Predictors of the Initiation of Islet Autoimmunity and Progression to Multiple Autoantibodies and Clinical Diabetes: The TEDDY Study

Intake of B vitamins and the risk of developing islet autoimmunity and type 1 diabetes in the TEDDY study

PURPOSE

The aim was to study the association between dietary intake of B vitamins in childhood and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D) by the age of 10 years.

METHODS

We followed 8500 T1D-susceptible children born in the U.S., Finland, Sweden, and Germany in 2004 -2010 from the Environmental Determinants of Diabetes in the Young (TEDDY) study, which is a prospective observational birth cohort. Dietary intake of seven B vitamins was calculated from foods and dietary supplements based on 24-h recall at 3 months and 3-day food records collected regularly from 6 months to 10 years of age. Cox proportional hazard models were adjusted for energy, HLA-genotype, first-degree relative with T1D, sex, and country.

RESULTS

A total of 778 (9.2) children developed at least one autoantibody (any IA), and 335 (3.9%) developed multiple autoantibodies. 280 (3.3%) children had IAA and 319 (3.8%) GADA as the first autoantibody. 344 (44%) children with IA progressed to T1D. We observed that higher intake of niacin was associated with a decreased risk of developing multiple autoantibodies (HR 0.95; 95% CI 0.92, 0.98) per 1 mg/1000 kcal in niacin intake. Higher intake of pyridoxine (HR 0.66; 95% CI 0.46, 0.96) and vitamin B12 (HR 0.87; 95% CI 0.77, 0.97) was associated with a decreased risk of IAA-first autoimmunity. Higher intake of riboflavin (HR 1.38; 95% CI 1.05, 1.80) was associated with an increased risk of GADA-first autoimmunity. There were no associations between any of the B vitamins and the outcomes "any IA" and progression from IA to T1D.  CONCLUSION: In this multinational, prospective birth cohort of children with genetic susceptibility to T1D, we observed some direct and inverse associations between different B vitamins and risk of IA.

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.

Caesarean section and risk of type 1 diabetes

AIMS/HYPOTHESIS

Delivery by Caesarean section continues to rise globally and has been associated with the risk of developing type 1 diabetes and the rate of progression from pre-symptomatic stage 1 or 2 type 1 diabetes to symptomatic stage 3 disease. The aim of this study was to examine the association between Caesarean delivery and progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes.

METHODS

Caesarean section was examined in 8135 children from the TEDDY study who had an increased genetic risk for type 1 diabetes and were followed from birth for the development of islet autoantibodies and type 1 diabetes.

RESULTS

The likelihood of delivery by Caesarean section was higher in children born to mothers with type 1 diabetes (adjusted OR 4.61, 95% CI 3.60, 5.90, p<0.0001), in non-singleton births (adjusted OR 4.35, 95% CI 3.21, 5.88, p<0.0001), in premature births (adjusted OR 1.91, 95% CI 1.53, 2.39, p<0.0001), in children born in the USA (adjusted OR 2.71, 95% CI 2.43, 3.02, p<0.0001) and in children born to older mothers (age group >28-33 years: adjusted OR 1.19, 95% CI 1.04, 1.35, p=0.01; age group >33 years: adjusted OR 1.80, 95% CI 1.58, 2.06, p<0.0001). Caesarean section was not associated with an increased risk of developing pre-symptomatic early-stage type 1 diabetes (risk by age 10 years 5.7% [95% CI 4.6%, 6.7%] for Caesarean delivery vs 6.6% [95% CI 6.0%, 7.3%] for vaginal delivery, p=0.07). Delivery by Caesarean section was associated with a modestly increased rate of progression to stage 3 type 1 diabetes in children who had developed multiple islet autoantibody-positive pre-symptomatic early-stage type 1 diabetes (adjusted HR 1.36, 95% CI 1.03, 1.79, p=0.02). No interaction was observed between Caesarean section and non-HLA SNPs conferring susceptibility for type 1 diabetes.

CONCLUSIONS/INTERPRETATION

Caesarean section increased the rate of progression to stage 3 type 1 diabetes in children with pre-symptomatic early-stage type 1 diabetes.

DATA AVAILABILITY

Data from the TEDDY study ( https://doi.org/10.58020/y3jk-x087 ) reported here will be made available for request at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository (NIDDK-CR) Resources for Research (R4R) ( https://repository.niddk.nih.gov/ ).

