Claus Vinter Bødker Hviid1,2 · Nicklas Højgaard-Hessellund Rasmussen2,3 · Johan Røikjer2,3,4

Received: 5 December 2024 / Accepted: 22 March 2025 / Published online: 7 April 2025© The Author(s) 2025

Abstract

Background Objective and easily applicable biomarkers for diabetic polyneuropathy (DPN) are warranted. Circulating nerve-specific proteins have emerged as valuable biomarkers for central nervous system disease but few of these have been tested in peripheral neuropathy. Glial Fibrillary Acidic Protein (GFAP) is highly expressed in non-myelinating Schwann cells while UCH-L1 is a neuron expressed stress protein not previous analyzed in DPN. In this pilot study, we explore serum  GFAP and UCH-L1 levels in patients with/without DPN and controls.

Methods Persons with DPN (n=28), without DPN (n=31), and controls (n=30) were evaluated in a cross-sectional design. Sural nerve conduction (velocity and amplitude) was evaluated by NC-stat DPNCheck™ and quantitative sensory testing of cold detection and pain was performed. GFAP and UCH-L1 levels were compared across study groups and the unadjusted correlation with nerve assessments evaluated.

Results Serum GFAP were lower in persons with DPN (20.9±10.9 pg/ml) than in persons without DPN (26.2±14.1 pg/ ml) (p=0.04) or controls (31.7±26.0 pg/ml) (p=0.02). GFAP levels were not different in persons without DPN and controls (p=0.61). UCH-L1 levels were not different between study groups (p=0.48). GFAP levels correlated with cold pain thresh-old (Rho= − 0.320, p=0.02) but failed to reach significance for cold detection (Rho= − 0.236, p=0.09). No correlation was observed between GFAP and nerve amplitude (p=0.58) or conductivity (p=0.86).

Conclusion Serum GFAP levels are reduced in persons with DPN compared to persons without DPN and controls. Reduced serum GFAP levels may be associated with reduced markers of small nerve fiber damage obtained from quantitative sensory testing in people with diabetes.

Keywords Diabetic polyneuropathy · Diabetes · Biomarkers · Glial fibrillary acidic protein · Quantitative sensory testing

Haixia Qi1  · Tao Zhang2  · Lijie Hou3  · Qi LI4  · Ruiping Huang3  · Lihua Ma1,3

Received: 23 December 2024 / Accepted: 29 March 2025 / Published online: 19 April 2025 © The Author(s) 2025, corrected publication 2025

Abstract

Objective This study aimed to comprehensively review the latest advancements in diabetic foot risk prediction models over the past four years to address the severe challenges posed by diabetic foot ulcers, which are among the leading causes of disability and mortality among diabetic patients. Diabetic foot ulcers are characterized by their complex aetiology, pose a grave threat to life and impose enormous social and economic burdens, thus becoming a critical issue in public health that urgently requires attention. By accurately predicting the risk of diabetic foot and implementing early intervention strategies, this study aimed to reduce its incidence and mortality rates.

Methods This study employed a systematic review and comprehensive analysis framework, conducted extensive searches of electronic databases (including PubMed, EMBASE, the Cochrane Library, CNKI, etc.) and supplemented these searches with manual literature collection to ensure comprehensive information coverage. During the literature screening and evalua-tion phase, strict adherence to the predetermined inclusion and exclusion criteria was maintained to guarantee the high qual-ity of the included studies. Further detailed quality assessments, data extraction, and analysis of the selected literature were conducted, with a focus on exploring the construction strategies of risk prediction models, the selection of key variables, the evaluation indicators of model performance, and the validation methods.

Results By comparing and analysing the differences among studies in terms of methodology, model effectiveness, and prac-tical application potential, this study summarized the development trends of diabetic foot risk prediction models and antici-pated future research directions. These findings indicate that with the assistance of advanced diabetic foot risk prediction models, potential risk factors can be identified and addressed early on, thereby effectively reducing the incidence of diabetic foot and significantly improving patients’ quality of life.

