A Development and Analysis Pipeline for MicroRNA Biomarker Signatures in Molecular Diagnostics Based on Circulating EVs

A Development and Analysis Pipeline for MicroRNA Biomarker Signatures in Molecular Diagnostics Based on Circulating EVs

Abstract
Extracellular vesicles (EVs) circulate in body liquids and are involved in the intercellular communication. They have significant regulative functions in almost any physiological or pathological process. Especially exosome-like small EVs have gained huge scientific and clinical interests because of their specific microRNA biomarker signature and hence potential in clinical and molecular diagnostics.
The past decade has brought about the development and commercialization of a multitude of extraction methods to isolate and purify EVs, primarily from blood liquid biopsies. The EV purity, concentration and which subpopulations are captured strongly depend on the applied EV isolation method. This determines how suitable resulting EV samples are for potential downstream applications, small-RNA sequencing, quantitative RNA measurements, and microRNA biomarker discovery. Hence, an overall transcriptomic analysis pipeline was developed, optimized and validated on various clinical patient cohorts. Applied isolation and characterization methods were benchmarked regarding their suitability for microRNA biomarker discovery as well as biological characteristics of captured EVs, according to the latest MISEV 2018 guidelines.
To deeply analyze the small-RNA deep sequencing results various self-developed bioinformatical tools were applied: (1) comprehensive small-RNA analysis pipeline (via caRNAge), (2) analysis of microRNA isoforms (via isomiRROR), (3) identification of stable microRNA references (via miREV). (4) Differential expressed microRNAs candidates were identified by various multivariate statistics (HCA, PCA, PLS-DA) to find reliable biomarkers. (5) Final goal was the development of a stable and reliable microRNA biomarker signature for an early diagnosis and a valid classification of critical ill patients with different clinical pictures.
Various independent patient cohorts were investigated: healthy volunteers, mild- or severe pneumonia, acute pulmonary failure (ARDS), septic shock, and various stages of Covid-19 patients. Distinct microRNA signatures could be identified, which are applicable to indicate disease progression from healthy, over limited inflammation present in pneumonia, to severe inflammatory changes as seen in ARDS, septic shock or Covid-19.
The study results indicate that EV microRNA biomarkers have high potential for early diagnosis of pneumonia and to indicate disease progression towards severe inflammation events, like ARDS, septic shock or Covid-19. Furthermore, the methodological findings provides guidance for navigating the multitude of EV isolation methods available, and helps researchers and clinicians in the field of molecular diagnostics to make the right choice about the optimal isolation strategy and bioinformatical analysis of small-RNA sequencing datasets to get a valid EV biomarker signature.