CXADR polymorphism rs6517774 modifies islet autoimmunity characteristics and exhibits sex disparity

Enteroviral infections have been linked to the development of islet autoimmunity (IA) and type 1 diabetes (T1D), and the coxsackie and adenovirus receptor (CXADR) is one of the ligands used by adenoviruses and enteroviruses for cell internalization. Two CXADR single nucleotide polymorphisms (SNPs), rs6517774 and rs2824404, were previously associated with an increased susceptibility to IA in the international TEDDY study (The Environmental Determinants of Diabetes in the Young). This study aimed to replicate the results by genotyping 2886 children enrolled in the Finnish Diabetes Prediction and Prevention study (DIPP). In our preliminary analysis of the SNPs' allelic distributions, we could not find any association with IA susceptibility. However, a stratified analysis revealed a sex disparity, since the allelic distribution of rs6517774 was different when comparing autoantibody positive females with males; a difference not seen in healthy subjects. By using HLA risk groups and sex as covariates, a Cox regression survival analysis found that the rs6517774 (A/G) SNP was associated with a lower age at seroconversion in females (Female*rs6517774-AA; HR = 1.53, p = 0.002), while introducing a protective effect in males. Accordingly, we propose that rs6517774 alters IA characteristics by modifying the age at seroconversion in a sex-dependent manner. In light of this observation, rs6517774 now joins a limited set on SNPs found to introduce sex-dependent risk effects on the age at IA initiation.

Immune responses to gut bacteria associated with time to diagnosis and clinical response to T cell-directed therapy for type 1 diabetes prevention

Immune-targeted therapies have efficacy for treatment of autoinflammatory diseases. For example, treatment with the T cell-specific anti-CD3 antibody teplizumab delayed disease onset in participants at high risk for type 1 diabetes (T1D) in the TrialNet 10 (TN-10) trial. However, heterogeneity in therapeutic responses in TN-10 and other immunotherapy trials identifies gaps in understanding disease progression and treatment responses. The intestinal microbiome is a potential source of biomarkers associated with future T1D diagnosis and responses to immunotherapy. We previously reported that antibody responses to gut commensal bacteria were associated with T1D diagnosis, suggesting that certain antimicrobial immune responses may help predict disease onset. Here, we investigated anticommensal antibody (ACAb) responses against a panel of taxonomically diverse intestinal bacteria species in sera from TN-10 participants before and after teplizumab or placebo treatment. We identified IgG2 responses to three species that were associated with time to T1D diagnosis and with teplizumab treatment responses that delayed disease onset. These antibody responses link human intestinal bacteria with T1D progression, adding predictive value to known T1D risk factors. ACAb analysis provides a new approach to elucidate heterogeneity in responses to immunotherapy and identify individuals who may benefit from teplizumab, recently approved by the U.S. Food and Drug Administration for delaying T1D onset.

Type 1 Diabetes Risk Phenotypes Using Cluster Analysis

Background

Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal clinically meaningful clusters in the at-risk population and allow for non-linear relationships between predictors are lacking. We aimed to identify and characterize clusters of islet autoantibody-positive individuals that share similar characteristics and type 1 diabetes risk.

Methods

We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention (PTP) study data (n=1127). The outcome of the analysis was time to type 1 diabetes and variables in the model included demographics, genetics, metabolic factors and islet autoantibodies. An independent dataset (Diabetes Prevention Trial of Type 1 Diabetes, DPT-1 study) (n=704) was used for validation.

Findings

The analysis revealed 8 clusters with varying type 1 diabetes risks, categorized into three groups. Group A had three clusters with high glucose levels and high risk. Group B included four clusters with elevated autoantibody titers. Group C had three lower-risk clusters with lower autoantibody titers and glucose levels. Within the groups, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels, age, and genetic risk. A decision rule for assigning individuals to clusters was developed. The validation dataset confirms that the clusters can identify individuals with similar characteristics.

Interpretation

Demographic, metabolic, immunological, and genetic markers can be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables.

SARS-CoV-2 Infection and Development of Islet Autoimmunity in Early Childhood

Importance

The incidence of diabetes in childhood has increased during the COVID-19 pandemic. Elucidating whether SARS-CoV-2 infection is associated with islet autoimmunity, which precedes type 1 diabetes onset, is relevant to disease etiology and future childhood diabetes trends.

Objective

To determine whether there is a temporal relationship between SARS-CoV-2 infection and the development of islet autoimmunity in early childhood.

