BACKGROUND:Heart failure with preserved ejection fraction (HFpEF) is a poorly understood, multisystem disease with high morbidity and mortality. To improve understanding of its pathobiology, we analyzed single-nucleus RNA sequencing in human HFpEF myocardium versus controls. METHODS:Septal myocardial biopsies from 19 HFpEF and 24 nonfailing controls were analyzed using the 10× Genomics Chromium platform, with nuclei isolated from combined samples (6 patients/pool). Genotype-based demultiplexing was performed with souporcell, and gene expression was quantified with CellRanger and CellBender. After quality control, nuclei were annotated by cell types, and differential expression was performed between HFpEF versus controls using limma-voom. Functional analysis was performed using Gene Set Enrichment Analysis. Data were compared with prior single-nucleus RNA sequencing in dilated cardiomyopathy versus controls. RESULTS:We successfully demultiplexed pooled myocardial biopsies, assigning >70% of nuclei to individuals. After quality control, we recovered 48 886 nuclei and identified 14 cell types. Many differentially expressed genes across cell types were detected in HFpEF versus controls (fibroblasts, 5905; cardiomyocytes, 5159; endothelial cells, 2143; pericytes, 1812; and macrophages, 1405). Enriched pathways common to multiple cell types included immune activation, transcription/translation, metabolism, and protein quality control. They were particularly shared between cardiomyocytes and fibroblasts. Vascular smooth muscle cells had a more synthetic, proliferative phenotype. Immune cell analyses suggested enhanced T-cell activation and reduced macrophage clearance programs. Comparative analysis between HFpEF and dilated cardiomyopathy identified transcriptional differences primarily in cardiomyocytes. Two of 3 cardiomyocyte differential expression genes unique to HFpEF were validated to have concordant protein expression changes in HFpEF (MAP2K6 and PLPP3). CONCLUSIONS:Our findings reveal a distinct, cell-type-specific transcriptomic landscape in the human HFpEF myocardium. While HFpEF and dilated cardiomyopathy share significant molecular pathways across most cell types, the profound divergence within cardiomyocytes suggests a unique pathological driver for HFpEF. These signatures may provide a high-resolution roadmap for identifying precision therapeutic targets in HFpEF.

Cardiovascular disease remains the leading cause of global mortality. Understanding its complexity requires dissecting the heart's cellular landscape. Here we present HeartMap, a comprehensive single-nucleus RNA sequencing atlas of the adult human heart. This resource integrates data from nine studies, encompassing over 2.4 million nuclei, 209 individuals, eight anatomical regions and seven disease and healthy states. After rigorous data harmonization and method comparison of batch correction methods, we characterized transcriptional diversity across 14 cell types. To demonstrate the utility of HeartMap, we identified robust disease-associated gene signatures in dilated cardiomyopathy by comparing multiple studies. Notably, we identified distinct activated fibroblast populations, enriched for COL22A1 or TNC, that display variable prevalence across cardiomyopathies. HeartMap provides a valuable tool for exploring cardiac disease at the single-cell level, facilitating both fundamental research and potential therapeutic development.

Background: Mitral valve prolapse (MVP) affects 1–3% of the population and is linked to sudden cardiac death (SCD). Papillary muscle (PM) fibrosis, detectable by cardiac magnetic resonance imaging (MRI), is a recognized risk factor for SCD in MVP. However, the prevalence, clinical relevance, and genetic underpinnings of PM fibrosis in the general population—beyond the context of MVP—remain poorly understood. We hypothesized that PM T1, a measure of interstitial fibrosis, is associated with cardiovascular (CV) disease independent of left ventricular (LV) myocardial fibrosis and has a unique genetic architecture. Methods: We trained a deep learning model to segment PMs using 447 manually labelled cardiac T1 maps in the UK Biobank. In a test set (n=49), we demonstrated excellent correlation between model- and manually-derived PM T1 (r=0.94, 95% CI 0.89-0.97). We then applied the model to our full dataset (n=51,316) to segment PMs and measure PM T1 ( Fig. 1 ). Using multivariable models, adjusting for age, sex, body mass index, and LV T1, we examined the association of PM T1, independent of LV myocardial fibrosis, with relevant prevalent CV diseases and MRI measures of atrial/ventricular structure and function. Lastly, we performed a genome-wide association study (GWAS) of PM T1 across 9,855,505 imputed common variants. Results: Mean age was 65.4 ± 7.7 years and 51.2% were women. PM T1 was 83.6 ms (95% CI 82.9-84.1 ms) higher than LV T1, with mean values of 1,008±57.9 ms and 924.8±34.6 ms, respectively. After adjustment for LV T1, PM T1 (/100 ms) was significantly associated with a 39%, 22%, 31% and 43% increase in the odds of prevalent MVP/mitral regurgitation, heart failure, atrial fibrillation and ventricular arrhythmias, respectively ( Fig. 2a ). PM T1 was also independently associated with increased atrial and ventricular volumes and lower atrial and left ventricular ejection fraction ( Fig. 2b ). In our GWAS, we identified 6 genome-wide significant loci associated with PM T1 implicating genes linked to MVP ( DIRC3/TNS1 and TBX3 ), mitral annular diameter ( GOSR2 ), arrhythmogenic cardiomyopathy ( PLN ), cardiac conduction/arrhythmias ( NFIA ), and cardiac hypertrophy ( FOXO1 ) ( Fig. 3 ). Conclusions: In this first large-scale study of PM fibrosis, we highlight PM T1 as an imaging biomarker independently associated with CV disease and adverse cardiac remodeling. Furthermore, our genetic analysis yields new insights into biologically relevant pathways underlying PM fibrosis.

