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Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition

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A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Mechanisms of Diseases".

Deadline for manuscript submissions: 30 March 2026 | Viewed by 14843

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Special Issue Editors

Dr. Roberto Franceschi

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Guest Editor

Pediatric Unit, S. Chiara Hospital, 38122 Trento, Italy
Interests: diabetology; pediatric endocrinology; nutrition; obesity; bone metabolism
Special Issues, Collections and Topics in MDPI journals

Dr. Evelina Maines

E-Mail Website
Guest Editor

Division of Pediatrics, S. Chiara General Hospital, APSS Trento, 38122 Trento, Italy
Interests: metabolic disorder; diabetes mellitus; rare disorders; inborn errors of metabolism (IEM)

Special Issue Information

Dear Colleagues,

The heterogeneity in age at onset and clinical presentation within the same form of diabetes, differences in the response to treatments in patients with the same phenotype, and the variability in the course of the disease require personalized management. The precision medicine approach has been applied to individuals with monogenic diabetes (i.e., MODY, neonatal diabetes) and to type 1 and type 2 diabetes to select treatments that are most likely to offer benefits and least likely to cause side effects, with improvement of clinical outcomes and economic cost saving.

In the last 10 years, genetic, metabolomic, immunologic, and other sophisticated tests have become less expensive and more widespread; therefore, it is expected that precision medicine will become increasingly applied to diabetes care.

This Special Issue of Journal of Personalized Medicine aims to highlight the current state of precision medicine applied to diabetes to show some of the latest findings and future perspectives and integrate expertise from basic science, clinical, and population-based approaches. Topics of interest include novel insights into gene testing, polymorphisms and bioinformatics, metabolites and intestinal microbiome analysis, as well as their association with the risk of disease, drug metabolism, or disease complications.

Dr. Roberto Franceschi
Dr. Evelina Maines
Guest Editors

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Keywords

diabetes treatment
drug metabolism
disease complications
polymorphisms
epigenetics
metabolomics
proteomics

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Published Papers (8 papers)

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Research

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11 pages, 573 KB

Open AccessArticle

Cluster-Based Immunization Patterns in Diabetes Mellitus: Insights for Personalized Preventive Care

by Teresa Gisinger, Alexandra Kautzky-Willer and Michael Leutner

J. Pers. Med. 2025, 15(9), 441; https://doi.org/10.3390/jpm15090441 - 16 Sep 2025

Viewed by 366

Abstract

Background: We investigated immunization status and preventive care among diabetes mellitus (DM) patients by stratifying them into clinically distinct risk clusters based on comorbidities, reflecting a personalized medicine approach. Methods: Using the Austrian health interview survey 2019, we identified four groups: cluster 1 (DM, arterial hypertension (aHTN), dyslipidemia; n = 215), cluster 2 (DM, aHTN, dyslipidemia, obesity class II; n = 33), cluster 3 (DM, aHTN, dyslipidemia, depression; n = 65), and a control cohort (DM without hyperlipidemia, hypertension, depression, or obesity class II; n = 214). The cohorts were compared by chi² tests. By logistic regression the association of the cluster-related variables and the vaccination status/preventive care variables were analyzed. Results: Significant differences in intact diphtheria immunization between the cohorts exist (cluster 1: 45.6%, cluster 2: 27.3%, cluster 3: 52.3%, control: 51.9%, p-value 0.047). Differences in intact tetanus (42.4% vs. 64%, p = 0.027) and diphtheria (27.3% vs. 51.9%, p = 0.013) immunization between cluster 2 and control cohort were investigated. Cluster 2 was negatively associated with tetanus (OR 0.83, p = 0.009) and diphtheria (OR 0.85, p = 0.018) immunization. Cluster 1 reports higher rates of fecal occult blood test (50.7% vs. 39.3%, p = 0.022) and cluster 2 reports a higher rate of colonoscopy (24.2% vs. 8.9%, p = 0.015) in comparison to the control cohort. Conclusions: A personalized medicine approach reveals that DM patients with specific comorbidity patterns, particularly those with hypertension, dyslipidemia, and obesity class II, have lower immunization rates—highlighting the need for targeted preventive strategies. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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14 pages, 417 KB

