Performance of HbA1c as an early diagnostic indicator of type 1 diabetes in children and youth

Type 1 Diabetes Screening and Diagnosis

Those with concerning signs or symptoms should be evaluated for type 1 diabetes (T1D). Those with first-degree relatives with T1D or based on the presence of high-risk genes are at increased risk and benefit from screening. Universal screening should be considered in light of new potential therapies to delay disease progression. Although oral glucose tolerance test is the gold standard for T1D staging, there are multiple tools available when oral glucose tolerance test is not feasible. Risk score calculations increase the ability to predict disease progression. Testing should be repeated when symptoms of overt diabetes mellitus are not present.

Discordance between Glucose Management Indicator and Glycated Hemoglobin in a Pediatric Cohort with Type 1 Diabetes: A Real-World Study

The introduction of continuous glucose monitoring (CGM) systems in clinical practice has allowed a more detailed picture of the intra- and interdaily glycemic fluctuations of individuals with type 1 diabetes (T1D). However, CGM-measured glucose control indicators may be occasionally inaccurate. This study aims to assess the discrepancy between the glucose management indicator (GMI) and glycated hemoglobin (HbA1c) (ΔGMI-HbA1c) within a cohort of children and adolescents with T1D, exploring its correlation with other CGM metrics and blood count parameters. In this single-center, cross-sectional study, we gathered demographic and clinical data, including blood count parameters, HbA1c values, and CGM metrics, from 128 pediatric subjects with T1D (43% female; mean age, 13.4 ± 3.6 years). Our findings revealed higher levels of the coefficient of variation (CV) (p < 0.001) and time above range > 250 mg/dL (p = 0.033) among subjects with ΔGMI-HbA1c > 0.3%. No association was observed between blood count parameters and ΔGMI-HbA1c. In conclusion, despite the advancements and the widespread adoption of CGM systems, HbA1c remains an essential parameter for the assessment of glycemic control, especially in individuals with suboptimal metabolic control and extreme glycemic variability.

Continuous glucose monitoring has an increasing role in pre-symptomatic type 1 diabetes: advantages, limitations, and comparisons with laboratory-based testing

Type 1 diabetes (T1D) is well-recognised as a continuum heralded by the development of islet autoantibodies, progression to islet autoimmunity causing beta cell destruction, culminating in insulin deficiency and clinical disease. Abnormalities of glucose homeostasis are known to exist well before the onset of typical symptoms. Laboratory-based tests such as the oral glucose tolerance test (OGTT) and glycated haemoglobin (HbA1c) have been used to stage T1D and assess the risk of progression to clinical T1D. Continuous glucose monitoring (CGM) can detect early glycaemic abnormalities and can therefore be used to monitor for metabolic deterioration in pre-symptomatic, islet autoantibody positive, at-risk individuals. Early identification of these children can not only reduce the risk of presentation with diabetic ketoacidosis (DKA), but also determine eligibility for prevention trials, which aim to prevent or delay progression to clinical T1D. Here, we describe the current state with regard to the use of the OGTT, HbA1c, fructosamine and glycated albumin in pre-symptomatic T1D. Using illustrative cases, we present our clinical experience with the use of CGM, and advocate for an increased role of this diabetes technology, for monitoring metabolic deterioration and disease progression in children with pre-symptomatic T1D.

Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity

Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.

HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children

OBJECTIVE

Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study.

RESEARCH DESIGN AND METHODS

A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age.

RESULTS

It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p < 0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p = 0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p = 0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p < 0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p < 0.001).

CONCLUSION

In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.

Rising Hemoglobin A1c in the Nondiabetic Range Predicts Progression of Type 1 Diabetes As Well As Oral Glucose Tolerance Tests

OBJECTIVE

Biomarkers predicting risk of type 1 diabetes (stage 3) among children with islet autoantibodies are greatly needed to prevent diabetic ketoacidosis and facilitate prevention therapies.

RESEARCH DESIGN AND METHODS

Children in the prospective The Environmental Determinants of Diabetes in the Young (TEDDY) study (n = 707) with confirmed diabetes-associated autoantibodies (GAD antibody, IA-2A, and/or insulin autoantibody) and two or more HbA1c measurements were followed to diabetes or median age 11.1 years. Once confirmed autoantibody positive, HbA1c was measured quarterly. Cox models and receiver operative characteristic curve analyses revealed the prognostic utility for risk of stage 3 on a relative HbA1c increase from the baseline visit or an oral glucose tolerance test (OGTT) 2-h plasma glucose (2-hPG). This HbA1c approach was then validated in the Type 1 Diabetes TrialNet Pathway to Prevention Study (TrialNet) (n = 1,190).

