The Environmental Determinants of Diabetes in the Young (TEDDY) Study: 2018 Update

The impact of COVID-19 pandemic on the incidence, presentation, and management of type 1 diabetes in children and adolescents: a narrative review

Type 1 diabetes (T1D) is an autoimmune condition affecting approximately 1.5 million children and adolescents worldwide, with an incidence of approximately 2-3% each year and rising. During the recent COVID-19 pandemic, a significant increase in incidence of T1D in children and adolescents was observed in numerous countries worldwide, with an increased number of newly-diagnosed cases presenting with diabetic ketoacidosis. The increased frequency of T1D presenting with diabetic ketoacidosis has been attributed not only to the SARS-CoV-2 virus itself but also to the restrictions imposed by the pandemic. The shift to telemedicine and unwillingness to seek medical care due to fear of infection contributed to delayed diagnosis and more severe disease presentation. Furthermore, the periods of lockdown that were implemented during the pandemic presented multiple challenges for children and adolescents living with T1D and disrupted the management of their condition. Changes in physical activity and diet as well as shortage of medical supplies during that period have been linked to worsening of glycemic control, which were at least partly offset by increased parental involvement and use of telemedicine.

Structures and strategies for retaining an international pediatric cohort from birth: Lessons from The Environmental Determinants of Diabetes in the Young (TEDDY) study

Background

Retention of study participants in observational studies is essential to maintaining the representativeness of the population, minimizing selection bias, and assuring sufficient statistical power. The aim of this report is to describe the structures and strategies used to retain participants in The Environmental Determinants of Diabetes in the Young (TEDDY) Study, an observational study of children at increased genetic risk for type 1 diabetes followed in an intensive protocol from birth until age 15.

Methods

Teague et al.'s systematic review of study retention strategies identified four domains: barrier reduction; community building; follow-up/reminder; and tracing strategies (1). TEDDY retention strategies were categorized into each of these domains. A fifth category presented strategies unique to TEDDY.

Results

TEDDY employed over one hundred retention strategies during the 15 years of follow-up; many could be categorized within the Teague domains. Strategies unique to TEDDY included (1) study structures to support retention; (2) risk communication and education strategies specific to this population; (3) Data-informed retention strategies that addressed protocol challenges in real-time; and (4) implementation of a re-engagement protocol for those who had withdrawn from the study.

Conclusion

Pediatric cohort studies should include strategies, structures, and resources to address retention at the study's initiation and on an ongoing basis. Retention strategies should not remain static but change with the developmental needs of the child. Collecting and analyzing data on an ongoing basis permits retention strategies to be put in place to address protocol and retention challenges in real time.

Trial registration

ClinicalTrials.gov Identifier: NCT00279318.

Age-dependent gene expression trajectories during early childhood in children at increased risk for type 1 diabetes

Early childhood is a period of rapid growth and immune system development. It is also critical for type 1 diabetes (T1D) autoimmunity, which has a peak incidence between 1 and 2 years of age. Here, we investigated age-related longitudinal gene expression changes in peripheral blood mononuclear cells from children aged 3 months to 3 years who had an increased genetic risk for T1D, aiming to delineate gene expression trajectories and identify patterns potentially linked to the development of islet autoimmunity. We found 2 432 genes (12.5% of analyzed genes) to exhibit significant temporal dynamics in the first 3 years of life. These genes were grouped into six major clusters each demonstrating distinct expression trajectories of consistent increase or decrease with age, as well as U-shaped, and inverted U-shaped age-related patterns. Notably, genes in clusters with U-shaped expression trajectories, which mirrored the incidence of islet autoantibodies, were enriched for T1D susceptibility genes, particularly within the Major Histocompatibility Complex (MHC) region. This study underscores the dynamic nature of gene expression in early childhood and its potential connection to T1D risk.

Neonatal fungi promote lifelong metabolic health through macrophage-dependent β cell development

Loss of early-life microbial diversity is correlated with diabetes, yet mechanisms by which microbes influence disease remain elusive. We report a critical neonatal window in mice when microbiota disruption results in lifelong metabolic consequences stemming from reduced β cell development. We show evidence for the existence of a similar program in humans and identify specific fungi and bacteria that are sufficient for β cell growth. The microbiota also plays an important role in seeding islet-resident macrophages, and macrophage depletion during development reduces β cells. Candida dubliniensis increases β cells in a macrophage-dependent manner through distinctive cell wall composition and reduces murine diabetes incidence. Provision of C. dubliniensis after β cell ablation or antibiotic treatment improves β cell function. These data identify fungi as critical early-life commensals that promote long-term metabolic health.

Looking back at the TEDDY study: lessons and future directions

The goal of the TEDDY (The Environmental Determinants of Diabetes in the Young) study is to elucidate factors leading to the initiation of islet autoimmunity (first primary outcome) and those related to progression to type 1 diabetes mellitus (T1DM; second primary outcome). This Review outlines the key findings so far, particularly related to the first primary outcome. The background, history and organization of the study are discussed. Recruitment and follow-up (from age 4 months to 15 years) of 8,667 children showed high retention and compliance. End points of the presence of autoantibodies against insulin, GAD65, IA-2 and ZnT8 revealed the HLA-associated early appearance of insulin autoantibodies (1-3 years of age) and the later appearance of GAD65 autoantibodies. Competing autoantibodies against tissue transglutaminase (marking coeliac disease autoimmunity) also appeared early (2-4 years). Genetic and environmental factors, including enterovirus infection and gastroenteritis, support mechanistic differences underlying one phenotype of autoimmunity against insulin and another against GAD65. Infant growth and both probiotics and high protein intake affect the two phenotypes differently, as do serious life events during pregnancy. As the end of the TEDDY sampling phase is approaching, major omics approaches are in progress to further dissect the mechanisms that might explain the two possible endotypes of T1DM.

Current evidence on gender-related risk factors for type 1 diabetes, type 2 diabetes and prediabetes: a reappraisal of the Italian study group on gender difference in endocrine diseases

PURPOSE

Diabetes is a chronic disease with a significant socio-economic burden. Recognizing its risk factors and gender differences within its physio-pathological mechanisms may allow early diagnosis. This review aims to summarize the current evidence on gender differences in terms of prevalence, risk factors and pathogenesis for Type 1 Diabetes (T1D), Type 2 Diabetes (T2D) and prediabetes.

METHODS

A comprehensive search of English-language articles was conducted in PubMed, EMBASE and Cochrane Library until July 2024. We selected all studies that assessed gender differences on risk factors for diabetes and prediabetes.

RESULTS

T1D is an autoimmune disease, with a multifactorial pathogenesis. Contrary to most autoimmune diseases, it has a male gender bias, with a male predominance incidence after puberty, for which the involvement of hormones has been hypothesized in addition to genetic predisposition. In T2D, the accumulation of visceral adipose tissue is recognized as the main predisposing factor for insulin resistance and consequent β-cells loss and dysfunction. Sex hormones influence fat disposition resulting in different body composition between males and females and different metabolic impact. Gender differences in dietary patterns and socio-cultural determinants also influence the risk of T2D. Also, a gender-related risk factor has been detected in prediabetes; indeed, females are at greater risk of impaired glucose tolerance than males.

CONCLUSIONS

Evidence shows the existence of gender differences in risk factors for T1D, T2D and prediabetes. This suggests that gender should be considered in prevention and screening programs, with the goal of reducing incidence or making an early diagnosis.