Open AccessArticle

Association of Insulin Resistance with Dysglycemia in Elder Koreans: Age- and Sex-Specific Cutoff Values

by Sang Min Yoon and Boyoung Park

J. Pers. Med. 2025, 15(9), 438; https://doi.org/10.3390/jpm15090438 - 15 Sep 2025

Viewed by 770

Abstract

Background/Objectives: Dysglycemia including pre-diabetes mellitus (Pre-DM) and type 2 diabetes mellitus (T2DM) is associated with insulin resistance. This study aimed to support personalized early diagnosis of dysglycemia by proposing optimal, sex- and age-specific cutoff values for Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and Homeostatic Model Assessment of Beta-Cell Function (HOMA-β) in Koreans aged ≥65 years. Methods: This study analyzed 3862 older Koreans from the 8th Korea National Health and Nutrition Examination Survey data (2019–2021), excluding those with prior diabetes or medication. The participants were classified into normal and dysglycemia groups, based on fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). Sex- and age-specific optimal cutoff values were determined using Youden’s Index (YI) and area under the curve (AUC). Results: For T2DM, the optimal HOMA-IR cutoff was 2.25 for men and 2.03 for women, with strong discriminative performance (AUCs: 0.828 and 0.823, respectively). Stratifying cutoff values further by sex and age improved the diagnostic accuracy (AUC > 0.83 in most subgroups), underscoring the value of tailored thresholds. For pre-DM, the HOMA-IR cutoff was 1.73 in men and 1.85 in women (AUCs: 0.682 and 0.665, respectively). Age- and sex-specific cutoffs modestly improved AUCs, particularly in men (up to 0.7), although the improvement was less consistent among women. HOMA-β showed no significant association with dysglycemia, and no meaningful cutoff values were identified. Conclusions: HOMA-IR is a promising marker for the early identification of dysglycemia in older adults when interpreted through a personalized lens. Applying sex- and age-specific cutoff values enhances diagnostic precision and supports a more individualized approach to metabolic risk assessment. Further longitudinal studies are warranted to validate these personalized thresholds and to optimize early detection strategies in diverse populations. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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12 pages, 1302 KB

Open AccessArticle

Exploring the Relationship Between Insulin Resistance, Liver Health, and Restrictive Lung Diseases in Type 2 Diabetes

by Mani Roshan, Christian Mudrack, Alba Sulaj, Ekaterina von Rauchhaupt, Thomas Fleming, Lukas Schimpfle, Lukas Seebauer, Viktoria Flegka, Valter D. Longo, Elisabeth Kliemank, Stephan Herzig, Anna Hohneck, Zoltan Kender, Julia Szendroedi and Stefan Kopf

J. Pers. Med. 2025, 15(8), 340; https://doi.org/10.3390/jpm15080340 - 1 Aug 2025

Viewed by 797

Abstract

Background: Restrictive lung disease (RLD) is a potential complication in type 2 diabetes (T2D), but its relationship with insulin resistance and liver-related metabolic dysfunction remains unclear. This study evaluated the association between lung function and metabolic markers in T2D and retrospectively assessed whether metabolic improvements from dietary intervention were accompanied by changes in lung function. Methods: This cross-sectional analysis included 184 individuals (101 with T2D, 33 with prediabetes, and 50 glucose-tolerant individuals). Lung function parameters—vital capacity (VC), total lung capacity by plethysmography (TLC-B), and diffusion capacity for carbon monoxide (TL_CO)—were assessed alongside metabolic markers including HOMA2-IR, fatty liver index (FLI), NAFLD score, and Fibrosis-4 index (FIB-4). In a subset of 54 T2D participants, lung function was reassessed after six months following either a fasting-mimicking diet (FMD, n = 14), Mediterranean diet (n = 13), or no dietary intervention (n = 27). Results: T2D participants had significantly lower VC and TLC-B compared to glucose-tolerant and prediabetic individuals, with 18–21% falling below clinical thresholds for RLD. Lung volumes were negatively correlated with HOMA2-IR, FLI, NAFLD score, and FIB-4 across the cohort and within the T2D group. Although the FMD intervention led to significant improvements in HOMA2-IR and FLI, no corresponding changes in lung function were observed over the six-month period. Conclusions: Restrictive lung impairment in T2D is associated with insulin resistance and markers of liver steatosis and fibrosis. While short-term dietary interventions can improve metabolic parameters, their effect on lung function may require a longer duration or additional interventions and targeted follow-up. These findings highlight the relevance of pulmonary assessment in individuals with metabolic dysfunction. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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10 pages, 399 KB

Open AccessArticle

Incidence of Type 1 Diabetes in Children Aged 0–14 Years in Trentino–Alto Adige Region and Determinants of Onset with Ketoacidosis

by Stefania Fanti, Denise Lazzarotto, Petra Reinstadler, Nadia Quaglia, Evelina Maines, Maria Agostina Lamberti, Vittoria Cauvin, Riccardo Pertile, Massimo Soffiati and Roberto Franceschi

