-group difference at 6 months (p = 0.012) but did not operate as a mediation outcome. CONCLUSIONS: Medication adherence fully mediates the AQoL-6D HRQoL benefit of a gamified mHealth intervention in T2DM, as confirmed by both the primary and HbA1c-adjusted sensitivity analyses. These findings support integration of behaviourally informed digital adjuncts into routine primary diabetes care.

Humans↗

PubMed2026

Efficacy of dapagliflozin on hepatic steatosis and fibrosis in patients with type 2 diabetes mellitus and metabolic dysfunction-associated steatotic liver disease: a pre-specified single-arm analysis from a randomized controlled trial.

AIM: To evaluate the association of dapagliflozin therapy with changes in hepatic steatosis and non-invasive fibrosis surrogate markers in patients with type 2 diabetes mellitus (T2DM) and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) over 12 months. METHODS: This is a pre-specified single-arm analysis from a randomised, open-label, parallel-group trial. Of 54 participants randomised to dapagliflozin 10 mg daily, 50 (92.6%) completed the 12-month follow-up and were included in the per-protocol analysis. Assessments at baseline, 3, 6, and 12 months included transient elastography (CAP and LSM), ultrasonography, and biochemical tests. Primary endpoints were changes in hepatic steatosis (CAP) and non-invasive fibrosis surrogates (LSM). RESULTS: Significant reductions were observed in hepatic steatosis (CAP: 316.7 to 245.7 dB/m; mean change - 71.02 dB/m, 95% CI: -63.4 to - 78.6; p < 0.001) and in liver stiffness as a non-invasive fibrosis surrogate (LSM: 8.59 to 7.28 kPa; mean change - 1.31 kPa, 95% CI: -0.92 to - 1.70; p < 0.001). Improvements were also observed in glycaemic control, body weight, lipid profile, liver enzymes, ultrasonographic steatosis grading, and serum fibrosis markers. Genitourinary infections were the most frequently reported adverse events (32%); no serious adverse events were recorded. CONCLUSIONS: Dapagliflozin was associated with significant improvements in hepatic steatosis, non-invasive fibrosis surrogate markers, metabolic parameters, and liver function in T2DM patients with MASLD over 12 months. These findings provide region-specific evidence for an Indian population and support further controlled investigation. However, these findings should be interpreted in light of the pre-specified single-arm design of this analysis, the open-label methodology, relatively small sample size, and the absence of liver biopsy confirmation.

Humans↗