Periodontitis and diabetes: a bidirectional link

Thanh T. Nguyen1,2 · Miguel Bandeira3  · Catherine Giannopoulou3  · Alkisti Zekeridou3  · Dongryeol Ryu1  ·  Karim Gariani4,5

Received: 10 September 2025 / Accepted: 6 January 2026 © The Author(s) 2026

Abstract

Periodontitis is a chronic inflammatory disease affecting the tooth-supporting structures, and its closely linked to diabetes mellitus through a well-established bidirectional relationship. Diabetes exacerbates periodontal destruction via systemic inflammation, oxidative stress, and immune dysfunction, while periodontitis can impair glycemic control by increasing systemic inflammatory burden. The pathogenesis of periodontitis remains only partially understood, involving microbial dysbiosis, host immune responses, and metabolic disturbances. The 2018 classification system defines stages and grades based on disease severity and progression risk. Epidemiological data reveal a high global prevalence, particularly among individuals with type 2 diabetes. Studies have shown that periodontal therapy contributes to improved glycemic control and may reduce cardiovascular risk. Despite its clinical significance, periodontitis remains underdiagnosed in the context of diabetic care. Effective management requires integrated medical and dental collaboration, targeting both glycemic regulation and periodontal health. This dual approach offers mutual benefits for reducing complications and improving long-term outcomes in diabetic patients. In this review, we present the current knowledge on the relationship between diabetes and periodontitis, focusing on epidemiology, pathogenesis, and management.

Keywords Diabetes · Periodontitis · Oral health · Oral inflammation · Cardiovascular

Communicated by Annunziata Lapolla.

Karim Gariani

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1 Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

2 Center of Endocrinology, Metabolism, Genetic/Genomics and Molecular Therapy, Vietnam National Children’s Hospital, Hanoi, Vietnam

3 Division of Regenerative Dental Medicine and Periodontology, University Clinics of Dental Medicine, University of Geneva, Geneva, Switzerland

4 Division of Endocrinology, Diabetes and Metabolism, Department of Medical Specialties, Geneva University Hospitals, Geneva 1205, Switzerland

5 Faculty Diabetes Center, University of Geneva Medical Center, University of Geneva, Geneva, Switzerland

Relationship between body adiposity and glycemic control in children and adolescents with type 1 diabetes

Claudio Maffeis1  · Ilaria Fierri1  · Elisa Morotti1  · Erika Caiazza1  · Quincy Pedranzini1  · Marco Marigliano1  · Claudia Piona1

Received: 20 October 2025 / Accepted: 6 January 2026 / Published online: 31 January 2026 © The Author(s) 2026

Abstract

Aims To investigate the relationship between body adiposity and glycemic control in children and adolescents with type 1 diabetes (T1D).

Methods This cross-sectional study included 364 children and adolescents aged 6–18 years with T1D. Anthropometric indi-ces [BMI, BMI Z-score, waist-to-height ratio (WHtR)] and body composition [fat mass (FM), FM%, fat mass index (FMI)], assessed using bioelectrical impedance analysis, were obtained. Hemoglobin A1c and glucose sensor metrics, including time in range (TIR), were used to assess glycemic control. Associations between variables were analyzed using Spearman’s correlation. Logistic regression models were run to identify independent predictors of HbA1c<7.0% and TIR>70%, with FMI, WHtR, total daily insulin dose per kg (TDD), treatment modalities, sex, age, diabetes duration, and pubertal stage as independent variables.

Results Adiposity measures (FMI, FM%, and WHtR) were positively associated with HbA1c and negatively with TIR in both sexes. Logistic regression showed that HbA1c<7% and TIR>70% were significantly predicted by FMI [OR(95%CI): 0.822(0.704–0.960), p=0.013, and 0.807(0.681–0.955), p=0.012, respectively] and WHtR(x100) [OR(95%CI): 0.927(0.874– 0.983), p=0.013, and 0.923(0.866–0.985), p=0.015, respectively], independently of TDD, sex, treatment modalities and the other independent variables.

