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OBJECTIVE Maturity-onset diabetes of the young (MODY) is frequently misdiagnosed as type 1 or type 2 diabetes. Correct diagnosis may result in a change in clinical treatment and impacts prediction of complications and familial risk. In this study, we aimed to assess the prevalence of MODY in multiethnic youth under age 20 years with a clinical diagnosis of type 2 diabetes. RESEARCH DESIGN AND METHODS We evaluated whole-exome sequence data of youth with a clinical diagnosis of type 2 diabetes. We considered participants to have MODY if they carried a MODY gene variant classified as likely pathogenic (LP) or pathogenic (P) according to current guidelines. RESULTS Of 3,333 participants, 93 (2.8%) carried an LP/P variant in HNF4A (16 participants), GCK (23), HNF1A (44), PDX1 (5), INS (4), and CEL (1). Compared with those with no LP/P variants, youth with MODY had a younger age at diagnosis (12.9 ± 2.5 vs. 13.6 ± 2.3 years, P = 0.002) and lower fasting C-peptide levels (3.0 ± 1.7 vs. 4.7 ± 3.5 ng/mL, P < 0.0001). Youth with MODY were less likely to have hypertension (6.9% vs. 19.5%, P = 0.007) and had higher HDL cholesterol (43.8 vs. 39.7 mg/dL, P = 0.006). CONCLUSIONS By comprehensively sequencing the coding regions of all MODY genes, we identified MODY in 2.8% of youth with clinically diagnosed type 2 diabetes; importantly, in 89% (n = 83) the specific diagnosis would have changed clinical management. No clinical criterion reliably separated the two groups. New tools are needed to find ideal criteria for selection of individuals for genetic testing.

The prevalence of type 2 diabetes in youth has increased substantially, yet the genetic underpinnings remain largely unexplored. To identify genetic variants predisposing to youth-onset type 2 diabetes, we formed ProDiGY, a multiethnic collaboration of three studies (TODAY, SEARCH, and T2D-GENES) with 3,006 youth case subjects with type 2 diabetes (mean age 15.1 ± 2.9 years) and 6,061 diabetes-free adult control subjects (mean age 54.2 ± 12.4 years). After stratifying by principal component–clustered ethnicity, we performed association analyses on ∼10 million imputed variants using a generalized linear mixed model incorporating a genetic relationship matrix to account for population structure and adjusting for sex. We identified seven genome-wide significant loci, including the novel locus rs10992863 in PHF2 (P = 3.2 × 10−8; odds ratio [OR] = 1.23). Known loci identified in our analysis include rs7903146 in TCF7L2 (P = 8.0 × 10−20; OR 1.58), rs72982988 near MC4R (P = 4.4 × 10−14; OR 1.53), rs200893788 in CDC123 (P = 1.1 × 10−12; OR 1.32), rs2237892 in KCNQ1 (P = 4.8 × 10−11; OR 1.59), rs937589119 in IGF2BP2 (P = 3.1 × 10−9; OR 1.34), and rs113748381 in SLC16A11 (P = 4.1 × 10−8; OR 1.04). Secondary analysis with 856 diabetes-free youth control subjects uncovered an additional locus in CPEB2 (P = 3.2 × 10−8; OR 2.1) and consistent direction of effect for diabetes risk. In conclusion, we identified both known and novel loci in the first genome-wide association study of youth-onset type 2 diabetes.

