IU Indianapolis ScholarWorks :: Browsing by Author "Wentworth, John M."

Browsing by Author "Wentworth, John M."

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Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables
(Springer Nature, 2019-01) Wentworth, John M.; Bediaga, Naiara G.; Giles, Lynne C.; Ehlers, Mario; Gitelman, Stephen E.; Geyer, Susan; Evans-Molina, Carmella; Harrison, Leonard C.; Medicine, School of Medicine
AIMS/HYPOTHESIS: Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS: Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS: A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION: CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes.
Clinical trial data validate the C-peptide estimate model in type 1 diabetes
(SpringerLink, 2020-04) Wentworth, John M.; Bediaga, Naiara G.; Gitelman, Stephen E.; Evans-Molina, Carmela; Gottlieb, Peter A.; Colman, Peter G.; Haller, Michael J.; Harrison, Leonard C.; Medicine, School of Medicine
Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes
(Springer, 2024-09) Phillip, Moshe; Achenbach, Peter; Addala, Ananta; Albanese-O'Neill, Anastasia; Battelino, Tadej; Bell, Kirstine J.; Besser, Rachel E. J.; Bonifacio, Ezio; Colhoun, Helen M.; Couper, Jennifer J.; Craig, Maria E.; Danne, Thomas; de Beaufort, Carine; Dovc, Klemen; Driscoll, Kimberly A.; Dutta, Sanjoy; Ebekozien, Osagie; Elding Larsson, Helena; Feiten, Daniel J.; Frohnert, Brigitte I.; Gabbay, Robert A.; Gallagher, Mary P.; Greenbaum, Carla J.; Griffin, Kurt J.; Hagopian, William; Haller, Michael J.; Hendrieckx, Christel; Hendriks, Emile; Holt, Richard I. G.; Hughes, Lucille; Ismail, Heba M.; Jacobsen, Laura M.; Johnson, Suzanne B.; Kolb, Leslie E.; Kordonouri, Olga; Lange, Karin; Lash, Robert W.; Lernmark, Åke; Libman, Ingrid; Lundgren, Markus; Maahs, David M.; Marcovecchio, M. Loredana; Mathieu, Chantal; Miller, Kellee M.; O'Donnell, Holly K.; Oron, Tal; Patil, Shivajirao P.; Pop-Busui, Rodica; Rewers, Marian J.; Rich, Stephen S.; Schatz, Desmond A.; Schulman-Rosenbaum, Rifka; Simmons, Kimber M.; Sims, Emily K.; Skyler, Jay S.; Smith, Laura B.; Speake, Cate; Steck, Andrea K.; Thomas, Nicholas P. B.; Tonyushkina, Ksenia N.; Veijola, Riitta; Wentworth, John M.; Wherrett, Diane K.; Wood, Jamie R.; Ziegler, Anette-Gabriele; DiMeglio, Linda A.; Pediatrics, School of Medicine
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.