Longitudinal phage-bacteria dynamics in the early life gut microbiome

Microbial colonization of the human gut occurs soon after birth, proceeds through well-studied phases and is affected by lifestyle and other factors. Less is known about phage community dynamics during infant gut colonization due to small study sizes, an inability to leverage large databases and a lack of appropriate bioinformatics tools. Here we reanalysed whole microbial community shotgun sequencing data of 12,262 longitudinal samples from 887 children from four countries across four years of life as part of the The Environmental Determinants of Diabetes in the Young (TEDDY) study. We developed an extensive metagenome-assembled genome catalogue using the Marker-MAGu pipeline, which comprised 49,111 phage taxa from existing human microbiome datasets. This was used to identify phage marker genes and their integration into the MetaPhlAn 4 bacterial marker gene database enabled simultaneous assessment of phage and bacterial dynamics. We found that individual children are colonized by hundreds of different phages, which are more transitory than bacteria, accumulating a more diverse phage community over time. Type 1 diabetes correlated with a decreased rate of change in bacterial and viral communities in children aged one and two. The addition of phage data improved the ability of machine learning models to discriminate samples by country. Finally, although phage populations were specific to individuals, we observed trends of phage ecological succession that correlated well with putative host bacteria. This resource improves our understanding of phage-bacteria interactions in the developing early life microbiome.

Data from a multi-year targeted proteomics study of a longitudinal birth cohort of type 1 diabetes

The deployment of liquid chromatography-mass spectrometry-based plasma proteomics experiments in a large cohort is sparse, leading to a lack of data available for benchmarking, method development or validation. Comprised of 6,426 plasma analyses, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics experiments in the literature to date. The proteomics data from this study were generated over the course of 2.5 years from over 900 study subjects, each providing up to 29 longitudinal samples. The data also includes 916 quality control samples. The targeted mass spectrometry assay was comprised of 694 peptides mapping to 167 proteins and the panel was measured in each subject and QC sample. The targeted proteomic dataset presented here can be used as a resource for new computational methods development, such as for batch correction, as well as for benchmarking and comparing the performance of different methods/tools.

COVID-19 infection and inactivated vaccination: Impacts on clinical and immunological profiles in Chinese children with type 1 diabetes

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has been linked to an increased incidence of diabetes and diabetic ketoacidosis (DKA). However, the relationship between COVID-19 infection and progression to type 1 diabetes (T1D) in children has not been well defined.

AIM

To evaluate the influence of COVID-19 infection and inactivated vaccine administration on the progression of T1D among Chinese children.

METHODS

A total of 197 newly diagnosed patients with T1D were retrospectively enrolled from Children's Hospital of Fudan University between September 2020 and December 2023. The patients were divided into three groups based on their history of COVID-19 infection and vaccination: the infection group, the vaccination-only group, and the non-infection/non-vaccination group. Comprehensive clinical assessments and detailed immunological evaluations were performed to delineate the characteristics and immune responses of these groups.

RESULTS

The incidence of DKA was significantly higher in the COVID-19 infection group (70.2%) compared to the non-infection/non-vaccination group (62.5%) and vacscination-only group (45.6%; P = 0.015). Prior COVID-19 infection was correlated with increased DKA risk (OR: 1.981, 95%CI: 1.026-3.825, P = 0.042), while vaccination was associated with a reduced risk (OR: 0.558, 95%CI: 0.312-0.998, P = 0.049). COVID-19 infection mildly altered immune profiles, with modest differences in autoantibody positivity, lymphocyte distribution, and immunoglobulin levels. Notably, HLA-DR3 positive children with a history of COVID-19 infection had an earlier T1D onset and lower fasting C-peptide levels than the HLA-DR3 negative children with a history of infection (both P < 0.05).

CONCLUSION

COVID-19 infection predisposes children to severe T1D, characterized by enhanced DKA risk. Inactivated vaccination significantly lowers DKA incidence at T1D onset. These findings are valuable for guiding future vaccination and T1D risk surveillance strategies in epidemic scenarios in the general pediatric population.

Understanding genetic variants in context

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

Untangling the genetics of beta cell dysfunction and death in type 1 diabetes

BACKGROUND

Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise.

SCOPE OF REVIEW

Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D.

MAJOR CONCLUSIONS

We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.

HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07)

OBJECTIVE

To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression.

RESULTS

First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression.

CONCLUSIONS

These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

Incidence and trends of type 1 diabetes before and after 2000 in the Western Pacific Region: A systematic review and meta-analysis

OBJECTIVES

To undertake a systematic review of publications describing Type 1 diabetes (T1DM) incidence, trends over time and associated factors in the Western Pacific Region (WPR).

METHODS

As per the PROSPERO-registered (CRD42019122646) protocol English (MEDLINE, Embase, Global Health) and Chinese data-bases (China National Knowledge Infrastructure, VIP, Wanfang) from onset to 31/12/2019 were searched for T1DM incidence in the WPR. Country level data extracted included annual crude incidence rates by sex, number of new cases per annum (p.a.) and cumulatively, and the population at-risk. A meta-analysis for T1DM incidence was performed (by region and narrow age-bands, where possible) with subgroup analyses by time and by region.

FINDINGS

Forty-five population-based studies (21 from China), published 1973-2017, estimated T1DM incidence, mostly in youth, in 11 WPR countries. After 2000, mean annual T1DM incidence/100,000 person years aged 0-14 years ranged from 0.9 (95 % confidence intervals (CI), 0.6-1.3) in Fiji to 23.2 (95 % CI, 21.3-25.2) in Australia. The mean annual increase over time ranged from 2.8 % in Australia (1990-2002) to 14.2 % in Shanghai (1997-2011). T1DM incidence increased most in China (2.7-fold over 30-years) then Thailand (2-fold over 15-years). Most studies documented increasing incidence with age, though only two studies included people aged ≥ 20 years. Many, but not all studies reported significantly higher T1DM incidence in females vs. males.

CONCLUSION

T1DM incidence in the WPR is generally increasing, varying by age, sex, time and country. Results increase understanding of regional T1DM incidence and inform research and healthcare strategies.

EVOO supplement prevents type 1 diabetes by modulating gut microbiota and serum metabolites in NOD mice

AIMS

Extra virgin olive oil (EVOO) is the highest quality olive oil available and has been shown to regulate postprandial blood glucose in patients with type 1 diabetes (T1D). However, it remains uncertain whether EVOO can prevent the onset of T1D. In this study, we investigated the potential preventive effect of orally administered EVOO on T1D in non-obese diabetic (NOD) mice.

MAIN METHODS

We analyzed changes in fecal microbes using 16 s rDNA sequencing and serum metabolites using Ultra High-Performance Liquid Chromatography and Quadrupole Time-of-Flight Mass Spectrometry (Q-TOF-MS).

KEY FINDINGS

Our findings showed that EVOO supplementation in NOD mice slowed gastric emptying, reduced insulitis, and delayed T1D onset. Moreover, EVOO altered the composition of fecal microbes, increasing the Bacteroidetes/Firmicutes ratio, and promoting the growth of short-chain fatty acids (SCFAs)-producing bacteria, such as Lachnoclostridium and Ruminococcaceae_UCG-005. Moreover, it also increased beneficial serum metabolites, including unsaturated fatty acid and triterpenoid, which positively correlated with the increased SCFA-producing bacteria and negatively correlated with the disease indicators. Conversely, most decreased serum lipid metabolites, such as Oleamide, showed the opposite trend.

