Staging Presymptomatic Type 1Diabetes: A Scientific Statementof JDRF, the Endocrine Society,and the American DiabetesAssociationDiabetes Care 2015;38:1964–1974 | DOI: 10.2337/dc15-1419

The Adoption of the Staging Classification System Is Endorsed by the AmericanAssociation of Clinical Endocrinologists, the International Society for Pediatric andAdolescent Diabetes, and The Leona M. and Harry B. Helmsley Charitable Trust

Insights from prospective, longitudinal studies of individuals at risk for developingtype 1 diabetes have demonstrated that the disease is a continuum thatprogresses sequentially at variable but predictable rates through distinct identifi-able stages prior to the onset of symptoms. Stage 1 is defined as the presence ofb-cell autoimmunity as evidenced by the presence of two or more islet autoanti-bodies with normoglycemia and is presymptomatic, stage 2 as the presence ofb-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 asonset of symptomatic disease. Adoption of this staging classification provides astandardized taxonomy for type 1 diabetes and will aid the development of ther-apies and the design of clinical trials to prevent symptomatic disease, promoteprecision medicine, and provide a framework for an optimized benefit/risk ratiothat will impact regulatory approval, reimbursement, and adoption of interven-tions in the early stages of type 1 diabetes to prevent symptomatic disease.

Type 1 diabetes is a chronic autoimmune disease with both genetic and environ-mental contributions that results over time in an immune-mediated loss of func-tional pancreatic b-cell mass, leading to symptomatic diabetes and lifelong insulindependence (1–3). The disorder represents a disease continuum that begins prior toits symptomatic manifestations. The risk of developing symptomatic type 1 diabetescan be identified and quantified, the disease can be characterized into well-definedstages, and the rate of progression to symptomatic disease can be predicted withappreciable accuracy. The ability to screen for risk and to stage type 1 diabetes priorto symptomatic type 1 diabetes provides an opportunity to intervene to delay andultimately to prevent the onset of clinical symptoms.Herein, we propose a staging classification system that recognizes the earliest

stages of human type 1 diabetes. Adoption of this staging classification will 1)provide a new standardized taxonomy for human type 1 diabetes; 2) acceleratethe clinical development of therapies to prevent symptomatic disease; 3) aid thedesign of clinical trials through the use of risk profiles, subject stratification, andstage-specific clinical trial end points; 4) promote precision medicine involvingthe tailoring of optimal therapies to specific individuals at specific stages of the

1JDRF, New York, NY2UF Diabetes Institute, University of Florida,Gainesville, FL3American Diabetes Association, Alexandria, VA4Colorado School of Public Health, University ofColorado, Denver, CO5Barbara Davis Center for Childhood Diabetes,University of Colorado, Aurora, CO6Benaroya Research Institute at Virginia Mason,Seattle, WA7Department of Immunobiology, Yale School ofMedicine, New Haven, CT8Department of Pediatrics, Pediatric Epidemiol-ogy Center,Morsani College ofMedicine, Univer-sity of South Florida, Tampa, FL9Lund University/Clinical Research Centre, SkaneUniversity Hospital, Malmo, Sweden10Diabetes Research Institute, University of Mi-ami, Miami, FL11Institute of Diabetes Research, HelmholtzZentrumMunchen, Munich and ForschergruppeDiabetes, Klinikum rechts der Isar, TechnischeUniversitat Munchen, Neuherberg, Germany

Corresponding author: Richard A. Insel, rinsel@jdrf.org.

This scientific statement was reviewed and ap-proved by the American Diabetes AssociationProfessional Practice Committee in June 2015and ratified by the American Diabetes Associa-tion Board of Directors in June 2015.

The adoption of the staging classification systemis endorsed by the American Association of Clin-ical Endocrinologists, the International Societyfor Pediatric and Adolescent Diabetes, and TheLeonaM. andHarry B. Helmsley Charitable Trust.

© 2015 by the American Diabetes Association.Readers may use this article as long as the workis properly cited, the use is educational and notfor profit, and the work is not altered.

Richard A. Insel,1 Jessica L. Dunne,1

Mark A. Atkinson,2 Jane L. Chiang,3

Dana Dabelea,4 Peter A. Gottlieb,5

Carla J. Greenbaum,6 Kevan C. Herold,7

Jeffrey P. Krischer,8 Ake Lernmark,9

Robert E. Ratner,3 Marian J. Rewers,5

Desmond A. Schatz,2 Jay S. Skyler,10

Jay M. Sosenko,10 and Anette-G. Ziegler11

1964 Diabetes Care Volume 38, October 2015

SCIENTIFICSTATEMEN

T

disease; and 5) provide a frameworkand approach for an optimized bene-fit/risk ratio that should impact regula-tory approval, reimbursement, andadoption of interventions in the earlystages of type 1 diabetes to preventsymptomatic disease.

OVERVIEW OF STAGING OF TYPE 1DIABETES

As originally proposed over 25 years ago,human type 1 diabetes arises from bothgenetic and environmental factors thatlead to immune-mediated destruction ofpancreatic b-cells and loss of b-cell func-tion. After onset of islet autoimmunity,the disease progresses through a pre-symptomatic stage identified by markersof autoimmunity and glucose intolerance,or so-called dysglycemia, arising from fur-ther loss ofb-cell function and culminatesultimately with clinical symptoms andsigns of diabetes (1–3). In children andadults, the rate of progression fromonsetofb-cell autoimmunity to glucose intoler-ance and then to symptomatic disease isvariable, lasting from months to decades(2,3).Today, type 1 diabetes is typically di-

agnosed based on clinical symptomatol-ogy associated with overt hyperglycemiaandmetabolic imbalance. As detailed be-low, however, the disease can now beidentified at earlier presymptomaticstages. Indeed, first- or second-degreerelatives of individuals with type 1 diabe-tes or children identified from the gen-eral population are being screened forincreased risk for developing type 1 di-abetes in the research setting (4–6). Dis-tinct asymptomatic stages of type 1diabetes with prognostic implication havebeen identified, and prevention clinical tri-als are ongoing with enrollment criteriaand end points based on specific diseasestages.As shown in Fig. 1 and as detailed

below, a broad body of evidence sup-ports a standardized classification of dis-tinct early stages of type 1 diabetes withprognostic significance.

Stage 1: Autoimmunity1/Normoglycemia/PresymptomaticType 1 DiabetesStage 1 represents individuals who havedeveloped two ormore type 1 diabetes–associated islet autoantibodies but arenormoglycemic. For children who werescreened for genetic risk at birth and

reach this stage, the 5-year and 10-year risks of symptomatic disease areapproximately 44% and 70%, respec-tively, and the lifetime risk approaches100% (7). The risk at this stage is quitesimilar in genetically at-risk children andin relatives of individuals with type 1 di-abetes, as detailed below (7–9).

Stage 2: Autoimmunity1/Dysglycemia/Presymptomatic Type 1DiabetesStage 2, like stage 1, includes individualswith two or more islet autoantibodiesbut whose disease has now progressedto the development of glucose intoler-ance, or dysglycemia, from loss of func-tional b-cell mass. The 5-year risk ofsymptomatic disease at this stage is ap-proximately 75%, and the lifetime riskapproaches 100% (10).

Stage 3: Autoimmunity1/Dysglycemia/Symptomatic Type 1DiabetesStage 3 represents manifestations of thetypical clinical symptoms and signs ofdiabetes, which may include polyuria,polydipsia, weight loss, fatigue, diabeticketoacidosis (DKA), and others.

PRE-STAGE 1: GENETICSUSCEPTIBILITY AND GENETICRISK DETECTION OF TYPE 1DIABETES

The HLA region on chromosome 6 ac-counts for about 30–50% of the geneticrisk of type 1 diabetes (11), with thegreatest association with HLA class IIhaplotypes DRB1*0301-DQB1*0201(DR3-DQ2) and DRB1*0401-DQB1*0302(DR4-DQ8) (Table 1). The genotype associ-ated with the highest risk for type 1diabetes is the heterozygous DR3/4genotype. HLA class II DRB1*1501 andDQA1*0102-DQB1*0602 confer disease re-sistance, at least in children younger than12 years of age. The rising incidence of type1 diabetes (12–14) has been accompaniedby a decrease in the relative contributionfrom the highest risk HLA genotype (15,16).

The remaining genetic r isk fortype 1 diabetes can be attributed tothe approximately 50 non-HLA genesor loci identified via candidate geneand genome-wide association studyapproaches, each with modest to smalleffects on disease risk. The highestnon-HLA genetic contribution arisesfrom the INS, PTPN22, CTLA4, andIL2RA genes, with the latter three genes

also contributing to susceptibility toother autoimmune diseases (17). Non-HLA genetic contribution may be actingthrough immune regulation (18), al-though the recent demonstration ofgene expression commonly in pancre-atic islets and the alternative splicingof several of these gene products incytokine-stimulated islets have raised thequestion of whether some of these genesmay in part be acting in the b-cell (19).