J. Pers. Med. 2024, 14(10), 1055; https://doi.org/10.3390/jpm14101055 - 11 Oct 2024

Cited by 1 | Viewed by 2555

Abstract

Aim: To assess the incidence and the temporal trend of type 1 diabetes (T1D) and diabetic ketoacidosis (DKA) during the period 2014–2023 in youths aged 0–14 years in the Trentino–Alto Adige region, Italy. Methods: A retrospective review of all incident cases of T1D diagnosed at the two Pediatric Diabetes Centers of Bolzano and Trento was matched with diabetes exemptions (No. 344). Demographic, clinical, and socioeconomic status (SES) data at first hospitalization were collected from subjects who agreed to participate (No. 272). Results: The incidence of T1D was 21.5/100,000 person/years, with a peak of 31.1 in 2021 during the COVID-19 pandemic. The mean age at the onset was 8.8 ± 3.9 years. Seventy-nine percent of the subjects were Italians, primarily residents in rural areas, and SES was equally represented. The mean incidence of DKA was 36.9%. The logistic regression analysis showed that the independent characteristics of the patients with DKA were of a younger age and displayed higher glycated hemoglobin (HbA1c) values. No relation of DKA with seasonality, ethnicity, or first-degree relative (FDR) with T1D or SES was detected. Conclusions: Our study revealed an incidence of T1D in the Trentino–Alto Adige region comparable to other areas in the North of Italy. The DKA rate negatively correlated with age; therefore, targeted prevention educational campaigns to increase awareness are needed. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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16 pages, 425 KB

Open AccessArticle

Coffee Consumption and CYP1A2 Polymorphism Involvement in Type 2 Diabetes in a Romanian Population

by Laura Claudia Popa, Simona Sorina Farcas and Nicoleta Ioana Andreescu

J. Pers. Med. 2024, 14(7), 717; https://doi.org/10.3390/jpm14070717 - 3 Jul 2024

Cited by 4 | Viewed by 5153

Abstract

Cytochrome P450 1A2 (CYP1A2) is known to be the main enzyme directly responsible for caffeine metabolism. Rs762551 (NC_000015.10:g.74749576C>A) is a single nucleotide polymorphism of the CYP1A2 gene, and it is known mainly for metabolizing caffeine. A significant worldwide health issue, type 2 diabetes (T2DM), has been reported to be negatively associated with coffee consumption. Yet, some studies have proven that high intakes of coffee can lead to a late onset of T2DM. Objectives: This study aims to find any significant correlations among CYP1A2 polymorphism, coffee consumption, and T2DM. Methods: A total of 358 people were enrolled in this study—218 diagnosed with T2DM, and 140 representing the control sample. The qPCR technique was performed, analyzing rs762551 (assay C_8881221) on the LightCycler 480 (Roche, Basel, Switzerland) with Gene Scanning software version 1.5.1 (Roche). Results: Our first observation was that the diabetic patients were likely to consume more coffee than the non-diabetic subjects. People with the AA genotype, or the fast metabolizers, are the least common, yet they are the highest coffee consumers and present the highest glucose and cholesterol levels. Another important finding is the correlation between coffee intake and glucose level, which showed statistically significant differences between the diabetic group (p = 0.0002) and the control group (p = 0.029). Conclusions: The main conclusion of this study is that according to genotype, caffeine levels, glucose, and cholesterol are interconnected and proportionally related, regardless of type 2 diabetes. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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Review

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30 pages, 1399 KB

Open AccessReview

From Architecture to Outcomes: Mapping the Landscape of Digital Twins for Personalized Diabetes Care—A Scoping Review

by Danilo Andrés Cáceres-Gutiérrez, Diana Marcela Bonilla-Bonilla, Yamil Liscano and Jhony Alejandro Díaz Vallejo

