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PubMed2026

Protective association of the ELMO1 rs741301 variant against diabetes mellitus and diabetic nephropathy: a systematic meta-analysis of case-control studies.

CONTEXT: Diabetes mellitus (DM), an endocrine disorder, is characterised by persistently elevated blood glucose levels due to inadequate insulin production. Diabetic nephropathy (DN), is a critical complication associated with DM, often leading to end-stage renal failure and increased mortality. OBJECTIVE: This meta-analysis aimed to evaluate the association between the ELMO1 rs741301 polymorphism and susceptibility to DN among individuals with diabetes. METHOD: A systematic literature search was conducted for studies published between 2014 and 2024 using Embase, Google Scholar, and PubMed. Eligible case-control studies investigating the association between ELMO1 rs741301 and DN among individuals with DM were selected according to predefined inclusion criteria. Nine case-control studies comprising 880 individuals with DM and 1008 individuals with DN were included in the meta-analysis. RESULTS: The pooled analysis demonstrated a significant protective association between the ELMO1 rs741301 polymorphism and DN under the allelic model (OR = 0.77, 95% CI: 0.67-0.88), recessive model (OR = 0.74, 95% CI: 0.61-0.90), and dominant model (OR = 0.68, 95% CI: 0.53-0.88). In contrast, no statistically significant association was observed under the over-dominant model. CONCLUSION: The findings suggest that the ELMO1 rs741301 polymorphism may be associated with a reduced susceptibility to DN among individuals with DM. These findings provide evidence for a potential genetic contribution of ELMO1 to DN susceptibility and may help improve understanding of the genetic factors underlying diabetic complications. Further well-designed studies in diverse populations are warranted to validate this association.

Humans↗

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↗

PubMed2025

Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.

Diabetes mellitus encompasses several disorders, each with differing clinical presentation, prognoses and pathophysiology. Distinct polygenic architectures underlie type 1 diabetes mellitus and type 2 diabetes mellitus, and govern numerous pathophysiological pathways that converge on dysglycaemia. Over the previous decade, polygenic risk scores (PRS) derived from large genome-wide association studies have become broadly recognized for their potential in precision medicine. PRS, and now partitioned polygenic scores generated by clustering of risk variants, can quantify individual genetic predisposition to diabetes mellitus and reveal molecular heterogeneity responsible for variation in clinical presentation and prognoses. In this Review, we examine and contrast progress in the development of type 1 diabetes mellitus PRS and type 2 diabetes mellitus PRS, and discuss paths to further methodological advances. We examine how studies in the past 10 years have harnessed PRS and novel partitioned polygenic scores to reveal insights into diabetes mellitus aetiology and characterize changes in cellular and tissue-specific disease-modifying molecular pathways. Additionally, we discuss advances and opportunities in areas of clinical translation, including improved classification of diabetes mellitus type, screening of those at risk and personalized interventions informed by PRS. Finally, we emphasize the urgent need to overcome ancestry-related challenges and highlight current progress and gaps in ensuring the equitable translation of PRS for diabetes mellitus precision medicine.

Humans↗

PubMed2026

A three-metabolite microbiota-associated signature for early risk stratification of gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes and long-term metabolic and cardiovascular risk. However, oral glucose tolerance testing at 24-28 gestational weeks limits early risk stratification. Gut microbiota-associated metabolites may reflect early metabolic abnormalities, including those relevant to cardiometabolic health, but robust early-pregnancy biomarkers remain limited. METHODS: We conducted a multicenter nested case-control and prospective study involving 2,693 pregnant women. Untargeted metabolomics and metagenomics were integrated to identify GDM-associated metabolites and gut microbial alterations. Three consistently dysregulated metabolites, 3-hydroxydecanoic acid, γ-Glu-Leu, and propionic acid, were quantified by targeted LC-MS/MS. Candidate algorithms were compared using repeated 10-fold cross-validation, and a final generalized linear model was externally and prospectively validated. RESULTS: Women who later developed GDM showed an adverse early-pregnancy metabolic profile, including higher BMI, triglycerides, and platelet count. Untargeted metabolomics identified 14 persistently altered metabolites enriched in energy, oxidative stress, and amino acid metabolism pathways. Metagenomics revealed taxonomic restructuring and coordinated microbiota-metabolite associations. The three-metabolite model achieved AUCs of 0.838 (95% CI, 0.791-0.885) in training, 0.840 (95% CI, 0.769-0.911) in internal validation, 0.955 (95% CI, 0.925-0.985) and 0.917 (95% CI, 0.875-0.958) in two external cohorts, and 0.969 (95% CI, 0.937-1.000) in the prospective cohort. CONCLUSION: Early microbiota-associated metabolic dysregulation is detectable before routine GDM diagnosis. This compact three-metabolite panel may support early GDM risk stratification and provides metabolic evidence relevant to broader cardiometabolic risk assessment in pregnancy.

