The Genetics of Type 2 Diabetes in Youth: Where We Are and the Road Ahead

Abstract

The incidence of type 2 diabetes (T2D) is on the rise in youth in the US1Dabelea D. Mayer-Davis E.J. Saydah S. Imperatore G. Linder B. Divers J. et al.Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009.JAMA. 2014; 311: 1778-1786Crossref PubMed Scopus (933) Google Scholar,2Mayer-Davis E.J. Dabelea D. Lawrence J.M. Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012.N Engl J Med. 2017; 377: 301Crossref PubMed Scopus (7) Google Scholar and worldwide.3Pinhas-Hamiel O. Zeitler P. The global spread of type 2 diabetes mellitus in children and adolescents.J Pediatr. 2005; 146: 693-700Abstract Full Text Full Text PDF PubMed Scopus (484) Google Scholar T2D is characterized by hyperglycemia from a combination of insulin resistance and relative deficiency of insulin secretion. The contribution of insulin resistance to diabetes pathogenesis explains the clinical association of diabetes with obesity and, subsequently, the coincidence of increasing T2D prevalence with increasing prevalence and severity of obesity in children.4Skinner A.C. Ravanbakht S.N. Skelton J.A. Perrin E.M. Armstrong S.C. Prevalence of obesity and severe obesity in US children, 1999-2016.Pediatrics. 2018; 141: e20173459Crossref PubMed Scopus (783) Google Scholar Differences have been described in the natural history of youth-onset T2D and adult-onset T2D. Compared with adults, T2D in youth appears to progress more rapidly, with higher rates of metformin treatment failure and more rapid rates of beta cell decline.5Zeitler P. Hirst K. Pyle L. Linder B. Copeland K. et al.TODAY Study GroupA clinical trial to maintain glycemic control in youth with type 2 diabetes.N Engl J Med. 2012; 366: 2247-2256Crossref PubMed Scopus (597) Google Scholar, 6Bacha F. Pyle L. Nadeau K. Cuttler L. Goland R. Haymond M. et al.Determinants of glycemic control in youth with type 2 diabetes at randomization in the TODAY study.Pediatr Diabetes. 2012; 13: 376-383Crossref PubMed Scopus (33) Google Scholar, 7Narasimhan S. Weinstock R.S. Youth-onset type 2 diabetes mellitus: lessons learned from the TODAY study.Mayo Clin Proc. 2014; 89: 806-816Abstract Full Text Full Text PDF PubMed Scopus (63) Google ScholarThe presence of diabetes encumbers those affected with a long-term burden of chronic disease and an increased risk of cardiovascular and microvascular complications. This risk increases with the duration of the disease, putting children with T2D at extremely high risk for complications. Follow-up data from both the SEARCH for Diabetes in Youth study and the Treatment Options for Diabetes in Youth (TODAY) trial have found a substantial presence of diabetes complications as early as adolescence and young adulthood.8TODAY Study GroupRapid rise in hypertension and nephropathy in youth with type 2 diabetes: the TODAY clinical trial.Diabetes Care. 2013; 36: 1735-1741Crossref PubMed Scopus (188) Google Scholar, 9TODAY Study GroupLipid and inflammatory cardiovascular risk worsens over 3 years in youth with type 2 diabetes: the TODAY clinical trial.Diabetes Care. 2013; 36: 1758-1764Crossref PubMed Scopus (122) Google Scholar, 10Maahs D.M. Snively B.M. Bell R.A. Dolan L. Hirsch I. Imperatore G. et al.Higher prevalence of elevated albumin excretion in youth with type 2 than type 1 diabetes: the SEARCH for Diabetes in Youth study.Diabetes Care. 2007; 30: 2593-2598Crossref PubMed Scopus (126) Google Scholar, 11Mayer-Davis E.J. Davis C. Saadine J. D'Agostino Jr., R.B. Dabelea D. Dolan L. et al.Diabetic retinopathy in the SEARCH for Diabetes in Youth cohort: a pilot study.Diabet Med. 2012; 29: 1148-1152Crossref PubMed Scopus (55) Google Scholar Moreover, the prevalence of complications and overall mortality are higher in youth with T2D compared with adults with T2D or even youth with type 1 diabetes.12Constantino M.I. Molyneaux L. Limacher-Gisler F. Al-Saeed A. Luo C. Wu T. et al.Long-term complications and mortality in young-onset diabetes: type 2 diabetes