Context There is substantial heterogeneity in insulin sensitivity, and genetics may suggest possible mechanisms by which common variants influence this trait. Objectives We aimed to evaluate an 11-variant polygenic lipodystrophy genetic risk score (GRS) for association with anthropometric, glycemic and metabolic traits in the Diabetes Prevention Program (DPP). In secondary analyses, we tested the association of the GRS with cardiovascular risk factors in the DPP. Design In 2713 DPP participants, we evaluated a validated GRS of 11 common variants associated with fasting insulin-based measures of insulin sensitivity discovered through genome-wide association studies that cluster with a metabolic profile of lipodystrophy, conferring high metabolic risk despite low body mass index (BMI). Results At baseline, a higher polygenic lipodystrophy GRS was associated with lower weight, BMI, and waist circumference measurements, but with worse insulin sensitivity index (ISI) values. Despite starting at a lower weight and BMI, a higher GRS was associated with less weight and BMI reduction at one year and less improvement in ISI after adjusting for baseline values but was not associated with diabetes incidence. A higher GRS was also associated with more atherogenic low-density lipoprotein peak-particle-density at baseline but was not associated with coronary artery calcium scores in the Diabetes Prevention Program Outcomes Study. Conclusions In the DPP, a higher polygenic lipodystrophy GRS for insulin resistance with lower BMI was associated with diminished improvement in insulin sensitivity and potential higher cardiovascular disease risk. This GRS helps characterize insulin resistance in a cohort of individuals at high risk for diabetes, independent of adiposity.

Objective: Real-time continuous glucose monitoring (CGM) is effective for diabetes management in T1D and adults with T2D, but has not been assessed in youth with T2D. The objective of this study was to assess the feasibility and acceptability of CGM use in youth with T2D. Methods: Youth (13- 21 years old) with T2D ≥ 6 months and A1c > 7%, on any FDA approved treatment regimen were included. After a blinded run-in period, participants were given a Dexcom G6 CGM system for 12 weeks. The use and acceptability of the real-time CGM were evaluated by sensor usage, surveys, and focus group qualitative data. Results: Youth (n=8) had median age 19.4 (IQR 15.5-20.6) years, were 75% female, 50% hispanic/latino ethnicity, 50% non-English speaking at home, and 91% had public insurance. Baseline A1c was 11.7 (±2.8)% with mean diabetes duration of 2.5 (IQR 1.4 - 5.1) years and 75% were on basal insulin. Of the 7 participants who have completed the CGM intervention, all reported CGM was a positive experience (50% very positive, 50% slightly positive), easy to use (50% very easy, 50% easy), and useful (83% useful, 17% useful). All participants desired to continue to use real-time CGM in the future. 85% were “extremely” likely to recommend real-time CGM to friends. 67% of participants self-reported eating fewer meals while using CGM. All participants used sensors for the duration of the study. Conclusion: Real-time CGM is feasible and acceptable for youth with type 2 diabetes. Larger randomized controlled trials are needed to assess effects on glycemic control, healthy lifestyle changes, and diabetes distress. Disclosure H. Chesser: None. S. Srinivasan: None. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.

Youth-onset type 2 diabetes (T2D) has a strong genetic predisposition and is regarded as a phenotypic extreme of adult-onset T2D. In this study, we aimed to investigate the contribution of rare coding variants to the genetic basis of youth-onset T2D by analyzing whole-exome sequences of 3,005 persons with youth-onset T2D (diagnosed before 20 years of age) from the Progress in Diabetes Genetics in Youth (ProDiGY) consortium and 9,777 ancestry matched adult controls. We identified three genes with aggregate rare variant associations reaching exome-wide significance (P Disclosure S. Kwak: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. E. M. Isganaitis: None. M. W. Haymond: Advisory Panel; Self; Daiichi Sankyo, Zealand Pharma A/S, Other Relationship; Self; AstraZeneca, Stock/Shareholder; Self; Xeris Pharmaceuticals, Inc. L. L. Levitsky: Consultant; Self; Eli Lilly and Company. T. I. Pollin: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. J. Flannick: None. On behalf of the prodigy consortium: n/a. S. Srinivasan: None. L. Chen: None. J. Todd: None. E. T. Jensen: None. J. Divers: None. A. K. Mottl: Advisory Panel; Self; Bayer U. S. C. Pihoker: None. R. Gandica: None. Funding National Institutes of Health (1R01DK125490-01)

