The role of the blood transcriptome in innate inflammation and stroke

Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data

As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via:  https://drinchai.shinyapps.io/BloodGen3Module/ .

BloodGen3Module: Blood transcriptional module repertoire analysis and visualization using R

Motivation

We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires.

Results

We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states.

Availability and implementation

The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module.

Supplementary information

Supplementary data are available at Bioinformatics online.

Transcriptomic differences in MSA clinical variants

Background: Multiple system atrophy (MSA) is a rare oligodendroglial synucleinopathy of unknown etiopathogenesis including two major clinical variants with predominant parkinsonism (MSA-P) or cerebellar dysfunction (MSA-C). Objective: To identify novel disease mechanisms we performed a blood transcriptomic study investigating differential gene expression changes and biological process alterations in MSA and its clinical subtypes. Methods: We compared the transcriptome from rigorously gender and age-balanced groups of 10 probable MSA-P, 10 probable MSA-C cases, 10 controls from the Catalan MSA Registry (CMSAR), and 10 Parkinson Disease (PD) patients. Results: Gene set enrichment analyses showed prominent positive enrichment in processes related to immunity and inflammation in all groups, and a negative enrichment in cell differentiation and development of the nervous system in both MSA-P and PD, in contrast to protein translation and processing in MSA-C. Gene set enrichment analysis using expression patterns in different brain regions as a reference also showed distinct results between the different synucleinopathies. Conclusions: In line with the two major phenotypes described in the clinic, our data suggest that gene expression and biological processes might be differentially affected in MSA-P and MSA-C. Future studies using larger sample sizes are warranted to confirm these results.

Impact of Hyperbaric Oxygen on Tissue Healing around Dental Implants in Beagles

Background

The impact of hyperbaric oxygen (HBO) on the healing of soft tissues around dental implants was studied in a beagle model.

Material/Methods

Beagle dogs were randomized to receive implants, followed by postoperative HBO therapy or not (n=10 per group). On postoperative days 3, 7, and 14, tissue specimens were paraffin-embedded and analyzed by hematoxylin-eosin and Masson staining, as well as immunohistochemistry against CD31.

Results

Scores for inflammation pathology based on hematoxylin-eosin staining and mean optical density of collagen fibers were significantly different between the HBO and control groups on postoperative days 3 and 7 (P<0.05), but not on day 14. Mean optical density due to anti-CD31 staining was significantly higher in the HBO group on postoperative days 3, 7, and 14 (P<0.05).

Conclusions

These results suggest that HBO may promote early osteogenesis and soft tissue healing after implantation.

Discordant Expression of Circulating microRNA from Cellular and Extracellular Sources

MicroRNA (miRNA) expression has rapidly grown into one of the largest fields for disease characterization and development of clinical biomarkers. Consensus is lacking in regards to the optimal sample source or if different circulating sources are concordant. Here, using miRNA measurements from contemporaneously obtained whole blood- and plasma-derived RNA from 2391 individuals, we demonstrate that plasma and blood miRNA levels are divergent and may reflect different biological processes and disease associations.

Diverse human extracellular RNAs are widely detected in human plasma

There is growing appreciation for the importance of non-protein-coding genes in development and disease. Although much is known about microRNAs, limitations in bioinformatic analyses of RNA sequencing have precluded broad assessment of other forms of small-RNAs in humans. By analysing sequencing data from plasma-derived RNA from 40 individuals, here we identified over a thousand human extracellular RNAs including microRNAs, piwi-interacting RNA (piRNA), and small nucleolar RNAs. Using a targeted quantitative PCR with reverse transcription approach in an additional 2,763 individuals, we characterized almost 500 of the most abundant extracellular transcripts including microRNAs, piRNAs and small nucleolar RNAs. The presence in plasma of many non-microRNA small-RNAs was confirmed in an independent cohort. We present comprehensive data to demonstrate the broad and consistent detection of diverse classes of circulating non-cellular small-RNAs from a large population.

Extracellular miRNAs are present in a variety of bodily fluids. Here, Freedman et al. analysed plasma-derived RNA by RNA-seq from 40 people followed by targeted RT-qPCR in an additional 2,763 people, and report over 1,000 extracellular RNAs including microRNAs, piwi-interacting RNA and small nucleolar RNAs.

The Use of High-Throughput Technologies to Investigate Vascular Inflammation and Atherosclerosis

The greatest challenge of scientific research is to understand the causes and consequences of disease. In recent years, great efforts have been devoted to unraveling the basic mechanisms of atherosclerosis (the underlying pathology of cardiovascular disease), which remains a major cause of morbidity and mortality worldwide. Because of the complex and multifactorial pathophysiology of cardiovascular disease, different research techniques have increasingly been combined to unravel genetic aspects, molecular pathways, and cellular functions involved in atherogenesis, vascular inflammation, and dyslipidemia to gain a multifaceted picture addressing this complexity. Thanks to the rapid evolution of high-throughput technologies, we are now able to generate large-scale data on the DNA, RNA, and protein levels. With the help of sophisticated computational tools, these data sets are integrated to enhance information extraction and are being increasingly used in a systems biology approach to model biological processes as interconnected and regulated networks. This review exemplifies the use of high-throughput technologies—such as genomics, transcriptomics, proteomics, and epigenomics—and systems biology to explore pathomechanisms of vascular inflammation and atherosclerosis.

Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans

Whole genome expression microarrays can be used to study gene expression in blood, which comes in part from leukocytes, immature platelets, and red blood cells. Since these cells are important in the pathogenesis of stroke, RNA provides an index of these cellular responses to stroke. Our studies in rats have shown specific gene expression changes 24  hours after ischemic stroke, hemorrhage, status epilepticus, hypoxia, hypoglycemia, global ischemia, and following brief focal ischemia that simulated transient ischemic attacks in humans. Human studies show gene expression changes following ischemic stroke. These gene profiles predict a second cohort with >90% sensitivity and specificity. Gene profiles for ischemic stroke caused by large-vessel atherosclerosis and cardioembolism have been described that predict a second cohort with >85% sensitivity and specificity. Atherosclerotic genes were associated with clotting, platelets, and monocytes, and cardioembolic genes were associated with inflammation, infection, and neutrophils. These gene profiles predicted the cause of stroke in 58% of cryptogenic patients. These studies will provide diagnostic, prognostic, and therapeutic markers, and will advance our understanding of stroke in humans. New techniques to measure all coding and noncoding RNAs along with alternatively spliced transcripts will markedly advance molecular studies of human stroke.