is more hazardous and lethal than type 1 diabetes.Diabetes Care. 2013; 36: 3863-3869Crossref PubMed Scopus (268) Google Scholar,13Dabelea D. Stafford J.M. Mayer-Davis E.J. D'Agostino Jr., R. Dolan L. Imperatore G. et al.Association of type 1 diabetes vs type 2 diabetes diagnosed during childhood and adolescence with complications during teenage years and young adulthood.JAMA. 2017; 317: 825-835Crossref PubMed Scopus (2) Google Scholar This burden of disease underscores the need to improve our understanding of diabetes risk, prevention, and optimal treatment in youth.T2D is a complex, multifactorial disease influenced by both environmental factors and genetic variation as well as their interactions.14Barroso I. McCarthy M.I. The genetic basis of metabolic disease.Cell. 2019; 177: 146-161Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar,15Kolb H. Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes.BMC Med. 2017; 15: 131Crossref PubMed Scopus (256) Google Scholar The heritability of T2D is demonstrated by both the high concordance rates in identical twins16Barnett A.H. Eff C. Leslie R.D. Pyke D.A. Diabetes in identical twins. A study of 200 pairs.Diabetologia. 1981; 20: 87-93Crossref PubMed Scopus (835) Google Scholar,17Willemsen G. Ward K.J. Bell C.G. Christensen K. Bowden J. Dalgård C. et al.The concordance and heritability of type 2 diabetes in 34,166 twin pairs from international twin registers: the Discordant Twin (DISCOTWIN) Consortium.Twin Res Hum Genet. 2015; 18: 762-771Crossref PubMed Scopus (82) Google Scholar and the typical presence of a family history of T2D in those with the disease.18Copeland K.C. Zeitler P. Geffner M. Guandalini C. Higgins J. Hirst K. et al.Characteristics of adolescents and youth with recent-onset type 2 diabetes: the TODAY cohort at baseline.J Clin Endocrinol Metab. 2011; 96: 159-167Crossref PubMed Scopus (283) Google Scholar,19Klein B.E. Klein R. Moss S.E. Cruickshanks K.J. Parental history of diabetes in a population-based study.Diabetes Care. 1996; 19: 827-830Crossref PubMed Scopus (100) Google Scholar Investigations of the genetics of diabetes risk have examined both overall T2D risk as well as individual glycemic traits that may predispose to diabetes, such as fasting glucose levels, insulin secretion, insulin resistance, and β-cell function. Understanding the genetic underpinnings of diabetes risk offers an opportunity to improve both our knowledge of the mechanisms contributing to diabetes pathogenesis and our understanding of how best to individualize diabetes treatment and prevent complications. Here we review the current state of T2D genetics, specifically as it pertains to children and adolescents.Monogenic DiabetesDiabetes as a result of a single gene abnormality, or monogenic diabetes, shares clinical overlap with T2D, particularly T2D in youth. There are 3 major subgroups of monogenic diabetes: neonatal diabetes, syndromic diabetes, and maturity-onset diabetes of the young (MODY). Neonatal diabetes presents in infancy, although only a subset of infants develops diabetes in the neonatal period (the first 30 days of life); the majority of patients become symptomatic within the first 6 months of life.20Rubio-Cabezas O. Ellard S. Diabetes mellitus in neonates and infants: genetic heterogeneity, clinical approach to diagnosis, and therapeutic options.Horm Res Paediatr. 2013; 80: 137-146Crossref PubMed Scopus (66) Google Scholar Syndromic diabetes presents with additional extrapancreatic features, typically also in infancy.20Rubio-Cabezas O. Ellard S. Diabetes mellitus in neonates and infants: genetic heterogeneity, clinical approach to diagnosis, and therapeutic options.Horm Res Paediatr. 2013; 80: 137-146Crossref PubMed Scopus (66) Google Scholar MODY is characterized by non–insulin-dependent diabetes diagnosed at a young age (<25 years) demonstrating an autosomal dominant inheritance pattern.21Tattersall R.B. Fajans S.S. A difference between the inheritance of classical juvenile-onset and maturity-onset type diabetes of young people.Diabetes. 