RESULTS

A 10% relative HbA1c increase from baseline best marked the increased risk of stage 3 in TEDDY (74% sensitive; 88% specific). Significant predictors of risk for HbA1c change were age and HbA1c at the baseline test, genetic sex, maximum number of autoantibodies, and maximum rate of HbA1c increase by time of change. The multivariable model featuring a HbA1c ≥10% increase and these additional factors revealed increased risk of stage 3 in TEDDY (hazard ratio [HR] 12.74, 95% CI 8.7-18.6, P < 0.0001) and TrialNet (HR 5.09, 95% CI 3.3-7.9, P < 0.0001). Furthermore, the composite model using HbA1c ≥10% increase performed similarly to an OGTT 2-hPG composite model (TEDDY area under the curve [AUC] 0.88 and 0.85, respectively) and to the HbA1c model in TrialNet (AUC 0.82).

CONCLUSIONS

An increase of ≥10% in HbA1c from baseline is as informative as OGTT 2-hPG in predicting risk of stage 3 in youth with genetic risk and diabetes-associated autoantibodies.

Index60 Is Superior to HbA1c for Identifying Individuals at High Risk for Type 1 Diabetes

CONTEXT

HbA1c from ≥ 5.7% to < 6.5% (39-46 mmol/mol) indicates prediabetes according to American Diabetes Association guidelines, yet its identification of prediabetes specific for type 1 diabetes has not been assessed. A composite glucose and C-peptide measure, Index60, identifies individuals at high risk for type 1 diabetes.

OBJECTIVE

We compared Index60 and HbA1c thresholds as markers for type 1 diabetes risk.

METHODS

TrialNet Pathway to Prevention study participants with ≥ 2 autoantibodies (GADA, IAA, IA-2A, or ZnT8A) who had oral glucose tolerance tests and HbA1c measurements underwent 1) predictive time-dependent modeling of type 1 diabetes risk (n = 2776); and 2) baseline comparisons between high-risk mutually exclusive groups: Index60 ≥ 2.04 (n = 268) vs HbA1c ≥ 5.7% (n = 268). The Index60 ≥ 2.04 threshold was commensurate in ordinal ranking with the standard prediabetes threshold of HbA1c ≥ 5.7%.

RESULTS

In mutually exclusive groups, individuals exceeding Index60 ≥ 2.04 had a higher cumulative incidence of type 1 diabetes than those exceeding HbA1c ≥ 5.7% (P < 0.0001). Appreciably more individuals with Index60 ≥ 2.04 were at stage 2, and among those at stage 2, the cumulative incidence was higher for those with Index60 ≥ 2.04 (P = 0.02). Those with Index60 ≥ 2.04 were younger, with lower BMI, greater autoantibody number, and lower C-peptide than those with HbA1c ≥ 5.7% (P < 0.0001 for all comparisons).

CONCLUSION

Individuals with Index60 ≥ 2.04 are at greater risk for type 1 diabetes with features more characteristic of the disorder than those with HbA1c ≥ 5.7%. Index60 ≥ 2.04 is superior to the standard HbA1c ≥ 5.7% threshold for identifying prediabetes in autoantibody-positive individuals. These findings appear to justify using Index60 ≥ 2.04 as a prediabetes criterion in this population.

Evaluating T cell responses prior to the onset of type 1 diabetes

AIMS

In the current study we aimed to evaluat T cell phenotypes and metabolic profiles in high-risk individuals who progressed to type 1 diabetes compared to those remaining disease free.

METHODS

A Fluorspot assay was used to examine T cell responses to a panel of islet autoantigen peptides in samples obtained 6- and 30-months preceding disease onset and at the same timepoints in non-progressors.

RESULTS

We noted a significant increase in the magnitude of the proinflammatory interferon-γ response to proinsulin and insulin peptides in individuals who progressed to type 1 diabetes. In contrast, in the non-progressors, we observed an increase in the regulatory IL-10 response to proinsulin peptides. Furthermore, the T cell responses to the islet peptide panel predisposed towards a proinflammatory interferon-γ bias in the progressors.

CONCLUSIONS

Collectively, these data suggest that a proinflammatory T cell response is prevalent in high-risk individuals who progress to type 1 diabetes and can be detected up to 6 months prior to onset of disease. This observation, albeit in a small cohort, can potentially be harnessed in disease staging, particularly in identifying autoantibody-positive individuals transitioning from stage 2 (dysglycemia present and pre-symptomatic) to stage 3 (dysglycemia present and symptomatic). The detection of these different T cell phenotypes in progressors and non-progressors suggests the presence of disease endotypes.

Continuous Glucose Monitoring Profiles in Healthy, Nondiabetic Young Children

Context

Continuous glucose monitoring (CGM) is increasingly being used for both day-to-day management in patients with diabetes and in clinical research. While data on glycemic profiles of healthy, non-diabetic individuals exists, data on non-diabetic very young children are lacking.

Objective

To establish reference sensor glucose ranges in healthy, non-diabetic young children, using a current generation CGM sensor.

Design

Prospective observational study

Setting

Institutional practice

Participants

Healthy, non-diabetic children 1-6 years old; with normal body mass index

Intervention

A blinded Dexcom G6 Pro CGM was worn for approximately 10 days by each participant.

