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PURPOSE: The 'Biomarkers of heterogeneity in type 1 diabetes' study cohort was set up to identify genetic, physiological and psychosocial factors explaining the observed heterogeneity in disease progression and the development of complications in people with long-standing type 1 diabetes (T1D). PARTICIPANTS: Data and samples were collected in two subsets. A prospective cohort of 611 participants aged ≥16 years with ≥5 years T1D duration from four Dutch Diabetes clinics between 2016 and 2021 (median age 32 years; median diabetes duration 12 years; 59% female; mean glycated haemoglobin (HbA1c) 61 mmol/mol (7.7%); 61% on insulin pump; 23% on continuous glucose monitoring (CGM)). Physical assessments were performed, blood and urine samples were collected, and participants completed questionnaires. A subgroup of participants underwent mixed-meal tolerance tests (MMTTs) at baseline (n=169) and at 1-year follow-up (n=104). Genetic data and linkage to medical and administrative records were also available. A second cross-sectional cohort included participants with ≥35 years of T1D duration (currently n=160; median age 64 years; median diabetes duration 45 years; 45% female; mean HbA1c 58 mmol/mol (7.4%); 51% on insulin pump; 83% on CGM), recruited from five centres and measurements, samples and 5-year retrospective data were collected. FINDINGS TO DATE: Stimulated residual C-peptide was detectable in an additional 10% of individuals compared with fasting residual C-peptide secretion. MMTT measurements at 90 min and 120 min showed good concordance with the MMTT total area under the curve. An overall decrease of C-peptide at 1-year follow-up was observed. Fasting residual C-peptide secretion is associated with a decreased risk of impaired awareness of hypoglycaemia. FUTURE PLANS:Research groups are invited to consider the use of these data and the sample collection. Future work will include additi

ObjectiveStandardised person-reported outcomes (PRO) data can contextualise clinical outcomes enabling precision diabetes monitoring and care. Comprehensive outcome sets can guide this process, but their implementation in routine diabetes care has remained challenging and unsuccessful at international level. We aimed to address this by developing a person-centred outcome set for Type 1 and Type 2 diabetes, using a methodology with prospects for increased implementability and sustainability in international health settings.MethodsWe used a three-round questionnaire-based Delphi study to reach consensus on the outcome set. We invited key stakeholders from 19 countries via purposive snowball sampling, namely people with diabetes (N = 94), healthcare professionals (N = 65), industry (N = 22) and health authorities (N = 3), to vote on the relevance and measurement frequency of 64 previously identified clinical and person-reported outcomes. Subsequent consensus meetings concluded the study.ResultsThe list of preliminary outcomes was shortlisted via the consensus process to 46 outcomes (27 clinical outcomes and 19 PROs). Two main collection times were recommended: (1) linked to a medical visit (e.g. diabetes-specific well-being, symptoms and psychological health) and (2) annually (e.g. clinical data, general well-being and diabetes self management-related outcomes).ConclusionsPROs are often considered in a non-standardised way in routine diabetes care. We propose a person-centred outcome set for diabetes, specifically considering psychosocial and behavioural aspects, which was agreed by four international key stakeholder groups. It guides standardised collection of meaningful outcomes at scale, supporting individual and population level healthcare decision making. It will be implemented and tested in Europe as part of the H2O project.

