The Influence of Type 2 Diabetes-Associated Factors on Type 1 Diabetes

A Glucose Fraction Independent of Insulin Secretion: Implications for Type 1 Diabetes Progression in Autoantibody-Positive Cohorts

Objective: We assessed whether there is an impactful glucose fraction independent of insulin secretion in autoantibody-positive individuals. Research Design and Methods: Baseline 2-h oral glucose tolerance test data from the TrialNet Pathway to Prevention (TNPTP; n = 6190) and Diabetes Prevention Trial-Type 1 (DPT-1; n = 705) studies were used. Linear regression of area under the curve (AUC) glucose versus Index60 was performed to identify two fractions: dependent (dAUCGLU) or independent (iAUCGLU) of insulin secretion. Results: The lack of correlation (r = 0.06) of iAUCGLU and the inverse correlation of dAUCGLU (r = -0.59) with the first-phase insulin response from DPT-1 were consistent with the independent and dependent designations of the glucose fractions. Correlations of AUC C-peptide were inverse with dAUCGLU and positive with iAUCGLU (TNPTP: r = -0.72, r = 0.57; DPT-1: r = -0.56, r = 0.60). The explained variance of AUC C-peptide increased markedly after separating AUC glucose into its fractions (from 4% to 85% in TNPTP; from 1% to 67% in DPT-1). The independent fraction contributed more to the increased glycemia of impaired glucose tolerance (IGT) than did the dependent fraction. Both dAUCGLU and iAUCGLU predicted IGT and type 1 diabetes (T1D) (P < 0.0001 for all). However, whereas dAUCGLU was more predictive of T1D (chi-square: 849 vs. 249), iAUCGLU was more predictive of IGT (chi-square: 451 vs. 176). Conclusions: A glucose fraction independent of insulin secretion was identified that was appreciable in autoantibody-positive individuals. It provides insight into the relation between glucose and C-peptide, contributes substantially to the glycemia of IGT, and predicts both T1D and IGT, particularly the latter.

Diabetes Management Based on the Phenotype and Stage of the Disease: An Expert Proposal from the AGORA Diabetes Collaborative Group

Diabetes is a complex and rapidly growing disease with heterogeneous clinical presentations. Recent advances in molecular and genetic technologies have led to the identification of various subtypes of diabetes. These advancements offer the potential for a more precise, individualized approach to treatment, known as precision medicine. Recognizing high-risk phenotypes and intervening early and intensively is crucial. A staging system for type 1 diabetes has been proposed and accepted globally. In this article, we will explore the different methods for categorizing and classifying type 2 diabetes (T2D) based on clinical characteristics, progression patterns, risk of complications, and the use of molecular techniques for patient grouping. We, as a team of experts, will also present an easy-to-follow treatment plan and guidance for non-specialists, particularly primary care physicians, that integrates the classification and staging of diabetes. This will help ensure that the most suitable therapy is applied to the different types of T2D at each stage of the disease's progression.

Family History of Type 2 Diabetes and Its Association with Beta Cell Function and Lipid Profile in Newly Diagnosed Pediatric Patients with Type 1 Diabetes

OBJECTIVE

The objective of this study was to explore the associations between a family history of type 2 diabetes (T2D) and beta-cell function, as well as lipid profile, in pediatric patients newly diagnosed with type 1 diabetes (T1D).

METHODS

A retrospective analysis was conducted on children under 14 years of age who were newly diagnosed with T1D at the Children's Hospital of Zhejiang University between August 2018 and August 2022. Clinical features, metabolic profiles, beta-cell function, and lipid profile were evaluated.

RESULTS

A total of 316 children were diagnosed with new-onset T1D. Among them, 28.2% had a family history of T2D. Patients with T1D who had a family history of T2D experienced a later onset of the disease (p = 0.016), improved HOMA2-%B levels (p = 0.003), and increased concentrations of HDL-C (p = 0.005). In addition, no statistically significant differences in age at onset, HOMA2-%B levels, or HDL-C were found when assessing the interaction between family history of T2D and type of diabetes mellitus (autoimmune T1D/idiopathic T1D).