SIGNIFICANCE

Our study demonstrates that EVOO may ameliorate pancreas inflammation and prevent T1D onset in NOD mice by modulating gut microbiota and serum metabolites.

Gastrointestinal Infections Modulate the Risk for Insulin Autoantibodies as the First-Appearing Autoantibody in the TEDDY Study

OBJECTIVE

To investigate gastrointestinal infection episodes (GIEs) in relation to the appearance of islet autoantibodies in The Environmental Determinants of Diabetes in the Young (TEDDY) cohort.

RESEARCH DESIGN AND METHODS

GIEs on risk of autoantibodies against either insulin (IAA) or GAD (GADA) as the first-appearing autoantibody were assessed in a 10-year follow-up of 7,867 children. Stool virome was characterized in a nested case-control study.

RESULTS

GIE reports (odds ratio [OR] 2.17 [95% CI 1.39-3.39]) as well as Norwalk viruses found in stool (OR 5.69 [1.36-23.7]) at <1 year of age were associated with an increased IAA risk at 2-4 years of age. GIEs reported at age 1 to <2 years correlated with a lower risk of IAA up to 10 years of age (OR 0.48 [0.35-0.68]). GIE reports at any other age were associated with an increase in IAA risk (OR 2.04 for IAA when GIE was observed 12-23 months prior [1.41-2.96]). Impacts on GADA risk were limited to GIEs <6 months prior to autoantibody development in children <4 years of age (OR 2.16 [1.54-3.02]).

CONCLUSIONS

Bidirectional associations were observed. GIEs were associated with increased IAA risk when reported before 1 year of age or 12-23 months prior to IAA. Norwalk virus was identified as one possible candidate factor. GIEs reported during the 2nd year of life were associated with a decreased IAA risk.

Phage-bacteria dynamics during the first years of life revealed by trans-kingdom marker gene analysis

Humans are colonized with commensal bacteria soon after birth, and, while this colonization is affected by lifestyle and other factors, bacterial colonization proceeds through well-studied phases. However, less is known about phage communities in early human development due to small study sizes, inability to leverage large databases, and lack of appropriate bioinformatics tools. In this study, whole genome shotgun sequencing data from the TEDDY study, composed of 12,262 longitudinal samples from 887 children in 4 countries, is reanalyzed to assess phage and bacterial dynamics simultaneously. Reads from these samples were mapped to marker genes from both bacteria and a new database of tens of thousands of phage taxa from human microbiomes. We uncover that each child is colonized by hundreds of different phages during the early years, and phages are more transitory than bacteria. Participants' samples continually harbor new phage species over time whereas the diversification of bacterial species begins to saturate. Phage data improves the ability for machine learning models to discriminate samples by country. Finally, while phage populations were individual-specific, striking patterns arose from the larger dataset, showing clear trends of ecological succession amongst phages, which correlated well with putative host bacteria. Improved understanding of phage-bacterial relationships may reveal new means by which to shape and modulate the microbiome and its constituents to improve health and reduce disease, particularly in vulnerable populations where antibiotic use and/or other more drastic measures may not be advised.

Circulating metabolic signatures of rapid and slow progression to type 1 diabetes in islet autoantibody-positive children

Aims/hypothesis

Appearance of multiple islet cell autoantibodies in early life is indicative of future progression to overt type 1 diabetes, however, at varying rates. Here, we aimed to study whether distinct metabolic patterns could be identified in rapid progressors (RP, disease manifestation within 18 months after the initial seroconversion to autoantibody positivity) vs. slow progressors (SP, disease manifestation at 60 months or later from the appearance of the first autoantibody).

Methods

Longitudinal samples were collected from RP (n=25) and SP (n=41) groups at the ages of 3, 6, 12, 18, 24, or ≥ 36 months. We performed a comprehensive metabolomics study, analyzing both polar metabolites and lipids. The sample series included a total of 239 samples for lipidomics and 213 for polar metabolites.

Results

We observed that metabolites mediated by gut microbiome, such as those involved in tryptophan metabolism, were the main discriminators between RP and SP. The study identified specific circulating molecules and pathways, including amino acid (threonine), sugar derivatives (hexose), and quinic acid that may define rapid vs. slow progression to type 1 diabetes. However, the circulating lipidome did not appear to play a major role in differentiating between RP and SP.

Conclusion/interpretation

Our study suggests that a distinct metabolic profile is linked with the type 1 diabetes progression. The identification of specific metabolites and pathways that differentiate RP from SP may have implications for early intervention strategies to delay the development of type 1 diabetes.

Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies

Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short-term) trial durations. Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual-level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes-related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2-h oral glucose tolerance values assessed at each visit were included as a time-varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.

Covid-19 infection in children and adolescents and its association with type 1 diabetes mellitus (T1d) presentation and management

Children seem to be affected by the new SARS-CoV-2 virus less severely than adults, with better prognosis and low mortality. Serious complications of COVID-19 infection in children include multisystem inflammatory response syndrome in COVID-19 infection (MIS-C), myo-or pericarditis and, less frequently, long COVID syndrome. On the other hand, adults with type 1 (T1D) or type 2 diabetes (T2D) are among the most vulnerable groups affected by COVID-19, with increased morbidity and mortality. Moreover, an association of SARS-CoV-2 with diabetes has been observed, possibly affecting the frequency and severity of the first clinical presentation of T1D or T2D, as well as the development of acute diabetes after COVID-19 infection. The present review summarizes the current data on the incidence of T1D among children and adolescents during the COVID-19 pandemic, as well as its severity. Moreover, it reports on the types of newly diagnosed diabetes after COVID infection and the possible pathogenetic mechanisms. Additionally, this study presents current data on the effect of SARS-CoV-2 on diabetes control in patients with known T1D and on the severity of clinical presentation of COVID infection in these patients. Finally, this review discusses the necessity of immunization against COVID 19 in children and adolescents with T1D.

Prevalence and detection rate of celiac disease in Italy: Results of a SIGENP multicenter screening in school-age children

BACKGROUND

Celiac disease is a common lifelong disorder. Recent studies indicate that the number of clinically detected cases has increased over the last decades, however little is known about changes in the prevalence and the detection rate of celiac disease.

AIM

To evaluate the current prevalence and detection rate of celiac disease in Italy by a multicenter, mass screening study on a large sample of school-age children.

METHODS

children aged 5-11 years were screened at school by HLA-DQ2 and -DQ8 determination on a drop of blood in six Italian cities; total serum IgA and IgA anti-transglutaminase were determined in children showing HLA-DQ2 and/or -DQ8 positivity. Diagnosis of celiac disease was confirmed according to the European guidelines.

RESULTS

5994 children were eligible, 4438 participated and 1873 showed predisposing haplotypes (42.2%, 95% CI=40.7-43.7). The overall prevalence of celiac disease was 1.65% (95% CI, 1.34%-2.01%). Only 40% of celiac children had been diagnosed prior to the school screening. Symptoms evoking celiac disease were as common in celiac children as in controls.

CONCLUSION

In this multicenter study the prevalence of celiac disease in school-age Italian children was one of the highest in the world. Determination of HLA predisposing genotypes is an easy and fast first-level screening test for celiac disease. Without a mass screening strategy, 60% of celiac patients remain currently undiagnosed in Italy.

