138 results on '"Steck AK"'
Search Results
2. Development of a standardized MRI protocol for pancreas assessment in humans
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Jin, M, Virostko, J, Craddock, RC, Williams, JM, Triolo, TM, Hilmes, MA, Kang, H, Du, L, Wright, JJ, Kinney, M, Maki, JH, Medved, M, Waibel, M, Kay, TWH, Thomas, HE, Greeley, SAW, Steck, AK, Moore, DJ, Powers, AC, Jin, M, Virostko, J, Craddock, RC, Williams, JM, Triolo, TM, Hilmes, MA, Kang, H, Du, L, Wright, JJ, Kinney, M, Maki, JH, Medved, M, Waibel, M, Kay, TWH, Thomas, HE, Greeley, SAW, Steck, AK, Moore, DJ, and Powers, AC
- Abstract
Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes.
- Published
- 2021
3. TCF7L2 genetic variants contribute to phenotypic heterogeneity of T1DM
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Wentworth J, Michels A, Anderson M, Sosenko J, Geyer S, Pugliese A, Xu P, Antinozzi P, Steck Ak, and Redondo Mj
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Genetics ,Genetic heterogeneity ,Genetic variants ,Biology ,TCF7L2 - Published
- 2018
4. A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk
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Redondo, MJ, Geyer, S, Steck, AK, Sharp, S, Wentworth, JM, Weedon, MN, Antinozzi, P, Sosenko, J, Atkinson, M, Pugliese, A, Oram, RA, Redondo, MJ, Geyer, S, Steck, AK, Sharp, S, Wentworth, JM, Weedon, MN, Antinozzi, P, Sosenko, J, Atkinson, M, Pugliese, A, and Oram, RA
- Abstract
OBJECTIVE: We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals. RESEARCH DESIGN AND METHODS: We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables. RESULTS: Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002). CONCLUSIONS: The T1D GRS independently predicts p
- Published
- 2018
5. TCF7L2 Genetic Variants Contribute to Phenotypic Heterogeneity of Type 1 Diabetes
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Redondo, MJ, Geyer, S, Steck, AK, Sosenko, J, Anderson, M, Antinozzi, P, Michels, A, Wentworth, J, Xu, P, Pugliese, A, Redondo, MJ, Geyer, S, Steck, AK, Sosenko, J, Anderson, M, Antinozzi, P, Michels, A, Wentworth, J, Xu, P, and Pugliese, A
- Abstract
OBJECTIVE: The phenotypic diversity of type 1 diabetes suggests heterogeneous etiopathogenesis. We investigated the relationship of type 2 diabetes-associated transcription factor 7 like 2 (TCF7L2) single nucleotide polymorphisms (SNPs) with immunologic and metabolic characteristics at type 1 diabetes diagnosis. RESEARCH DESIGN AND METHODS: We studied TrialNet participants with newly diagnosed autoimmune type 1 diabetes with available TCF7L2 rs4506565 and rs7901695 SNP data (n = 810; median age 13.6 years; range 3.3-58.6). We modeled the influence of carrying a TCF7L2 variant (i.e., having 1 or 2 minor alleles) on the number of islet autoantibodies and oral glucose tolerance test (OGTT)-stimulated C-peptide and glucose measures at diabetes diagnosis. All analyses were adjusted for known confounders. RESULTS: The rs4506565 variant was a significant independent factor of expressing a single autoantibody, instead of multiple autoantibodies, at diagnosis (odds ratio [OR] 1.66 [95% CI 1.07, 2.57], P = 0.024). Interaction analysis demonstrated that this association was only significant in participants ≥12 years old (n = 504; OR 2.12 [1.29, 3.47], P = 0.003) but not younger ones (n = 306, P = 0.73). The rs4506565 variant was independently associated with higher C-peptide area under the curve (AUC) (P = 0.008) and lower mean glucose AUC (P = 0.0127). The results were similar for the rs7901695 SNP. CONCLUSIONS: In this cohort of individuals with new-onset type 1 diabetes, type 2 diabetes-linked TCF7L2 variants were associated with single autoantibody (among those ≥12 years old), higher C-peptide AUC, and lower glucose AUC levels during an OGTT. Thus, carriers of the TCF7L2 variant had a milder immunologic and metabolic phenotype at type 1 diabetes diagnosis, which could be partly driven by type 2 diabetes-like pathogenic mechanisms.
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- 2018
6. Do non-HLA genes influence development of persistent islet autoimmunity and type 1 diabetes in children with high-risk HLA-DR,DQ genotypes?
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Steck AK, Zhang W, Bugawan TL, Barriga KJ, Blair A, Erlich HA, Eisenbarth GS, Norris JM, Rewers MJ, Steck, Andrea K, Zhang, Weiming, Bugawan, Teodorica L, Barriga, Katherine J, Blair, Alan, Erlich, Henry A, Eisenbarth, George S, Norris, Jill M, and Rewers, Marian J
- Abstract
Objective: Specific alleles of non-HLA genes INS, CTLA-4, and PTPN22 have been associated with type 1 diabetes. We examined whether some of these alleles influence development of islet autoimmunity or progression from persistent islet autoimmunity to type 1 diabetes in children with high-risk HLA-DR,DQ genotypes.Research Design and Methods: Since 1993, the Diabetes Autoimmunity Study in the Young (DAISY) has followed 2,449 young children carrying HLA-DR,DQ genotypes associated with type 1 diabetes. Of those, 112 have developed islet autoimmunity (persistent autoantibodies to insulin, GAD65, and/or IA-2), and 47 of these have progressed to type 1 diabetes. The influence of polymorphisms of INS(-23Hph1), CTLA-4(T17A), and PTPN22(R620W) on development of persistent islet autoimmunity and progression to type 1 diabetes was evaluated by parametric models and by survival analyses.Results: PTPN22(R620W) allele T was associated with development of persistent islet autoimmunity (hazard ratio 1.83 [95% CI 1.27-2.63]) controlling for ethnicity, presence of HLA-DR3/4,DQB1*0302, and having a first-degree relative with type 1 diabetes. Survival analyses showed a significantly (P = 0.002) higher risk of persistent islet autoimmunity by age 10 years for the TT genotype (27.3%) than for the CT or CC genotype (7.9 and 5.3%, respectively). Cumulative risk of persistent islet autoimmunity was slightly higher (P = 0.02) for the INS(-23Hph1) AA genotype (7.8%) than for the AT or TT genotype (4.2 and 6.4% risk by age 10 years, respectively).Conclusions: Whereas the HLA-DR3/4,DQB1*0302 genotype had a dramatic influence on both development of islet autoimmunity and progression to type 1 diabetes, the PTPN22(R620W) T allele significantly influences progression to persistent islet autoimmunity in the DAISY cohort. [ABSTRACT FROM AUTHOR]- Published
- 2009
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7. Association of the PTPN22/LYP gene with type 1 diabetes.
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Steck AK, Liu SY, McFann K, Barriga KJ, Babu SR, Eisenbarth GS, Rewers MJ, and She JX
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- 2006
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8. Age of islet autoantibody appearance and mean levels of insulin, but not GAD or IA-2 autoantibodies, predict age of diagnosis of type 1 diabetes: diabetes autoimmunity study in the young.
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Steck AK, Johnson K, Barriga KJ, Miao D, Yu L, Hutton JC, Eisenbarth GS, Rewers MJ, Steck, Andrea K, Johnson, Kelly, Barriga, Katherine J, Miao, Dongmei, Yu, Liping, Hutton, John C, Eisenbarth, George S, and Rewers, Marian J
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AGE factors in disease , *AUTOANTIBODIES , *ENZYMES , *IMMUNOGLOBULINS , *INSULIN , *ISLANDS of Langerhans , *TYPE 1 diabetes , *LONGITUDINAL method , *RESEARCH funding , *DISEASE progression , *DIAGNOSIS - Abstract
Objective: We evaluated predictors of progression to diabetes in children with high-risk HLA genotypes and persistent islet autoantibodies.Research Design and Methods: The Diabetes Autoimmunity Study in the Young (DAISY) followed 2,542 children with autoantibodies measured to GAD, IA-2, and insulin.Results: Persistent islet autoantibodies developed in 169 subjects, and 55 of those progressed to diabetes. Children expressing three autoantibodies showed a linear progression to diabetes with 74% cumulative incidence by the 10-year follow-up compared with 70% with two antibodies and 15% with one antibody (P < 0.0001). Both age of appearance of first autoantibody and insulin autoantibody (IAA) levels, but not GAD or IA-2 autoantibodies, were major determinants of the age of diabetes diagnosis (r = 0.79, P < 0.0001).Conclusions: In the DAISY cohort, 89% of children who progressed to diabetes expressed two or more autoantibodies. Age of diagnosis of diabetes is strongly correlated with age of appearance of first autoantibody and IAA levels. [ABSTRACT FROM AUTHOR]- Published
- 2011
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9. Temporal development of T cell receptor repertoires during childhood in health and disease
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Mitchell, AM, primary, Baschal, EE, additional, McDaniel, KA, additional, Simmons, KM, additional, Pyle, L, additional, Waugh, K, additional, Steck, AK, additional, Yu, L, additional, Gottlieb, PA, additional, Rewers, MJ, additional, Nakayama, M, additional, and Michels, AW, additional
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10. Erratum. Consensus Guidance for Monitoring Individuals With Islet Autoantibody-Positive Pre-Stage 3 Type 1 Diabetes. Diabetes Care 2024;47:1276-1298.
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Phillip M, Achenbach P, Addala A, Albanese-O'Neill A, Battelino T, Bell KJ, Besser REJ, Bonifacio E, Colhoun HM, Couper JJ, Craig ME, Danne T, Beaufort C, Dovc K, Driscoll KA, Dutta S, Ebekozien O, Larsson HE, Feiten DJ, Frohnert BI, Gabbay RA, Gallagher MP, Greenbaum CJ, Griffin KJ, Hagopian W, Haller MJ, Hendrieckx C, Hendriks E, Holt RIG, Hughes L, Ismail HM, Jacobsen LM, Johnson SB, Kolb LE, Kordonouri O, Lange K, Lash RW, Lernmark Å, Libman I, Lundgren M, Maahs DM, Marcovecchio ML, Mathieu C, Miller KM, O'Donnell HK, Oron T, Patil SP, Pop-Busui R, Rewers MJ, Rich SS, Schatz DA, Schulman-Rosenbaum R, Simmons KM, Sims EK, Skyler JS, Smith LB, Speake C, Steck AK, Thomas NPB, Tonyushkina KN, Veijola R, Wentworth JM, Wherrett DK, Wood JR, Ziegler AG, and DiMeglio LA
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- 2024
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11. Identification of type 1 diabetes risk phenotypes using an outcome-guided clustering analysis.