Genetic variation likely influencesboth immune regulation and the hostresponse to environmental etiologies,which determine an individual’s initialdisease susceptibility and progressionthrough sequential homeostatic check-points prior to onset of symptomaticdisease. In fact, unlike the HLA type 1diabetes susceptibility genes that ap-pear to have a limited effect on therate of progression to symptomatic dis-ease after the onset of islet autoim-munity (20), several non-HLA type 1diabetes susceptibility genes havebeen demonstrated to influence dis-ease progression, including IL2, CD25,INS VNTR, IL18RAP, IL10, IFIH1, andPTPN22 (21). As a result, non-HLA singlenucleotide polymorphisms and risk al-lele scores have been used to stratifyrisk for both developing islet autoanti-bodies and progressing from islet au-toimmunity to symptomatic type 1diabetes (22,23). With larger databases,this analysis will likely be refined andimproved.

Multiple environmental factors havebeen invoked as contributing to thepathogenesis of type 1 diabetes, includ-ing, but not limited to, maternal andintrauterine environment, route ofneonatal delivery, viruses, host micro-biome, antibiotics, and food/diet (24–26). The Environmental Determinantsof Diabetes in the Young (TEDDY) study(27) is exploring the role of putative en-vironmental etiologies. Because causal-ity of type 1 diabetes has not beenconclusively demonstrated, environ-mental factors do not currently contrib-ute to screening for risk, staging, orprevention of the disease.

The impact of HLA and non-HLA ge-netic risk is observed in relatives of in-dividuals with type 1 diabetes, whohave a 10-fold to more than 100-foldgreater risk than the general population(Table 1). The cumulative risk ofdeveloping type 1 diabetes among

care.diabetesjournals.org Insel and Associates 1965

monozygotic twins is reported to be ashigh as 65–70% (28), with higher ratesobserved when the proband developstype 1 diabetes at an earlier age (29). Ahigh risk is also observed in siblings ofindividuals with type 1 diabetes whoare DR3-DQ2/DR4-DQ8 and have

inherited both HLA haplotypes identicalby descent with their proband sibling,with a risk as high as 80% for developingtype1diabetes–associated autoimmunityby age 15 years (30). In siblings withshared DR3-DQ2/DR4-DQ8 HLA haplo-types, the age of onset of symptomatic

type 1 diabetes in the proband is aprominent risk factor, with a 12-foldhigher risk of developing symptomaticdisease by age 15 years in the sibling ifthe proband develops the disease be-fore age 10 years (31).

This increased risk in relatives of indi-viduals with type 1 diabetes has beenexploited in the research setting to iden-tify at-risk individuals to better under-stand the natural history of type 1diabetes and to conduct trials to preventsymptomatic disease, as exemplified bythe Diabetes Prevention Trial–Type 1(DPT-1) (4,32) and the National Instituteof Diabetes and Digestive and KidneyDiseases–sponsored Type 1 DiabetesTrialNet studies (33). Approximately15,000 children and young adults whoare first- or second-degree relatives ofindividuals with type 1 diabetes arescreened annually for the presence ofislet autoantibodies through TrialNet(33). A recent position statement ofthe American Diabetes Association(ADA) recommended that at-risk rela-tives of individuals with type 1 diabetesbe informed of the opportunity to havetheir relatives tested for type 1 diabetesrisk in the setting of a clinical researchstudy (34). Although screening more

Figure 1—Early stages of type 1 diabetes.

Table 1—Type 1 diabetes risk stratification by family history and genetic susceptibility

PopulationRisk of type 1diabetes (%)

Frequency inpopulation (%)

Frequency in all type 1diabetes (%)

Low risk (,1%)Newborns: European/U.S. population 0.4–1 100 100Newborns with HLA protective genotypes (124) ,0.05 75 7.2FDR with HLA protective genotypes (124) 0.3 0.3 ,1FDR with low gene risk score* (HLA and non-HLA

risk genes) (23) ,1 0.1 ,1

Intermediate risk (1–12%)Newborns with HLA high-risk genotypes (37) 4 4–5 36Newborns with high gene risk score** (HLA and non-HLA

risk genes) (23) 12 1 27Newborn first-degree relatives of people with type 1

diabetes5 0.5–1 10

High risk (12–25%)FDR plus HLA high-risk genotypes (125) 10–20 0.1 ,5FDR plus high gene risk score*** (HLA and non-HLA risk

genes) (23) 40 0.1 ,5Multiple affected FDRs (126) 20–25 ,,0.1 ,,5

Very high risk (.25%)Identical twin of a patient with type 1 diabetes (28,29) 30–70 ,,0.1 ,,5Multiple affected FDRs plus HLA risk genotypes (126) 50 ,,0.1 ,,5Sibling affected plus HLA risk genes, identical by

descent (30) 30–70 ,,0.1 ,,5

FDR, newborn first-degree relatives of people with type 1 diabetes. HLA risk genotypes: HLA DRB1*03 and *04 and DQB1*0302. HLA protectivegenotypes: HLA DQB1*0602, *0301, *0303, *0603, and *0503. Genetic risk score derived from HLA plus nine single nucleotide polymorphismsfrom PTPN22, INS, IL2RA, ERBB3, ORMDL3, BACH2, IL27, GLIS3, and RNLS genes. *Threshold set to lower 10th centile of FDR; **threshold set toupper 99th centile of general population; ***threshold set to upper 90th centile of FDR.

1966 Scientific Statement Diabetes Care Volume 38, October 2015

than 150,000 individuals over the pastdecade by TrialNet represents a formi-dable accomplishment, screening of rel-atives leaves a large gap in identifyingindividuals at risk for developing type 1diabetes because a family history oftype 1 diabetes is present in only up to;15% of cases of newly diagnosed type1 diabetes (35,36).On the basis of HLA genotype risk of

type 1 diabetes, newborns and infants inthe general population have also beenscreened for risk in the research settingand subsequently recruited into naturalhistory studies. TheTEDDY study screenednewborns from the general populationusing four high-risk HLA genotypes(90% specificity, 69% sensitivity, and22% positive predictive value) and new-borns with first-degree relatives using 10HLA genotypes (94% specificity, 50%sensitivity, and 4.8% positive predictivevalue), a strategy predicted to identify50% of type 1 diabetes cases from thegeneral population study and 70% ofcases among relatives that occurred byage 15 years (37). It should be empha-sized that the majority of HLA at-riskindividuals never develop symptomatictype 1 diabetes and thus the positivepredictive value of HLA is low, necessi-tating follow-up with additional bio-markers to detect risk of developingsymptomatic disease, such as the pres-ence of islet autoantibodies.

STAGE 1: AUTOIMMUNITY1/NORMOGLYCEMIA/PRESYMPTOMATIC TYPE 1DIABETES

Stage 1 is defined as the presence of twoor more islet autoantibodies to insulin,GAD65, IA-2, and/or ZnT8. The mecha-nisms leading to b-cell autoimmune re-activity have not been completelyelucidated. (Pro)insulin, GAD65, IA-2,and ZnT8 and their peptides have beenidentified as target antigens in type 1 di-abetes (38,39). Although T lymphocytesare thought to be primarily responsibleforb-cell destruction, they are rare in thecirculating blood, and no standardizedand validated human T-cell assays havebeen developed to screen for T-cell–mediated b-cell reactivity. However, isletautoantibodies are also generated and re-main in the circulation and can be mea-sured with standardized, sensitive, andhigh-throughput assays. Ongoing studies

of T-lymphocyte phenotype, cytokinepatterns of antigen-specific T cells,lymphocyte-mediated immunoregu-lation, and responses of effector T cellsto immunoregulation of autoantibody-positive subjects prior to symptomaticdisease should provide further insightsinto the role of T-cell responses and ul-timately may provide useful biomarkers.

In Finnish and German at-risk childrenfollowed longitudinally from birth, isletautoantibodies were initially detectedafter 6 months of age and peaked be-tween 9 and 24 months of age with amedian age of detection of 15 months(40,41). In the TEDDY study of at-riskinfants and children, the initial detec-tion of islet autoantibodies occurredrarely prior to 6 months of age andpeaked between 9 and 24 months ofage (42). In most cases, autoantibodiesto insulin developed earlier than auto-antibodies to GAD65, whereas IA-2 andZnT8 were rarely the first autoantibodyto develop (9,40–44).

Progression from single to two ormore autoantibodies occurs more com-monly in children less than 5 years ofage, usually occurs within 2 years of ini-tial seroconversion, and is less frequentafter 4 years of initial seroconversion(40–45).