Conclusions Body adiposity negatively impacts glycemic control in children and adolescents with T1D, independent of sex and insulin treatment modalities. Despite technological advances in diabetes care, excess adiposity is emerging as a key modifiable factor associated with poorer glycemic outcomes and, consequently, poorer long-term health in children and adolescents with T1D.

Keywords Type 1 diabetes · Children · Body mass index · Adiposity · HbA1c · TIR

Abbreviations

ADA American Diabetes Association

AID Automated insulin delivery

BMI Body mass index

BP blood pressure

CGM Continuous glucose monitoring

Communicated by Annunziata Lapolla

Marco Marigliano

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1 Section of Pediatric Diabetes and Metabolism, Department of Surgery, Dentistry, Pediatrics, and Gynecology, University and Azienda Ospedaliera Universitaria Integrata of Verona, Piazzale Stefani, 1, Verona 37126, Italy

CVRFs Cardiovascular risk factors

FM Fat mass

FMI Fat mass index

GRI Glycemia risk index

HDL High-density lipoprotein cholesterol

IP Insulin Pump

ISPAD International Society for Pediatric and Adoles

cent Diabetes

LDL Low-density lipoprotein

MDI Multiple daily injection

PwD People with type 1 diabetes

TAR Time above range

TBR Time below range

TDD Total daily dose/kg of body weight

TG Triglycerides (TG)

TIR Time in range

T1D Type 1 diabetes

WC Waist circumference

WHtR Waist-to-height ratio

One year after gestational diabetes: metabolic changes and predictors of postpartum dysglycaemia

Alessia Gaglio1  · Yana Pigotskaya1  · Gabriele Rossi2  · Marco Mirani3  · Federico Giacchetti5  · Valeria Grancini1  · Valeria Maggi2  · Giovanna Mantovani1,4 · Irene Cetin2,4 · Emanuela Orsi5  · Veronica Resi1

Received: 21 November 2025 / Accepted: 17 January 2026

© The Author(s) 2026

Abstract

Background Women with previous gestational diabetes mellitus (GDM) are at high risk of developing type 2 diabetes mel-litus (T2DM). Although early postpartum screening is recommended, metabolic changes occurring during the first year remain poorly characterized, and Italian guidelines do not include assessment at this time point.

Aim To evaluate glycaemic and metabolic changes one year after delivery in women with previous GDM and identify clini-cal and lifestyle predictors of postpartum glucose impairment.

Methods A cohort of 134 women with prior GDM was assessed at 6–12 weeks (T0) and one year postpartum (T1). Anthro-pometric, biochemical, nutritional, lifestyle, and quality-of-life parameters were collected. Dietary habits were evaluated using a 3-day food diary and the PREDIMED questionnaire; physical activity was assessed using the International Physical Activity Questionnaire (IPAQ). Logistic regression models were used to identify predictors of altered OGTT at T1.

Results At baseline, 32.9% of women showed altered OGTT; this increased to 38.8% at one year, while T2DM prevalence rose from 2.2 to 5.2%. Insulin therapy during pregnancy was the only independent predictor of dysglycaemia at T1 (OR 3.5, 95% CI 1.28–9.50, p=0.015). Women with altered OGTT reported lower SF-36 scores in the domains “role limitations due to physical health” (p=0.016) and “health change” (p=0.030). Breastfeeding was associated with more favourable glucose outcomes (p=0.009).

Conclusions One-year follow-up after GDM reveals early metabolic and psychosocial differences not detectable in the early postpartum period. Insulin therapy during pregnancy strongly predicts glucose impairment, highlighting the need for extended postpartum surveillance and targeted lifestyle interventions.

Keywords Gestational diabetes · Postpartum follow-up · Impaired glucose tolerance · Lifestyle · Breastfeeding

Communicated by Annunziata Lapolla.

