Browsing by Author "Ismail, Heba M."

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    4033 Evaluating the Effect of Prebiotics on the Gut Microbiome Profile and Beta-cell Function in Newly-Diagnosed Type 1 Diabetes
    (Cambridge University Press, 2020-07-29) Ismail, Heba M.; Evans-Molina, Carmella; DiMeglio, Linda; Pediatrics, School of Medicine
    OBJECTIVES/GOALS: Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing β-cells. Emerging data suggest that differences in intestinal microbiota might be critically involved both in autoimmunity and in glucose homeostasis. The prebiotic high amylose maize starch (HAMS) alters the gut microbiome profile and metabolites positively by increasing production of beneficial short chain fatty acids (SCFAs) that have significant anti-inflammatory effects. HAMS also improves glycemia, insulin sensitivity and secretion in healthy non-diabetic adults. Further, an acetylated and butyrylated form of HAMS (HAMS-AB) that increases beneficial SCFA production, namely acetate and butyrate, has been safe and effective in disease prevention in mouse T1D models. The objective of the proposed study is to assess the effect of administering a prebiotic, such as HAMS-AB, on the gut microbiome profile, SCFA production, glycemia and β-cell function in humans with T1D. METHODS/STUDY POPULATION: We hypothesize that administration of HAMS-AB will (i) improve the gut microbiome profile in humans with T1D, (ii) increase SCFA production, and (iii) improve β-cell health, β-cell function and overall glycemia. We propose a pilot randomized controlled cross-over trial of HAMS-AB in 12 youth with newly-diagnosed T1D. We will use state-of-the-art markers to profile the gut microbiome (using 16S rRNA sequencing), measure stool SCFA levels (using gas chromatography), asses β-cell stress/death (by measuring proinsulin to C-peptide ratios) and glycemia (assessed by continuous glucose monitoring and HbA1c measurements). RESULTS/ANTICIPATED RESULTS: We expect that the use of HAMS-AB in newly diagnosed youth with type 1 diabetes will alter the gut microbiome profile (thus increasing the number of fermenters and SCFA levels), β-cell function and glycemia in humans with T1D. DISCUSSION/SIGNIFICANCE OF IMPACT: Given the unknown long-term effects of immune-modulatory therapy on those at risk for or those diagnosed with T1D, the use of a prebiotic such as HAMS-AB offers a simple, safe, yet inexpensive and tolerated dietary alternative approach to mitigating disease.
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    Associations of HbA1c with the Timing of C‐peptide Responses during the Oral Glucose Tolerance Test at the Diagnosis of Type 1 Diabetes
    (Wiley, 2019) Ismail, Heba M.; Evans-Molina, Carmella; DiMeglio, Linda A.; Becker, Dorothy J.; Libman, Ingrid; Sims, Emily K.; Boulware, David; Herold, Kevan C.; Rafkin, Lisa; Skyler, Jay; Cleves, Mario A.; Palmer, Jerry; Sosenko, Jay; Pediatrics, School of Medicine
    Background In new onset type 1 diabetes (T1D), overall C‐peptide measures such as area under the curve (AUC) C‐peptide and peak C‐peptide are useful for estimating the extent of β‐cell dysfunction, and for assessing responses to intervention therapy. However, measures of the timing of C‐peptide responsiveness could have additional value. Objectives We assessed the contribution of the timing of C‐peptide responsiveness during oral glucose tolerance tests (OGTTs) to HbA1c variation at T1D diagnosis. Methods We analyzed data from 85 individuals <18 years with OGTTs and HbA1c measurements at diagnosis. Overall [AUC and peak C‐peptide] and timing measures [30‐0 minute C‐peptide (early); 60 to 120 minute C‐peptide sum‐30 minutes (late); 120/30 C‐peptide; time to peak C‐peptide] were utilized. Results At diagnosis, the mean (±SD) age was 11.2±3.3 years, BMI‐z was 0.4±1.1, 51.0% were male and the HbA1c was 43.54±8.46 mmol/mol (6.1±0.8%). HbA1c correlated inversely with the AUC C‐peptide (p<0.001), peak C‐peptide (p<0.001), early and late C‐peptide responses (p<0.001 each), and 120/30 C‐peptide (p<0.001). Those with a peak C‐peptide occurring at ≤60 minutes had higher HbA1c values than those with peaks later (p=0.003). HbA1c variance was better explained with timing measures added to regression models (R2=11.6% with AUC C‐peptide alone; R2=20.0% with 120/30 C‐peptide added; R2=13.7% with peak C‐peptide alone, R2=20.4% with timing of the peak added). Similar associations were seen between the 2‐hr glucose and the C‐peptide measures. Conclusions These findings show that the addition of timing measures of C‐peptide responsiveness better explains HbA1c variation at diagnosis than standard measures alone.