Early autoantibody seroconversion ismost common in children with the high-risk HLA DR3/4-DQ8 or DR4/4-DQ8/8genotype (40–42), and the order of ap-pearance of autoantibodies is relatedto HLA-DQ genotype. In the TEDDYstudy, HLA-DQ2/8, DQ8/8, and DQ4/8children developed primarily insulinautoantibodies as the first autoanti-body, whereas DQ2/2 children initiallydeveloped GAD65 autoantibodies (42).The associations between insulin auto-antibodies and HLA-DQ8, but not DQ2,and between GAD65 autoantibodiesand HLA-DQ2, but not DQ8, are also ob-served in new-onset type 1 diabetes(46–48). These findings suggest the pos-sibility of a distinct etiopathogenesis re-lated to HLA.

TrialNet autoantibody screening ofrelatives of individuals with type 1 dia-betes has a yield of ;5% autoantibodypositivity, and those with autoantibod-ies are further staged for risk with met-abolic and genetic tests (33). For thosesubjects who are initially autoantibodynegative, the rate of seroconversion ishigher in relatives younger than age 10

years, with about 75% of seroconver-sions occurring by age 13 years (49,50).

The detection of two or more isletautoantibodies increases the rate ofprogression to symptomatic type 1diabetes. In a study of 585 high-risk chil-dren with two or more islet autoanti-bodies enrolled in three prospectivebirth cohort studies (U.S. Diabetes Au-toimmunity Study in the Young[DAISY], Finnish Diabetes Predictionand Prevention [DIPP] study, and Ger-man BABYDIAB and BABYDIET studies),symptomatic type 1 diabetes developedin 43.5%, 69.7%, and 84.2% at 5, 10,and 15 years of follow-up (Fig. 2) (7).Thus, the lifetime risk of developingsymptomatic type 1 diabetes approaches100% once two or more islet autoanti-bodies are detected in genetically at-riskchildren.

The number of detectable islet auto-antibodies correlates with risk. In thehigh-risk birth cohort noted above,symptomatic disease occurred by 15years after seroconversion in 12.7%,61.6%, and 79.1% of children with a sin-gle, two, and three autoantibodies, re-spectively (7) (Fig. 3). In the TEDDYstudy, the 5-year risk of symptomatic di-abetes was 11%, 36%, and 47%, respec-tively, in those with one, two, and threeautoantibodies (9). Faster progressionto symptomatic disease after serocon-version is also observed with youngerage of seroconversion (,3 years) andHLA DR3-DQ2/DR4-DQ8 genotype andin female participants (7,9). In relativesof individuals with type 1 diabetes inDPT-1, the 5-year risk of developingsymptomatic disease with multipleautoantibodies ranged from ;25% fortwo autoantibodies to 40% for threeautoantibodies and 50% for four auto-antibodies (Fig. 4) (8).

On the basis of these observations,universal childhood population–basedscreening for multiple autoantibodieswas initiated in January 2015 in 200,000healthy children at well-child visits atages 3 and 4 years in Bavaria, Germany, inthe Fr1da study (51).Multiple autoantibody-positive children will be offered theopportunity to enroll in an interven-tional clinical trial to arrest diseaseprogression.

The rate of progression to symptom-atic disease in the presence of two ormore islet autoantibodies is asso-ciated not only with the number of

care.diabetesjournals.org Insel and Associates 1967

autoantibodies detected and the ageof autoantibody seroconversion butalso with the magnitude of the autoim-munity titer, affinity of the autoanti-body, and the type of autoantibody(9,42,52–56). Higher titers of insulin andIA-2 autoantibodies are associated withearlier onset of symptomatic type 1 di-abetes. The presence of IA-2 or ZnT8autoantibodies is associated with fasterprogression to symptomatic disease com-pared with when both are absent. In first-degree relatives of individuals with type 1diabetes, IA-2 and/or ZnT8 autoantibody

seroconversion is associatedwith a 5-yearprogression rate to diabetes of 45% (57),and the presence of either of these auto-antibodies is detected in 78% of progres-sors to symptomatic disease (58).

Thus, the presence of two or moreautoantibodies is used as the major cri-terion for stage 1. The majority of indi-viduals (85%) with a single autoantibodydo not progress to overt symptomatictype 1 diabetes within 10 years. How-ever, some single autoantibody subjectscan progress, and progression appearsto occur more frequently in children

aged ,5 years (44,45), if the single au-toantibody is directed to IA-2 (7), or ifthe single autoantibody displays higheraffinity (56,59,60). Assays that preferen-tially detect high-affinity autoantibodiesor detect those single autoantibodiesassociated with progression to symp-tomatic type 1 diabetes are being inves-tigated (56,59–62) and, if validated, maymodify the criteria for the detection oftwo autoantibodies in stage 1 to includedetection of single autoantibodies predic-tive of progression.

STAGE 2: AUTOIMMUNITY1/DYSGLYCEMIA/PRESYMPTOMATICTYPE 1 DIABETES

Stage 2, like stage 1, includes individualswith islet autoantibodies but whosedisease has now progressed to the de-velopment of glucose intolerance, ordysglycemia, that arises from loss offunctional b-cell mass. Dysglycemia inthis stage of type 1 diabetes has beendefined in several studies by impairedfasting plasma glucose of $100 mg/dL($5.6 mmol/L) or $110 mg/dL ($6.2mmol/L), impaired glucose tolerancewith 2-h plasma glucose with a 75-goral glucose tolerance test (OGTT) of$140 mg/dL ($7.8 mmol/L), high glu-cose levels at intermediate time pointson OGTT (30, 60, 90 min levels of $200mg/dL [$11.1 mmol/L]), and/or HbA1c$5.7% ($39 mmol/mol). At this stageof the disease, there is ;60% risk in 2years and ;75% risk in 4–5 years of

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69 38 8 0 399 158 41 3 117 61 21 5

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No. of eventsNo. at riskDiabetesLost to follow-up

No. at riskColoradoFinlandGermany

FinlandColoradoGermany

Figure 2—Progression to symptomatic stage 3 type 1 diabetes from time of islet autoantibody seroconversion in stage 1 at-risk childrenwithmultipleislet autoantibodies (7).

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Figure 3—Probability of progression to stage 3 symptomatic type 1 diabetes stratified fornumber of islet autoantibodies from birth (7).

1968 Scientific Statement Diabetes Care Volume 38, October 2015

developing symptomatic type 1 diabe-tes, with a positive predictive value of96% within 5 years (Fig. 5) (10,63). It isnot clear, however, whether the ADA orthe American Association of Clinical En-docrinologists (AACE) diagnostic labora-tory criteria, which were developed todiagnose prediabetes in the type 2 di-abetes setting (64,65), are the optimalvalues for predicting rate of progressionto onset of symptomatic type 1 diabetes,or stage 3 of type 1 diabetes. Metabolictesting, however, has been the key mea-surement of functional b-cell mass inthis stage of the disease (66,67).There is an accelerated decline in the

first-phase insulin response on intrave-nous glucose tolerance tests during theprogression to type 1 diabetes, whichbecomes especially marked between

1.5 and 0.5 years before diagnosis (68).A first-phase insulin response less thanthe first percentile is associated with a50% risk of developing symptomatictype 1 diabetes within 1 year (69).

Individuals in this stage have, onaverage, a prolonged, gradual metabolicdeterioration with the persistence ofsubstantial b-cell function until at least6 months before type 1 diabetes occurs(70). The 2-h OGTT glucose levels bestpredicted progression to disease in DPT-1(71) but did not begin to change until;0.8 years before diagnosis and thenrose rapidly (72). In high-risk relatives ofindividuals with type 1 diabetes, b-cellglucose sensitivity as measured by theOGTT decreases up to 1.45 years priorto symptomatic disease and correlateswith type 1 diabetes progression

independent of sex, age, BMI, and clinicalrisk (72). Impaired b-cell glucose sensitiv-ity is also prognostic for progression fromprediabetes to type 2 diabetes (73,74). Incontrast, baseline insulin sensitivity, fast-ing insulin secretion, and total postglu-cose insulin output were not predictiveof progression (72). There can be transientreversion from a dysglycemic to a normalOGTT in this setting, but such does notalter the rate of progression to symptom-atic disease in at-risk children (63,75).

A decrease in stimulated C-peptide lagsbehind changes in the OGTT. An accelera-ted decline in stimulated C-peptide levelsis observed;6months prior to symptom-atic type 1 diabetes, with a faster decline3monthsprior to the symptoms (76),whilefasting C-peptide levels are maintained inthenormal rangeduring this period (70). At4 years from the time of a 20% decrease inC-peptide frombaseline, there is a 47% riskof symptomatic type 1 diabetes, with apositive predictive value of symptomatictype 1 diabetes within 5 years of 78% (10).

Increased insulin resistance or de-creased insulin sensitivity can be observedin the later stages of progression to symp-tomatic type 1 diabetes and may contrib-ute to b-cell dysfunction (75,77–79).

