Type 2 diabetes in prepubertal children

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.

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.

Impact of Preparative Isolation of C-Glycosylflavones Derived from Dianthus superbus on In Vitro Glucose Metabolism

Dianthus superbus L. has been extensively studied for its potential medicinal properties in traditional Chinese medicine and is often consumed as a tea by traditional folk. It has the potential to be exploited in the treatment of inflammation, immunological disorders, and diabetic nephropathy. Based on previous studies, this study continued the separation of another subfraction of Dianthus superbus and established reversed-phase/reversed-phase and reversed-phase/hydrophilic (RPLC) two-dimensional (2D) high-performance liquid chromatography (HPLC) modes, quickly separating two C-glycosylflavones, among which 2″-O-rhamnosyllutonarin was a new compound and isomer with 6‴-O-rhamnosyllutonarin. This is the first study to investigate the effects of 2″-O-rhamnosyllutonarin and 6‴-O-rhamnosyllutonarin on cellular glucose metabolism in vitro. First, molecular docking was used to examine the effects of 2″-O-rhamnosyllutonarin and 6″-O-rhamnosyllutonarin on AKT and AMPK; these two compounds exhibited relatively high activity. Following this, based on the HepG2 cell model of insulin resistance, it was proved that both of the 2″-O-rhamnosyllutonarin and 6‴-O-rhamnosyllutonarin demonstrated substantial efficacy in ameliorating insulin resistance and were found to be non-toxic. Simultaneously, it is expected that the methods developed in this study will provide a basis for future studies concerning the separation and pharmacological effects of C-glycosyl flavonoids.

Approach to the Patient: Youth-Onset Type 2 Diabetes

Youth-onset type 2 diabetes is a growing epidemic with a rising incidence worldwide. Although the pathogenesis and diagnosis of youth-onset type 2 diabetes are similar to adult-onset type 2 diabetes, youth-onset type 2 diabetes is unique, with greater insulin resistance, insulin hypersecretion, and faster progression of pancreatic beta cell function decline. Individuals with youth-onset type 2 diabetes also develop complications at higher rates within short periods of time compared to adults with type 2 diabetes or youth with type 1 diabetes. The highest prevalence and incidence of youth-onset type 2 diabetes in the United States is among youth from minoritized racial and ethnic groups. Risk factors include obesity, family history of type 2 diabetes, comorbid conditions and use of medications associated with insulin resistance and rapid weight gain, socioeconomic and environmental stressors, and birth history of small-for-gestational-age or pregnancy associated with gestational or pregestational diabetes. Patients with youth-onset type 2 diabetes should be treated using a multidisciplinary model with frequent clinic visits and emphasis on addressing of social and psychological barriers to care and glycemic control, as well as close monitoring for comorbidities and complications. Intensive health behavior therapy is an important component of treatment, in addition to medical management, both of which should be initiated at the diagnosis of type 2 diabetes. There are limited but growing pharmacologic treatment options, including metformin, insulin, glucagon-like peptide 1 receptor agonists, and sodium-glucose cotransporter 2 inhibitors. Although long-term outcomes are not fully known, metabolic/bariatric surgery in youth with type 2 diabetes has led to improved cardiometabolic outcomes.

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.

Characteristics of Type 2 Diabetes in Female and Male Youth

The incidence of type 2 diabetes in children is rising and carries a worse prognosis than in adults. The influence of sex on pediatric type 2 diabetes outcomes has not been well investigated. We studied 715 youth with type 2 diabetes diagnosed at a median age of 13.7 years and compared sex differences in demographic, clinical, and laboratory characteristics within the first year of diagnosis. Females diagnosed with type 2 diabetes were younger and at a higher stage of pubertal development than males, yet presented with lower A1Cs, a lower prevalence of diabetic ketoacidosis, and higher HDL cholesterol levels.

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.