CONCLUSION

A family history of T2D may contribute to the heterogeneity of T1D patients in terms of HOMA2-%B levels and lipid profile. This highlights the significance of taking into account T2D-related factors in the diagnosis and treatment of T1D.

Cardiovascular diseases consequences of type 1, type 2 diabetes mellitus and glycemic traits: A Mendelian randomization study

OBJECTIVE

This Mendelian randomization (MR) study aimed to investigate the relationships between type 1 diabetes (T1D), type 2 diabetes (T2D), and glycemic traits, including fasting insulin, fasting glucose, and HbA1c, with cardiovascular diseases (CVDs).

METHODS

We selected genetic instruments for predisposition to T1D, T2D, fasting insulin, fasting glucose, and HbA1c based on published genome-wide association studies. Using a 2-Sample MR approach, we assessed associations with 12 common CVDs sourced from the FinnGen and UK Biobank studies, along with stroke subtypes obtained from the GIGASTROKE and MEGASTROKE Consortium.

RESULTS

T1D was associated with SVS. T2D showed associations with AIS, LAA, CES, SVS, coronary heart disease, myocardial infarction, pulmonary embolism, DVT of lower extremities, peripheral vascular diseases. Genetically predicted higher HbA1c levels were associated with eight CVDs. The results of MVMR aligned with the primary findings for T1D and T2D.

CONCLUSIONS

T1D and T2D exhibit different genetic predisposition to CVDs. BMI, LDL, and HDL play intermediary roles in connecting TID and T2D to specific types of CVDs, providing insights into the potential underlying pathways and mechanisms involved in these relationships. Strategies aimed at achieving sustained reductions in HbA1c levels may offer potential for reducing the risk of various CVDs.

Type 2 Diabetes Family History as a Significant Index on the Clinical Heterogeneity Differentiation in Type 1 Diabetes

CONTEXT

Family history of type 2 diabetes (T2D) is an important but neglected parameter; however, its role in identifying the heterogeneity and subtypes of type 1 diabetes (T1D) remains unclear.

OBJECTIVE

We investigated the effect of family history of T2D on the clinical phenotype of T1D patients and evaluated its value in T1D classification.

METHODS

A total of 1410 T1D patients were enrolled in this prospective study. Information on family history of T2D in first-degree relatives (FDRs) was collected by research nurses using a semi-structured questionnaire as previously described. The effect of family history of T2D on clinical characteristics was evaluated in overall and subgroups of T1D patients stratified by islet autoantibodies, onset age, and human leukocyte antigen (HLA) genotype. Cluster analysis was performed to identify family history of T2D-related subgroups.

RESULTS

A total of 10% (141/1410) of patients had at least 1 FDR diagnosed with T2D. A milder phenotype associated with family history of T2D was present in overall T1D patients, including older onset age (P < .001), higher body mass index (P < .001), higher fasting and postprandial C-peptide levels (all P < .01), lower positive rates of all islet autoantibodies, and susceptible HLA genotypes (all P < .05). Clinical heterogeneity associated with family history of T2D in the T1D subgroup stratified by autoimmunity, age of onset, and HLA genotypes was consistent. Using family history of T2D as a cluster variable, T1D patients were divided into 5 clusters, and patients in the T2D family history cluster displayed a milder phenotype than others.

CONCLUSION

Family history of T2D should be considered as an important indicator for precise subclassification of T1D patients based on clinical heterogeneity.