BACKGROUND:Heart failure with preserved ejection fraction (HFpEF) is a poorly understood, multi-system disease with high morbidity and mortality. To improve our understanding of its underlying biology, we used single-nucleus RNA sequencing (snRNA-seq) to characterize cell-specific gene expression patterns in human HFpEF myocardium. METHODS:Septal myocardial biopsies (2-3 mg) from 30 HFpEF patients and 29 non-failing donor controls were analyzed using the 10X Genomics platform, with nuclei isolated from combined samples (6 patients/pool). Genotype-based demultiplexing was performed with souporcell, and gene expression quantified with CellRanger and CellBender. After quality control, nuclei were clustered and annotated by cell types based on specific marker genes. Differential expression (DE) by cell-type in HFpEF vs controls was performed using limma-voom and functional analysis performed using Gene Set Enrichment Analysis. Data were compared to dilated cardiomyopathy (DCM) using prior snRNA-seq in DCM vs respective controls. RESULTS:We successfully demultiplexed pooled myocardial biopsies, assigning >75% of droplets to individual patients. From eight pooled samples (19 HFpEF, 24 controls), we recovered 48,886 nuclei and identified 14 cell types. Cardiomyocytes (5159 differentially expressed [DE] genes, 36%) and fibroblasts (5905 DE genes, 49%) showed the most DE genes, while endothelial cells (2143), pericytes (1812), and macrophages (1405) had fewer. Enriched pathways common to multiple cell types included transcription/translation, immune activation, metabolism, and protein quality control. Of 7848 DE genes identified via pseudo-bulk snRNA-seq, 51% were DE in fibroblasts and 47% in cardiomyocytes, compared to <20% in other cell types. Unlike dilated cardiomyopathy (DCM), sub-clustering fibroblasts did not reveal an activated fibroblast population in HFpEF. Comparative analysis between HFpEF and DCM identified transcriptional differences primarily in cardiomyocytes. CONCLUSIONS:This study demonstrates the power of genotype-based demultiplexing for single-cell transcriptomic analyses of small endomyocardial biopsies and identifies cardiomyocytes as the principal cell type with distinct transcriptional changes in HFpEF versus DCM. These findings, coupled with differential gene expression and functional pathway analyses, illuminate HFpEF pathways and may nominate compelling targets for future mechanistic studies and therapeutic efforts for HFpEF.

Atrial fibrillation (AF) is the most common heart rhythm abnormality and is a leading cause of heart failure and stroke. This large-scale meta-analysis of genome-wide association studies increased the power to detect single-nucleotide variant associations and found more than 350 AF-associated genetic loci. We identified candidate genes related to muscle contractility, cardiac muscle development and cell-cell communication at 139 loci. Furthermore, we assayed chromatin accessibility using assay for transposase-accessible chromatin with sequencing and histone H3 lysine 4 trimethylation in stem cell-derived atrial cardiomyocytes. We observed a marked increase in chromatin accessibility for our sentinel variants and prioritized genes in atrial cardiomyocytes. Finally, a polygenic risk score (PRS) based on our updated effect estimates improved AF risk prediction compared to the CHARGE-AF clinical risk score and a previously reported PRS for AF. The doubling of known risk loci will facilitate a greater understanding of the pathways underlying AF.