Main Outcome Measure

CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability

Results

39 participants were included in the analyses. Mean average glucose was 103 mg/dL (5.7 mmol/L). Median % time between 70-140 mg/dL (3.9-7.8 mmol/L) was 96% (IQR 92%-97%), mean within-individual coefficient of variation was 17±3%, median time spent with glucose levels &gt;140mg/dL was 3.4% (49 min/day), and median time &lt;70 mg/dL (3.9 mmol/L) was 0.4% (6 min/day).

Conclusions

Collecting normative sensor glucose data and describing glycemic measures for young children fills an important informational gap and will be useful as a benchmark for future clinical studies.

Heterogeneity of DKA Incidence and Age-Specific Clinical Characteristics in Children Diagnosed With Type 1 Diabetes in the TEDDY Study

OBJECTIVE

The Environmental Determinants of Diabetes in the Young (TEDDY) study is uniquely capable of investigating age-specific differences associated with type 1 diabetes. Because age is a primary driver of heterogeneity in type 1 diabetes, we sought to characterize by age metabolic derangements prior to diagnosis and clinical features associated with diabetic ketoacidosis (DKA).

RESEARCH DESIGN AND METHODS

The 379 TEDDY children who developed type 1 diabetes were grouped by age at onset (0-4, 5-9, and 10-14 years; n = 142, 151, and 86, respectively) with comparisons of autoantibody profiles, HLAs, family history of diabetes, presence of DKA, symptomatology at onset, and adherence to TEDDY protocol. Time-varying analysis compared those with oral glucose tolerance test data with TEDDY children who did not progress to diabetes.

RESULTS

Increasing fasting glucose (hazard ratio [HR] 1.09 [95% CI 1.04-1.14]; P = 0.0003), stimulated glucose (HR 1.50 [1.42-1.59]; P < 0.0001), fasting insulin (HR 0.89 [0.83-0.95]; P = 0.0009), and glucose-to-insulin ratio (HR 1.29 [1.16-1.43]; P < 0.0001) were associated with risk of progression to type 1 diabetes. Younger children had fewer autoantibodies with more symptoms at diagnosis. Twenty-three children (6.1%) had DKA at onset, only 1 (0.97%) of 103 with and 22 (8.0%) of 276 children without a first-degree relative (FDR) with type 1 diabetes (P = 0.008). Children with DKA were more likely to be nonadherent to study protocol (P = 0.047), with longer duration between their last TEDDY evaluation and diagnosis (median 10.2 vs. 2.0 months without DKA; P < 0.001).

CONCLUSIONS

DKA at onset in TEDDY is uncommon, especially for FDRs. For those without familial risk, metabolic monitoring continues to provide a primary benefit of reduced DKA but requires regular follow-up. Clinical and laboratory features vary by age at onset, adding to the heterogeneity of type 1 diabetes.

CGM Metrics Predict Imminent Progression to Type 1 Diabetes: Autoimmunity Screening for Kids (ASK) Study

OBJECTIVE

Children identified with stage 1 type 1 diabetes are at high risk for progressing to stage 3 (clinical) diabetes and require accurate monitoring. Our aim was to establish continuous glucose monitoring (CGM) metrics that could predict imminent progression to diabetes.

RESEARCH DESIGN AND METHODS

In the Autoimmunity Screening for Kids study, 91 children who were persistently islet autoantibody positive (median age 11.5 years; 48% non-Hispanic White; 57% female) with a baseline CGM were followed for development of diabetes for a median of 6 (range 0.2-34) months. Of these, 16 (18%) progressed to clinical diabetes in a median of 4.5 (range 0.4-29) months.

RESULTS

Compared with children who did not progress to clinical diabetes (nonprogressors), those who did (progressors) had significantly higher average sensor glucose levels (119 vs. 105 mg/dL, P < 0.001) and increased glycemic variability (SD 27 vs. 16, coefficient of variation, 21 vs. 15, mean of daily differences 24 vs. 16, and mean amplitude of glycemic excursions 43 vs. 26, all P < 0.001). For progressors, 21% of the time was spent with glucose levels >140 mg/dL (TA140) and 8% of time >160 mg/dL, compared with 3% and 1%, respectively, for nonprogressors. In survival analyses, the risk of progression to diabetes in 1 year was 80% in those with TA140 >10%; in contrast, it was only 5% in the other participants. Performance of prediction by receiver operating curve analyses showed area under the curve of ≥0.89 for both individual and combined CGM metric models.

CONCLUSIONS

TA140 >10% is associated with a high risk of progression to clinical diabetes within the next year in autoantibody-positive children. CGM should be included in the ongoing monitoring of high-risk children and could be used as potential entry criterion for prevention trials.

