Baseline Assessment of Circulating MicroRNAs Near Diagnosis of Type 1 Diabetes Predicts Future Stimulated Insulin Secretion |
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Authors: | Isaac Snowhite Ricardo Pastori Jay Sosenko Shari Messinger Cayetano Alberto Pugliese |
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Affiliation: | 1.Diabetes Research Institute, Leonard M. Miller School of Medicine, University of Miami, Miami, FL;2.Division of Endocrinology and Metabolism, Department of Medicine, Leonard M. Miller School of Medicine, University of Miami, Miami, FL;3.Department of Public Health Sciences, Leonard M. Miller School of Medicine, University of Miami, Miami, FL;4.Department of Microbiology and Immunology, Leonard M. Miller School of Medicine, University of Miami, Miami, FL |
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Abstract: | Type 1 diabetes is an autoimmune disease resulting in severely impaired insulin secretion. We investigated whether circulating microRNAs (miRNAs) are associated with residual insulin secretion at diagnosis and predict the severity of its future decline. We studied 53 newly diagnosed subjects enrolled in placebo groups of TrialNet clinical trials. We measured serum levels of 2,083 miRNAs, using RNA sequencing technology, in fasting samples from the baseline visit (<100 days from diagnosis), during which residual insulin secretion was measured with a mixed meal tolerance test (MMTT). Area under the curve (AUC) C-peptide and peak C-peptide were stratified by quartiles of expression of 31 miRNAs. After adjustment for baseline C-peptide, age, BMI, and sex, baseline levels of miR-3187-3p, miR-4302, and the miRNA combination of miR-3187-3p/miR-103a-3p predicted differences in MMTT C-peptide AUC/peak levels at the 12-month visit; the combination miR-3187-3p/miR-4723-5p predicted proportions of subjects above/below the 200 pmol/L clinical trial eligibility threshold at the 12-month visit. Thus, miRNA assessment at baseline identifies associations with C-peptide and stratifies subjects for future severity of C-peptide loss after 1 year. We suggest that miRNAs may be useful in predicting future C-peptide decline for improved subject stratification in clinical trials. |
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