Genomic and Epigenomic Biomarkers of Toxicology and Disease. Группа авторов

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Genomic and Epigenomic Biomarkers of Toxicology and Disease - Группа авторов

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markets OsteomiR™, a product measuring the expression level of 19 blood-circulating miRNAs intended to calculate the risk of a first fracture in female patients with postmenopausal osteoporosis and type-2 diabetes. Similarly, TAmiRNA also provides the ThrombomiR™ panel (11 miRNAs), so as to assess platelet function in cardiovascular disease. In addition, miRNA-based therapeutics—including miRNA mimics or antagonists targeting miRNAs involved in hepatitis C, fibrosis, T-cell lymphoma, heart failure, mesothelioma, and ulcerative colitis—are in various phases of clinical trials (Vandana Saini et al. 2021).

      Challenges and Future Focus

      While there is considerable promise in the use of miRNA biomarkers in biofluids, the precise quantification of circulating miRNAs is challenging and the validation of introduced biomarkers is often unsuccessful. This is indicated by a decline in published biofluid-based miRNA biomarker research in the past couple of years, whereas between 2009 and 2015 yearly publications nearly doubled (Chorley et al. 2021a). This downward trajectory is partially attributed to technical obstacles for measuring miRNAs, some of which have been discussed in the preceding sections. Pre-analytical variables such as sample collection, processing, storage, and extraction are potential causes of inconsistency in miRNA measurements. Post-analytical challenges include the normalization of data and the interpretation of miRNA changes observed to be due to perturbation and release into biofluids. These uncertainties and challenges have inhibited full implementation in multiple sectors such as clinical, regulatory, and academic use.

      For pre-analytical steps, the standardization of procedures and quality assurance will significantly reduce measurement variability. These considerations extend to consistency in sampling during normal cyclic patterns (circadian, menstrual, etc.), location and fraction of sampling (for example in blood: sublingual, aortic, jugular, etc. and whole blood, serum, plasma, or EV fraction), minimization of hemolysis of collected blood samples, and short-term and long-term storage considerations. Also, miRNAs in biofluids may vary in stability owing to interactions with RNA-binding proteins, EVs, and lipoproteins that may impart protection from high RNase activity in these matrices. In freshly isolated human serum, miRs-16, -21, and -142–3p demonstrated greater stability than miRs-122 and -1 after twenty-four hours at room temperature (Koberle et al. 2013). This difference was affected by RNase activity in the serum, whereas miRNAs in EVs were protected against this activity.

      While miRNAs can be consistently measured methodologically, a primary post-analytical challenge is data normalization. The normalization of measured miRNA data would theoretically correct for natural inter-individual fluctuations in fluid volume and rhythmic or cyclic release, as well as for technical variations attributed to miRNA extraction methods, assay inhibition due to biological factors, and other variables. This would allow precise site-to-site, temporal, and methodological comparisons, alongside increasing confidence in interindividual evaluations. Endogenous “housekeeping” calibrators measured in biofluids such as miRNAs or other nucleic acids would be ideal; however, no universally invariant calibrator has been found (Saliminejad et al. 2019). Where endogenous normalizers may not be available or optimized, synthetic exogenous normalizers or miRNAs “spiked-in” during or after small RNA extraction are commonly used to correct technical variations introduced during sample processing and measurement. A recent study analyzed the intra- and inter-individual variability of circulating miRNAs among healthy and cancer patients (Vigneron et al. 2016). Intra-individual variability significantly improved with a geometric mean of three exogenous measurements by comparison with endogenous normalization. These same normalizers—and, interestingly, the endogenous normalizer miR-16-5p—also improved cross-platform correlation of qRT-PCR and microarray measurements. Much like pre-analytical variables, normalization procedures must be optimized for each individual system and application to increase one’s confidence in the measurements taken.

      Conclusions

      The identification of miRNA biomarkers that can distinguish the biological effects of toxicant and other environmental chemical exposures is a much needed tool for toxicological and regulatory science. Studies have suggested that these biomarkers, which are stable and present in most biofluids, may indicate general toxicity in a tissue-specific manner. Further, the RNA content of EVs may reflect the type and the physiological or pathological state of the source cells. Extracellular vesicle-mediated functional transfer of miRNAs to recipient cells has been demonstrated both in vitro and in vivo for a variety of diseases and physiological states, but the mechanisms by which EVs are selectively packaged and “addressed” to different cell types are still largely unknown. In addition to specificity of tissue and MOA, in vitro and in vivo studies suggest early, dose-responsive alterations in expression that can indicate breaking points that may lead to adverse health outcomes. Recent

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