Evaluating the effect of prebiotics on the gut microbiome profile and β cell function in youth with newly diagnosed type 1 diabetes: protocol of a pilot randomized controlled trial

INTRODUCTION

Data show that disturbances in the gut microbiota play a role in glucose homeostasis, type 1 diabetes (T1D) risk and progression. The prebiotic high amylose maize starch (HAMS) alters the gut microbiome profile and metabolites favorably with an increase in bacteria producing short chain fatty acids (SCFAs) that have significant anti-inflammatory effects. HAMS also improves glycemia, insulin sensitivity, and secretion in healthy non-diabetic adults. Additionally, a recent study testing an acetylated and butyrylated form of HAMS (HAMS-AB) that further increases SCFA production prevented T1D in a rodent model without adverse safety effects. The overall objective of this human study will be to assess how daily HAMS-AB consumption impacts the gut microbiome profile, SCFA production, β cell heath, function, and glycemia as well as immune responses in newly diagnosed T1D youth.

METHODS AND ANALYSIS

We hypothesize that HAMS-AB intake will improve the gut microbiome profile, increase SCFA production, improve β cell health, function and glycemia as well as modulate the immune system. We describe here a pilot, randomized crossover trial of HAMS-AB in 12 newly diagnosed T1D youth, ages 11-17 years old, with residual β cell function. In Aim 1, we will determine the effect of HAMS-AB on the gut microbiome profile and SCFA production; in Aim 2, we will determine the effect of HAMS-AB on β cell health, function and glycemia; and in Aim 3, we will determine the peripheral blood effect of HAMS-AB on frequency, phenotype and function of specific T cell markers. Results will be used to determine the effect-size estimate of using HAMS-AB. We anticipate beneficial effects from a simple, inexpensive, and safe dietary approach.

ETHICS AND DISSEMINATION

The Institutional Review Board at Indiana University approved the study protocol. The findings of this trial will be submitted to a peer-reviewed pediatric journal. Abstracts will be submitted to relevant national and international conferences.

TRIAL REGISTRATION

NCT04114357; Pre-results.

The Rare and Atypical Diabetes Network (RADIANT) Study: Design and Early Results

OBJECTIVE

The Rare and Atypical Diabetes Network (RADIANT) will perform a study of individuals and, if deemed informative, a study of their family members with uncharacterized forms of diabetes.

RESEARCH DESIGN AND METHODS

The protocol includes genomic (whole-genome [WGS], RNA, and mitochondrial sequencing), phenotypic (vital signs, biometric measurements, questionnaires, and photography), metabolomics, and metabolic assessments.

RESULTS

Among 122 with WGS results of 878 enrolled individuals, a likely pathogenic variant in a known diabetes monogenic gene was found in 3 (2.5%), and six new monogenic variants have been identified in the SMAD5, PTPMT1, INS, NFKB1, IGF1R, and PAX6 genes. Frequent phenotypic clusters are lean type 2 diabetes, autoantibody-negative and insulin-deficient diabetes, lipodystrophic diabetes, and new forms of possible monogenic or oligogenic diabetes.

CONCLUSIONS

The analyses will lead to improved means of atypical diabetes identification. Genetic sequencing can identify new variants, and metabolomics and transcriptomics analysis can identify novel mechanisms and biomarkers for atypical disease.

Who Is Enrolling? The Path to Monitoring in Type 1 Diabetes TrialNet's Pathway to Prevention

OBJECTIVE

To better understand potential facilitators of individual engagement in type 1 diabetes natural history and prevention studies through analysis of enrollment data in the TrialNet Pathway to Prevention (PTP) study.

RESEARCH DESIGN AND METHODS

We used multivariable logistic regression models to examine continued engagement of eligible participants at two time points: 1) the return visit after screening to confirm an initial autoantibody-positive (Ab⁺) test result and 2) the initial oral glucose tolerance test (OGTT) for enrollment into the monitoring protocol.

RESULTS

Of 5,387 subjects who screened positive for a single autoantibody (Ab), 4,204 (78%) returned for confirmatory Ab testing. Younger age was associated with increased odds of returning for Ab confirmation (age <12 years vs. >18 years: odds ratio [OR] 2.12, P < 0.0001). Racial and ethnic minorities were less likely to return for confirmation, particularly nonwhite non-Hispanic (OR 0.50, P < 0.0001) and Hispanic (OR 0.69, P = 0.0001) relative to non-Hispanic white subjects. Of 8,234 subjects, 5,442 (66%) were identified as eligible to be enrolled in PTP OGTT monitoring. Here, younger age and identification as multiple Ab⁺ were associated with increased odds of returning for OGTT monitoring (age <12 years vs. >18 years: OR 1.43, P < 0.0001; multiple Ab⁺: OR 1.36, P < 0.0001). Parents were less likely to enroll into monitoring than other relatives (OR 0.78, P = 0.004). Site-specific factors, including site volume and U.S. site versus international site, were also associated with differences in rates of return for Ab⁺ confirmation and enrollment into monitoring.

CONCLUSIONS

These data confirm clear differences between successfully enrolled populations and those lost to follow-up, which can serve to identify strategies to increase ongoing participation.

Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

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 progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.