Replacing insulin with immunotherapy: Time for a paradigm change in Type 1 diabetes

For almost a hundred years, the management of Type 1 diabetes has not advanced beyond insulin replacement. However, insulin does not provide satisfactory glycaemic control in the majority of individuals and there remains a major unmet need for novel treatments for Type 1 diabetes. Immunomodulation to preserve beta-cell function offers the prospect of making treatment with insulin easier and/or preventing the need for insulin, particularly when it comes to novel low-risk immunotherapies. Led by the concept that the best insulin-producing cell is a patient's own beta-cell, the Type 1 diabetes scientific community has a challenging task ahead-to fundamentally change the management of this devastating disease by using low-risk immunotherapy to preserve endogenous beta-cell function and make metabolic control substantially easier. In that way, insulin and/or beta-cell replacement (stem cell or transplantation) should in the future be considered rescue therapies reserved for delayed presentations.

Increasing plasma glucose before the development of type 1 diabetes-the TRIGR study

OBJECTIVE

The β-cell stress hypothesis suggests that increased insulin demand contributes to the development of type 1 diabetes. In the TRIGR trial we set out to assess the profile of plasma glucose and HbA1c before the diagnosis of clinical diabetes compared to nondiabetic children.

RESEARCH DESIGN AND METHODS

A cohort of children (N = 2159) with an affected first-degree relative and increased HLA risk were recruited 2002-2007 and followed until 2017. To study the relationship between plasma glucose/HbA1c and the development of autoantibodies or clinical disease Kaplan-Meir curves were developed. Mixed models were constructed for plasma glucose and HbA1c separately.

RESULTS

A family history of type 2 diabetes was related to an increase in plasma glucose (p < 0.001). An increase in glucose from the previous sample predicted clinical diabetes (p < 0.001) but not autoantibodies. An increase of HbA1c of 20% or 30% from the previous sample predicted the development of any autoantibody (p < 0.003 resp <0.001) and the development of diabetes (p < 0.002 resp <0.001. Participants without autoantibodies had lower HbA1c (mean 5.18%, STD 0.24; mean 33.08 mmol/mol, STD 2.85) than those who progressed to clinical disease (5.31%, 0.42; 34.46 mmol/mol, 4.68; p < 0.001) but higher than those who developed any autoantibody (5.10%, 0.30; 32.21 mmol/mol, 3.49; p < 0.001), or multiple autoantibodies (5.11%, 0.35; 32.26 mmol/mol, 3.92; p < 0.003).

CONCLUSIONS

A pronounced increase in plasma glucose and HbA1c precedes development of clinical diabetes, while the association between plasma glucose or HbA1c and development of autoantibodies is complex. Increased insulin demand may contribute to development of type 1 diabetes.

Beta cell function in participants with single or multiple islet autoantibodies at baseline in the TEDDY Family Prevention Study: TEFA

Aim

The aim of the present study was to assess beta cell function based on an oral glucose tolerance test (OGTT) in participants with single islet autoantibody or an intravenous glucose tolerance test (IvGTT) in participants with multiple islet autoantibodies.

Materials and methods

Healthy participants in Sweden and Finland, between 2 and 49.99 years of age previously identified as positive for a single (n = 30) autoantibody to either insulin, glutamic acid decarboxylase, islet antigen-2, zinc transporter 8 or islet cell antibodies or multiple autoantibodies (n = 46), were included. Participants positive for a single autoantibody underwent a 6-point OGTT while participants positive for multiple autoantibodies underwent an IvGTT. Glucose, insulin and C-peptide were measured from OGTT and IvGTT samples.

Results

All participants positive for a single autoantibody had a normal glucose tolerance test with 120 minutes glucose below 7.70 mmol/L and HbA1c values within the normal range (<42 mmol/mol). Insulin responses to the glucose challenge on OGTT ranged between 13.0 and 143 mIU/L after 120 minutes with C-peptide values between 0.74 and 4.60 nmol/L. In Swedish participants, the first-phase insulin response (FPIR) on IvGTT was lower in those positive for three or more autoantibodies (n = 13; median 83.0 mIU/L; range 20.0-343) compared to those with two autoantibodies (n = 15; median 146 mIU/L; range 19.0-545; P = .0330).

Conclusion

Participants positive for a single autoantibody appeared to have a normal beta cell function. Participants positive for three or more autoantibodies had a lower FPIR as compared to participants with two autoantibodies, supporting the view that their beta cell function had deteriorated.

Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children

CONTEXT

Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons.

OBJECTIVE

The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset.

DESIGN AND SETTING

The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D.

PARTICIPANTS

We analyzed 23 Ab+ participants with available longitudinal CGM data.

MAIN OUTCOME MEASURE

CGM metrics as glycemic predictors of progression to T1D.

RESULTS

Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up.

CONCLUSIONS

Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children.

Antibodies to oxidized insulin improve prediction of type 1 diabetes in children with positive standard islet autoantibodies

BACKGROUND

Antibodies to posttranslationally modified insulin (oxPTM-INS-Ab) are a novel biomarker of type 1 diabetes (T1D). Here, we evaluated whether oxPTM-INS-Ab can improve T1D prediction in children with positive standard islet autoantibodies (AAB).

METHODS

We evaluated sensitivity, specificity, accuracy, and risk for progression to T1D associated with oxPTM-INS-Ab and the standard islet AAB that include insulin (IAA), GAD (GADA), and tyrosine phosphatase 2 (IA-2A) in a cohort of islet AAB-positive (AAB⁺ ) children from the general population (median follow-up 8.8 years).

