The challenges of identifying and studying type 1 diabetes in adults

Type 1 diabetes presenting in adults: Trends, diagnostic challenges and unique features

Type 1 diabetes (T1D) has been historically regarded as a childhood-onset disease; however, recent epidemiological data indicate that adult-onset T1D accounts for a substantial proportion of cases worldwide. There is evidence that adult-onset T1D is associated with the classic T1D triad of elevated genetic risk, the presence of islet-specific autoantibodies and progression to severe insulin deficiency. In this article, we review our understanding of the commonalities and differences between childhood and adult-onset T1D, and we highlight significant knowledge gaps in our understanding of the diagnosis, incidence, trajectory and treatment of adult-onset T1D. Compared to children, adults presenting with T1D exhibit differences in genetic risk, immunologic profiles and metabolic outcomes, including differences in the type and number of autoantibodies present, genetic associations and total genetic burden, rates of C-peptide decline, the persistence of C-peptide in long-duration disease and glycaemic control. In addition, obesity and metabolic syndrome are increasingly common in adults, which not only blurs the clinical distinction of adult-onset T1D from type 2 diabetes (T2D) but also likely contributes to differences in metabolic outcomes and rates of progression. Because T2D is so prevalent in the adult population, adult-onset T1D is misclassified as T2D in at least one in three cases, leading to delays in appropriate treatment. Current diagnostic tools, including autoantibody testing and C-peptide measurement, are underutilised or lack specificity in distinguishing adult-onset T1D from atypical T2D. Additionally, the impact of different responses to disease-modifying therapy between adults and children is unclear. Addressing these knowledge gaps requires expanded epidemiological studies, diverse patient registries and refined classification criteria to improve early detection and treatment strategies. A deeper understanding of adult-onset T1D will be critical to reduce the burden of misdiagnosis, lead to earlier diagnosis and treatment and optimise population-based screening approaches in this under-recognised population. PLAIN LANGUAGE SUMMARY: Type 1 diabetes (T1D) is an autoimmune disease that causes metabolic and nutritional complications due to the destruction of insulin-producing pancreatic β cells. T1D was formerly known as "juvenile diabetes" because it was assumed that most cases occurred in childhood; however, recent epidemiological data show that nearly half of all T1D cases are diagnosed in adulthood. Despite the high prevalence of adult-onset T1D, there are challenges with correctly diagnosing T1D in adulthood, and significant knowledge gaps remain regarding the incidence, trajectory, and treatment of adult-onset T1D. In this article, we summarize the current understanding of commonalities and differences between childhood and adult-onset T1D. Particularly, we highlight age-related differences in genetic risk, immunologic profiles, and metabolic outcomes and complications. Finally, we highlight key gaps in our understanding of adult-onset T1D that need to be addressed to reduce the burden of misdiagnosis and allow for better screening and treatment of T1D in adulthood.

Envisioning Tools to Help Classify Type 1 Diabetes and Type 2 Diabetes in New-Onset Adult Diabetes

A tool is needed to distinguish type 1 diabetes (T1D) and type 2 diabetes (T2D) in adults with new-onset diabetes because correct classification is needed for correct diagnoses and treatments. Current classification methods are usually applied to biomarkers using binary or quantitative classification with a cut point and may not be adequately nuanced. Combinations of clinical features are not necessarily specific for classifying and may not always indicate a single diagnosis. A probabilistic decision tree classification tool with multiple branches per decision node is needed for adults with new-onset diabetes to avoid misdiagnosis of actual T1D as T2D, misdiagnosis of actual T2D or monogenic diabetes as T1D, and misclassified patients in future population health studies which will lead to incorrect conclusions and suboptimal patient outcomes.

Technological functionality and system architecture of mobile health interventions for diabetes management: a systematic review and meta-analysis of randomized controlled trials

Introduction

Despite advancements in digital health, systematic evaluations of mobile applications (Apps) for diabetes management are limited.

Methods

Researchers conducted searches on PUBMED, EMBASE, COCHRANE, SCOPUS, and WEB OF SCIENCE from inception to August 2024. The researchers included randomized controlled trials (RCTs) that investigated the effectiveness of app-based interventions in health management among diabetic patients. Reviewers were paired and independently conducted the screening of studies, data extraction, and evaluation of study quality. The primary outcome of interest was the modification of hemoglobin A1c (HbA1c). The researchers utilized a random effects model to calculate the weighted mean differences (WMDs) and 95% confidence intervals (CIs) and used the I2 statistic to assess study heterogeneity. Publication bias for the primary outcomes underwent assessment. Studies were Appraised for quality using the Cochrane Risk of Bias assessment.