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You L, Ferrat LA, Oram RA, Parikh HM, Steck AK, Krischer J, and Redondo MJ
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- Humans, Cluster Analysis, Female, Male, Adult, Adolescent, Child, Risk Factors, Young Adult, Blood Glucose metabolism, Diabetes Mellitus, Type 1 immunology, Diabetes Mellitus, Type 1 genetics, Autoantibodies immunology, Autoantibodies blood, Phenotype
- Abstract
Aims/hypothesis: Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal the heterogeneity of the at-risk population by identifying clinically meaningful clusters are lacking. We aimed to identify and characterise clusters of islet autoantibody-positive individuals who share similar characteristics and type 1 diabetes risk., Methods: We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention study data (n=1123). The outcome of the analysis was the time to development of type 1 diabetes, and variables in the model included demographic characteristics, genetics, metabolic factors and islet autoantibodies. An independent dataset (the Diabetes Prevention Trial of Type 1 Diabetes Study) (n=706) was used for validation., Results: The analysis revealed six clusters with varying type 1 diabetes risks, categorised into three groups based on the hierarchy of clusters. Group A comprised one cluster with high glucose levels (median for glucose mean AUC 9.48 mmol/l; IQR 9.16-10.02) and high risk (2-year diabetes-free survival probability 0.42; 95% CI 0.34, 0.51). Group B comprised one cluster with high IA-2A titres (median 287 DK units/ml; IQR 250-319) and elevated autoantibody titres (2-year diabetes-free survival probability 0.73; 95% CI 0.67, 0.80). Group C comprised four lower-risk clusters with lower autoantibody titres and glucose levels (with 2-year diabetes-free survival probability ranging from 0.84-0.99 in the four clusters). Within group C, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels and age. A decision rule for assigning individuals to clusters was developed. Use of the validation dataset confirmed that the clusters can identify individuals with similar characteristics., Conclusions/interpretation: Demographic, metabolic, immunological and genetic markers may be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
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- 2024
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12. Correction to: Consensus guidance for monitoring individuals with islet autoantibody‑positive pre‑stage 3 type 1 diabetes.
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Phillip M, Achenbach P, Addala A, Albanese-O'Neill A, Battelino T, Bell KJ, Besser REJ, Bonifacio E, Colhoun HM, Couper JJ, Craig ME, Danne T, de Beaufort C, Dovc K, Driscoll KA, Dutta S, Ebekozien O, Larsson HE, Feiten DJ, Frohnert BI, Gabbay RA, Gallagher MP, Greenbaum CJ, Griffin KJ, Hagopian W, Haller MJ, Hendrieckx C, Hendriks E, Holt RIG, Hughes L, Ismail HM, Jacobsen LM, Johnson SB, Kolb LE, Kordonouri O, Lange K, Lash RW, Lernmark Å, Libman I, Lundgren M, Maahs DM, Marcovecchio ML, Mathieu C, Miller KM, O'Donnell HK, Oron T, Patil SP, Pop-Busui R, Rewers MJ, Rich SS, Schatz DA, Schulman-Rosenbaum R, Simmons KM, Sims EK, Skyler JS, Smith LB, Speake C, Steck AK, Thomas NPB, Tonyushkina KN, Veijola R, Wentworth JM, Wherrett DK, Wood JR, Ziegler AG, and DiMeglio LA
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- 2024
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13. Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes.
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Phillip M, Achenbach P, Addala A, Albanese-O'Neill A, Battelino T, Bell KJ, Besser REJ, Bonifacio E, Colhoun HM, Couper JJ, Craig ME, Danne T, de Beaufort C, Dovc K, Driscoll KA, Dutta S, Ebekozien O, Larsson HE, Feiten DJ, Frohnert BI, Gabbay RA, Gallagher MP, Greenbaum CJ, Griffin KJ, Hagopian W, Haller MJ, Hendrieckx C, Hendriks E, Holt RIG, Hughes L, Ismail HM, Jacobsen LM, Johnson SB, Kolb LE, Kordonouri O, Lange K, Lash RW, Lernmark Å, Libman I, Lundgren M, Maahs DM, Marcovecchio ML, Mathieu C, Miller KM, O'Donnell HK, Oron T, Patil SP, Pop-Busui R, Rewers MJ, Rich SS, Schatz DA, Schulman-Rosenbaum R, Simmons KM, Sims EK, Skyler JS, Smith LB, Speake C, Steck AK, Thomas NPB, Tonyushkina KN, Veijola R, Wentworth JM, Wherrett DK, Wood JR, Ziegler AG, and DiMeglio LA
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- Humans, Consensus, Islets of Langerhans immunology, Disease Progression, Diabetic Ketoacidosis diagnosis, Diabetic Ketoacidosis immunology, Diabetes Mellitus, Type 1 immunology, Diabetes Mellitus, Type 1 diagnosis, Autoantibodies immunology, Autoantibodies blood
- Abstract
Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb
+ ) children and adults who are at risk of (confirmed single IAb+ ) or living with (multiple IAb+ ) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+ ; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care., (© 2024. American Diabetes Association and European Association for the Study of Diabetes.)- Published
- 2024
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14. Longitudinal changes in DNA methylation during the onset of islet autoimmunity differentiate between reversion versus progression of islet autoimmunity.
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Carry PM, Vanderlinden LA, Johnson RK, Buckner T, Steck AK, Kechris K, Yang IV, Fingerlin TE, Fiehn O, Rewers M, and Norris JM
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- Humans, Female, Male, Child, Adolescent, Longitudinal Studies, Child, Preschool, Genome-Wide Association Study, Epigenesis, Genetic, Diabetes Mellitus, Type 1 immunology, Diabetes Mellitus, Type 1 genetics, Autoimmunity genetics, Islets of Langerhans immunology, Disease Progression, Autoantibodies blood, Autoantibodies immunology, DNA Methylation
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Background: Type 1 diabetes (T1D) is preceded by a heterogenous pre-clinical phase, islet autoimmunity (IA). We aimed to identify pre vs. post-IA seroconversion (SV) changes in DNAm that differed across three IA progression phenotypes, those who lose autoantibodies (reverters), progress to clinical T1D (progressors), or maintain autoantibody levels (maintainers)., Methods: This epigenome-wide association study (EWAS) included longitudinal DNAm measurements in blood (Illumina 450K and EPIC) from participants in Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, one or more islet autoantibodies on at least two consecutive visits. We compared reverters - individuals who sero-reverted, negative for all autoantibodies on at least two consecutive visits and did not develop T1D (n=41); maintainers - continued to test positive for autoantibodies but did not develop T1D (n=60); progressors - developed clinical T1D (n=42). DNAm data were measured before (pre-SV visit) and after IA (post-SV visit). Linear mixed models were used to test for differences in pre- vs post-SV changes in DNAm across the three groups. Linear mixed models were also used to test for group differences in average DNAm. Cell proportions, age, and sex were adjusted for in all models. Median follow-up across all participants was 15.5 yrs. (interquartile range (IQR): 10.8-18.7)., Results: The median age at the pre-SV visit was 2.2 yrs. (IQR: 0.8-5.3) in progressors, compared to 6.0 yrs. (IQR: 1.3-8.4) in reverters, and 5.7 yrs. (IQR: 1.4-9.7) in maintainers. Median time between the visits was similar in reverters 1.4 yrs. (IQR: 1-1.9), maintainers 1.3 yrs. (IQR: 1.0-2.0), and progressors 1.8 yrs. (IQR: 1.0-2.0). Changes in DNAm, pre- vs post-SV, differed across the groups at one site (cg16066195) and 11 regions. Average DNAm (mean of pre- and post-SV) differed across 22 regions., Conclusion: Differentially changing DNAm regions were located in genomic areas related to beta cell function, immune cell differentiation, and immune cell function., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Carry, Vanderlinden, Johnson, Buckner, Steck, Kechris, Yang, Fingerlin, Fiehn, Rewers and Norris.)
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- 2024
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15. The Influence of Pubertal Development on Autoantibody Appearance and Progression to Type 1 Diabetes in the TEDDY Study.
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Warncke K, Tamura R, Schatz DA, Veijola R, Steck AK, Akolkar B, Hagopian W, Krischer JP, Lernmark Å, Rewers MJ, Toppari J, McIndoe R, Ziegler AG, Vehik K, Haller MJ, and Elding Larsson H
- Abstract
Context: The 2 peaks of type 1 diabetes incidence occur during early childhood and puberty., Objective: We sought to better understand the relationship between puberty, islet autoimmunity, and type 1 diabetes., Methods: The relationships between puberty, islet autoimmunity, and progression to type 1 diabetes were investigated prospectively in children followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Onset of puberty was determined by subject self-assessment of Tanner stages. Associations between speed of pubertal progression, pubertal growth, weight gain, homeostasis model assessment of insulin resistance (HOMA-IR), islet autoimmunity, and progression to type 1 diabetes were assessed. The influence of individual factors was analyzed using Cox proportional hazard ratios., Results: Out of 5677 children who were still in the study at age 8 years, 95% reported at least 1 Tanner Stage score and were included in the study. Children at puberty (Tanner Stage ≥2) had a lower risk (HR 0.65, 95% CI 0.45-0.93; P = .019) for incident autoimmunity than prepubertal children (Tanner Stage 1). An increase of body mass index Z-score was associated with a higher risk (HR 2.88, 95% CI 1.61-5.15; P < .001) of incident insulin autoantibodies. In children with multiple autoantibodies, neither HOMA-IR nor rate of progression to Tanner Stage 4 were associated with progression to type 1 diabetes., Conclusion: Rapid weight gain during puberty is associated with development of islet autoimmunity. Puberty itself had no significant influence on the appearance of autoantibodies or type 1 diabetes. Further studies are needed to better understand the underlying mechanisms., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society.)
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- 2024
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16. Genetic Associations with C-peptide Levels before Type 1 Diabetes Diagnosis in At-Risk Relatives.
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Triolo TM, Parikh HM, Tosur M, Ferrat L, You L, Gottlieb PA, Oram RA, Onengut-Gumuscu S, Krischer JP, Rich SS, Steck AK, and Redondo MJ
- Abstract
Objective: We sought to determine whether the type 1 diabetes genetic risk score-2 (T1D-GRS2) and single nucleotide polymorphisms (SNPs) are associated with C-peptide preservation before type 1 diabetes diagnosis., Methods: We conducted a retrospective analysis of 713 autoantibody-positive participants who developed type 1 diabetes in the TrialNet Pathway to Prevention Study who had T1DExomeChip data. We evaluated the relationships of 16 known SNPs and T1D-GRS2 with area under the curve (AUC) C-peptide levels during oral glucose tolerance tests conducted in the 9 months before diagnosis., Results: Higher T1D-GRS2 was associated with lower C-peptide AUC in the 9 months before diagnosis in univariate (β=-0.06, P<0.0001) and multivariate (β=-0.03, P=0.005) analyses. Participants with the JAZF1 rs864745 T allele had lower C-peptide AUC in both univariate (β=-0.11, P=0.002) and multivariate (β=-0.06, P=0.018) analyses., Conclusions: The type 2 diabetes-associated JAZF1 rs864745 T allele and higher T1D-GRS2 are associated with lower C-peptide AUC prior to diagnosis of type 1 diabetes, with implications for the design of prevention trials., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
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- 2024
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17. Lower Prevalence of Diabetic Ketoacidosis at Diagnosis in Research Participants Monitored for Hyperglycemia.