Although used as a diagnostic crite-rion for type 2 diabetes, an increasedHbA1c level has variable performanceas a marker for type 1 diabetes. In theprospective DPT-1, TEDDY, Trial to Re-duce IDDM in the Genetically at Risk(TRIGR), and TrialNet Natural Historystudies, HbA1c $6.5% ($48 mmol/mol)had very low sensitivity but high speci-ficity for progression (80). However, in-creasing HbA1c at levels ,6.5% (,48mmol/mol) may be observed in the12–18 months before symptomatic dis-ease and occurs independent of abnor-mal random fasting glucose levels andthe number of autoantibodies. Thus, in-creasing HbA1cmay serve as a biomarkerof type 1 diabetes progression (10,81,82).Analysis of TrialNet Natural History datashowed that a 10% increase in HbA1cabove baseline in subjects with multipleautoantibodies was associated with an84% 3-year risk of developing eitherADA diabetes diagnostic laboratory crite-ria or symptomatic type 1 diabetes, and a20% increase in HbA1c was associatedwith a nearly 100% risk over 3–5 years,with a 5-year positive predictive value of98% (10). In the Finnish HLA at-risk child-hood cohort, a 10% increase in HbA1c

Figure 4—Probability of progression in islet autoantibody-positive relatives of individuals withtype 1 diabetes stratified for number of autoantibodies (8).

Figure 5—Probability of progression from dysglycemia stage 2 in DPT-1. IGT, impaired glucosetolerance (unpublished data from DPT-1 [4,32]).

care.diabetesjournals.org Insel and Associates 1969

levels in samples taken 3–12 monthsapart increased risk 6-fold and predictedthe diagnosis of clinical diabetes (hazardratio5.7),whichhad itsonsetwithamediantime of 1.1 years. In addition, two consecu-tive HbA1c values$5.9% ($41 mmol/mol)were associated with a 12-fold risk (haz-ard ratio 11.9) with a median time untildiagnosis of 0.9 years (82).At-risk children and adults who have

been intensively followed in prospectivenatural history clinical research studieswith monitoring for dysglycemia (i.e.,OGTT, intravenous glucose tolerancetest, HbA1c) are frequently started oninsulin replacement therapy in the ab-sence of symptoms based on exhibitingADA or AACE diagnostic laboratory cri-teria for diabetes. It has not been deter-mined, however, whether the ADA orAACE diabetes diagnostic laboratory cri-teria, which were developed for type 2diabetes, are optimized for recommend-ing initiation of insulin therapy in pre-symptomatic type 1 diabetes.

CURRENT BENEFITS OF STAGINGTYPE 1 DIABETES

There are beneficial short-term clinicaloutcomes for subjects followed pro-spectively in natural history studies. InDAISY, a study of genetically at-risk chil-dren, only 3% of study participants werehospitalized at diagnosis compared with44% of age- and sex-matched childrendiagnosed in the community (83). Inthe TEDDY study, 30% of children aged,5 years were presymptomatic at thetime of diagnosis of type 1 diabetesbased on ADA diagnostic criteria and, ifsymptomatic, were significantly lesslikely to experience DKA at onset thancomparable populations (84). Similarly,in the German BABYDIAB and the Mu-nich Family Study, children who werefollowed after screening positive for is-let autoantibodies had a lower preva-lence of DKA (85). A majority of DPT-1study participants (63.3%) were diag-nosed with type 1 diabetes based onlaboratory metabolic parameters with-out symptoms, with only 3.67% devel-oping DKA (86). In contrast, DKA at onsetof type 1 diabetes was observed in;30% of youth in the population-basedSEARCH for Diabetes in Youth (SEARCH)study (87) and affected 46% of youth atdiagnosis in Colorado in 2012, repre-senting a 55% increase from 1998 to2012 (88). DKA at onset of type 1 diabetes

is associated with increased mortalityand longer hospitalizations; is less likelyto be associated with a partial remis-sion, or “honeymoon phase”; and ismore commonly associated with lowerresidual b-cell function, worse metaboliccontrol, higher insulin requirements, andadverse short-term neurocognitive out-comes (85,89–91).

Children diagnosed through prospec-tive natural history studies of type 1 di-abetes often have better metabolicindicators both at and shortly after thediagnosis, which over the long-termmaymake the disease easier to manage, de-crease hypoglycemic episodes, delaythe development of long-term compli-cations, and decrease cost. Preservationof C-peptide secretion is linked toreduced risk of progression of retinopa-thy, nephropathy, and neuropathy and alower risk of hypoglycemia (92,93).Moreover, intensive diabetes treatmentbegun after the diagnosis of symptom-atic type 1 diabetes improves the likeli-hood of a honeymoon phase (94), helpspatients to maintain higher C-peptidelevels (92), and decreases mortality(95), suggesting that patients who aretreated as early as possible will have im-proved long-term outcomes.

About one-half of diagnosed DPT-1participants had HbA1c levels withinthe normal range with an averageHbA1c value of 6.4% (46 mmol/mol)(86), a figure much less than the 10.9%(96 mmol/mol) average HbA1c value in acohort of children diagnosed in the com-munity (83). A significant proportion ofDPT-1 participants (35.4%) had normalfasting glucose levels at diagnosis, andnearly all (96.6%) had detectableC-peptide levels .0.2 ng/dL (86).DAISY children had lower HbA1c levelsfor at least 1 month and lower insulinrequirements for 12 months after thediagnosis compared with children diag-nosed in the community (83), and chil-dren participating in the DiabetesPrediction in Skane (DiPiS) longitudinalstudy had lower HbA1c levels at 12 and 24months after the diagnosis in the face ofsimilar daily insulin dose requirements (96).

DESIGN OF STAGE-SPECIFICCLINICAL TRIALS TO DELAY ANDPREVENT TYPE 1 DIABETESPROGRESSION

The increasing incidence and prevalenceof type 1 diabetes (12–14), the daily

burden and challenges of living withtype 1 diabetes with poor daily glucoseand metabolic control (97,98), and thesignificant morbidity and prematuremortality of the disease (95,99,100)have catalyzed approaches to preventprogression and onset of symptomaticdisease. The predictable progression oftype 1 diabetes from the onset of auto-immunity to dysglycemia prior to theonset of symptomatic disease may facil-itate the design of smarter, shorter, andless expensive clinical trials using sub-ject stratification and intermediate endpoints (10). Some current clinical trialshave leveraged this concept (Table 2).For example, the TrialNet CTLA4-Ig (aba-tacept) trial (ClinicalTrials.gov identifierNCT01773707) is enrolling subjects whoare autoantibody positive and at risk oftype 1 diabetes at stage 1with transitionto stage 2 as the trial primary outcome.

REFINEMENT OF STAGING

Staging type 1 diabetes and predictingits progressionwill be refined during thisdecade. As described above, improvedassays for detecting autoantibodies,and especially single, high-affinity auto-antibodies, are being developed, and fu-ture efforts will need to focus on theirclinical significance and standardization.Furthermore, in a small number of peo-ple who appear clinically to have type 1diabetes at the time of clinical diagnosis,existing antibody measurements mayfail to detect the presence of autoimmu-nity. Whether these individuals have anautoimmune process to an as-yet-unidentified antigen or another disease,such as monogenic diabetes, is un-known, and studies are ongoing to ex-plore this. Efforts are under way tobetter predict the risk of developmentof autoimmunity and its earliest stagesusing metabolomics (101–105), micro-biome metagenomics (106–110), andtranscriptomics (111,112), amongothers. Decreased levels of phospholi-pids, especially choline-containingphospholipids, in umbilical cord bloodhave been detected in at-risk childrenwho progress to symptomatic type 1diabetes early in life (101–103) and, ifvalidated, may provide informativemarkers for earlier staging. A type I in-terferon signature is detected in HLAgenetically predisposed children priorto the development of autoantibodies(113,114) and may provide a novel

1970 Scientific Statement Diabetes Care Volume 38, October 2015

diagnostic for early risk detection. Theseapproaches may ultimately help todefine a new stage that occurs prior tothe current stage 1.New diagnostic approaches to refine

staging are under development. A ma-jor limitation of detecting islet inflam-mation or insulitis associated with type1 diabetes is the inability to image in-flammation in the pancreas. Refinedislet imaging approaches have demon-strated the ability to detect islet inflam-mation in new-onset type 1 diabetes(115) and will likely be applied toearlier stages of the disease. Analysis ofongoing b-cell destruction by detectingcirculating demethylated insulin DNA isbeing investigated in both new-onsettype 1 diabetes and the at-risk settings,and the assays are being refined and val-idated (116–120). There are also ongoingefforts to integrate and model diversedata (genetic, immunologic, metabolic,age, etc.) to develop composite predictiverisk scores to better predict progression(121–123).For broad application and accep-

tance, it will prove critical to have well-standardized validated biomarker assays.Long-term efforts will need to focus onworking with regulatory authoritiesaround biomarker qualification and

adoption of surrogate biomarkers thatcan substitute for true clinical end pointsfor clinical trials to arrest progression tosymptomatic type 1 diabetes.