Results

41 studies of 3911 initially identified articles that met the selection criteria. The results showed that Apps' intervention significantly improved glycemic control in diabetic patients, with a mean reduction in HbA1c levels of 0.49% (95%CI: -0.65 to -0.32%) compared to standard care. The analysis also revealed that Apps enhanced patient self-management behaviors. Subgroup analyses failed to resolve heterogeneity, but studies consistently observed improved HbA1c levels. The quality assessment results indicated that most studies performed well in the completeness of outcome data and selective reporting.

Discussion

This meta-analysis confirms that mobile health applications with practical technological functionalities and system architectures are beneficial in managing diabetes. These applications significantly reduced HbA1c levels and improved self-management behaviors. Although some studies exhibited a moderate risk of bias, the overall evidence supports using these applications as valuable tools in diabetes care. Future research should standardize application features, refine system architectures, and address bias issues to enhance.

Systematic Review Registration

PROSPERO (CRD42023441365).

The epidemiology of type 1 diabetes mellitus in older adults

Although type 1 diabetes mellitus (T1DM) is traditionally viewed as a youth-onset disorder, the number of older adults being diagnosed with this disease is growing. Improvements in the average life expectancy of people with T1DM have also contributed to the growing number of older people living with this disease. We summarize the evidence regarding the epidemiology (incidence, prevalence and excess mortality) of T1DM in older adults (ages ≥60 years) as well as the genetics, immunology and diagnostic challenges. Several studies report an incidence peak of T1DM in older adults of a similar size to or exceeding that in children, and population prevalence generally increases with increasing age. Glutamic acid decarboxylase antibody positivity is frequently observed in adult-onset T1DM. Guidelines for differentiating T1DM from type 2 diabetes mellitus in older adults recommend measuring levels of C-peptide and autoantibodies, including glutamic acid decarboxylase antibodies. However, there is no gold standard for differentiating T1DM from type 2 diabetes mellitus in people aged 60 years and over. As such, the global variation observed in T1DM epidemiology might be in part explained by misclassification, which increases with increasing age of diabetes mellitus onset. With a growing global population of older adults with T1DM, improved genetic and immunological evidence is needed to differentiate diabetes mellitus type at older ages so that a clear epidemiological picture can emerge.

Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches

A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes. In the overall cohort, WGS-based T1DGRS demonstrated strong correlation with TOPMed-imputed array-based score (r = 0.996, average WGS-based score 0.0028 standard deviations (SD) lower, p < 10- 31), while showing lower correlation with 1000 Genomes-imputed array-based scores (r = 0.981, 0.043 SD lower in WGS, p < 10- 300). Ancestry-stratified analyses between WGS-based and TOPMed-imputed array-based score showed the highest correlation with European ancestry (r = 0.996, 0.044 SD lower in WGS, p < 10- 300) followed by African ancestry (r = 0.989, 0.0193 SD lower in WGS, p < 10- 14) and South Asian ancestry (r = 0.986, 0.0129 SD lower in WGS, p < 10 - 6). These differences were more pronounced when comparing WGS based score with 1000 Genomes-imputed array-based scores (r = 0.982, 0.975, 0.957 for European, South Asian, African respectively). Population-level analysis using WGS-based T1DGRS revealed significant ancestry-based stratification, with European ancestry individuals showing the highest scores, followed by South Asian (average 0.28 SD lower than Europeans, p < 10- 58) and African ancestry individuals (average 0.89 SD lower than Europeans, p < 10- 300). Notably, when applying the European ancestry-derived 90th centile risk threshold, only 0.71% (95% CI 0.41-1.13) of African ancestry individuals and 6.4% (95% CI 5.6-7.2) of South Asian individuals were identified as high-risk, substantially below the expected 10%. In conclusion, while WGS is viable for generating T1DGRS, with TOPMed-imputed genotypes offering a cost-effective alternative, the persistence of ancestry-based variations in T1DGRS distribution even using whole genome sequencing emphasises the need for ancestry-specific or pan-ancestry standards in clinical practice.