Humans↗

PubMed2024

Association between OX40L polymorphism and type 2 diabetes mellitus in Iranians.

INTRODUCTION: Diabetes mellitus (DM) is one of the leading causes of morbidity and mortality worldwide. It is a multifactorial disease that genetic and environmental factors contribute to its development. The aim of the study was to investigate the association of OX40L promoter gene polymorphisms with type 2 diabetes mellitus (T2DM) in Iranians. MATERIALS AND METHODS: Three hundred and sixty-eight subjects including 184 healthy subjects and 184 T2DM patients were enrolled in our study. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was applied to detect genotype and allele frequencies of rs3850641, rs1234313 and rs10912580. In addition, SNPStats web tool was applied to estimate haplotype frequency and linkage disequilibrium (LD). RESULTS: The distribution of tested polymorphisms was statistically different between the T2DM patients and healthy subjects (P < 0.01). rs1234313 AG (OR = 0.375, 95% CI = 0.193-0.727, P = 0.004) and rs10912580 AG (OR = 0.351, 95% CI = 0.162-0.758, P = 0.008) genotypes were associated with the decreased risk of T2DM in Iranians. Moreover, our prediction revealed that AAG (OR = 0.46, 95% CI= (0.28-0.76), P = 0.0028) and GAG (OR = 0.24, 95% CI= (0.13-0.45), P < 0.0001) haplotypes were related to the reduced risk of the disease. However, the tested polymorphisms had no effect on biochemical parameters and body mass index (BMI) in the patient group (P > 0.05). CONCLUSION: Our findings revealed that OX40L promoter gene polymorphisms are associated with T2DM. Moreover, genotype and allelic variations were related to the decreased risk of T2DM in Iranians. Further studies are recommended to show whether these polymorphic variations could affect OX40/OX40L interaction or OX40L phenotype.

Adult↗

PubMed2026

Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.

Type 1 diabetes (T1D) is a chronic metabolic disease mediated by autoimmunity. Its pathogenesis involves complex interactions between genetic susceptibility and environmental factors. Conventional T1D risk stratification primarily relies on genetic markers, islet autoantibodies, and glycemic indicators. Although these biomarkers remain indispensable in current clinical practice, they are often insufficient when used alone to accurately identify ultra-early high-risk individuals, predict disease progression rates, or support individualized preventive strategies. Consequently, more comprehensive molecular approaches are needed to improve precision risk stratification. In recent years, the rapid development of multi-omics technologies has provided new strategies for precise risk stratification of T1D. This narrative review critically evaluates how multi-omics integration strategies can improve precision risk stratification throughout the T1D disease continuum by integrating complementary molecular information from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and the microbiome. Particular emphasis is placed on stage-specific biomarker discovery, multi-omics data integration frameworks, artificial intelligence-assisted prediction models, biomarker validation, and the opportunities and challenges associated with clinical translation. Current evidence suggests that integrated multi-omics approaches have the potential to improve risk prediction accuracy, distinguish heterogeneous disease trajectories, identify individuals at imminent risk of progression, and provide biologically informed targets for precision intervention. However, important challenges remain, including data harmonization, external validation, model interpretability, cost-effectiveness, and integration into routine clinical screening programs. Future research should prioritize prospective multicenter cohorts, standardized analytical pipelines, externally validated prediction models, and clinically interpretable multi-omics frameworks to facilitate the translation of precision risk stratification into routine T1D prevention and management.