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Background: Longitudinal studies including parental distress when examining adverse health outcomes in adolescents with type 1 diabetes are lacking. This study examined whether parental depression and anxiety predict adolescent emotional distress and glycated hemoglobin A1c (HbA1c) 1 year later and whether a relation between parental distress and HbA1c is mediated by the level of parental involvement in diabetes care and by treatment behaviors.Methods: Longitudinal path modeling was applied to data from 154 adolescents and parents from diabetes centers participating in the Longitudinal study of Emotional problems in Adolescents with type 1 diabetes and their Parents/caregivers (Diabetes LEAP). At baseline and 1-year follow-up, participants completed measures of depression and anxiety. HbA1c was extracted from medical charts. Responsibility and treatment behavior questionnaires were completed by adolescents at baseline.Results: Baseline parental depressive and anxiety symptoms were not associated with 1-year adolescent depressive symptoms, anxiety symptoms, and HbA1c. Responsibility division and treatment behaviors did not mediate associations between parental emotional distress and 1-year HbA1c.Conclusions: Parental depressive and anxiety symptoms did not predict adolescent health outcomes 1 year later. Future studies may determine whether the link is present in case of mood/anxiety disorders or severe diabetes-specific distress, or whether adolescents are resilient in the face of parental distress.Impact: Adolescents with T1D are a vulnerable group in terms of psychological and health outcomes. Whether parental emotional distress (i.e., depressive and anxiety symptoms) is prospectively associated with adolescent emotional distress and/or HbA1c has been understudied. Our results show that parental distress was not related to adolescent distress or HbA1c 1 year later. Responsibility division and treatm

AIMS: To update and extend a previous cross-sectional international comparison of glycaemic control in people with type 1 diabetes.METHODS: Data were obtained for 520,392 children and adults with type 1 diabetes from 17 population and five clinic-based data sources in countries or regions between 2016 and 2020. Median HbA1c (IQR) and proportions of individuals with HbA1c < 58 mmol/mol (<7.5%), 58-74 mmol/mol (7.5-8.9%) and ≥75 mmol/mol (≥9.0%) were compared between populations for individuals aged <15, 15-24 and ≥25 years. Logistic regression was used to estimate the odds ratio (OR) of HbA1c < 58 mmol/mol (<7.5%) relative to ≥58 mmol/mol (≥7.5%), stratified and adjusted for sex, age and data source. Where possible, changes in the proportion of individuals in each HbA1c category compared to previous estimates were calculated.RESULTS: Median HbA1c varied from 55 to 79 mmol/mol (7.2 to 9.4%) across data sources and age groups so a pooled estimate was deemed inappropriate. OR (95% CI) for HbA1c < 58 mmol/mol (<7.5%) were 0.91 (0.90-0.92) for women compared to men, 1.68 (1.65-1.71) for people aged <15 years and 0.81 (0.79-0.82) aged15-24 years compared to those aged ≥25 years. Differences between populations persisted after adjusting for sex, age and data source. In general, compared to our previous analysis, the proportion of people with an HbA1c < 58 mmol/l (<7.5%) increased and proportions of people with HbA1c ≥ 75 mmol/mol (≥9.0%) decreased.CONCLUSIONS: Glycaemic control of type 1 diabetes continues to vary substantially between age groups and data sources. While some improvement over time has been observed, glycaemic control remains sub-optimal for most people with Type 1 diabetes.

AIMS: To update and extend a previous cross-sectional international comparison of glycaemic control in people with type 1 diabetes.METHODS: Data were obtained for 520,392 children and adults with type 1 diabetes from 17 population and five clinic-based data sources in countries or regions between 2016 and 2020. Median HbA1c (IQR) and proportions of individuals with HbA1c < 58 mmol/mol (<7.5%), 58-74 mmol/mol (7.5-8.9%) and ≥75 mmol/mol (≥9.0%) were compared between populations for individuals aged <15, 15-24 and ≥25 years. Logistic regression was used to estimate the odds ratio (OR) of HbA1c < 58 mmol/mol (<7.5%) relative to ≥58 mmol/mol (≥7.5%), stratified and adjusted for sex, age and data source. Where possible, changes in the proportion of individuals in each HbA1c category compared to previous estimates were calculated.RESULTS: Median HbA1c varied from 55 to 79 mmol/mol (7.2 to 9.4%) across data sources and age groups so a pooled estimate was deemed inappropriate. OR (95% CI) for HbA1c < 58 mmol/mol (<7.5%) were 0.91 (0.90-0.92) for women compared to men, 1.68 (1.65-1.71) for people aged <15 years and 0.81 (0.79-0.82) aged15-24 years compared to those aged ≥25 years. Differences between populations persisted after adjusting for sex, age and data source. In general, compared to our previous analysis, the proportion of people with an HbA1c < 58 mmol/l (<7.5%) increased and proportions of people with HbA1c ≥ 75 mmol/mol (≥9.0%) decreased.CONCLUSIONS: Glycaemic control of type 1 diabetes continues to vary substantially between age groups and data sources. While some improvement over time has been observed, glycaemic control remains sub-optimal for most people with Type 1 diabetes.