Trends in the incidence of young-adult-onset diabetes by diabetes type: a multi-national population-based study from an international diabetes consortium

BACKGROUND

Population-based incidence data on young-adult-onset type 1 diabetes and type 2 diabetes are limited. We aimed to examine secular trends in the incidence of diagnosed type 1 diabetes and type 2 diabetes with an age of onset between 15 and 39 years.

METHODS

In this multicountry aggregate data analysis, we assembled eight administrative datasets from high-income jurisdictions and countries (Australia, Denmark, Finland, Hungary, Japan, Scotland, South Korea, and Spain [Catalonia]) that had appropriate data available from an international diabetes consortium (GLOBODIAB) describing incidence by diabetes type among people aged 15-39 years from 2000 to 2020. We modelled type 1 diabetes and type 2 diabetes incidence rates using Poisson regression including age and calendar time by sex.

FINDINGS

During the years 2000-20, there were 349 591 incident diabetes (both types) cases from 346 million person-years of follow-up among people aged 15-39 years. Over time, there was no statistically significant change in the incidence of type 1 diabetes in Hungary and Japan. The incidence of type 1 diabetes significantly increased in Australia, Denmark, Finland, Scotland, South Korea, and Spain, with annual changes ranging from 0·5% to 6·0%. The incidence of type 2 diabetes significantly increased in four of eight jurisdictions (Denmark, Finland, Japan, and South Korea), with annual increases from 2·0% to 8·5%. The magnitude of increase in incidence of type 2 diabetes was greater in Asian than non-Asian jurisdictions. There was no statistically significant change in type 2 diabetes incidence in Australia and Hungary. The incidence of type 2 diabetes significantly decreased in Scotland and Spain, with annual changes of -0·7% and -1·5%, respectively.

INTERPRETATION

There is variability in the trajectory of the incidence of young-adult-onset type 2 diabetes among high-income countries or jurisdictions, with a greater evidence of increase in Asian than non-Asian countries. Evolving trends in the incidence of type 1 and type 2 diabetes in young adults call for the ongoing surveillance of diabetes incidence and a greater research focus on this population.

FUNDING

US Centers for Disease Control and Prevention, Diabetes Australia Research Programme, and Victoria State Government Operational Infrastructure Support Programme.

Choline Metabolites and 15-Year Risk of Incident Diabetes in a Prospective Cohort of Adults: Coronary Artery Risk Development in Young Adults (CARDIA) Study

OBJECTIVE

The potential for choline metabolism to influence the development of diabetes has received increased attention. Previous studies on circulating choline metabolites and incident diabetes have been conducted in samples of older adults, often with a high prevalence of risk factors.

RESEARCH DESIGN AND METHODS

Participants were from year 15 of follow-up (2000-2001) in the Coronary Artery Risk Development in Young Adults (CARDIA) Study (n = 3,133, aged 33-45 years) with plasma choline metabolite (choline, betaine, and trimethylamine N-oxide [TMAO]) data. We quantified associations between choline metabolites and 15-year risk of incident diabetes (n = 387) among participants free of diabetes at baseline using Cox proportional hazards regression models adjusted for sociodemographics, health behaviors, and clinical variables.

RESULTS

Betaine was inversely associated with 15-year risk of incident diabetes (hazard ratio 0.76 [95% CI 0.67, 0.88] per 1-SD unit betaine), and TMAO was positively associated with 15-year risk of incident diabetes (1.11 [1.01, 1.22] per 1-SD unit). Choline was not significantly associated with 15-year risk of incident diabetes (1.05 [0.94, 1.16] per 1-SD).

CONCLUSIONS

Our findings are consistent with other published literature supporting a role for choline metabolism in diabetes. Our study extends the current literature by analyzing a racially diverse population-based cohort of early middle-aged individuals in whom preventive activities may be most relevant.

Insights into Knowledge and Attitudes About Autoantibody Screening from People Affected by Type 1 Diabetes: A Brief Report

INTRODUCTION

Screening for islet-specific autoantibodies can identify individuals at risk for type 1 diabetes (T1D). Despite calls for increased nationwide autoantibody screening efforts, it is unclear how many individuals have participated in screening among people who may benefit from it. Moreover, knowledge and perceptions of autoantibody screening in real-world samples are not well understood.