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    Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals
    (Oxford University Press, 2024) Sims, Emily K.; Cuthbertson, David; Jacobsen, Laura; Ismail, Heba M.; Nathan, Brandon M.; Herold, Kevan C.; Redondo, Maria J.; Sosenko, Jay; Pediatrics, School of Medicine
    Context: Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. Objective: Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. Methods: Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. Results: Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide-based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. Conclusion: The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials.
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    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.
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    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
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    COVID-19 Pandemic Effects on Caregivers of Youth With Type 1 Diabetes: Stress and Self-Efficacy
    (American Diabetes Association, 2022-03-11) Ismail, Heba M.; Hand, Breanne L.; DiMeglio, Linda A.; Oyetoro, Rebecca; Soni, Priya Y.; Adams, Janey; Westen, Sarah; Driscoll, Kimberly A.; Albanese-O’Neill, Anastasia; Pediatrics, School of Medicine
    Background Little is known about the coronavirus disease 2019 (COVID-19) pandemic’s psychological effects on caregivers of children with type 1 diabetes. Objective This study aimed to investigate the experience of caregivers of youth with type 1 diabetes during the COVID-19 pandemic. Methods A 49-item questionnaire using a 5-point Likert scale and open-response questions was distributed via e-mail and type 1 diabetes–related social media platforms from 4 May to 22 June 2020. Quantitative data were analyzed using SPSS v.25 statistical software. Descriptive statistics were used. Relationships were compared using Pearson correlation. Qualitative data were coded and categorized. Results A total of 272 caregivers participated (mean ± SD respondent age 42.1 ± 7.8 years; 94.5% females; 81.3% with college degree or higher; 52.6% with annual income >$99,000; 80.1% with private insurance). The mean ± SD age of caregivers’ children with type 1 diabetes was 11.0 ± 4.1 years, and their mean ± SD diabetes duration was 4.2 ± 3.5 years. Participants reported being diagnosed with or knowing someone with COVID-19 (24.6%), increased stress (71.9%), job loss (10.3%), and financial difficulty (26.8%) as a result of the pandemic. General self-efficacy scores were high (mean ± SD 16.2 ± 2.6, range 8–20) and significantly correlated with COVID-19–related self-efficacy (mean ± SD 12.6 ± 2.1; R = 0.394, P <0.001) and type 1 diabetes self-efficacy during COVID-19 (mean ± SD 17.1 ± 2.5; R = 0.421, P <0.001). Conclusion Despite reporting high overall self-efficacy, caregivers of children with type 1 diabetes reported greater overall stress and challenges during the pandemic. Health care providers should be prepared to provide families with specific social and mental health support.
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    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.
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    Does the Gut Microbiome Play a Role in Obesity in Type 1 Diabetes? Unanswered Questions and Review of the Literature
    (Frontiers Media, 2022-07-08) Ismail, Heba M.; Evans-Molina, Carmella; Pediatrics, School of Medicine
    Evidence suggests that type 1 diabetes (T1D) risk and progression are associated with gut bacterial imbalances. Children with either T1D or islet antibody positivity exhibit gut dysbiosis (microbial imbalance) characterized by lower gram-positive to gram-negative gut bacterial ratios compared to healthy individuals, leading to a pro-inflammatory milieu. In addition, specific gut microbiome changes, including increased virulence factors, elevated phage, prophage, and motility genes, and higher amplitude stress responses, have been identified in individuals who have or are progressing towards T1D. Additionally, gut microbiome differences are associated with and thought to contribute to obesity, a comorbidity that is increasingly prevalent among persons with T1D. Obesity in T1D is problematic because individuals with obesity progress faster to T1D, have reduced insulin sensitivity compared to their lean counterparts, and have higher risk of complications. Animal and human studies suggest higher relative abundance of bacterial taxa associated with changes in bile acid and short chain fatty acid biosynthesis in obesity. However, it is unknown to what extent the gut microbiome plays a role in obesity in T1D and these worse outcomes. In this review, we aim to evaluate potential gut microbiome changes and associations in individuals with T1D who are obese, highlighting the specific gut microbiome changes associated with obesity and with T1D development. We will identify commonalities and differences in microbiome changes and examine potential microbiota-host interactions and the metabolic pathways involved. Finally, we will explore interventions that may be of benefit to this population, in order to modify disease and improve outcomes.