Alessia Gaglio

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1 Endocrinology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122 Milan, Italy

2 Obstetric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy

3 Endocrinology, Diabetology and Andrology Unit, IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano, 20089 Milan, Italy

4 Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy

5 Diabetology and Nutritional Unit, Department of Specialist Medicine, ASST Santi Paolo e Carlo, Milan, Italy

Metabolic challenges in rheumatoid arthritis: a translational overview from pathogenesis to patient care

Sara Ferrigno1  · Eneida Çela1  · Mauro Fatica1,2 · Benedetta Monosi1  · Arianna D’Antonio1  · Paola Conigliaro1  · Marina Cardellini3,4 · Susanna Longo3,4 · Massimo Federici3,4 · Maria Sole Chimenti1

Received: 20 February 2026 / Accepted: 26 March 2026 © The Author(s) 2026

Abstract

Rheumatoid arthritis (RA) is an inflammatory disease characterized by a higher burden of cardiovascular and metabolic diseases than in the general population. Altered lipid and glucose metabolic pathways are widely observed, primarily due to chronic inflammation. However, metabolic dysfunction may also affect RA pathogenesis, further enhancing immune cell activation and joint damage. Glucose and lipid alterations observed in RA help define the comorbidity burden of this disease, significantly affecting disease activity and prognosis. The aim of the present review is to describe the role of metabolic dysfunctions in RA and to examine how disease activity and treatments can influence these conditions. We also summarized the main management strategies based on current literature and developed a cardiometabolic monitoring algorithm across different clinical settings to support daily patient care of these patients.

Keywords Rheumatoid arthritis · Glucose metabolism · Lipid metabolism · Atherogenesis · Inflammation · Immune-metabolism · Cardiovascular risk

Sara Ferrigno and Eneida Çela contributed equally to this manuscript

Communicated by Salvatore Corrao, M.D

Sara Ferrigno

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1 Rheumatology, Allergology and Clinical Immunology, Department of Systems Medicine, Department of “Medicina dei Sistemi”, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy

2 Academic Rheumatology Unit, Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, Via Giovanni Paolo II, C/da Tappino, Campobasso 86100, Italy

3 Department of Systems Medicine, University of Rome Tor Vergata, Via Montpellier 1, Rome 00133, Italy

4 Center for Atherosclerosis, Policlinico Tor Vergata, Viale Oxford 81, Rome 00133, Italy

Associations between cardiometabolic traits and diabetic cardiomyopathy: an imaging-based analysis

Georgios Mavraganis1  · Dimitrios Bampatsias1,2 · Christina Konstantaki1  · Kamil Stankowski3,4 ·Stavros Athanasopoulos1  · Chrysoula Moustou1  · Alexandros Alexandropoulos1  · Stefano Figliozzi3,4 ·Angelos Soranides1  · Ioannis Petropoulos1  · Dimitrios Klettas5  · Kimon Stamatelopoulos1,6 ·Georgios Georgiopoulos1,7

Received: 12 December 2025 / Accepted: 15 March 2026 © The Author(s) 2026

Abstract

Introduction Diabetic cardiomyopathy (DCM) often evades diagnosis before manifestation of clinical symptoms. In this study we explored how cardiometabolic traits influence early cardiac structure and function in asymptomatic people living with diabetes (PwD), using advanced imaging.

Methods We conducted a cross-sectional study of 88 participants: 57 people living with type 2 diabetes (PwT2D), 16 people living with type 1 diabetes (PwT1D) and 15 controls. All subjects underwent transthoracic echocardiography and/or cardiac magnetic resonance (CMR) imaging. Strain analysis, perfusion indices, and tissue characterization (T1, T2, and extracellular volume) were assessed. Arterial stiffness via pulse wave velocity (PWV), ventricular-arterial coupling (VAC), circulating biomarkers and liver fibrosis indices were evaluated.

