Blood RNA Biomarkers Identify Bacterial and Biofilm Coinfections in COVID-19 Intensive Care Patients.

Purpose: Secondary opportunistic coinfections are a significant contributor to morbidity and mortality in intensive care unit (ICU) patients, but can be difficult to identify. Presently, new blood RNA biomarkers were tested in ICU patients to diagnose viral, bacterial, and biofilm coinfections. Methods: COVID-19 ICU patients had whole blood drawn in RNA preservative and stored at -80°C. Controls and subclinical infections were also studied. Droplet digital polymerase chain reaction (ddPCR) quantified 6 RNA biomarkers of host neutrophil activation to bacterial (DEFA1), biofilm (alkaline phosphatase [ALPL], IL8RB/CXCR2), and viral infections (IFI27, RSAD2). Viral titer in blood was measured by ddPCR for SARS-CoV2 (SCV2). Results: RNA biomarkers were elevated in ICU patients relative to controls. DEFA1 and ALPL RNA were significantly higher in severe versus incidental/moderate cases. SOFA score was correlated with white blood cell count (0.42), platelet count (-0.41), creatinine (0.38), and lactate dehydrogenase (0.31). ALPL RNA (0.59) showed the best correlation with SOFA score. IFI27 (0.52) and RSAD2 (0.38) were positively correlated with SCV2 viral titer. Overall, 57.8% of COVID-19 patients had a positive RNA biomarker for bacterial or biofilm infection. Conclusions: RNA biomarkers of host neutrophil activation indicate the presence of bacterial and biofilm coinfections in most COVID-19 patients. Recognizing coinfections may help to guide the treatment of ICU patients.

RNAseq analysis of treatment-dependent signaling changes during inflammation in a mouse cutaneous wound healing model.

BACKGROUND: Despite proven therapeutic effects in inflammatory conditions, the specific mechanisms of phytochemical therapies are not well understood. The transcriptome effects of Traumeel (Tr14), a multicomponent natural product, and diclofenac, a non-selective cyclooxygenase (COX) inhibitor, were compared in a mouse cutaneous wound healing model to identify both known and novel pathways for the anti-inflammatory effect of plant-derived natural products. METHODS: Skin samples from abraded mice were analyzed by single-molecule, amplification-free RNAseq transcript profiling at 7 points between 12 and 192 h after injury. Immediately after injury, the wounds were treated with either diclofenac, Tr14, or placebo control (n = 7 per group/time). RNAseq levels were compared between treatment and control at each time point using a systems biology approach. RESULTS: At early time points (12-36 h), both control and Tr14-treated wounds showed marked increase in the inducible COX2 enzyme mRNA, while diclofenac-treated wounds did not. Tr14, in contrast, modulated lipoxygenase transcripts, especially ALOX12/15, and phospholipases involved in arachidonate metabolism. Notably, Tr14 modulated a group of cell-type specific markers, including the T cell receptor, that could be explained by an overarching effect on the type of cells that were recruited into the wound tissue. CONCLUSIONS: Tr14 and diclofenac had very different effects on the COX/LOX synthetic pathway after cutaneous wounding. Tr14 allowed normal autoinduction of COX2 mRNA, but suppressed mRNA levels for key enzymes in the leukotriene synthetic pathway. Tr14 appeared to have a broad 'phytocellular' effect on the wound transcriptome by altering the balance of cell types present in the wound.

An efficient concordant integrative analysis of multiple large-scale two-sample expression data sets.

MOTIVATION: We have proposed a mixture model based approach to the concordant integrative analysis of multiple large-scale two-sample expression datasets. Since the mixture model is based on the transformed differential expression test P-values (z-scores), it is generally applicable to the expression data generated by either microarray or RNA-seq platforms. The mixture model is simple with three normal distribution components for each dataset to represent down-regulation, up-regulation and no differential expression. However, when the number of datasets increases, the model parameter space increases exponentially due to the component combination from different datasets. RESULTS: In this study, motivated by the well-known generalized estimating equations (GEEs) for longitudinal data analysis, we focus on the concordant components and assume that the proportions of non-concordant components follow a special structure. We discuss the exchangeable, multiset coefficient and autoregressive structures for model reduction, and their related expectation-maximization (EM) algorithms. Then, the parameter space is linear with the number of datasets. In our previous study, we have applied the general mixture model to three microarray datasets for lung cancer studies. We show that more gene sets (or pathways) can be detected by the reduced mixture model with the exchangeable structure. Furthermore, we show that more genes can also be detected by the reduced model. The Cancer Genome Atlas (TCGA) data have been increasingly collected. The advantage of incorporating the concordance feature has also been clearly demonstrated based on TCGA RNA sequencing data for studying two closely related types of cancer. AVAILABILITY AND IMPLEMENTATION: Additional results are included in a supplemental file. Computer program R-functions are freely available at http://home.gwu.edu/∼ylai/research/Concordance. CONTACT: ylai@gwu.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs.