1975; 24: 44-53Crossref PubMed Scopus (346) Google Scholar Subtypes of MODY are based on specific genetic defects, with involvement of different genes associated with differences in clinical and physiologic phenotypes.22Hattersley A.T. Maturity-onset diabetes of the young: clinical heterogeneity explained by genetic heterogeneity.Diabet Med. 1998; 15: 15-24Crossref PubMed Scopus (264) Google ScholarMonogenic diabetes can be caused by pathogenic mutations in genes that disrupt glucose sensing, insulin transcription, the potassium–adenosine triphosphate channel that transduces the signal for insulin release, the insulin gene, or pancreatic development. Understanding the genes associated with monogenic forms of diabetes has provided insight into the disease mechanisms of diabetes. Eleven different genes have been identified as causal for MODY in the Online Mendelian Inheritance in Man catalog: HNF4A (MODY 1), GCK (MODY 2), HNF1A (MODY 3), PDX1 (MODY 4), HNF1B (MODY 5), NEUROD1 (MODY 6), CEL (MODY 8), INS (MODY 10), ABCC8 (MODY 12), KCNJ11 (MODY 13), and APPL1 (MODY 14). Note that the genes previously reported as causal for MODY 7, MODY 9, and MODY 11 are absent from this list, owing to the recent proposal to eliminate them from the list of causal MODY genes based on updated genetic evidence.23Laver T.W. Wakeling M.N. Knox O. Colclough K. Wright C.F. Ellard S. et al.Evaluation of evidence for pathogenicity demonstrates that BLK, KLF11, and PAX4 should not be included in diagnostic testing for MODY.Diabetes. 2022; 71: 1128-1136Crossref PubMed Scopus (4) Google Scholar Mutations in the HNF4A and HNF1A genes lead to abnormal insulin secretion, and MODY caused by variants in these genes can be effectively managed with oral sulfonylurea therapy.24Pearson E.R. Pruhova S. Tack C.J. Johansen A. Castleden H.A. Lumb P.J. et al.Molecular genetics and phenotypic characteristics of MODY caused by hepatocyte nuclear factor 4alpha mutations in a large European collection.Diabetologia. 2005; 48: 878-885Crossref PubMed Scopus (178) Google Scholar,25Pearson E.R. Starkey B.J. Powell R.J. Gribble F.M. Clark P.M. Hattersley A.T. Genetic cause of hyperglycaemia and response to treatment in diabetes.Lancet. 2003; 362: 1275-1281Abstract Full Text Full Text PDF PubMed Scopus (461) Google Scholar MODY caused by pathogenic variants in GCK, the gene encoding glucokinase, which phosphorylates glucose to glucose-6-phosphate in pancreatic cells and acts as a glucose sensor, is characterized by a mild, stable hyperglycemia with a low risk of complications that commonly does not require any treatment.26Steele A.M. Shields B.M. Wensley K.J. Colclough K. Ellard S. Hattersley A.T. Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia.JAMA. 2014; 311: 279-286Crossref PubMed Scopus (200) Google ScholarGiven the clinical overlap between T2D and rarer forms of diabetes, a long-held hypothesis is that the genetic underpinnings of both common and rare forms of diabetes might not be entirely distinct. Multiple studies have shown that MODY affects a small but not insignificant subset of youth with diabetes, including those clinically diagnosed with T2D. The SEARCH for Diabetes in Youth Study published the first systematic study of MODY prevalence in US youth, which reported a 1.2% overall prevalence of MODY.27Pihoker C. Gilliam L.K. Ellard S. Dabelea D. Davis C. Dolan L.M. et al.Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for Diabetes in Youth.J Clin Endocrinol Metab. 