Pediatric Obesity: Complications and Current Day Management

Obesity affects approximately 1 in 5 youth globally and increases the risk of complications during adolescence and young adulthood, including type 2 diabetes, dyslipidemia, hypertension, non-alcoholic fatty liver disease, obstructive sleep apnea, and polycystic ovary syndrome. Children and adolescents with obesity frequently experience weight stigma and have an impaired quality of life, which may exacerbate weight gain. Pediatric obesity is typically defined using sex-, age-, and population-specific body mass index percentiles. Once identified, pediatric obesity should always be managed with lifestyle modification. However, adolescents with obesity may also benefit from anti-obesity medications (AOM), several of which have been approved for use in adolescents by the US Food and Drug Administration, including liraglutide, phentermine/topiramate, and semaglutide. For children with specific, rare monogenic obesity disorders, setmelanotide is available and may lead to significant weight loss. Metabolic and bariatric surgery may be used for the management of severe obesity in youth; though highly effective, it is limited to specialized centers and has had relatively low pediatric uptake. In this narrative review using pediatric-focused data from original research, reviews, clinical practice guidelines, governmental agencies, and pharmaceutical companies, we review obesity-related metabolic complications in youth and management strategies, including AOM and bariatric surgery.

Clinical Characterization of Data-Driven Diabetes Clusters of Pediatric Type 2 Diabetes

Background

Pediatric Type 2 diabetes (T2D) is highly heterogeneous. Previous reports on adult-onset diabetes demonstrated the existence of diabetes clusters. Therefore, we set out to identify unique diabetes subgroups with distinct characteristics among youth with T2D using commonly available demographic, clinical, and biochemical data.

Methods

We performed data-driven cluster analysis (K-prototypes clustering) to characterize diabetes subtypes in pediatrics using a dataset with 722 children and adolescents with autoantibody-negative T2D. The six variables included in our analysis were sex, race/ethnicity, age, BMI Z-score and hemoglobin A1c at the time of diagnosis, and non-HDL cholesterol within first year of diagnosis.

Results

We identified five distinct clusters of pediatric T2D, with different features, treatment regimens and risk of diabetes complications: Cluster 1 was characterized by higher A1c; Cluster 2, by higher non-HDL; Cluster 3, by lower age at diagnosis and lower A1c; Cluster 4, by lower BMI and higher A1c; and Cluster 5, by lower A1c and higher age. Youth in Cluster 1 had the highest rate of diabetic ketoacidosis (DKA) (p = 0.0001) and were most prescribed metformin (p = 0.06). Those in Cluster 2 were most prone to polycystic ovarian syndrome (p = 0.001). Younger individuals with lowest family history of diabetes were least frequently diagnosed with diabetic ketoacidosis (p = 0.001) and microalbuminuria (p = 0.06). Low-BMI individuals with higher A1c had the lowest prevalence of acanthosis nigricans (p = 0.0003) and hypertension (p = 0.03).

Conclusions

Utilizing clinical measures gathered at the time of diabetes diagnosis can be used to identify subgroups of pediatric T2D with prognostic value. Consequently, this advancement contributes to the progression and wider implementation of precision medicine in diabetes management.

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.

Enrollment of underrepresented racial and ethnic groups in the Rare and Atypical Diabetes Network (RADIANT)

Introduction

Diabetes mellitus in underrepresented racial and ethnic groups (URG) is rapidly increasing in incidence and has worse outcomes than diabetes in non-Hispanic White individuals. Rare and Atypical Diabetes Network (RADIANT) established recruitment targets based on the racial and ethnic distribution of the USA to enroll a diverse study population. We examined participation of URG across RADIANT study stages and described strategies to enhance recruitment and retention of URG.

Materials and Methods

RADIANT is a multicenter NIH-funded study of people with uncharacterized forms of atypical diabetes. RADIANT participants consent online and progress through three sequential study stages, as eligible.

Results

We enrolled 601 participants with mean age 44 ± 16.8 years, 64.4% female. At Stage 1, 80.6% were White, 7.2% African American (AA), 12.2% other/more than one race, and 8.4% Hispanic. Enrollment of URG was significantly below preset targets across most stages. Referral sources differed by race (p < 0.001) but not ethnicity (p = 0.15). Most AA participants were referred by RADIANT investigators (58.5% vs. 24.5% in Whites), whereas flyers, news, social media, and family or friends were more frequent referral sources for White individuals (26.4% vs. 12.2% in AA). Ongoing initiatives to increase enrollment of URG in RADIANT include engaging with clinics/hospitals serving URG, screening electronic medical records, and providing culturally competent study coordination and targeted advertisement.