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Sooy MGQ, Pyle L, Alonso GT, Broncucia HC, Rewers A, Gottlieb PA, Simmons KMW, Rewers MJ, and Steck AK
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Context: In Colorado children, the prevalence of diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes (T1D) has been increasing over time., Objective: Evaluate the prevalence of and factors involved in DKA at T1D diagnosis among participants followed in monitoring research studies before diagnosis compared to patients from the community., Setting and Participants: Patients < 18 years diagnosed with T1D between 2005 and 2021 at the Barbara Davis Center for Diabetes., Outcome: Prevalence of and factors associated with DKA at diagnosis among participants in preclinical monitoring studies compared to those diagnosed in the community., Results: Of 5049 subjects, 164 were active study participants, 42 inactive study participants, and 4843 were community patients. Active study participants, compared to community patients, had lower HbA1c (7.3% vs 11.9%]; P < 0.001) and less frequently experienced DKA (4.9% vs 48.5%; P < 0.001), including severe DKA (1.2% vs 16.2%; P < 0.001). Inactive study participants had intermediate levels for both prevalence and severity of DKA. DKA prevalence increased in community patients, from 44.0% to 55%, with less evidence for a temporal trend in study participants. DKA prevalence was highest in children <2 years (13% in active study participants vs 83% in community patients). In community patients, younger age (P = 0.0038), public insurance (P < 0.0001), rural residence (P < 0.0076), higher HbA1c (P < 0.0001), and ethnicity minority status (P < 0.0001) were associated with DKA at diagnosis., Conclusions: While DKA prevalence increases in community patients over time, it stayed <5% in active research participants, who have a 10 times lower prevalence of DKA at diagnosis, including in minorities., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
- Published
- 2024
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18. Longitudinal Assessment of Pancreas Volume by MRI Predicts Progression to Stage 3 Type 1 Diabetes.
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Virostko J, Wright JJ, Williams JM, Hilmes MA, Triolo TM, Broncucia H, Du L, Kang H, Nallaparaju S, Valencia LG, Reyes D, Hammel B, Russell WE, Philipson LH, Waibel M, Kay TWH, Thomas HE, Greeley SAW, Steck AK, Powers AC, and Moore DJ
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- Humans, Prospective Studies, Pancreas diagnostic imaging, Pancreas metabolism, Risk Factors, Autoantibodies, Magnetic Resonance Imaging, Diabetes Mellitus, Type 1 diagnosis
- Abstract
Objective: This multicenter prospective cohort study compared pancreas volume as assessed by MRI, metabolic scores derived from oral glucose tolerance testing (OGTT), and a combination of pancreas volume and metabolic scores for predicting progression to stage 3 type 1 diabetes (T1D) in individuals with multiple diabetes-related autoantibodies., Research Design and Methods: Pancreas MRI was performed in 65 multiple autoantibody-positive participants enrolled in the Type 1 Diabetes TrialNet Pathway to Prevention study. Prediction of progression to stage 3 T1D was assessed using pancreas volume index (PVI), OGTT-derived Index60 score and Diabetes Prevention Trial-Type 1 Risk Score (DPTRS), and a combination of PVI and DPTRS., Results: PVI, Index60, and DPTRS were all significantly different at study entry in 11 individuals who subsequently experienced progression to stage 3 T1D compared with 54 participants who did not experience progression (P < 0.005). PVI did not correlate with metabolic testing across individual study participants. PVI declined longitudinally in the 11 individuals diagnosed with stage 3 T1D, whereas Index60 and DPTRS increased. The area under the receiver operating characteristic curve for predicting progression to stage 3 from measurements at study entry was 0.76 for PVI, 0.79 for Index60, 0.79 for DPTRS, and 0.91 for PVI plus DPTRS., Conclusions: These findings suggest that measures of pancreas volume and metabolism reflect distinct components of risk for developing stage 3 type 1 diabetes and that a combination of these measures may provide superior prediction than either alone., (© 2024 by the American Diabetes Association.)
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- 2024
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19. OGTT Metrics Surpass Continuous Glucose Monitoring Data for T1D Prediction in Multiple-Autoantibody-Positive Individuals.
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Ylescupidez A, Speake C, Pietropaolo SL, Wilson DM, Steck AK, Sherr JL, Gaglia JL, Bender C, Lord S, and Greenbaum CJ
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- Humans, Glucose Tolerance Test, Blood Glucose metabolism, Autoantibodies, Blood Glucose Self-Monitoring, Continuous Glucose Monitoring, Diabetes Mellitus, Type 1 diagnosis
- Abstract
Context: The value of continuous glucose monitoring (CGM) for monitoring autoantibody (AAB)-positive individuals in clinical trials for progression of type 1 diabetes (T1D) is unknown., Objective: Compare CGM with oral glucose tolerance test (OGTT)-based metrics in prediction of T1D., Methods: At academic centers, OGTT and CGM data from multiple-AAB relatives were evaluated for associations with T1D diagnosis. Participants were multiple-AAB-positive individuals in a TrialNet Pathway to Prevention (TN01) CGM ancillary study (n = 93). The intervention was CGM for 1 week at baseline, 6 months, and 12 months. Receiver operating characteristic (ROC) curves of CGM and OGTT metrics for prediction of T1D were analyzed., Results: Five of 7 OGTT metrics and 29/48 CGM metrics but not HbA1c differed between those who subsequently did or did not develop T1D. ROC area under the curve (AUC) of individual CGM values ranged from 50% to 69% and increased when adjusted for age and AABs. However, the highest-ranking metrics were derived from OGTT: 4/7 with AUC ∼80%. Compared with adjusted multivariable models using CGM data, OGTT-derived variables, Index60 and DPTRS (Diabetes Prevention Trial-Type 1 Risk Score), had higher discriminative ability (higher ROC AUC and positive predictive value with similar negative predictive value)., Conclusion: Every 6-month CGM measures in multiple-AAB-positive individuals are predictive of subsequent T1D, but less so than OGTT-derived variables. CGM may have feasibility advantages and be useful in some settings. However, our data suggest there is insufficient evidence to replace OGTT measures with CGM in the context of clinical trials., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
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- 2023
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20. Anxiety and Risk Perception in Parents of Children Identified by Population Screening as High Risk for Type 1 Diabetes.
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O'Donnell HK, Rasmussen CG, Dong F, Simmons KM, Steck AK, Frohnert BI, Bautista K, Rewers MJ, and Baxter J
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- Child, Humans, Infant, Child, Preschool, Adolescent, Autoantibodies, Parents, Anxiety diagnosis, Perception, Diabetes Mellitus, Type 1 epidemiology, Islets of Langerhans
- Abstract
Objective: To assess anxiety and risk perception among parents whose children screened positive for islet autoantibodies, indicating elevated risk for type 1 diabetes (T1D)., Research Design and Methods: The Autoimmunity Screening for Kids (ASK) study identified 319 children age 1 to 17 years at risk for T1D via screening for islet autoantibodies; 280 children with confirmed islet autoantibodies and their caregivers enrolled in a follow-up education and monitoring program to prevent diabetic ketoacidosis at diagnosis. Parents completed questionnaires at each monitoring visit, including a 6-item version of the State Anxiety Inventory (SAI), to assess anxiety about their child developing T1D, and a single question to assess risk perception., Results: At the first ASK follow-up monitoring visit, mean parental anxiety was elevated above the clinical cutoff of 40 (SAI 46.1 ± 11.2). At the second follow-up monitoring visit (i.e., visit 2), mean anxiety remained elevated but started to trend down. Approximately half (48.9%) of parents reported their child was at increased risk for T1D at the initial follow-up monitoring visit (visit 1). Parents of children with more than one islet autoantibody and a first-degree relative with T1D were more likely to report their child was at increased risk., Conclusions: Most parents of autoantibody-positive children have high anxiety about their child developing T1D. Information about the risk of developing T1D is difficult to convey, as evidenced by the wide range of risk perception reported in this sample., (© 2023 by the American Diabetes Association.)
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- 2023
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21. Historical Insights and Current Perspectives on the Diagnosis and Management of Presymptomatic Type 1 Diabetes.
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Simmons KMW, Frohnert BI, O'Donnell HK, Bautista K, Geno Rasmussen C, Gerard Gonzalez A, Steck AK, and Rewers MJ
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- Humans, Practice Guidelines as Topic, Diabetes Mellitus, Type 1 diagnosis, Diabetes Mellitus, Type 1 therapy, Prediabetic State diagnosis, Prediabetic State therapy
- Abstract
Objective: The article provides practical guidance for (1) interpreting and confirming islet autoantibody screening results for type 1 diabetes (T1D) and (2) follow-up of individuals with early stages of T1D with the goal of ensuring medical safety and providing patients and their families with an assessment of risk for progression to a clinical diagnosis of T1D. Research Design and Methods: We used an explicit a priori methodology to identify areas of agreement and disagreement in how to manage patients with early T1D. We used a modified Delphi method, which is a systematic, iterative approach to identifying consensus. We developed a list of topic questions, ranked them by importance, and developed consensus statements based on available evidence and expert opinion around each of the 30 topic questions consistently ranked as being most important. Results: Consensus statements for screening and monitoring are supported with figures proposing an algorithm for confirmation of T1D diagnosis and management of early T1D until clinical diagnosis. Conclusions: Disseminating and increasing knowledge related to how to interpret T1D screening tests, confirm early T1D diagnosis and monitor for medical safety and clinical disease risk prediction is critically important as there are currently no clinical recommendations. Published guidance will promote better management of T1D screening-detected individuals.
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- 2023
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22. Hydroxychloroquine in Stage 1 Type 1 Diabetes.
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Libman I, Bingley PJ, Becker D, Buckner JH, DiMeglio LA, Gitelman SE, Greenbaum C, Haller MJ, Ismail HM, Krischer J, Moore WV, Moran A, Muir AB, Raman V, Steck AK, Toledo FGS, Wentworth J, Wherrett D, White P, You L, and Herold KC
- Subjects
- Humans, Autoantibodies, Insulin, Glucose, Hydroxychloroquine therapeutic use, Diabetes Mellitus, Type 1
- Abstract
Objective: Innate immune responses may be involved in the earliest phases of type 1 diabetes (T1D)., Research Design and Methods: To test whether blocking innate immaune cells modulated progression of the disease, we randomly assigned 273 individuals with stage 1 T1D to treatment with hydroxychloroquine (n = 183; 5 mg/kg per day to a maximum of 400 mg) or placebo (n = 90) and assessed whether hydroxychloroquine treatment delayed or prevented progression to stage 2 T1D (i.e., two or more islet autoantibodies with abnormal glucose tolerance)., Results: After a median follow-up of 23.3 months, the trial was stopped prematurely by the data safety monitoring board because of futility. There were no safety concerns in the hydroxychloroquine arm, including in annual ophthalmologic examinations. Preplanned secondary analyses showed a transient decrease in the glucose average area under the curve to oral glucose in the hydroxychloroquine-treated arm at month 6 and reduced titers of anti-GAD and anti-insulin autoantibodies and acquisition of positive autoantibodies in the hydroxychloroquine arm (P = 0.032)., Conclusions: We conclude that hydroxychloroquine does not delay progression to stage 2 T1D in individuals with stage 1 disease. Drug treatment reduces the acquisition of additional autoantibodies and the titers of autoantibodies to GAD and insulin., (© 2023 by the American Diabetes Association.)