Polygenic scores (PS) of T2D genetic variants based on pathophysiologic mechanisms underlying diabetes have been developed. We investigated whether T2D cluster PS influences response to interventions for diabetes prevention. We examined 2,647 DPP participants with impaired glucose tolerance and genetic data randomized to intensive lifestyle, metformin or placebo arms for diabetes prevention. We generated five PS clusters including β-cell related clusters (β-cell, proinsulin) and insulin resistance clusters (liver/lipid, obesity, lipodystrophy). We examined associations of PS with baseline and 1-year glycemic traits after intervention derived from oral glucose tolerance tests using general linear models, and with diabetes incidence over an average period of 3 years using Cox Regression Models. Models were adjusted for sex, age, and 10 principal components, respective baseline trait, and treatment group. At one-year follow-up, β-cell PS was associated with reduction in the insulinogenic index and corrected insulin response, in each treatment group and, statistically significant, in all combined (P We conclude that high genetic burden in β-cell cluster PS is associated with greater risk of diabetes and a decrease in insulin secretion, seen across all treatment groups. Despite interventions with intensive lifestyle and metformin, participants with high β-cell cluster genetic burden had an increased risk of diabetes and worsening in insulin secretion similar to placebo group. These data suggest that alternate therapies may be needed to prevent β-cell decline in this subset of prediabetes patients. Disclosure L. K. Billings: Advisory Panel; Self; Bayer Inc., Lilly Diabetes, Novo Nordisk, Sanofi. S. Raghavan: None. S. Srinivasan: None. J. Xu: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. M. Udler: None. D. Research group: None. K. A. Jablonski: None. P. W. Franks: Advisory Panel; Self; Zoe Global Limited, Consultant; Self; Eli Lilly and Company, Novo Nordisk. R. B. Goldberg: None. M. Hivert: None. S. E. Kahn: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. W. C. Knowler: None. C. Lee: None. J. Merino: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK048489)

Context Dyslipidemia is highly prevalent in youth with type 2 diabetes (T2D), yet the pathogenic components of dyslipidemia in youth with T2D are poorly understood. Objective To evaluate the genetic determinants of lipid traits in youth with T2D through a genome-wide association study. Design, Participants, and Main Outcome Measures We genotyped 206 928 variants and imputed 17 642 824 variants in 1076 youth (mean age 15.0 ± 2.48 years) with T2D from the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) and SEARCH for Diabetes in Youth (SEARCH) studies as part of the Progress in Diabetes Genetics in Youth (ProDiGY) consortium. We performed association testing for triglyceride and low-density lipoprotein cholesterol and high-density lipoprotein cholesterol (HDL-c) concentrations adjusted for the genetic relationship matrix within each substudy followed by meta-analyses for each trait. Results We identified a novel association between a deletion on chromosome 3 (3:67817380_AT/A_Deletion:RP11-81N13.1) and triglyceride levels at genome-wide level of significance (P = 2.3 × 10−8) with each risk allele increasing triglycerides by 20%. We also identified a genome-wide significant signal at rs247617 (P = 5.1 × 10−9) between HERFUD1 and CETP associated with HDL-c, with carriers of 1 copy of the risk allele having twice higher HDL-c. Conclusions Our genetic analyses of lipid traits in youth with T2D have identified 1 novel and 1 previously known locus. Additional studies are needed to further characterize the genetic architecture of dyslipidemia in youth with T2D.

The prevalence of type 2 diabetes in childhood is increasing, largely due to the obesity epidemic in youth. Recent research has found that young adults who developed type 2 diabetes as children have alarmingly high rates of diabetes complications affecting the kidneys, eyes, heart, nerves, and adversely affecting pregnancy outcomes. More aggressive management of youth-onset type 2 diabetes is needed to prevent the development of these serious complications (TODAY2 results: tracking type 2 diabetes in youth. Beyond Type 2 2019. https://beyondtype2.org/today2-results-tracking-type-2-diabetes-in-youth/ [Accessed 5 December 2019]). Currently, lifestyle modifications, metformin, liraglutide, and insulin are the only medications approved for use in children. Improved understanding of the pathophysiology, initial management, and chronic management as frontline providers is important for the development of effective preventative and therapeutic strategies.