Correction to: Consensus guidance for monitoring individuals with islet autoantibody‑positive pre‑stage 3 type 1 diabetes
(Springer, 2024) Phillip, Moshe; Achenbach, Peter; Addala, Ananta; Albanese-O'Neill, Anastasia; Battelino, Tadej; Bell, Kirstine J.; Besser, Rachel E. J.; Bonifacio, Ezio; Colhoun, Helen M.; Couper, Jennifer J.; Craig, Maria E.; Danne, Thomas; de Beaufort, Carine; Dovc, Klemen; Driscoll, Kimberly A.; Dutta, Sanjoy; Ebekozien, Osagie; Elding Larsson, Helena; Feiten, Daniel J.; Frohnert, Brigitte I.; Gabbay, Robert A.; Gallagher, Mary P.; Greenbaum, Carla J.; Griffin, Kurt J.; Hagopian, William; Haller, Michael J.; Hendrieckx, Christel; Hendriks, Emile; Holt, Richard I. G.; Hughes, Lucille; Ismail, Heba M.; Jacobsen, Laura M.; Johnson, Suzanne B.; Kolb, Leslie E.; Kordonouri, Olga; Lange, Karin; Lash, Robert W.; Lernmark, Åke; Libman, Ingrid; Lundgren, Markus; Maahs, David M.; Marcovecchio, M. Loredana; Mathieu, Chantal; Miller, Kellee M.; O'Donnell, Holly K.; Oron, Tal; Patil, Shivajirao P.; Pop-Busui, Rodica; Rewers, Marian J.; Rich, Stephen S.; Schatz, Desmond A.; Schulman-Rosenbaum, Rifka; Simmons, Kimber M.; Sims, Emily K.; Skyler, Jay S.; Smith, Laura B.; Speake, Cate; Steck, Andrea K.; Thomas, Nicholas P. B.; Tonyushkina, Ksenia N.; Veijola, Riitta; Wentworth, John M.; Wherrett, Diane K.; Wood, Jamie R.; Ziegler, Anette-Gabriele; DiMeglio, Linda A.; Pediatrics, School of Medicine
Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review
(Springer Nature, 2023-10-05) Felton, Jamie L.; Griffin, Kurt J.; Oram, Richard A.; Speake, Cate; Long, S. Alice; Onengut-Gumuscu, Suna; Rich, Stephen S.; Monaco, Gabriela S. F.; Evans-Molina, Carmella; DiMeglio, Linda A.; Ismail, Heba M.; Steck, Andrea K.; Dabelea, Dana; Johnson, Randi K.; Urazbayeva, Marzhan; Gitelman, Stephen; Wentworth, John M.; Redondo, Maria J.; Sims, Emily K.; Pediatrics, School of Medicine
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.
Dysglycemia and Index60 as Prediagnostic End Points for Type 1 Diabetes Prevention Trials
(American Diabetes Association, 2017-11) Nathan, Brandon M.; Boulware, David; Geyer, Susan; Atkinson, Mark A.; Colman, Peter; Goland, Robin; Russell, William; Wentworth, John M.; Wilson, Darrell M.; Evans-Molina, Carmella; Wherrett, Diane; Skyler, Jay S.; Moran, Antoinette; Sosenko, Jay M.; Type 1 Diabetes TrialNet and Diabetes Prevention Trial–Type 1 Study Groups; Medicine, School of Medicine
OBJECTIVE: We assessed dysglycemia and a T1D Diagnostic Index60 (Index60) ≥1.00 (on the basis of fasting C-peptide, 60-min glucose, and 60-min C-peptide levels) as prediagnostic end points for type 1 diabetes among Type 1 Diabetes TrialNet Pathway to Prevention Study participants. RESEARCH DESIGN AND METHODS: Two cohorts were analyzed: 1) baseline normoglycemic oral glucose tolerance tests (OGTTs) with an incident dysglycemic OGTT and 2) baseline Index60 <1.00 OGTTs with an incident Index60 ≥1.00 OGTT. Incident dysglycemic OGTTs were divided into those with (DYS/IND+) and without (DYS/IND-) concomitant Index60 ≥1.00. Incident Index60 ≥1.00 OGTTs were divided into those with (IND/DYS+) and without (IND/DYS-) concomitant dysglycemia. RESULTS: The cumulative incidence for type 1 diabetes was greater after IND/DYS- than after DYS/IND- (P < 0.01). Within the normoglycemic cohort, the cumulative incidence of type 1 diabetes was higher after DYS/IND+ than after DYS/IND- (P < 0.001), whereas within the Index60 <1.00 cohort, the cumulative incidence after IND/DYS+ and after IND/DYS- did not differ significantly. Among nonprogressors, type 1 diabetes risk at the last OGTT was greater for IND/DYS- than for DYS/IND- (P < 0.001). Hazard ratios (HRs) of DYS/IND- with age and 30- to 0-min C-peptide were positive (P < 0.001 for both), whereas HRs of type 1 diabetes with these variables were inverse (P < 0.001 for both). In contrast, HRs of IND/DYS- and type 1 diabetes with age and 30- to 0-min C-peptide were consistent (all inverse [P < 0.01 for all]). CONCLUSIONS: The findings suggest that incident dysglycemia without Index60 ≥1.00 is a suboptimal prediagnostic end point for type 1 diabetes. Measures that include both glucose and C-peptide levels, such as Index60 ≥1.00, appear better suited as prediagnostic end points.