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

BACKGROUND: With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. METHODS: In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. RESULTS: We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. CONCLUSIONS: This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

BACKGROUND: Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. METHODS: We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. RESULTS: We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. CONCLUSIONS: This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.

Single-molecule long-read 16S sequencing to characterize the lung microbiome from mechanically ventilated patients with suspected pneumonia.

In critically ill patients, the development of pneumonia results in significant morbidity and mortality and additional health care costs. The accurate and rapid identification of the microbial pathogens in patients with pulmonary infections might lead to targeted antimicrobial therapy with potentially fewer adverse effects and lower costs. Major advances in next-generation sequencing (NGS) allow culture-independent identification of pathogens. The present study used NGS of essentially full-length PCR-amplified 16S ribosomal DNA from the bronchial aspirates of intubated patients with suspected pneumonia. The results from 61 patients demonstrated that sufficient DNA was obtained from 72% of samples, 44% of which (27 samples) yielded PCR amplimers suitable for NGS. Out of the 27 sequenced samples, only 20 had bacterial culture growth, while the microbiological and NGS identification of bacteria coincided in 17 (85%) of these samples. Despite the lack of bacterial growth in 7 samples that yielded amplimers and were sequenced, the NGS identified a number of bacterial species in these samples. Overall, a significant diversity of bacterial species was identified from the same genus as the predominant cultured pathogens. The numbers of NGS-identifiable bacterial genera were consistently higher than identified by standard microbiological methods. As technical advances reduce the processing and sequencing times, NGS-based methods will ultimately be able to provide clinicians with rapid, precise, culture-independent identification of bacterial, fungal, and viral pathogens and their antimicrobial sensitivity profiles.

On the importance of small changes in RNA expression.

The analysis of the differential expression of genes has been the key goal of many molecular biology methods for decades and will remain with us for decades to come. It constitutes a fundamental resource at our disposal for determining the relationship between products of transcription, biology and disease. The completed genome sequencing of many common species allowed microarrays and RNA sequencing (RNAseq) to become major tools in Systems Biology. However, we estimate that at least half of all experiments ignore transcripts that change less than some subjectively chosen threshold, typically around 2-3 fold. Here we show that a majority of the informative RNAs and differentially expressed transcripts can exhibit fold changes less than 2. We use highly quantitative single-molecule sequencing of total cellular RNA derived from a time course of inflammatory response, a process critical to a large number of diseases. Furthermore, we show that enrichment of biologically-relevant functions occurs even at very low fold changes in RNA levels. In addition, we show that most of the common statistical methods can reliably detect transcripts with low fold change when as few as 3 biological replicates are sequenced using single-molecule based RNAseq. In conclusion, given the prevalence of expression profiling in current research, the loss of data in half of all expression studies results in a significant, yet needless drain on the discovery process.

RNAseq of INOCA patients identifies innate, invariant, and acquired immune changes: potential autoimmune microvascular dysfunction.

Background: Ischemia with non-obstructive coronary arteries (INOCA) is a major clinical entity that involves potentially 20%-30% of patients with chest pain. INOCA is typically attributed either to coronary microvascular disease and/or vasospasm, but is likely distinct from classical coronary artery disease (CAD). Objectives: To gain insights into the etiology of INOCA and CAD, RNA sequencing of whole blood from patients undergoing both stress testing and elective invasive coronary angiography (ICA) was conducted. Methods: Stress testing and ICA of 177 patients identified 40 patients (23%) with INOCA compared to 39 controls (stress-, ICA-). ICA+ patients divided into 38 stress- and 60 stress+. RNAseq was performed by Illumina with ribosomal RNA depletion. Transcriptome changes were analyzed by DeSeq2 and curated by manual and automated methods. Results: Differentially expressed genes for INOCA were associated with elevated levels of transcripts related to mucosal-associated invariant T (MAIT) cells, plasmacytoid dendritic cells (pcDC), and memory B cells, and were associated with autoimmune diseases such as rheumatoid arthritis. Decreased transcripts were associated with neutrophils, but neutrophil transcripts, per se, were not less abundant in INOCA. CAD transcripts were more related to T cell functions. Conclusions: Elevated transcripts related to pcDC, MAIT, and memory B cells suggest an autoimmune component to INOCA. Reduced neutrophil transcripts are likely attributed to chronic activation leading to increased translation and degradation. Thus, INOCA could result from stimulation of B cell, pcDC, invariant T cell, and neutrophil activation that compromises cardiac microvascular function.

