Exosomes, first isolated 30 years ago, are nanoscale vesicles shed by most types of cells. The nucleic acid rich content of these nanoparticles, floating in virtually all bodily fluids, has great potential for non-invasive molecular diagnostics and may represent a novel therapeutic delivery system. However, current isolation techniques such as ultracentrifugation are not convenient and do not result in high purity isolation. This represents an interesting challenge for microfluidic technologies, from a cost-effective perspective as well as for enhanced purity capabilities, and point-of-care acquisition and diagnosis. In this frontier review, we present the current challenges, comment the first microfluidic advances in this new field and propose a roadmap for future developments. This review enables biologists and clinicians familiar with exosome enrichment to assess the performance of novel microfluidic devices and, equally, enables microfluidic engineers to educate themselves about this new class of promising biomarker-rich particles and the challenges arising from their clinical use.

Chief Scientist Office of the Scottish Government.

Our objective was to identify microRNA (miRNA) biomarkers of drug-induced liver and kidney injury by profiling the circulating miRNome in patients with acetaminophen overdose. Plasma miRNAs were quantified in age- and sex-matched overdose patients with (N = 27) and without (N = 27) organ injury (APAP-TOX and APAP-no TOX, respectively). Classifier miRNAs were tested in a separate cohort (N = 81). miRNA specificity was determined in non-acetaminophen liver injury and murine models. Sensitivity was tested by stratification of patients at hospital presentation (N = 67). From 1809 miRNAs, 75 were 3-fold or more increased and 46 were 3-fold or more decreased with APAP-TOX. A 16 miRNA classifier model accurately diagnosed APAP-TOX in the test cohort. In humans, the miRNAs with the largest increase (miR-122-5p, miR-885-5p, miR-151a-3p) and the highest rank in the classifier model (miR-382-5p) accurately reported non-acetaminophen liver injury and were unaffected by kidney injury. miR-122-5p was more sensitive than ALT for reporting liver injury at hospital presentation, especially combined with miR-483-3p. A miRNA panel was associated with human kidney dysfunction. In mice, miR-122-5p, miR-151a-3p and miR-382-5p specifically reported APAP toxicity - being unaffected by drug-induced kidney injury. Profiling of acetaminophen toxicity identified multiple miRNAs that report acute liver injury and potential biomarkers of drug-induced kidney injury.

Drug-induced liver injury (DILI) is a major challenge in clinical medicine and drug development. New models are needed for predicting which potential therapeutic compounds will cause DILI in humans, and new markers and mediators of DILI still need to be identified. This review highlights the strengths and weaknesses of using zebrafish as a high-throughput in vivo model for studying DILI. Although the zebrafish liver architecture is different from that of the mammalian liver, the main physiological processes remain similar. Zebrafish metabolize drugs using similar pathways to those in humans; they possess a wide range of cytochrome P450 enzymes that enable metabolic reactions including hydroxylation, conjugation, oxidation, demethylation and de-ethylation. Following exposure to a range of hepatotoxic drugs, the zebrafish liver develops histological patterns of injury comparable to those of mammalian liver, and biomarkers for liver injury can be quantified in the zebrafish circulation. The zebrafish immune system is similar to that of mammals, but the zebrafish inflammatory response to DILI is not yet defined. In order to quantify DILI in zebrafish, a wide variety of methods can be used, including visual assessment, quantification of serum enzymes and experimental serum biomarkers and scoring of histopathology. With further development, the zebrafish may be a model that complements rodents and may have value for the discovery of new disease pathways and translational biomarkers.