Understanding diabetes heterogeneity: key steps towards precision medicine in diabetes

Diabetes is a highly heterogeneous condition; yet, it is diagnosed by measuring a single blood-borne metabolite, glucose, irrespective of aetiology. Although pragmatically helpful, disease classification can become complex and limit advances in research and medical care. Here, we describe diabetes heterogeneity, highlighting recent approaches that could facilitate management by integrating three disease models across all forms of diabetes, namely, the palette model, the threshold model and the gradient model. Once diabetes has developed, further worsening of established diabetes and the subsequent emergence of diabetes complications are kept in check by multiple processes designed to prevent or circumvent metabolic dysfunction. The impact of any given disease risk factor will vary from person-to-person depending on their background, diabetes-related propensity, and environmental exposures. Defining the consequent heterogeneity within diabetes through precision medicine, both in terms of diabetes risk and risk of complications, could improve health outcomes today and shine a light on avenues for novel therapy in the future.

The pathogenic "symphony" in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas

Type 1 diabetes (T1D) is widely considered to result from the autoimmune destruction of insulin-producing β cells. This concept has been a central tenet for decades of attempts seeking to decipher the disorder's pathogenesis and prevent/reverse the disease. Recently, this and many other disease-related notions have come under increasing question, particularly given knowledge gained from analyses of human T1D pancreas. Perhaps most crucial are findings suggesting that a collective of cellular constituents-immune, endocrine, and exocrine in origin-mechanistically coalesce to facilitate T1D. This review considers these emerging concepts, from basic science to clinical research, and identifies several key remaining knowledge voids.

Prevalence, clinical characteristics and HLA genotypes of idiopathic type 1 diabetes: A cross-sectional study

AIMS

Idiopathic type 1 diabetes (T1D) is a neglected subtype of T1D. Our aim was to investigate the frequency, clinical characteristics, and human leucocyte antigen (HLA) genotypes of idiopathic T1D.

METHODS

We enrolled 1205 newly diagnosed T1D patients in our analysis. To exclude monogenic diabetes in autoantibody-negative patients, we utilised a custom monogenic diabetes gene panel. Individuals negative for autoantibodies and subsequently excluded for monogenic diabetes were diagnosed with idiopathic T1D. We collected clinical characteristics, measured islet autoantibodies by radioligand assay and obtained HLA data.

RESULTS

After excluding 11 patients with monogenic diabetes, 284 cases were diagnosed with idiopathic T1D, accounting for 23.8% (284/1194) of all newly diagnosed T1D cases. When compared with autoimmune T1D, idiopathic T1D patients showed an older onset age, higher body mass index among adults, lower haemoglobin A1c, higher levels of fasting C-peptide and 2-h postprandial C-peptide, and were likely to have type 2 diabetes (T2D) family history and carry 0 susceptible HLA haplotype (all p < 0.01). A lower proportion of individuals carrying 2 susceptible HLA haplotypes in idiopathic T1D was observed in the adult-onset subgroup (15.7% vs. 38.0% in child-onset subgroup, p < 0.001) and in subgroup with preserved beta-cell function (11.0% vs. 30.1% in subgroup with poor beta-cell function, p < 0.001). Multivariable correlation analyses indicated that being overweight, having T2D family history and lacking susceptible HLA haplotypes were associated with negative autoantibodies.

CONCLUSIONS

Idiopathic T1D represents about 1/4 of newly diagnosed T1D, with adult-onset and preserved beta-cell function patients showing lower HLA susceptibility and more insulin resistance.

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.

Data Mining Framework for Discovering and Clustering Phenotypes of Atypical Diabetes

CONTEXT

Some individuals present with forms of diabetes that are "atypical" (AD), which do not conform to typical features of either type 1 diabetes (T1D) or type 2 diabetes (T2D). These forms of AD display a range of phenotypic characteristics that likely reflect different endotypes based on unique etiologies or pathogenic processes.

OBJECTIVE

To develop an analytical approach to identify and cluster phenotypes of AD.