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- 2023
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23. Type 1 Diabetes Risk Phenotypes Using Cluster Analysis.
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You L, Ferrat LA, Oram RA, Parikh HM, Steck AK, Krischer J, and Redondo MJ
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Background: Although statistical models for predicting type 1 diabetes risk have been developed, approaches that reveal clinically meaningful clusters in the at-risk population and allow for non-linear relationships between predictors are lacking. We aimed to identify and characterize clusters of islet autoantibody-positive individuals that share similar characteristics and type 1 diabetes risk., Methods: We tested a novel outcome-guided clustering method in initially non-diabetic autoantibody-positive relatives of individuals with type 1 diabetes, using the TrialNet Pathway to Prevention (PTP) study data (n=1127). The outcome of the analysis was time to type 1 diabetes and variables in the model included demographics, genetics, metabolic factors and islet autoantibodies. An independent dataset (Diabetes Prevention Trial of Type 1 Diabetes, DPT-1 study) (n=704) was used for validation., Findings: The analysis revealed 8 clusters with varying type 1 diabetes risks, categorized into three groups. Group A had three clusters with high glucose levels and high risk. Group B included four clusters with elevated autoantibody titers. Group C had three lower-risk clusters with lower autoantibody titers and glucose levels. Within the groups, the clusters exhibit variations in characteristics such as glucose levels, C-peptide levels, age, and genetic risk. A decision rule for assigning individuals to clusters was developed. The validation dataset confirms that the clusters can identify individuals with similar characteristics., Interpretation: Demographic, metabolic, immunological, and genetic markers can be used to identify clusters of distinctive characteristics and different risks of progression to type 1 diabetes among autoantibody-positive individuals with a family history of type 1 diabetes. The results also revealed the heterogeneity in the population and complex interactions between variables.
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- 2023
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24. Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review.
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Felton JL, Griffin KJ, Oram RA, Speake C, Long SA, Onengut-Gumuscu S, Rich SS, Monaco GSF, Evans-Molina C, DiMeglio LA, Ismail HM, Steck AK, Dabelea D, Johnson RK, Urazbayeva M, Gitelman S, Wentworth JM, Redondo MJ, and Sims EK
- Abstract
Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification., Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument., Results: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings., Conclusions: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design., (© 2023. Springer Nature Limited.)
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- 2023
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25. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.
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Tobias DK, Merino J, Ahmad A, Aiken C, Benham JL, Bodhini D, Clark AL, Colclough K, Corcoy R, Cromer SJ, Duan D, Felton JL, Francis EC, Gillard P, Gingras V, Gaillard R, Haider E, Hughes A, Ikle JM, Jacobsen LM, Kahkoska AR, Kettunen JLT, Kreienkamp RJ, Lim LL, Männistö JME, Massey R, Mclennan NM, Miller RG, Morieri ML, Most J, Naylor RN, Ozkan B, Patel KA, Pilla SJ, Prystupa K, Raghavan S, Rooney MR, Schön M, Semnani-Azad Z, Sevilla-Gonzalez M, Svalastoga P, Takele WW, Tam CH, Thuesen ACB, Tosur M, Wallace AS, Wang CC, Wong JJ, Yamamoto JM, Young K, Amouyal C, Andersen MK, Bonham MP, Chen M, Cheng F, Chikowore T, Chivers SC, Clemmensen C, Dabelea D, Dawed AY, Deutsch AJ, Dickens LT, DiMeglio LA, Dudenhöffer-Pfeifer M, Evans-Molina C, Fernández-Balsells MM, Fitipaldi H, Fitzpatrick SL, Gitelman SE, Goodarzi MO, Grieger JA, Guasch-Ferré M, Habibi N, Hansen T, Huang C, Harris-Kawano A, Ismail HM, Hoag B, Johnson RK, Jones AG, Koivula RW, Leong A, Leung GKW, Libman IM, Liu K, Long SA, Lowe WL Jr, Morton RW, Motala AA, Onengut-Gumuscu S, Pankow JS, Pathirana M, Pazmino S, Perez D, Petrie JR, Powe CE, Quinteros A, Jain R, Ray D, Ried-Larsen M, Saeed Z, Santhakumar V, Kanbour S, Sarkar S, Monaco GSF, Scholtens DM, Selvin E, Sheu WH, Speake C, Stanislawski MA, Steenackers N, Steck AK, Stefan N, Støy J, Taylor R, Tye SC, Ukke GG, Urazbayeva M, Van der Schueren B, Vatier C, Wentworth JM, Hannah W, White SL, Yu G, Zhang Y, Zhou SJ, Beltrand J, Polak M, Aukrust I, de Franco E, Flanagan SE, Maloney KA, McGovern A, Molnes J, Nakabuye M, Njølstad PR, Pomares-Millan H, Provenzano M, Saint-Martin C, Zhang C, Zhu Y, Auh S, de Souza R, Fawcett AJ, Gruber C, Mekonnen EG, Mixter E, Sherifali D, Eckel RH, Nolan JJ, Philipson LH, Brown RJ, Billings LK, Boyle K, Costacou T, Dennis JM, Florez JC, Gloyn AL, Gomez MF, Gottlieb PA, Greeley SAW, Griffin K, Hattersley AT, Hirsch IB, Hivert MF, Hood KK, Josefson JL, Kwak SH, Laffel LM, Lim SS, Loos RJF, Ma RCW, Mathieu C, Mathioudakis N, Meigs JB, Misra S, Mohan V, Murphy R, Oram R, Owen KR, Ozanne SE, Pearson ER, Perng W, Pollin TI, Pop-Busui R, Pratley RE, Redman LM, Redondo MJ, Reynolds RM, Semple RK, Sherr JL, Sims EK, Sweeting A, Tuomi T, Udler MS, Vesco KK, Vilsbøll T, Wagner R, Rich SS, and Franks PW
- Subjects
- Humans, Consensus, Evidence-Based Medicine, Precision Medicine, Diabetes Mellitus diagnosis, Diabetes Mellitus genetics, Diabetes Mellitus therapy
- Abstract
Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)
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- 2023
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26. Type 1 Diabetes Prevention: a systematic review of studies testing disease-modifying therapies and features linked to treatment response.
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Felton JL, Griffin KJ, Oram RA, Speake C, Long SA, Onengut-Gumuscu S, Rich SS, Monaco GS, Evans-Molina C, DiMeglio LA, Ismail HM, Steck AK, Dabelea D, Johnson RK, Urazbayeva M, Gitelman S, Wentworth JM, Redondo MJ, and Sims EK
- Abstract
Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention., Methods: To understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument., Results: We identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings., Conclusions: While the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention., Plain Language Summary: Type 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.
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- 2023
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27. CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study.
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Wilson DM, Pietropaolo SL, Acevedo-Calado M, Huang S, Anyaiwe D, Scheinker D, Steck AK, Vasudevan MM, McKay SV, Sherr JL, Herold KC, Dunne JL, Greenbaum CJ, Lord SM, Haller MJ, Schatz DA, Atkinson MA, Nelson PW, and Pietropaolo M
- Subjects
- Humans, Female, Adolescent, Male, Blood Glucose metabolism, Blood Glucose Self-Monitoring, Glucose therapeutic use, Autoantibodies, Diabetes Mellitus, Type 1 drug therapy
- Abstract
Objective: Continuous glucose monitoring (CGM) parameters may identify individuals at risk for progression to overt type 1 diabetes. We aimed to determine whether CGM metrics provide additional insights into progression to clinical stage 3 type 1 diabetes., Research Design and Methods: One hundred five relatives of individuals in type 1 diabetes probands (median age 16.8 years; 89% non-Hispanic White; 43.8% female) from the TrialNet Pathway to Prevention study underwent 7-day CGM assessments and oral glucose tolerance tests (OGTTs) at 6-month intervals. The baseline data are reported here. Three groups were evaluated: individuals with 1) stage 2 type 1 diabetes (n = 42) with two or more diabetes-related autoantibodies and abnormal OGTT; 2) stage 1 type 1 diabetes (n = 53) with two or more diabetes-related autoantibodies and normal OGTT; and 3) negative test for all diabetes-related autoantibodies and normal OGTT (n = 10)., Results: Multiple CGM metrics were associated with progression to stage 3 type 1 diabetes. Specifically, spending ≥5% time with glucose levels ≥140 mg/dL (P = 0.01), ≥8% time with glucose levels ≥140 mg/dL (P = 0.02), ≥5% time with glucose levels ≥160 mg/dL (P = 0.0001), and ≥8% time with glucose levels ≥160 mg/dL (P = 0.02) were all associated with progression to stage 3 disease. Stage 2 participants and those who progressed to stage 3 also exhibited higher mean daytime glucose values; spent more time with glucose values over 120, 140, and 160 mg/dL; and had greater variability., Conclusions: CGM could aid in the identification of individuals, including those with a normal OGTT, who are likely to rapidly progress to stage 3 type 1 diabetes., (© 2023 by the American Diabetes Association.)
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- 2023
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28. Barriers to Screening: An Analysis of Factors Impacting Screening for Type 1 Diabetes Prevention Trials.
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Kinney M, You L, Sims EK, Wherrett D, Schatz D, Lord S, Krischer J, Russell WE, Gottlieb PA, Libman I, Buckner J, DiMeglio LA, Herold KC, and Steck AK
- Abstract
Context: Participants with stage 1 or 2 type 1 diabetes (T1D) qualify for prevention trials, but factors involved in screening for such trials are largely unknown., Objective: To identify factors associated with screening for T1D prevention trials., Methods: This study included TrialNet Pathway to Prevention participants who were eligible for a prevention trial: oral insulin (TN-07, TN-20), teplizumab (TN-10), abatacept (TN-18), and oral hydroxychloroquine (TN-22). Univariate and multivariate logistic regression models were used to examine participant, site, and study factors at the time of prevention trial accrual., Results: Screening rates for trials were: 50% for TN-07 (584 screened/1172 eligible), 9% for TN-10 (106/1249), 24% for TN-18 (313/1285), 17% for TN-20 (113/667), and 28% for TN-22 (371/1336). Younger age and male sex were associated with higher screening rates for prevention trials overall and for oral therapies. Participants with an offspring with T1D showed lower rates of screening for all trials and oral drug trials compared with participants with other first-degree relatives as probands. Site factors, including larger monitoring volume and US site vs international site, were associated with higher prevention trial screening rates., Conclusions: Clear differences exist between participants who screen for prevention trials and those who do not screen and between the research sites involved in prevention trial screening. Participant age, sex, and relationship to proband are significantly associated with prevention trial screening in addition to key site factors. Identifying these factors can facilitate strategic recruitment planning to support rapid and successful enrollment into prevention trials., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society.)
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- 2023
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29. Prevalence of SARS-CoV-2 Antibodies Among Healthy Children From Colorado From 2020 to 2021: A Brief Report.