HOMA2-B enhances assessment of type 1 diabetes risk among TrialNet Pathway to Prevention participants
(Springer, 2022) Felton, Jamie L.; Cuthbertson, David; Warnock, Megan; Lohano, Kuldeep; Meah, Farah; Wentworth, John M.; Sosenko, Jay; Evans-Molina, Carmella; Type 1 Diabetes TrialNet Study Group; Pediatrics, School of Medicine
Aims/hypothesis: Methods to identify individuals at highest risk for type 1 diabetes are essential for the successful implementation of disease-modifying interventions. Simple metabolic measures are needed to help stratify autoantibody-positive (Aab+) individuals who are at risk of developing type 1 diabetes. HOMA2-B is a validated mathematical tool commonly used to estimate beta cell function in type 2 diabetes using fasting glucose and insulin. The utility of HOMA2-B in association with type 1 diabetes progression has not been tested. Methods: Baseline HOMA2-B values from single-Aab+ (n = 2652; mean age, 21.1 ± 14.0 years) and multiple-Aab+ (n = 3794; mean age, 14.5 ± 11.2 years) individuals enrolled in the TrialNet Pathway to Prevention study were compared. Cox proportional hazard models were used to determine associations between HOMA2-B tertiles and time to progression to type 1 diabetes, with adjustments for age, sex, HLA status and BMI z score. Receiver operating characteristic (ROC) analysis was used to test the association of HOMA2-B with type 1 diabetes development in 1, 2, 5 and 10 years. Results: At study entry, HOMA2-B values were higher in single- compared with multiple-Aab+ Pathway to Prevention participants (91.1 ± 44.5 vs 83.9 ± 38.9; p < 0.001). Single- and multiple-Aab+ individuals in the lowest HOMA2-B tertile had a higher risk and faster rate of progression to type 1 diabetes. For progression to type 1 diabetes within 1 year, area under the ROC curve (AUC-ROC) was 0.685, 0.666 and 0.680 for all Aab+, single-Aab+ and multiple-Aab+ individuals, respectively. When correlation between HOMA2-B and type 1 diabetes risk was assessed in combination with additional factors known to influence type 1 diabetes progression (insulin sensitivity, age and HLA status), AUC-ROC was highest for the single-Aab+ group's risk of progression at 2 years (AUC-ROC 0.723 [95% CI 0.652, 0.794]). Conclusions/interpretation: These data suggest that HOMA2-B may have utility as a single-time-point measurement to stratify risk of type 1 diabetes development in Aab+ individuals.
Imatinib therapy for patients with recent-onset type 1 diabetes: a multicentre, randomised, double-blind, placebo-controlled, phase 2 trial
(Elsevier, 2021) Gitelman, Stephen E.; Bundy, Brian N.; Ferrannini, Ele; Lim, Noha; Blanchfield, J. Lori; DiMeglio, Linda A.; Felner, Eric I.; Gaglia, Jason L.; Gottlieb, Peter A.; Long, S. Alice; Mari, Andrea; Mirmira, Raghavendra G.; Raskin, Philip; Sanda, Srinath; Tsalikian, Eva; Wentworth, John M.; Willi, Steven M.; Krischer, Jeffrey P.; Bluestone, Jeffrey A.; Gleevec Trial Study Group; Pediatrics, School of Medicine
Background: Type 1 diabetes results from autoimmune-mediated destruction of β cells. The tyrosine kinase inhibitor imatinib might affect relevant immunological and metabolic pathways, and preclinical studies show that it reverses and prevents diabetes. Our aim was to evaluate the safety and efficacy of imatinib in preserving β-cell function in patients with recent-onset type 1 diabetes. Methods: We did a multicentre, randomised, double-blind, placebo-controlled, phase 2 trial. Patients with recent-onset type 1 diabetes (<100 days from diagnosis), aged 18-45 years, positive for at least one type of diabetes-associated autoantibody, and with a peak stimulated C-peptide of greater than 0·2 nmol L-1 on a mixed meal tolerance test (MMTT) were enrolled from nine medical centres in the USA (n=8) and Australia (n=1). Participants were randomly assigned (2:1) to receive either 400 mg imatinib mesylate (4 × 100 mg film-coated tablets per day) or matching placebo for 26 weeks via a computer-generated blocked randomisation scheme stratified by centre. Treatment