Multivariate indicators of disease severity in COVID-19.

The novel coronavirus pandemic continues to cause significant morbidity and mortality around the world. Diverse clinical presentations prompted numerous attempts to predict disease severity to improve care and patient outcomes. Equally important is understanding the mechanisms underlying such divergent disease outcomes. Multivariate modeling was used here to define the most distinctive features that separate COVID-19 from healthy controls and severe from moderate disease. Using discriminant analysis and binary logistic regression models we could distinguish between severe disease, moderate disease, and control with rates of correct classifications ranging from 71 to 100%. The distinction of severe and moderate disease was most reliant on the depletion of natural killer cells and activated class-switched memory B cells, increased frequency of neutrophils, and decreased expression of the activation marker HLA-DR on monocytes in patients with severe disease. An increased frequency of activated class-switched memory B cells and activated neutrophils was seen in moderate compared to severe disease and control. Our results suggest that natural killer cells, activated class-switched memory B cells, and activated neutrophils are important for protection against severe disease. We show that binary logistic regression was superior to discriminant analysis by attaining higher rates of correct classification based on immune profiles. We discuss the utility of these multivariate techniques in biomedical sciences, contrast their mathematical basis and limitations, and propose strategies to overcome such limitations.

Nanolock-Nanopore Facilitated Digital Diagnostics of Cancer Driver Mutation in Tumor Tissue.

Cancer driver mutations are clinically significant biomarkers. In precision medicine, accurate detection of these oncogenic changes in patients would enable early diagnostics of cancer, individually tailored targeted therapy, and precise monitoring of treatment response. Here we investigated a novel nanolock-nanopore method for single-molecule detection of a serine/threonine protein kinase gene BRAF V600E mutation in tumor tissues of thyroid cancer patients. The method lies in a noncovalent, mutation sequence-specific nanolock. We found that the nanolock formed on the mutant allele/probe duplex can separate the duplex dehybridization procedure into two sequential steps in the nanopore. Remarkably, this stepwise unzipping kinetics can produce a unique nanopore electric marker, with which a single DNA molecule of the cancer mutant allele can be unmistakably identified in various backgrounds of the normal wild-type allele. The single-molecule sensitivity for mutant allele enables both binary diagnostics and quantitative analysis of mutation occurrence. In the current configuration, the method can detect the BRAF V600E mutant DNA lower than 1% in the tumor tissues. The nanolock-nanopore method can be adapted to detect a broad spectrum of both transversion and transition DNA mutations, with applications from diagnostics to targeted therapy.

Polycationic Probe-Guided Nanopore Single-Molecule Counter for Selective miRNA Detection.

MicroRNAs (miRNAs) are a class of noncoding RNAs that are being explored as a new type of disease biomarkers. The nanopore single-molecule sensor offers a potential noninvasive tool to detect miRNAs for diagnostics and prognosis applications. However, one of the challenges that limits its clinical applications is the presence of a large variety of nontarget nucleic acids in the biofluid extracts. Upon interacting with the nanopore, nontarget nucleic acids produce "contaminative" nanopore signals that interfere with target miRNA discrimination, thus severely lowering the accuracy in target miRNA detection. We have reported a novel method that utilizes a designed polycationic peptide-PNA probe to specifically guide the target miRNA migration toward the nanopore, whereas any nontarget nucleic acids without the probe bound is rejected by the nanopore. Consequently, nontarget species are driven away from the nanopore and only the target miRNA can be detected at low concentration. This method is also able to discriminate miRNAs with single-nucleotide difference by using PNA to capture miRNA. Considering the significance and impact of this substantial advance for the future miRNA detection in biofluid samples, we prepared this detailed protocol, by which the readers can view the experimental procedure, data analysis, and resulting explanation.