A nationwide registry-based cohort study of the association between childhood dental caries and gingivitis with type 2 diabetes in adulthood

Nikoline Nygaard1  · Anne Kirstine Eriksen2  · Lars Ängquist3  · Daniel Belstrøm1  · Evelina Stankevic3  · Torben Hansen3  · Anja Olsen2  · Merete Markvart1

Received: 15 August 2024 / Accepted: 22 December 2024 / Published online: 13 January 2025 © The Author(s) 2025

Abstract

Background Evidence suggests a bidirectional relationship between oral health status and type 2 diabetes (T2D) in adults. Studies on associations between childhood oral health and T2D in adulthood are lacking.

Methods This is a nationwide Danish registry-based cohort study of individuals born between 1963 and 1972, having at least one registration in the National Child Odontology Registry between 1972 and 1987 (n=627,758). Follow-up lasted from 1995 to 2018. Main exposure variables were the highest achieved levels of dental caries and gingivitis between 1972 and 1987. The outcome was T2D diagnosis during follow-up. Data was analyzed using Cox-regression, stratified on sex, with age as the underlying timescale and highest achieved level of education between age 25–30 years as Cox-strata. Main analyses were conducted with and without age-restrictions (T2D diagnosis before/after age 40).

Results Compared to lowest-level references, high levels of gingivitis associated with increased hazard ratios (HRs) of T2D in both males (HR [95% confidence interval]: 1.59 [1.47; 1.72]) and females (1.87 [1.68; 2.08]), as did severe dental caries (males: (1.15 [1.04; 1.27], in females: 1.19 [1.06; 1.35]). Below age 40, gingivitis associated with increased HRs in males (1.84 ([1.58; 2.15]) and females (1.94 [1.63; 2.30]). Above age 40, both exposures displayed higher HRs in males (high gin-givitis: 1.52 [1.39; 1.66] vs. severe caries: 1.23 [1.09; 1.38]) and females (1.83 [1.59; 2.10] vs. 1.37 [1.17; 1.59]).

Conclusions Data suggest an association between childhood dental caries and gingivitis with risk of receiving a T2D diag-nosis in adulthood. However, results are affected by residual confounding warranting further studies.

Keywords Cohort studies · Dental caries · Diabetes mellitus · Type 2 · Gingivitis

Improving detection of monogenic diabetes through reanalysis of GCK variants of uncertain significance

Sunita M. C. De Sousa1,2,3  · Jennifer M. N. Phan4,5 · Amanda Wells4  · Kathy H. C. Wu6,7,8,9 · Hamish S. Scott1,4,10

Received: 12 December 2024 / Accepted: 3 January 2025 / Published online: 16 January 2025 © The Author(s) 2025, corrected publication 2025

Abstract

Aims To assess the utility of reanalysing GCK variants of uncertain significance (VUS) as an intervention to improve the detection of monogenic diabetes.

Methods We examined GCK VUS in a local cohort of individuals with suspected monogenic diabetes and re-curated each variant against the recent ClinGen GCK-specific variant classification guidelines.

Results Variant reanalysis achieved a new ‘likely pathogenic’ classification (i.e., positive results) in 4/8 identified VUS.The single most common newly applied criterion indicating variant pathogenicity was a confirmed phenotype of GCK-hyperglycaemia. RNA sequencing and segregation studies were performed in two cases but not additive to reclassification.

Conclusions This is the first VUS reclassification study in monogenic diabetes using gene-specific guidelines. Within the limits of this small study, we observed a high rate (50%) of VUS upgrades to a positive result, thereby confirming the util-ity of VUS reanalysis– particularly with biochemical phenotyping– in increasing the detection of monogenic diabetes. We recommend HbA1c, fasting blood glucose and either pancreatic autoantibody negativity or a small oral glucose tolerance test increment as a feasible minimum dataset to inform variant classification at the individual patient level, noting the ongoing work of the ClinGen Monogenic Diabetes Expert Panel in systematically reviewing GCK variants at the international level.