RESULTS

oxPTM-INS-Ab was the most sensitive and specific autoantibody biomarker (74% sensitivity, 91% specificity), followed by IA-2A (71% sensitivity, 91% specificity). GADA and IAA showed lower sensitivity (65% and 50%, respectively) and specificity (66% and 68%, respectively). Accuracy (AUC of ROC) of oxPTM-INS-Ab was higher than GADA and IAA (P = 0.003 and P = 0.017, respectively), and similar to IA-2A (P = 0.896). oxPTM-INS-Ab and IA-2A were more effective than IAA for detecting progr-T1D when used as second-line biomarker in GADA⁺ children. Risk for diabetes was higher (P = 0.03) among multiple AAB⁺ who were also oxPTM-INS-Ab⁺ compared with those who were oxPTM-INS-Ab^- . Importantly, when replacing IAA with oxPTM-INS-Ab, diabetes risk increased to 100% in children with oxPTM-INS-Ab⁺ in combination with GADA⁺ and IA-2A⁺ , compared with 84.37% in those with IAA⁺ , GADA⁺ , and IA-2A⁺ (P = 0.04).

CONCLUSIONS

Antibodies to oxidized insulin (oxPTM-INS-Ab), compared with IAA which measure autoantibodies to native insulin, improve T1D risk assessment and prediction accuracy in AAB⁺ children.

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children

OBJECTIVE

The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study.

METHODS

Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A).

RESULTS

A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models.

CONCLUSIONS

This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches.

Gut Microbiota and Type 1 Diabetes

Recently, the onset of type 1 diabetes (T1D) has increased rapidly and became a major public health concern worldwide. Various factors are associated with the development of T1D, such as diet, genome, and intestinal microbiota. The gastrointestinal (GI) tract harbors a complex and dynamic population of microorganisms, the gut microbiota, which exert a marked influence on the host homeostasis and metabolic diseases. Recent evidence shows that altered gut bacterial composition (dysbiosis) is highly associated with the pathogenesis of insulin dysfunction and T1D and, thus, targeting gut microbiota may serve as a therapeutic potential for T1D patients. In this study, we updated the effect of gut microbiota on T1D and potential mechanisms were discussed.

Early prediction of autoimmune (type 1) diabetes

Underlying type 1 diabetes is a genetic aetiology dominated by the influence of specific HLA haplotypes involving primarily the class II DR-DQ region. In genetically predisposed children with the DR4-DQ8 haplotype, exogenous factors, yet to be identified, are thought to trigger an autoimmune reaction against insulin, signalled by insulin autoantibodies as the first autoantibody to appear. In children with the DR3-DQ2 haplotype, the triggering reaction is primarily against GAD signalled by GAD autoantibodies (GADA) as the first-appearing autoantibody. The incidence rate of insulin autoantibodies as the first-appearing autoantibody peaks during the first years of life and declines thereafter. The incidence rate of GADA as the first-appearing autoantibody peaks later but does not decline. The first autoantibody may variably be followed, in an apparently non-HLA-associated pathogenesis, by a second, third or fourth autoantibody. Although not all persons with a single type of autoantibody progress to diabetes, the presence of multiple autoantibodies seems invariably to be followed by loss of functional beta cell mass and eventually by dysglycaemia and symptoms. Infiltration of mononuclear cells in and around the islets appears to be a late phenomenon appearing in the multiple-autoantibody-positive with dysglycaemia. As our understanding of the aetiology and pathogenesis of type 1 diabetes advances, the improved capability for early prediction should guide new strategies for the prevention of type 1 diabetes.

Comparing glucose and hemoglobin A1c diagnostic tests among a high metabolic risk Hispanic population

BACKGROUND

Compare glycated hemoglobin (HbA1c ) diagnostic tests for prediabetes and diabetes with plasma glucose criteria and compare the metabolic profiles of people classified by HbA1c versus by glucose levels.

METHODS

Participants were recruited for the San Juan Overweight Adults Longitudinal Study. The participants were primarily Hispanic (98%), without previously diagnosed diabetes, and aged 40 to 65 years. Participants classified as normal glycemic, prediabetes, or diabetes on the basis of baseline HbA1c and plasma glucose criteria were compared with respect to baseline cardiometabolic factors.

RESULTS

The 1342 participants had a mean age of 50.5 ± 6.8 years and 28% were men. Thirty-one percent were diagnosed with prediabetes by plasma glucose criteria and 53.4% by HbA1c , and 8.1% were diagnosed with diabetes by plasma glucose criteria and 6.3% by HbA1c ; overall concordance rate was 55.1%. The area under the receiver operating characteristic curve of HbA1c compared to plasma glucose criteria was 0.62 for impaired glucose and 0.76 for diabetes. A worse cardiometabolic profile was seen within subgroups that met HbA1c and plasma glucose criteria for diabetes or prediabetes. Those diagnosed with prediabetes by plasma glucose criteria had significantly higher systolic blood pressure and higher homeostatic model assessment than those diagnosed using HbA1c . Participants diagnosed with diabetes by plasma glucose criteria had lower body mass index, smaller waist circumference, and lower insulinogenic and disposition indices, but higher homeostatic model assessment of insulin resistance, than those diagnosed by HbA1c .