2013; 98: 4055-4062Crossref PubMed Scopus (219) Google Scholar A genetic sequencing study of participants in the TODAY study found that 4.5% carried a pathogenic variant in a MODY gene.28Kleinberger J.W. Copeland K.C. Gandica R.G. Haymond M.W. Levitsky L.L. Linder B. et al.Monogenic diabetes in overweight and obese youth diagnosed with type 2 diabetes: the TODAY clinical trial.Genet Med. 2018; 20: 583-590Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar A larger genetic study conducted by the Progress in Diabetes Genetics in Youth (ProDiGY) consortium that included the TODAY cohort, a second cohort recruited by the TODAY researchers for genetic studies, and a subset of the SEARCH for Diabetes in Youth study participants identified a 2.8% incidence of MODY.28Kleinberger J.W. Copeland K.C. Gandica R.G. Haymond M.W. Levitsky L.L. Linder B. et al.Monogenic diabetes in overweight and obese youth diagnosed with type 2 diabetes: the TODAY clinical trial.Genet Med. 2018; 20: 583-590Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar,29Todd J.N. Kleinberger J.W. Zhang H. Srinivasan S. Tollefsen S.E. Levitsky L.L. et al.Monogenic diabetes in youth with presumed type 2 diabetes: results from the Progress in Diabetes Genetics in Youth (ProDiGY) collaboration.Diabetes Care. 2021; 44: 2312-2319Crossref Scopus (10) Google Scholar These studies focused on rare, highly penetrant variants in known MODY genes. In adult studies of T2D genetics, there is increasing overlap of common variant associations and genes associated with monogenic diabetes.30Flannick J. Johansson S. Njølstad P.R. Common and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes.Nat Rev Endocrinol. 2016; 12: 394-406Crossref PubMed Scopus (78) Google Scholar Although such associations have not yet been shown in youth with T2D, it is possible that further examination of rarer variants will find associations along a spectrum of disease risk in genes or pathways relevant to diabetes.Candidate Gene StudiesMany efforts to understand the genetic underpinnings of T2D in children have focused on genetic variants with known associations with glycemic traits or T2D risk in adults, examining whether similar associations exist in youth. Individual variants have been shown to have similar associations in children for both fasting glucose31Barker A. Sharp S.J. Timpson N.J. Bouatia-Naji N. Warrington N.M. Kanoni S. et al.Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children.Diabetes. 2011; 60: 1805-1812Crossref PubMed Scopus (87) Google Scholar,32Kelliny C. Ekelund U. Andersen L.B. Brage S. Loos R.J. Wareham N.J. et al.Common genetic determinants of glucose homeostasis in healthy children: the European Youth Heart Study.Diabetes. 2009; 58: 2939-2945Crossref PubMed Scopus (50) Google Scholar and the homeostasis model assessment of β cell function.31Barker A. Sharp S.J. Timpson N.J. Bouatia-Naji N. Warrington N.M. Kanoni S. et al.Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children.Diabetes. 2011; 60: 1805-1812Crossref PubMed Scopus (87) Google Scholar Several T2D risk genes have been associated with youth-onset T2D, including TCF7L2,33Dabelea D. Dolan L.M. D'Agostino Jr., R. Hernandez A.M. McAteer J.B. Hamman R.F. et al.Association testing of TCF7L2 polymorphisms with type 2 diabetes in multi-ethnic youth.Diabetologia. 2011; 54: 535-539Crossref PubMed Scopus (42) Google Scholar,34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google Scholar SLC16A11, and ABCA1.34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google ScholarGenetic risk scores (GRSs), which allow for the assessment of the aggregate genetic risk of a given trait, have demonstrated association of GRSs constructed from variants associated in adults with glycemic traits and/or T2D risk with fasting glucose and measures of β-cell function,35Carayol J. Hosking J. Pinkney J. Marquis J. Charpagne A. Metairon S. et al.Genetic susceptibility determines β-cell function and fasting glycemia trajectories throughout childhood: a 12-year cohort study (EarlyBird 76).Diabetes Care. 2020; 43: 653-660Crossref PubMed Scopus (9) Google Scholar, 36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar, 37Morandi A. Bonnefond A. Lobbens S. Yengo L. Miraglia Del Giudice E. Grandone A. et al.Associations between type 2 diabetes-related genetic scores and metabolic traits, in obese and normal-weight youths.J Clin Endocrinol Metab. 