CONCLUSIONS ANDRECOMMENDATIONS

Disease staging classification approacheshave been used successfully for other dis-orders and have provided a frameworkfor both diagnosis and therapeutic inter-ventions. The type 1 diabetes staging clas-sification recommendation presentedherein captures the natural history andpredictability of progression in at-risk in-dividuals and provides a framework forresearch and development of preventivetherapies and, ultimately, their adoptionfor clinical care.

At the present time, this classifica-tion system should be used for clinicalresearch where it will aid in design ofrisk screening, clinical trial subjectstratification, and design of naturalhistory and intervention clinical trials,but risk screening and staging as out-lined here are not recommended atthis time for clinical practice in the ab-sence of cost-effective screening, stag-ing, and effective interventions thatdelay progression to symptomatictype 1 diabetes.

Human type 1 diabetes is a contin-uum that can be staged, starting withthe detection of two or more islet auto-antibodies (stage 1) and progressingat a variable rate to a second stage ofglucose intolerance or dysglycemia(stage 2) before becoming clinicallysymptomatic (stage 3). The time of on-set of symptomatic disease can be pre-dicted based on stage-specificbiomarkers. This classification system,which will be continuously refinedwith the development of novel stage-specific biomarkers, provides a newtaxonomy of type 1 diabetes and aframework for clinical trial design,benefit/risk decisions around inter-ventions, and, ultimately, the practiceof precision medicine to prevent symp-tomatic type 1 diabetes.

Acknowledgments. The authors acknowl-edge the contributions of the AACE, theADA, the Endocrine Society, the InternationalSociety for Pediatric and Adolescent Diabetes,JDRF, and The LeonaM. and Harry B. HelmsleyCharitable Trust in the development of thisstaging classification system. Each of theseorganizations endorses the adoption of thestaging classification system that recognizesthe earliest stages of human type 1 diabetesbefore clinical symptoms develop. The au-thors thank Campbell Hutton, Bennie Johnson,

Table 2—Type 1 diabetes stage 1 and 2 intervention clinical trials

Stage TrialClinicalTrials.gov

identifier AgentTarget

population Status Reference

1 DENIS; ENDITNicotinamide

Oral nicotinamide Completed Lampeter et al. (127),Gale et al. (128)

1 DPT-1 NCT00004984 Oral insulin At-riskrelatives

Completed Skyler et al. (32)Oral insulin

1 DIPP NCT00223613 Intranasal insulin At-riskchildren

Completed Nanto-Salonen et al. (129)Intranasal insulin

1 Belgian Diabetes RegistryParenteral insulin

Parenteral insulin At-riskrelatives

Completed Vandemeulebrouckeet al. (130)

1 DiAPREV-IT NCT01122446 Parenteral GAD-alum At-riskchildren

Follow-up Andersson et al. (131)

1 DiAPREV-IT2 NCT02387164 Parenteral GAD-alum;oral vitamin D3

At-riskchildren

Recruiting

1 TrialNet NCT00419562 Oral insulin At-riskrelatives

RecruitingOral insulin

1 TrialNet NCT01773707 Parenteral abatacept At-riskrelatives

RecruitingCTLA4-Ig

1 DVDC NCT00336674 Intranasal insulin At-riskrelatives

RecruitingINIT II

2 DPT-1 NCT00004984 Parenteral insulin At-riskrelatives

Completed DPT-1 Study Group (4)Parenteral insulin

2 TrialNet NCT01030861 Parenteral teplizumab At-riskrelatives

RecruitingAnti-CD3

DVDC, Diabetes Vaccine Development Centre; INIT II, Intranasal Insulin Trial.

care.diabetesjournals.org Insel and Associates 1971

Marjana Marinac, Cynthia Rice, and JessicaRoth of JDRF’s Advocacy staff for their assis-tance in organizing, advising, and champion-ing this effort. The authors thank Erika GebelBerg, PhD (ADA), for her excellent editorialsupport. The authors also thank the NationalInstitutes of Health for providing the manyyears of research funding that produceddata that helped to enable the developmentof this staging classification.Duality of Interest. A.L. is a member of thescientific advisory board for Diamyd Medical AB,Stockholm, Sweden. No other potential conflictsof interest relevant to this article were reported.

References1. Eisenbarth GS. Type I diabetes mellitus. Achronic autoimmune disease. N Engl J Med1986;314:1360–13682. Atkinson MA, Eisenbarth GS. Type 1 diabe-tes: new perspectives on disease pathogenesisand treatment. Lancet 2001;358:221–2293. Atkinson MA, Eisenbarth GS, Michels AW.Type 1 diabetes. Lancet 2014;383:69–824. Diabetes Prevention Trial–Type 1 DiabetesStudy Group. Effect of insulin in relatives of pa-tients with type 1 diabetes mellitus. N Engl JMed 2002;346:1685–16915. Hagopian WA, Lernmark A, Rewers MJ, et al.TEDDYdThe Environmental Determinants ofDiabetes in the Young: an observational clinicaltrial. Ann N Y Acad Sci 2006;1079:320–3266. Skyler JS, GreenbaumCJ, Lachin JM, et al.; Type1 Diabetes TrialNet Study Group. Type 1 DiabetesTrialNetdan international collaborative clinical tri-als network. Ann N Y Acad Sci 2008;1150:14–247. Ziegler AG, Rewers M, Simell O, et al. Sero-conversion to multiple islet autoantibodies andrisk of progression to diabetes in children. JAMA2013;309:2473–24798. Orban T, Sosenko JM, Cuthbertson D, et al.;Diabetes Prevention Trial–Type 1 Study Group.Pancreatic islet autoantibodies as predictorsof type 1 diabetes in the Diabetes PreventionTrial–Type 1. Diabetes Care 2009;32:2269–22749. Steck AK, Vehik K, Bonifacio E, et al.; TEDDYStudy Group. Predictors of progression from theappearance of islet autoantibodies to earlychildhood diabetes: The Environmental Deter-minants of Diabetes in the Young (TEDDY). Di-abetes Care 2015;38:808–81310. Krischer JP; Type 1 Diabetes TrialNet StudyGroup. The use of intermediate endpoints in thedesign of type 1 diabetes prevention trials. Dia-betologia 2013;56:1919–192411. Noble JA, Valdes AM, Cook M, Klitz W,Thomson G, Erlich HA. The role of HLA class IIgenes in insulin-dependent diabetes mellitus:molecular analysis of 180 Caucasian, multiplexfamilies. Am J Hum Genet 1996;59:1134–114812. Patterson CC, Dahlquist GG, Gyurus E,Green A, Soltesz G; EURODIAB Study Group. In-cidence trends for childhood type 1 diabetes inEurope during 1989-2003 and predicted newcases 2005-20: a multicentre prospective regis-tration study. Lancet 2009;373:2027–203313. Harjutsalo V, Sjoberg L, Tuomilehto J. Timetrends in the incidence of type 1 diabetes in Finnishchildren:a cohort study. Lancet2008;371:1777–178214. Vehik K, Hamman RF, Lezotte D, et al. Increas-ing incidenceof type1diabetes in 0- to 17-year-oldColorado youth. Diabetes Care 2007;30:503–509