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Frost HM, Geno Rasmussen C, Shorrosh H, Pyle L, Bautista K, Frohnert BI, Stahl M, Simmons K, Steck AK, Jia X, Yu L, and Rewers M
- Subjects
- Child, Humans, Adolescent, Infant, Child, Preschool, Colorado epidemiology, Prevalence, Seroepidemiologic Studies, Antibodies, Viral, SARS-CoV-2, COVID-19 epidemiology
- Abstract
There are few estimates of the seroprevalence of SARS-CoV-2 antibodies among children in the United States. We measured vaccine and infection induced seroprevalence among nearly 5000 healthy 1 to 17-year-old children in Colorado from 2020 to 2021. By December 2021, 89% of older children, ages 12 to 18, had antibodies detected. The increase was largely driven from vaccination rather than infection.
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- 2023
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30. The Transition From a Compensatory Increase to a Decrease in C-peptide During the Progression to Type 1 Diabetes and Its Relation to Risk.
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Ismail HM, Cuthbertson D, Gitelman SE, Skyler JS, Steck AK, Rodriguez H, Atkinson M, Nathan BM, Redondo MJ, Herold KC, Evans-Molina C, DiMeglio LA, and Sosenko J
- Subjects
- Blood Glucose metabolism, C-Peptide metabolism, Glucose, Glucose Tolerance Test, Humans, Diabetes Mellitus, Type 1 diagnosis
- Abstract
Objective: To define the relationship between glucose and C-peptide during the progression to type 1 diabetes (T1D)., Research Design and Methods: We longitudinally studied glucose and C-peptide response curves (GCRCs), area under curve (AUC) for glucose, and AUC C-peptide from oral glucose tolerance tests (OGTTs), and Index60 (which integrates OGTT glucose and C-peptide values) in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 72) and TrialNet Pathway to Prevention Study (TNPTP) (n = 82) participants who had OGTTs at baseline and follow-up time points before diagnosis., Results: Similar evolutions of GCRC configurations were evident between DPT-1 and TNPTP from baseline to 0.5 years prediagnosis. Whereas AUC glucose increased throughout from baseline to 0.5 years prediagnosis, AUC C-peptide increased from baseline until 1.5 years prediagnosis (DPT-1, P = 0.004; TNPTP, P = 0.012) and then decreased from 1.5 to 0.5 years prediagnosis (DPT-1, P = 0.017; TNPTP, P = 0.093). This change was mostly attributable to change in the late AUC C-peptide response (i.e., 60- to 120-min AUC C-peptide). Median Index60 values of DPT-1 (1.44) and TNPTP (1.05) progressors to T1D 1.5 years prediagnosis (time of transition from increasing to decreasing AUC C-peptide) were used as thresholds to identify individuals at high risk for T1D in the full cohort at baseline (5-year risk of 0.75-0.88 for those above thresholds)., Conclusions: A transition from an increase to a decrease in AUC C-peptide ∼1.5 years prediagnosis was validated in two independent cohorts. The median Index60 value at that time point can be used as a pathophysiologic-based threshold for identifying individuals at high risk for T1D., (© 2022 by the American Diabetes Association.)
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- 2022
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31. Temporal development of T cell receptor repertoires during childhood in health and disease.
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Mitchell AM, Baschal EE, McDaniel KA, Simmons KM, Pyle L, Waugh K, Steck AK, Yu L, Gottlieb PA, Rewers MJ, Nakayama M, and Michels AW
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- Child, High-Throughput Nucleotide Sequencing methods, Humans, Infant, Receptors, Antigen, T-Cell metabolism, Receptors, Antigen, T-Cell, alpha-beta genetics, Diabetes Mellitus, Type 1 genetics, Influenza, Human
- Abstract
T cell receptor (TCR) sequences are exceptionally diverse and can now be comprehensively measured with next-generation sequencing technologies. However, a thorough investigation of longitudinal TCR repertoires throughout childhood in health and during development of a common childhood disease, type 1 diabetes (T1D), has not been undertaken. Here, we deep sequenced the TCR-β chain repertoires from longitudinal peripheral blood DNA samples at 4 time points beginning early in life (median age of 1.4 years) from children who progressed to T1D (n = 29) and age/sex-matched islet autoantibody-negative controls (n = 25). From 53 million TCR-β sequences, we show that the repertoire is extraordinarily diverse early in life and narrows with age independently of disease. We demonstrate the ability to identify specific TCR sequences, including those known to recognize influenza A and, separately, those specific for insulin and its precursor, preproinsulin. Insulin-reactive TCR-β sequences were more common and frequent in number as the disease progressed in those who developed T1D compared with genetically at risk nondiabetic children, and this was not the case for influenza-reactive sequences. As an independent validation, we sequenced and analyzed TCR-β repertoires from a cohort of new-onset T1D patients (n = 143), identifying the same preproinsulin-reactive TCRs. These results demonstrate an enrichment of preproinsulin-reactive TCR sequences during the progression to T1D, highlighting the importance of using disease-relevant TCR sequences as powerful biomarkers in autoimmune disorders.
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- 2022
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32. Changes in the Coexpression of Innate Immunity Genes During Persistent Islet Autoimmunity Are Associated With Progression of Islet Autoimmunity: Diabetes Autoimmunity Study in the Young (DAISY).
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Carry PM, Waugh K, Vanderlinden LA, Johnson RK, Buckner T, Rewers M, Steck AK, Yang I, Fingerlin TE, Kechris K, and Norris JM
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- Animals, Autoantibodies, Autoimmunity genetics, Diabetes Mellitus, Type 2, Disease Progression, Humans, Immunity, Innate genetics, Mice, Diabetes Mellitus, Type 1 metabolism, Islets of Langerhans metabolism
- Abstract
Longitudinal changes in gene expression during islet autoimmunity (IA) may provide insight into biological processes that explain progression to type 1 diabetes (T1D). We identified individuals from Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, autoantibodies present on two or more visits. Illumina's NovaSeq 6000 was used to quantify gene expression in whole blood. With linear mixed models we tested for changes in expression after IA that differed across individuals who progressed to T1D (progressors) (n = 25), reverted to an autoantibody-negative stage (reverters) (n = 47), or maintained IA positivity but did not develop T1D (maintainers) (n = 66). Weighted gene coexpression network analysis was used to identify coexpression modules. Gene Ontology pathway analysis of the top 150 differentially expressed genes (nominal P < 0.01) identified significantly enriched pathways including leukocyte activation involved in immune response, innate immune response, and regulation of immune response. We identified a module of 14 coexpressed genes with roles in the innate immunity. The hub gene, LTF, is known to have immunomodulatory properties. Another gene within the module, CAMP, is potentially relevant based on its role in promoting β-cell survival in a murine model. Overall, results provide evidence of alterations in expression of innate immune genes prior to onset of T1D., (© 2022 by the American Diabetes Association.)
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- 2022
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33. High-Throughput Multiplex Electrochemiluminescence Assay Applicable to General Population Screening for Type 1 Diabetes and Celiac Disease.
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He L, Jia X, Rasmussen CG, Waugh K, Miao D, Dong F, Frohnert B, Steck AK, Simmons KM, Rewers M, and Yu L
- Subjects
- Autoantibodies, Child, Humans, Sensitivity and Specificity, COVID-19, Celiac Disease diagnosis, Diabetes Mellitus, Type 1
- Abstract
Objective: Large-scale screening of the general population for islet autoantibodies (IAbs) to detect type 1 diabetes (T1D) has started worldwide. The standard screening method of separate radio-binding assay (RBA) for each IAb is an inefficient bottleneck. Furthermore, most positive results by RBA in screening of general population individuals without a clinical diagnosis of T1D are low-affinity and not predictive of future diabetes. Research Design and Methods: We have developed and validated a novel 6-Plex assay based on electrochemiluminescence (ECL) technology that combines in a single well high-affinity IAbs (to insulin, GAD, IA-2, and ZnT8), transglutaminase autoantibodies for celiac disease, and severe acute respiratory syndrome coronavirus 2 antibodies. The Autoimmunity Screening for Kids (ASK) provided 880 serum samples, from 828 children aged 1-17 years without diabetes who were previously tested for IAbs using single ECL assays and RBA assays. Results: Levels of all six antibodies in the 6-Plex ECL assay correlated well with respective single ECL assay levels. Similar to single ECL assays, the 6-Plex ECL assay positivity was congruent with the RBA in 95% (35/37) of children who later developed T1D and in 88% (105/119) high-risk children with multiple IAbs. In contrast, only 56% (86/154, P < 0.0001) of children with persistent single IAb by RBA were found to be positive by 6-Plex ECL assay. Of 555 samples negative for all IAbs by RBA, few (0.2%-0.5%) were positive at low levels in the 6-Plex ECL assay. Conclusions: The study demonstrated that the 6-Plex ECL assay compares favorably to the standard RBAs in terms of disease specificity for general population screening in children. The 6-Plex ECL assay was therefore adopted as the primary screening tool in the general population screening ASK program with advantages of high efficiency, low cost, and low serum volume.
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- 2022
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34. Continuous Glucose Monitoring Profiles in Healthy, Nondiabetic Young Children.
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DuBose SN, Kanapka LG, Bradfield B, Sooy M, Beck RW, and Steck AK
- Abstract
Context: Continuous glucose monitoring (CGM) is increasingly being used both for day-to-day management in patients with diabetes and in clinical research. While data on glycemic profiles of healthy, nondiabetic individuals exist, data on nondiabetic very young children are lacking., Objective: This work aimed to establish reference sensor glucose ranges in healthy, nondiabetic young children, using a current-generation CGM sensor., Methods: This prospective observational study took place in an institutional practice with healthy, nondiabetic children aged 1 to 6 years with normal body mass index. A blinded Dexcom G6 Pro CGM was worn for approximately 10 days by each participant. Main outcome measures included CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability., Results: Thirty-nine participants were included in the analyses. Mean average glucose was 103 mg/dL (5.7 mmol/L). Median percentage time between 70 and 140 mg/dL (3.9-7.8 mmol/L) was 96% (interquartile range, 92%-97%), mean within-individual coefficient of variation was 17 ± 3%, median time spent with glucose levels greater than 140 mg/dL was 3.4% (49 min/day), and median time less than 70 mg/dL (3.9 mmol/L) was 0.4% (6 min/day)., Conclusion: Collecting normative sensor glucose data and describing glycemic measures for young children fill an important informational gap and will be useful as a benchmark for future clinical studies., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.)
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- 2022
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35. Characterising the age-dependent effects of risk factors on type 1 diabetes progression.