Cardiovascular disease remains the leading cause of global mortality. Understanding its complexity requires dissecting the heart's cellular landscape. We present HeartMap, a comprehensive single-nucleus RNA sequencing atlas of the adult human heart. This resource integrates data from nine studies, encompassing over 2.4 million nuclei, 209 individuals, eight anatomical regions, and seven disease and healthy states. After rigorous data harmonization and benchmarking of batch-correction methods, we characterized transcriptional diversity across 14 cell types. To demonstrate the utility of HeartMap, we identified robust disease-associated gene signatures in dilated cardiomyopathy by comparing across multiple studies. Notably, we identified distinct activated fibroblast populations, with COL22A1 or TNC enrichment, revealing potential differences between inherited and ischemic cardiomyopathies. HeartMap provides a valuable tool for exploring cardiac disease at the single-cell level, facilitating both fundamental research and potential therapeutic development.

IntroductionIndigenous communities globally are inequitably affected by non-communicable diseases such as cancer and coronary artery disease. Increased focus on personalized medicine approaches for the treatment of these diseases offers opportunities to improve the health of Indigenous people. Conversely, poorly implemented approaches pose increased risk of further exacerbating current inequities in health outcomes for Indigenous peoples. The advancement of modern biology techniques, such as three-dimensional (3D) in vitro models and next generation sequencing (NGS) technologies, have enhanced our understanding of disease mechanisms and individualized treatment responses. However, current representation of Indigenous peoples in these datasets is lacking. It is crucial that there is appropriate and ethical representation of Indigenous peoples in generated datasets to ensure these technologies can be used to maximize the benefit of personalized medicine for Indigenous peoples.MethodsThis project discusses the use of 3D tumor organoids and single cell/nucleus RNA sequencing to study cancer treatment responses and explore immune cell roles in coronary artery disease. Using key pillars from currently available Indigenous bioethics frameworks, strategies were developed for the use of Māori participant samples for live tissue and sequencing studies. These were based on extensive collaborations with local Māori community, scientific leaders, clinical experts, and international collaborators from the Broad Institute of MIT and Harvard. Issues surrounding the use of live tissue, genomic data, sending samples overseas and Indigenous data sovereignty were discussed.ResultsThis paper illustrates a real-world example of how collaboration with community and the incorporation of Indigenous worldviews can be applied to molecular biology studies in a practical and culturally responsive manner, ensuring fair and equitable representation of Indigenous peoples in modern scientific data.

Atrial fibrillation (AF) is the most common sustained arrhythmia in humans, yet the molecular basis of AF remains incompletely understood. To determine the cell type-specific transcriptional changes underlying AF, we perform single-nucleus RNA-seq (snRNA-seq) on left atrial (LA) samples from patients with AF and controls. From more than 175,000 nuclei we find that only cardiomyocytes (CMs) and macrophages (M Phi s) have a significant number of differentially expressed genes in patients with AF. Attractin Like 1 (ATRNL1) was overexpressed in CMs among patients with AF and localized to the intercalated disks. Further, in both knockdown and overexpression experiments we identify a potent role for ATRNL1 in cell stress response, and in the modulation of the cardiac action potential. Finally, we detect an unexpected expression pattern for a leading AF candidate gene, KCNN3. In sum, we uncover a role for ATRNL1 which may serve as potential therapeutic target for this common arrhythmia. Characterizing atrial fibrillation (AF) at the single cell level is challenging. Here, the authors perform snRNA-seq on 18 patients with AF to investigate the cell composition, and gene expression shifts associated with this common arrhythmia.