15. Steck AK, Armstrong TK, Babu SR, EisenbarthGS; Type 1 Diabetes Genetics Consortium. Step-wise or linear decrease in penetrance of type 1diabetes with lower-risk HLA genotypes over thepast 40 years. Diabetes 2011;60:1045–104916. Vehik K, Hamman RF, Lezotte D, et al.Trends in high-risk HLA susceptibility genesamong Colorado youth with type 1 diabetes.Diabetes Care 2008;31:1392–139617. Concannon P, Rich SS, Nepom GT. Geneticsof type 1A diabetes. N Engl J Med 2009;360:1646–165418. Pociot F, McDermott MF. Genetics of type 1diabetes mellitus. Genes Immun 2002;3:235–24919. Santin I, Eizirik DL. Candidate genes for type1 diabetes modulate pancreatic islet inflamma-tion and b-cell apoptosis. Diabetes Obes Metab2013;15(Suppl. 3):71–8120. Lipponen K, Gombos Z, Kiviniemi M, et al.Effect of HLA class I and class II alleles on pro-gression from autoantibody positivity to overttype 1 diabetes in children with risk-associatedclass II genotypes. Diabetes 2010;59:3253–325621. Achenbach P, Hummel M, Thumer L,Boerschmann H, Hofelmann D, Ziegler AG. Char-acteristics of rapid vs slow progression to type 1diabetes in multiple islet autoantibody-positivechildren. Diabetologia 2013;56:1615–162222. Winkler C, Krumsiek J, Lempainen J, et al. Astrategy for combining minor genetic susceptibil-ity genes to improve prediction of disease in type1 diabetes. Genes Immun 2012;13:549–55523. Winkler C, Krumsiek J, Buettner F, et al. Fea-ture ranking of type 1 diabetes susceptibilitygenes improves prediction of type 1 diabetes.Diabetologia 2014;57:2521–252924. Eringsmark Regnell S, Lernmark A. The envi-ronment and theorigins of islet autoimmunityandtype 1 diabetes. Diabet Med 2013;30:155–16025. Craig ME, Nair S, Stein H, Rawlinson WD.Viruses and type 1 diabetes: a new look at anold story. Pediatr Diabetes 2013;14:149–15826. Stene LC, Gale EA. The prenatal environ-ment and type 1 diabetes. Diabetologia 2013;56:1888–189727. TEDDY Study Group. The Environmental De-terminants ofDiabetes in the Young (TEDDY) study:study design. Pediatr Diabetes 2007;8:286–29828. Redondo MJ, Jeffrey J, Fain PR, EisenbarthGS, Orban T. Concordance for islet autoimmu-nity among monozygotic twins. N Engl J Med2008;359:2849–285029. Redondo MJ, Yu L, Hawa M, et al. Hetero-geneity of type I diabetes: analysis of monozy-gotic twins in Great Britain and the UnitedStates. Diabetologia 2001;44:354–36230. Aly TA, Ide A, Jahromi MM, et al. Extremegenetic risk for type 1A diabetes. Proc Natl AcadSci U S A 2006;103:14074–1407931. Gillespie KM, Aitken RJ, Wilson I, WilliamsAJ, Bingley PJ. Early onset of diabetes in theproband is the major determinant of risk inHLA DR3-DQ2/DR4-DQ8 siblings. Diabetes2014;63:1041–104732. Skyler JS, Krischer JP, Wolfsdorf J, et al. Ef-fects of oral insulin in relatives of patients withtype 1 diabetes: the Diabetes Prevention Trial–Type 1. Diabetes Care 2005;28:1068–107633. Mahon JL, Sosenko JM, Rafkin-Mervis L,et al.; TrialNet Natural History Committee;Type 1 Diabetes TrialNet Study Group. The Trial-Net Natural History Study of the Development of

Type 1 Diabetes: objectives, design, and initialresults. Pediatr Diabetes 2009;10:97–10434. Chiang JL, KirkmanMS, Laffel LM, Peters AL;Type 1 Diabetes Sourcebook Authors. Type 1 di-abetes through the life span: a position state-ment of the American Diabetes Association.Diabetes Care 2014;37:2034–205435. Kostraba JN, Gay EC, Cai Y, et al. Incidenceof insulin-dependent diabetes mellitus in Colo-rado. Epidemiology 1992;3:232–23836. The EURODIAB ACE Study Group and theEURODIAB ACE Substudy 2 Study Group. Famil-ial risk of type I diabetes in European children.Diabetologia 1998;41:1151–115637. Hagopian WA, Erlich H, Lernmark A, et al.;TEDDY Study Group. The Environmental Deter-minants of Diabetes in the Young (TEDDY): ge-netic criteria and international diabetes riskscreening of 421 000 infants. Pediatr Diabetes2011;12:733–74338. Lieberman SM, DiLorenzo TP. A compre-hensive guide to antibody and T-cell responsesin type 1 diabetes. Tissue Antigens 2003;62:359–37739. Roep BO, Peakman M. Antigen targets oftype 1 diabetes autoimmunity. Cold SpringHarb Perspect Med 2012;2:a00778140. Ziegler AG, Bonifacio E; BABYDIAB-BABYDIETStudy Group. Age-related islet autoantibody in-cidence in offspring of patients with type 1 di-abetes. Diabetologia 2012;55:1937–194341. Parikka V, Nanto-Salonen K, Saarinen M,et al. Early seroconversion and rapidly increas-ing autoantibody concentrations predict prepu-bertal manifestation of type 1 diabetes inchildren at genetic risk. Diabetologia 2012;55:1926–193642. Krischer JP, LynchKF, SchatzDA, et al.; TEDDYStudy Group. The 6 year incidence of diabetes-associated autoantibodies in genetically at-riskchildren: the TEDDY study. Diabetologia 2015;58:980–98743. Ziegler AG, Hummel M, Schenker M,Bonifacio E. Autoantibody appearance and riskfor development of childhood diabetes in off-spring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB Study.Diabetes 1999;48:460–46844. Hummel M, Bonifacio E, Schmid S, WalterM, Knopff A, Ziegler AG. Brief communication:early appearance of islet autoantibodies pre-dicts childhood type 1 diabetes in offspring ofdiabetic parents. Ann Intern Med 2004;140:882–88645. Chmiel R, Giannopoulou EZ, Winkler C,Achenbach P, Ziegler AG, Bonifacio E. Progres-sion from single to multiple islet autoantibodiesoften occurs soon after seroconversion: impli-cations for early screening. Diabetologia 2015;58:411–41346. Ziegler AG, Standl E, Albert E, Mehnert H.HLA-associated insulin autoantibody formationin newly diagnosed type I diabetic patients. Di-abetes 1991;40:1146–114947. Graham J, Hagopian WA, Kockum I, et al.;Diabetes Incidence in Sweden Study Group;Swedish Childhood Diabetes Study Group. Ge-netic effects on age-dependent onset and isletcell autoantibody markers in type 1 diabetes.Diabetes 2002;51:1346–135548. Delli AJ, Vaziri-Sani F, Lindblad B, et al.;Better Diabetes Diagnosis Study Group. Zinc

1972 Scientific Statement Diabetes Care Volume 38, October 2015

transporter 8 autoantibodies and their associ-ation with SLC30A8 and HLA-DQ genes differbetween immigrant and Swedish patientswith newly diagnosed type 1 diabetes in theBetter Diabetes Diagnosis study. Diabetes2012;61:2556–256449. Vehik K, Haller MJ, Beam CA, et al.; DPT-1Study Group. Islet autoantibody seroconversionin the DPT-1 study: justification for repeatscreening throughout childhood. DiabetesCare 2011;34:358–36250. Vehik K, Beam CA, Mahon JL, et al.; TrialNetNatural History Study Group. Development ofautoantibodies in the TrialNet Natural HistoryStudy. Diabetes Care 2011;34:1897–190151. Insel R, Dunne J, Ziegler A. General popula-tion screening for type 1 diabetes: has its timecome? Curr Opin Endocrinol Diabetes Obes2015;22:270–27652. Achenbach P, Warncke K, Reiter J, et al.Stratification of type 1 diabetes risk on the basisof islet autoantibody characteristics. Diabetes2004;53:384–39253. Achenbach P, Bonifacio E, Koczwara K,Ziegler AG. Natural history of type 1 diabetes.Diabetes 2005;54(Suppl. 2):S25–S3154. Steck AK, Johnson K, Barriga KJ, et al. Age ofislet autoantibody appearance and mean levelsof insulin, but not GAD or IA-2 autoantibodies,predict age of diagnosis of type 1 diabetes: di-abetes autoimmunity study in the young. Dia-betes Care 2011;34:1397–139955. Achenbach P, Koczwara K, Knopff A,Naserke H, Ziegler AG, Bonifacio E. Maturehigh-affinity immune responses to (pro)insulinanticipate the autoimmune cascade that leadsto type 1 diabetes. J Clin Invest 2004;114:589–59756. Yu L, Dong F,Miao D, Fouts AR,Wenzlau JM,Steck AK. Proinsulin/insulin autoantibodiesmeasured with electrochemiluminescent assayare the earliest indicator of prediabetic islet au-toimmunity. Diabetes Care 2013;36:2266–227057. De Grijse J, AsanghanwaM, Nouthe B, et al.;Belgian Diabetes Registry. Predictive power ofscreening for antibodies against insulinoma-associated protein 2 beta (IA-2beta) and zinctransporter-8 to select first-degree relatives oftype 1 diabetic patients with risk of rapid pro-gression to clinical onset of the disease: implica-tions for prevention trials. Diabetologia 2010;53:517–52458. Gorus FK, Balti EV, Vermeulen I, et al.;Belgian Diabetes Registry. Screening for insuli-noma antigen 2 and zinc transporter 8 autoanti-bodies: a cost-effective and age-independentstrategy to identify rapid progressors to clinicalonset among relatives of type 1 diabetic pa-tients. Clin Exp Immunol 2013;171:82–9059. Miao D, Steck AK, Zhang L, et al.; Type 1Diabetes TrialNet Study Group. Electrochemilu-minescence assays for insulin and glutamic aciddecarboxylase autoantibodies improve predic-tion of type 1 diabetes risk. Diabetes TechnolTher 2015;17:119–12760. Bingley PJ, Williams AJ. Islet autoantibodytesting: an end to the trials and tribulations?Diabetes 2013;62:4009–401161. Yu L, Miao D, Scrimgeour L, Johnson K,Rewers M, Eisenbarth GS. Distinguishing per-sistent insulin autoantibodies with differentialrisk: nonradioactive bivalent proinsulin/insulin