METHODS

We surveyed a sample of individuals (aged 18+ years old) from T1D Exchange Registry with a personal or family history of T1D to assess their self-reported T1D autoantibody knowledge, experiences, and attitudes. Participants belonged to one of three groups: adults with T1D who had a biological child without T1D or future plans for a child (PWD); parents without T1D who had a biological child with T1D and one or more biological children without T1D (Caregivers); and first-degree adult children or siblings to a person with T1D (Relatives). Descriptive analyses (means, standard deviations, frequencies) are presented by participant groups.

RESULTS

A total of 510 participants enrolled in the study. Across groups, participants reported feeling a little to somewhat knowledgeable about autoantibody screening and positive perceptions of autoantibody screening in general. However, few participants had screened their child without T1D (PWDs, 21.94%; Caregivers, 46.30%) or themselves (Relatives, 19.23%). Among those who had screened, participants reported generally positive experiences. Among those who had not screened, many participants were "undecided" about autoantibody screening (PWD, 38.46%; Caregivers, 40.52%; Relatives, 44.44%). Influences reported for participants' decisions to screen, not screen, or their current indecision differed by group: PWDs (21.70%) and Caregivers (26.87%) most often reported self-initiated research as an influence and Relatives reported they had not previously considered screening (48.28%).

CONCLUSION

Results highlight the need for more accessible information about screening, including real experiences from those who have screened.

A functional variant rs912304 for late-onset T1D risk contributes to islet dysfunction by regulating proinflammatory cytokine-responsive gene STXBP6 expression

BACKGROUND

Our previous genome‑wide association studies (GWAS) have suggested rs912304 in 14q12 as a suggestive risk variant for type 1 diabetes (T1D). However, the association between this risk region and T1D subgroups and related clinical risk features, the underlying causal functional variant(s), putative candidate gene(s), and related mechanisms are yet to be elucidated.

METHODS

We assessed the association between variant rs912304 and T1D, as well as islet autoimmunity and islet function, stratified by the diagnosed age of 12. We used epigenome bioinformatics analyses, dual luciferase reporter assays, and expression quantitative trait loci (eQTL) analyses to prioritize the most likely functional variant and potential causal gene. We also performed functional experiments to evaluate the role of the causal gene on islet function and its related mechanisms.

RESULTS

We identified rs912304 as a risk variant for T1D subgroups with diagnosed age ≥ 12 but not < 12. This variant is associated with residual islet function but not islet-specific autoantibody positivity in T1D individuals. Bioinformatics analysis indicated that rs912304 is a functional variant exhibiting spatial overlaps with enhancer active histone marks (H3K27ac and H3K4me1) and open chromatin status (ATAC-seq) in the human pancreas and islet tissues. Luciferase reporter gene assays and eQTL analyses demonstrated that the biallelic sites of rs912304 had differential allele-specific enhancer activity in beta cell lines and regulated STXBP6 expression, which was defined as the most putative causal gene based on Open Targets Genetics, GTEx v8 and Tiger database. Moreover, Stxbp6 was upregulated by T1D-related proinflammatory cytokines but not high glucose/fat. Notably, Stxbp6 over-expressed INS-1E cells exhibited decreasing insulin secretion and increasing cell apoptosis through Glut1 and Gadd45β, respectively.

CONCLUSIONS

This study expanded the genomic landscape regarding late-onset T1D risk and supported islet function mechanistically connected to T1D pathogenesis.

Islet autoantibody frequency in relatives of children with type 1 diabetes who have a type 2 diabetes diagnosis

AIM

This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes.

METHODS

Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests.

RESULTS

Among 226 relatives (64% men; mean age at sampling 41 years; mean age 54 years at diagnosis), 32 (14%) were islet autoantibody-positive for at least one autoantibody more than a decade before diagnosis. Approximately half of these (n = 15) were treated with insulin. GADA-positivity was higher in insulin-treated relatives than in non-insulin-treated relatives (12/18 [67%] vs. 6/18 [33%], p < 0.001). IAA-positivity was observed in 13/32 (41%) of relatives with autoantibodies. GRS2 scores were increased in autoantibody-positive relatives (p = 0.032), but there was no clear evidence for a difference according to treatment (p = 0.072).