Humans↗

PubMed2026

Molecular and Genomic Mechanisms Linking Diabetes Mellitus and Periodontitis: From Pathogenesis to Translational Opportunities.

Diabetes mellitus and periodontitis are bidirectionally associated chronic disorders linked through metabolic dysregulation, host inflammation, microbial dysbiosis, and impaired tissue remodeling. This review summarizes clinical, molecular, cellular, genomic, epigenomic, transcriptomic, and microbial evidence concerning the mechanisms underlying this relationship and their potential translational relevance. Chronic hyperglycemia is associated with advanced glycation end product signaling through the receptor for advanced glycation end products, mitogen-activated protein kinase/nuclear factor-κB activation, reactive oxygen species production, oxidative stress, and NLR family pyrin domain-containing 3 inflammasome activation, which may contribute to enhanced cytokine responses and periodontal tissue injury. Diabetes is also associated with altered neutrophil and macrophage function, increased T helper 17/interleukin-17 signaling, and an elevated receptor activator of nuclear factor-κB ligand/osteoprotegerin ratio, thereby favoring osteoclastogenesis and alveolar bone loss. Conversely, periodontal inflammation and microbial products may contribute to systemic low-grade inflammation, insulin resistance, and metabolic dysregulation. Multi-omics studies have identified shared susceptibility loci, regulatory networks, and disease-associated cell states, although their causal and clinical significance remains incompletely defined. These findings suggest potential roles for integrated medical-dental care, glycemic screening in dental settings, periodontal inflammation control, host-modulatory therapies, and regenerative biomaterials. Further longitudinal and experimental studies are needed to determine their clinical applicability.

Humans↗

PubMed2026

Genomic, virulent and phenotypic characterization of a cerebrospinal fluid-derived ST86-KL2 hypervirulent Klebsiella pneumoniae isolate from a patient with meningitis and diabetes mellitus.

BACKGROUND: Hypervirulent Klebsiella pneumoniae (hvKP) is an important cause of invasive community-acquired infection, particularly in individuals with diabetes mellitus. However, cerebrospinal fluid (CSF)-derived hvKP isolates, especially those belonging to the ST86-KL2 lineage, remain poorly characterized at the integrated clinical, genomic, and phenotypic levels. METHODS: A K. pneumoniae isolate, designated BP9811, was recovered from the CSF of a patient with meningitis and diabetes mellitus and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and 16 S rRNA sequencing. Antimicrobial susceptibility testing and whole-genome sequencing were performed to define its resistance, virulence, sequence type (ST), capsular type, and plasmid content. Virulence was evaluated using the Galleria mellonella infection model. In addition, interaction with human cerebral microvascular endothelial cells was preliminarily assessed using adhesion, gentamicin protection, and transmission electron microscopy assays, together with measurement of relative ompA transcription by reverse transcription-quantitative polymerase chain reaction. Comparative phylogenetic analyses were performed using publicly available CSF-derived and KL2 K. pneumoniae genomes. RESULTS: BP9811 was identified as a hypermucoviscous ST86-KL2 hvKP isolate that remained susceptible to all tested antimicrobial agents. Whole-genome sequencing revealed an IncHI1B virulence plasmid carrying canonical hvKP-associated determinants, including rmpA/rmpA2, peg-344, iucABCD, and iroBCD. In the Galleria mellonella model, BP9811 showed high virulence comparable to that of the hypervirulent reference strain NTUH-2044. In HCMEC/D3 cells, BP9811 exhibited increased adhesion and intracellular recovery under the tested conditions, and transmission electron microscopy confirmed bacterial internalization. BP9811 also showed higher ompA transcript levels than the control strain. Phylogenetic analysis indicated that BP9811 was genetically distinct from currently available CSF-derived isolates and occupied a related branch within the KL2 population. CONCLUSIONS: This study provides an integrated clinical, genomic, and phenotypic characterization of BP9811, a CSF-derived ST86-KL2 hvKP isolate recovered from a patient with meningitis and diabetes mellitus. BP9811 carried a canonical hvKP virulence plasmid, displayed marked virulence-associated phenotypes, and showed enhanced interaction with human cerebral microvascular endothelial cells in vitro under the tested conditions. These findings expand the limited isolate-level evidence on central nervous system-associated hvKP and provide a basis for future comparative and mechanistic studies.

