Fig. 1: Study design and identification of a signature of 50 PREDICT T1D miRNAs through a discovery and data-driven approach using published datasets. | Nature Medicine

Fig. 1: Study design and identification of a signature of 50 PREDICT T1D miRNAs through a discovery and data-driven approach using published datasets.

From: A microRNA-based dynamic risk score for type 1 diabetes

Fig. 1

a, Schematic flow chart of the four elements of this study (shown using block arrows at the top), details of the discovery cohorts, DRS generation and validation datasets, and their application in T1D therapy datasets. GAI-aided eDRS4C methods are detailed in the text. b, Significant miRNAs identified through our wet lab discovery analyses across n = 254 human samples (including plasma from n = 5 controls and n = 5 participants with newly diagnosed T1D) are shown at the top. Additionally, miRNAs from the literature that were reported to be significant but not reaching significance in our wet lab discovery analyses were also included in this PREDICT T1D miRNA panel. Details of miRNA spike-in controls, internal and positive controls, and negative controls are also provided. The Sankey plot shows the miRNA categories based on our discovery analyses (top) and all published reports (Supplementary Table 1) wherein these miRNAs have been associated with HLA, autoantibody, early diagnosis or T1D versus control (indicated by the filled blue circles), emphasizing the reason for these miRNAs to be included in the panel.

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