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Decoding the PITX2-controlled genetic network in atrial fibrillation
Jeffrey D. Steimle, Francisco J. Grisanti Canozo, Minjun Park, Zachary A. Kadow, Md. Abul Hassan Samee, James F. Martin
Jeffrey D. Steimle, Francisco J. Grisanti Canozo, Minjun Park, Zachary A. Kadow, Md. Abul Hassan Samee, James F. Martin
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Resource and Technical Advance Cardiology

Decoding the PITX2-controlled genetic network in atrial fibrillation

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Abstract

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia and a major risk factor for stroke, often arises through ectopic electrical impulses derived from the pulmonary veins (PVs). Sequence variants in enhancers controlling expression of the transcription factor PITX2, which is expressed in the cardiomyocytes (CMs) of the PV and left atrium (LA), have been implicated in AF predisposition. Single nuclei multiomic profiling of RNA and analysis of chromatin accessibility combined with spectral clustering uncovered distinct PV- and LA-enriched CM cell states. Pitx2-mutant PV and LA CMs exhibited gene expression changes consistent with cardiac dysfunction through cell type–distinct, PITX2-directed, cis-regulatory grammars controlling target gene expression. The perturbed network targets in each CM were enriched in distinct human AF predisposition genes, suggesting combinatorial risk for AF genesis. Our data further reveal that PV and LA Pitx2-mutant CMs signal to endothelial and endocardial cells through BMP10 signaling with pathogenic potential. This work provides a multiomic framework for interrogating the basis of AF predisposition in the PVs of humans.

Authors

Jeffrey D. Steimle, Francisco J. Grisanti Canozo, Minjun Park, Zachary A. Kadow, Md. Abul Hassan Samee, James F. Martin

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Figure 2

Identification of PV-enriched cardiomyocyte populations.

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Identification of PV-enriched cardiomyocyte populations.
(A) Uniform man...
(A) Uniform manifold approximation and projection (UMAP) representation of the cardiomyocyte (CM) subsets alone. (B) UMAP of CM subsets separated and colored by sample source. (C) The percentage of each CM subset in each sample. (D) The percentage CM subset from a given sample source. (E) Top CM subset markers identified by multiple pairwise comparison. Full list of markers is in Supplemental Table 2. (F) Heatmap of top 20 parent Gene Ontology (GO) terms identified across the 3 CM subsets. Complete details and child terms can be found in Supplemental Table 3. (G) Volcano plot showing the distribution of differentially accessible regions (DARs) between CM1 and CM2 (Supplemental Table 4). (H) Odds ratio plot by Fisher’s exact test for the association between differentially expressed genes (DEGs) and DARs enriched in CM1 or CM2. