NRF2 is a key regulator of endothelial microRNA expression under proatherogenic stimuli

AIMS

Oxidized phospholipids and microRNAs (miRNAs) are increasingly recognized to play a role in endothelial dysfunction driving atherosclerosis. NRF2 transcription factor is one of the key mediators of the effects of oxidized phospholipids, but the gene regulatory mechanisms underlying the process remain obscure. Here, we investigated the genome-wide effects of oxidized phospholipids on transcriptional gene regulation in human umbilical vein endothelial cells and aortic endothelial cells with a special focus on miRNAs.

METHODS AND RESULTS

We integrated data from HiC, ChIP-seq, ATAC-seq, GRO-seq, miRNA-seq, and RNA-seq to provide deeper understanding of the transcriptional mechanisms driven by NRF2 in response to oxidized phospholipids. We demonstrate that presence of NRF2 motif and its binding is more prominent in the vicinity of up-regulated transcripts and transcriptional initiation represents the most likely mechanism of action. We further identified NRF2 as a novel regulator of over 100 endothelial pri-miRNAs. Among these, we characterize two hub miRNAs miR-21-5p and miR-100-5p and demonstrate their opposing roles on mTOR, VEGFA, HIF1A, and MYC expressions. Finally, we provide evidence that the levels of miR-21-5p and miR-100-5p in exosomes are increased upon senescence and exhibit a trend to correlate with the severity of coronary artery disease.

CONCLUSION

Altogether, our analysis provides an integrative view into the regulation of transcription and miRNA function that could mediate the proatherogenic effects of oxidized phospholipids in endothelial cells.

Profiling of Primary and Mature miRNA Expression in Atherosclerosis-Associated Cell Types

[Figure: see text].

Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility

Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.

Integrative multi-omics profiling in human decedents receiving pig heart xenografts

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

Simultaneous metabolomics analysis of atrial tissue, pericardial fluid and blood reveal novel metabolite signatures of the pathophysiology and biomarkers related to permanent atrial fibrillation

Introduction

Atrial fibrillation (AF) is the most common, complex, and clinically relevant arrhythmia [1]. It is a growing medical condition associated with significant morbidity and mortality, but its pathophysiology has remained widely unknown [2].

Aims

We aim to unravel the complex pathophysiological mechanisms of AF and identify clinically relevant AF-related metabolites. We aim to identify targets for therapeutical interventions and biomarkers for AF diagnostics. Our study material is unique as we can safely study human heart and pericardial fluid in addition to blood, that has been mainly examined in previous studies.

Material and methods

Patients recruited were undergoing cardiac surgery due to valve defects at the University Hospital. For our research, we collected preoperative blood samples and intraoperative right atrial appendage biopsy and pericardial fluid. For our metabolomics study on AF patients, we selected 16 patients with permanent AF and 17 age, gender and underlying disease matched control patients (Fig. 1). Liquid chromatography mass spectrometry (LC-MS) was used to identify molecules and metabolites related to AF. We integrated targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds and metabolites.

Results

Untargeted mass spectrometry (MS) metabolite analysis identified altogether 15751 molecular features and metabolites divided unequally between the sample types (Fig. 2). Altogether, we found 1041 (p<0.05) metabolites from the heart tissue, 774 from the pericardial fluid and 382 from the blood. There were 61 metabolites associated with permanent AF that were found in all three sample types. The approach and our research set-up also allowed us to distinguish metabolites that entered directly from heart tissue to blood and those that remained in heart tissue and pericardial fluid. According to the identified metabolites in the heart tissue, permanent AF was associated with a clear metabolite signature including signs of dysregulated energy -, histidine -, glutathione -, purine -, sugar -, and lipid metabolism and antioxidant defense. Altogether we identified altered, circulating AF-related biomarkers including novel carnitines and acylcarnitines, aminoacids, metabolites from immune response and lipid metabolism. Among the highest statistical significance with qualifiable difference (multivariate α-level 0.0007) we found two novel circulating molecules with known MS spectrum and molecular weight.

Conclusions

We identified totally new pathophysiological processes and novel potential metabolites related to permanent AF to be used as AF biomarkers. Permanent AF is associated with dysreculation of multiple biologically relevant metabolic pathways.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): Academy of FinlandThe Finnish Foundation for Cardiovascular Research

QClus: a droplet filtering algorithm for enhanced snRNA-seq data quality in challenging samples

Single-nuclei RNA sequencing remains a challenge for many human tissues, as incomplete removal of background signal masks cell-type-specific signals and interferes with downstream analyses. Here, we present Quality Clustering (QClus), a droplet filtering algorithm targeted toward challenging samples. QClus uses additional metrics, such as cell-type-specific marker gene expression, to cluster nuclei and filter empty and highly contaminated droplets, providing reliable filtering of samples with varying number of nuclei and contamination levels. In a benchmarking analysis against seven alternative methods across six datasets, consisting of 252 samples and over 1.9 million nuclei, QClus achieved the highest quality in the greatest number of samples over all evaluated quality metrics and recorded no processing failures, while robustly retaining numbers of nuclei within the expected range. QClus combines high quality, automation and robustness with flexibility and user-adjustability, catering to diverse experimental needs and datasets.

Transcriptomic and spatial dissection of human ex vivo right atrial tissue reveals proinflammatory microvascular changes in ischemic heart disease

Cardiovascular disease plays a central role in the electrical and structural remodeling of the right atrium, predisposing to arrhythmias, heart failure, and sudden death. Here, we dissect with single-nuclei RNA sequencing (snRNA-seq) and spatial transcriptomics the gene expression changes in the human ex vivo right atrial tissue and pericardial fluid in ischemic heart disease, myocardial infarction, and ischemic and non-ischemic heart failure using asymptomatic patients with valvular disease who undergo preventive surgery as the control group. We reveal substantial differences in disease-associated gene expression in all cell types, collectively suggesting inflammatory microvascular dysfunction and changes in the right atrial tissue composition as the valvular and vascular diseases progress into heart failure. The data collectively suggest that investigation of human cardiovascular disease should expand to all functionally important parts of the heart, which may help us to identify mechanisms promoting more severe types of the disease.

Genetics, transcriptomics, metagenomics, and metabolomics in the pathogenesis and prediction of atrial fibrillation

The primary cellular substrates of atrial fibrillation (AF) and the mechanisms underlying AF onset remain poorly characterized and therefore, its risk assessment lacks precision. While the use of omics may enable discovery of novel AF risk factors and narrow down the cellular pathways involved in AF pathogenesis, the work is far from complete. Large-scale genome-wide association studies and transcriptomic analyses that allow an unbiased, non-candidate-gene-based delineation of molecular changes associated with AF in humans have identified at least 150 genetic loci associated with AF. However, only few of these loci have been thoroughly mechanistically dissected, indicating that much remains to be discovered for targeted diagnostics and therapeutics. Metabolomics and metagenomics, on the other hand, add to the understanding of AF downstream of the primary substrate and integrate the signalling of environmental and host factors, respectively. These two rapidly developing fields have already provided several correlates of prevalent and incident AF that require additional validation in external cohorts and experimental studies. In this review, we take a look at the recent developments in genetics, transcriptomics, metagenomics, and metabolomics and how they may aid in improving the discovery of AF risk factors and shed light into the molecular mechanisms leading to AF onset.

Targeting IL-1 controls refractory pityriasis rubra pilaris

Pityriasis rubra pilaris (PRP) is a rare inflammatory skin disease with a poorly understood pathogenesis. Through a molecularly driven precision medicine approach and an extensive mechanistic pathway analysis in PRP skin samples, compared to psoriasis, atopic dermatitis, healed PRP, and healthy controls, we identified IL-1β as a key mediator, orchestrating an NF-κB-mediated IL-1β-CCL20 axis, including activation of CARD14 and NOD2. Treatment of three patients with the IL-1 antagonists anakinra and canakinumab resulted in rapid clinical improvement and reversal of the PRP-associated molecular signature with a 50% improvement in skin lesions after 2 to 3 weeks. This transcriptional signature was consistent with in vitro stimulation of keratinocytes with IL-1β. With the central role of IL-1β underscoring its potential as a therapeutic target, our findings propose a redefinition of PRP as an autoinflammatory keratinization disorder. Further clinical trials are needed to validate the efficacy of IL-1β antagonists in PRP.

Global MicroRNA Profiling of Vascular Endothelial Cells

MicroRNA sequencing (miRNA-seq) enables the detection and characterization of the cell miRNome, including miRNA isoforms (isomiRs) and novel miRNA species. In roughly half of the cases, the most abundant isomiR in the cells is not the reference miRNA given in miRBase, which highlights the importance of isomiR-specific analysis. Here, we describe a gel-free protocol for global miRNA profiling in vascular endothelial cells and the main steps of the subsequent data analysis with two alternative analysis methods. In addition to endothelial cells, the protocol is suitable for other cell and tissue types and has been successfully used to obtain miRNA-seq data from human cardiac tissue, plasma, pericardial fluid, and biofluid exosomes.

Protocol for achieving enhanced snRNA-seq data quality using Quality Clustering

Single-nucleus RNA sequencing (snRNA-seq) data analysis presents a challenge in samples that have high levels of ambient RNA contamination. Quality Clustering (QClus) removes empty and highly contaminated droplets by utilizing multiple contamination metrics. Here, we present the steps for snRNA-seq data preprocessing using the QClus algorithm. First, we describe how to set up a computational environment. Next, we demonstrate how to use QClus to remove highly contaminated droplets, and finally, we show how to visualize and evaluate the results. For complete details on the use and execution of this protocol, please refer to Schmauch et al.1.