CONCLUSIONS

Low concordance was seen between HbA1c and glucose measurements. The HbA1c is not a good test for prediabetes but shows reasonable validity for diabetes in this high-risk predominantly female Hispanic population. People classified by HbA1c , plasma glucose criteria, or both show different metabolic profiles; a combined test may be ideal.

Clinical measures of obesity and cumulative cardiometabolic risk in adolescents

Obesity tracks from childhood to adulthood most strongly of all cardiometabolic risk factors. To determine relationship of body mass index (BMI) and waist circumference (WC) with cardiometabolic risk (dyslipidemia, hyperglycemia and elevated blood pressure) in a large U.S. population ages 12-19 and demographic subgroups. Pooled 1999-2014 National Health and Nutrition Examination Survey data were analyzed (N = 23 438). In addition to standard cutoffs of BMI and WC, risk levels were identified for each laboratory variable: HDL-cholesterol, LDL-cholesterol, triglycerides, total cholesterol (category = lipids); fasting glucose, glycated haemoglobin (category = glucose); systolic/diastolic pressures (category =blood pressure). Within each category, being high-risk on any of the variables was high-risk; being borderline-risk on any, without being high-risk on any, was borderline-risk. Obesity severity was strongly associated with increased cardiometabolic risk, with prevalence of borderline-risk greater than high-risk. Anthropometric indicators in males and Hispanics, versus females and Whites/Blacks, respectively, had stronger associations with cardiometabolic risks. BMI and WC performed well for identifying adolescents with at least one borderline-risk or high-risk level measure for lipids, glucose and blood pressure; relationship strength varying by gender and race/ethnicity. Thus, to prevent or better manage clinical diseases of adolescents with elevated BMI and/or WC, all recommended laboratory tests are warranted.

Substantial proportion of MODY among multiplex families participating in a Type 1 diabetes prediction programme

AIMS

Patients with maturity-onset diabetes of the young (MODY) might be over-represented in families with histories of Type 1 diabetes. Our aim was to re-evaluate families participating in the Czech T1D Prediction Programme (PREDIA.CZ) with at least two members affected with diabetes to assess the proportion of MODY among these families and determine its most significant clinical predictors.

METHODS

Of the 557 families followed up by the PREDIA.CZ, 53 (9.5%) had two or more family members with diabetes. One proband with diabetes from these families was chosen for direct sequencing of the GCK, HNF1A, HNF4A and INS genes. Non-parametric tests and a linear logistic regression model were used to evaluate differences between MODY and non-MODY families.

RESULTS

MODY was genetically diagnosed in 24 of the 53 families with multiple occurrences of diabetes (45%). Mutations were detected most frequently in GCK (58%), followed by HNF1A (38%) and INS (4%). MODY families were more likely to have a parent with diabetes and had a higher proportion of females with diabetes than non-MODY families. Higher age (P < 0.001), a lower level of HbA_1c (P < 0.001) at clinical onset and at least two generations affected by diabetes were the variables most predictive for probands of MODY families already presenting with diabetes.

CONCLUSIONS

A prediction programme for Type 1 diabetes would provide a useful new source of patients with MODY most likely to benefit from an accurate diagnosis. This identification has implications for patient treatment and disease prognosis.

A Novel Physiology-Based Mathematical Model to Estimate Red Blood Cell Lifespan in Different Human Age Groups

Direct measurement of red blood cell (RBC) survival in humans has improved from the original accurate but limited differential agglutination technique to the current reliable, safe, and accurate biotin method. Despite this, all of these methods are time consuming and require blood sampling over several months to determine the RBC lifespan. For situations in which RBC survival information must be obtained quickly, these methods are not suitable. With the exception of adults and infants, RBC survival has not been extensively investigated in other age groups. To address this need, we developed a novel, physiology-based mathematical model that quickly estimates RBC lifespan in healthy individuals at any age. The model is based on the assumption that the total number of RBC recirculations during the lifespan of each RBC (denoted by N max) is relatively constant for all age groups. The model was initially validated using the data from our prior infant and adult biotin-labeled red blood cell studies and then extended to the other age groups. The model generated the following estimated RBC lifespans in 2-year-old, 5-year-old, 8-year-old, and 10-year-old children: 62, 74, 82, and 86 days, respectively. We speculate that this model has useful clinical applications. For example, HbA1c testing is not reliable in identifying children with diabetes because HbA1c is directly affected by RBC lifespan. Because our model can estimate RBC lifespan in children at any age, corrections to HbA1c values based on the model-generated RBC lifespan could improve diabetes diagnosis as well as therapy in children.