Design, Setting, and Participants

Between February 2018 and March 2021, the Primary Oral Insulin Trial, a European multicenter study, enrolled 1050 infants (517 girls) aged 4 to 7 months with a more than 10% genetically defined risk of type 1 diabetes. Children were followed up through September 2022.

Exposure

SARS-CoV-2 infection identified by SARS-CoV-2 antibody development in follow-up visits conducted at 2- to 6-month intervals until age 2 years from April 2018 through June 2022.

Main Outcomes and Measures

The development of multiple (≥2) islet autoantibodies in follow-up in consecutive samples or single islet antibodies and type 1 diabetes. Antibody incidence rates and risk of developing islet autoantibodies were analyzed.

Results

Consent was obtained for 885 (441 girls) children who were included in follow-up antibody measurements from age 6 months. SARS-CoV-2 antibodies developed in 170 children at a median age of 18 months (range, 6-25 months). Islet autoantibodies developed in 60 children. Six of these children tested positive for islet autoantibodies at the same time as they tested positive for SARS-CoV-2 antibodies and 6 at the visit after having tested positive for SARS-CoV-2 antibodies. The sex-, age-, and country-adjusted hazard ratio for developing islet autoantibodies when the children tested positive for SARS-CoV-2 antibodies was 3.5 (95% CI, 1.6-7.7; P = .002). The incidence rate of islet autoantibodies was 3.5 (95% CI, 2.2-5.1) per 100 person-years in children without SARS-CoV-2 antibodies and 7.8 (95% CI, 5.3-19.0) per 100 person-years in children with SARS-CoV-2 antibodies (P = .02). Islet autoantibody risk in children with SARS-CoV-2 antibodies was associated with younger age (<18 months) of SARS-CoV-2 antibody development (HR, 5.3; 95% CI, 1.5-18.3; P = .009).

Conclusion and relevance

In young children with high genetic risk of type 1 diabetes, SARS-CoV-2 infection was temporally associated with the development of islet autoantibodies.

Heterogeneity and endotypes in type 1 diabetes mellitus

Despite major advances over the past decade, prevention and treatment of type 1 diabetes mellitus (T1DM) remain suboptimal, with large and unexplained variations in individual responses to interventions. The current classification schema for diabetes mellitus does not capture the complexity of this disease or guide clinical management effectively. One of the approaches to achieve the goal of applying precision medicine in diabetes mellitus is to identify endotypes (that is, well-defined subtypes) of the disease each of which has a distinct aetiopathogenesis that might be amenable to specific interventions. Here, we describe epidemiological, clinical, genetic, immunological, histological and metabolic differences within T1DM that, together, suggest heterogeneity in its aetiology and pathogenesis. We then present the emerging endotypes and their impact on T1DM prediction, prevention and treatment.

Possible heterogeneity of initial pancreatic islet beta-cell autoimmunity heralding type 1 diabetes

The etiology of type 1 diabetes (T1D) foreshadows the pancreatic islet beta-cell autoimmune pathogenesis that heralds the clinical onset of T1D. Standardized and harmonized tests of autoantibodies against insulin (IAA), glutamic acid decarboxylase (GADA), islet antigen-2 (IA-2A), and ZnT8 transporter (ZnT8A) allowed children to be followed from birth until the appearance of a first islet autoantibody. In the Environmental Determinants of Diabetes in the Young (TEDDY) study, a multicenter (Finland, Germany, Sweden, and the United States) observational study, children were identified at birth for the T1D high-risk HLA haploid genotypes DQ2/DQ8, DQ2/DQ2, DQ8/DQ8, and DQ4/DQ8. The TEDDY study was preceded by smaller studies in Finland, Germany, Colorado, Washington, and Sweden. The aims were to follow children at increased genetic risk to identify environmental factors that trigger the first-appearing autoantibody (etiology) and progress to T1D (pathogenesis). The larger TEDDY study found that the incidence rate of the first-appearing autoantibody was split into two patterns. IAA first peaked already during the first year of life and tapered off by 3-4 years of age. GADA first appeared by 2-3 years of age to reach a plateau by about 4 years. Prior to the first-appearing autoantibody, genetic variants were either common or unique to either pattern. A split was also observed in whole blood transcriptomics, metabolomics, dietary factors, and exposures such as gestational life events and early infections associated with prolonged shedding of virus. An innate immune reaction prior to the adaptive response cannot be excluded. Clarifying the mechanisms by which autoimmunity is triggered to either insulin or GAD65 is key to uncovering the etiology of autoimmune T1D.