Experiences of Caregivers and At-Risk Children Enrolled in a Prospective Pregnancy-Birth Cohort Study into the Causes of Type 1 Diabetes: The ENDIA Study

Background: We sought research experiences of caregivers and their children were enrolled in the Environmental Determinants of Islet Autoimmunity (ENDIA) study. Methods: ENDIA is a pregnancy–birth cohort investigating early-life causes of type 1 diabetes (T1D). Surveys were sent to 1090 families between June 2021 and March 2022 with a median participation of >5 years. Caregivers completed a 12-item survey. Children ≥ 3 years completed a four-item survey. Results: The surveys were completed by 550/1090 families (50.5%) and 324/847 children (38.3%). The research experience was rated as either “excellent” or “good” by 95% of caregivers, and 81% of children were either “ok”, “happy” or “very happy”. The caregivers were motivated by contributing to research and monitoring their children for T1D. Relationships with the research staff influenced the experience. The children most liked virtual reality headsets, toys, and “helping”. Blood tests were least liked by the children and were the foremost reason that 23.4% of the caregivers considered withdrawing. The children valued gifts more than their caregivers. Only 5.9% of responses indicated dissatisfaction with some aspects of the protocol. The self-collection of samples in regional areas, or during the COVID-19 pandemic restrictions, were accepted. Conclusions: This evaluation identified modifiable protocol elements and was conducted to further improve satisfaction. What was important to the children was distinct from their caregivers.

Gluten-free diet adherence in children with screening-detected celiac disease using a prospective birth cohort study

BACKGROUND

Celiac disease has an increasing incidence worldwide and is treated with lifelong adherence to a gluten-free diet. We aimed to describe gluten-free diet adherence rates in children with screening-identified celiac disease, determine adherence-related factors, and compare adherence to food records in a multinational prospective birth cohort study.

METHODS

Children in The Environmental Determinants of Diabetes in the Young study with celiac disease were included. Subjects had at least annual measurement of adherence (parent-report) and completed 3-day food records. Descriptive statistics, t-tests, Kruskal-Wallis tests and multivariable logistic and linear regression were employed.

RESULTS

Two hundred ninety (73%) and 199 (67%) of subjects were always adherent to a gluten-free diet at 2 and 5 years post celiac disease diagnosis respectively. The percentage of children with variable adherence increased from 1% at 2 years to 15% at 5 years. Children with a first-degree relative with celiac disease were more likely to be adherent to the gluten-free diet. Gluten intake on food records could not differentiate adherent from nonadherent subjects. Adherent children from the United States had more gluten intake based on food records than European children (P < .001 and P = .007 at 2 and 5 years respectively).

CONCLUSION

Approximately three-quarters of children with screening-identified celiac disease remain strictly adherent to a gluten-free diet over time. There are no identifiable features associated with adherence aside from having a first-degree relative with celiac disease. Despite good parent-reported adherence, children from the United States have more gluten intake when assessed by food records. Studies on markers of gluten-free diet adherence, sources of gluten exposure (particularly in the United States), and effects of adherence on mucosal healing are needed.

The National Clinical Care Commission Report to Congress: Leveraging Federal Policies and Programs to Prevent Diabetes in People With Prediabetes

Individuals with an elevated fasting glucose level, elevated glucose level after glucose challenge, or elevated hemoglobin A1c level below the diagnostic threshold for diabetes (collectively termed prediabetes) are at increased risk for type 2 diabetes. More than one-third of U.S. adults have prediabetes but fewer than one in five are aware of the diagnosis. Rigorous scientific research has demonstrated the efficacy of both intensive lifestyle interventions and metformin in delaying or preventing progression from prediabetes to type 2 diabetes. The National Clinical Care Commission (NCCC) was a federal advisory committee charged with evaluating and making recommendations to improve federal programs related to the prevention of diabetes and its complications. In this article, we describe the recommendations of an NCCC subcommittee that focused primarily on prevention of type 2 diabetes in people with prediabetes. These recommendations aim to improve current federal diabetes prevention activities by 1) increasing awareness of and diagnosis of prediabetes on a population basis; 2) increasing the availability of, referral to, and insurance coverage for the National Diabetes Prevention Program and the Medicare Diabetes Prevention Program; 3) facilitating Food and Drug Administration review and approval of metformin for diabetes prevention; and 4) supporting research to enhance the effectiveness of diabetes prevention. Cognizant of the burden of type 1 diabetes, the recommendations also highlight the importance of research to advance our understanding of the etiology of and opportunities for prevention of type 1 diabetes.

Successful integration of newborn genetic testing into UK routine screening using prospective consent to determine eligibility for clinical trials

OBJECTIVE

INGR1D (INvestigating Genetic Risk for type 1 Diabetes) was a type 1 diabetes (T1D) genetic screening study established to identify participants for a primary prevention trial (POInT, Primary Oral Insulin Trial).

METHODS

The majority of participants were recruited by research midwives in antenatal clinics from 18 weeks' gestation. Using the NHS Newborn Bloodspot Screening Programme (NBSP) infrastructure, participants enrolled in INGR1D had an extra sample taken from their day 5 bloodspot card sent for T1D genetic screening. Those at an increased risk of T1D were informed of the result, given education about T1D and the opportunity to take part in POInT.

RESULTS

Between April 2018 and November 2020, 66% of women approached about INGR1D chose to participate. 15 660 babies were enrolled into INGR1D and 14 731 blood samples were processed. Of the processed samples, 157 (1%) had confirmed positive results, indicating an increased risk of T1D, of whom a third (n=49) enrolled into POInT (20 families were unable to participate in POInT due to COVID-19 lockdown restrictions).

CONCLUSION

The use of prospective consent to perform personalised genetic testing on samples obtained through the routine NBSP represents a novel mechanism for clinical genetic research in the UK and provides a model for further population-based genetic studies in the newborn.

Type 1 Diabetes: A Disorder of the Exocrine and Endocrine Pancreas

Type 1 diabetes has historically been described as an endocrine (β-cell) specific autoimmune disease. However, a substantial reduction (20-50%) in pancreas organ size and subclinical to symptomatic exocrine pancreatic insufficiency are present at diagnosis and may begin even prior to the development of islet autoimmunity. The mechanisms of exocrine loss in type 1 diabetes are not well understood, but leading hypotheses include developmental defects, β-cell loss resulting in exocrine atrophy, or autoimmune or inflammatory destruction of exocrine cells. Inflammatory changes including acute and chronic pancreatitis, exocrine T cell infiltration and classical complement activation, and serum exocrine autoantibodies within type 1 diabetes individuals suggest that an autoimmune or inflammatory process may contribute to exocrine pancreatic dysfunction. Exocrine pancreas atrophy primarily occurs prior to the onset of clinical disease. Indeed, recent work implicates exocrine-specific alterations in gene and protein expression as key in type 1 diabetes development. Measures of exocrine size and function could be useful additions in the prediction of disease onset and in identifying potential therapeutic responders to disease therapies, however, this is an underdeveloped area of research. Additionally, exocrine pancreatic insufficiency is underdiagnosed in individuals with type 1 diabetes and individualized treatment protocols are lacking. Much work remains to be done in this area, but we can definitively say that type 1 diabetes is a disorder of both the exocrine and endocrine pancreas likely from the start.