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    Early and late C-peptide responses during oral glucose tolerance testing are oppositely predictive of type 1 diabetes in autoantibody-positive individuals
    (Wiley, 2020-01-31) Ismail, Heba M.; Becker, Dorothy J.; Libman, Ingrid; Herold, Kevan C.; Redondo, Maria J.; Atkinson, Mark A.; Cleves, Mario A.; Palmer, Jerry; Sosenko, Jay; Pediatrics, School of Medicine
    We examined whether the timing of the C-peptide response during an oral glucose tolerance test (OGTT) in relatives of patients with type 1 diabetes (T1D) is predictive of disease onset. We examined baseline 2-h OGTTs from 670 relatives participating in the Diabetes Prevention Trial-Type 1 (age: 13.8 ± 9.6 years; body mass index z score: 0.3 ± 1.1; 56% male) using univariate regression models. T1D risk increased with lower early C-peptide responses (30–0 min) (χ2 = 28.8, P < 0.001), and higher late C-peptide responses (120–60 min) (χ2 = 23.3, P < 0.001). When both responses were included in a proportional hazards model, they remained independently and oppositely associated with T1D, with a stronger overall association for the combined model than either response alone (χ2 = 41.1; P < 0.001). Using receiver operating characteristic curve analysis, the combined early and late C-peptide response was more accurately predictive of T1D than area under the curve C-peptide (P = 0.005). Our findings demonstrate that lower early and higher late C-peptide responses serve as indicators of increased T1D risk.
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    Emotional distress, stress, anxiety, and the impact of the COVID-19 pandemic on early- to mid-career women in healthcare sciences research
    (Cambridge University Press, 2022-06-13) Bittar, Noor; Cohee, Andrea; Bhamidipalli, Surya Sruthi; Savoy, April; Ismail, Heba M.; Pediatrics, School of Medicine
    Objectives: The main objective of this study was to report stress and anxiety levels during the COVID-19 pandemic on early- to mid-career women researchers in healthcare sciences research and determine the associated factors. Methods: A 50-item self-administered internet questionnaire was developed using a mix of Likert-type scales and open-ended response questions. The survey was distributed June 10-August 3, 2020. Anxiety and stress as well as personal/family demands were assessed through validated measures (Patient Reported Outcomes Measurement Information System [PROMIS]-Anxiety Short Form and Perceived Stress Scale [PSS]) and open-ended responses. Results: One hundred and fifty-one early-career women in healthcare sciences research completed the survey; mean respondent age was 37.3 ± 5.2 years; and all had a college degree or higher, 50.3% holding a PhD and 35.8% MD. Race and ethnicity were reported in 128; the majority were White (74.0%). One-third (31.2%) reported being "very much" concerned about reaching their research productivity goals and 30.1% were "very much" concerned about academic promotion and tenure. Fifty percent reported a "moderate" PROMIS anxiety score and 72.1% reported a "moderate" PSS score. For the open-ended responses, 65.6% reported a worry about their professional goals because of the COVID-19 pandemic. Major concerns revolved around finances, childcare, and job security. Conclusions: Throughout the pandemic, early- and mid-career women in healthcare sciences research have reported moderate to high overall stress, anxiety, and worries. These concerns appear related to household settings, additional responsibilities, financial concerns, and reduced research productivity. Institutions and funding agencies should take these concerns into consideration and offer support.