Background Not much is known about the effects of glycemic variability (GV) during the pre- and periconception period on pregnancy/perinatal complications. GV could potentially contribute to identification of high-risk pregnancies in women with type 1 diabetes. Methods An explorative retrospective cohort study was conducted between January 2014 and May 2019. Glucose data were retrieved from electronic patient charts. Pre-/periconceptional GV and GV during all three trimesters was expressed as mean glucose, standard deviation (SD), Coefficient of Variation (CV), High Blood Glucose Index (HBGI), Low Blood Glucose Index (LBGI) and Average Daily Risk Range (ADRR). Maternal and neonatal complications were summarized using a composite total complication score. Binary logistic regression analyses were conducted to assess associations between the GV measures and a total complication score>3, a maternal complication score>1 and a neonatal complication score>1. Results Of 63 eligible women, 29 women (38 pregnancies) were included. Women in the group with a total complication score>3 had a significantly higher ADRR at conception (OR 1.1, CI 1.0-1.2, p=0.048). No statistically significant correlations between complication score and any other GV metric besides the ADRR were found. Although not significant, in the group with a complication score>3, odds ratios>1 were found for SD in trimester 1 (OR 1.6, CI 0.6-4.5, p=0.357) and trimester 2 (OR 1.8, CI 0.5-6.2, p=0.376). Conclusions Presence of a positive association between GV and pregnancy and perinatal complications depends on which pregnancy period is assessed and the GV metrics that are used.

Introduction This study aimed to assess the association between fasting serum C-peptide levels and the presence of impaired awareness of hypoglycemia (IAH) in people with type 1 diabetes. Research design and methods We performed a cross-sectional study among 509 individuals with type 1 diabetes (diabetes duration 5-65 years). Extensive clinical data and fasting serum C-peptide concentrations were collected and related to the presence or absence of IAH, which was evaluated using the validated Dutch version of the Clarke questionnaire. A multivariable logistic regression model was constructed to investigate the association of C-peptide and other clinical variables with IAH. Results In 129 (25%) individuals, residual C-peptide secretion was detected, while 75 (15%) individuals reported IAH. The median (IQR) C-peptide concentration among all participants was 0.0 (0.0-3.9) pmol/L. The prevalence of severe hypoglycemia was lower in people with demonstrable C-peptide versus those with absent C-peptide (30% vs 41%, p=0.025). Individuals with IAH were older, had longer diabetes duration, more frequently had macrovascular and microvascular complications, and more often used antihypertensive drugs, antiplatelet agents and cholesterol-lowering medication. There was a strong association between IAH and having a severe hypoglycemia in the preceding year. In multivariable regression analysis, residual C-peptide, either continuously or dichotomous, was associated with lower prevalence of IAH (p=0.040-0.042), while age at diabetes onset (p=0.001), presence of microvascular complications (p=0.003) and body mass index (BMI) (p=0.003) were also independently associated with the presence of IAH. Conclusions Higher BMI, the presence of microvascular complications and higher age at diabetes onset were independent risk factors for IAH in people with type 1 diabetes, while residual C-peptide secretion was associated with lower risk of this