METHODS

We developed Discover Atypical Diabetes (DiscoverAD), a data mining framework, to identify and cluster phenotypes of AD. DiscoverAD was trained against characteristics of manually classified patients with AD among 278 adults with diabetes within the Cameron County Hispanic Cohort (CCHC) (Study A). We then tested DiscoverAD in a separate population of 758 multiethnic children with T1D within the Texas Children's Hospital Registry for New-Onset Type 1 Diabetes (TCHRNO-1) (Study B).

RESULTS

We identified an AD frequency of 11.5% in the CCHC (Study A) and 5.3% in the pediatric TCHRNO-1 (Study B). Cluster analysis identified 4 distinct groups of AD in Study A: cluster 1, positive for the 65 kDa glutamate decarboxylase autoantibody (GAD65Ab), adult-onset, long disease duration, preserved beta-cell function, no insulin treatment; cluster 2, GAD65Ab negative, diagnosed at age ≤21 years; cluster 3, GAD65Ab negative, adult-onset, poor beta-cell function, lacking central obesity; cluster 4, diabetic ketoacidosis (DKA)-prone participants lacking a typical T1D phenotype. Applying DiscoverAD to the pediatric patients with T1D in Study B revealed 2 distinct groups of AD: cluster 1, autoantibody negative, poor beta-cell function, lower body mass index (BMI); cluster 2, autoantibody positive, higher BMI, higher incidence of DKA.

CONCLUSION

DiscoverAD can be adapted to different datasets to identify and define phenotypes of participants with AD based on available clinical variables.

The impact of family history of type 2 diabetes on clinical heterogeneity in idiopathic type 1 diabetes

AIM

To investigate the impact of family history of type 2 diabetes (T2D) on the clinical phenotypes of patients with idiopathic type 1 diabetes (T1D).

METHODS

In clinically diagnosed T1D cases, a total of 335 idopathic T1D patients were included in the study, after excluding autoimmune T1D using islet autoantibody testing and monogenic diabetes using a custom monogenic diabetes gene panel obtained from clinically diagnosed T1D cases. A semi-structured questionnaire was used to collect information on the presence of T2D in first-degree relatives. The demographic and metabolic markers of idiopathic T1D patients were analysed. Subgroup analysis was performed to investigate potential interactions between T2D family history and human leukocyte antigen (HLA) genotypes.

RESULTS

A total of 18.2% of individuals with idiopathic T1D had a T2D family history, and these individuals were more likely to have features associated with T2D, such as older age of onset, higher body mass index at diagnosis, lower insulin dosage and better beta-cell function, as indicated by higher levels of fasting C-peptide and 2-hour postprandial C-peptide (all P < 0.05). Additionally, regardless of HLA susceptible genotypes, the impact of family history of T2D was consistently observed in idiopathic T1D patients. Multivariable analyses showed that T2D family history was negatively correlated with the risk of beta-cell function failure in idiopathic T1D patients (P < 0.05).

CONCLUSIONS

Family history of T2D may be implicated in the heterogeneity of idiopathic T1D patients.

The Association of CTLA-4 rs231775 and rs3087243 Polymorphisms with Latent Autoimmune Diabetes in Adults: A Meta-Analysis

Polymorphisms rs231775 and rs3087243 of cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) gene have been associated with risk of latent autoimmune diabetes in adults (LADA). However, the results were inconsistent. The purpose of this study was to quantitatively assess the relationship between polymorphisms rs231775 and rs3087243 of CTLA-4 and LADA in a larger pooled population by performing a meta-analysis. Systematic search for eligible studies was conducted in PubMed, Web of Science, and Embase. Case-control studies containing genotype frequencies of polymorphisms rs231775 or rs3087243 were selected, and pooled odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the associations between polymorphisms of CTLA-4 and LADA in allelic, dominant and recessive genetic model. A total of eleven studies, in which five studies reported rs231775, two studies reported rs3087342, and four studies reported both rs231775 and rs3087243, were identified. Among them, one study wasn't included in the following meta-analysis because the distribution of genotypes in the control group didn't comply with Hardy-Weinberg equilibrium. Significant associations with susceptibility to LADA were detected for rs231775 (785 cases and 3435 controls) and for rs3087243 (820 cases and 4824 controls) in overall population. Further subgroup analyses for ethnicity (Asian, Caucasian, and African) have also indicated the positive association between rs231775 and LADA. As for rs3087243, subgroup analyses detected the association between polymorphism and LADA in Caucasian population under recessive model. Polymorphisms rs231775 and rs3087243 of CTLA-4 gene are potential risk factors for LADA and may serve as novel genetic biomarkers of LADA.