OBJECTIVE The rs7903146 T allele in transcription factor 7 like 2 (TCF7L2) is strongly associated with type 2 diabetes (T2D), but the mechanisms for increased risk remain unclear. We evaluated the physiologic and hormonal effects of TCF7L2 genotype before and after interventions that influence glucose physiology. RESEARCH DESIGN AND METHODS We genotyped rs7903146 in 608 individuals without diabetes and recorded biochemical data before and after 1) one dose of glipizide (5 mg) on visit 1 and 2) a 75-g oral glucose tolerance test (OGTT) performed after administration of metformin 500 mg twice daily over 2 days. Incretin levels were measured in 150 of the 608 participants. RESULTS TT risk-allele homozygotes had 1.6 mg/dL higher baseline fasting glucose levels and 2.5 pg/mL lower glucagon levels per T allele than carriers of other genotypes at baseline. In a subset of participants, the T allele was associated with higher basal glucagon-like peptide 1 (GLP-1) levels at visit 1 (β = 1.52, P = 0.02 and β = 0.96, P = 0.002 for total and active GLP-1, respectively), and across all points of the OGTT after metformin administration. Regarding drug response, the T allele was associated with a shorter time (β = −7.00, P = 0.03) and a steeper slope (β = 0.23, P = 0.04) to trough glucose levels after glipizide administration, and lower visit 2 fasting glucose level adjusted for visit 1 fasting glucose level (β = −1.02, P = 0.04) and a greater decline in glucose level between visits (β = −1.61, P = 0.047) after metformin administration. CONCLUSIONS Our findings demonstrate that common variation at TCF7L2 influences acute responses to both glipizide and metformin in people without diabetes and highlight altered incretin signaling as a potential mechanism by which TCF7L2 variation increases T2D risk.

Type 2 diabetes (T2D) in youth is associated with a pro-atherogenic lipid profile characterized by high triglycerides (TG), high low-density lipoprotein cholesterol (LDL-c), and low high-density lipoprotein cholesterol (HDL-c). Genome wide association studies (GWAS) in adults have discovered more than 100 variants associated with lipid traits, but the association of genetic variants to dyslipidemia in youth with T2D remains unknown. Therefore, we genotyped 206,928 variants and imputed 17,642,824 variants in 1,076 youth with T2D from the Treatment Options for type 2 diabetes in Adolescents and Youth (TODAY) and SEARCH for Diabetes in Youth (SEARCH) as part of ProDiGY, a collaboration with type 2 diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES). Using a linear mixed model, we performed association testing for TG, LDL-c and HDL-c adjusted for age, sex, body mass index (BMI) Z-score, HbA1c, and genetic relationship matrix within each sub-study followed by meta-analyses for each lipid trait. We identified a novel variant between a deletion on chromosome 3 (3:67817380_AT/A_Deletion:RP11-81N13.1) that was associated with TG levels at genome wide level of significance (P-value=2.26×10-8, β=0.21±0.09). We also identified a genome-wide significant variant rs247617 (P-value=5.12×10-9, β=2.52±0.43) between HERFUD1 and CETP for association with HDL-c. This variant has been previously reported to be associated with HDL-c in adults in the Global Lipids Genetics Consortium (GLGC). We did not find any genome-wide significant variants in the LDL-c analysis. In summary, our genetic analyses of lipid traits in youth with T2D identified one novel and one previously known locus. Further multi-phenotype analysis may uncover additional loci associated with lipid traits in youth with T2D. Disclosure L. Chen: None. S. Srinivasan: None. N. Santoro: None. J. Todd: None. J. Divers: None. A.S. Shah: None. S. Gidding: Research Support; Self; Color Genomics. B.K. Burke: None. M.W. Haymond: Advisory Panel; Self; Daiichi Sankyo Company, Limited, Zealand Pharma A/S. Stock/Shareholder; Self; Xeris Pharmaceuticals, Inc. Other Relationship; Self; AstraZeneca. L. Lange: None. S.M. Marcovina: None. A. Chait: Consultant; Self; MedImmune. J. Flannick: Consultant; Self; Decibel Therapeutics. S. Caprio: None. J.C. Florez: None. Funding National Institutes of Health