Humans↗

PubMed1975

[Treatment of hypertonus in diabetes mellitus].

When pathophysiological and pathogenetic aspects of hypertension are taken into consideration with special regard to diabetes mellitus the exhaustion of the "insulin enhancement" within the cerebrovisceral functional systems (Baumann) are discussed and the authors enter possible connections of diabetes mellitus to the renin-angiotensin-aldosterone system. After explanation of the diabetogenic and antidiabetogenic pharmacodynamic qualities of the antihypertensive drugs adequate therapeutic recommendations are proposed summarized in a figure. The authors conclude that for the present antihypertensive therapy in diabetics taking into consideration the references reported on there are sufficient possibilities of treatment for all degrees of severity of hypertension. Such preparations as Rausedan, Disotat, Dopegyt appear as particularly suitable; moreover, the beta receptor blockers, Haemiton, Depressan as well as Guanitil and Pargylin prove to be possible or without disadvantage, respectively. Especially when diuretics are described an exact control of the metabolism should be carried out.

Adrenergic beta-Antagonists↗

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

Conventional and Shared Genetic Association Analysis Between Diabetes Mellitus and Sensorineural Hearing Loss.

PURPOSE: This study aims to investigate the epidemiological and genetic associations between diabetes mellitus (DM) and sensorineural hearing loss (SNHL) across different subtypes. METHODS: We analyzed 502,490 participants from the UK Biobank using multivariate logistic regression to examine the association between DM and SNHL, considering gender, age, and HbA1c levels. Genetic correlations and causality were examined by linkage disequilibrium score regression and bidirectional Mendelian randomization. Cross-trait meta-analyses identified shared loci between DM and SNHL, followed by gene annotation, functional analysis, and drug candidate exploration for the shared traits. RESULTS: Observational analysis revealed significant associations between DM and SNHL, consistent in subgroups based on age, sex, and certain HbA1c levels. A positive genetic correlation was found between type 2 diabetes mellitus (T2D) and SNHL (Rg = 0.0982, p = 0.0095) between T2D and SNHL, and four loci were identified, with ARHGEF28 and TCF7L2 prioritized as credible pleiotropic genes. Enrichment was indicated in glucose metabolism and organogenesis, with shared heritability in metabolic tissues and outer hair cells. Metformin was identified as potential drug candidates for the T2D-SNHL comorbidity. CONCLUSION: These findings progress our understanding of the epidemiological association, shared genetic basis, and potential therapeutic targets between T2D and SNHL, which might contribute to the management of their comorbidity.

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↗

PubMed2026

ZBTB16-associated NK cell alterations reveal shared immunometabolic signatures linking primary Sjögren's syndrome and type 1 diabetes mellitus.

BACKGROUND: Primary Sjögren's syndrome (pSS) and type 1 diabetes mellitus (T1DM) share immune-inflammatory features, yet conserved pathogenic signatures linking these autoimmune disorders remain incompletely understood. The present research sought to uncover common molecular markers and dissect the underlying immune-metabolic cross-talk underlying pSS and T1DM. METHODS: Gene expression profiles of patients with pSS and T1DM were retrieved from the Gene Expression Omnibus database, normalized, and corrected for batch effects prior to downstream analyses. Overlapping potential biomarkers were screened by integrating differential expression analysis, weighted gene co-expression network analysis and least absolute shrinkage and selection operator regression. Functional enrichment based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases was implemented to interpret gene biological properties, and a protein-protein interaction network was further established afterwards. Diagnostic performance was evaluated using receiver operating characteristic analysis. Experimental validation was conducted in non-obese diabetic (NOD) mice using quantitative PCR, immunohistochemistry, and flow cytometry. The CIBERSORT algorithm was adopted to quantify immune cell infiltration levels. RESULTS: ZBTB16 was identified as a shared hub biomarker in both pSS and T1DM and exhibited favorable diagnostic performance. Experimental validation confirmed significantly reduced ZBTB16 expression in peripheral blood mononuclear cells, salivary gland tissues, and pancreatic tissues of NOD mice. Gene Set Enrichment Analysis indicated that ZBTB16-associated signatures were enriched in mitochondrial-related processes, neuroactive ligand-receptor interactions, and ribosome-related pathways. Immune infiltration analysis revealed that resting natural killer (NK) cells were positively correlated with ZBTB16 expression in both diseases. Flow cytometric analysis further confirmed a reduced proportion of resting NK cells in peripheral blood of NOD mice, consistent with the CIBERSORT-based prediction. CONCLUSION: This study identifies ZBTB16 as a shared biomarker linking pSS and T1DM. Reduced resting NK-cell abundance was consistently observed in both computational and experimental analyses, and bioinformatic correlation analysis suggested a positive association with ZBTB16 expression. These findings provide evidence for shared molecular and immunological signatures underlying the two autoimmune disorders and support further investigation of the biological role and diagnostic value of ZBTB16 in pSS and T1DM.

