Challenges in the diagnosis of diabetes type in pediatrics

Inaccurate diagnosis of diabetes type in youth: prevalence, characteristics, and implications

Classifying diabetes at diagnosis is crucial for disease management but increasingly difficult due to overlaps in characteristics between the commonly encountered diabetes types. We evaluated the prevalence and characteristics of youth with diabetes type that was unknown at diagnosis or was revised over time. We studied 2073 youth with new-onset diabetes (median age [IQR] = 11.4 [6.2] years; 50% male; 75% White, 21% Black, 4% other race; overall, 37% Hispanic) and compared youth with unknown versus known diabetes type, per pediatric endocrinologist diagnosis. In a longitudinal subcohort of patients with data for ≥ 3 years post-diabetes diagnosis (n = 1019), we compared youth with steady versus reclassified diabetes type. In the entire cohort, after adjustment for confounders, diabetes type was unknown in 62 youth (3%), associated with older age, negative IA-2 autoantibody, lower C-peptide, and no diabetic ketoacidosis (all, p < 0.05). In the longitudinal subcohort, diabetes type was reclassified in 35 youth (3.4%); this was not statistically associated with any single characteristic. In sum, among racially/ethnically diverse youth with diabetes, 6.4% had inaccurate diabetes classification at diagnosis. Further research is warranted to improve accurate diagnosis of pediatric diabetes type.

Global, regional, and national burden of type 1 diabetes in adolescents and young adults

BACKGROUND

Type 1 diabetes (T1D) incidence in adolescents varies widely, but has increased globally in recent years. This study reports T1D burden among adolescents and young adults aged 10-24-year-old age group at global, regional, and national levels.

METHODS

Based on the Global Burden of Disease Study 2019, we described the burden of T1D in the 10-24-year-old age group. We further analyzed these trends by age, sex, and the Social Development Index. Joinpoint regression analysis was used to assess temporal trends.

RESULTS

T1D incidence among adolescents and young adults increased from 7·78 per 100,000 population (95% UI, 5·27-10·60) in 1990 to 11·07 per 100,000 population (95% UI, 7·42-15·34) in 2019. T1D mortality increased from 5701·19 (95% UI, 4642·70-6444·08) in 1990 to 6,123·04 (95% UI, 5321·82-6887·08) in 2019, representing a 7·40% increase in mortality. The European region had the highest T1D incidence in 2019. Middle-SDI countries exhibited the largest increase in T1D incidence between 1990 and 2019.

CONCLUSION

T1D is a growing health concern globally, and T1D burden more heavily affects countries with low SDI. Specific measures and effective collaboration among countries with different SDIs are required to improve diabetes care in adolescents.

IMPACT

We assessed trends in T1D incidence and burden among youth in the 10-24-year-old age group by evaluating data from the Global Burden of Disease Study 2019. Our results demonstrated that global T1D incidence in this age group increased over the past 30 years, with the European region having the highest T1D incidence. Specific measures and effective collaboration among countries with different SDIs are required to improve diabetes care in adolescents.

Diabetes Study of Children of Diverse Ethnicity and Race: Study design

AIMS

Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth.

MATERIALS AND METHODS

The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model.

RESULTS

The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis.

CONCLUSIONS

Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Plasma amino acid signatures define types of pediatric diabetes

BACKGROUND & AIMS

Metabolic biomarkers with pathophysiological relevance is lacking in pediatric diabetes. We aimed to identify novel metabolic biomarkers in pediatric type 1 (T1D) and type 2 diabetes (T2D). We hypothesized that (1) targeted plasma metabolomics, focused on plasma amino acid concentrations, could identify distinctively altered patterns in children with T1D or T2D, and (2) there are specific changes in concentrations of metabolites related to branch chain amino acids (BCAA) and arginine metabolism in children with T2D.

METHODS

In a pilot study, we enrolled children with T1D (n = 15) and T2D (n = 13), and healthy controls (n = 15). Fasting plasma amino acid concentrations were measured by ultra-performance liquid chromatography, and compared between the groups after adjustment for confounding factors.

RESULTS

The mean age (SD) of participants was 16.4 (0.9) years. There were no group differences in age, gender, race/ethnicity, or 24-h protein intake. Mean BMI percentile was higher in the T2D than the T1D group or controls (p < 0.001). The T2D group had lower arginine, citrulline, glutamine, glycine, phenylalanine, methionine, threonine, asparagine and symmetric dimethylarginine (SDMA) but higher aspartate than controls, after adjusting for BMI percentiles (all p < 0.05). Children with T2D also had lower glycine but higher ornithine, proline, leucine, isoleucine, valine, total BCAA, lysine and tyrosine than those with T1D after adjusting for confounding factors (all p < 0.05). Children with T1D had lower phenylalanine, methionine, threonine, glutamine, tyrosine, asymmetric dimethylarginine (ADMA) and SDMA than controls (all p < 0.05).

