RESUMO
The global public health crisis caused by the COVID-19 pandemic has intensified the global concern regarding viral respiratory tract infections. Despite their considerable impact on health, society and the economy, effective management of these conditions remains a significant challenge. Integrating high-throughput analyses is pivotal for early detection, prognostication of adverse outcomes, elucidating pathogenetic pathways and developing therapeutic approaches. In recent years, microRNAs (miRNAs), a subset of small noncoding RNAs (ncRNAs), have emerged as promising tools for molecular phenotyping. Current evidence suggests that miRNAs could serve as innovative biological markers, aiding in informed medical decision-making. The cost-effective quantification of miRNAs in standardized samples using techniques routinely employed in clinical laboratories has become feasible. In this context, samples obtained from the airways represent a valuable source of information due to their direct exposure to the infectious agent and host response within the respiratory tract. This review explores viral and host miRNA profiling in airway-derived biosamples as a source of molecular information to guide patient management, with a specific emphasis on SARS-CoV-2 infection.
Assuntos
Biomarcadores , COVID-19 , MicroRNAs , Infecções Respiratórias , SARS-CoV-2 , Humanos , MicroRNAs/genética , COVID-19/genética , COVID-19/virologia , COVID-19/diagnóstico , Infecções Respiratórias/virologia , Infecções Respiratórias/genética , Infecções Respiratórias/diagnóstico , Biomarcadores/metabolismo , SARS-CoV-2/genética , RNA Viral/genética , Sistema Respiratório/virologia , Sistema Respiratório/metabolismoRESUMO
The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies ("multiomic" strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.
Assuntos
Aprendizado de Máquina , RNA não Traduzido , Humanos , RNA não Traduzido/genética , Biomarcadores , Transcriptoma , Biologia Computacional/métodosRESUMO
Elucidating the pathobiological mechanisms underlying post-acute pulmonary sequelae following SARS-CoV-2 infection is essential for early interventions and patient stratification. Here, we investigated the potential of microRNAs (miRNAs) as theranostic agents for pulmoprotection in critical illness survivors. Multicenter study including 172 ICU survivors. Diffusion impairment was defined as a lung-diffusing capacity for carbon monoxide (DLCO) <80% within 12 months postdischarge. A disease-associated 16-miRNA panel was quantified in plasma samples collected at ICU admission. Bioinformatic analyses were conducted using KEGG, Reactome, GTEx, and Drug-Gene Interaction databases. The results were validated using an external RNA-seq dataset. A 3-miRNA signature linked to diffusion impairment (miR-27a-3p, miR-93-5p, and miR-199a-5p) was identified using random forest. Levels of miR-93-5p and miR-199a-5p were independently associated with the outcome, improving patient classification provided by the electronic health record. The experimentally validated targets of these miRNAs exhibited enrichment across diverse pathways, with telomere length quantification in an additional set of samples (n = 83) supporting the role of cell senescence in sequelae. Analysis of an external dataset refined the pathobiological fingerprint of pulmonary sequelae. Gene-drug interaction analysis revealed four FDA-approved drugs. Overall, this study advances our understanding of lung recovery in postacute respiratory infections, highlighting the potential of miRNAs and their targets for pulmoprotection.
RESUMO
Circulating cell-free microRNAs (miRNAs) are promising biomarkers for medical decision-making. Suitable endogenous controls are essential to ensure reproducibility. We aimed to identify and validate endogenous reference miRNAs for qPCR data normalization in samples from SARS-CoV-2-infected hospitalized patients. We used plasma samples (nâ¯=â¯170) from COVID-19 patients collected at hospital admission (COVID-Ponent project, www.clinicaltrials.gov/NCT04824677). First, 179 miRNAs were profiled using RT-qPCR. After stability assessment, candidates were validated using the same methodology. miRNA stability was analyzed using the geNorm, NormFinder and BestKeeper algorithms. Stability was further evaluated using an RNA-seq dataset derived from COVID-19 hospitalized patients, along with plasma samples from patients with critical COVID-19 profiled using RT-qPCR. In the screening phase, after strict control of expression levels, stability assessment selected eleven candidates (miR-17-5p, miR-20a-5p, miR-30e-5p, miR-106a-5p, miR-151a-5p, miR-185-5p, miR-191-5p, miR-423-3p, miR-425-5p, miR-484 and miR-625-5p). In the validation phase, all algorithms identified miR-106a-5p and miR-484 as top endogenous controls. No association was observed between these miRNAs and clinical or sociodemographic characteristics. Both miRNAs were stably detected and showed low variability in the additional analyses. In conclusion, a 2-miRNA panel composed of miR-106a-5p and miR-484 constitutes a first-line normalizer for miRNA-based biomarker development using qPCR in hospitalized patients infected with SARS-CoV-2.
Assuntos
Biomarcadores , COVID-19 , MicroRNAs , SARS-CoV-2 , Humanos , COVID-19/genética , COVID-19/diagnóstico , Biomarcadores/sangue , SARS-CoV-2/genética , MicroRNAs/sangue , MicroRNAs/genética , Masculino , Feminino , Pessoa de Meia-Idade , Índice de Gravidade de Doença , Idoso , MicroRNA Circulante/sangue , MicroRNA Circulante/genética , Adulto , Reprodutibilidade dos TestesRESUMO
BACKGROUND AND PURPOSE: The post-acute sequelae of SARS-CoV-2 infection pose a significant global challenge, with nearly 50% of critical COVID-19 survivors manifesting persistent lung abnormalities. The lack of understanding about the molecular mechanisms and effective treatments hampers their management. Here, we employed microRNA (miRNA) profiling to decipher the systemic molecular underpinnings of the persistent pulmonary complications. EXPERIMENTAL APPROACH: We conducted a longitudinal investigation including 119 critical COVID-19 survivors. A comprehensive pulmonary evaluation was performed in the short-term (median = 94.0 days after hospital discharge) and long-term (median = 358 days after hospital discharge). Plasma miRNAs were quantified at the short-term evaluation using the gold-standard technique, RT-qPCR. The analyses combined machine learning feature selection techniques with bioinformatic investigations. Two additional datasets were incorporated for validation. KEY RESULTS: In the short-term, 84% of the survivors exhibited impaired lung diffusion (DLCO < 80% of predicted). One year post-discharge, 54.4% of this patient subgroup still presented abnormal DLCO . Four feature selection methods identified two specific miRNAs, miR-9-5p and miR-486-5p, linked to persistent lung dysfunction. The downstream experimentally validated targetome included 1473 genes, with heterogeneous enriched pathways associated with inflammation, angiogenesis and cell senescence. Validation studies using RNA-sequencing and proteomic datasets emphasized the pivotal roles of cell migration and tissue repair in persistent lung dysfunction. The repositioning potential of the miRNA targets was limited. CONCLUSION AND IMPLICATIONS: Our study reveals early mechanistic pathways contributing to persistent lung dysfunction in critical COVID-19 survivors, offering a promising approach for the development of targeted disease-modifying agents.