2016; 101: 4244-4250Crossref PubMed Scopus (7) Google Scholar as well as measures of insulin resistance35Carayol J. Hosking J. Pinkney J. Marquis J. Charpagne A. Metairon S. et al.Genetic susceptibility determines β-cell function and fasting glycemia trajectories throughout childhood: a 12-year cohort study (EarlyBird 76).Diabetes Care. 2020; 43: 653-660Crossref PubMed Scopus (9) Google Scholar,36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar,38Graae A.S. Hollensted M. Kloppenborg J.T. Mahendran Y. Schnurr T.M. Appel E.V. et al.An adult-based insulin resistance genetic risk score associates with insulin resistance, metabolic traits and altered fat distribution in Danish children and adolescents who are overweight or obese.Diabetologia. 2018; 61: 1769-1779Crossref PubMed Scopus (9) Google Scholar in youth. Two studies have examined the ability of GRSs to identify children at risk of progressing to T2D; even though the scores were shown to be associated with T2D risk,36Giannini C. Dalla Man C. Groop L. Cobelli C. Zhao H. Shaw M.M. et al.Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.Diabetes Care. 2014; 37: 475-482Crossref PubMed Scopus (29) Google Scholar,39Miranda-Lora A.L. Vilchis-Gil J. Juárez-Comboni D.B. Cruz M. Klünder-Klünder M. A genetic risk score improves the prediction of type 2 diabetes mellitus in Mexican youths but has lower predictive utility compared with non-genetic factors.Front Endocrinol (Lausanne). 2021; 12: 647864Crossref PubMed Scopus (4) Google Scholar in one of the studies clinical factors such as body mass index (BMI) and family history of T2D had higher predictive utility.34Miranda-Lora A.L. Cruz M. Molina-Díaz M. Gutiérrez J. Flores-Huerta S. Klünder-Klünder M. Associations of common variants in the SLC16A11, TCF7L2, and ABCA1 genes with pediatric-onset type 2 diabetes and related glycemic traits in families: a case-control and case-parent trio study.Pediatr Diabetes. 2017; 18: 824-831Crossref PubMed Scopus (16) Google ScholarGenome-Wide Association StudiesSince the first genome-wide association study (GWAS) for T2D in adults was published in 2007,40Sladek R. Rocheleau G. Rung J. Dina C. Shen L. Serre D. et al.A genome-wide association study identifies novel risk loci for type 2 diabetes.Nature. 2007; 445: 881-885Crossref PubMed Scopus (2352) Google Scholar there has been an explosion of genetic discoveries related to adult T2D with extremely well-powered studies and advanced analytic techniques. At the time of this publication, >400 variants have been associated with T2D in adults.41Mahajan A. Taliun D. Thurner M. Robertson N.R. Torres J.M. Rayner N.W. et al.Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps.Nat Genet. 2018; 50: 1505-1513Crossref PubMed Scopus (671) Google Scholar In comparison, large scale studies of pediatric T2D have not been conducted, largely due to limited sample sizes. To address this gap, we and colleagues formed the ProDiGY Consortium, which is a collaboration of 3 research groups: the TODAY study,42Zeitler P. Epstein L. Grey M. Hirst K. Kaufman F. et al.Today Study GroupTreatment options for type 2 diabetes in adolescents and youth: a study of the comparative efficacy of metformin alone or in combination with rosiglitazone or lifestyle intervention in adolescents with type 2 diabetes.Pediatr Diabetes. 2007; 8: 74-87Crossref PubMed Scopus (194) Google Scholar SEARCH for Diabetes in Youth,43SEARCH Study GroupSEARCH for Diabetes in Youth: a multicenter study of the prevalence, incidence and classification of diabetes mellitus in youth.Control Clin Trials. 2004; 25: 458-471Abstract Full Text Full Text PDF PubMed Scopus (216) Google Scholar and the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Consortium.44Fuchsberger C. Flannick J. Teslovich T.M. Mahajan A. Agarwala V. Gaulton K.J. et al.The genetic architecture of type 2 diabetes.Nature. 2016; 536: 41-47Crossref PubMed Scopus (685) Google Scholar The ProDiGY study is a collaborative effort to increase understanding of the genetics of T2D in youth by combining the sample sizes and rich phenotypic data of 2 pediatric T2D studies with the genetic prowess and resources of a large-scale adult diabetes genetics consortium.In ProDiGY, we conducted the first GWAS for T2D in youth to identify genetic variants specifically predisposing to youth-onset T2D.45Srinivasan S. Chen L. Todd J. Divers J. Gidding S. Chernausek S. et al.The first genome-wide association study for type 2 diabetes in youth: the Progress in Diabetes Genetics in Youth (ProDiGY) Consortium.Diabetes. 2021; 70: 996-1005Crossref PubMed Scopus (10) Google Scholar We performed our genetic analysis in 3006 multiethnic youth with T2D who were autoantibody-negative for selected pancreatic autoantibodies and 6061 adult controls aged >50 years and diabetes-free. We identified 7 genome-wide significant loci, including the novel locus rs10992863 in PHF2 with an OR of 1.23 for T2D, implying that each copy of the G risk allele conferred a 23% greater odds of having T2D compared with the wild-type A allele. The remaining 6 loci were previously identified in adults and included TCF7L2, MC4R, CDC123, KCNQ1, IGFBP2, and SLC16A11.45Srinivasan S. Chen L. Todd J. Divers J. Gidding S. Chernausek S. et al.The first genome-wide association study for type 2 diabetes in youth: the Progress in Diabetes Genetics in Youth (ProDiGY) Consortium.Diabetes. 2021; 70: 996-1005Crossref PubMed Scopus (10) Google ScholarAt the outset of our ProDiGY collaboration, our hypothesis was that genetic effects were greater in youth with T2D compared with adults, given the “extreme” T2D phenotype with respect to early age of presentation. To explore this premise, we constructed GRSs in ProDiGY from known T2D variants identified in adults.46Mahajan A. Go M.J. Zhang W. Below J.E. Gaulton K.J. Ferreira T. et al.Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.Nat Genet. 2014; 46: 234-244Crossref PubMed Scopus (730) Google Scholar Our comparison of the association of the polygenic risk score between youth and adult cases and controls showed a significantly higher OR for T2D in the youth analysis compared with the adult analysis, in accordance with our hypothesis.45Srinivasan S. Chen L. Todd J. Divers J. Gidding S. Chernausek S. et al.The first genome-wide association study for type 2 diabetes in youth: the Progress in Diabetes Genetics in Youth (ProDiGY) Consortium.Diabetes. 2021; 70: 996-1005Crossref PubMed Scopus (10) Google Scholar Overall, the efforts of the ProDiGY consortium have provided initial insight into the genetic architecture of T2D in youth and have shown that the genetic architecture of T2D in youth largely overlaps with that in adults but with a greater aggregate genetic risk burden. Functional studies of candidate genes are needed to understand how the identified genetic variants affect disease risk. Studies evaluating the interplay between lifestyle and genetic factors are also needed to comprehensively evaluate T2D risk in youth.Applications of Genetics in Youth-Onset T2DThere has been substantive growth in our understanding of the genetics of T2D in youth secondary to large-scale improvements in genotyping technology, next-generation sequencing techniques, and collaborative approaches such as ProDiGY to increase sample sizes. Here we appraise the various applications of genetics as it pertains to pediatric T2D.Characterizing Disease SubtypesPediatric T2D is a heterogenous disease likely because of differing contributions from both environmental and genetic factors, as well as varying degrees of insulin resistance and β-cell dysfunction among individuals. The benefit of sulfonylureas in MODY 3 is a concrete example of how genetics can be used to characterize disease and dictate treatment. Although not always as targeted, genetics also can be used to characterize subtypes for the more common form of T2D. A soft clustering approach has been used to deconstruct the heterogeneity of T2D with groups of loci representing various mechanisms of disease based on β cell function, insulin resistance, and fat distribution47Udler M.S. Kim J. von Grotthuss M. Bonàs-Guarch S. Cole J.B. Chiou J. et al.Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: a soft clustering analysis.PLoS Med. 2018; 15: e1002654Crossref PubMed Scopus (192) Google Scholar,48Mansour Aly D. Dwivedi O.P. Prasad R.B. Käräjämäki A. Hjort R. Thangam M. et al.Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes.Nat Genet. 2021; 53: 1534-1542Crossref PubMed Scopus (18) Google Scholar (Figure). These efforts to categorize subtypes help to better characterize pathophysiology, with the hope of informing clinical management and the risk of complications in the future. The benefit of using genetic data to characterize disease is that it remains unchanged over an individual's lifetime and can be measured even before symptoms develop, a particularly valuable characteristic for high-risk children who often have very short latent periods before full-blown T2D develops.Risk PredictionCurrent guidelines from the American Diabetes Association recommend screening youth with obesity for T2D based on the presence of certain additional risk factors, including a family history of T2D, high-risk race/ethnicity, maternal history of gestational diabetes, and physical features associated with insulin resistance, such as acanthosis nigricans.49American Diabetes Association13. Children and adolescents: standards of medical care in diabetes—2021.Diabetes Care. 2021; 44: S180-S199Crossref PubMed Scopus (102) Google Scholar Although these criteria allow clinicians to readily identify youth requiring diabetes screening, it is not clear which of these youth will go on to develop T2D. In addition, there is no simple or direct correlation between clinical features as body mass index, fasting insulin level, or C-peptide level and the progression to T2D.In the early days of T2D GWAS efforts, studies showed that a polygenic risk score for T2D in adults does not outperform clinical models of prediction, but when added to routine clinical risk factors, genetic information may enhance predictive utility, particularly for populations of younger adults in whom risk factors, such as glucose intolerance, might not have fully manifested.50Walford G.A. Green T. Neale B. Isakova T. Rotter J.I. Grant S.F. et al.Common genetic variants differentially influence the transition from clinically defined states of fasting glucose metabolism.Diabetologia. 2012; 55: 331-339Crossref PubMed Scopus (35) Google Scholar Recently, a trans-ancestry polygenic risk score (PRS) of 1 259 754 HapMap3 variants and weights showed that the top 2% of the PRS distribution can identify adults with a roughly 2.5- to 4.5-fold increase in T2D risk. Using the top 2% of the PRS as the classifier, the reported prevalence-adjusted positive predictive value was 0.26 and the negative predictive value was 0.90.51Ge T. Patki A. Srinivasasainagendra V. Lin Y.F. Irvin M.R. Tiwari H.K. et al.Validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations.medRxiv. 2022; ([preprint])https://doi.org/10.1101/2021.09.11.21263413Crossref Scopus (0) Google Scholar Although the current clinical utility of PRSs remains limited, in the future more sophisticated scores derived from diverse populations likely will continue to improve the predictive performance of these scores.Insight into Biologic MechanismsGenetic discovery can help uncover underlying biology related to T2D with the interrogation of pathways related to the genetic loci. For example, the intronic SNP rs7903146 in TCF7L2, which has one of the strongest known effect sizes for common variants in both youth and adults with T2D,33Dabelea D. Dolan L.M. D'Agostino Jr., R. Hernandez A.M. McAteer J.B. Hamman R.F. et al.Association testing of TCF7L2 polymorphisms with type 2 diabetes in multi-ethnic youth.Diabetologia. 2011; 54: 535-539Crossref PubMed Scopus (42) Google Scholar,40Sladek R. Rocheleau G. Rung J. Dina C. Shen L. Serre D. et al.A genome-wide association study identifies novel risk loci for type 2 diabetes.Nature. 2007; 445: 881-885Crossref PubMed Scopus (2352) Google Scholar,45Srinivasan S. Chen L. Todd J. Diver