C-peptide levels and the prevalence of islets autoantibodies in children with type 1 diabetes mellitus with different duration of the disease

BACKGROUND: T1D is characterized by autoimmune destruction of pancreatic β-cells, which develops due to genetic and environmental risk factors. Shortly after initiating the treatment with insulin, 80% of children with T1D may require smaller doses of insulin and develop clinical and laboratory remission of the disease so called «honeymoon». The issue of whether there is a need of differential diagnosis between autoimmune DM and non-immune forms of DM raises in cases of preclinical diagnosis of T1D and laboratory remission for more than 6 months.AIM: To study the clinical, immunological, genetic characteristics of T1D remission phase and MODY in children, to determine the diagnostic criteria for T1D and MODY in children.MATERIALS AND METHODS: A single-centre, cross sectional noncontrolled comparative study of two independent cohorts. Data of 150 children examined in the Endocrinology Research Center (January 2016–June 2021). First cohort included patients with complete clinical and laboratory remission of T1D (n=36), second cohort included patients with MODY, confirmed by genetic study (n=114).RESULTS: The median age of diabetes manifestation was significantly higher in patients with T1D — 11.25 years [8.33; 13.78] than in patients with MODY — 7.5 years [4.6; 12.2] (p=0.004). In patients with T1D remission the level of glycated hemoglobin was 6.0% [5.6; 6.4], in group with MODY — 6.5% [6.2; 6.7] (p<0.001). Patients with monogenic diabetes had impaired fasting glucose — 6.27 mmol/l [5.38; 6.72], while patients with remission phase had normoglycemia — 5.12 mmol/l [4.17; 5.87]. The oral glucose tolerance test was perform to all patients, two-hour glucose level did not significantly differ in two groups (p=0.08). A strong family history of diabetes in patients with MODY registered more often (93% vs. 66.7%). A positive autoantibody titer detected more often in patients with remission of T1D (77.8%) than in patients with MODY (11.4%). In addition, no more than 1 type of autoantibodies was detected in patients with MODY.CONCLUSION: Antibodies ZnT8 and IA2 showed the greatest significance for the differential diagnosis of T1D and MODY in cases with long absents of insulin requirement in children with diabetes mellitus. Genetic test is recommended in seronegative cases. If only one type of AT is detected, specialist should decide on the need to do diagnostic genetic test based on a comprehensive analysis of the patient’s clinic characteristics, including family history, manifestation and blood glucose levels.

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The role of specific pancreatic antibodies in the differential diagnosis of complete clinical and laboratory remission of type 1 diabetes mellitus and MODY in children

Sechko

Romanenkova

Еремина

et al. 2022

Diabetes mellitus

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Islet autoantibodies and residual beta-cell function in children with type 1 diabetes depending on age of manifestation

Romanenkova,

Zufarova,

Sorokin

et al. 2023

Diabetes mellitus

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BACKGROUND: Type 1 diabetes mellitus (T1D) is an autoimmune disorder that leads to pancreatic β-cells destruction and progressive decrease of insulin secretion. Specific islet autoantibodies (AAbs) are the main diagnostic marker of T1D. Residual β-cell function, as measured by C-peptide, has repeatedly been demonstrated to be clinically important.AIM: To study the frequency and levels of residual C-peptide secretion and persistence of pancreatic AAbs in children with T1D with different duration and age of manifestation of the disease.MATERIALS AND METHODS: The levels of C-peptide and AAbs to ZnT8 (zinc transporter 8), AAbs to IA-2 (Insulinoma Antigen 2), AAbs to GAD (Glutamate Decarboxylase), IAA (insulin autoantibodies) were measured. Patients were divided into 3 groups depending on the duration of T1D (1st — <1 year, 2nd — from 1 to 5 years, 3rd — >5 years) and age of manifestation (A — prepubertal and B — puberty).RESULTS: The median duration of T1D was 1.8 [0,8;3,9], 76.3% out of 1333 patients were seropositive, 40% had residual levels of C-peptide. With disease duration there were a decrease in AAbs+: 1st group 74%, 2nd group 69%, and 3rd group 48%. In all groups, percentage of patients with positive levels of one or more AAbs was significantly higher in children with T1D manifestation at puberty. GADA and ZnT8A were more common in the first year of the disease. IA-2A were observed with the same frequency in the group of adolescents. IAA were more common in patients at prepubertal age. An undetectable level of C-peptide was observed significantly higher in children with T1D manifestation in prepubertal age (p<0.05): 1А — 13% and 1B — 5%, 2А — 51% and 2B — 14%, 3А — 82% and 3B — 50%, reference range of C-peptide was observed in adolescents (p<0,05): 1А — 6% and 1B — 44%, 2А — 2% and 2b — 25%, 3А — 2% and 3B — 11%.CONCLUSION: AAbs+ is relatively common in children with T1D and about half of them are seropositive in more than 5 years after manifestation. GADA and ZnT8A have high specificity for patients with new-onset T1D. C-peptide secretion depends on the age of the disease manifestation.

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Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus

Sorokin,

Trufanova,

Rebrova

et al. 2024

Diabetes mellitus

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BACKGROUND: Widely available diabetes devices (continuous glucose monitoring, insulin pump etc.) generate large amount of data and development of an advanced clinical decision support system (CDSS), able to automatically evaluate and optimize insulin therapy, is relevant.AIM: Development of a mathematical model and an CDSS based on it to optimize insulin therapy in children with type 1 diabetes (T1D) and assessment of the agreement between the recommendations of the CDSS and the physician on insulin pump (IP) parameters: basal profile (BP), carbohydrate ratio (CR), correction factor (СF).MATERIALS AND METHODS: Data from 504 children with T1DM were analyzed over the period of 7875 days. The data included glucose, insulin, food, sex, age, height, weight, diabetes duration and HbA1c. We constructed recurrent neural network (RNN) to predict glucose concentration for 30-120 minutes, an algorithm for optimizing IP settings using prediction results. Next, a software product was developed — a CDSS. To assess the agreement of the recommendations of the CDSS and physicians, retrospective data from 40 remote telemedicine consultations of 40 patients with T1D (median age 11.6 years [7; 15]) were used and 960 points of possible adjustments were analyzed. Three degrees of agreement have been introduced: complete agreement, partial agreement, and complete disagreement. The magnitude of the adjustments was also analyzed.RESULTS: The accuracy of glycemic predictions was better or comparable with other similar models. The assessment of agreement for BP, CR and CF, according to the Kappa index, showed slight and weak agreement. The frequency of complete agreement between recommendations for adjusting the ongoing IP therapy between the CDSS and physicians is 37.5–53.8%, and complete inconsistency is 4.5–17.4%. From a clinical point of view, consistency in the frequency of occurrence of the indicator is more important. There were no differences in median IP settings between the CDSS and physicians.CONCLUSION: The CDSS has an acceptable accuracy of glycemic predictions. The CDSS and physicians provide comparable recommendations regarding CSII parameters.

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C-peptide levels and the prevalence of islets autoantibodies in children with type 1 diabetes mellitus with different duration of the disease

Cited by 4 publications

References 22 publications

The role of specific pancreatic antibodies in the differential diagnosis of complete clinical and laboratory remission of type 1 diabetes mellitus and MODY in children

The role of specific pancreatic antibodies in the differential diagnosis of complete clinical and laboratory remission of type 1 diabetes mellitus and MODY in children

Islet autoantibodies and residual beta-cell function in children with type 1 diabetes depending on age of manifestation

Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus

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