Project description:An integrative analysis of human biofluid data in the exRNA Atlas revealed the existence of distinct extracellular RNA cargo types. To gain further insight on the biological nature of these cargo types, we correlated exRNA Atlas cargo profiles with a variety of other RNA-seq profiles. This study focuses on lipoprotein particle (LPP) exRNA profiles obtained via sequential density ultracentrifugation (SD-UC) and fast protein liquid chromatography (FPLC).
Project description:Circulating extracellular RNAs (exRNAs) have the potential to serve as biomarkers for a wide range of medical conditions. However, limitations in existing exRNA isolation methods and a lack of knowledge on parameters affecting exRNA variability in human samples may hinder their successful discovery and clinical implementation. Using novel combinations of denaturants, reducing agents, proteolysis and revised organic extraction, we developed an automated, high-throughput approach for recovery of exRNAs and extracellular DNA (exDNA) from the same biofluid sample. We applied the method to characterize exRNAs from 312 plasma and serum samples collected from thirteen healthy volunteers at twelve time points over a two-month period.
Project description:An integrative analysis of human biofluid data in the exRNA Atlas revealed the existence of distinct extracellular RNA cargo types. To determine whether different RNA isolation kits biased detection of certain exRNA cargo types, an integrative analysis was performed using pooled plasma and serum samples, where 10 different RNA isolation kits were applied.
Project description:An integrative analysis of human biofluid data in the exRNA Atlas revealed the existence of distinct extracellular RNA cargo types. In order to detect differences in density between cargo types, cushioned density gradient ultracentrifugation (C-DGUC) of serum and plasma was performed using OptiPrem (TM) density gradient.
Project description:The extracellular RNAs (exRNAs) from human biofluid have recently been systematically characterized. However, the correlations of biofluid exRNA levels and human diseases remain largely untested. Here, considering the unmet need for presymptomatic biomarkers of sporadic Alzheimer’s disease (AD), we leveraged the recently developed SILVER-seq (small-input liquid volume extracellular RNA sequencing) technology to generate exRNA profiles from a longitudinal collection of human plasma samples. These 164 plasma samples were collected from research subjects 70 years or older with up to 15 years of clinical follow-up prior to death and whose clinical diagnoses were confirmed by pathological analysis of their post mortem brains. The exRNAs of AD-activated genes and transposons in the brain exhibited a concordant trend of increase in AD plasma in comparison with age-matched control plasma. However, when we required statistical significance with multiple testing adjustments, phosphoglycerate dehydrogenase (PHGDH) was the only gene that exhibited consistent upregulation in AD brain transcriptomes from 3 independent cohorts and an increase in AD plasma as compared to controls. We validated PHGDH’s serum exRNA and brain protein expression increases in AD by using 5 additional published cohorts. Finally, we compared the time-course exRNA trajectories between “converters” and controls. Plasma PHGDH exRNA exhibited presymptomatic increases in each of the 11 converters during their transitions from normal to cognitive impairment but remained stable over the entire follow-up period in 8 out of the 9 control elderly subjects. These data suggest the potential utilities of plasma exRNA levels for screening and longitudinal exRNA changes as a presymptomatic indication of sporadic AD.
Project description:An integrative analysis of human biofluid data in the exRNA Atlas revealed the existence of distinct extracellular RNA cargo types. To gain further insight on the biological nature of these cargo types, we correlated exRNA Atlas cargo profiles with a variety of other RNA-seq profiles. This study focuses on those samples obtained via ultracentrifugation and nanoscale deterministic lateral displacement (nanoDLD).
Project description:<p>Brain injury resulting from hemorrhagic stroke is clinically challenging to manage and results in high rates of morbidity and mortality. The pathophysiology of brain damage resulting from aneurysmal subarachnoid hemorrhage (aSAH) is largely unknown, and methods to treat and monitor patients are variable with no meaningful correlations to patient outcome. Prediction of patient risk for serious neurological complications is currently a significant clinical obstacle. An extracellular RNA (exRNA) biomarker to predict onset and severity of brain damage would improve patient outcomes. We sequenced plasma and CSF samples from adult patients with SAH. Samples were collected from post bleed day 1 to day 7. Total exRNA was isolated from each sample. In addition, we prepared a subset of 140 CSF samples, isolating the RNA contained within extracellular vesicles and vesicle-depleted biofluid.</p>