Month of birth and the risk of developing type 1 diabetes among children in the Swedish national Better Diabetes Diagnosis Study

AIM

Previous studies have reported an association between month of birth and incidence of type 1 diabetes. Using population-based data, including almost all newly diagnosed children with type 1 diabetes in Sweden, we tested whether month of birth influences the risk of type 1 diabetes.

METHODS

For 8761 children diagnosed with type 1 diabetes between May 2005 and December 2016 in the Better Diabetes Diagnosis study, month of birth, sex and age were compared. Human leucocyte antigen (HLA) genotype and autoantibodies at diagnosis were analysed for a subset of the cohort (n = 3647). Comparisons with the general population used data from Statistics Sweden.

RESULTS

We found no association between month of birth or season and the incidence of type 1 diabetes in the cohort as a whole. However, boys diagnosed before 5 years were more often born in May (p = 0.004). We found no correlation between month of birth and HLA or antibodies.

CONCLUSION

In this large nationwide study, the impact of month of birth on type 1 diabetes diagnosis was weak, except for boys diagnosed before 5 years of age, who were more likely born in May. This may suggest different triggers for different subgroups of patients with type 1 diabetes.

The association of physical activity to oral glucose tolerance test outcomes in multiple autoantibody positive children: The TEDDY Study

OBJECTIVE

To examine the association of physical activity (PA), measured by accelerometry, to hemoglobin AIC (HbA1c) and oral glucose tolerance test (OGTT) outcomes in children who were multiple persistent confirmed autoantibody positive for type 1 diabetes (T1D).

METHODS

The Environmental Determinants of Diabetes in the Young (TEDDY) multinational study followed children from birth. Children ≥3 years of age who were multiple persistent confirmed autoantibody positive were monitored by OGTTs every 6 months. TEDDY children's PA was measured by accelerometry beginning at 5 years of age. We examined the relationship between moderate plus vigorous (mod + vig) PA, HbA1c, and OGTT in 209 multiple autoantibody children who had both OGTT and PA measurements.

RESULTS

Mod + vig PA was associated with both glucose and C-peptide measures (fasting, 120-min, and AUC); higher mod + vig PA was associated with a better OGTT response primarily in children with longer duration of multiple autoantibody positivity. Mod + vig PA also interacted with child age; lower mod + vig PA was associated with a greater increase in C-peptide response across age. Mod + vig PA was not related to fasting insulin, HOMA-IR or HbA1c.

CONCLUSIONS

The OGTT is the gold standard for diabetes diagnosis and is used to monitor those at high risk for T1D. We found higher levels of mod + vig PA were associated with better OGTT outcomes in children ≥5 years of age who have been multiple autoantibody positive for longer periods of time. Physical activity should be the focus of future efforts to better understand the determinants of disease progression in high-risk children.

Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests

OBJECTIVE

Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies.

RESEARCH DESIGN AND METHODS

Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190).

RESULTS

A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82).

CONCLUSIONS

An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies.

INnoVative trial design for testing the Efficacy, Safety and Tolerability of 6-month treatment with incretin-based therapy to prevent type 1 DIAbetes in autoantibody positive participants: A protocol for three parallel double-blind, randomised controlled trials (INVESTDIA)

AIMS

β-cell stress and dysfunction may contribute to islet autoimmunity and progression to clinical type 1 diabetes. We present a protocol of three randomised controlled trials assessing the effects of glucagon-like peptide 1 (GLP - 1) analogue liraglutide in three early stages of type 1 diabetes.

METHODS

We will test 10- to 30-year-old people with multiple islet autoantibodies for their glucose metabolism and randomise participants with stage 1 (multiple islet autoantibodies and normoglycaemia), stage 2 (multiple islet autoantibodies and dysglycaemia) and early stage 3 (clinical diagnosis) type 1 diabetes, 10-14 persons in each, to a 6-month intervention with liraglutide or placebo with 6-month follow-up in the stage 2 and stage 3 trials and 18-month follow-up in the stage 1 trial. Primary efficacy outcome in the stage 1 and stage 2 trials is a first-phase insulin response in an intravenous glucose tolerance test and C-peptide area under the curve in a 2-h mixed-meal tolerance test in the stage 3 trial. In addition, safety and tolerability of liraglutide treatment will be assessed.

CONCLUSIONS

Most prevention trials of type 1 diabetes have targeted the immune system. Treatment with GLP-1 analogue liraglutide supports the pancreatic β-cells, which should likewise attenuate islet autoimmunity. Our innovative study design allows simultaneous investigation of an intervention in three groups of people who represent various early stages of type 1 diabetes and maximises the eligibility to participate.

TRIAL REGISTRATION

NCT02611232 (stage 1 trial), NCT02898506 (stage 2 trial), NCT02908087 (stage 3 trial).

Microbial risk score for capturing microbial characteristics, integrating multi-omics data, and predicting disease risk

BACKGROUND

With the rapid accumulation of microbiome-wide association studies, a great amount of microbiome data are available to study the microbiome's role in human disease and advance the microbiome's potential use for disease prediction. However, the unique features of microbiome data hinder its utility for disease prediction.

METHODS

Motivated from the polygenic risk score framework, we propose a microbial risk score (MRS) framework to aggregate the complicated microbial profile into a summarized risk score that can be used to measure and predict disease susceptibility. Specifically, the MRS algorithm involves two steps: (1) identifying a sub-community consisting of the signature microbial taxa associated with disease and (2) integrating the identified microbial taxa into a continuous score. The first step is carried out using the existing sophisticated microbial association tests and pruning and thresholding method in the discovery samples. The second step constructs a community-based MRS by calculating alpha diversity on the identified sub-community in the validation samples. Moreover, we propose a multi-omics data integration method by jointly modeling the proposed MRS and other risk scores constructed from other omics data in disease prediction.

RESULTS

Through three comprehensive real-data analyses using the NYU Langone Health COVID-19 cohort, the gut microbiome health index (GMHI) multi-study cohort, and a large type 1 diabetes cohort separately, we exhibit and evaluate the utility of the proposed MRS framework for disease prediction and multi-omics data integration. In addition, the disease-specific MRSs for colorectal adenoma, colorectal cancer, Crohn's disease, and rheumatoid arthritis based on the relative abundances of 5, 6, 12, and 6 microbial taxa, respectively, are created and validated using the GMHI multi-study cohort. Especially, Crohn's disease MRS achieves AUCs of 0.88 (0.85-0.91) and 0.86 (0.78-0.95) in the discovery and validation cohorts, respectively.

CONCLUSIONS

The proposed MRS framework sheds light on the utility of the microbiome data for disease prediction and multi-omics integration and provides a great potential in understanding the microbiome's role in disease diagnosis and prognosis. Video Abstract.

Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years

CONTEXT

Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically predisposed children can facilitate interventions to delay or prevent the disease.

OBJECTIVE

This work aimed to determine if a combination of genetic, immunologic, and metabolic features, measured at infancy, can be used to predict the likelihood that a child will develop T1D by age 6 years.

METHODS

Newborns with human leukocyte antigen (HLA) typing were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY). TEDDY ascertained children in Finland, Germany, Sweden, and the United States. TEDDY children were either from the general population or from families with T1D with an HLA genotype associated with T1D specific to TEDDY eligibility criteria. From the TEDDY cohort there were 702 children will all data sources measured at ages 3, 6, and 9 months, 11.4% of whom progressed to T1D by age 6 years. The main outcome measure was a diagnosis of T1D as diagnosed by American Diabetes Association criteria.