Sjogren's Syndrome↗

PubMed2025

Exploring proteomic immunoprofiles: common neurological and immunological pathways in multiple sclerosis and type 1 diabetes mellitus.

BACKGROUND: Interest in the study of type 1 diabetes mellitus (T1DM) and multiple sclerosis (MS) has increased because of their significant negative impact on the patient quality of life and the profound implications for the health care system. Although the clinical symptoms of T1DM differ from those of MS, such as pancreatic β-cell failure in T1DM and demyelination in the central nervous system (CNS) in MS, both pathologies are considered as autoimmune-related diseases with shared pathogenic pathways, which include autophagy, inflammation and degeneration, among others. Considering the challenges in obtaining pancreatic β-cells and CNS tissue from patients with T1DM and MS, respectively, it is fundamental to explore alternative methods for evaluating disease status. Proteomic analysis of peripheral blood mononuclear cells (PBMCs) is an ideal approach for identifying novel and potential biomarkers for both autoimmune diseases. METHODS: We conducted a proteomic analysis of PBMCs from patients with T1DM and relapsing remitting Multiple Sclerosis (herein forth MS) patients (n = 9 per condition), using a label-free quantitative proteomics approach. The patients were diagnosed following the American Diabetes Association (ADA) criteria for T1DM and McDonald criteria for MS respectively, and were aged over 18 years and more than 2 years from the onset respectively. RESULTS: A total of 2476 proteins were differentially expressed in PBMCs from patients with T1DM and MS patients compared with those form healthy controls (H). Predictive analysis highlighted 15 common proteins, up- or downregulated in PBMCs from patients with T1DM and MS patients vs. healthy controls, involved in the immune system activity (BTF3, TTR, CD59, CSTB), diseases of the neuronal system (TTR), signal transduction (STMN1, LAMTOR5), metabolism of nucleotides (RPS21), proteins (TTR, ENAM, CD59, RPS21, SRP9) and RNA (SRSF10, RPS21). In addition, this study revealed both shared and distinct molecular patterns between the two conditions. CONCLUSIONS: Compared with H, patients with T1DM and MS presented a specific expression pattern of common proteins has been identified. This pattern underscores the shared mechanisms involved in their immune responses and neurological complications, alongside dysregulation of the autophagy pathway. Notably, CSTB has emerged as a differential biomarker, distinguishing between these two autoimmune diseases.

Humans↗

PubMed2026

METTL14 alleviates pyroptosis of placental trophoblasts in gestational diabetes mellitus through the lncRNA MEG8/WNT7A axis via m6A modification.