Toward an Improved Classification of Type 2 Diabetes: Lessons From Research into the Heterogeneity of a Complex Disease

CONTEXT

Accumulating evidence indicates that type 2 diabetes (T2D) is phenotypically heterogeneous. Defining and classifying variant forms of T2D are priorities to better understand its pathophysiology and usher clinical practice into an era of "precision diabetes."

EVIDENCE ACQUISITION AND METHODS

We reviewed literature related to heterogeneity of T2D over the past 5 decades and identified a range of phenotypic variants of T2D. Their descriptions expose inadequacies in current classification systems. We attempt to link phenotypically diverse forms to pathophysiology, explore investigative methods that have characterized "atypical" forms of T2D on an etiological basis, and review conceptual frameworks for an improved taxonomy. Finally, we propose future directions to achieve the goal of an etiological classification of T2D.

EVIDENCE SYNTHESIS

Differences among ethnic and racial groups were early observations of phenotypic heterogeneity. Investigations that uncover complex interactions of pathophysiologic pathways leading to T2D are supported by epidemiological and clinical differences between the sexes and between adult and youth-onset T2D. Approaches to an etiological classification are illustrated by investigations of atypical forms of T2D, such as monogenic diabetes and syndromes of ketosis-prone diabetes. Conceptual frameworks that accommodate heterogeneity in T2D include an overlap between known diabetes types, a "palette" model integrated with a "threshold hypothesis," and a spectrum model of atypical diabetes.

CONCLUSION

The heterogeneity of T2D demands an improved, etiological classification scheme. Excellent phenotypic descriptions of emerging syndromes in different populations, continued clinical and molecular investigations of atypical forms of diabetes, and useful conceptual models can be utilized to achieve this important goal.

A Comprehensive Review of Neuronal Changes in Diabetics

There has been an exponential rise in diabetes mellitus (DM) cases on a global scale. Diabetes affects almost every system of the body, and the nervous system is no exception. Although the brain is dependent on glucose, providing it with the energy required for optimal functionality, glucose also plays a key role in the regulation of oxidative stress, cell death, among others, which furthermore contribute to the pathophysiology of neurological disorders. The variety of biochemical processes engaged in this process is only matched by the multitude of clinical consequences resulting from it. The wide-ranging effects on the central and peripheral nervous system include, but are not limited to axonopathies, neurodegenerative diseases, neurovascular diseases, and general cognitive impairment. All language search was conducted on MEDLINE, COCHRANE, EMBASE, and GOOGLE SCHOLAR till September 2021. The following search strings and Medical Subject Headings (MeSH terms) were used: "Diabetes Mellitus," "CNS," "Diabetic Neuropathy," and "Insulin." We explored the literature on diabetic neuropathy, covering its epidemiology, pathophysiology with the respective molecular pathways, clinical consequences with a special focus on the central nervous system and finally, measures to prevent and treat neuronal changes. Diabetes is slowly becoming an epidemic, rapidly increasing the clinical burden on account of its wide-ranging complications. This review focuses on the neuronal changes occurring in diabetes such as the impact of hyperglycemia on brain function and structure, its association with various neurological disorders, and a few diabetes-induced peripheral neuropathic changes. It is an attempt to summarize the relevant literature about neuronal consequences of DM as treatment options available today are mostly focused on achieving better glycemic control; further research on novel treatment options to prevent or delay the progression of neuronal changes is still needed.