RESULTS

Machine learning-based feature selection yielded classifiers based on disparate demographic, immunologic, genetic, and metabolite features. The accuracy of the model using all available data evaluated by the area under a receiver operating characteristic curve is 0.84. Reducing to only 3- and 9-month measurements did not reduce the area under the curve significantly. Metabolomics had the largest value when evaluating the accuracy at a low false-positive rate.

CONCLUSION

The metabolite features identified as important for progression to T1D by age 6 years point to altered sugar metabolism in infancy. Integrating this information with classic risk factors improves prediction of the progression to T1D in early childhood.

Preclinical Autoimmune Disease: a Comparison of Rheumatoid Arthritis, Systemic Lupus Erythematosus, Multiple Sclerosis and Type 1 Diabetes

The preclinical phase of autoimmune disorders is characterized by an initial asymptomatic phase of varying length followed by nonspecific signs and symptoms. A variety of autoimmune and inflammatory manifestations can be present and tend to increase in the last months to years before a clinical diagnosis can be made. The phenotype of an autoimmune disease depends on the involved organs, the underlying genetic susceptibility and pathophysiological processes. There are different as well as shared genetic or environmental risk factors and pathophysiological mechanisms between separate diseases. To shed more light on this, in this narrative review we compare the preclinical disease course of four important autoimmune diseases with distinct phenotypes: rheumatoid arthritis (RA), Systemic Lupus Erythematosus (SLE), multiple sclerosis (MS) and type 1 diabetes (T1D). In general, we observed some notable similarities such as a North-South gradient of decreasing prevalence, a female preponderance (except for T1D), major genetic risk factors at the HLA level, partly overlapping cytokine profiles and lifestyle risk factors such as obesity, smoking and stress. The latter risk factors are known to produce a state of chronic systemic low grade inflammation. A central characteristic of all four diseases is an on average lengthy prodromal phase with no or minor symptoms which can last many years, suggesting a gradually evolving interaction between the genetic profile and the environment. Part of the abnormalities may be present in unaffected family members, and autoimmune diseases can also cluster in families. In conclusion, a promising strategy for prevention of autoimmune diseases might be to address adverse life style factors by public health measures at the population level.

Microbial Risk Score for Capturing Microbial Characteristics, Integrating Multi-omics Data, and Predicting Disease Risk

Background

With the rapid accumulation of microbiome-wide association studies, a great amount of microbiome data are available to study the microbiome's role in human disease and advance the microbiome's potential use for disease prediction. However, the unique features of microbiome data hinder its utility for disease prediction.

Methods

Motivated from the polygenic risk score framework, we propose a microbial risk score (MRS) framework to aggregate the complicated microbial profile into a summarized risk score that can be used to measure and predict disease susceptibility. Specifically, the MRS algorithm involves two steps: 1) identifying a sub-community consisting of the signature microbial taxa associated with disease, and 2) integrating the identified microbial taxa into a continuous score. The first step is carried out using the existing sophisticated microbial association tests and pruning and thresholding method in the discovery samples. The second step constructs a community-based MRS by calculating alpha diversity on the identified sub-community in the validation samples. Moreover, we propose a multi-omics data integration method by jointly modeling the proposed MRS and other risk scores constructed from other omics data in disease prediction.

Results

Through three comprehensive real data analyses using the NYU Langone Health COVID-19 cohort, the gut microbiome health index (GMHI) multi-study cohort, and a large type 1 diabetes cohort separately, we exhibit and evaluate the utility of the proposed MRS framework for disease prediction and multi-omics data integration. In addition, the disease-specific MRSs for colorectal adenoma, colorectal cancer, Crohn's disease, and rheumatoid arthritis based on the relative abundances of 5, 6, 12, and 6 microbial taxa respectively are created and validated using the GMHI multi-study cohort. Especially, Crohn's disease MRS achieves AUCs of 0.88 ([0.85-0.91]) and 0.86 ([0.78-0.95]) in the discovery and validation cohorts, respectively.

Conclusions

The proposed MRS framework sheds light on the utility of the microbiome data for disease prediction and multi-omics integration, and provides great potential in understanding the microbiome's role in disease diagnosis and prognosis.

Genetic Variants Associated with Neuropeptide Y Autoantibody Levels in Newly Diagnosed Individuals with Type 1 Diabetes

(1) Autoantibodies to the leucine variant of neuropeptide Y (NPY-LA) have been found in individuals with type 1 diabetes (T1D). We investigated the association between the levels of NPY-LA and single nucleotide polymorphisms (SNP) to better understand the genetic regulatory mechanisms of autoimmunity in T1D and the functional impacts of increased NPY-LA levels. (2) NPY-LA measurements from serum and SNP genotyping were done on 560 newly diagnosed individuals with T1D. SNP imputation with the 1000 Genomes reference panel was followed by an association analysis between the SNPs and measured NPY-LA levels. Additionally, functional enrichment and pathway analyses were done. (3) Three loci (DGKH, DCAF5, and LINC02261) were associated with NPY-LA levels (p-value < 1.5 × 10−6), which indicates an association with neurologic and vascular disorders. SNPs associated with variations in expression levels were found in six genes (including DCAF5). The pathway analysis showed that NPY-LA was associated with changes in gene transcription, protein modification, immunological functions, and the MAPK pathway. (4) Conclusively, we found NPY-LA to be significantly associated with three loci (DGKH, DCAF5, and LINC02261), and based on our findings we hypothesize that the presence of NPY-LA is associated with the regulation of the immune system and possibly neurologic and vascular disorders.

Proinflammatory cytokines induce rapid, NO-independent apoptosis, expression of chemotactic mediators and interleukin-32 secretion in human pluripotent stem cell-derived beta cells

AIMS/HYPOTHESIS

The aim of this study was to examine the effects of proinflammatory cytokines on cells of different developmental stages during the generation of stem cell-derived beta cells (SC-beta cells) from human pluripotent stem cells (hPSCs). We wanted to find out to what extent human SC-beta cells are suitable as an experimental cellular model and, with regard to a possible therapeutic use, whether SC-beta cells have a comparable vulnerability to cytokines as bona fide beta cells.

METHODS

hPSCs were differentiated towards pancreatic organoids (SC-organoids) using a 3D production protocol. SC-beta cells and non-insulin-producing cells were separated by FACS and differential gene expression profiles of purified human SC-beta cells, progenitor stages and the human beta cell line EndoC-βH1, as a reference, were determined after 24 h incubation with the proinflammatory cytokines IL-1β, TNF-α and IFN-γ via a transcriptome microarray. Furthermore, we investigated apoptosis based on caspase cleavage, the generation of reactive oxygen species and activation of mitogen-activated protein-kinase (MAPK) stress-signalling pathways.