assignments were masked for all participants and study personnel except pharmacists at each clinical site. The primary endpoint was the difference in the area under the curve (AUC) mean for C-peptide response in the first 2 h of an MMTT at 12 months in the imatinib group versus the placebo group, with use of an ANCOVA model adjusting for sex, baseline age, and baseline C-peptide, with further observation up to 24 months. The primary analysis was by intention to treat (ITT). Safety was assessed in all randomly assigned participants. This study is registered with ClinicalTrials.gov, NCT01781975 (completed). Findings: Patients were screened and enrolled between Feb 12, 2014, and May 19, 2016. 45 patients were assigned to receive imatinib and 22 to receive placebo. After withdrawals, 43 participants in the imatinib group and 21 in the placebo group were included in the primary ITT analysis at 12 months. The study met its primary endpoint: the adjusted mean difference in 2-h C-peptide AUC at 12 months for imatinib versus placebo treatment was 0·095 (90% CI -0·003 to 0·191; p=0·048, one-tailed test). This effect was not sustained out to 24 months. During the 24-month follow-up, 32 (71%) of 45 participants who received imatinib had a grade 2 severity or worse adverse event, compared with 13 (59%) of 22 participants who received placebo. The most common adverse events (grade 2 severity or worse) that differed between the groups were gastrointestinal issues (six [13%] participants in the imatinib group, primarily nausea, and none in the placebo group) and additional laboratory investigations (ten [22%] participants in the imatinib group and two [9%] in the placebo group). Per the trial protocol, 17 (38%) participants in the imatinib group required a temporary modification in drug dosing and six (13%) permanently discontinued imatinib due to adverse events; five (23%) participants in the placebo group had temporary modifications in dosing and none had a permanent discontinuation due to adverse events. Interpretation: A 26-week course of imatinib preserved β-cell function at 12 months in adults with recent-onset type 1 diabetes. Imatinib might offer a novel means to alter the course of type 1 diabetes. Future considerations are defining ideal dose and duration of therapy, safety and efficacy in children, combination use with a complimentary drug, and ability of imatinib to delay or prevent progression to diabetes in an at-risk population; however, careful monitoring for possible toxicities is required.
Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review
(Springer Nature, 2024-04-06) Felton, Jamie L.; Redondo, Maria J.; Oram, Richard A.; Speake, Cate; Long, S. Alice; Onengut-Gumuscu, Suna; Rich, Stephen S.; Monaco, Gabriela S. F.; Harris-Kawano, Arianna; Perez, Dianna; Saeed, Zeb; Hoag, Benjamin; Jain, Rashmi; Evans-Molina, Carmella; DiMeglio, Linda A.; Ismail, Heba M.; Dabelea, Dana; Johnson, Randi K.; Urazbayeva, Marzhan; Wentworth, John M.; Griffin, Kurt J.; Sims, Emily K.; ADA/EASD PMDI; Pediatrics, School of Medicine
Background: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. Methods: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. Results: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. Conclusions: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.
The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening
(Springer Verlag, 2020-03) Jacobsen, Laura M.; Bocchino, Laura; Evans-Molina, Carmella; DiMeglio, Linda; Goland, Robin; Wilson, Darrell M.; Atkinson, Mark A.; Aye, Tandy; Russell, William E.; Wentworth, John M.; Boulware, David; Geyer, Susan; Sosenko, Jay M.; Medicine, School of Medicine
Aims/hypothesis: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. Methods: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. Results: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. Conclusions/interpretation: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress.

Browsing by Author "Wentworth, John M."

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