autoantibody assay. Diabetes 2012;61:179–18662. Miao D, Guyer KM, Dong F, et al. GAD65autoantibodies detected by electrochemilumi-nescence assay identify high risk for type 1 di-abetes. Diabetes 2013;62:4174–417863. Sosenko JM, Palmer JP, Rafkin-Mervis L,et al.; Diabetes Prevention Trial–Type 1 StudyGroup. Incident dysglycemia and progression totype 1 diabetes among participants in the Di-abetes Prevention Trial–Type 1. Diabetes Care2009;32:1603–160764. American Diabetes Association. Classifica-tion and diagnosis of diabetes. Sec. 2. In Stand-ards of Medical Care in Diabetesd2015.Diabetes Care 2015;38(Suppl. 1):S8–S1665. Handelsman Y, Bloomgarden ZT, GrunbergerG, et al. American Association of ClinicalEndocrinologists and American College ofEndocrinologydclinical practice guidelines fordeveloping a diabetes mellitus comprehen-sive care pland2015. Endocr Pract 2015;21(Suppl. 1):1–8766. Greenbaum CJ, Buckingham B, Chase HP,Krischer J; Diabetes Prevention Trial, Type 1 Di-abetes (DPT-1) Study Group. Metabolic tests todetermine risk for type 1 diabetes in clinicaltrials. Diabetes Metab Res Rev 2011;27:584–58967. Sosenko JM, Skyler JS, Herold KC, Palmer JP;Type 1 Diabetes TrialNet and Diabetes Preven-tion Trial–Type 1 Study Groups. The metabolicprogression to type 1 diabetes as indicated byserial oral glucose tolerance testing in the Di-abetes Prevention Trial–Type 1. Diabetes 2012;61:1331–133768. Sosenko JM, Skyler JS, Beam CA, et al.; Type1 Diabetes TrialNet and Diabetes Prevention Trial–Type1StudyGroups. Acceleration of the loss of thefirst-phase insulin response during the progres-sion to type 1 diabetes in Diabetes PreventionTrial–Type 1 participants. Diabetes 2013;62:4179–418369. Vardi P, Crisa L, Jackson RA. Predictive valueof intravenous glucose tolerance test insulin se-cretion less than or greater than the first per-centile in islet cell antibody positive relatives oftype 1 (insulin-dependent) diabetic patients. Di-abetologia 1991;34:93–10270. Sosenko JM, Palmer JP, Greenbaum CJ,et al. Patterns of metabolic progression totype 1 diabetes in the Diabetes PreventionTrial–Type 1. Diabetes Care 2006;29:643–64971. Xu P, Wu Y, Zhu Y, et al.; Diabetes Preven-tion Trial–Type 1 (DPT-1) Study Group. Prognos-tic performance of metabolic indexes inpredicting onset of type 1 diabetes. DiabetesCare 2010;33:2508–251372. Ferrannini E, Mari A, Nofrate V, SosenkoJM, Skyler JS; DPT-1 Study Group. Progressionto diabetes in relatives of type 1 diabetic pa-tients: mechanisms and mode of onset. Diabe-tes 2010;59:679–68573. Walker M, Mari A, Jayapaul MK, BennettSM, Ferrannini E. Impaired beta cell glucose sen-sitivity and whole-body insulin sensitivity aspredictors of hyperglycaemia in non-diabeticsubjects. Diabetologia 2005;48:2470–247674. Cnop M, Vidal J, Hull RL, et al. Progressiveloss of beta-cell function leads to worseningglucose tolerance in first-degree relatives ofsubjects with type 2 diabetes. Diabetes Care2007;30:677–682

75. Sosenko JM, Skyler JS, Krischer JP, et al.;Diabetes Prevention Trial–Type 1 Study Group.Glucose excursions between states of glycemiawith progression to type 1 diabetes in the Di-abetes Prevention Trial–Type 1 (DPT-1). Diabe-tes 2010;59:2386–238976. Sosenko JM, Palmer JP, Rafkin-Mervis L,et al. Glucose and C-peptide changes in the peri-onset period of type 1 diabetes in the DiabetesPrevention Trial–Type 1. Diabetes Care 2008;31:2188–219277. Fourlanos S, Narendran P, Byrnes GB,Colman PG, Harrison LC. Insulin resistance is arisk factor for progression to type 1 diabetes.Diabetologia 2004;47:1661–166778. Xu P, Cuthbertson D, Greenbaum C, PalmerJP, Krischer JP; Diabetes Prevention Trial–Type 1Study Group. Role of insulin resistance in pre-dicting progression to type 1 diabetes. DiabetesCare 2007;30:2314–232079. Bingley PJ, Mahon JL, Gale EA; EuropeanNicotinamide Diabetes Intervention TrialGroup. Insulin resistance and progression totype 1 diabetes in the European NicotinamideDiabetes Intervention Trial (ENDIT). DiabetesCare 2008;31:146–15080. Vehik K, Cuthbertson D, Boulware D, et al.;TEDDY, TRIGR, Diabetes Prevention Trial–Type1, and Type 1 Diabetes TrialNet Natural HistoryStudy Groups. Performance of HbA1c as an earlydiagnostic indicator of type 1 diabetes in chil-dren and youth. Diabetes Care 2012;35:1821–182581. Stene LC, Barriga K, Hoffman M, et al. Nor-mal but increasing hemoglobin A1c levels pre-dict progression from islet autoimmunity toovert type 1 diabetes: Diabetes AutoimmunityStudy in the Young (DAISY). Pediatr Diabetes2006;7:247–25382. Helminen O, Aspholm S, Pokka T, et al.HbA1c predicts time to diagnosis of type 1 di-abetes in children at risk. Diabetes 2015;64:1719–172783. Barker JM, Goehrig SH, Barriga K, et al.;DAISY Study. Clinical characteristics of childrendiagnosed with type 1 diabetes through inten-sive screening and follow-up. Diabetes Care2004;27:1399–140484. Elding Larsson H, Vehik K, Bell R, et al.;TEDDY Study Group; SEARCH Study Group;Swediabkids Study Group; DPV Study Group;Finnish Diabetes Registry Study Group. Reducedprevalence of diabetic ketoacidosis at diagnosisof type 1 diabetes in young children participat-ing in longitudinal follow-up. Diabetes Care2011;34:2347–235285. Winkler C, Schober E, Ziegler AG, Holl RW.Markedly reduced rate of diabetic ketoacidosisat onset of type 1 diabetes in relatives screenedfor islet autoantibodies. Pediatr Diabetes 2012;13:308–31386. Triolo TM, Chase HP, Barker JM; DPT-1Study Group. Diabetic subjects diagnosedthrough the Diabetes Prevention Trial–Type 1(DPT-1) are often asymptomatic with normalA1C at diabetes onset. Diabetes Care 2009;32:769–77387. Dabelea D, Rewers A, Stafford JM, et al.;SEARCH for Diabetes in Youth Study Group.Trends in the prevalence of ketoacidosis at di-abetes diagnosis: the SEARCH for Diabetes inYouth study. Pediatrics 2014;133:e938–e945