RESULTS

A 24 h exposure of SC-beta cells to proinflammatory cytokines resulted in significant activation of caspase 3/7 and apoptosis via the extrinsic and intrinsic apoptosis signalling pathways. At this time point, SC-beta cells showed a markedly higher sensitivity towards proinflammatory cytokines than non-insulin-producing cells and EndoC-βH1 cells. Furthermore, we were able to demonstrate the generation of reactive oxygen species and rule out the involvement of NO-mediated stress. A transient activation of stress-signalling pathways p38 mitogen-activated protein kinases (p38) and c-Jun N-terminal kinase (JNK) was already observed after 10 min of cytokine exposure. The transcriptome analysis revealed that the cellular response to proinflammatory cytokines increased with the degree of differentiation of the cells. Cytokines induced the expression of multiple inflammatory mediators including IL-32, CXCL9 and CXCL10 in SC-beta cells and in non-insulin-producing cells.

CONCLUSIONS/INTERPRETATION

Our results indicate that human SC-beta cells respond to proinflammatory cytokines very similarly to human islets. Due to the fast and fulminant cellular response of SC-beta cells, we conclude that SC-beta cells represent a suitable model for diabetes research. In light of the immaturity of SC-beta cells, they may be an attractive model for developmentally young beta cells as they are, for example, present in patients with early-onset type 1 diabetes. The secretion of chemotactic signals may promote communication between SC-beta cells and immune cells, and non-insulin-producing cells possibly participate in the overall immune response and are thus capable of amplifying the immune response and further stimulating inflammation. We demonstrated that cytokine-treated SC-organoids secrete IL-32, which is considered a promising candidate for type 1 diabetes onset. This underlines the need to ensure the survival of SC-beta cells in an autoimmune environment such as that found in type 1 diabetes.

Hydrogels and Hydrogel Nanocomposites: Enhancing Healthcare through Human and Environmental Treatment

Humans are constantly exposed to exogenous chemicals throughout their life, which can lead to a multitude of negative health impacts. Advanced materials can play a key role in preventing or mitigating these impacts through a wide variety of applications. The tunable properties of hydrogels and hydrogel nanocomposites (e.g., swelling behavior, biocompatibility, stimuli responsiveness, functionality, etc.) have deemed them ideal platforms for removal of environmental contaminants, detoxification, and reduction of body burden from exogenous chemical exposures for prevention of disease initiation, and advanced treatment of chronic diseases, including cancer, diabetes, and cardiovascular disease. In this review, three main junctures where the use of hydrogel and hydrogel nanocomposite materials can intervene to positively impact human health are highlighted: 1) preventing exposures to environmental contaminants, 2) prophylactic treatments to prevent chronic disease initiation, and 3) treating chronic diseases after they have developed.

Role of the SARS-CoV-2 virus in the appearance of new onset type 1 diabetes mellitus in children in Gran Canaria, Spain

OBJECTIVES

It has been hypothesized that SARS-CoV-2 may play a role in the development of different forms of diabetes mellitus (DM). The Canary Islands have the highest incidence of type 1 DM (T1DM) reported in Spain (30-35/100,000 children under 14 years/year). In 2020-2021 we observed the highest incidence so far on the island of Gran Canaria, as a result of which we decided to evaluate the possible role of COVID-19 in the increased number of onsets.

METHODS

We examined the presence of IgG antibodies against SARS-CoV-2 in children with new onset T1DM between October 2020 and August 2021. We compared recent T1DM incidence with that of the previous 10 years.

RESULTS

Forty-two patients were diagnosed with T1DM (48.1/100,000 patients/year), representing a nonsignificant 25.7% increase from the expected incidence. Of the 33 patients who consented to the study, 32 presented negative IgG values, with only one patient reflecting undiagnosed past infection. Forty-four percent of patients presented with ketoacidosis at onset, which was similar to previous years.

CONCLUSIONS

We conclude that there is no direct relationship between the increased incidence of T1DM and SARS-CoV-2 in the region. The COVID-19 pandemic did not result in an increased severity of T1DM presentation.

Birth cohort studies using symptom diaries for assessing respiratory diseases-a scoping review

BACKGROUND

Respiratory infections are the most frequent health problem in childhood leading to morbidity and socioeconomic burden. Studying symptoms of respiratory infections in home based settings requires dedicated prospective cohort studies using diaries. However, no information is available on which birth cohort studies using symptom diary data. A review of birth cohort studies with available symptom diary data, follow-up data, and bio samples is needed to support research collaborations and create potential synergies.

METHODS

We conducted a scoping review of birth cohort studies using diaries for the collection of respiratory symptoms. The scoping review was conducted in accordance with the PRISMA Extension. We searched the electronic databases PubMed, Embase, Web of science and CINAHL (last search November 2020) resulting in 5872 records (based on title and abstract screening) eligible for further screening.

RESULTS

We examined 735 records as full text articles and finally included 57 according to predefined inclusion criteria. We identified 22 birth cohort studies that collect(ed) data on respiratory symptoms using a symptom diary starting at birth. Numbers of participants ranged from 129 to 8677. Eight studies collected symptom diary information only for the first year of life, nine for the first two years or less and six between three and six years. Most of the cohorts collected biosamples (n = 18) and information on environmental exposures (n = 19).

CONCLUSION

Information on respiratory symptoms with daily resolution was collected in several birth cohorts, often including related biosamples, and these data and samples can be used to study full spectrum of infections, particularly including those which did not require medical treatment.

Enteroviruses and Type 1 Diabetes: Multiple Mechanisms and Factors?

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by insulin deficiency and resultant hyperglycemia. Complex interactions of genetic and environmental factors trigger the onset of autoimmune mechanisms responsible for development of autoimmunity to β cell antigens and subsequent development of T1D. A potential role of virus infections has long been hypothesized, and growing evidence continues to implicate enteroviruses as the most probable triggering viruses. Recent studies have strengthened the association between enteroviruses and development of autoimmunity in T1D patients, potentially through persistent infections. Enterovirus infections may contribute to different stages of disease development. We review data from both human cohort studies and experimental research exploring the potential roles and molecular mechanisms by which enterovirus infections can impact disease outcome.

Enteroviruses and Type 1 Diabetes: Multiple Mechanisms and Factors?

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by insulin deficiency and resultant hyperglycemia. Complex interactions of genetic and environmental factors trigger the onset of autoimmune mechanisms responsible for development of autoimmunity to β cell antigens and subsequent development of T1D. A potential role of virus infections has long been hypothesized, and growing evidence continues to implicate enteroviruses as the most probable triggering viruses. Recent studies have strengthened the association between enteroviruses and development of autoimmunity in T1D patients, potentially through persistent infections. Enterovirus infections may contribute to different stages of disease development. We review data from both human cohort studies and experimental research exploring the potential roles and molecular mechanisms by which enterovirus infections can impact disease outcome.

HLA Allele-Specific Quantitative Profiling of Type 1 Diabetic B Lymphocyte Immunopeptidome

Peptide ligands presented by human leukocyte antigen (HLA) molecules on the cell surface represent the immunopeptidome that could be utilized for identification of antigenic peptides for immunotherapy and prevention of autoimmune diseases. Although T-cells are well-known key players in the destruction of pancreatic beta-cells in type 1 diabetes (T1D), increasing evidence points toward a role for B-cells in disease pathogenesis. However, as antigen presenting cells, little is known about the comprehensive immunopeptidome of B cells and their changes in the context of T1D. We performed HLA allele-specific quantitative immunopeptidomics using B lymphocytes derived from T1D patients and healthy controls. Hundreds of HLA-I and HLA-II immunopeptides were identified as differentially regulated in T1D per HLA allele for B cells sharing identical HLA alleles. The results were further validated using additional T1D and healthy B cells with partially overlapped HLA alleles. Differentially expressed immunopeptides were confirmed with targeted proteomics and for reactivity using known T-cell assays in the immune epitope database. Considering samples with identical HLA alleles are difficult to obtain for T1D and other similar HLA-restricted diseases, our work represents a viable approach to better understand HLA allele-specific antigen presentation and may facilitate identification of immunopeptides for therapeutic applications in autoimmune diseases. Data are available via ProteomeXchange with identifier PXD026184.

