Mark Chaffin

Right ventricular failure (RVF) independently predicts mortality in heart failure, yet its pathophysiology is poorly understood. Here we present a multi-modal atlas of human right ventricular pressure loading and failure, including bulk ( n = 142), single-nucleus ( n = 11) and Xenium spatial ( n = 9) transcriptomics in adults, plus pediatric ( n = 14) and mouse pulmonary artery banding cohorts. Subclustering resolved 34 cell subtypes across 12 lineages along a two-phase trajectory. Phase 1 (non-failing to pressure-loaded) accounts for most of the transcriptional change detectable by bulk and single-nucleus RNA sequencing and is marked by loss of resident macrophage identity, fibroblast activation, endothelial expansion and erosion of tissue-protective programs. Phase 2 (pressure-loaded to RVF) produces little change in bulk RNA sequencing but is resolved by spatial transcriptomics, engaging multi-lineage fibrotic, endothelial-activation and cardiomyocyte-reactivation programs, with a gain of extracellular matrix (collagen, laminin, thrombospondin) signaling over a stable cell contact adhesion baseline. Mitochondrial respirometry revealed respiratory dysfunction in adult and mouse RVF but not pediatric RVF. Multi-lineage remodeling of the cardiac microenvironment emerges as the central molecular program of RVF, meriting further study as possible disease-modifying targets.

Cardiovascular disease remains the leading cause of global mortality. Understanding its complexity requires dissecting the heartʼs 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: 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.

Rare coding genetic variants may exert large effects on risk of common disease, yet their contribution to disease architecture and their utility in gene prioritization remain limited by inadequate sample sizes. Here, we performed a massive-scale rare variant association study (RVAS), analyzing over 1.1 million sequenced participants among which 130,000 had atrial fibrillation (AF). Through a multi-mask burden testing approach, we identified 15 genes significantly associated with AF through rare large-effect variation. Integrative analyses revealed strong convergence between genes implicated by rare and common variation, and highlighted instances where RVAS data may aid in GWAS prioritization. Nevertheless, several RVAS genes were not among GWAS loci ( FAM189A2 , ACTC1 , FNIP1 , FBN1 ), or were not nominated through contemporary GWAS prioritization ( KDM5B , ZFP36L2 ). Finally, we observed that ultra-rare protein-disrupting variants - concentrated in a small number of large-effect size genes - explained at least 2% of AF susceptibility across European and African ancestry groups. These findings refine the genetic architecture of AF, while highlighting the value and cost of RVAS for genomic discovery in common disease.

Summary: The 9p21.3 locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of 9p21.3 in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates MTAP as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that MTAP loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF- β –driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at 9p21.3 modulates CAD risk via MTAP —a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype. Highlights: 9p21.3 CAD risk locus harbors 12 functional enhancers active in vascular wall cell types CAD heritability is enriched in stressed vascular fibroblasts and smooth muscle cells High-resolution CRISPRi-MAC-seq maps 9p21.3 enhancer-gene and SNP-gene interactions MTAP identified as a causal effector gene regulated by 9p21.3 fine-mapped and constrained variants MTAP modulates TGF-β-driven pathological vascular cell transitions

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.

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.

Atrial fibrillation (AF) is a prevalent and morbid abnormality of the heart rhythm with a strong genetic component. Here, we meta-analyzed genome and exome sequencing data from 36 studies that included 52,416 AF cases and 277,762 controls. In burden tests of rare coding variation, we identified novel associations between AF and the genes MYBPC3, LMNA, PKP2, FAM189A2 and KDM5B. We further identified associations between AF and rare structural variants owing to deletions in CTNNA3 and duplications of GATA4. We broadly replicated our findings in independent samples from MyCode, deCODE and UK Biobank. Finally, we found that CRISPR knockout of KDM5B in stem-cell-derived atrial cardiomyocytes led to a shortening of the action potential duration and widespread transcriptomic dysregulation of genes relevant to atrial homeostasis and conduction. Our results highlight the contribution of rare coding and structural variants to AF, including genetic links between AF and cardiomyopathies, and expand our understanding of the rare variant architecture for this common arrhythmia.

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.