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So M, O'Rourke C, Ylescupidez A, Bahnson HT, Steck AK, Wentworth JM, Bruggeman BS, Lord S, Greenbaum CJ, and Speake C
- Subjects
- Adolescent, Adult, Autoantibodies, Child, Child, Preschool, Disease Progression, Genetic Predisposition to Disease, HLA-DR3 Antigen, Humans, Infant, Male, Middle Aged, Risk Factors, Young Adult, Diabetes Mellitus, Type 1
- Abstract
Aims/hypothesis: Age is known to be one of the most important stratifiers of disease progression in type 1 diabetes. However, what drives the difference in rate of progression between adults and children is poorly understood. Evidence suggests that many type 1 diabetes disease predictors do not have the same effect across the age spectrum. Without a comprehensive analysis describing the varying risk profiles of predictors over the age continuum, researchers and clinicians are susceptible to inappropriate assessment of risk when examining populations of differing ages. We aimed to systematically assess and characterise how the effect of key type 1 diabetes risk predictors changes with age., Methods: Using longitudinal data from single- and multiple-autoantibody-positive at-risk individuals recruited between the ages of 1 and 45 years in TrialNet's Pathway to Prevention Study, we assessed and visually characterised the age-varying effect of key demographic, immune and metabolic predictors of type 1 diabetes by employing a flexible spline model. Two progression outcomes were defined: participants with single autoantibodies (n=4893) were analysed for progression to multiple autoantibodies or type 1 diabetes, and participants with multiple autoantibodies were analysed (n=3856) for progression to type 1 diabetes., Results: Several predictors exhibited significant age-varying effects on disease progression. Amongst single-autoantibody participants, HLA-DR3 (p=0.007), GAD65 autoantibody positivity (p=0.008), elevated BMI (p=0.007) and HOMA-IR (p=0.002) showed a significant increase in effect on disease progression with increasing age. Insulin autoantibody positivity had a diminishing effect with older age in single-autoantibody-positive participants (p<0.001). Amongst multiple-autoantibody-positive participants, male sex (p=0.002) was associated with an increase in risk for progression, and HLA DR3/4 (p=0.05) showed a decreased effect on disease progression with older age. In both single- and multiple-autoantibody-positive individuals, significant changes in HR with age were seen for multiple measures of islet function. Risk estimation using prediction risk score Index60 was found to be better at a younger age for both single- and multiple-autoantibody-positive individuals (p=0.007 and p<0.001, respectively). No age-varying effect was seen for prediction risk score DPTRS (p=0.861 and p=0.178, respectively). Multivariable analyses suggested that incorporating the age-varying effect of the individual components of these validated risk scores has the potential to enhance the risk estimate., Conclusions/interpretation: Analysing the age-varying effect of disease predictors improves understanding and prediction of type 1 diabetes disease progression, and should be leveraged to refine prediction models and guide mechanistic studies., (© 2022. Crown.)
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- 2022
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36. Association of High-Affinity Autoantibodies With Type 1 Diabetes High-Risk HLA Haplotypes.
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Triolo TM, Pyle L, Broncucia H, Armstrong T, Yu L, Gottlieb PA, and Steck AK
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- Adolescent, Adult, Autoantibodies, Child, Child, Preschool, Female, Glutamate Decarboxylase, HLA Antigens genetics, HLA-DR3 Antigen genetics, HLA-DR4 Antigen genetics, Haplotypes, Humans, Insulin Antibodies, Male, Young Adult, Diabetes Mellitus, Type 1 diagnosis
- Abstract
Objective: Electrochemiluminescence (ECL) assays are high-affinity autoantibody (Ab) tests that are more specific than Abs detected by traditional radiobinding assays (RBA) for risk screening and prediction of progression to type 1 diabetes. We sought to characterize the association of high-risk human leukocyte antigen (HLA) haplotypes and genotypes with ECL positivity and levels in relatives of individuals with type 1 diabetes., Methods: We analyzed 602 participants from the TrialNet Pathway to Prevention Study who were positive for at least 1 RBA diabetes-related Ab [glutamic acid decarboxylase autoantibodies (GADA) or insulin autoantibodies (IAA)] and for whom ECL and HLA data were available. ECL and RBA Ab levels were converted to SD units away from mean (z-scores) for analyses., Results: Mean age at initial visit was 19.4 ± 13.7 years; 344 (57.1%) were female and 104 (17.3%) carried the high-risk HLA-DR3/4*0302 genotype. At initial visit 424/602 (70.4%) participants were positive for either ECL-GADA or ECL-IAA, and 178/602 (29.6%) were ECL negative. ECL and RBA-GADA positivity were associated with both HLA-DR3 and DR4 haplotypes (all Ps < 0.05), while ECL and RBA-GADA z-score titers were higher in participants with HLA-DR3 haplotypes only (both Ps < 0.001). ECL-IAA (but not RBA-IAA) positivity was associated with the HLA-DR4 haplotype (P < 0.05)., Conclusions: ECL-GADA positivity is associated with the HLA-DR3 and HLA-DR4 haplotypes and levels are associated with the HLA-DR3 haplotype. ECL-IAA positivity is associated with HLA-DR4 haplotype. These studies further contribute to the understanding of genetic risk and islet autoimmunity endotypes in type 1 diabetes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
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- 2022
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37. Heterogeneity of DKA Incidence and Age-Specific Clinical Characteristics in Children Diagnosed With Type 1 Diabetes in the TEDDY Study.
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Jacobsen LM, Vehik K, Veijola R, Warncke K, Toppari J, Steck AK, Gesualdo P, Akolkar B, Lundgren M, Hagopian WA, She JX, Rewers M, Ziegler AG, Krischer JP, Larsson HE, and Haller MJ
- Subjects
- Age Factors, Child, Humans, Incidence, Insulin, Diabetes Mellitus, Type 1 complications, Diabetic Ketoacidosis complications, Diabetic Ketoacidosis etiology
- Abstract
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., (© 2022 by the American Diabetes Association.)
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- 2022
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38. CGM Metrics Predict Imminent Progression to Type 1 Diabetes: Autoimmunity Screening for Kids (ASK) Study.
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Steck AK, Dong F, Geno Rasmussen C, Bautista K, Sepulveda F, Baxter J, Yu L, Frohnert BI, and Rewers MJ
- Subjects
- Autoimmunity, Benchmarking, Blood Glucose analysis, Blood Glucose Self-Monitoring, Child, Child, Preschool, Female, Glycated Hemoglobin analysis, Humans, Infant, Infant, Newborn, Male, Diabetes Mellitus, Type 1 diagnosis
- Abstract
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., (© 2022 by the American Diabetes Association.)
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- 2022
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39. High-affinity ZnT8 Autoantibodies by Electrochemiluminescence Assay Improve Risk Prediction for Type 1 Diabetes.
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Jia X, He L, Miao D, Waugh K, Rasmussen CG, Dong F, Steck AK, Rewers M, and Yu L
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- Adult, Aged, Autoantibodies immunology, China epidemiology, Cohort Studies, Diabetes Mellitus, Type 1 blood, Diabetes Mellitus, Type 1 epidemiology, Diabetes Mellitus, Type 1 immunology, Electrochemistry, Female, Follow-Up Studies, Humans, Incidence, Luminescent Measurements, Male, Middle Aged, Prognosis, Risk Factors, Autoantibodies blood, Biomarkers blood, Diabetes Mellitus, Type 1 diagnosis, Mass Screening methods, Zinc Transporter 8 immunology
- Abstract
Context: Single ZnT8 autoantibody (ZnT8A) positivity by standard radiobinding assay (RBA) is commonly seen in nondiabetes population-based screening and the risk of progression to type 1 diabetes (T1D) in subjects with single ZnT8A is unknown., Objective: Identify the risk of progression to T1D in individuals positive only for ZnT8A., Methods: We developed an electrochemiluminescence (ECL) assay to detect high-affinity ZnT8A and validated it in 3 populations: 302 patients newly diagnosed with T1D, 135 nondiabetic children positive for ZnT8A by RBA among 23 400 children screened by the Autoimmunity Screening for Kids (ASK) study, and 123 nondiabetic children multiple autoantibody positive or single ZnT8A positive by RBA participating in the Diabetes Autoimmunity Study in the Young (DAISY)., Results: In 302 patients with T1D at diagnosis, the positivity for ZnT8A was 62% both in RBA and ECL. Among ASK 135 participants positive for RBA-ZnT8A, 64 were detected ZnT8A as the only islet autoantibody. Of these 64, only 9 were confirmed by ECL-ZnT8A, found to be of high affinity with increased T1D risk. The overall positive predictive value of ECL-ZnT8A for T1D risk was 87.1%, significantly higher than that of RBA-ZnT8A (53.5%, P < .001). In DAISY, 11 of 2547 children who had no positivity previously detected for other islet autoantibodies were identified as single ZnT8A by RBA; of these, 3 were confirmed positive by ECL-ZnT8A and all 3 progressed to clinical T1D., Conclusion: A large proportion of ZnT8A by RBA are single ZnT8A with low T1D risk, whereas ZnT8A by ECL was of high affinity and high prediction for T1D development., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society.)
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- 2021
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40. Time to Peak Glucose and Peak C-Peptide During the Progression to Type 1 Diabetes in the Diabetes Prevention Trial and TrialNet Cohorts.
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Voss MG, Cuthbertson DD, Cleves MM, Xu P, Evans-Molina C, Palmer JP, Redondo MJ, Steck AK, Lundgren M, Larsson H, Moore WV, Atkinson MA, Sosenko JM, and Ismail HM
- Subjects
- Adolescent, Adult, Blood Glucose, C-Peptide, Child, Child, Preschool, Female, Glucose Tolerance Test, Humans, Male, Young Adult, Diabetes Mellitus, Type 1, Disease Progression
- Abstract
Objective: To assess the progression of type 1 diabetes using time to peak glucose or C-peptide during oral glucose tolerance tests (OGTTs) in autoantibody-positive relatives of people with type 1 diabetes., Research Design and Methods: We examined 2-h OGTTs of participants in the Diabetes Prevention Trial Type 1 (DPT-1) and TrialNet Pathway to Prevention (PTP) studies. We included 706 DPT-1 participants (mean ± SD age, 13.84 ± 9.53 years; BMI Z-score, 0.33 ± 1.07; 56.1% male) and 3,720 PTP participants (age, 16.01 ± 12.33 years; BMI Z-score, 0.66 ± 1.3; 49.7% male). Log-rank testing and Cox regression analyses with adjustments (age, sex, race, BMI Z-score, HOMA-insulin resistance, and peak glucose/C-peptide levels, respectively) were performed., Results: In each of DPT-1 and PTP, higher 5-year diabetes progression risk was seen in those with time to peak glucose >30 min and time to peak C-peptide >60 min ( P < 0.001 for all groups), before and after adjustments. In models examining strength of association with diabetes development, associations were greater for time to peak C-peptide versus peak C-peptide value (DPT-1: χ
2 = 25.76 vs. χ2 = 8.62; PTP: χ2 = 149.19 vs. χ2 = 79.98; all P < 0.001). Changes in the percentage of individuals with delayed glucose and/or C-peptide peaks were noted over time., Conclusions: In two independent at-risk populations, we show that those with delayed OGTT peak times for glucose or C-peptide are at higher risk of diabetes development within 5 years, independent of peak levels. Moreover, time to peak C-peptide appears more predictive than the peak level, suggesting its potential use as a specific biomarker for diabetes progression., (© 2021 by the American Diabetes Association.)- Published
- 2021
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41. Advances in Type 1 Diabetes Prediction Using Islet Autoantibodies: Beyond a Simple Count.
