Systematic Assessment of Small RNA Profiling in Human Extracellular Vesicles.

MOTIVATION: Extracellular vesicles (EVs) are produced and released by most cells and are now recognized to play a role in intercellular communication through the delivery of molecular cargo, including proteins, lipids, and RNA. Small RNA sequencing (small RNA-seq) has been widely used to characterize the small RNA content in EVs. However, there is a lack of a systematic assessment of the quality, technical biases, RNA composition, and RNA biotypes enrichment for small RNA profiling of EVs across cell types, biofluids, and conditions. METHODS: We collected and reanalyzed small RNA-seq datasets for 2756 samples from 83 studies involving 55 with EVs only and 28 with both EVs and matched donor cells. We assessed their quality by the total number of reads after adapter trimming, the overall alignment rate to the host and non-host genomes, and the proportional abundance of total small RNA and specific biotypes, such as miRNA, tRNA, rRNA, and Y RNA. RESULTS: We found that EV extraction methods varied in their reproducibility in isolating small RNAs, with effects on small RNA composition. Comparing proportional abundances of RNA biotypes between EVs and matched donor cells, we discovered that rRNA and tRNA fragments were relatively enriched, but miRNAs and snoRNA were depleted in EVs. Except for the export of eight miRNAs being context-independent, the selective release of most miRNAs into EVs was study-specific. CONCLUSION: This work guides quality control and the selection of EV isolation methods and enhances the interpretation of small RNA contents and preferential loading in EVs.

Quantitative assessment of cell population diversity in single-cell landscapes.

Single-cell RNA sequencing (scRNA-seq) has become a powerful tool for the systematic investigation of cellular diversity. As a number of computational tools have been developed to identify and visualize cell populations within a single scRNA-seq dataset, there is a need for methods to quantitatively and statistically define proportional shifts in cell population structures across datasets, such as expansion or shrinkage or emergence or disappearance of cell populations. Here we present sc-UniFrac, a framework to statistically quantify compositional diversity in cell populations between single-cell transcriptome landscapes. sc-UniFrac enables sensitive and robust quantification in simulated and experimental datasets in terms of both population identity and quantity. We have demonstrated the utility of sc-UniFrac in multiple applications, including assessment of biological and technical replicates, classification of tissue phenotypes and regional specification, identification and definition of altered cell infiltrates in tumorigenesis, and benchmarking batch-correction tools. sc-UniFrac provides a framework for quantifying diversity or alterations in cell populations across conditions and has broad utility for gaining insight into tissue-level perturbations at the single-cell resolution.

Mortality associated with implantation and management of intrathecal opioid drug infusion systems to treat noncancer pain.

BACKGROUND: In 2006, the authors observed a cluster of three deaths, which circumstances suggested were opioid-related, within 1 day after placement of intrathecal opioid pumps for noncancer pain. Further investigation suggested that mortality among such patients was higher than previously appreciated. The authors performed investigations to quantify that mortality and compare the results to control populations, including spinal cord stimulation and low back surgery. METHODS: After analyzing nine index cases--three sentinel cases and six identified by a prospective strategy--the authors used epidemiological methods to investigate whether mortality rates reflected patient- or therapy-related differences. Mortality rates after intrathecal opioid therapy and spinal cord stimulation were derived by correlating Medtronic device registration data with de-identified data from the Social Security Death Master File. Aggregate demographic and comorbidity data were obtained from Medicare and United Healthcare population databases to examine the influence of demographics and comorbidities on mortality. RESULTS: Device registration and Social Security analyses revealed an intrathecal opioid therapy mortality rate of 0.088% at 3 days after implantation, 0.39% at 1 month, and 3.89% at 1 yr-a higher mortality than after spinal cord stimulation implants or after lumbar diskectomy in community hospitals. Demographic, illness profile, and mortality analyses of large databases suggest, despite limitations, that excess mortality was related to intrathecal opioid therapy, and could not be fully explained by other factors. These findings were consistent with the nine index cases that revealed that respiratory arrest caused or contributed to death in all patients. No device malfunctions associated with overinfusion were identified among cases where data were available. CONCLUSIONS: Patients with noncancer pain treated with intrathecal opioid therapy experience increased mortality compared to similar patients treated by using other therapies. Respiratory depression as a consequence of intrathecal drug overdosage or mixed intrathecal and systemic drug interactions is one plausible, but hypothetical mechanism. The exact causes for patient deaths and the proportion of those deaths attributable to intrathecal opioid therapy remain to be determined. These findings, although based on incomplete information, suggest that it may be possible to reduce mortality in noncancer intrathecal opioid therapy patients.