COVID-19 point-of-care tests can identify low-antibody individuals: In-depth immunoanalysis of boosting benefits in a healthy cohort.

The recommended COVID-19 booster vaccine uptake is low. At-home lateral flow assay (LFA) antigen tests are widely accepted for detecting infection during the pandemic. Here, we present the feasibility and potential benefits of using LFA-based antibody tests as a means for individuals to detect inadequate immunity and make informed decisions about COVID-19 booster immunization. In a health care provider cohort, we investigated the changes in the breadth and depth of humoral and T cell immune responses following mRNA vaccination and boosting in LFA-positive and LFA-negative antibody groups. We show that negative LFA antibody tests closely reflect the lack of functional humoral immunity observed in a battery of sophisticated immune assays, while positive results do not necessarily reflect adequate immunity. After booster vaccination, both groups gain depth and breadth of systemic antibodies against evolving SARS-CoV-2 and related viruses. Our findings show that LFA-based antibody tests can alert individuals about inadequate immunity against COVID-19, thereby increasing booster shots and promoting herd immunity.

Diagnostic accuracy of novel mRNA blood biomarkers of infection to predict outcomes in emergency department patients with undifferentiated abdominal pain.

Abdominal pain represents greater than 20% of US Emergency Department (ED) visits due to a wide range of illnesses. There are currently no reliable blood biomarkers to predict serious outcomes in patients with abdominal pain. Our previous studies have identified three mRNA transcripts related to innate immune activation: alkaline phosphatase (ALPL), interleukin-8 receptor-ß (IL8RB), and defensin-1 (DEFA1) as promising candidates to detect an intra-abdominal infection. The objective of this study was to evaluate the accuracy of these mRNA biomarkers to predict likely infection, hospitalization and surgery in Emergency Department patients with undifferentiated abdominal pain. We prospectively enrolled Emergency Department patients with undifferentiated abdominal pain who received an abdominal CT scan as part of their evaluation. Clinical outcomes were abstracted from the CT scan and medical records. mRNA biomarker levels were calculated independent of the clinical outcomes and their accuracy was assessed to predict infectious diagnoses, surgery and hospital admission. 89 patients were enrolled; 21 underwent surgery; 47 underwent hospital admission; and, no deaths were observed within 30 days. In identifying which cases were likely infectious, mRNA biomarkers' AUC values were: ALPL, 0.83; DEFA1 0.51; IL8RB, 0.74; and ALPL + IL8RB, 0.79. In predicting which Emergency Department patients would receive surgery, the AUC values were: ALPL, 0.75; DEFA1, 0.58; IL8RB, 0.75; and ALPL + IL8RB, 0.76. In predicting hospital admission, the AUC values were: ALPL, 0.78; DEFA1, 0.52; IL8RB, 0.74; and, ALPL + IL8RB, 0.77. For predicting surgery, ALPL + IL8RB's positive likelihood ratio (LR) was 3.97; negative LR (NLR) was 0.70. For predicting hospital admission, the same marker's positive LR was 2.80 with an NLR of 0.45. Where the primary cause for admission was a potentially infectious disorder, 33 of 34 cases (97%) had positive RNA scores. In a pragmatic, prospective diagnostic accuracy trial in Emergency Department patients with undifferentiated abdominal pain, mRNA biomarkers showed good accuracy to identify patients with potential infection, as well as those needing surgery or hospital admission.

RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance.

Background: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD. Methods: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA). Results: The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells. Conclusions: These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Longitudinal Analysis of Humoral and Cellular Immune Response Following SARS-CoV-2 Vaccination Supports Utilizing Point-Of-Care Tests to Enhance COVID-19 Booster Uptake.