Background: Single-nucleus RNA sequencing (snRNA-seq) is a powerful tool to define the cell-type specific transcriptional signature in health and disease. Although it has been applied to study many forms of cardiovascular disease, few resources exist to compare results across studies and disease states. Methods: We identified 9 studies from the literature with > 10k nuclei, individuals > 18 years, and non-diseased controls. Existing data was downloaded, similarly re-processed, aligned to the GRCh38 reference transcriptome, and aggregated for quality control. Sixteen versions of data integration methods were benchmarked with the single-cell integration benchmarking (scIB) package. Clustering analysis was conducted in SCANPY using established methods to identify global cell types and distinct cell states within cell types. Cell type and cell state labels were assigned to clusters based on differential expression testing using limma-voom. Compositional analysis was conducted using scCODA. Results: HeartMap contains 2,600,078 cells across 36,601 genes from 9 studies, 260 individuals, 7 disease states and normal controls, and 8 anatomical regions. The median age was 54 years (IQR: 17) and 40% were female. Benchmarking selected single cell annotated variational inference as the optimal integration method. Global clustering of all nuclei revealed 14 major cell types. At the sample level, after controlling for differences between studies, the strongest sources of variation in transcription included disease status, patient sex, and anatomical region of sample. To demonstrate the utility of this resource, we identified 10 distinct fibroblast sub-populations among ~580,000 fibroblast cells. Two sub-populations of activated fibroblasts show POSTN+COL22A1+ and POSTN+TNC+ enrichment in primary (DCM/HCM) and ischemic (ICM/AMI/CAD) cardiomyopathies, respectively. Validation using RNA-scope and immunofluorescence staining revealed peri-vascular patterns of TNC+ fibroblasts and interstitial patterns of COL22A1+ fibroblasts in diseased tissues. Conclusions: HeartMap provides a unique resource to the cardiovascular research community and provides additional insights into the transcriptional diversity in health and disease.

Background: Right ventricular failure (RVF) is most commonly observed as a sequela of left ventricular failure (LVF)—for which it more than doubles the risk of mortality. Moreover, isolated RVF is the most common cause of death in pulmonary hypertension and is a leading cause of major adverse events in systemic right ventricle congenital heart diseases. Therapies which effectively treat LVF show poor efficacy for RVF. For example, beta blockade, a cornerstone of LVF therapy, has no efficacy in RVF. Therefore, there is a need for broader exploratory research to identify pathways which are dysregulated in RVF and which could serve as targets for future therapies. Methods/Results: To this end, we performed single-nucleus RNA sequencing (N=11) on RV myocardium from nonfailing or dilated cardiomyopathy (DCM) hearts subgrouped by preserved systolic and diastolic RV function (pRV) or RVF. After cell-type assignment and differential expression analysis, we find a progressive upregulation of pro-angiogenic signaling in vascular endothelial cells (ECs) from nonfailing to pRV and RVF. There is a concomitant expansion of the EC pool from nonfailing to pRV and RVF (EC percentage 5%, 9%,15% for NF, pRV, and RVF; p < 0.05 for one-way ANOVA). We find increased HIF-mediated and VEGF-mediated signaling in these ECs, which may be mediating this expansion. Surprisingly, there is also increased expression of genes regulated by type 1 interferon signaling, which is thought to be anti-angiogenic. Discussion: In summary, we have conducted a single-nuclei transcriptomic study of human RVF and found evidence for increased angiogenic signaling and EC expansion. These findings are significant, as the balance of pro-angiogenic and anti-angiogenic factors in RVF is still unclear, with studies in animal models showing conflicting results in terms of changes in macro/microvasculature in RVF. Here, we provide evidence that in human RVF the balance tends to lead toward a pro-angiogenic phenotype, even in dysfunctional RVs. Orthogonal studies to validate the causal nature of these observed changes in pathogenesis of RVF are currently ongoing.

Ischemic cardiomyopathy (ICM) is the leading cause of heart failure worldwide, yet the cellular and molecular signature of this disease is largely unclear. Using single-nucleus RNA sequencing (snRNA-seq) and integrated computational analyses, we profile the transcriptomes of over 99,000 human cardiac nuclei from the non-infarct region of the left ventricle of 7 ICM transplant recipients and 8 non-failing (NF) controls. We find the cellular composition of the ischemic heart is significantly altered, with decreased cardiomyocytes and increased proportions of lymphatic, angiogenic, and arterial endothelial cells in patients with ICM. We show that there is increased LAMININ signaling from endothelial cells to other cell types in ICM compared with NF. Finally, we find that the transcriptional changes that occur in ICM are similar to those in hypertrophic and dilated cardiomyopathies and that the mining of these combined datasets can identify druggable genes that could be used to target end-stage heart failure.

Background: Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue. Methods: Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data. Results: We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations. Conclusions: Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function 1 , 2 and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts 3 , 4 , but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts. The transcriptional profiles of dilated or hypertrophic cardiomyopathy hearts broadly converged at the tissue and cell-type level. Further, a subset of hearts from patients with cardiomyopathy harbour a unique population of activated fibroblasts that is almost entirely absent from non-failing samples. We performed a CRISPR-knockout screen in primary human cardiac fibroblasts to evaluate this fibrotic cell state transition; knockout of genes associated with fibroblast transition resulted in a reduction of myofibroblast cell-state transition upon TGFβ1 stimulation for a subset of genes. Our results provide insights into the transcriptional diversity of the human heart in health and disease as well as new potential therapeutic targets and biomarkers for heart failure.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Extracellular RNAs are initiating increased interest due to their potentials in serving as novel biomarkers, mediators of intercellular communication, and therapeutic applications. As a newly emerging field, one of the main obstacles is the lack of standardized protocols for RNA isolations. Here we describe protocols for commercially available kits that have been modified to yield consistent results for isolation of extracellular RNA from both whole serum/plasma and extracellular vesicle-enriched serum/plasma samples.