Objectives: We aim to determine the prevalence and the course of anxiety and mood disorders in Dutch adolescents (12–18 years old) with type 1 diabetes, and to examine correlates of symptom severity, including parental emotional distress. Methods: Participants were 171 adolescents and 149 parents. The Diagnostic Interview Schedule for Children-IV was used to assess current, past year and lifetime anxiety and mood disorders in adolescents. Symptom severity and diabetes distress were measured with validated questionnaires. Correlates of these symptoms were examined using hierarchical regression analyses and included demographics (adolescent sex and age), clinical factors (diabetes duration, treatment modality, most recent glycated hemoglobin A1c; all extracted from medical charts), adolescent diabetes distress, and parent emotional distress. Results: Twenty-four (14%) adolescents met the criteria for ≥1 disorder(s) in the previous 12 months. Anxiety disorders were more prevalent than mood disorders (13% vs. 4%). Lifetime prevalence of anxiety and mood disorders was 29% (n = 49). The presence of any of these disorders earlier in life (from 5 years old up to 12 months prior to assessment) was associated with disorders in the past 12 months (OR = 4.88, p = 0.001). Higher adolescent diabetes distress was related to higher symptoms of anxiety (b = 0.07, p = 0.001) and depression (b = 0.13, p = 0.001), while demographics, clinical characteristics, and parental emotional distress were not related. Conclusions: Anxiety and mood disorders are common among adolescents and related to earlier disorders. Higher diabetes distress was related to higher symptom severity. Clinicians are advised to address past psychological problems and remain vigilant of these problems.

Background Type 1 diabetes (T1D) is a chronic metabolic condition requiring intensive daily self-care to avoid both high and low blood glucose levels. Self-care and glycemic outcomes are particularly problematic in adolescence, a period known for its increased risk of emotional problems. However, the true scope of mood and anxiety disorders in adolescents with T1D is unknown. Earlier studies are limited by a small sample size, lack of diagnostic interview data, a focus on depression only, non-adolescent specific estimates, lack of information about parental emotional problems and/or a cross-sectional design. Diabetes LEAP is a two-year prospective observational cohort study examining (a) the prevalence and course of depression and anxiety in adolescents with T1D and their parents/caregivers, (b) the risk factors predicting the presence of these emotional problems, (c) their longitudinal relation with diabetes outcomes, and (d) the psychosocial care currently in place. Methods Adolescents (12-18 years) from 8 Dutch pediatric diabetes clinics are interviewed using the DISC-IV to establish the presence of mood and anxiety disorders in the previous 4 weeks, the previous 12 months, and lifetime. They also complete questionnaires, including CDI-2, GAD-7, and PAID-T. Parents/caregivers complete PHQ-9, GAD-7, and PAID-PR. Follow-up assessments take place after 1 and 2 years. Discussion This longitudinal study with diagnostic interviews in a large cohort of adolescents with T1D in the Netherlands will provide much needed information regarding the prevalence and course of depression and anxiety in this group, thereby opening avenues for proper recognition, prevention and timely treatment.

In this issue of Diabetologia, Alavi and Werner (10.1007/s00125-018-4676-1) criticise the attempts to use positron emission tomography (PET) for in vivo imaging of pancreatic beta cells, which they consider as futile'. In support of this strong statement, they point out the limitations of PET imaging, which they believe render beta cell mass impossible to estimate using this method. In our view, the Alavi and Werner presentation of the technical limitations of PET imaging does not reflect the current state of the art, which leads them to questionable conclusions towards the feasibility of beta cell imaging using this approach. Here, we put forward arguments in favour of continuing the development of innovative technologies enabling in vivo imaging of pancreatic beta cells and concisely present the current state of the art regarding putative technical limitations of PET imaging. Indeed, far from being a futile' effort, we demonstrate that beta cell imaging is now closer than ever to becoming a long-awaited clinical reality.