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So M, Speake C, Steck AK, Lundgren M, Colman PG, Palmer JP, Herold KC, and Greenbaum CJ
- Subjects
- Autoantibodies, Disease Progression, Humans, Prospective Studies, Diabetes Mellitus, Type 1 diagnosis, Islets of Langerhans
- Abstract
Islet autoantibodies are key markers for the diagnosis of type 1 diabetes. Since their discovery, they have also been recognized for their potential to identify at-risk individuals prior to symptoms. To date, risk prediction using autoantibodies has been based on autoantibody number; it has been robustly shown that nearly all multiple-autoantibody-positive individuals will progress to clinical disease. However, longitudinal studies have demonstrated that the rate of progression among multiple-autoantibody-positive individuals is highly heterogenous. Accurate prediction of the most rapidly progressing individuals is crucial for efficient and informative clinical trials and for identification of candidates most likely to benefit from disease modification. This is increasingly relevant with the recent success in delaying clinical disease in presymptomatic subjects using immunotherapy, and as the field moves toward population-based screening. There have been many studies investigating islet autoantibody characteristics for their predictive potential, beyond a simple categorical count. Predictive features that have emerged include molecular specifics, such as epitope targets and affinity; longitudinal patterns, such as changes in titer and autoantibody reversion; and sequence-dependent risk profiles specific to the autoantibody and the subject's age. These insights are the outworking of decades of prospective cohort studies and international assay standardization efforts and will contribute to the granularity needed for more sensitive and specific preclinical staging. The aim of this review is to identify the dynamic and nuanced manifestations of autoantibodies in type 1 diabetes, and to highlight how these autoantibody features have the potential to improve study design of trials aiming to predict and prevent disease., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
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- 2021
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42. TCF7L2 Genetic Variants Do Not Influence Insulin Sensitivity or Secretion Indices in Autoantibody-Positive Individuals at Risk for Type 1 Diabetes.
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Redondo MJ, Warnock MV, Libman IM, Bocchino LE, Cuthbertson D, Geyer S, Pugliese A, Steck AK, Evans-Molina C, Becker D, Sosenko JM, and Bacha F
- Subjects
- Adolescent, C-Peptide, Humans, Insulin, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein genetics, Diabetes Mellitus, Type 1 genetics, Diabetes Mellitus, Type 2, Insulin Resistance genetics
- Abstract
Objective: We aimed to test whether type 2 diabetes (T2D)-associated TCF7L2 genetic variants affect insulin sensitivity or secretion in autoantibody-positive relatives at risk for type 1 diabetes (T1D)., Research Design and Methods: We studied autoantibody-positive TrialNet Pathway to Prevention study participants ( N = 1,061) (mean age 16.3 years) with TCF7L2 single nucleotide polymorphism (SNP) information and baseline oral glucose tolerance test (OGTT) to calculate indices of insulin sensitivity and secretion. With Bonferroni correction for multiple comparisons, P values < 0.0086 were considered statistically significant., Results: None, one, and two T2D-linked TCF7L2 alleles were present in 48.1%, 43.9%, and 8.0% of the participants, respectively. Insulin sensitivity (as reflected by 1/fasting insulin [1/I
F ]) decreased with increasing BMI z score and was lower in Hispanics. Insulin secretion (as measured by 30-min C-peptide index) positively correlated with age and BMI z score. Oral disposition index was negatively correlated with age, BMI z score, and Hispanic ethnicity. None of the indices were associated with TCF7L2 SNPs. In multivariable analysis models with age, BMI z score, ethnicity, sex, and TCF7L2 alleles as independent variables, C-peptide index increased with age, while BMI z score was associated with higher insulin secretion (C-peptide index), lower insulin sensitivity (1/IF ), and lower disposition index; there was no significant effect of TCF7L2 SNPs on any of these indices. When restricting the analyses to participants with a normal OGTT ( n = 743; 70%), the results were similar., Conclusions: In nondiabetic autoantibody-positive individuals, TCF7L2 SNPs were not related to insulin sensitivity or secretion indices after accounting for BMI z score, age, sex, and ethnicity., (© 2021 by the American Diabetes Association.)- Published
- 2021
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43. Development of a standardized MRI protocol for pancreas assessment in humans.
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Virostko J, Craddock RC, Williams JM, Triolo TM, Hilmes MA, Kang H, Du L, Wright JJ, Kinney M, Maki JH, Medved M, Waibel M, Kay TWH, Thomas HE, Greeley SAW, Steck AK, Moore DJ, and Powers AC
- Subjects
- Adult, Diffusion Magnetic Resonance Imaging methods, Female, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, Male, Phantoms, Imaging, Prospective Studies, Reproducibility of Results, Magnetic Resonance Imaging methods, Magnetic Resonance Imaging standards, Pancreas diagnostic imaging
- Abstract
Magnetic resonance imaging (MRI) has detected changes in pancreas volume and other characteristics in type 1 and type 2 diabetes. However, differences in MRI technology and approaches across locations currently limit the incorporation of pancreas imaging into multisite trials. The purpose of this study was to develop a standardized MRI protocol for pancreas imaging and to define the reproducibility of these measurements. Calibrated phantoms with known MRI properties were imaged at five sites with differing MRI hardware and software to develop a harmonized MRI imaging protocol. Subsequently, five healthy volunteers underwent MRI at four sites using the harmonized protocol to assess pancreas size, shape, apparent diffusion coefficient (ADC), longitudinal relaxation time (T1), magnetization transfer ratio (MTR), and pancreas and hepatic fat fraction. Following harmonization, pancreas size, surface area to volume ratio, diffusion, and longitudinal relaxation time were reproducible, with coefficients of variation less than 10%. In contrast, non-standardized image processing led to greater variation in MRI measurements. By using a standardized MRI image acquisition and processing protocol, quantitative MRI of the pancreas performed at multiple locations can be incorporated into clinical trials comparing pancreas imaging measures and metabolic state in individuals with type 1 or type 2 diabetes., Competing Interests: The authors have declared that no competing interests exist.
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- 2021
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44. Phospholipid Levels at Seroconversion Are Associated With Resolution of Persistent Islet Autoimmunity: The Diabetes Autoimmunity Study in the Young.
- Author
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Carry PM, Vanderlinden LA, Johnson RK, Buckner T, Fiehn O, Steck AK, Kechris K, Yang I, Fingerlin TE, Rewers M, and Norris JM
- Subjects
- Child, Child, Preschool, Diabetes Mellitus, Type 1 etiology, Diabetes Mellitus, Type 1 immunology, Female, Humans, Male, Metabolomics, Proportional Hazards Models, Autoimmunity, Islets of Langerhans immunology, Phospholipids blood, Seroconversion
- Abstract
Reversion of islet autoimmunity (IA) may point to mechanisms that prevent IA progression. We followed 199 individuals who developed IA during the Diabetes Autoimmunity Study in the Young. Untargeted metabolomics was performed in serum samples following IA. Cox proportional hazards models were used to test whether the metabolites (2,487) predicted IA reversion: two or more consecutive visits negative for all autoantibodies. We conducted a principal components analysis (PCA) of the top metabolites; |hazard ratio (HR) >1.25| and nominal P < 0.01. Phosphatidylcholine (16:0_18:1(9Z)) was the strongest individual metabolite (HR per 1 SD 2.16, false discovery rate (FDR)-adjusted P = 0.0037). Enrichment analysis identified four clusters (FDR P < 0.10) characterized by an overabundance of sphingomyelin (d40:0), phosphatidylcholine (16:0_18:1(9Z)), phosphatidylcholine (30:0), and l-decanoylcarnitine. Overall, 63 metabolites met the criteria for inclusion in the PCA. PC1 (HR 1.4, P < 0.0001), PC2 (HR 0.85, P = 0.0185), and PC4 (HR 1.28, P = 0.0103) were associated with IA reversion. Given the potential influence of diet on the metabolome, we investigated whether nutrients were correlated with PCs. We identified 20 nutrients that were correlated with the PCs ( P < 0.05). Total sugar intake was the top nutrient. Overall, we identified an association between phosphatidylcholine, sphingomyelin, and carnitine levels and reversion of IA., (© 2021 by the American Diabetes Association.)
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- 2021
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45. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes.
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Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, Chen WM, Santa Cruz DF, Yang H, Cutler AJ, Crouch DJM, Farber E, Bridges SL Jr, Edberg JC, Kimberly RP, Buckner JH, Deloukas P, Divers J, Dabelea D, Lawrence JM, Marcovina S, Shah AS, Greenbaum CJ, Atkinson MA, Gregersen PK, Oksenberg JR, Pociot F, Rewers MJ, Steck AK, Dunger DB, Wicker LS, Concannon P, Todd JA, and Rich SS
- Subjects
- Autoimmunity genetics, CD4-Positive T-Lymphocytes immunology, CD4-Positive T-Lymphocytes metabolism, Diabetes Mellitus, Type 1 drug therapy, Diabetes Mellitus, Type 1 metabolism, Drug Discovery, Gene Expression, Humans, Molecular Targeted Therapy, Protein Interaction Mapping, Alleles, Chromosome Mapping, Diabetes Mellitus, Type 1 genetics, Genetic Predisposition to Disease, Genetic Variation, Genomics methods
- Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10
-8 ) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D., (© 2021. Crown.)- Published
- 2021
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46. Factors Associated With the Decline of C-Peptide in a Cohort of Young Children Diagnosed With Type 1 Diabetes.
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Steck AK, Liu X, Krischer JP, Haller MJ, Veijola R, Lundgren M, Ahmed S, Akolkar B, Toppari J, Hagopian WA, Rewers MJ, and Elding Larsson H
- Subjects
- Adolescent, Age of Onset, Autoantibodies blood, Case-Control Studies, Child, Child, Preschool, Cohort Studies, Diabetes Mellitus, Type 1 diagnosis, Diabetes Mellitus, Type 1 epidemiology, Disease Progression, Down-Regulation, Female, Follow-Up Studies, Humans, Infant, Male, C-Peptide blood, Diabetes Mellitus, Type 1 blood
- Abstract
Context: Understanding factors involved in the rate of C-peptide decline is needed to tailor therapies for type 1 diabetes (T1D)., Objective: Evaluate factors associated with rate of C-peptide decline after a T1D diagnosis in young children., Design: Observational study., Setting: Academic centers., Participants: A total of 57 participants from the Environmental Determinants of Diabetes in the Young (TEDDY) study who were enrolled at 3 months of age and followed until T1D, and 56 age-matched children diagnosed with T1D in the community., Intervention: A mixed meal tolerance test was used to measure the area under the curve (AUC) C-peptide at 1, 3, 6, 12, and 24 months postdiagnosis., Outcome: Factors associated with rate of C-peptide decline during the first 2 years postdiagnosis were evaluated using mixed effects models, adjusting for age at diagnosis and baseline C-peptide., Results: Adjusted slopes of AUC C-peptide decline did not differ between TEDDY subjects and community controls (P = 0.21), although the former had higher C-peptide baseline levels. In univariate analyses combining both groups (n = 113), younger age, higher weight and body mass index z-scores, female sex, an increased number increased number of islet autoantibodies, and IA-2A or ZnT8A positivity at baseline were associated with a higher rate of C-peptide loss. Younger age, female sex, and higher weight z-score remained significant in multivariate analysis (all P < 0.02). At 3 months after diagnosis, higher HbA1c became an additional independent factor associated with a higher rate of C-peptide decline (P < 0.01)., Conclusion: Younger age at diagnosis, female sex, higher weight z-score, and HbA1c were associated with a higher rate of C-peptide decline after T1D diagnosis in young children., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
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- 2021
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47. Proinsulin:C-peptide ratio trajectories over time in relatives at increased risk of progression to type 1 diabetes.