Extracellular RNAs are emerging as novel biomarkers and mediators of intercellular communication. Various methods to isolate RNA from biofluids and cell culture supernatants have been previously used by investigators. Here, we describe several standardized protocols for the isolation of RNAs from cell culture supernatants that utilize commercially available kits and reagents.

Physiological cardiac hypertrophy, in response to stimuli such as exercise, is considered adaptive and beneficial. In contrast, pathological cardiac hypertrophy that arises in response to pathological stimuli such as unrestrained high blood pressure and oxidative or metabolic stress is maladaptive and may precede heart failure. We found that the transcript encoding DNA damage-inducible transcript 4-like (DDiT4L) was expressed in murine models of pathological cardiac hypertrophy but not in those of physiological cardiac hypertrophy. In cardiomyocytes, DDiT4L localized to early endosomes and promoted stress-induced autophagy through a process involving mechanistic target of rapamycin complex 1 (mTORC1). Exposing cardiomyocytes to various types of pathological stress increased the abundance of DDiT4L, which inhibited mTORC1 but activated mTORC2 signaling. Mice with conditional cardiac-specific overexpression of DDiT4L had mild systolic dysfunction, increased baseline autophagy, reduced mTORC1 activity, and increased mTORC2 activity, all of which were reversed by suppression of transgene expression. Genetic suppression of autophagy also reversed cardiac dysfunction in these mice. Our data showed that DDiT4L may be an important transducer of pathological stress to autophagy through mTOR signaling in the heart and that DDiT4L could be therapeutically targeted in cardiovascular diseases in which autophagy and mTOR signaling play a major role.

Introduction: Extracellular vesicles (EVs) function as novel mediators of intercellular communication. Here, we describe a novel, fluorescence switch-based, experimental model to study EV-mediated communication between RBCs and the heart that permits characterization of cross-talk between RBCs and cardiomyocytes at homeostasis and after myocardial infarction. Methods: Mice with RBC-specific expression of cre (Erythropoietin Receptor (EpoR) Cre) were crossed with reporter mTmG Rosa26 mice to yield EpoRCre/mTmG off-springs with membrane GFP expression in RBCs and RBC-derived EVs. Cultured dermal fibroblasts from mTmG mice and a mT/floxed/mGFP HEK 293 reporter cell line were used to assess transfer of functional cre in RBC-derived EVs. To determine targets of RBC-EVs, organs from i)EpoRCre/mTmG (n=3), ii) mTmG (n=3) or iii) mTmG mice transfused with RBC-EVs from EpoR-cre mice and targets of RBC-EVs (determined by mGFP expression due to cre-recombination) were assessed by confocal microscopy. Finally, ischemia-reperfusion-infarction (30 min. LAD ligation) was done in EpoRCre/mGmT mice (n=3) and their blood and organs harvested after a span of 4 weeks to analyze changes in quality and quantity of RBC-EV targets following MI. Results: 1. RBC-EVs (mGFP positive) in plasma accounted for about 9% of total fluorescent EVs as detected by nano-flow cytometry and microscopy. 2. RBC-EVs contained cre protein by EM, and in vitro dermal fibroblasts from mTmG mice or mT/floxed/mGFP HEK 293 reporter cells showed mGFP expression with EpoRCre RBC-EVs, suggesting EV-mediated transfer of functional cre. 3. Cre-mediated recombination was noted in diverse organs in EpoRCre/mTmG mice and mTmTG mice transfused with EpoRCre- EVs with the bone marrow, heart, lungs, kidney and spleen showing the largest degree of recombined cells. 4. Target profile of RBC-EVs demonstrates a distinct pattern of EV-mediated communication among the organs at baseline that may be altered in different disease models. Conclusion: We show proof-of-concept for a novel model to study origin and targets of EV-mediated intercellular communication with significant EV-mediated communication between RBCs and cardiomyocytes under homeostatic conditions.