Individuals with weaker neutralizing responses show reduced protection with SARS-CoV-2 variants. Booster vaccines are recommended for vaccinated individuals, but the uptake is low. We present the feasibility of utilizing point-of-care tests (POCT) to support evidence-based decision-making around COVID-19 booster vaccinations. Using infectious virus neutralization, ACE2 blocking, spike binding, and TCR sequencing assays, we investigated the dynamics of changes in the breadth and depth of blood and salivary antibodies as well as T-cell clonal response following mRNA vaccination in a cohort of healthcare providers. We evaluated the accuracy of two POCTs utilizing either blood or saliva to identify those in whom humoral immunity was inadequate. >4 months after two doses of mRNA vaccine, SARS-CoV-2 binding and neutralizing Abs (nAbs) and T-cell clones declined 40-80%, and 2/3rd lacked Omicron nAbs. After the third mRNA booster, binding and neutralizing Abs increased overall in the systemic compartment; notably, individuals with previously weak nAbs gained sharply. The third dose failed to stimulate secretory IgA, but salivary IgG closely tracked systemic IgG levels. Vaccine boosting increased Ab breadth against a divergent bat sarbecovirus, SHC014, although the TCR-beta sequence breadth was unchanged. Post 3rd booster dose, Ab avidity increased for the Wuhan and Delta strains, while avidity against Omicron and SHC014 increased to levels seen for Wuhan after the second dose. Negative results on POCTs strongly correlated with a lack of functional humoral immunity. The third booster dose helps vaccinees gain depth and breadth of systemic Abs against evolving SARS-CoV-2 and related viruses. Our findings show that POCTs are useful and easy-to-access tools to inform inadequate humoral immunity accurately. POCTs designed to match the circulating variants can help individuals with booster vaccine decisions and could serve as a population-level screening platform to preserve herd immunity. One Sentence Summary: SARS-CoV-2 point-of-care antibody tests are valuable and easy-to-access tools to inform inadequate humoral immunity and to support informed decision-making regarding the current and future booster vaccination.

Apolipoprotein L6, induced in atherosclerotic lesions, promotes apoptosis and blocks Beclin 1-dependent autophagy in atherosclerotic cells.

Inflammatory cytokine-regulated apoptosis and autophagy play pivotal roles in plaque rupture and thrombosis of atherosclerotic lesions. However, the molecular interplay between apoptosis and autophagy in vascular cells has not been investigated. Our prior study showed that human apolipoprotein L6 (ApoL6), a pro-apoptotic BH3-only member of the Bcl-2 family, was one of the downstream targets of interferon-γ (INFγ), which sensitizes atherosclerotic lesion-derived cells (LDCs) to Fas-induced apoptosis. To investigate whether ApoL6 plays a causal role in atherosclerotic apoptosis and autophagy, in this study, we demonstrate that IFNγ treatment itself strongly induces ApoL6, and ApoL6 is highly expressed and partially co-localized with activated caspase 3 in activated smooth muscle cells in atherosclerotic lesions. In addition, overexpression of ApoL6 promotes reactive oxygen species (ROS) generation, caspase activation, and subsequent apoptosis, which can be blocked by pan caspase inhibitor and ROS scavenger. Knockdown of ApoL6 expression by siApoL6 suppresses INFγ- and Fas-mediated apoptosis. Further, ApoL6 binds Bcl-X(L), one of the most abundant anti-death proteins in LDCs. Interestingly, forced ApoL6 expression in LDCs induces degradation of Beclin 1, accumulation of p62, and subsequent attenuation of LC3-II formation and translocation and thus autophagy, whereas siApoL6 treatment reverts the phenotype. Taken together, our results suggest that ApoL6 regulates both apoptosis and autophagy in SMCs. IFNγ-initiated, ApoL6-induced apoptosis in vascular cells may be an important factor causing plaque instability and a potential therapeutic target for treating atherosclerosis and cardiovascular disease.

Intronic RNAs constitute the major fraction of the non-coding RNA in mammalian cells.