Staging the progression to type 1 diabetes with prediagnostic markers

PURPOSE OF REVIEW

There are an increasing number of markers that are used to predict the occurrence of type 1 diabetes (T1D), and to study the progression of pathologic changes prior to diagnosis. This review discusses some of those markers, particularly markers for which data are available that pertain to the progression to T1D.

RECENT FINDINGS

A study of birth cohorts showed that young children who develop multiple autoantibodies are at a particularly high risk for developing T1D, and that there appears to be a typical sequence for autoantibody development. The measurement of autoantibodies by electrochemiluminescence can increase the prediction accuracy for T1D. A new marker of changes in glucose over 6 months (PS6 M) has potential utility as an endpoint in short-term prevention trials. Markers which combine C-peptide and glucose, such as the Diabetes Prevention Trial-Type 1 Risk Score and the Index60, can increase the accuracy of prediction, and can potentially be utilized as prediagnostic endpoints. β-cell death measurements could have substantial utility in future T1D research.

SUMMARY

Markers are highly useful for studying the prediction of and progression to T1D. Moreover, markers can possibly be utilized to diagnose T1D at an earlier stage of disease.

Relationship between glycaemic variability and hyperglycaemic clamp-derived functional variables in (impending) type 1 diabetes

AIMS/HYPOTHESIS

We examined whether measures of glycaemic variability (GV), assessed by continuous glucose monitoring (CGM) and self-monitoring of blood glucose (SMBG), can complement or replace measures of beta cell function and insulin action in detecting the progression of preclinical disease to type 1 diabetes.

METHODS

Twenty-two autoantibody-positive (autoAb(+)) first-degree relatives (FDRs) of patients with type 1 diabetes who were themselves at high 5-year risk (50%) for type 1 diabetes underwent CGM, a hyperglycaemic clamp test and OGTT, and were followed for up to 31 months. Clamp variables were used to estimate beta cell function (first-phase [AUC5-10 min] and second-phase [AUC120-150 min] C-peptide release) combined with insulin resistance (glucose disposal rate; M 120-150 min). Age-matched healthy volunteers (n = 20) and individuals with recent-onset type 1 diabetes (n = 9) served as control groups.

RESULTS

In autoAb(+) FDRs, M 120-150 min below the 10th percentile (P10) of controls achieved 86% diagnostic efficiency in discriminating between normoglycaemic FDRs and individuals with (impending) dysglycaemia. M 120-150 min outperformed AUC5-10 min and AUC120-150 min C-peptide below P10 of controls, which were only 59-68% effective. Among GV variables, CGM above the reference range was better at detecting (impending) dysglycaemia than elevated SMBG (77-82% vs 73% efficiency). Combined CGM measures were equally efficient as M 120-150 min (86%). Daytime GV variables were inversely correlated with clamp variables, and more strongly with M 120-150 min than with AUC5-10 min or AUC120-150 min C-peptide.

CONCLUSIONS/INTERPRETATION

CGM-derived GV and the glucose disposal rate, reflecting both insulin secretion and action, outperformed SMBG and first- or second-phase AUC C-peptide in identifying FDRs with (impending) dysglycaemia or diabetes. Our results indicate the feasibility of developing minimally invasive CGM-based criteria for close metabolic monitoring and as outcome measures in trials.

Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association

Insights from prospective, longitudinal studies of individuals at risk for developing type 1 diabetes have demonstrated that the disease is a continuum that progresses sequentially at variable but predictable rates through distinct identifiable stages prior to the onset of symptoms. Stage 1 is defined as the presence of β-cell autoimmunity as evidenced by the presence of two or more islet autoantibodies with normoglycemia and is presymptomatic, stage 2 as the presence of β-cell autoimmunity with dysglycemia and is presymptomatic, and stage 3 as onset of symptomatic disease. Adoption of this staging classification provides a standardized taxonomy for type 1 diabetes and will aid the development of therapies and the design of clinical trials to prevent symptomatic disease, promote precision medicine, and provide a framework for an optimized benefit/risk ratio that will impact regulatory approval, reimbursement, and adoption of interventions in the early stages of type 1 diabetes to prevent symptomatic disease.

HbA1c Predicts Time to Diagnosis of Type 1 Diabetes in Children at Risk

Prediction of type 1 diabetes is based on the detection of multiple islet autoantibodies in subjects who are at increased genetic risk. Prediction of the timing of diagnosis is challenging, however. We assessed the utility of HbA1c levels in predicting the clinical disease in genetically predisposed children with multiple autoantibodies. Cord blood samples from 168,055 newborn infants were screened for class II HLA genotypes in Finland, and 14,876 children with increased genetic risk for type 1 diabetes were invited to participate in regular follow-ups, including screening for diabetes-associated autoantibodies. When two or more autoantibodies were detected, HbA1c levels were analyzed at each visit. During follow-up, multiple (two or more) autoantibodies developed in 466 children; type 1 diabetes was diagnosed in 201 of these children (43%, progressors), while 265 children remained disease free (nonprogressors) by December 2011. A 10% increase in HbA1c levels in samples obtained 3-12 months apart predicted the diagnosis of clinical disease (hazard ratio [HR] 5.7 [95% CI 4.1-7.9]) after a median time of 1.1 years (interquartile range [IQR] 0.6-3.1 years) from the observed rise of HbA1c. If the HbA1c level was ≥5.9% (41 mmol/mol) in two consecutive samples, the median time to diagnosis was 0.9 years (IQR 0.3-1.5, HR 11.9 [95% CI 8.8-16.0]). In conclusion, HbA1c is a useful biochemical marker when predicting the time to diagnosis of type 1 diabetes in children with multiple autoantibodies.