Physical Activity and the Development of Islet Autoimmunity and Type 1 Diabetes in 5- to 15-Year-Old Children Followed in the TEDDY Study

OBJECTIVE

This study investigated physical activity and its association with the development of islet autoimmunity and type 1 diabetes in genetically at-risk children aged 5-15 years.

RESEARCH DESIGN AND METHODS

As part of the longitudinal Environmental Determinants of Diabetes in the Young (TEDDY) study, annual assessment of activity using accelerometry was conducted from age 5 years. Time-to-event analyses using Cox proportional hazard models were used to assess the association between time spent in moderate to vigorous physical activity per day and the appearance of one or several autoantibodies and progression to type 1 diabetes in three risk groups: 1) 3,869 islet autoantibody (IA)-negative children, of whom 157 became single IA positive; 2) 302 single IA-positive children, of whom 73 became multiple IA positive; and 3) 294 multiple IA-positive children, of whom 148 developed type 1 diabetes.

RESULTS

No significant association was found in risk group 1 or risk group 2. A significant association was seen in risk group 3 (hazard ratio 0.920 [95% CI 0.856, 0.988] per 10-min increase; P = 0.021), particularly when glutamate decarboxylase autoantibody was the first autoantibody (hazard ratio 0.883 [95% CI 0.783, 0.996] per 10-min increase; P = 0.043).

CONCLUSIONS

More daily minutes spent in moderate to vigorous physical activity was associated with a reduced risk of progression to type 1 diabetes in children aged 5-15 years who had developed multiple IAs.

The countdown to type 1 diabetes: when, how and why does the clock start?

'The clock to type 1 diabetes has started when islet antibodies are first detected', commented George Eisenbarth with regard to the pathogenesis of type 1 diabetes. This review focuses on 'starting the clock', i.e. the initiation of pre-symptomatic islet autoimmunity/the first appearance of islet autoantibodies. In particular, this review addresses why susceptibility to developing islet autoimmunity is greatest in the first 2 years of life and why beta cells are a frequent target of the immune system during this fertile period. A concept for the development of beta cell autoimmunity in childhood is discussed and three factors are highlighted that contribute to this early predisposition: (1) high beta cell activity and potential vulnerability to stress; (2) high rates of and first exposures to infection; and (3) a heightened immune response, with a propensity for T helper type 1 (Th1) immunity. Arguments are presented that beta cell injury, accompanied by activation of an inflammatory immune response, precedes the initiation of autoimmunity. Finally, the implications for strategies aimed at primary prevention for a world without type 1 diabetes are discussed.

Clostridia and Enteroviruses as Synergistic Triggers of Type 1 Diabetes Mellitus

What triggers type 1 diabetes mellitus (T1DM)? One common assumption is that triggers are individual microbes that mimic autoantibody targets such as insulin (INS). However, most microbes highly associated with T1DM pathogenesis, such as coxsackieviruses (COX), lack INS mimicry and have failed to induce T1DM in animal models. Using proteomic similarity search techniques, we found that COX actually mimicked the INS receptor (INSR). Clostridia were the best mimics of INS. Clostridia antibodies cross-reacted with INS in ELISA experiments, confirming mimicry. COX antibodies cross-reacted with INSR. Clostridia antibodies further bound to COX antibodies as idiotype-anti-idiotype pairs conserving INS-INSR complementarity. Ultraviolet spectrometry studies demonstrated that INS-like Clostridia peptides bound to INSR-like COX peptides. These complementary peptides were also recognized as antigens by T cell receptor sequences derived from T1DM patients. Finally, most sera from T1DM patients bound strongly to inactivated Clostridium sporogenes, while most sera from healthy individuals did not; T1DM sera also exhibited evidence of anti-idiotype antibodies against idiotypic INS, glutamic acid decarboxylase, and protein tyrosine phosphatase non-receptor (islet antigen-2) antibodies. These results suggest that T1DM is triggered by combined enterovirus-Clostridium (and possibly combined Epstein-Barr-virus-Streptococcal) infections, and the probable rate of such co-infections approximates the rate of new T1DM diagnoses.

Maternal depression or anxiety during pregnancy and offspring type 1 diabetes: a population-based family-design cohort study

INTRODUCTION

To investigate the association between maternal depression/anxiety during pregnancy and offspring type 1 diabetes, to assess the specific importance of exposure during pregnancy by comparing across different exposure periods before and/or after pregnancy, and to explore potential unmeasured familial confounding.