GAD-65 antibodies in a case of HNF1A-Maturity-Onset Diabetes of the Young: Double diabetes?

Diabetes classification is not as defined as it used to be. A patient with one type of diabetes can have diagnostic criteria of another type, which may affect the course of the disease. Clinicians need to consider that when dealing with patients who do not fit the exact description of their diagnosed type of diabetes.

Autoantibody-Negative Type 1 Diabetes: A Neglected Subtype

Up to 15% of individuals with a clinical phenotype of type 1 diabetes (T1D) do not have evidence of seropositivity for pancreatic islet autoantibodies. On this basis, they are classified as nonimmune or idiopathic, and remain an understudied population, as they are excluded from T1D immunomodulatory trials. Our limited understanding of the disease aetiopathogenesis in autoantibody-negative T1D hinders our ability to improve diagnostic pathways and discover novel therapeutic agents; particularly as we progress towards an era of precision medicine. This review summarises the current understanding and challenges in studying autoantibody-negative T1D. We review the literature regarding T1D classification, and the role of autoimmunity and defects in the immunogenic pathway that may distinguish autoantibody-positive and -negative T1D.

Index60 as an additional diagnostic criterion for type 1 diabetes

AIMS/HYPOTHESIS

We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both.

METHODS

We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165].

RESULTS

Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%).

CONCLUSIONS/INTERPRETATION

Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.

Family history of type 2 diabetes and characteristics of children with newly diagnosed type 1 diabetes

AIMS/HYPOTHESIS

Shared aetiopathogenetic factors have been proposed in type 1 diabetes and type 2 diabetes and both diseases have been shown to cluster in families. Characteristics related to type 2 diabetes have been described in patients with type 1 diabetes with a positive family history of type 2 diabetes. We wanted to characterise the family history of type 2 diabetes and its possible effects on the phenotype and genotype of type 1 diabetes in affected children at diagnosis.

METHODS

A total of 4993 children under the age of 15 years with newly diagnosed type 1 diabetes from the Finnish Pediatric Diabetes Register were recruited (56.6% boys, median age of 8.2 years) for a cross-sectional, observational, population-based investigation. The family history of diabetes at diagnosis was determined by a structured questionnaire, and markers of metabolic derangement, autoantibodies and HLA class II genetics at diagnosis were analysed.

RESULTS

Two per cent of the children had an immediate family member and 36% had grandparents with type 2 diabetes. Fathers and grandfathers were affected by type 2 diabetes more often than mothers and grandmothers. The children with a positive family history for type 2 diabetes were older at the diagnosis of type 1 diabetes (p < 0.001), had higher BMI-for-age (p = 0.01) and more often tested negative for all diabetes-related autoantibodies (p = 0.02).

CONCLUSIONS/INTERPRETATION

Features associated with type 2 diabetes, such as higher body weight, older age at diagnosis and autoantibody negativity, are more frequently already present at the diagnosis of type 1 diabetes in children with a positive family history of type 2 diabetes.

Nutrition and Obesity in the Pathogenesis of Youth-Onset Type 1 Diabetes and Its Complications

Since the 1980s, there has been a dramatic rise in the prevalence of overweight and obesity in pediatric populations, in large part driven by sedentary lifestyles and changing dietary patterns with more processed foods. In parallel with the rise in pediatric obesity in the general population, the prevalence of overweight and obesity has increased among children and adolescents with type 1 diabetes. Adiposity has been implicated in a variety of mechanisms both potentiating the risk for type 1 diabetes as well as exacerbating long-term complications, particularly cardiovascular disease. Treatment options targeting the unique needs of obese pediatric patients, both before and after diagnosis of type 1 diabetes, are limited. In this review, we discuss the history of the epidemiology of the obesity epidemic in the context of pediatric type 1 diabetes, highlight the possible role of obesity in type 1 diabetes pathogenesis and review the concept of "double diabetes". The impact of obesity at and after diagnosis will be discussed, including noted differences in clinical and biochemical markers, lipid abnormalities, and long-term cardiovascular complications. Finally, we will review the existing literature on pharmacologic and nutritional interventions as potential treatment strategies for youth with coexisting type 1 diabetes and obesity.

