DNA double-strand breaks (DSBs) are linked to neurodegeneration and senescence. However, it is not clear how DSB-bearing neurons influence neuroinflammation associated with neurodegeneration. Here, we characterize DSB-bearing neurons from the CK-p25 mouse model of neurodegeneration using single-nucleus, bulk, and spatial transcriptomic techniques. DSB-bearing neurons enter a late-stage DNA damage response marked by nuclear factor κB (NFκB)–activated senescent and antiviral immune pathways. In humans, Alzheimer’s disease pathology is closely associated with immune activation in excitatory neurons. Spatial transcriptomics reveal that regions of CK-p25 brain tissue dense with DSB-bearing neurons harbor signatures of inflammatory microglia, which is ameliorated by NFκB knockdown in neurons. Inhibition of NFκB in DSB-bearing neurons also reduces microglia activation in organotypic mouse brain slice culture. In conclusion, DSBs activate immune pathways in neurons, which in turn adopt a senescence-associated secretory phenotype to elicit microglia activation. These findings highlight a previously unidentified role for neurons in the mechanism of disease-associated neuroinflammation.

Ischemic heart disease is the single most common cause of death worldwide with an annual death rate of over 9 million people. Genome-wide association studies have uncovered over 200 genetic loci underlying the disease, providing a deeper understanding of the causal mechanisms leading to it. However, in order to understand ischemic heart disease at the cellular and molecular level, it is necessary to identify the cell-type-specific circuits enabling dissection of driver variants, genes, and signaling pathways in normal and diseased tissues. Here, we provide the first detailed single-cell dissection of the cell types and disease-associated gene expression changes in the living human heart, using cardiac biopsies collected during open-heart surgery from control, ischemic heart disease, and ischemic and non-ischemic heart failure patients. We identify 84 cell types/states, grouped in 12 major cell types. We define markers for each cell type, providing the first extensive reference set for the live human heart. These major cell types include cardiovascular cells (cardiomyocytes, endothelial cells, fibroblasts), rarer cell types (B lymphocytes, neurons, Schwann cells), and rich populations of previously understudied layer-specific epicardial and endocardial cells. In addition, we reveal substantial differences in disease-associated gene expression at the cell subtype level, revealing arterial pericytes as having a central role in the pathogenesis of ischemic heart disease and heart failure. Our results demonstrate the importance of high-resolution cellular subtype mapping in gaining mechanistic insight into human cardiovascular disease.

Single nuclei RNA sequencing (snRNA-seq) is widely used to study tissues and diseases. However, the technique remains challenging, as cytoplasmic RNA often contaminates nuclei-containing droplets and may even complicate the removal of empty droplets. Incomplete removal of contaminated background signal masks cell type-specific signal and interferes with differential gene expression analysis. Thus, removing empty droplets and highly contaminated nuclei is of paramount importance in snRNA-seq analysis. This is especially the case in solid tissues such as the heart. Here, we present QClus, a novel nuclei filtering method targeted to human heart samples. In the human heart, most of the contamination originates from cytoplasmic RNA, stemming from cardiomyocytes. Therefore, we use specific metrics such as splicing, mitochondrial gene expression, nuclear gene expression, and non-cardiomyocyte and cardiomyocyte marker gene expression to cluster nuclei and filter empty and highly contaminated droplets. This approach combined with other filtering steps enables for flexible, automated, and reliable cleaning of samples with varying number of nuclei, quality, and contamination levels. To confirm the robustness of our method, we ran QClus on our dataset of 32 human heart samples and compared results to six alternative methods. None of the methods resulted in the same filtering quality as QClus, each of them failing significantly in some samples. As snRNA-seq is predominantly used on unique human tissue samples, sample failure due to inadequate data processing seems unacceptable. Our study shows that, instead of using universal preprocessing methods, challenging tissue types, such as heart tissue, may benefit from methods that are more specific to the tissue under study, as QClus outperforms the other methods primarily due to improved integration of sample type-specific features.

DNA double strand breaks (DSBs) are linked to aging, neurodegeneration, and senescence. However, the role played by neurons burdened with DSBs in disease-associated neuroinflammation is not well understood. Here, we isolate neurons harboring DSBs from the CK-p25 mouse model of neurodegeneration through fluorescence-activated nuclei sorting (FANS), and characterize their transcriptomes using single-nucleus, bulk, and spatial sequencing techniques. We find that neurons harboring DSBs enter a late-stage DNA damage response marked by the activation of senescent and antiviral-like immune pathways. We identify the NFkB transcription factor as a master regulator of immune gene expression in DSB-bearing neurons, and find that the expression of cytokines like Cxcl10 and Ccl2 develop in DSB-bearing neurons before glial cell types. Alzheimers Disease pathology is significantly associated with immune activation in excitatory neurons, and direct purification of DSB-bearing neurons from Alzheimers Disease brain tissue further validates immune gene upregulation. Spatial transcriptomics reveal that regions of brain tissue dense with DSB-bearing neurons also harbor signatures of inflammatory microglia, which is ameliorated by NFkB knock down in neurons. Inhibition of NFkB or depletion of Ccl2 and Cxcl10 in DSB-bearing neurons also reduces microglial activation in organotypic brain slice culture. In conclusion, we find that in the context of age-associated neurodegenerative disease, DSBs activate immune pathways in neurons, which in turn adopt a senescence associated secretory phenotype to elicit microglia activation. These findings highlight a novel role for neurons in the mechanism of age-associated neuroinflammation.

MicroRNAs (miRNAs) are small RNA molecules that act as regulators of gene expression through targeted mRNA degradation. They are involved in many biological and pathophysiological processes and are widely studied as potential biomarkers and therapeutics agents for human diseases, including cardiovascular disorders. Recently discovered isoforms of miRNAs (isomiRs) exist in high quantities and are very diverse. Despite having few differences with their corresponding reference miRNAs, they display specific functions and expression profiles, across tissues and conditions. However, they are still overlooked and understudied, as we lack a comprehensive view on their condition-specific regulation and impact on differential expression analysis. Here, we show that isomiRs can have major effects on differential expression analysis results, as their expression is independent of their host miRNA genes or reference sequences. We present two miRNA-seq datasets from human umbilical vein endothelial cells, and assess isomiR expression in response to senescence and compartment-specificity (nuclear/cytosolic) under hypoxia. We compare three different methods for miRNA analysis, including isomiR-specific analysis, and show that ignoring isomiRs induces major biases in differential expression. Moreover, isomiR analysis permits higher resolution of complex signal dissection, such as the impact of hypoxia on compartment localization, and differential isomiR type enrichments between compartments. Finally, we show important distribution differences across conditions, independently of global miRNA expression signals. Our results raise concerns over the quasi exclusive use of miRNA reference sequences in miRNA-seq processing and experimental assays. We hope that our work will guide future isomiR expression studies, which will correct some biases introduced by golden standard analysis, improving the resolution of such assays and the biological significance of their downstream studies.

Genome-wide association studies have uncovered over 200 genetic loci underlying coronary artery disease (CAD), providing great hope for a deeper understanding of the causal mechanisms leading to this disease. However, in order to understand CAD at the molecular level, it is necessary to uncover cell-type-specific circuits and to use these circuits to dissect driver variants, genes, pathways, and cell types, in normal and diseased tissues. Here, we provide the most detailed single-cell dissection of human heart cell types, using cardiac biopsies collected during open-heart surgery from healthy, CAD, and CAD-related heart failure donors, and profiling both transcriptional (scRNA-seq) and epigenomic (scATAC-seq) changes. Using this approach, we identify 12 major heart cell types, including typical cardiovascular cells (cardiomyocytes, endothelial cells, fibroblasts), rarer cell types (B cells, neurons, Schwann cells), and previously-unrecognized layer-specific epithelial and endothelial cell types. We define markers for each cell type, providing the first extensive reference set for the living human heart. In addition, we define differential gene expression patterns in CAD relative to control samples, revealing substantial differences in cell-type-specific expression of disease-related genes, emphasizing, for example, the importance of the vascular endothelium in the pathogenesis of CAD. Strikingly, further clustering of the cell types based on specific subtypes revealed important differences in their expression patterns of disease-associated genes. These changes enrich in known CAD genetic loci, enabling us to recognize their likely target genes from scRNA-seq expression changes, candidate driver variants based on scATAC-seq localization and differential DNA accessibility, and candidate upstream regulators based on their enriched motif occurrences in scATAC loci. Overall, our results highlight the relevance and potential of single-cell transcriptional and epigenomic analyses to gain new biological insights into cardiovascular disease, and to recognize novel therapeutic target genes, pathways, and the cell types where they act.

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