The effectiveness of age on HbA1c as a criterion for the diagnosis of diabetes in Chinese different age subjects

OBJECTIVE

To analyse the effectiveness of age on HbA1c as a criterion for the diagnosis of diabetes in Chinese different age subjects.

METHODS

This retrospective study enrolled a total of 1147 outpatients with untreated newly diagnosed diabetes (aged 18-80 years, 42·55% women) from the Fujian Province, China, and 427 age and gender-matched (control) subjects without diabetes. Receiver operating characteristic curve (ROC) was plotted to determine the performance of HbA1c against results of oral glucose tolerance test (OGTT) performed at the same time according to specific age groups. The ORs and 95%CIs between diabetes and other metabolic disorders were analysed.

RESULTS

(i) HbA1c provided an age-specific diagnosis for diabetes: there was a high diagnostic titter of HbA1c in the 18- to 39-year age group; conversely, there was a low diagnostic titter of HbA1c in the ≥70-year-old age groups. (ii) After adjusted for age, individuals with diabetes by OGTT criteria but not by WHO HbA1c criteria had an increased chance of having abnormal weight, hypertriglyceridaemia, HDL hypocholesterolaemia and insulin resistance. (iii) The diagnostic cut-off points of HbA1c for diabetes in different age groups (18-39, 40-49, 50-59, 60-69 and ≥70 years) were 6·1, 6·3, 6·4, 6·5 and 6·4, respectively. The age-specific HbA1c criteria exhibited the higher positive rate, sensitivity and lower false-negative rate when compared with WHO HbA1c criteria.

CONCLUSIONS

This provided evidence indicating that there may be drawbacks in the use of HbA1c in the diagnosis of diabetes. Thus, we proposed that the impact of introducing HbA1c for diabetes diagnosis should be considered in terms of age. Cohort studies are needed to further confirm the suitability of age-specific HbA1c criteria for the diagnosis of diabetes.

Early hyperglycemia detected by continuous glucose monitoring in children at risk for type 1 diabetes

OBJECTIVE

We explore continuous glucose monitoring (CGM) as a new approach to defining early hyperglycemia and diagnosing type 1 diabetes in children with positive islet autoantibodies (Ab+).

RESEARCH DESIGN AND METHODS

Fourteen Ab+ children, free of signs or symptoms of diabetes, and nine antibody-negative (Ab-) subjects, followed by the Diabetes Autoimmunity Study in the Young, were asked to wear a Dexcom SEVEN CGM.

RESULTS

The Ab+ subjects showed more hyperglycemia, with 18% time spent above 140 mg/dL, compared with 9% in Ab- subjects (P = 0.04). Their average maximum daytime glucose value was higher, and they had increased glycemic variability. The mean HbA1c in the Ab+ subjects was 5.5% (37 mmol/mol). Among Ab+ subjects, ≥18-20% CGM time spent above 140 mg/dL seems to predict progression to diabetes.

CONCLUSIONS

CGM can detect early hyperglycemia in Ab+ children who are at high risk for progression to diabetes. Proposed CGM predictors of progression to diabetes require further validation.

Significance of HbA1c and its measurement in the diagnosis of diabetes mellitus: US experience

The 2014 American Diabetes Association guidelines denote four means of diagnosing diabetes. The first of these is a glycosylated hemoglobin (HbA1c) >6.5%. This literature review summarizes studies (n=47) in the USA examining the significance, strengths, and limitations of using HbA1c as a diagnostic tool for diabetes, relative to other available means. Due to the relatively recent adoption of HbA1c as a diabetes mellitus diagnostic tool, a hybrid systematic, truncated review of the literature was implemented. Based on these studies, we conclude that HbA1c screening for diabetes has been found to be convenient and effective in diagnosing diabetes. HbA1c screening is particularly helpful in community-based and acute care settings where tests requiring fasting are not practical. Using HbA1c to diagnose diabetes also has some limitations. For instance, HbA1c testing may underestimate the prevalence of diabetes, particularly among whites. Because this bias differs by racial group, prevalence and resulting estimates of health disparities based on HbA1c screening differ from those based on other methods of diagnosis. In addition, existing evidence suggests that HbA1c screening may not be valid in certain subgroups, such as children, women with gestational diabetes, patients with human immunodeficiency virus, and those with prediabetes. Further guidelines are needed to clarify the appropriate use of HbA1c screening in these populations.