BACKGROUND: The function of RNA from the non-coding (the so called "dark matter") regions of the genome has been a subject of considerable recent debate. Perhaps the most controversy is regarding the function of RNAs found in introns of annotated transcripts, where most of the reads that map outside of exons are usually found. However, it has been reported that the levels of RNA in introns are minor relative to those of the corresponding exons, and that changes in the levels of intronic RNAs correlate tightly with that of adjacent exons. This would suggest that RNAs produced from the vast expanse of intronic space are just pieces of pre-mRNAs or excised introns en route to degradation. RESULTS: We present data that challenges the notion that intronic RNAs are mere by-standers in the cell. By performing a highly quantitative RNAseq analysis of transcriptome changes during an inflammation time course, we show that intronic RNAs have a number of features that would be expected from functional, standalone RNA species. We show that there are thousands of introns in the mouse genome that generate RNAs whose overall abundance, which changes throughout the inflammation timecourse, and other properties suggest that they function in yet unknown ways. CONCLUSIONS: So far, the focus of non-coding RNA discovery has shied away from intronic regions as those were believed to simply encode parts of pre-mRNAs. Results presented here suggest a very different situation--the sequences encoded in the introns appear to harbor a yet unexplored reservoir of novel, functional RNAs. As such, they should not be ignored in surveys of functional transcripts or other genomic studies.

Transforming growth factor-ß and atherosclerosis: interwoven atherogenic and atheroprotective aspects.

Age-related progression of cardiovascular disease is by far the largest health problem in the US and involves vascular damage, progressive vascular fibrosis and the accumulation of lipid-rich atherosclerotic lesions. Advanced lesions can restrict flow to key organs and can trigger occlusive thrombosis resulting in a stroke or myocardial infarction. Transforming growth factor-beta (TGF-ß) is a major orchestrator of the fibroproliferative response to tissue damage. In the early stages of repair, TGF-ß is released from platelets and activated from matrix reservoirs; it then stimulates the chemotaxis of repair cells, modulates immunity and inflammation and induces matrix production. At later stages, it negatively regulates fibrosis through its strong antiproliferative and apoptotic effects on fibrotic cells. In advanced lesions, TGF-ß might be important in arterial calcification, commonly referred to as "hardening of the arteries". Because TGF-ß can signal through multiple pathways, namely the SMADs, a MAPK pathway and the Rho/ROCK pathways, selective defects in TGF-ß signaling can disrupt otherwise coordinated pathways of tissue regeneration. TGF-ß is known to control cell proliferation, cell migration, matrix synthesis, wound contraction, calcification and the immune response, all being major components of the atherosclerotic process. However, many of the effects of TGF-ß are essential to normal tissue repair and thus, TGF-ß is often thought to be "atheroprotective". The present review attempts to parse systematically the known effects of TGF-ß on both the major risk factors for atherosclerosis and to isolate the role of TGF-ß in the many component pathways involved in atherogenesis.

RNA Sequencing in COVID-19 patients identifies neutrophil activation biomarkers as a promising diagnostic platform for infections.

Infection with the SARS-CoV2 virus can vary from asymptomatic, or flu-like with moderate disease, up to critically severe. Severe disease, termed COVID-19, involves acute respiratory deterioration that is frequently fatal. To understand the highly variable presentation, and identify biomarkers for disease severity, blood RNA from COVID-19 patient in an intensive care unit was analyzed by whole transcriptome RNA sequencing. Both SARS-CoV2 infection and the severity of COVID-19 syndrome were associated with up to 25-fold increased expression of neutrophil-related transcripts, such as neutrophil defensin 1 (DEFA1), and 3-5-fold reductions in T cell related transcripts such as the T cell receptor (TCR). The DEFA1 RNA level detected SARS-CoV2 viremia with 95.5% sensitivity, when viremia was measured by ddPCR of whole blood RNA. Purified CD15+ neutrophils from COVID-19 patients were increased in abundance and showed striking increases in nuclear DNA staining by DAPI. Concurrently, they showed >10-fold higher elastase activity than normal controls, and correcting for their increased abundance, still showed 5-fold higher elastase activity per cell. Despite higher CD15+ neutrophil elastase activity, elastase activity was extremely low in plasma from the same patients. Collectively, the data supports the model that increased neutrophil and decreased T cell activity is associated with increased COVID-19 severity, and suggests that blood DEFA1 RNA levels and neutrophil elastase activity, both involved in neutrophil extracellular traps (NETs), may be informative biomarkers of host immune activity after viral infection.

