Novel micro-RNA and Microbiome Signature Profiles as Biomarkers for Predicting the Risk of Autoimmune Type 1 Diabetes Development
1Dept of Surgery, University of Virginia Health System, Charlottesville, VA, 2Dept of Biology, University of Virginia Health System, Charlottesville, VA
Meeting: 2020 American Transplant Congress
Abstract number: A-327
Keywords: Autoimmunity, Immunoglobulins (Ig), Mice, NOD, Prediction models
Session Information
Session Name: Poster Session A: Biomarker Discovery and Immune Modulation
Session Type: Poster Session
Date: Saturday, May 30, 2020
Session Time: 3:15pm-4:00pm
Presentation Time: 3:30pm-4:00pm
Location: Virtual
*Purpose: To identify reliable microRNA (miRNA) and microbiome biomarkers for predicting risk of autoimmune beta-cell destruction in type 1 diabetes (T1D) and to investigate alterations in miRNA expression and cecal microbial composition during the development of T1D with or without IgM therapy. *Background: The most commonly used biomarkers for predicting T1D development are serum autoantibodies against β-cell antigens, which are not very reliable. Identifying miRNA and microbiome signatures that accurately predict T1D risk has potential for guiding and implementing immuno-intervention therapies. IgM therapy prevents T1D, and miRNA and/or microbiome profile analysis may help monitor treatment efficacy.
*Methods: Female non-obese diabetic (NOD) mice treated with IgM or saline (n=20/grp) were divided into 5wks−old non-diabetic; 9-12wks−old prehyperglycemic stage-1; ≥13wks−old prehyperglycemic stage-2; and diabetic groups. a) Total RNA from pancreas and peripheral blood mononuclear cells (PBMCs) was used for GeneChip miRNA v3.0 array hybridization. Expression intensities were normalized using RMA algorithm. Pairwise t-test comparisons were fit (Significance: False-Discovery-Rate<10% and Fold-change>1.5). b)16S rRNA libraries were prepared from bacterial DNA and deep-sequenced.
*Results: Dysregulated pancreatic miRNA signatures (miR-130b, -17, -1224, -29a, -378) were identified in prehyperglycemic animals as predictive biomarkers for T1D. MiR-29a, -130b, -21 were dysregulated in pancreas and PBMCs of diabetic mice. Interestingly, IgM therapy reversed expression of dysregulated miRNAs, and two IgM-treatment−specific miRNAs induced immune-suppressor cells. Relevant miRNAs were validated by RT-PCR. Significant dysbiosis was observed in the cecal microbiome with the progression of T1D development, characterized by an increase in the bacteroidetes:firmicutes ratio. In contrast, IgM conserved normal bacteroidetes:firmicutes ratio and this effect was long-lasting. Furthermore, oral gavage using cecal content from IgM-treated mice significantly diminished the incidence of diabetes in NOD mice compared to cecal content from saline-injected mice. IgM maintained normal levels of S24-7 and Lachnospiraceae, increased Lacobacillus and Turicibacter, and decreased Clostridiales.
*Conclusions: The paradigm for identification of high-risk individuals using miRNA and microbiome profiles should be applicable to a variety of disease states requiring pharmacologic and/or surgical interventions.
To cite this abstract in AMA style:
Chhabra P, Ricardo G, Spano A, Mas V, Timko M, Brayman K. Novel micro-RNA and Microbiome Signature Profiles as Biomarkers for Predicting the Risk of Autoimmune Type 1 Diabetes Development [abstract]. Am J Transplant. 2020; 20 (suppl 3). https://atcmeetingabstracts.com/abstract/novel-micro-rna-and-microbiome-signature-profiles-as-biomarkers-for-predicting-the-risk-of-autoimmune-type-1-diabetes-development/. Accessed December 10, 2024.« Back to 2020 American Transplant Congress