Prenatal Betamethasone Exposure and its Impact on Pediatric Type 1 Diabetes Mellitus: A Preliminary Study in a Spanish Cohort

BACKGROUND

Betamethasone, a glucocorticoid used to induce lung maturation when there is a risk of preterm delivery, can affect the immune system maturation and type 1 diabetes (T1D) incidence in the progeny. It has been described that prenatal betamethasone protects offspring from experimental T1D development. The main aim of this study was to evaluate the possible association between betamethasone prenatal exposure and T1D in humans. Research Design and Methods. A retrospective case-control study with a total of 945 children, including 471 patients with T1D and 474 healthy siblings, was performed. Participants were volunteers from the Germans Trias i Pujol Hospital and DiabetesCero Foundation. Parents of children enrolled in the study completed a questionnaire that included questions about weeks of gestation, preterm delivery risk, weight at birth, and prenatal betamethasone exposure of their children. Multiple logistic regression was used to detect the association between betamethasone exposure and T1D.

RESULTS

We compared T1D prevalence between subjects prenatally exposed or unexposed to betamethasone. The percent of children with T1D in the exposed group was 37.5% (21 of 56), and in the unexposed group was 49.52% (410 of 828) (p = 0.139). The percentage of betamethasone-treated subjects with T1D in the preterm group (18.05%, 13 of 72) was significantly higher than that found in the control group (12.5%, 9 of 72) (p = 0.003). The odds ratio for T1D associated with betamethasone in the univariate logistic regression was 0.59 (95% confidence interval, 0.33; 1.03 [p = 0.062]) and in the multivariate logistic regression was 0.83 (95% confidence interval, 0.45; 1.52 [p = 0.389]).

CONCLUSIONS

The results demonstrate that the prenatal exposure to betamethasone does not increase T1D susceptibility, and may even be associated with a trend towards decreased risk of developing the disease. These preliminary findings require further prospective studies with clinical data to confirm betamethasone exposure effect on T1D risk.

Antibiotic Consumption Patterns in European Countries Might Be Associated with the Prevalence of Type 1 and 2 Diabetes

Several publications have raised the issue that the development of diabetes precedes the alteration of the microbiome (dysbiosis) and the role of environmental factors. Antibiotic use induces dysbiosis, and we wanted to estimate the associations between the consumption of antibiotics and the prevalence of diabetes (both types 1 and 2; T1D and T2D, respectively) in European countries. If such an association exists, the dominant use antibiotic classes might be reflected in the prevalence rates of T1D and T2D in different countries. Comparisons were performed between the prevalence of diabetes estimated for 2019 and featured in the Diabetes Atlas and the average yearly consumption of antibiotic classes between 2010 and 2109, calculated from the European Centre for Disease Prevention and Control (ECDC) yearly reports on antibiotic consumption in Europe. Pearson's correlation and variance analyses were used to estimate the possible relationship. Strong positive (enhancer) associations were found between the prevalence of T1D and the consumption of tetracycline (J01A: p = 0.001) and the narrow-spectrum penicillin (J01CE: p = 0.006; CF: p = 0.018). A strong negative (inhibitor) association was observed with broad-spectrum, beta-lactamase-resistant penicillin (J01CR: p = 0.003), macrolide (J01F: p = 0.008), and quinolone (J01M: p = 0.001). T2D showed significant positive associations with cephalosporin (J01D: p = 0.048) and quinolone (J01M: p = 0.025), and a non-significant negative association was detected with broad-spectrum, beta-lactamase-sensitive penicillin (J01CA: p = 0.067). Countries showing the highest prevalence rates of diabetes (top 10) showed concordance with the higher consumption of "enhancer" and the lower consumption of "inhibitor" antibiotics (top 10), as indicated by variance analysis. Countries with high prevalence rates of T1D showed high consumption of tetracycline (p = 0.015) and narrow-spectrum, beta-lactamase sensitive penicillin (p = 0.008) and low consumption of "inhibitor" antibiotics [broad-spectrum, beta-lactamase-resistant, combination penicillin (p = 0.005); cephalosporin (p = 0.036); and quinolone (p = 0.003)]. Countries with high prevalence rates of T2D consumed more cephalosporin (p = 0.084) and quinolone (p = 0.054) and less broad-spectrum, beta-lactamase-sensitive penicillin (p = 0.012) than did other countries. The development of diabetes-related dysbiosis might be related to the higher consumption of specific classes of antibiotics, showing positive (enhancer) associations with the prevalence of diabetes, and the low consumption of other classes of antibiotics, those showing negative (inhibitory) associations. These groups of antibiotics are different in T1D and T2D.

Elucidate multidimensionality of type 1 diabetes mellitus heterogeneity by multifaceted information

Type 1 diabetes (T1D) is an autoimmune disease. Different factors, including genetics and viruses may contribute to T1D, but the causes of T1D are not fully known, and there is currently no cure. The advent of high-throughput technologies has revolutionized the field of medicine and biology, and analysis of multi-source data along with clinical information has brought a better understanding of the mechanisms behind disease pathogenesis. The aim of this work was the development of a data repository linking clinical information and interactome studies in T1D. To address this goal, we analyzed the electronic health records and online databases of genes, proteins, miRNAs, and pathways to have a global view of T1D. There were common comorbid diseases such as anemia, hypertension, vitreous diseases, renal diseases, and atherosclerosis in the phenotypic disease networks. In the protein-protein interaction network, CASP3 and TNF were date-hub proteins involved in several pathways. Moreover, CTNNB1, IGF1R, and STAT3 were hub proteins, whereas miR-155-5p, miR-34a-5p, miR-23-3p, and miR-20a-5p were hub miRNAs in the gene-miRNA interaction network. Multiple levels of information including genetic, protein, miRNA and clinical data resulted in multiple results, which suggests the complementarity of multiple sources. With the integration of multifaceted information, it will shed light on the mechanisms underlying T1D; the provided data and repository has utility in understanding phenotypic disease networks for the potential development of comorbidities in T1D patients as well as the clues for further research on T1D comorbidities.

Environmental Determinants of Type 1 Diabetes: From Association to Proving Causality

The rising incidence of type 1 diabetes (T1D) cannot be ascribed to genetics alone, and causative environmental triggers and drivers must also be contributing. The prospective TEDDY study has provided the greatest contributions in modern time, by addressing misconceptions and refining the search strategy for the future. This review outlines the evidence to date to support the pathways from association to causality, across all stages of T1D (seroconversion to beta cell failure). We focus on infections and vaccinations; infant growth and childhood obesity; the gut microbiome and the lifestyle factors which cultivate it. Of these, the environmental determinants which have the most supporting evidence are enterovirus infection, rapid weight gain in early life, and the microbiome. We provide an infographic illustrating the key environmental determinants in T1D and their likelihood of effect. The next steps are to investigate these environmental triggers, ideally though gold-standard randomised controlled trials and further prospective studies, to help explore public health prevention strategies.