CONCLUSIONS

Children with T2D and T1D have distinct fasting plasma amino acid signatures that suggest varying pathogenic mechanisms and could serve as biomarkers for these conditions.

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.

Severe multiple organ failure as a consequence of diabetic ketoacidosis in an adolescent with new-onset type 1 diabetes: A case report

The initial presentation of pediatric diabetes is variable, making prompt diagnosis and treatment challenging. The overlap between type 1 and type 2 diabetes and presence of developmental delays can complicate diagnosis, resulting in delays and severe illness at presentation. Here we describe a case of a 13-year-old male with autism and attention deficit hyperactivity disorder who presented with severe diabetic ketoacidosis, multiple organ failure, and shock. Within 2 weeks of this initial presentation, he had further clinical decompensation due to an intestinal perforation. Cultures from resected gastrointestinal tissue grew mucormycosis, protracting his hospital stay and recovery. He was able to go home several months later with remarkable improvement. This case highlights the necessity of careful history taking and early testing, and how investigation for rare complications of diabetes is vital when patients do not improve as expected.

Imprecise Diagnosis of Diabetes Type in Youth: Prevalence, Characteristics, and Implications

Classifying diabetes at diagnosis is crucial for disease management but increasingly difficult due to overlaps in characteristics between the commonly encountered diabetes types. We evaluated the prevalence and characteristics of youth with diabetes type that was unknown at diagnosis or was revised over time. We studied 2073 youth with new-onset diabetes (median age [IQR]=11.4 [6.2] years; 50% male; 75% White, 21% Black, 4% other race; overall, 37% Hispanic) and compared youth with unknown versus known diabetes type, per pediatric endocrinologist diagnosis. In a longitudinal subcohort of patients with data for ≥3 years post-diabetes diagnosis (n=1019), we compared youth with unchanged versus changed diabetes classification. In the entire cohort, after adjustment for confounders, diabetes type was unknown in 62 youth (3%), associated with older age, negative IA-2 autoantibody, lower C-peptide, and no diabetic ketoacidosis (all, p<0.05). In the longitudinal subcohort, diabetes classification changed in 35 youth (3.4%); this was not statistically associated with any single characteristic. Having unknown or revised diabetes type was associated with less continuous glucose monitor use on follow-up (both, p<0.004). In sum, among racially/ethnically diverse youth with diabetes, 6.5% had imprecise diabetes classification at diagnosis. Further research is warranted to improve accurate diagnosis of pediatric diabetes type.

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.

Diabetes of Unclear Type in an Adolescent Boy With Multiple Islet-cell Autoantibody Positivity Successfully Managed With Glucagon-like Peptide-1 Receptor Agonist Alone: A Case Report

Diabetes classification has traditionally considered type 1 and type 2 diabetes as 2 separate entities with different pathogenic mechanisms. However, clinicians and researchers see increasingly more exceptions to this conventional paradigm, leading to a concept of mixed phenotypes in diabetes classification. Herein we report the case of an adolescent with unclear diabetes type due to the presence of obesity, robust endogenous insulin production, multiple islet autoantibody positivity and severe hyperglycemia at diabetes diagnosis that has been successfully treated with liraglutide therapy alone. Our case report highlights the difficulty of diabetes classification and subsequent need for personalized medicine with regard to diabetes management.

Optimizing maturity-onset diabetes of the young detection in a pediatric diabetes population

INTRODUCTION

Maturity-onset diabetes of the young (MODY) is often misdiagnosed as type 1/type 2 diabetes. We aimed to define patient characteristics to guide the decision to test for MODY in youth with diabetes.

RESEARCH DESIGN AND METHODS

Of 4750 patients enrolled in the Diabetes Registry at Texas Children's Hospital between July 2016 and July 2019, we selected ("Study Cohort", n = 350) those with: (1) diabetes diagnosis <25 years, (2) family history of diabetes in three consecutive generations, and (3) absent islet autoantibodies except for GAD65. We retrospectively studied their clinical and biochemical characteristics and available MODY testing results. Cluster analysis was then performed to identify the cluster with highest rate of MODY diagnosis.

RESULTS

Patients in the Study Cohort were 3.5 times more likely to have been diagnosed with MODY than in the overall Diabetes Registry (4.6% vs. 1.3%, p < 0.001). The cluster (n = 16) with the highest rate of clinician-diagnosed MODY (25%, n = 4/16) had the lowest age (10.9 ± 2.5 year), BMI-z score (0.5 ± 0.9), C-peptide level (1.5 ± 1.2 ng/ml) and acanthosis nigricans frequency (12.5%) at diabetes diagnosis (all p < 0.05). In this cluster, three out of five patients who underwent MODY genetic testing had a pathogenic variant.