Objective: The reason for center differences in metabolic control of childhood diabetes is still unknown. We sought to determine to what extent the targets, expectations, and goals that diabetes care professionals have for their patients is a determinant of center differences in metabolic outcomes. Research Design and Methods: Children, under the age of 11 with type 1 diabetes and their parents treated at the study centers participated. Clinical, medical, and demographic data were obtained, along with blood sample for centralized assay. Parents and all members of the diabetes care team completed questionnaires on treatment targets for hemoglobin A1c (HbA1c) and recommended frequency of blood glucose monitoring. Results: Totally 1113 (53% male) children (mean age 8.0±2.1years) from 18 centers in 17 countries, along with parents and 113 health-care professionals, participated. There were substantial differences in mean HbA1c between centers ranging from 7.3±0.8% (53mmol/mol±8.7) to 8.9±1.1% (74mmol/mol±12.0). Centers with lower mean HbA1c had (1) parents who reported lower targets for their children, (2) health-care professionals that reported lower targets and more frequent testing, and (3) teams with less disagreement about recommended targets. Multiple regression analysis indicated that teams reporting higher HbA1c targets and more target disagreement had parents reporting higher treatment targets. This seemed to partially account for center differences in Hb1Ac. Conclusions: The diabetes care teams' cohesiveness and perspectives on treatment targets, expectations, and recommendations have an influence on parental targets, contributing to the differences in pediatric diabetes center outcomes.

In this issue of Diabetologia, Alavi and Werner (https://doi.org/10.1007/s00125-018-4676-1) criticise the attempts to use positron emission tomography (PET) for in vivo imaging of pancreatic beta cells, which they consider as ‘futile’. In support of this strong statement, they point out the limitations of PET imaging, which they believe render beta cell mass impossible to estimate using this method. In our view, the Alavi and Werner presentation of the technical limitations of PET imaging does not reflect the current state of the art, which leads them to questionable conclusions towards the feasibility of beta cell imaging using this approach. Here, we put forward arguments in favour of continuing the development of innovative technologies enabling in vivo imaging of pancreatic beta cells and concisely present the current state of the art regarding putative technical limitations of PET imaging. Indeed, far from being a ‘futile’ effort, we demonstrate that beta cell imaging is now closer than ever to becoming a long-awaited clinical reality., SCOPUS: no.j, info:eu-repo/semantics/published

Objective: The reason for center differences in metabolic control of childhood diabetes is still unknown. We sought to determine to what extent the targets, expectations, and goals that diabetes care professionals have for their patients is a determinant of center differences in metabolic outcomes. Research Design and Methods: Children, under the age of 11 with type 1 diabetes and their parents treated at the study centers participated. Clinical, medical, and demographic data were obtained, along with blood sample for centralized assay. Parents and all members of the diabetes care team completed questionnaires on treatment targets for hemoglobin A1c (HbA1c) and recommended frequency of blood glucose monitoring. Results: Totally 1113 (53% male) children (mean age 8.0 ± 2.1 years) from 18 centers in 17 countries, along with parents and 113 health-care professionals, participated. There were substantial differences in mean HbA1c between centers ranging from 7.3 ± 0.8% (53 mmol/mol ± 8.7) to 8.9 ± 1.1% (74 mmol/mol ± 12.0). Centers with lower mean HbA1c had (1) parents who reported lower targets for their children, (2) health-care professionals that reported lower targets and more frequent testing, and (3) teams with less disagreement about recommended targets. Multiple regression analysis indicated that teams reporting higher HbA1c targets and more target disagreement had parents reporting higher treatment targets. This seemed to partially account for center differences in Hb1Ac. Conclusions: The diabetes care teams’ cohesiveness and perspectives on treatment targets, expectations, and recommendations have an influence on parental targets, contributing to the differences in pediatric diabetes center outcomes., SCOPUS: ar.j, info:eu-repo/semantics/published