Keywords Glucokinase · Monogenic diabetes · DNA sequencing · Genetics

Abbreviations

PVS Pathogenic very strong

PS Pathogenic strong

PM Pathogenic moderate

PP Pathogenic supporting

FHx Family history

AR Autosomal recessive

del/ins Deletion/insertion

IFG Impaired fasting glucose

OGTT Oral glucose tolerance test

Communicated by Massimo Federici, M.D.

Sunita M. C. De Sousa

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1 Adelaide Medical School, University of Adelaide, Adelaide, Australia

2 Endocrine & Metabolic Unit, Royal Adelaide Hospital, Adelaide, Australia

3 Adult Genetics Unit, Royal Adelaide Hospital, Adelaide, Australia

4 Department of Genetics & Molecular Pathology, SA Pathology, Adelaide, Australia

5 Flinders Medical School, Flinders University, Adelaide, Australia

6 Clinical Genomics, St Vincent’s Hospital, Darlinghurst, Australia

7 School of Medicine, University of New South Wales, Sydney, Australia

8 Discipline of Genomic Medicine, Faculty of Medicine and Health, University of Sydney, Sydney, Australia

9 School of Medicine, University of Notre Dame, Sydney, Australia

10 Centre for Cancer Biology, an alliance between SA Pathology, University of South Australia, Adelaide, Australia

A web-based application for diabetes subtyping: The DDZ DiabetesCluster-Tool

Tim Mori1,2  · Katsiaryna Prystupa2,3  · Klaus Straßburger1,2  · Marc Bonn2,4 · Oana Patricia Zaharia2,3,5  · Olaf Spörkel2,4 · Oliver Kuß1,2,6  · Michael Roden2,3,5  · Robert Wagner2,3,5

Received: 10 December 2024 / Accepted: 13 December 2024 / Published online: 17 January 2025 © The Author(s) 2025

Gestational diabetes severity stratification during pregnancy: role of plasma oleic acid as a possible early marker

Chiara M. Soldavini1  · Gabriele Piuri1  · Paola A. Corsetto2  · Irma Colombo2  · Veronica Resi3  · Stefania Zava2  · Gabriele Rossi1  · Enrico Ferrazzi1,4 · Angela M. Rizzo2

Received: 27 December 2024 / Accepted: 2 March 2025 / Published online: 1 April 2025 © The Author(s) 2025

Abstract

Normal pregnancy is characterized by changes in lipid metabolism with significant implications for the health of both mother and offspring. When these changes develop into maternal dyslipidemia, a significant association with adverse pregnancy outcomes has been observed, including the development of gestational diabetes (GD), modulation of the inflam-matory response, and excessive fetal growth. In the present study, we performed a lipidomic assessment of patients at GD diagnosis (24–28 weeks of gestation) and 12 weeks after diagnosis. We found higher levels of esterified oleic acid in plasma at the time of GD diagnosis in women who subsequently required pharmacological therapy to control blood glu-cose levels compared to those who did not require additional treatment, suggesting that the measurement of plasma oleic acid might be an additional tool for the early identification of patients with a more severe form of gestational diabetes. Moreover, plasma oleic acid levels showed a positive correlation with fetal growth in the context of adequate glycemic control, supporting a metabolic dysregulation of other pathways whose identification could help clinicians to discriminate different cases within the spectrum of severity of the disease. Finally, the correlation between plasma oleic acid and circu-lating BAFF levels at the time of diagnosis and 12 weeks later adds a possible mechanism to support the pro-inflammatory and pro-diabetic state in the metabolic set of GD. Overall, these findings strongly support the role of plasma oleic acid as a possible early marker for GD severity stratification during pregnancy.

Keywords Gestational diabetes · Lipidomics · Oleic acid · Fatty acid · Pregnancy inflammation · Biomarker

Glial fibrillary acidic protein: a potential biomarker for small fiber neuropathy?

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

Research progress on risk prediction models for the diabetic foot

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