CONCLUSIONS

Using a stepwise approach, we identified that younger age, lower BMI, lower C-peptide, and absence of acanthosis nigricans increase likelihood of MODY in racially/ethnically diverse children with diabetes who have a multigenerational family history of diabetes and negative islet autoantibodies, and can be used by clinicians to select patients for MODY testing.

Demographic and diagnostic markers in new onset pediatric type 1 and type 2 diabetes: differences and overlaps

PURPOSE

Type 1 diabetes (T1D) is the most common type of diabetes in children, but the frequency of type 2 diabetes (T2D) is increasing rapidly. Classification of diabetes is based on a constellation of features that vary by type. We aimed to compare demographic, clinical, and laboratory characteristics at diagnosis of pediatric T1D and T2D.

METHODS

We studied children who visited a large academic hospital in Houston, Texas (USA) with a new diagnosis of T2D (n=753) or T1D (n=758). We compared age, sex, race/ethnicity, presence of obesity, glucose, hemoglobin A1c, islet autoantibody positivity, C-peptide, and presence of diabetic ketoacidosis (DKA) at diabetes diagnosis.

RESULTS

At diagnosis, children with T2D, compared with those with T1D, were older (13.6 years vs. 9.7 years), more likely female (63.2% vs. 47.8%), of racial/ethnic minority (91.1% vs. 42.3%), and obese (90.9% vs. 19.4%) and were less likely to have DKA (7.8% vs. 35.0%) and diabetes autoantibodies (5.5% vs. 95.4%). Children with T2D also had significantly lower glucose, lower hemoglobin A1c and lower C-peptide level (all comparisons, p<0.0001). In multiple logistic regression analysis, older age, racial/ethnic minority, obesity, higher C-peptide, and negative islet autoantibodies were independently associated with T2D (all, p<0.05), while sex, glucose, hemoglobin A1c, and DKA were not (model p<0.0001).

CONCLUSION

There are important demographic, clinical, and laboratory differences between T1D and T2D in children. However, none of the characteristics were unique to either diabetes type, which poses challenges to diabetes classification at diagnosis.

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.

Type 2 diabetes in pediatrics

Type 2 diabetes (T2D) in adolescents has become an increasing health concern throughout the world and its prevention and screening should be implemented in pediatric care. As clinical features at presentation, in some cases can be similar to type 1 diabetes and family history can be in favour of a monogenic form of diabetes, it is pivotal for physicians to be aware of youth-onset T2D specificities to ensure an accurate diagnosis. The global increase of overweight and obesity can complicate the diagnostic process and makes it essential to apply a systematic approach to each new diagnosis. Microvascular complications may be present at the time of diagnosis and chronic complications are frequent and need to be screened regularly. Regular screening of comorbidities should also be performed. Childhood T2D should be followed up by pediatric diabetes units to avoid diagnostic errors and delay in care. A multidisciplinary approach, by an experienced team, is pivotal to provide treatment options targeting the unique needs of pediatric patients. Treatment programs must include the whole family and address all the aspects of the care (lifestyle, pharmacological therapy, psychological aspects, complications and comorbidities). An organized process of transition to adult care is essential.

The accuracy of provider diagnosed diabetes type in youth compared to an etiologic criteria in the SEARCH for Diabetes in Youth Study

BACKGROUND

Although surveillance for diabetes in youth relies on provider-assigned diabetes type from medical records, its accuracy compared to an etiologic definition is unknown.

METHODS

Using the SEARCH for Diabetes in Youth Registry, we evaluated the validity and accuracy of provider-assigned diabetes type abstracted from medical records against etiologic criteria that included the presence of diabetes autoantibodies (DAA) and insulin sensitivity. Youth who were incident for diabetes in 2002-2006, 2008, or 2012 and had complete data on key analysis variables were included (n = 4001, 85% provider diagnosed type 1). The etiologic definition for type 1 diabetes was ≥1 positive DAA titer(s) or negative DAA titers in the presence of insulin sensitivity and for type 2 diabetes was negative DAA titers in the presence of insulin resistance.

RESULTS

Provider diagnosed diabetes type correctly agreed with the etiologic definition of type for 89.9% of cases. Provider diagnosed type 1 diabetes was 96.9% sensitive, 82.8% specific, had a positive predictive value (PPV) of 97.0% and a negative predictive value (NPV) of 82.7%. Provider diagnosed type 2 diabetes was 82.8% sensitive, 96.9% specific, had a PPV and NPV of 82.7% and 97.0%, respectively.

CONCLUSION

Provider diagnosis of diabetes type agreed with etiologic criteria for 90% of the cases. While the sensitivity and PPV were high for youth with type 1 diabetes, the lower sensitivity and PPV for type 2 diabetes highlights the value of DAA testing and assessment of insulin sensitivity status to ensure estimates are not biased by misclassification.