Honghong Zhang¹ · Changlin Zhai¹ · Huilin Hu¹ · Gang Qian¹ · Menghui Mao¹

Received: 1 November 2025 / Accepted: 18 January 2026©The Author(s) 2026

Abstract

Objective This study aimed to investigate gut microbiota composition and metabolic functions in patients with type 2 diabetes mellitus (DM) complicated by myocardial infarction (MI) and to explore potential mechanisms linking the gut microbiome to MI development.

Methods Sixty patients with DM complicated by MI and 52 patients with DM alone were initially recruited.After quality control, 29 DM +MI patients and 33 DM patients were included in the final analysis. Gut microbial profiles were characterized using shotgun metagenomic sequencing and bioinformatics analyses. Microbial diversity, composition, and gene functions were compared between groups based on KEGG, COG, and CAZy annotations.

Results Overall microbial diversity and metabolic profiles were comparable between the two groups; however, significant differences were observed in specific taxa and functional genes.Taxa enriched in the DM +MI group included Bacteroidales, Prevotellaceae, and Lachnospiraceae. In total, 510 KEGG orthology (KO) units and 21 pathways—including ABC transporters, quorum sensing, and general metabolic pathways—differed significantly between groups. Carbohydrate transport and metabolism, as well as glycoside hydrolase activity, represented the most enriched functional categories. Random forest models based on selected microbial species,KO units, and KEGG pathways achieved areas under the curve (AUCs) of0.868, 0.885, and 0.820, respectively.

Conclusion Patients with DM complicated by MI exhibit distinct gut microbial compositions and functional gene signatures compared with patients with DM alone. These microbiome-based markers may contribute to early risk stratification and provide potential targets for microbiota-focused interventions to mitigate MI risk in patients with diabetes.

Keywords Gut microbiome · Type 2 diabetes mellitus · Myocardial infarction · Metagenomics

Riccardo Magris¹ · Andrea Monte¹ · NicolòVigolo² · Francesca Nardello¹ · Michele Trinchi¹ · Carlo Negri² · Paolo Gisondi³ · Chiara Cosma⁴ · Giovanni Sartore⁴ · Annunziata Lapolla⁴ · Paolo Moghetti² · Paola Zamparo¹

Received: 17 November 2025 / Accepted: 11 April 2026©The Author(s) 2026

Abstract

Aims This study aimed to investigate the impact of type 2 diabetes (T2D) on muscle and tendon mechanics by comparing individuals with controlled diabetes to a healthy cohort matched for age, BMI, and physical activity level. A secondary aim was to investigate the possible association between muscle-tendon proprieties and glycated haemoglobin (HbA1c) or advanced glycated end products (AGE, RAGE) as determined in blood and skin biopsies.

Methods Twenty-eight patients and eighteen controls were recruited for this study.Achilles tendon stiffness (k_T), muscletendon stiffness (k_M, in gastrocnemius medialis) and the rate of torque development (RTD) were evaluated by combining dynamometric and ultrasound data.

Results Diabetic patients showed increased tendon stiffness and reduced tendon elongation compared to controls, but similar RTD and k_M values. No differences in advanced glycation end products (in serum or biopsies) were observed between cohorts,but a significant positive correlation was observed between k_T and HbA1c (r =0.610,N=46,P<0.001).

Conclusion Our data indicate that muscle, but not tendon, properties can be preserved in controlled and physically active diabetic patients and that higher tendon stiffness does not result in a functional deficit (i.e., same explosive capacity between cohorts).Although this study is cross-sectional and has a limited sample size, our data suggest a potential role of HbA1c as a non-invasive biomarker of altered tendon mechanics in people with diabetes.

ClinicalTrials.gov, protocol number NCT05585502 .

Keywords Advanced glycation end products · Glycated haemoglobin · Tendon stiffness · Muscle stiffness

Bárbara Maria Farias Kruschewsky1  · Roseanne Montargil Rocha1  · Marcelo Araújo2  · Rafael Ernane Andrade3  · Icaro J. S. Ribeiro1

Received: 17 February 2026 / Accepted: 12 April 2026 © The Author(s) 2026

Abstract

Aims To identify patterns of complication burden among individuals with diabetes mellitus based on sociodemographic, behavioral, and clinical characteristics, and to examine their co-occurrence with diabetes-related comorbidities.

Methods This cross-sectional study was conducted during a diabetes health campaign in a municipality in southern Bahia, Brazil, involving 1,542 patients. Data were obtained through a standardized questionnaire and ophthalmological examina-tions. Latent class analysis was applied to identify subgroups with similar clinical characteristics. Models with two to four classes were estimated, with the two-class model presenting the most parsimonious and interpretable solution according to BIC. Associations between classes and comorbidities were estimated using Poisson regression with robust variance, adjusted for age and sex.

Results Two classes were identified. Class 1 (86.6%) showed lower complication burden, with preserved vascular and sen-sory function. Class 2 (13.4%) was characterized by a higher frequency of ulceration, amputation, absent peripheral pulses, and impaired protective sensation. Individuals in Class 2 presented higher prevalence of cardiovascular disease (PR=1.47), myocardial infarction (PR=1.64), neurological disease (PR=1.67), and retinopathy (PR=1.63).

Conclusion The identified classes primarily reflect differences in peripheral complication burden, with higher co-occurrence of vascular and microvascular conditions in the more affected group. These findings describe patterns of complication clus-tering within a screening population and may support population-level strategies for identifying individuals with greater healthcare needs.

Keywords Diabetes mellitus · Risk stratification · Latent class analysis

Merve Oruc1  · Ozant Helvacı2  · Ahmet Oruc3  · Ulver Derici2

Received: 13 February 2026 / Accepted: 12 April 2026 © The Author(s) 2026

Abstract

Background Orthostatic hypotension (OH) is associated with adverse cardiovascular outcomes and may reflect underlying autonomic and vascular dysfunction. Arterial stiffness is a key determinant of cardiovascular risk; however, its relationship with OH in patients with diabetes mellitus (DM) remains unclear.

Objective To evaluate factors associated with OH and investigate the relationship between arterial stiffness parameters and OH in patients with DM.

Methods This single-center cross-sectional study included 193 patients with DM. Orthostatic blood pressure was measured in the supine position and 3 min after standing. Arterial stiffness was assessed using oscillometric pulse wave velocity (PWV) and related parameters with the Mobil-O-Graph device. Clinical, laboratory, and medication data were analyzed. Logistic regression analyses were performed to identify factors associated with OH.

Results OH was present in 56 patients (29%). Patients with OH had significantly higher central blood pressure and arterial stiffness parameters, including PWV, augmentation pressure, and augmentation index. In multivariate analysis, female sex, older age, diabetic neuropathy, and PWV were independently associated with OH. PWV remained significantly associated with OH after adjustment for confounders. No significant differences were observed between groups regarding antihyper-tensive medication classes.

Conclusion In patients with DM, OH is independently associated with increased arterial stiffness and diabetic neuropathy. These findings suggest a link between orthostatic blood pressure dysregulation and adverse vascular characteristics. Prospec-tive studies are needed to clarify causal relationships and clinical implications.

Keywords Orthostatic hypotension · Arterial stiffness · Pulse wave velocity · Diabetes mellitus · Cardiovascular autonomic neuropathy

Communicated by Salvatore Corrao, M.D

Merve Oruc

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1 Department of Nephrology, Meram School of Medicine, Necmettin Erbakan University, Konya, Turkey

2 Department of Nephrology, Gazi University Faculty of Medicine, Ankara, Turkey

3 Department of Medical Oncology, Meram School of Medicine, Necmettin Erbakan University, Konya, Turkey