Results PwD had lower cardiac index than controls. Global longitudinal strain (GLS) and global radial strain were lower in both diabetes mellitus (DM) groups, while left atrial strain was most impaired in PwT2D (β-coefficient= − 11.77, P=0.003). DM duration≥10 years was associated with worse GLS (β-coefficient= − 2.18, P=0.033) and right VAC (β-coefficient= − 0.27, P=0.027) after multivariable analysis. While tissue characterization and perfusion indices showed no significant group differences, tight glycemic control in PwD correlated with improved myocardial strain parameters. PwT2D exhib-ited greater arterial stiffness (β-coefficient=1.52, P=0.003). In PwD, elevated non-alcoholic fatty liver disease score cor-related with increased left ventricular mass (β-coefficient=6,195, P=0.022) and decreased left ventricular ejection fraction (LVEF) (β-coefficient= − 3.12, P=0.017). Higher growth differentiation factor levels were associated with reduced LVEF (β-coefficient= − 0.005, P=0.029).

Conclusion This multimodal imaging study highlights myocardial and vascular changes in asymptomatic PwD. Early com-prehensive cardiovascular assessment may help identify dysfunction before overt heart failure develops.

Keywords Diabetic cardiomyopathy · Cardiac magnetic resonance · Echocardiography · Arterial stiffness · Ventricular-arterial coupling · Liver fibrosis

Role of automated insulin delivery (AID) systems in glucose control in patients with diabetes mellitus undergoing dialysis in Calabria: AID-DIAL-CAL

Elena Succurro1,2  · Giuseppe Cersosimo3  · Paola Sarnelli4  · Francesco Brisinda1  · Ilaria Gattuso1  · Valeria Mazza1  ·Giuseppe Fabiano1  · Fiorella Iorio3  · Roberta Arena3  · Giovanni Mazzitello5  · Ramona Nicotera5  · Maria Capria1  ·Gianluigi Zaza6  · Michele Andreucci1  · Raffaele Mancini5  · Francesco Andreozzi1,2

Received: 22 December 2025 / Accepted: 16 March 2026© The Author(s) 2026

Abstract

Aims To describe the main glycemic outcomes and the Quality of Life (QOL) observed in a cohort of people with type 1(T1D) or type 2 (T2D) insulin-treated diabetes under dialysis who started an Automated Insulin Delivery (AID) system.

Methods This is a longitudinal retrospective pilot real-world analysis of 14 individuals with T1D and T2D undergoingdialysis who began using an AID system to optimize glycemic control. All subjects used the MiniMed™ 780G system. Glu-cose metrics were collected at baseline, 3, 6, and 12 months after initiating the SmartGuard™ feature. The WHOQoL-Bref questionnaire was administered at the last follow-up to evaluate the QOL.

Results Out of the 14 people, 8 reached 1-year follow-up. Time in Range (TIR) increased from 63% at baseline to 69% at 12 months, Time Below Range <70 mg/dL (TBR70) decreased from 0.3% to 0%, and Time Above Range >250 mg/dL (TAR250) decreased from 6.7% to 3.9%. Seven out of eight subjects who reached a 12-month follow-up achieved all three glycemic targets for this fragile population (TIR>50%, TBR70<1% and TAR250<10%). At the last follow-up, 58.3% of the users were satisfied or very satisfied with their health status, versus only 25% with the previous treatment, and 81.7% had a good or very good QOL, whereas only 8.3% had a good QOL, and no one had a very good QOL with the previous

Conclusion This pilot real-world study showed how the use of an AID system is safe and can help to improve the glycemic outcomes and the QOL of people with diabetes in dialysis.

Keywords Automated insulin delivery system · End-stage kidney disease · Dialysis · Time in range · Diabetes mellitus · Quality of Life

Communicated by Salvatore Corrao, M.D

Elena Succurro

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1 Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, Viale Europa, Catanzaro 88100, Italy

2 Research Center for the Prevention and Treatment of Metabolic Diseases (CR METDIS), University Magna Graecia of Catanzaro, Catanzaro, Italy

3 Azienda Ospedaliera Annunziata Cosenza, Cosenza, Italy

4 ASL Viterbo, Viterbo, Italy

5 ASP Catanzaro, Catanzaro, Italy

6 Department of Civil Engineering, University of Calabria, Rende, Italy