Diabetes
Conditions
Keywords
Type 1 diabetes, islet autoantibodies
Brief summary
This study is a test to find out if genetic information can be used to help healthcare providers identify diseases. Specifically, the investigators want to find out how genetic information can help healthcare providers identify people who may benefit from early screening for type 1 diabetes, even before people feel sick. This study aims to guide future research to improve screening, prevent disease, slow progression, and expand treatment options for type 1 diabetes.
Detailed description
In this proof-of-concept study, the investigators will show that genetic enrichment offers an efficient way to identify individuals who may be in the presymptomatic window of Type 1 diabetes (T1D) when stage-specific intervention is available. Additionally, understanding which clinical features are associated with autoimmunity within this genetically enriched group can help refine recruitment strategies for future studies and guide eventual implementation in practice. The study aims to enroll approximately 150 participants. Individuals aged 18-79 years will initially be selected from the top 2.5% of the T1D polygenic score (PS) distribution. The PS threshold and number of participants undergoing antibody testing may subsequently be adjusted based on recruitment, islet autoantibody yield, and available funding. Electronic Health Record (EHR) data will be extracted to assess eligibility and characterize the cohort, including age, sex, genetic ancestry, autoimmune disease, diabetes diagnosis, body mass index (BMI), family history, and relevant laboratory values (e.g., HbA1c, glucose, C-peptide, and islet autoantibodies). Individuals with current or prior treatment with immune checkpoint inhibitors (e.g., PD-1, PD-L1, or CTLA-4 inhibitors), as well as individuals with diabetes secondary to pancreatic disease, including pancreatic cancer, pancreatitis, pancreatic surgery/pancreatectomy, cystic fibrosis, or hemochromatosis, will be excluded. Availability of archived plasma samples within the MGB Biobank will also be determined. Participants with archived plasma or serum samples will be prioritized for islet autoantibody screening. Participants without archived plasma or serum samples suitable for analysis will be invited for an in-person visit to collect blood samples for biomarker testing and repeat biospecimen collection. Participants with one or more positive islet autoantibodies identified through study testing or extracted from the EHR, who do not have a prior diagnosis of diabetes and meet oral glucose tolerance test (OGTT) eligibility criteria, will be invited to undergo an OGTT at the Diabetes Research Center (anticipated up to 25 participants). Repeat islet autoantibody testing and additional research blood collection may also be performed at the study visit following informed consent. Clinical, biochemical, and immunologic data collected during the study will be used to characterize participants with presymptomatic autoimmune diabetes and evaluate associations between autoantibody positivity and established clinical risk factors. Participants may choose to allow investigators to notify their primary care provider of their results, as the research findings do not establish a clinical diagnosis and may require confirmation in a CLIA-certified clinical laboratory before clinical decision-making.
Interventions
None listed
Sponsors
Study design
Eligibility
Inclusion criteria
* Adults aged 18-79 years who had participated in the Mass General Brigham (MGB) Biobank and agreed to be recontacted for future study
Exclusion criteria
* Individuals with current or prior treatment with immune checkpoint inhibitors (e.g., PD-1, PD-L1, or CTLA-4 inhibitors), as well as individuals with diabetes secondary to pancreatic disease, including pancreatic cancer, pancreatitis, pancreatic surgery/pancreatectomy, cystic fibrosis, or hemochromatosis
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Comparisons between high genetic risk vs. the rest of the cohort | 12 months | The distribution of clinical features between the top 2.5% of the T1D polygenic score and the remainder of the MGB Biobank will be compared, and within the high genetic-risk stratum, between autoantibody-positive and autoantibody-negative participants. Analyses will summarize standardized differences and use logistic regression for autoantibody positivity (primary outcome), adjusted for age, sex, and ancestry PCs. To prioritize features for future recall-by-genotype enrichment, the investigators will quantify incremental discrimination (ΔAUC), partial R², and likelihood-ratio tests. Missing covariates will be mitigated via brief surveys and multiple imputation. |
Contacts
Massachusetts General Hospital