- Author
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Triolo TM, Pyle L, Seligova S, Yu L, Simmons K, Gottlieb P, Evans-Molina C, and Steck AK
- Abstract
Objective: Biomarkers are needed to characterize heterogeneity within populations at risk for type 1 diabetes. The ratio of proinsulin to C-peptide (PI:C ratio), has been proposed as a biomarker of beta cell dysfunction and is associated with progression to type 1 diabetes. However, relationships between PI:C ratios and autoantibody type and number have not been examined. We sought to characterize PI:C ratios in multiple islet autoantibody positive, single autoantibody positive and autoantibody negative relatives of individuals with type 1 diabetes., Methods: We measured PI:C ratios and autoantibodies with both electrochemiluminescence (ECL) assays (ECL-IAA, ECL-GADA and ECL-IA2A) and radiobinding (RBA) assays (mIAA, GADA, IA2A and ZnT8A) in 98 relatives of individuals with type 1 diabetes followed in the TrialNet Pathway to Prevention Study at the Barbara Davis Center for a mean of 7.4 ± 4.1 years. Of these subjects, eight progressed to T1D, 31 were multiple autoantibody (Ab) positive, 37 were single Ab positive and 22 were Ab negative (by RBA)., Results: In cross-sectional analyses, there were no significant differences in PI:C ratios between type 1 diabetes and/or multiple Ab positive subjects (4.16 ± 4.06) compared to single Ab positive subjects (4.08 ± 4.34) and negative Ab subjects (3.72 ± 3.78) (p = 0.92) overall or after adjusting for age, sex and BMI. Higher PI:C ratios were associated with mIAA titers (p = 0.03) and showed an association with ECL-IA2A titers (p = 0.09), but not with ECL-IAA, GADA, ECL-GADA, IA2A nor ZnT8A titers. In mixed-effects longitudinal models, the trajectories of PI:C ratio over time were significantly different between the Ab negative and multiple Ab positive/type 1 diabetes groups, after adjusting for sex, age, and BMI (p = 0.04)., Conclusions: PI:C ratio trajectories increase over time in subjects who have multiple Ab or develop type 1 diabetes and may be a helpful biomarker to further characterize and stratify risk of progression to type 1 diabetes over time., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)
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- 2021
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48. T-cell responses to hybrid insulin peptides prior to type 1 diabetes development.
- Author
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Mitchell AM, Alkanani AA, McDaniel KA, Pyle L, Waugh K, Steck AK, Nakayama M, Yu L, Gottlieb PA, Rewers MJ, and Michels AW
- Subjects
- Adolescent, Adult, Autoantibodies genetics, Autoantibodies immunology, Autoantigens immunology, Autoimmunity genetics, Autoimmunity immunology, CD4-Positive T-Lymphocytes immunology, Child, Diabetes Mellitus, Type 1 immunology, Diabetes Mellitus, Type 1 pathology, Disease Progression, Female, Humans, Insulin genetics, Insulin-Secreting Cells immunology, Islets of Langerhans immunology, Islets of Langerhans pathology, Male, Peptides immunology, T-Lymphocytes immunology, Young Adult, Autoantigens genetics, Diabetes Mellitus, Type 1 genetics, Insulin immunology, Interferon-gamma genetics, Peptides genetics
- Abstract
T-cell responses to posttranslationally modified self-antigens are associated with many autoimmune disorders. In type 1 diabetes, hybrid insulin peptides (HIPs) are implicated in the T-cell-mediated destruction of insulin-producing β-cells within pancreatic islets. The natural history of the disease is such that it allows for the study of T-cell reactivity prior to the onset of clinical symptoms. We hypothesized that CD4 T-cell responses to posttranslationally modified islet peptides precedes diabetes onset. In a cohort of genetically at-risk individuals, we measured longitudinal T-cell responses to native insulin and hybrid insulin peptides. Both proinflammatory (interferon-γ) and antiinflammatory (interluekin-10) cytokine responses to HIPs were more robust than those to native peptides, and the ratio of such responses oscillated between pro- and antiinflammatory over time. However, individuals who developed islet autoantibodies or progressed to clinical type 1 diabetes had predominantly inflammatory T-cell responses to HIPs. Additionally, several HIP T-cell responses correlated to worsening measurements of blood glucose, highlighting the relevance of T-cell responses to posttranslationally modified peptides prior to autoimmune disease development., Competing Interests: Competing interest statement: P.A.G. and A.W.M. are inventors on a patent, “Insulin Mimotopes and Methods of Using the Same” (US patent number 10,363,288).
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- 2021
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49. Mass Screening for Celiac Disease: The Autoimmunity Screening for Kids Study.
- Author
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Stahl MG, Geno Rasmussen C, Dong F, Waugh K, Norris JM, Baxter J, Yu L, Steck AK, Frohnert BI, Liu E, and Rewers MJ
- Subjects
- Adolescent, Asymptomatic Diseases, Celiac Disease immunology, Child, Child, Preschool, Diagnostic Techniques, Radioisotope, Electrochemical Techniques, Female, Humans, Immunoglobulin A immunology, Immunoglobulin D immunology, Immunoglobulin E immunology, Immunoglobulin G immunology, Immunoglobulin M immunology, Infant, Male, Mass Screening, Protein Glutamine gamma Glutamyltransferase 2, Serologic Tests, Autoantibodies immunology, Celiac Disease diagnosis, GTP-Binding Proteins immunology, Transglutaminases immunology
- Abstract
Introduction: The Autoimmunity Screening for Kids (ASK) study is a large scale pediatric screening study in Colorado for celiac disease (CD) and type 1 diabetes. This is a report of the CD outcomes for the first 9,973 children screened through ASK., Methods: ASK screens children aged 1-17 years for CD using 2 highly sensitive assays for tissue transglutaminase autoantibodies (TGA): a radiobinding (RBA) assay for IgA TGA and an electrochemiluminescence (ECL) assay that detects all TGA isotypes. Children who test positive on either assay are asked to return for confirmatory testing. Those with a confirmed RBA TGA level ≥ 0.1 (twice the upper limit of normal) are referred to the Colorado Center for Celiac Disease for further evaluation; all others are referred to primary care., Results: Of the initial 9,973 children screened, 242 children were TGA+ by any assay. Of those initially positive, 185 children (76.4%) have completed a confirmation blood draw with 149 children (80.5%) confirming positive by RBA TGA. Confirmed RBA TGA+ was associated with a family history of CD (odds ratio [OR] = 1.83; 95% confidence interval 1.06-3.16), non-Hispanic white ethnicity (OR = 3.34; 2.32-4.79), and female sex (OR = 1.43; 1.03-1.98). Gastrointestinal symptoms of CD, assessed at the initial screening, were reported equally often among the RBA TGA+ vs TGA- children (32.1% vs 30.5%, P = 0.65)., Discussion: The initial results of this ongoing mass-screening program confirm a high prevalence of undiagnosed CD autoimmunity in a screened US population. Symptoms at initial screening were not associated with TGA status (see Visual abstract, Supplementary Digital Content 5, http://links.lww.com/AJG/B587)., (Copyright © 2020 by The American College of Gastroenterology.)
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- 2021
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50. Golimumab and Beta-Cell Function in Youth with New-Onset Type 1 Diabetes.
- Author
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Quattrin T, Haller MJ, Steck AK, Felner EI, Li Y, Xia Y, Leu JH, Zoka R, Hedrick JA, Rigby MR, and Vercruysse F
- Subjects
- Adolescent, Antibodies, Monoclonal adverse effects, Antibodies, Monoclonal pharmacology, Area Under Curve, C-Peptide metabolism, Child, Diabetes Mellitus, Type 1 blood, Diabetes Mellitus, Type 1 metabolism, Double-Blind Method, Drug Therapy, Combination, Female, Glycated Hemoglobin analysis, Humans, Hypoglycemia chemically induced, Hypoglycemic Agents adverse effects, Insulin administration & dosage, Insulin adverse effects, Insulin-Secreting Cells drug effects, Insulin-Secreting Cells metabolism, Male, Proinsulin metabolism, Young Adult, Antibodies, Monoclonal therapeutic use, Diabetes Mellitus, Type 1 drug therapy, Hypoglycemic Agents administration & dosage, Insulin metabolism, Tumor Necrosis Factor-alpha antagonists & inhibitors
- Abstract
Background: Type 1 diabetes is an autoimmune disease characterized by progressive loss of pancreatic beta cells. Golimumab is a human monoclonal antibody specific for tumor necrosis factor α that has already been approved for the treatment of several autoimmune conditions in adults and children. Whether golimumab could preserve beta-cell function in youth with newly diagnosed overt (stage 3) type 1 diabetes is unknown., Methods: In this phase 2, multicenter, placebo-controlled, double-blind, parallel-group trial, we randomly assigned, in a 2:1 ratio, children and young adults (age range, 6 to 21 years) with newly diagnosed overt type 1 diabetes to receive subcutaneous golimumab or placebo for 52 weeks. The primary end point was endogenous insulin production, as assessed according to the area under the concentration-time curve for C-peptide level in response to a 4-hour mixed-meal tolerance test (4-hour C-peptide AUC) at week 52. Secondary and additional end points included insulin use, the glycated hemoglobin level, the number of hypoglycemic events, the ratio of fasting proinsulin to C-peptide over time, and response profile., Results: A total of 84 participants underwent randomization - 56 were assigned to the golimumab group and 28 to the placebo group. The mean (±SD) 4-hour C-peptide AUC at week 52 differed significantly between the golimumab group and the placebo group (0.64±0.42 pmol per milliliter vs. 0.43±0.39 pmol per milliliter, P<0.001). A treat-to-target approach led to good glycemic control in both groups, and there was no significant difference between the groups in glycated hemoglobin level. Insulin use was lower with golimumab than with placebo. A partial-remission response (defined as an insulin dose-adjusted glycated hemoglobin level score [calculated as the glycated hemoglobin level plus 4 times the insulin dose] of ≤9) was observed in 43% of participants in the golimumab group and in 7% of those in the placebo group (difference, 36 percentage points; 95% CI, 22 to 55). The mean number of hypoglycemic events did not differ between the trial groups. Hypoglycemic events that were recorded as adverse events at the discretion of investigators were reported in 13 participants (23%) in the golimumab group and in 2 (7%) of those in the placebo group. Antibodies to golimumab were detected in 30 participants who received the drug; 29 had antibody titers lower than 1:1000, of whom 12 had positive results for neutralizing antibodies., Conclusions: Among children and young adults with newly diagnosed overt type 1 diabetes, golimumab resulted in better endogenous insulin production and less exogenous insulin use than placebo. (Funded by Janssen Research and Development; T1GER ClinicalTrials.gov number, NCT02846545.)., (Copyright © 2020 Massachusetts Medical Society.)
- Published
- 2020
- Full Text
- View/download PDF
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