Beyond genetics: epigenetic code in chronic kidney disease.

Epigenetics refers to a heritable change in the pattern of gene expression that is mediated by a mechanism specifically not due to alterations in the primary nucleotide sequence. Well-known epigenetic mechanisms encompass DNA methylation, chromatin remodeling (histone modifications), and RNA interference. Functionally, epigenetics provides an extra layer of transcriptional control and plays a crucial role in normal physiological development, as well as in pathological conditions. Aberrant DNA methylation is implicated in immune dysfunction, inflammation, and insulin resistance. Epigenetic changes may be responsible for 'metabolic memory' and development of micro- and macrovascular complications of diabetes. MicroRNAs are critical in the maintenance of glomerular homeostasis and hence RNA interference may be important in the progression of renal disease. Recent studies have shown that epigenetic modifications orchestrate the epithelial-mesenchymal transition and eventually fibrosis of the renal tissue. Oxidative stress, inflammation, hyperhomocysteinemia, and uremic toxins could induce epimutations in chronic kidney disease. Epigenetic alterations are associated with inflammation and cardiovascular disease in patients with chronic kidney disease. Reversible nature of the epigenetic changes gives a unique opportunity to halt or even reverse the disease process through targeted therapeutic strategies.

RNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance.

BACKGROUND: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography. Surprisingly, despite well-established clinical indications, up to 40% of the one million invasive cardiac catheterizations return a result of 'no blockage'. The present studies employed RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. METHODS: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by single-molecule sequencing of RNA (RNAseq) to identify transcripts associated with CAD (TRACs) in a discovery group of 96 patients presenting for elective coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs). RESULTS: Surprisingly, 98% of DEGs/TRACs were down-regulated ~ 1.7-fold in patients with mild to severe CAD (> 20% stenosis). The TRACs were independent of comorbid risk factors for CAD, such as sex, hypertension, and smoking. Bioinformatic analysis identified an enrichment in transcripts such as FoxP1, ICOSLG, IKZF4/Eos, SMYD3, TRIM28, and TCF3/E2A that are likely markers of regulatory T cells (Treg), consistent with known reductions in Tregs in CAD. A validation cohort of 80 patients confirmed the overall pattern (92% down-regulation) and supported many of the Treg-related changes. TRACs were enriched for transcripts associated with stress granules, which sequester RNAs, and ciliary and synaptic transcripts, possibly consistent with changes in the immune synapse of developing T cells. CONCLUSIONS: These studies identify a novel mRNA signature of a Treg-like defect in CAD patients and provides a blueprint for a diagnostic test for CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Cardiovascular inflammation and lesion cell apoptosis: a novel connection via the interferon-inducible immunoproteasome.

OBJECTIVE: Increasing evidence suggests that chronic inflammation contributes to atherogenesis, and that acute inflammatory events cause plaque rupture, thrombosis, and myocardial infarction. The present studies examined how inflammatory factors, such as interferon-gamma (IFNgamma), cause increased sensitivity to apoptosis in vascular lesion cells. METHODS AND RESULTS: Cells from the fibrous cap of human atherosclerotic lesions were sensitized by interferon-gamma (IFNgamma) to Fas-induced apoptosis, in a Bcl-X(L) reversible manner. Microarray profiling identified 72 INFgamma-induced transcripts with potential relevance to apoptosis. Half could be excluded because they were induced by IRF-1 overexpression, which did not sensitize to apoptosis. IFNgamma treatment strongly reduced Mcl-1, phospho-Bcl-2 (ser70), and phospho-Bcl-X(L) (ser62) protein levels. Candidate transcripts were modulated by siRNA, overexpression, or inhibitors to assess the effect on IFNgamma-induced Fas sensitivity. Surprisingly, siRNA knockdown of PSMB8 (LMP7), an "immunoproteasome" component, reversed IFNgamma-induced sensitivity to Fas ligation and prevented Fas/IFNgamma-induced degradation of Mcl-1, but did not protect p-Bcl-2 or p-Bcl-X(L). Proteasome inhibition markedly increased Mcl-1, p-Bcl-2, and p-Bcl-X(L) levels after IFNgamma treatment. CONCLUSIONS: Although critical for antigen presentation, the immunoproteasome appears to be a key link between inflammatory factors and the control of vascular cell apoptosis and may thus be an important factor in plaque rupture and myocardial infarction.