Conclusion This study revealed that diabetic foot risk prediction models have significant effects on accurately identifying risk factors and guiding early interventions, serving as effective tools to reduce the incidence of diabetic foot. Through early identification and intervention, the prognosis and quality of life of patients can be significantly improved, providing impor-tant references and guidance for the field of public health.

Keywords Diabetic foot ulcer · High-risk diabetic foot · Diabetes · Prediction model

Gabriele Angelo Vassallo1  · Tommaso Dionisi2,3  · Vittorio De Vita4  · Giuseppe Augello1  ·Antonio Gasbarrini3,5  · Dario Pitocco6  · Giovanni Addolorato2,3

Received: 25 January 2025 / Accepted: 29 March 2025 / Published online: 19 April 2025 © The Author(s) 2025

Abstract

Fecal microbiota transplantation (FMT) has emerged as a potential therapeutic strategy for modulating gut dysbiosis in diabetes mellitus. This review critically evaluates preclinical and clinical evidence on FMT in type 1 (T1D) and type 2 dia-betes (T2D). Studies suggest that FMT can restore microbial diversity, improve glycemic control, and modulate immune responses, with varying effects across diabetes subtypes. In T1D, preclinical models demonstrate that FMT influences regulatory T-cell expansion and β-cell preservation, though clinical translation remains limited. In T2D, FMT has shown transient improvements in insulin sensitivity, with sustained effects observed only in patients with specific microbiome signatures. However, heterogeneity in patient responses, donor variability, and methodological limitations complicate its clinical application. This review highlights the interplay between FMT, immune modulation, and microbial metabolism, advocating for phenotype-stratified trials and multi-omics integration to enhance therapeutic precision.

Keywords Fecal microbiota transplantation · Intestinal Microbiome · Diabetes · Insulin sensitivity · Metabolic syndrome · Beta-cell

Abbreviations

FMT Fecal microbiota transplantation TUDCA Tauroursodeoxycholic acid VEGF Vascular endothelial growth factor SCFAs Short-chain fatty acids MMTT Mixed meal tolerance test FVT Fecal virome transplantation OGTT Oral glucose tolerance test SRB Sulfate-reducing bacteria LSI Lifestyle intervention

Huanjia Qu1  · Lingling Zhou1  · Dong Tang2  · Qiuling Zhang1  · Pu Yang3  · Boyi Yang3  · Junping Shi4

Received: 25 December 2024 / Accepted: 22 March 2025 / Published online: 19 April 2025 © The Author(s) 2025

Abstract

Purpose Type 2 diabetes mellitus (T2DM) is associated with ectopic fat deposition, especially in the liver and pancreas.Therefore, this study aimed to evaluate the relationship between liver fat fraction (LFF), pancreatic fat fraction (PFF), and new-onset T2DM in metabolic dysfunction-associated fatty liver disease (MAFLD) by magnetic resonance imaging (MRI).

Methods This is a retrospective study of patients with MAFLD who underwent abdominal MRI between 2022 and July 2024. LFF and PFF were measured using an axial multi-echo Dixon-based sequence. All participants underwent routine medical history, anthropometric measurements, and laboratory tests. Multivariable stepwise selection models were con-structed to predict PFF and T2DM status based on variables of clinical interest.

Results This study included 80 MAFLD patients with 40 untreated new-onset T2DM and 40 non-T2DM controls. LFF, PFF, and homeostasis model assessment of insulin resistance (HOMA-IR) index were higher in the T2DM group than in the control group. In the new-onset T2DM group, PFF was linearly positively correlated with LFF (rs=0.321, P=0.04) and HOMA-IR (rs=0.350, P=0.03). After adjustment for several metabolic variables, PFF remained an independent risk factor for incident T2DM in MAFLD patients (all P<0.05). The area under the receiver operating characteristic curve for PFF and LFF to predict T2DM was 0.889 and 0.633 (P<0.001 and P=0.03), respectively.

Conclusion In MAFLD patients, PFF, and LFF play a prominent role in new-onset T2DM with high predictive and diag-nostic value.

Keywords Metabolic dysfunction-associated fatty liver disease · Type 2 diabetes mellitus · Liver fat fraction ·Pancreatic fat fraction · Ectopic fat deposition · MRI