RESEARCH DESIGN AND METHODS

This was a population-based cohort including 1 807 809 offspring born in Sweden 2002-2019. From national registers, data were available on diagnosis or medication prescription for depression/anxiety in and around pregnancy, as well as incident cases of type 1 diabetes defined through diagnosis or insulin treatment. Associations were examined using flexible parametric and Cox regression models. Familial confounding was explored using paternal exposure as a negative control and by comparing offspring exposed to maternal depression/anxiety with their unexposed siblings.

RESULTS

For exposure during pregnancy, maternal depression/anxiety was associated with an increased risk of offspring type 1 diabetes onset after, but not before, 8 years of age (adjusted HR (aHR) 1.21 (95% CI 1.03 to 1.42]). Exposure occurring only during pregnancy was similarly associated to type 1 diabetes (aHR 1.24 (0.96 to 1.60)), whereas exposure occurring only before pregnancy was not (aHR 0.91 (0.64 to 1.30)). Associations were close to the null for paternal depression/anxiety (aHR 0.95 (0.72 to 1.25)), and point estimates were above 1 in sibling comparisons, although with wide CIs (aHR 1.36 (0.82 to 2.26)).

CONCLUSIONS

Maternal depression/anxiety specifically during pregnancy seems to be associated with offspring type 1 diabetes. Paternal negative control and sibling comparisons indicate that the results cannot entirely be explained by familial confounding.

Precision Medicine in Type 1 Diabetes

Type 1 diabetes is a complex, chronic disease in which the insulin-producing beta cells in the pancreas are sufficiently altered or impaired to result in requirement of exogenous insulin for survival. The development of type 1 diabetes is thought to be an autoimmune process, in which an environmental (unknown) trigger initiates a T cell-mediated immune response in genetically susceptible individuals. The presence of islet autoantibodies in the blood are signs of type 1 diabetes development, and risk of progressing to clinical type 1 diabetes is correlated with the presence of multiple islet autoantibodies. Currently, a "staging" model of type 1 diabetes proposes discrete components consisting of normal blood glucose but at least two islet autoantibodies (Stage 1), abnormal blood glucose with at least two islet autoantibodies (Stage 2), and clinical diagnosis (Stage 3). While these stages may, in fact, not be discrete and vary by individual, the format suggests important applications of precision medicine to diagnosis, prevention, prognosis, treatment and monitoring. In this paper, applications of precision medicine in type 1 diabetes are discussed, with both opportunities and barriers to global implementation highlighted. Several groups have implemented components of precision medicine, yet the integration of the necessary steps to achieve both short- and long-term solutions will need to involve researchers, patients, families, and healthcare providers to fully impact and reduce the burden of type 1 diabetes.

Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics

Insulin is amongst the human genome's most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS-IGF2. This INS-IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS-IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3'UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.

Dietary fatty acid intake in childhood and the risk of islet autoimmunity and type 1 diabetes: the DIPP birth cohort study

PURPOSE

The aim was to study the associations between dietary intake of fatty acids in childhood and the risk of islet autoimmunity and type 1 diabetes (T1D).

METHODS

The prospective Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study included children with genetic susceptibility to T1D born between 1996 and 2004. Participants were followed up every 3 to 12 months up to 6 years for diet, islet autoantibodies, and T1D. Dietary intake of several fatty acids at the age of 3 months to 6 years was assessed 1-8 times per participant with a 3-day food record. Joint models adjusted for energy intake, sex, HLA genotype and familial diabetes were used to investigate the associations of longitudinal intake of fatty acids and the development of islet autoimmunity and T1D.

RESULTS

During the 6-year follow-up, 247 (4.4%) children of 5626 developed islet autoimmunity and 94 (1.7%) children of 5674 developed T1D. Higher intake of monounsaturated fatty acids (HR 0.63; 95% CI 0.47, 0.82), arachidonic acid (0.69; 0.50, 0.94), total n-3 fatty acids (0.64; 0.48, 0.84), and long-chain n-3 fatty acids (0.14; 0.04, 0.43), was associated with a decreased risk of islet autoimmunity with and without energy adjustment. Higher intake of total fat (0.73; 0.53, 0.98), and saturated fatty acids (0.55; 0.33, 0.90) was associated with a decreased risk of T1D only when energy adjusted.

CONCLUSION

Intake of several fatty acids was associated with a decreased risk of islet autoimmunity or T1D among high-risk children. Our findings support the idea that dietary factors, including n-3 fatty acids, may play a role in the disease process of T1D.