Gestational diabetes mellitus (GDM) is a pregnancy complication associated with abnormal placental trophoblast function. Pyroptosis has been implicated in GDM pathogenesis, yet the role of m6A modification in this process remains unclear. We hypothesized that METTL14 regulates trophoblast pyroptosis through m6A-dependent modulation of the lncRNA MEG8/WNT7A axis. This study investigated the mechanism of METTL14 in pyroptosis of placental trophoblasts in GDM. HG-treated HTR8/SVneo cells were used as a cell model. METTL14, WNT7A, and lncRNA MEG8 expression was detected by RT-qPCR and western blot. Placental damage, cell injury, and pyroptosis markers were assessed. YTHDF2-mediated m6A enrichment on lncRNA MEG8, the interaction between lncRNA MEG8 and EZH2, and H3K27me3 enrichment on the WNT7A promoter were analyzed. Results showed that lncRNA MEG8 was upregulated, while METTL14 and WNT7A were downregulated. METTL14 overexpression reduced placental damage and trophoblast pyroptosis. Mechanistically, METTL14 suppressed lncRNA MEG8 expression through YTHDF2-mediated m6A methylation. Reduced lncRNA MEG8 decreased EZH2 recruitment to the WNT7A promoter, lowered H3K27me3 levels, and consequently promoted WNT7A expression. Rescue experiments confirmed that lncRNA MEG8 overexpression or WNT7A knockdown attenuated the suppressive effect of METTL14 on pyroptosis. In conclusion, METTL14 acts as an upstream regulator that inhibits trophoblast pyroptosis and ameliorates GDM-induced damage through the lncRNA MEG8/WNT7A axis via YTHDF2-mediated m6A modification, highlighting METTL14 as a potential therapeutic target.

Humans↗

PubMed2026

Risk of mortality and complications in people with depressive disorder and co-occurring diabetes mellitus: a systematic review and meta-analysis.

AIMS: People with depressive disorder have increased premature mortality and higher rates of diabetes mellitus than general population. Evidence shows that diabetes may further increase their risk of premature death from diabetes-related complications, especially cardiovascular diseases (CVDs). Earlier studies examining depression-associated outcomes in diabetes patients have shown mixed results and were hindered by important limitations, especially the use of self-reported questionnaires to ascertain depression, causing misclassification bias by identifying subclinical symptoms or diabetes distress. Associations of depression with specific diabetes complications have not been systematically evaluated. This meta-analysis aimed to investigate the risk of mortality and complications among patients with depression and co-occurring diabetes (depression-diabetes group) relative to patients with diabetes-only (diabetes-only group), on their all-cause mortality rates, and if applicable cause-specific mortality rates, and occurrence of specific diabetes complications. METHODS: We systematically reviewed and quantitatively synthesized diabetes-related outcomes in patients with depression by searching Embase, MEDLINE, PsycInfo and Web-of-Science from inception to 20 December 2024, and included studies that examined mortality and complication outcomes in depression-diabetes group relative to diabetes-only group. Results were synthesized by random-effects meta-analytic models, with stratified-analyses (subgroup analyses and meta-regression) by study-level characteristics, including age, gender, study period, geographic region, follow-up duration and nature of diabetes sample. The study was registered with PROSPERO (CRD42024595145). RESULTS: Twenty-six studies were identified from nine geographic regions. Regarding mortality risk, depression-diabetes group exhibited increased risks of all-cause mortality (RR = 1.30 [95% CI: 1.21-1.39]) and CVD-specific mortality (1.15 [1.02-1.29]) relative to diabetes-only group. Regarding complication risk, depression-diabetes group showed increased risk of complications (1.28 [1.18-1.40]) relative to diabetes-only group, especially in incident-diabetes sample signifying advanced disease stage upon presentation, with stratified-analyses showing higher risk of metabolic complications (1.63 [1.33-1.99]) and cardiovascular complications (1.20 [1.11-1.29]), and lower likelihood of retinopathy (0.84 [0.76-0.94]), albeit comparable rates of cerebrovascular complications (1.36 [0.99-1.87]), nephropathy (1.09 [0.93-1.27]) and peripheral-vascular complications (0.97 [0.79-1.18]). Both overall mortality and complication risks were present in various regions and persisted over time. Heterogeneities were noted and could not be entirely explained by stratified analyses. CONCLUSIONS: Our study demonstrated that patients with depression and co-occurring diabetes were associated with elevated overall mortality risk and complication risk (particularly metabolic and cardiovascular-complications) than non-depressed counterparts, suggesting an overall poorer glycemic control that might eventually drive their earlier death. Comprehensive and multipronged interventions are needed for individualized risk estimation of diabetes-related outcomes, with consequent early interventions to minimize the avoidable physical morbidity and premature mortality in this vulnerable population.

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

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↗