Pillars Article: Islet-cell Antibodies in Diabetes Mellitus with Autoimmune Polyendocrine Deficiencies. Lancet. 1974. 304: 1279-1283

Organ-specific autoimmune markers in adult patients with type 1 diabetes mellitus

AIM

We aimed to investigate the presence of thyroid, celiac disease (CD) and anti-parietal cell antibodies (APCA) in adult type 1 diabetes (T1DM) patients.

METHODS

Data of 287 T1DM patients >16 years old were reviewed retrospectively. Thyroid disease related, CD related antibodies and APCA were evaluated. Patients were divided into early onset (<30 years old) and late-onset (≥30 years old) TIDM, and ≤10 years, 11-20 years and >20 years according to disease duration.

RESULTS

There were 142 (49.5%) female and 145 (50.5%) male patients. The median age at diagnosis and disease duration were 21 (2-53) and 6.91 (0-50.8) years, respectively. Antibody positivity rates were anti-glutamic acid decarboxylase (anti-GAD) 72.8%, anti-insulin 9.1%, anti-islet cell 25.7%, antithyroid peroxidase (anti-TPO) 34.8%, anti-thyroglobulin 19.9%, anti-endomysial IgA (EMA-IgA) 7.6%, anti-gliadin IgA (AGA-IgA), 12.2%, AGA-IgG 13.0%, tissue transglutaminase IgA 7.1% and APCA 14.4%. One hundred twenty-eight (44.6%) patients had at least one non-diabetes autoantibody. Thyroid autoantibodies and dysfunction were significantly higher in women than men. Anti-TPO positivity was higher in the late-onset group (P = .044). Anti-GAD level was correlated with thyroid related antibody positivity in male patients with positive anti-GAD (r: .340, P: .006). The positivity of EMA-IgA and AGA-IgA was higher in patients with disease duration >20 years (P = .017 and .039, respectively).

CONCLUSION

Almost half of the adult T1DM patients were positive for at least one non-diabetic antibody. It is important to investigate thyroid autoimmunity in patients diagnosed with T1DM at any age, including advanced age. CD associated antibody positivity increases with disease duration, suggesting that they should be re-evaluated at clinical suspicion, even if prior tests were negative.

β-Cell Death in Diabetes: Past Discoveries, Present Understanding, and Potential Future Advances

β-cell death is regarded as a major event driving loss of insulin secretion and hyperglycemia in both type 1 and type 2 diabetes mellitus. In this review, we explore past, present, and potential future advances in our understanding of the mechanisms that promote β-cell death in diabetes, with a focus on the primary literature. We first review discoveries of insulin insufficiency, β-cell loss, and β-cell death in human diabetes. We discuss findings in humans and mouse models of diabetes related to autoimmune-associated β-cell loss and the roles of autoreactive T cells, B cells, and the β cell itself in this process. We review discoveries of the molecular mechanisms that underlie β-cell death-inducing stimuli, including proinflammatory cytokines, islet amyloid formation, ER stress, oxidative stress, glucotoxicity, and lipotoxicity. Finally, we explore recent perspectives on β-cell death in diabetes, including: (1) the role of the β cell in its own demise, (2) methods and terminology for identifying diverse mechanisms of β-cell death, and (3) whether non-canonical forms of β-cell death, such as regulated necrosis, contribute to islet inflammation and β-cell loss in diabetes. We believe new perspectives on the mechanisms of β-cell death in diabetes will provide a better understanding of this pathological process and may lead to new therapeutic strategies to protect β cells in the setting of diabetes.

Diabetes Risk Data Mining Method Based on Electronic Medical Record Analysis

In today's society, the development of information technology is very rapid, and the transmission and sharing of information has become a development trend. The results of data analysis and research are gradually applied to various fields of social development, structured analysis, and research. Data mining of electronic medical records in the medical field is gradually valued by researchers and has become a major work in the medical field. In the course of clinical treatment, electronic medical records are edited, including all personal health and treatment information. This paper mainly introduces the research of diabetes risk data mining method based on electronic medical record analysis and intends to provide some ideas and directions for the research of diabetes risk data mining method. This paper proposes a research strategy of diabetes risk data mining method based on electronic medical record analysis, including data mining and classification rule mining based on electronic medical record analysis, which are used in the research experiment of diabetes risk data mining method based on electronic medical record analysis. The experimental results in this paper show that the average prediction accuracy of the decision tree is 91.21%, and the results of the training set and the test set are similar, indicating that there is no overfitting of the training set.

Gluten Free Diet for the Management of Non Celiac Diseases: The Two Sides of the Coin

A lifelong adherence to a gluten-free (GF) diet is currently the only treatment for Celiac disease (CD), an autoimmune disorder that arises after gluten ingestion in individuals who are genetically predisposed. The gluten intake exerts toxic effects through several pathways involving gut barrier integrity, intestinal microbiota composition and immune system stimulation. However, despite the great benefit of GF diet for CD patients, its use has been debated. Indeed, individuals who adopt this diet regime may be at risk of nutrient deficiencies. Emerging evidence supports a beneficial effect of a GF diet also for other pathological conditions, including gluten-related disorders (GRD) often associated to CD, such as Non celiac gluten sensitivity (NCGS) and Dermatitis Herpetiforme (DH) as well as Irritable bowel syndrome (IBS) and Diabetes. This suggests a pathogenic role of gluten in these conditions. Despite the growing popularity of GF diet among consumers, to date, there are limited evidences supporting its use for the management of non-celiac diseases. Therefore, in this review, we discuss whether the GF diet could really improve the general quality of life of patients with GRD and non-GRD conditions, keeping in mind its sensorial limitations and nutritional inadequacies. In addition, we discuss the current motivations, leading to the use of a GF diet, despite the inferior quality of GF products respect to those containing gluten.