Conclusions

There is low participation of URG in RADIANT, potentially limiting the generalizability of its discoveries. Investigations into barriers and facilitators for recruitment and retention of URG in RADIANT, with implications for other studies, are ongoing.

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.

A Novel Approach of Determining the Risks for the Development of Hyperinsulinemia in the Children and Adolescent Population Using Radial Basis Function and Support Vector Machine Learning Algorithm

Hyperinsulinemia is a condition with extremely high levels of insulin in the blood. Various factors can lead to hyperinsulinemia in children and adolescents. Puberty is a period of significant change in children and adolescents. They do not have to have explicit symptoms for prediabetes, and certain health indicators may indicate a risk of developing this problem. The scientific study is designed as a cross-sectional study. In total, 674 children and adolescents of school age from 12 to 17 years old participated in the research. They received a recommendation from a pediatrician to do an OGTT (Oral Glucose Tolerance test) with insulinemia at a regular systematic examination. In addition to factor analysis, the study of the influence of individual factors was tested using RBF (Radial Basis Function) and SVM (Support Vector Machine) algorithm. The obtained results indicated statistically significant differences in the values of the monitored variables between the experimental and control groups. The obtained results showed that the number of adolescents at risk is increasing, and, in the presented research, it was 17.4%. Factor analysis and verification of the SVM algorithm changed the percentage of each risk factor. In addition, unlike previous research, three groups of children and adolescents at low, medium, and high risk were identified. The degree of risk can be of great diagnostic value for adopting corrective measures to prevent this problem and developing potential complications, primarily type 2 diabetes mellitus, cardiovascular disease, and other mass non-communicable diseases. The SVM algorithm is expected to determine the most accurate and reliable influence of risk factors. Using factor analysis and verification using the SVM algorithm, they significantly indicate an accurate, precise, and timely identification of children and adolescents at risk of hyperinsulinemia, which is of great importance for improving their health potential, and the health of society as a whole.

Pediatric Diabetes on the Rise: Trends in Incident Diabetes During the COVID-19 Pandemic

Context

The effects of the coronavirus disease 2019 (COVID-19) pandemic on the incident cases of pediatric type 1 diabetes (T1D) and type 2 diabetes (T2D) are not clear.

Objective

To identify trends in incidence and presentation of pediatric new-onset T1D and T2D during the COVID-19 pandemic.

Methods

A retrospective chart review was conducted. Demographics, anthropometrics, and initial laboratory results from patients ages 0 through 21 years who presented with new-onset diabetes to a pediatric tertiary care center were recorded.

Results

During the pandemic, incident cases of pediatric T1D increased from 31 in each of the prior 2 years to 46; an increase of 48%. Incident cases of pediatric T2D increased by 231% from 2019 to 2020. The number of incident cases of pediatric T2D increased significantly more than the number of incident cases of pediatric T1D (P = 0.009). Patients with T2D were more likely to present in diabetic ketoacidosis (DKA), though this was not statistically significant (P = 0.093). Severe DKA was higher compared with moderate DKA (P = 0.036) in incident cases of pediatric T2D. During the pandemic, for the first time, incident cases of T2D accounted for more than one-half of all newly diagnosed pediatric diabetes cases (53%).

Conclusions

There were more incident pediatric T1D and T2D cases as well as an increase in DKA severity in T2D at presentation during the COVID-19 pandemic. More importantly, incident T2D cases were higher than the incident T1D during the pandemic. This clearly suggests a disruption and change in the pediatric diabetes trends with profound individual and community health consequences.

Spectrum of Phenotypes and Causes of Type 2 Diabetes in Children

Several factors, including genetics, family history, diet, physical activity, obesity, and insulin resistance in puberty, appear to increase the risk of type 2 diabetes in youth. Youth-onset type 2 diabetes is often thought of as a single entity but rather exists as a spectrum of disease with differences in presentation, metabolic characteristics, clinical progression, and complication rates. We review what is currently known regarding the risks associated with developing type 2 diabetes in youth. Additionally, we focus on the spectrum of phenotypes of pediatric type 2 diabetes, discuss the pathogenic underpinnings and potential therapeutic relevance of this heterogeneity, and compare youth-onset type 2 diabetes with type 1 diabetes and adult-onset type 2 diabetes. Finally, we highlight knowledge gaps in prediction and prevention of youth-onset type 2 diabetes.

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.