CONCLUSION

This study highlights the importance of measuring islet autoantibodies, including IAA, in relatives of people with type 1 diabetes to avoid misdiagnosis.

Machine Learning-Driven Prediction of Comorbidities and Mortality in Adults With Type 1 Diabetes

BACKGROUND

Comorbidities such as cardiovascular disease (CVD) and diabetic kidney disease (DKD) are major burdens of type 1 diabetes (T1D). Predicting people at high risk of developing comorbidities would enable early intervention. This study aimed to develop models incorporating socioeconomic status (SES) to predict CVD, DKD, and mortality in adults with T1D to improve early identification of comorbidities.

METHODS

Nationwide Danish registry data were used. Logistic regression models were developed to predict the development of CVD, DKD, and mortality within five years of T1D diagnosis. Features included age, sex, personal income, and education. Performance was evaluated by five-fold cross-validation with area under the receiver operating characteristic curve (AUROC) and the precision-recall area under the curve (PR-AUC). The importance of SES was assessed from feature importance plots.

RESULTS

Of the 6572 included adults (≥21 years) with T1D, 379 (6%) developed CVD, 668 (10%) developed DKD, and 921 (14%) died within the five-year follow-up. The AUROC (±SD) was 0.79 (±0.03) for CVD, 0.61 (±0.03) for DKD, and 0.87 (±0.01) for mortality. The PR-AUC was 0.18 (±0.01), 0.15 (±0.03), and 0.49 (±0.02), respectively. Based on feature importance plots, SES was the most important feature in the DKD model but had minimal impact on models for CVD and mortality.

CONCLUSIONS

The developed models showed good performance for predicting CVD and mortality, suggesting they could help in the early identification of these outcomes in individuals with T1D. The importance of SES in individual prediction within diabetes remains uncertain.

Global burden of type 1 diabetes in adults aged 65 years and older, 1990-2019: population based study

OBJECTIVES

To estimate the burden, trends, and inequalities of type 1 diabetes mellitus (T1DM) among older adults at global, regional, and national level from 1990 to 2019.

DESIGN

Population based study.

POPULATION

Adults aged ≥65 years from 21 regions and 204 countries and territories (Global Burden of Disease and Risk Factors Study 2019)from 1990 to 2019.

MAIN OUTCOME MEASURES

Primary outcomes were T1DM related age standardised prevalence, mortality, disability adjusted life years (DALYs), and average annual percentage change.

RESULTS

The global age standardised prevalence of T1DM among adults aged ≥65 years increased from 400 (95% uncertainty interval (UI) 332 to 476) per 100 000 population in 1990 to 514 (417 to 624) per 100 000 population in 2019, with an average annual trend of 0.86% (95% confidence interval (CI) 0.79% to 0.93%); while mortality decreased from 4.74 (95% UI 3.44 to 5.9) per 100 000 population to 3.54 (2.91 to 4.59) per 100 000 population, with an average annual trend of -1.00% (95% CI -1.09% to -0.91%), and age standardised DALYs decreased from 113 (95% UI 89 to 137) per 100 000 population to 103 (85 to 127) per 100 000 population, with an average annual trend of -0.33% (95% CI -0.41% to -0.25%). The most significant decrease in DALYs was observed among those aged <79 years: 65-69 (-0.44% per year (95% CI -0.53% to -0.34%)), 70-74 (-0.34% per year (-0.41% to -0.27%)), and 75-79 years (-0.42% per year (-0.58% to -0.26%)). Mortality fell 13 times faster in countries with a high sociodemographic index versus countries with a low-middle sociodemographic index (-2.17% per year (95% CI -2.31% to -2.02%) v -0.16% per year (-0.45% to 0.12%)). While the highest prevalence remained in high income North America, Australasia, and western Europe, the highest DALY rates were found in southern sub-Saharan Africa, Oceania, and the Caribbean. A high fasting plasma glucose level remained the highest risk factor for DALYs among older adults during 1990-2019.

CONCLUSIONS

The life expectancy of older people with T1DM has increased since the 1990s along with a considerable decrease in associated mortality and DALYs. T1DM related mortality and DALYs were lower in women aged ≥65 years, those living in regions with a high sociodemographic index, and those aged <79 years. Management of high fasting plasma glucose remains a major challenge for older people with T1DM, and targeted clinical guidelines are needed.