Childhood screening for type 1 diabetes comparing automated multiplex Antibody Detection by Agglutination-PCR (ADAP) with single plex islet autoantibody radiobinding assays.

BACKGROUND: Two or more autoantibodies against either insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A) or zinc transporter 8 (ZnT8A) denote stage 1 (normoglycemia) or stage 2 (dysglycemia) type 1 diabetes prior to stage 3 type 1 diabetes. Automated multiplex Antibody Detection by Agglutination-PCR (ADAP) assays in two laboratories were compared to single plex radiobinding assays (RBA) to define threshold levels for diagnostic specificity and sensitivity. METHODS: IAA, GADA, IA-2A and ZnT8A were analysed in 1504 (54% females) population based controls (PBC), 456 (55% females) doctor's office controls (DOC) and 535 (41% females) blood donor controls (BDC) as well as in 2300 (48% females) patients newly diagnosed (1-10 years of age) with stage 3 type 1 diabetes. The thresholds for autoantibody positivity were computed in 100 10-fold cross-validations to separate patients from controls either by maximizing the χ2-statistics (chisq) or using the 98th percentile of specificity (Spec98). Mean and 95% CI for threshold, sensitivity and specificity are presented. FINDINGS: The ADAP ROC curves of the four autoantibodies showed comparable AUC in the two ADAP laboratories and were higher than RBA. Detection of two or more autoantibodies using chisq showed 0.97 (0.95, 0.99) sensitivity and 0.94 (0.91, 0.97) specificity in ADAP compared to 0.90 (0.88, 0.95) sensitivity and 0.97 (0.94, 0.98) specificity in RBA. Using Spec98, ADAP showed 0.92 (0.89, 0.95) sensitivity and 0.99 (0.98, 1.00) specificity compared to 0.89 (0.77, 0.86) sensitivity and 1.00 (0.99, 1.00) specificity in the RBA. The diagnostic sensitivity and specificity were higher in PBC compared to DOC and BDC. INTERPRETATION: ADAP was comparable in two laboratories, both comparable to or better than RBA, to define threshold levels for two or more autoantibodies to stage type 1 diabetes. FUNDING: Supported by The Leona M. and Harry B. Helmsley Charitable Trust (grant number 2009-04078), the Swedish Foundation for Strategic Research (Dnr IRC15-0067) and the Swedish Research Council, Strategic Research Area (Dnr 2009-1039). AL was supported by the DiaUnion collaborative study, co-financed by EU Interreg ÖKS, Capital Region of Denmark, Region Skåne and the Novo Nordisk Foundation.

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

First European Case of Simultaneous Liver and Pancreas Transplantation as Treatment of Wolcott-Rallison Syndrome in a Small Child.

BACKGROUND: The concept of organ transplantation as treatment for complex genetic conditions, including Wolcott-Rallison syndrome (WRS), continues to show promise. Liver transplantation is essential for survival of patients with WRS, and pancreas transplantation cures their type I diabetes mellitus. METHODS: The recipient, a 3-year-old girl weighing 14 kg at the time of transplantation, suffered from major complications of WRS, including repetitive liver failure episodes and poorly controlled diabetes. The patient underwent a nonacute, combined, simultaneous liver and pancreas transplantation from a pediatric donor without using the en bloc technique. RESULTS: Well-preserved graft functions at 2-year follow-up with normal liver and pancreas function. CONCLUSIONS: This is the first case report of simultaneous liver and pancreas transplantation as treatment of WRS in a small child in Europe. Two-year follow-up demonstrates that organ transplantation can halt life-threating recurrent liver failure episodes and cure type 1 diabetes.

Practical management in Wolcott-Rallison syndrome with associated hypothyroidism, neutropenia, and recurrent liver failure: A case report.

Wolcott-Rallison syndrome is a rare genetic syndrome of neonatal diabetes, liver failure, and growth retardation. We present a case with a EIF2AK3 p.(Arg902Ter) mutation, additionally complicated by hypothyroidism, impaired renal function, and exocrine pancreas insufficiency, focusing on clinical management. For its optimization, thorough care of multiple organ systems is needed.

Childhood thyroid autoimmunity and relation to islet autoantibodies in children at risk for type 1 diabetes in the diabetes prediction in skåne (DiPiS) study.

BACKGROUND: The aim was to determine prevalence and age at seroconversion of thyroid autoimmunity in relation to islet autoantibodies, gender and HLA-DQ genotypes in children with increased risk for type 1 diabetes followed from birth. METHODS: In 10-year-old children (n = 1874), blood samples were analysed for autoantibodies against thyroid peroxidase (TPOAb), thyroglobulin (TGAb), glutamic acid decarboxylase 65 (GADA), Zink transporter 8 (ZnT8R/W/QA), insulinoma-associated protein-2 (IA-2A), insulin (IAA) and HLA-DQ genotypes. Prospectively collected samples from 2 years of age were next analysed for TPOAb, and TGAb and, finally, in confirming samples at 11-16 years of age along with TSH and FT4. Frequencies were tested with Chi-square or Fischer's exact tests, autoantibody levels with Wilcoxon and correlations between autoantibody levels with Spearman's rank correlation test. RESULTS: The prevalence of thyroid autoimmunity was 6.9%, overrepresented in girls (p < .001) also having higher TPOAb levels at 10 years (p = .049). TPOAb was associated with GADA (p = .002), ZnT8R/W/QA (p = .001) and IA-2A (p = .001) while TGAb were associated with ZnT8R/W/QA (p = .021). In boys only, TPOAb were associated with GADA (p = .002), IA-2A (p = .001), ZnT8R/W/QA (p = .001) and IAA (p = .009), and TGAb with GADA (p = .013), IA-2A (p = .005) and ZnT8R/W/QA (p = .003). Levels of IA-2A correlated to both TPOAb (p = .021) and to TGAb (p = .011). In boys only, levels of GADA and TGAb correlated (p = .009 as did levels of IA-2A and TPOAb (p = .013). The frequency and levels of thyroid autoantibodies increased with age. At follow-up, 22.3% had abnormal thyroid function or were treated with thyroxine. CONCLUSIONS: Thyroid autoimmunity and high TPOAb levels were more common in girls. In contrast, in boys only, there was a strong association with as well as correlation between levels of thyroid and islet autoantibodies. It is concluded that while girls may develop autoimmune thyroid disease (AITD) independent of islet autoantibodies, the risk for thyroid disease in boys may be linked to concomitant islet autoimmunity.