Predominantly genetic, intrauterine, and lifestyle aetiologies of type 2 diabetes are associated with distinct clinical presentations and risk of complications: a Danish cross-sectional and follow-up study.

1357-P: High Plasma Leptin Levels Are Associated with Low Birth Weight and Disease Severity in People with Recently Diagnosed Type 2 Diabetes

A Comprehensive Type 1 Diabetes Genetic Risk Score Is Associated with Type 2 Diabetes in the Framingham Heart Study

138-OR: Earlier Onset of Type 2 Diabetes Increases Genetic Risk of Cardiovascular Complication

Objective: Context: Early-onset type 2 diabetes (T2D) increases rapidly worldwide, alongside obesity, and carries an excess risk of microvascular complications and early death compared to when it started later in life. We have developed a multi-polygenic risk score (multiPRS) that predicts the risk of major micro- and macrovascular complications of T2D. We showed that individuals with high multiPRS scores for macrovascular events benefited more from tight blood pressure control while those with high multiPRS scores for microvascular events benefited from glycemic control. Early-onset T2D is genetically determined. Objective: To develop a genetic risk score that identifies individuals who are more susceptible to early-onset T2D and assess whether they could benefit from tight glycemic control. Design and method: We developed a genetic risk score (GRS) composed of 22 SNPs associated with early-onset T2D. We analysed 545 participants of European descent of ADVANCE with the highest GRS values and 526 subjects with the lowest GRS for early-onset T2D. Results: The median age at diagnosis of T2D was 54.9 in the high GRS and 64.6 in the low GRS group. Compared to participants with low GRS, those with high GRS were slightly heavier with a BMI of 30.8 (5.1 SD) vs 29.6 (4.9 SD), p = 7.2 x 10-5, they received more antidiabetic drugs (n= 1.5 (0.8) vs 1.2 (0.8), p = 1.2 x 10-7) and they died 5.7 years earlier (70.8 vs 76.5 years old p = 9 x 10-7). Contrary to the low GRS group, intensive glycemic control reduced mortality significantly in the high GRS group. Combination of intensive blood pressure and glycemia control led to a relative risk reduction of 52% (p = 0.028) and a number needed to treat of only 10 in the high GRS group while no significant effects were observed in the low GRS group. Conclusions: This novel GRS can identify individuals at risk of early-onset T2D who can benefit from tight glycemic control while its combination with blood pressure control is the most effective in reducing cardiorenal outcomes and death rate.

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 Study for type 2 diabetes in adolescents and a study of the of metformin or in combination with or in adolescents with type 2 Diabetes. 2007; PubMed Scopus Google Scholar SEARCH for Diabetes in Study for Diabetes in a study of the incidence and of diabetes mellitus in Clin Full Text Full Text PDF PubMed Scopus Google Scholar and the 2 Diabetes Genetic by in C. J. T.M. A. K.J. et al.The genetic of type 2 diabetes.Nature. 2016; PubMed Scopus Google Scholar The ProDiGY study is a to understanding of the genetics of T2D in youth by the sample and phenotypic data of 2 pediatric T2D studies with the genetic and of a adult diabetes genetics we conducted the first for T2D in youth to identify genetic variants specifically to youth-onset S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google Scholar our genetic in youth with T2D who were for pancreatic and adult years and identified genome-wide including the novel in with an of for T2D, that of the risk a of T2D compared with the A The 6 loci were previously identified in adults and included TCF7L2, and S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google the of our ProDiGY our hypothesis was that genetic were in youth with T2D compared with adults, given the T2D with to early age of To this we constructed GRSs in ProDiGY from known T2D variants identified in A. Zhang K.J. T. et meta-analysis insight into the genetic of type 2 diabetes Genet. 2014; PubMed Scopus Google Scholar of the association of the risk score between youth and adult and a higher for T2D in the youth compared with the adult in with our S. L. J. Divers J. S. S. et al.The first genome-wide association study for type 2 diabetes in the Progress in Diabetes Genetics in Youth (ProDiGY) 2021; PubMed Scopus (10) Google Scholar the efforts of the ProDiGY consortium have provided insight into the genetic of T2D in youth and have shown that the genetic of T2D in youth largely with that in adults but with a aggregate genetic risk studies of genes are to understand how the identified genetic variants disease the between and genetic factors are also to T2D risk in of Genetics in has been in our understanding of the genetics of T2D in youth to in sequencing and such as ProDiGY to sample sizes. Here we the of genetics as it pertains to pediatric T2D is a disease of from both environmental and genetic as well as of insulin resistance and β-cell among The of in MODY 3 is a of how genetics can be to disease and Although not as genetics also can be to for the more common of T2D. A approach has been to the heterogeneity of T2D with of loci mechanisms of disease based on β cell insulin resistance, and fat J. M. S. J.B. J. et 2 diabetes genetic loci by associations to disease mechanisms and a Med. 2018; 15: PubMed Scopus Google D. R.B. A. R. M. et association differences of Genet. 2021; PubMed Scopus Google Scholar These efforts to to with the of clinical and the risk of complications in the The of using genetic data to disease is that it over an and can be even a particularly for children who have T2D from the Diabetes Association youth with obesity for T2D based on the presence of additional risk including a family history of T2D, history of diabetes, and associated with insulin resistance, such as Diabetes and of in Care. 2021; 44: PubMed Scopus Google Scholar Although these allow to identify youth diabetes it is not which of these youth will on to T2D. In there is or between clinical as body mass fasting insulin or and the to the early days of T2D studies that a risk score for T2D in adults does not clinical of but to clinical risk genetic may predictive particularly for of adults in risk such as glucose might not have T. B. T. et al.Common genetic variants the from clinically of fasting glucose 2012; PubMed Scopus Google Scholar a risk score of 1 variants and that the of the distribution can identify adults with a to in T2D the of the as the the reported predictive was and the predictive was T. A. et of a risk score for type 2 diabetes in 2022; Scopus Google Scholar Although the current clinical utility of in the more scores from will to improve the predictive of these into can related to T2D with the of pathways related to the genetic the in TCF7L2, which has one of the known for common variants in both youth and adults with 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 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 S. L. J.

What is the prospective risk of Type 2 diabetes (T2D) in Nordic women with polycystic ovary syndrome (PCOS) compared to controls? A diagnosis of PCOS and BMI ≥30 kg/m2 is a high-risk phenotype for a prospective risk of T2D diagnosis across Nordic countries. The risk of T2D in women with PCOS is increased. The risk of T2D is related to BMI and the magnitude of risk in normal weight women with PCOS has been discussed. However, prospective data regarding risk of T2D in population-based cohorts of women with PCOS are limited. This national register-based study included women with PCOS and age-matched controls. The main study outcome was T2D diagnosis occurring after PCOS diagnosis. T2D was defined according to ICD-10 diagnosis codes and/or filled medicine prescriptions of anti-diabetic medication excluding metformin. The study cohort included women originating from Denmark (PCOS Denmark, N = 27016; controls, N = 133994), Finland (PCOS Finland, N = 20467; controls, N = 58051), and Sweden (PCOS Sweden, N = 52409; controls, N = 254010). The median age at cohort entry was 28 years in PCOS Denmark, Finland, and Sweden with a median follow-up time (interquartile range) in women with PCOS of 8.5 (4.0-14.8), 9.8 (5.1-15.1), and 6.0 (2.0-10.0) years, respectively. Cox regression analyses were adjusted for BMI and length of education. The crude hazard ratio (HR, 95% CI) for T2D diagnosis in women with PCOS was 4.28 (3.98-4.60) in Denmark, 3.40 (3.11-3.74) in Finland, and 5.68 (5.20-6.21) in Sweden. In adjusted regression analyses, BMI ≥30 vs <25 kg/m2 was associated with a 7.6- to 11.3-fold risk of T2D. In a combined meta-analysis (PCOS, N = 99892; controls, N = 446055), the crude HR for T2D in PCOS was 4.64 (3.40-5.87) and, after adjustment for BMI and education level, the HR was 2.92 (2.32-3.51). Inclusion of more severe cases of PCOS in the present study design could have lead to an overestimation of risk estimates in our exposed population. However, some women in the control group would have undiagnosed PCOS, which would lead to an underestimation of T2D risk in women with PCOS. BMI data were not available for all participants. The present study should be repeated in study cohorts with higher background risks of T2D, particularly in populations of other ethnicities. The prospective risk for diagnosis of T2D is increased in women with PCOS, and the risk is aggravated in women with BMI ≥30 kg/m2. Funding in Denmark was from the Region of Southern Denmark, Overlægerådet, Odense University Hospital. Funding in Finland was from Novo Nordisk Foundation, Finnish Research Council and Sigrid Juselius Foundation, the National Regional Fund, Sakari Alhopuro Foundation and Finnish Diabetes Research Foundation. E.E. has received a research grant from Ferring Pharmaceuticals (payment to institution) and serves as medical advisor for Tilly AB, not related to this manuscript. The remaining authors declare no conflict of interest. N/A.

244-OR: Toward Improved Identification of Adult-Onset Type 1 Diabetes (T1D): Clinical Characteristics Associated with T1D Polygenic Risk Scores in the Million Veteran Program (MVP)

Patients with type 2 diabetes (T2D) may disproportionately suffer the adverse cardiovascular effects of air pollution, but relevant evidence on microvascular outcome is lacking. We aimed to examine the association between air pollution exposure and the risk of microvascular complications among patients with T2D. This prospective study included 17 995 participants with T2D who were free of macro- and micro-vascular complications at baseline from the UK Biobank. Annual average concentrations of particulate matter (PM) with diameters <2.5 μm (PM2.5), <10 μm (PM10), nitrogen dioxide (NO2) and nitrogen oxides (NOx) were assessed using land use regression models. Cox proportional hazards regression was used to estimate the associations of air pollution exposure with incident diabetic microvascular complications. The joint effects of the air pollutant mixture were examined using quantile-based g-computation in a survival setting. In single-pollutant models, the adjusted hazard ratios (95% confidence intervals) for composite diabetic microvascular complications per interquartile range increase in PM2.5, PM10, NO2 and NOx were 1.09 (1.04-1.14), 1.06 (1.01-1.11), 1.07 (1.02-1.12) and 1.04 (1.00-1.08), respectively. Similar significant results were found for diabetic nephropathy and diabetic neuropathy, but not for diabetic retinopathy. The associations of certain air pollutants with composite microvascular complications and diabetic nephropathy were present even at concentrations below the World Health Organization limit values. Multi-pollutant analyses demonstrated that PM2.5 contributed most to the elevated risk associated with the air pollutant mixture. In addition, we found no interactions between air pollution and metabolic risk factor control on the risk of diabetic microvascular complications. Long-term individual and joint exposure to PM2.5, PM10, NO2 and NOx, even at low levels, was associated with an increased risk of diabetic microvascular complications, with PM2.5 potentially being the main contributor.

BackgroundBoth lifestyle and genetic predisposition determine the development of type 2 diabetes (T2D), and studies have indicated interactions between specific dietary components and individual genetic variants. However, it is unclear whether the importance of overall dietary habits, including T2D-related food intakes, differs depending on genetic predisposition to T2D. We examined interaction between a genetic risk score for T2D, constructed from 48 single nucleotide polymorphisms identified in genome-wide association studies, and a diet risk score of four foods consistently associated with T2D in epidemiological studies (processed meat, sugar-sweetened beverages, whole grain and coffee). In total, 25,069 individuals aged 45–74 years with genotype information and without prevalent diabetes from the Malmö Diet and Cancer cohort (1991–1996) were included. Diet data were collected with a modified diet history method.ResultsDuring 17-year follow-up, 3588 incident T2D cases were identified. Both the diet risk score (HR in the highest risk category 1.40; 95% CI 1.26, 1.58; P trend = 6 × 10−10) and the genetic risk score (HR in the highest tertile of the genetic risk score 1.67; 95% CI 1.54, 1.81; P trend = 7 × 10−35) were associated with increased incidence of T2D. No significant interaction between the genetic risk score and the diet risk score (P = 0.83) or its food components was observed. The highest risk was seen among the 6% of the individuals with both high genetic and dietary risk scores (HR 2.49; 95% CI 2.06, 3.01).ConclusionsThe findings thus show that both genetic heredity and dietary habits previously associated with T2D add to the risk of T2D, but they seem to act in an independent fashion, with the consequence that all individuals, whether at high or low genetic risk, would benefit from favourable food choices.

145-OR: ADA Presidents' Select Abstract: Association of Age at Type 1 Diabetes Diagnosis with Fatal Cardiovascular and Kidney Events

Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight. We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D. The T1D PS was not associated with T2D both in CHARGE (P = .15) and in the MGB Biobank (P = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, P = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, P = .03) in CHARGE T2D cases but not with other outcomes. In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

The relationship between the consumption of different beverages and the risk of microvascular complications in individuals with type 2 diabetes (T2D) is unclear. To investigate the association of individual beverage consumption, including artificially sweetened beverages (ASBs), sugar-sweetened beverages (SSBs), tea, coffee, natural juice, and yogurt, with the risk of microvascular complications in adults with T2D. This cohort study included 6676 participants with T2D who were free of macrovascular and microvascular complications at baseline in the UK Biobank. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 11.7 years, 1116 cases of composite microvascular complications were documented. After multivariable adjustment, a linear dose-response relationship was demonstrated between the consumption of ASBs and SSBs and the risk of microvascular complications. Compared with nonconsumers, those who consumed ≥2.0 units/day of ASBs and SSBs had an HR (95% CI) of 1.44 (1.18-1.75) and 1.32 (1.00-1.76) for composite microvascular complications, respectively. In addition, higher tea consumption was associated with a lower risk of diabetic retinopathy, with an HR (95% CI) of 0.72 (0.57-0.92) for whom consuming ≥4.0 units/day. There was no significant association between individual beverage consumption and the risk of diabetic neuropathy. No significant association was observed between the consumption of coffee, natural juice, or yogurt and the risks of microvascular complications. Moreover, substituting half units/day of ASBs or SSBs with tea or coffee was associated with a 16% to 28% lower risk of microvascular complications. Higher consumption of ASBs and SSBs was linearly associated with an increased risk of microvascular complications in adults with T2D.

243-OR: Integrating Genetic Risk Score and Islet Autoantibody Characteristics in the Predictive Model for Type 1 Diabetes in the TrialNet Study

278-OR: Ancestry-Specific Genetic Risk Scores of Type 2 Diabetes and Longitudinal Fetal Growth in a Race-Ethnic Diverse Population

Targets for Glycemic Control