It is often difficult to distinguish between type 1 (T1D) and type 2 diabetes (T2D), particularly in young adulthood. Both T1D and T2D have significant genetic contributions to risk and understanding their genetic overlap may offer clinical insight. We examined whether a T1D genetic risk score (GRS) is associated with clinical features and diagnosis of T2D in the Framingham Heart Study (FHS). We constructed a T1D GRS based on 79 SNPs from fine mapping results, with SNPs weighted by published effect sizes. The GRS included both HLA (27 SNPs) and non-HLA (52 SNPs) regions, and was applied to 1503 participants with T2D. Multivariable regression models assessed the association of the GRS with age of T2D onset, BMI, HbA1C, HOMA-β and HOMA-IR at the exam of diagnosis. Case-control analysis of 1503 cases and 5649 controls was done using multivariate generalized estimating equations (GEE) logistic models to determine the association between the T1D GRS and T2D risk with age and sex as covariates. In FHS participants, the mean age was 57.2 y, BMI was 30 kg/m2, and HbA1c 6.05%. The T1D GRS was not associated with T2D age of onset, or BMI, HbA1c, HOMA-β and HOMA-IR after excluding participants on medications for T2D. There was a trend towards lower HOMA-β and HOMA-IR values in the top quintile of the GRS (n=244, mean=2.47, SD= 0.7 for ln(HOMA-β) and mean=2.88, SD=0.8 for ln(HOMA-IR)) when compared to the lowest quintile of the GRS (n=260, mean= 2.53, SD=0.8 for ln(HOMA-β) and mean=2.92, SD=0.8 for ln(HOMA-IR)). The T1D GRS was associated with T2D (β = 0.per SD increase in GRS, SE= 0.03, OR =1.1, P = 0.04). When the non-HLA and HLA components of the GRS were tested separately, the results remained significant only for the non-HLA T1D GRS (β = 0.per SD increase in GRS, SE= 0.03, OR=1.1, P= 0.02). A T1D GRS of non-HLA SNPs is associated with T2D in the FHS participants. Our further analysis with increased sample size in multi-ethnic populations may refine the impact of the T1D GRS to characterize individuals with T2D. Disclosure S. Srinivasan: None. A. Leong: None. M. Udler: None. B.C. Porneala: None. J.B. Meigs: None. S.S. Rich: None. J. Dupuis: None.

The prevalence of type 2 diabetes is increasing in youth, particularly in certain ethnic groups, and studies have highlighted differences between youth- and adult-onset disease. However, its genetic determinants remain largely unexplored. To identify genetic variants predisposing to type 2 diabetes in youth, we formed ProDiGY, a multi-ethnic collaboration of the TODAY, SEARCH for Diabetes in Youth, and T2D-GENES studies, with 30young cases (mean age= 15.1 y ±2.8, 63% female, 22% white, 36% African American, 42% Hispanic) and 6061 diabetes-free adult controls (mean age = 54.2 y ±12.4; 57% female, 24% white, 18% African American, 58% Hispanic). After stratifying by self-reported and principal component-clustered ethnicity, we performed association analyses on 206,928 directly genotyped variants using a generalized linear mixed model using a genetic relationship matrix to account for population structure. We identified 5 genome-wide significant loci, including the novel locus rs13130484 in GNPDA2 (P= 1.4 ×10-8, odds ratio [OR]= 1.24), which has nominal association with type 2 diabetes in adults. Known loci identified in our analysis include rs4132670 in the well-known type 2 diabetes locus TCF7L2 (P= 4.2×10-13, OR 1.35) in high linkage disequilibrium with causal SNP rs7903146 (R2=0.83), rs11662368 near the obesity locus MC4R (P= 3.9×10-9, OR =1.31), rs11257655 in RN7SL232P (P= 5.7×10-12, OR= 1.33), and rs7075724 in CDC123 (P= 8.3×10-11, OR= 1.29); effect sizes are greater for these latter three loci than those found in adults (Pdiff= 8.2×10-5, 2.4×10-5, and 1.7×10-6, respectively). Secondary analysis with 856 diabetes-free youth controls demonstrated consistent direction of effect but no additional loci. In conclusion, we identified known and novel genetic loci predisposing to type 2 diabetes in youth. Our future analysis of ∼10 million variants holds the potential to uncover additional new type 2 diabetes susceptibility loci. Disclosure S. Srinivasan: None. J. Todd: None. L. Chen: None. J. Divers: None. S. Gidding: None. S. Chernausek: Advisory Panel; Self; Novo Nordisk Inc.. R. Gubitosi-Klug: None. M.M. Kelsey: Other Relationship; Self; Daiichi Sankyo Company, Limited, Merck Sharp & Dohme Corp.. R. Shah: None. M. Black: None. L.E. Wagenknecht: None. J.M. Mercader: None. A. Manning: None. J. Flannick: None. D. Dabelea: None. J.C. Florez: Consultant; Self; Intarcia Therapeutics, Inc.. Consultant; Spouse/Partner; Santen.