J. Pers. Med. 2025, 15(11), 504; https://doi.org/10.3390/jpm15110504 - 23 Oct 2025

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Abstract

Background/Objectives: Digital twins are emerging as a transformative technology in diabetes management, promising a shift from standardized protocols to highly personalized care. This scoping review aims to systematically map the current landscape of digital twin applications in diabetes, synthesizing evidence on their implementation architectures, analytical models, performance metrics, and clinical integration strategies to identify key trends and critical gaps. Methods: A systematic search was conducted across five electronic databases in accordance with PRISMA-ScR guidelines to identify empirical studies on digital twins for diabetes. Data from the selected articles were extracted to analyze bibliographic characteristics, population data, technological components, performance outcomes, and integration levels. A narrative synthesis was performed to map the evidence. Results: Seventeen studies were included, revealing a rapid increase in publications since 2022, with a notable concentration of research in India. The technological architecture shows a convergence toward machine learning models (e.g., LSTM) powered by data from IoT devices and wearables. Certain interventional studies have reported significant clinical impacts, including HbA1c reductions of up to 1.9% and T2DM remission rates as high as 76.5% in one trial. However, major implementation barriers were identified, including fragmented interoperability standards and low rates of full integration into clinical workflows (35.3%). Conclusions: Digital twins are emerging as powerful tools that show the potential to drive significant clinical outcomes in diabetes care. However, to translate this promise into widespread practice, future efforts must focus on overcoming the critical challenges of standardized interoperability and deep clinical integration. Rigorous, independently validated, long-term trials in diverse populations are essential to confirm these promising findings. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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14 pages, 282 KB

Open AccessReview

A Review of Stage 0 Biomarkers in Type 1 Diabetes: The Holy Grail of Early Detection and Prevention?

by Măriuca Mănescu, Ion Bogdan Mănescu and Alina Grama

J. Pers. Med. 2024, 14(8), 878; https://doi.org/10.3390/jpm14080878 - 20 Aug 2024

Cited by 5 | Viewed by 2267

Abstract

Type 1 diabetes mellitus (T1D) is an incurable autoimmune disease characterized by the destruction of pancreatic islet cells, resulting in lifelong dependency on insulin treatment. There is an abundance of review articles addressing the prediction of T1D; however, most focus on the presymptomatic phases, specifically stages 1 and 2. These stages occur after seroconversion, where therapeutic interventions primarily aim to delay the onset of T1D rather than prevent it. This raises a critical question: what happens before stage 1 in individuals who will eventually develop T1D? Is there a “stage 0” of the disease, and if so, how can we detect it to increase our chances of truly preventing T1D? In pursuit of answers to these questions, this narrative review aimed to highlight recent research in the field of early detection and prediction of T1D, specifically focusing on biomarkers that can predict T1D before the onset of islet autoimmunity. Here, we have compiled influential research from the fields of epigenetics, omics, and microbiota. These studies have identified candidate biomarkers capable of predicting seroconversion from very early stages to several months prior, suggesting that the prophylactic window begins at birth. As the therapeutic landscape evolves from treatment to delay, and ideally from delay to prevention, it is crucial to both identify and validate such “stage 0” biomarkers predictive of islet autoimmunity. In the era of precision medicine, this knowledge will enable early intervention with the potential for delaying, modifying, or completely preventing autoimmunity and T1D in at-risk children. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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Other

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18 pages, 584 KB

Open AccessSystematic Review

Diabetes Awareness Campaigns to Prevent Ketoacidosis at the Diagnosis of Type 1 Diabetes: Efficacy on Multiple Outcomes and Predictors of Success: A Systematic Review

by Elisa Minerba, Evelina Maines, Nadia Quaglia, Ludovica Fedi, Stefania Fanti, Alessandro Fierro and Enza Mozzillo

J. Pers. Med. 2024, 14(12), 1115; https://doi.org/10.3390/jpm14121115 - 21 Nov 2024

Cited by 3 | Viewed by 1800

Abstract

Background/Objectives: In Italy, the incidence of diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes (T1D) is still very high (35.7–39.6%), especially in youths. We aimed to determine the efficacy of awareness campaigns to prevent DKA on multiple outcomes and identify success predictors. Methods: We searched electronic databases (Pubmed, Cochrane, and Web of Science) for studies published between 1 August 1990 and 1 August 2024. The review included studies that focused on children under 18 years old, and outcomes were measured by comparing before and after implementing the campaigns in the same area and between areas where interventions took place or not. Results: Of 236 records identified, 15 were eligible for analysis. After campaign implementation, the pooled DKA reduction resulted between 1% and 65.5%, based on the characteristics of the campaigns. A decrease in the rate of acute complications, such as cerebral edema, was reported. Hemoglobin A1c (HbA1c) at onset showed a mean reduction of 0.7–5.1%; C-peptide increased in patients without DKA at diagnosis, and length of hospitalization decreased. Campaign costs were lower than the costs of treating subjects with DKA. Conclusions: This review demonstrated that DKA awareness campaigns effectively reduce DKA incidence and improve other parameters, such as acute complications, HbA1c and C-peptide levels, length of hospitalization, and costs, among youths with T1D. To be effective, campaigns must follow specific principles of target population, modality, and minimal duration, as reported in this review. Full article

(This article belongs to the Special Issue Diabetes Mellitus: Current Research and Future Perspectives, 2nd Edition)

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