The clinical consequences of heterogeneity within and between different diabetes types

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Management of Latent Autoimmune Diabetes in Adults: A Consensus Statement From an International Expert Panel

A substantial proportion of patients with adult-onset diabetes share features of both type 1 diabetes (T1D) and type 2 diabetes (T2D). These individuals, at diagnosis, clinically resemble T2D patients by not requiring insulin treatment, yet they have immunogenetic markers associated with T1D. Such a slowly evolving form of autoimmune diabetes, described as latent autoimmune diabetes of adults (LADA), accounts for 2-12% of all patients with adult-onset diabetes, though they show considerable variability according to their demographics and mode of ascertainment. While therapeutic strategies aim for metabolic control and preservation of residual insulin secretory capacity, endotype heterogeneity within LADA implies a personalized approach to treatment. Faced with a paucity of large-scale clinical trials in LADA, an expert panel reviewed data and delineated one therapeutic approach. Building on the 2020 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus for T2D and heterogeneity within autoimmune diabetes, we propose "deviations" for LADA from those guidelines. Within LADA, C-peptide values, proxy for β-cell function, drive therapeutic decisions. Three broad categories of random C-peptide levels were introduced by the panel: 1) C-peptide levels <0.3 nmol/L: a multiple-insulin regimen recommended as for T1D; 2) C-peptide values ≥0.3 and ≤0.7 nmol/L: defined by the panel as a "gray area" in which a modified ADA/EASD algorithm for T2D is recommended; consider insulin in combination with other therapies to modulate β-cell failure and limit diabetic complications; 3) C-peptide values >0.7 nmol/L: suggests a modified ADA/EASD algorithm as for T2D but allowing for the potentially progressive nature of LADA by monitoring C-peptide to adjust treatment. The panel concluded by advising general screening for LADA in newly diagnosed non-insulin-requiring diabetes and, importantly, that large randomized clinical trials are warranted.

Single Islet Autoantibody at Diagnosis of Clinical Type 1 Diabetes is Associated With Older Age and Insulin Resistance

CONTEXT

Multiple islet autoantibody positivity usually precedes clinical (stage 3) type 1 diabetes (T1D).

OBJECTIVE

To test the hypothesis that individuals who develop stage 3 T1D with only a single autoantibody have unique metabolic differences.

DESIGN

Cross-sectional analysis of participants in the T1D TrialNet study.

SETTING

Autoantibody-positive relatives of individuals with stage 3 T1D.

PARTICIPANTS

Autoantibody-positive relatives who developed stage 3 T1D (at median age 12.4 years, range = 1.4-58.6) and had autoantibody data close to clinical diagnosis (n = 786, 47.4% male, 79.9% non-Hispanic white).

MAIN OUTCOME MEASURES

Logistic regression modeling was used to assess relationships between autoantibody status and demographic, clinical, and metabolic characteristics, adjusting for potential confounders and correcting for multiple comparisons.

RESULTS

At diagnosis of stage 3 T1D, single autoantibody positivity, observed in 119 (15.1%) participants (72% GAD65, 13% microinsulin antibody assay, 11% insulinoma-associated antigen 2, 1% islet cell antibody, 3% autoantibodies to zinc transporter 8 [ZnT8]), was significantly associated with older age, higher C-peptide measures (fasting, area under the curve, 2-hour, and early response in oral glucose tolerance test), higher homeostatic model assessment of insulin resistance, and lower T1D Index60 (all P < 0.03). While with adjustment for age, 2-hour C-peptide remained statistically different, controlling for body mass index (BMI) attenuated the differences. Sex, race, ethnicity, human leukocyte antigen DR3-DQ2, and/or DR4-DQ8, BMI category, and glucose measures were not significantly associated with single autoantibody positivity.