care.diabetesjournals.org Insel and Associates 1973

88. Rewers A, Dong F, Slover RH, KlingensmithGJ, RewersM. Incidence of diabetic ketoacidosisat diagnosis of type 1 diabetes in Coloradoyouth, 1998-2012. JAMA 2015;313:1570–157289. Fernandez Casta~ner M, Monta~na E, Camps I,et al. Ketoacidosis at diagnosis is predictive oflower residual beta-cell function and poor meta-bolic control in type 1 diabetes. Diabetes Metab1996;22:349–35590. Bowden SA, Duck MM, Hoffman RP. Youngchildren (,5 yr) and adolescents (.12 yr) withtype 1 diabetes mellitus have low rate of partialremission: diabetic ketoacidosis is an importantrisk factor. Pediatr Diabetes 2008;9:197–20191. Cameron FJ, Scratch SE, Nadebaum C, et al.;DKA Brain Injury Study Group. Neurological con-sequences of diabetic ketoacidosis at initial pre-sentation of type 1 diabetes in a prospectivecohort study of children. Diabetes Care 2014;37:1554–156292. The Diabetes Control and ComplicationsTrial Research Group. Effect of intensive ther-apy on residual beta-cell function in patientswith type 1 diabetes in the diabetes controland complications trial. A randomized, con-trolled trial. Ann Intern Med 1998;128:517–52393. Steffes MW, Sibley S, Jackson M, ThomasW. Beta-cell function and the development ofdiabetes-related complications in the diabetescontrol and complications trial. Diabetes Care2003;26:832–83694. Ludvigsson J, Heding LG, Larsson Y, Leander E.C-peptide in juvenile diabetics beyond the postini-tial remission period. Relation to clinical manifesta-tions at onset of diabetes, remission and diabeticcontrol. Acta Paediatr Scand 1977;66:177–18495. Orchard TJ, Nathan DM, Zinman B, et al.;Writing Group for the DCCT/EDIC ResearchGroup. Association between 7 years of intensivetreatment of type 1 diabetes and long-termmortality. JAMA 2015;313:45–5396. Lundgren M, Sahlin A, Svensson C, et al.;DiPiS Study Group. Reduced mortality at diag-nosis and improved glycemic control in childrenpreviously enrolled in DiPiS follow-up. PediatrDiabetes 2014;15:494–50197. Wood JR, Miller KM, Maahs DM, et al.; T1DExchange Clinic Network. Most youth with type1 diabetes in the T1D Exchange clinic registry donot meet American Diabetes Association or In-ternational Society for Pediatric and AdolescentDiabetes clinical guidelines. Diabetes Care 2013;36:2035–203798. Naughton MJ, Yi-Frazier JP, Morgan TM,et al.; SEARCH for Diabetes in Youth StudyGroup. Longitudinal associations between sex,diabetes self-care, and health-related quality oflife among youth with type 1 or type 2 diabetesmellitus. J Pediatr 2014;164:1376–1383.e199. Livingstone SJ, Levin D, Looker HC, et al.;Scottish Diabetes Research Network Epidemiol-ogy Group; Scottish Renal Registry. Estimatedlife expectancy in a Scottish cohort with type 1diabetes, 2008-2010. JAMA 2015;313:37–44100. Lind M, Svensson AM, Kosiborod M, et al.Glycemic control and excess mortality in type 1diabetes. N Engl J Med 2014;371:1972–1982101. Oresic M, Simell S, Sysi-Aho M, et al. Dys-regulation of lipid and amino acid metabolismprecedes islet autoimmunity in children wholater progress to type 1 diabetes. J Exp Med2008;205:2975–2984

102. Oresic M, Gopalacharyulu P, Mykkanen J,et al. Cord serum lipidome in prediction of isletautoimmunity and type 1 diabetes. Diabetes2013;62:3268–3274103. La Torre D, Seppanen-Laakso T, LarssonHE, et al.; DiPiS Study Group. Decreased cord-blood phospholipids in young age-at-onset type1 diabetes. Diabetes 2013;62:3951–3956104. Oresic M. Metabolomics in the studies ofislet autoimmunity and type 1 diabetes. Rev Di-abet Stud 2012;9:236–247105. Lee HS, Burkhardt BR, McLeod W, et al.;TEDDY Study Group. Biomarker discovery studydesign for type 1 diabetes in The EnvironmentalDeterminants of Diabetes in the Young (TEDDY)study. Diabetes Metab Res Rev 2014;30:424–434106. Dunne JL, Triplett EW, Gevers D, et al. Theintestinal microbiome in type 1 diabetes. ClinExp Immunol 2014;177:30–37107. Giongo A, Gano KA, Crabb DB, et al. To-ward defining the autoimmune microbiome fortype 1 diabetes. ISME J 2011;5:82–91108. de Goffau MC, Fuentes S, van den BogertB, et al. Aberrant gut microbiota composition atthe onset of type 1 diabetes in young children.Diabetologia 2014;57:1569–1577109. Endesfelder D, zu Castell W, Ardissone A,et al. Compromised gut microbiota networks inchildren with anti-islet cell autoimmunity. Dia-betes 2014;63:2006–2014110. Kostic AD, Gevers D, Siljander H, et al.;DIABIMMUNE Study Group. The dynamics ofthe human infant gut microbiome in develop-ment and in progression toward type 1 diabe-tes. Cell Host Microbe 2015;17:260–273111. Levy H, Wang X, Kaldunski M, et al. Tran-scriptional signatures as a disease-specific andpredictive inflammatory biomarker for type 1diabetes. Genes Immun 2012;13:593–604112. Chen YG, Cabrera SM, Jia S, et al. Molecu-lar signatures differentiate immune states intype 1 diabetic families. Diabetes 2014;63:3960–3973113. Ferreira RC, Guo H, Coulson RM, et al. Atype I interferon transcriptional signature pre-cedes autoimmunity in children genetically atrisk for type 1 diabetes. Diabetes 2014;63:2538–2550114. Kallionpaa H, Elo LL, Laajala E, et al. Innateimmune activity is detected prior to serocon-version in children with HLA-conferred type 1diabetes susceptibility. Diabetes 2014;63:2402–2414115. Gaglia JL, Harisinghani M, Aganj I, et al.Noninvasive mapping of pancreatic inflamma-tion in recent-onset type-1 diabetes patients.Proc Natl Acad Sci U S A 2015;112:2139–2144116. Akirav EM, Lebastchi J, Galvan EM, et al.Detection of b cell death in diabetes using dif-ferentially methylated circulating DNA. ProcNatl Acad Sci U S A 2011;108:19018–19023117. Husseiny MI, Kuroda A, Kaye AN, Nair I,Kandeel F, Ferreri K. Development of a quanti-tative methylation-specific polymerase chainreaction method for monitoring beta cell deathin type 1 diabetes. PLoS One 2012;7:e47942118. Usmani-Brown S, Lebastchi J, Steck AK,Beam C, Herold KC, Ledizet M. Analysis ofb-cell death in type 1 diabetes by droplet digitalPCR. Endocrinology 2014;155:3694–3698119. FisherMM, Perez Chumbiauca CN,MatherKJ, Mirmira RG, Tersey SA. Detection of islet

b-cell death in vivo by multiplex PCR analysisof differentiallymethylated DNA. Endocrinology2013;154:3476–3481120. Herold KC, Usmani-Brown S, Ghazi T, et al.;Type 1 Diabetes TrialNet Study Group. b Celldeath and dysfunction during type 1 diabetesdevelopment in at-risk individuals. J Clin Invest2015;125:1163–1173121. Sosenko JM, Krischer JP, Palmer JP, et al.;Diabetes Prevention Trial–Type 1 Study Group.A risk score for type 1 diabetes derived fromautoantibody-positive participants in the Diabe-tes Prevention Trial–Type 1. Diabetes Care2008;31:528–533122. Sosenko JM, Skyler JS, Palmer JP, et al.;Type 1 Diabetes TrialNet Study Group; DiabetesPrevention Trial–Type 1 Study Group. The pre-diction of type 1 diabetes by multiple autoanti-body levels and their incorporation into anautoantibody risk score in relatives of type 1diabetic patients. Diabetes Care 2013;36:2615–2620123. Sosenko JM, Skyler JS, DiMeglio LA, et al.;Type 1 Diabetes TrialNet Study Group; DiabetesPrevention Trial–Type 1 Study Group. A newapproach for diagnosing type 1 diabetes inautoantibody-positive individuals based on pre-diction and natural history. Diabetes Care 2015;38:271–276124. Walter M, Albert E, Conrad M, et al.IDDM2/insulin VNTR modifies risk conferred byIDDM1/HLA for development of type 1 diabetesand associated autoimmunity. Diabetologia2003;46:712–720125. Schenker M, Hummel M, Ferber K, et al.Early expression and high prevalence of isletautoantibodies for DR3/4 heterozygous andDR4/4 homozygous offspring of parents withtype I diabetes: the German BABYDIAB study.Diabetologia 1999;42:671–677126. Bonifacio E, HummelM,WalterM, SchmidS, Ziegler AG. IDDM1 andmultiple family historyof type 1 diabetes combine to identify neonatesat high risk for type 1 diabetes. Diabetes Care2004;27:2695–2700127. Lampeter EF, Klinghammer A, ScherbaumWA, et al.; DENIS Group. The Deutsche Nico-tinamide Intervention Study: an attempt toprevent type 1 diabetes. Diabetes 1998;47:980–984128. Gale EA, Bingley PJ, Emmett CL, Collier T;European Nicotinamide Diabetes InterventionTrial (ENDIT) Group. European Nicotinamide Di-abetes Intervention Trial (ENDIT): a randomisedcontrolled trial of intervention before the onsetof type 1 diabetes. Lancet 2004;363:925–931129. Nanto-Salonen K, Kuplia A, Simell S, et al.Nasal insulin to prevent type 1 diabetes in chil-dren with HLA genotypes and autoantibodiesconferring increased risk of disease: a double-blind, randomised controlled trial. Lancet 2008;372:1746–1755130. Vandemeulebroucke E, Gorus FK,Decochez K, et al.; Belgian Diabetes Registry.Insulin treatment in IA-2A-positive relatives oftype 1 diabetic patients. Diabetes Metab 2009;35:319–327131. Andersson C, Carlsson A, Cilio C, et al.; Di-APREV-IT Study Group. Glucose tolerance andbeta-cell function in islet autoantibody-positivechildren recruited to a secondary preventionstudy. Pediatr Diabetes 2013;14:341–349

1974 Scientific Statement Diabetes Care Volume 38, October 2015