Background Strict glycemic control during adolescence decreases the risk of developing complications later in life, even if this level of control is not maintained afterwards. However, the majority of adolescents with type 1 diabetes (T1D) are in poor control and so far medical or psychological interventions have shown limited success. Adolescence is characterized by major biological, psychosocial, cognitive and parent–child relationship changes and the complex interaction between these developmental trajectories, and its impact on health outcomes is still poorly understood. A specific topic of interest in this context is the timing of diagnosis. The longitudinal study DINO (Diabetes IN develOpment) aims to examine: 1) If and how the onset of T1D before vs. during puberty results in different outcomes of glycemic control, self-management, psychological functioning and diabetes-related quality of life. 2) The timing of onset of disturbed eating behavior, its risk factors and its prospective course in relation to glycemic and psychological consequences. 3) If and how the onset of T1D before vs. during puberty results in different family functioning and parental well-being. 4) If and how the cognitive development of youth with T1D relates to glycemic control and diabetes self-management. Methods/design DINO, a longitudinal multi-center cohort study is conducted in youth with T1D in the age range 8–15 years at baseline. Participants will be divided into two subgroups: pre-pubertal and pubertal. Both groups will be followed for 3 years with assessments based on a bio-psychosocial model of diabetes, scheduled at baseline, 12 months, 24 months and 36 months examining the biological, psychosocial -including disturbed eating behaviors- and cognitive development, family functioning and parental well-being. Discussion A better understanding of how the different trajectories affect one another will help to gain insight in the protective and r

SCOPUS: ar.j, FLWIN, info:eu-repo/semantics/published

SCOPUS: ar.j, FLWIN, info:eu-repo/semantics/published

Objective: To evaluate glycaemic targets set by diabetes teams, their perception by adolescents and parents, and their influence on metabolic control.Methods: Clinical data and questionnaires were completed by adolescents, parents/carers and diabetes teams in 21 international centres. HbA1c was measured centrally.Results: A total of 2062 adolescents completed questionnaires (age 14.4 ± 2.3 yr; diabetes duration 6.1 ± 3.5 yr). Mean HbA 1c = 8.2 ± 1.4% with significant differences between centres (F = 12.3; p < 0.001) range from 7.4 to 9.1%. There was a significant correlation between parent (r = 0.20) and adolescent (r = 0.21) reports of their perceived ideal HbA1c and their actual HbA1c result (p < 0.001), and a stronger association between parents' (r = 0.39) and adolescents' (r = 0.4) reports of the HbA1c they would be happy with and their actual HbA1c result. There were significant differences between centres on parent and adolescent reports of ideal and happy with HbA1c (8.1 < F > 17.4;p < 0.001). A lower target HbA1c and greater consistency between members of teams within centres were associated with lower centre HbA1c (F = 16.0; df = 15; p < 0.001).Conclusions: Clear and consistent setting of glycaemic targets by diabetes teams is strongly associated with HbA1c outcome in adolescents. Target setting appears to play a significant role in explaining the differences in metabolic outcomes between centres. © 2009 John Wiley & Sons A/S., SCOPUS: ar.j, FLWIN, info:eu-repo/semantics/published

Objective: To evaluate glycaemic targets set by diabetes teams, their perception by adolescents and parents, and their influence on metabolic control.Methods: Clinical data and questionnaires were completed by adolescents, parents/carers and diabetes teams in 21 international centres. HbA1c was measured centrally.Results: A total of 2062 adolescents completed questionnaires (age 14.4 ± 2.3 yr; diabetes duration 6.1 ± 3.5 yr). Mean HbA 1c = 8.2 ± 1.4% with significant differences between centres (F = 12.3; p < 0.001) range from 7.4 to 9.1%. There was a significant correlation between parent (r = 0.20) and adolescent (r = 0.21) reports of their perceived ideal HbA1c and their actual HbA1c result (p < 0.001), and a stronger association between parents' (r = 0.39) and adolescents' (r = 0.4) reports of the HbA1c they would be happy with and their actual HbA1c result. There were significant differences between centres on parent and adolescent reports of ideal and happy with HbA1c (8.1 < F > 17.4;p < 0.001). A lower target HbA1c and greater consistency between members of teams within centres were associated with lower centre HbA1c (F = 16.0; df = 15; p < 0.001).Conclusions: Clear and consistent setting of glycaemic targets by diabetes teams is strongly associated with HbA1c outcome in adolescents. Target setting appears to play a significant role in explaining the differences in metabolic outcomes between centres. © 2009 John Wiley & Sons A/S., SCOPUS: ar.j, FLWIN, info:eu-repo/semantics/published