CONCLUSIONS

Compared with multiple autoantibody positivity, single autoantibody at diagnosis of stage 3 T1D was associated with older age and insulin resistance possibly mediated by elevated BMI, suggesting heterogeneous disease pathogenesis. These differences are potentially relevant for T1D prevention and treatment.

Progression to hypertension in youth and young adults with type 1 or type 2 diabetes: The SEARCH for Diabetes in Youth Study

Central obesity may contribute to the development of hypertension in youths with diabetes. The SEARCH for Diabetes in Youth Study followed 1518 youths with type 1 diabetes (T1D) and 177 with type 2 diabetes (T2D) diagnosed when <20 years of age for incident hypertension. Incident hypertension was defined as blood pressure ≥95th percentile (or ≥130/80 mm Hg) or reporting antihypertensive therapy among those without hypertension at baseline. Poisson regression models were stratified by diabetes type and included demographic and clinical factors, clinical site, and waist‐to‐height ratio (WHtR). Youths with T2D were more likely to develop hypertension than those with T1D (35.6% vs 14.8%, P < .0001). For each 0.01 unit of annual increase in WHtR, adjusted relative risk for hypertension was 1.53 (95% CI 1.36‐1.73) and 1.20 (95% CI 1.00‐1.43) for youths with T1D and T2D, respectively. Effective strategies targeted toward reducing central obesity may reduce hypertension among youths with diabetes.

Excess BMI Accelerates Islet Autoimmunity in Older Children and Adolescents

OBJECTIVE

Sustained excess BMI increases the risk of type 1 diabetes (T1D) in autoantibody-positive relatives without diabetes of patients. We tested whether elevated BMI also accelerates the progression of islet autoimmunity before T1D diagnosis.

RESEARCH DESIGN AND METHODS

We studied 706 single autoantibody-positive pediatric TrialNet participants (ages 1.6-18.6 years at baseline). Cumulative excess BMI (ceBMI) was calculated for each participant based on longitudinally accumulated BMI ≥85th age- and sex-adjusted percentile. Recursive partitioning analysis and multivariable modeling defined the age cut point differentiating the risk for progression to multiple positive autoantibodies.

RESULTS

At baseline, 175 children (25%) had a BMI ≥85th percentile. ceBMI range was -9.2 to 15.6 kg/m² (median -1.91), with ceBMI ≥0 kg/m² corresponding to persistently elevated BMI ≥85th percentile. Younger age increased the progression to multiple autoantibodies, with age cutoff of 9 years defined by recursive partitioning analysis. Although ceBMI was not significantly associated with progression from single to multiple autoantibodies overall, there was an interaction with ceBMI ≥0 kg/m², age, and HLA (P = 0.009). Among children ≥9 years old without HLA DR3-DQ2 and DR4-DQ8, ceBMI ≥0 kg/m² increased the rate of progression from single to multiple positive autoantibodies (hazard ratio 7.32, P = 0.004) and conferred a risk similar to that in those with T1D-associated HLA haplotypes. In participants <9 years old, the effect of ceBMI on progression to multiple autoantibodies was not significant regardless of HLA type.

CONCLUSIONS

These data support that elevated BMI may exacerbate islet autoimmunity prior to clinical T1D, particularly in children with lower risk based on age and HLA. Interventions to maintain normal BMI may prevent or delay the progression of islet autoimmunity.

A highly sensitive red-emitting probe for the detection of viscosity changes in living cells, zebrafish, and human blood samples

Intracellular viscosity can be measured to reflect the state of living cells. Fluorescent probes are powerful tools for viscosity detection in vivo.