PURPOSE OF REVIEW: To provide an update on knowledge the role of genetics in youth-onset type 2 diabetes (T2D). RECENT FINDINGS: The prevalence of T2D, once thought to be exclusively a disease of adults, has increased by over 35% since 2001. Youth with T2D tend to have higher rates of complications, more aggressive disease, with more rapid loss of beta-cell function and a less favorable response to treatment than adults. Obesity is the most important risk factor for T2D, and the rise in childhood overweight and obesity appears responsible for the dramatic increase in T2D in youth. However, some obese children do not develop T2D, consistent with genetic differences in susceptibility to the disease in the setting of obesity/insulin resistance, currently far less well characterized in youth than in adults. Recent studies have begun to show associations of several established adult T2D genetic risk variants with youth T2D and related glycemic quantitative traits, including the strongest known cross-population T2D genetic contributor TCF7L2. Maturity onset diabetes of the young (MODY), a diabetes subtype distinct from type 1 diabetes (T1D) and T2D, is now known to result from a highly penetrant gene mutation in one of several genes. MODY has been shown to account for or contribute to at least 4.5% of clinically diagnosed T2D, even among those who are overweight or obese, impacting treatment decisions. The recently formed ProDiGY (Progress in Diabetes Genetics in Youth) Consortium is using genome-wide association studies and whole exome sequencing to understand the genetic architecture of T2D in youth, including how it differs from that of adults. SUMMARY: The limited amount of research conducted to date on the genetics of youth-onset T2D, which tends to be a more aggressive disease than adult T2D, suggests some overlap with genes involved in adult T2D and a sizeable influence of highly penetrant monogenic diabetes variants. The ProDiGY Consortium is expected to provide a more comprehensive understanding of youth T2D genetics.

Type 2 diabetes has become an enormous public health burden, making diabetes prevention a pressing issue. While lifestyle modification is the most effective preventive strategy, it is resource-intensive and not universally sustainable. We review the evidence on pharmacological options for diabetes prevention, in search of a medication that is efficacious, easy to adhere to, well tolerated, and cost-effective. With the exception of metformin, most other drugs have either limited efficacy or costly side effects.

Pharmacogenetic studies of antidiabetic drugs have so far focused largely on response to metformin, which is the first-line therapy for treatment of type 2 diabetes (T2D). The first studies of metformin pharmacogenetics were focused on candidate genes that were implicated in metformin pharmacokinetics and transport. Since 2011, genome-wide association studies have been conducted in large cohorts of individuals with T2D identifying genes that are associated with glycemic response to metformin. There have been fewer pharmacogenetic studies of other antidiabetic drugs, and those have been largely limited to candidate gene studies with small sample sizes. Understanding the pharmacogenetics of antidiabetes medications is important for the integration of genetic screening into therapeutic decision making, and to achieve the goal of "precision medicine" for patients with T2D. In this chapter, we provide a review of the pharmacogenetics investigations of metformin and other antidiabetes medications. In addition, we highlight the importance of collaborative efforts with large sample size and representation from multiple ethnic groups in pharmacogenetics studies.

Type 2 diabetes, once considered a disease restricted to adults, has increased in prevalence in childhood, largely due to the obesity epidemic in youth. This disease represents a serious public health issue as it is associated with significant comorbidities and complications even when compared with adults with the same disease and children with type 1 diabetes. Presently, metformin and insulin are the only two medications approved for use in children and little is known about the prevention of type 2 diabetes in youth. There is an urgent need for a better understanding of the underlying biology of the disease in youth and for the development of effective preventative and therapeutic strategies.