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SCOPUS: ar.j, info:eu-repo/semantics/published

OBJECTIVE: Assessment of quality of life (QOL) in adolescents with diabetes requires patient, parent and health professional input. Psychometrically robust instruments to assess parent and professional perspectives are required. RESEARCH DESIGN AND METHODS: Questionnaires concerning adolescent QOL were developed for completion by parents and health professionals. In an international study assessing QOL in 2,101 adolescents with diabetes (median age 14 years, range 10-18; from 17 countries including Europe, Japan and North America), parents and health professionals completed their respective questionnaires between March and August 1998. RESULTS: Feasibility and acceptability of the new questionnaires were indicated by high questionnaire completion rates (adolescents 92%; parents 89%; health professionals 94%). Internal consistency was confirmed (Cronbach's alpha coefficients 0.80 parent; 0.86 health professional). Correlations of Diabetes Quality of Life Questionnaire for Youths (DQOLY) scores with parent and health professional global QOL ratings were generally low (r ranging from 0.12 to 0.36). Parent-rated burden decreased incrementally across adolescence, particularly for girls. Professional-rated burden followed a similar profile but only after age 15 years. Until then, burden was rated as uniformly high. Clinically relevant discrepancies in parent and professional burden scores were noted for one-parent families and families where adolescents had been referred for psychological help. In both cases, health professionals but not one-parent families perceived these as high burden situations. The clinical significance of this relates to the significantly poorer metabolic control recorded for adolescents in both situations. CONCLUSIONS: Parent and health professional questionnaires were found to have adequate internal consistency, and convergent and discriminant validity in relation to key clinical and QOL outcomes. The questionnaires are brief, easy to administer a

SCOPUS: ar.j, info:eu-repo/semantics/published

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OBJECTIVE - To study the association of autoantibodies against a 38-kDa glycated islet cell membrane-associated (GLIMA) protein with (pre)type 1 diabetes, patient characteristics, and other immune and genetic markers of the disease and to evaluate the possible added value of GLIMA antibody determinations for disease prediction and classification. RESEARCH DESIGN AND METHODS - Recent-onset type 1 diabetic patients (n = 100), prediabetic siblings (n = 23), and nondiabetic control subjects (n = 100) were consecutively recruited by the Belgian Diabetes Registry. GLIMA antibodies were determined by immunoprecipitation of radiolabeled islet cell proteins; islet cell antibodies (ICAs) were determined by indirect immunofluorescence; and insulin autoantibodies (IAAs), insulinoma-associated protein-2 antibodies (IA-2As), and GAD antibodies (GADAs) were determined by radioligand assays. RESULTS - GLIMA antibodies were detected in 38% of type 1 diabetic patients and 35 of prediabetic siblings (during follow-up) vs. 0% in control subjects (P < 0.001). Their prevalence was lower than that of other antibodies and was significantly associated with high levels of 1A-2A and ICA (P < 0.0001). In (pre)diabetes, GLIMA antibodies could only be demonstrated in sera positive for ≥1 other autoantibody. CONCLUSIONS - GLIMA antibodies are strongly associated with type 1 diabetes and antibody markers of rapid progression to clinical onset but have a lower diagnostic sensitivity for the disease than IAA, ICA, IA-2A, or GADA. In its present form, the GLIMA antibody assay does not provide much additional information for prediction or classification of diabetes, compared with that obtained from the measurement of IA-2As alone or in combination with IAAs, ICAs, and GADAs.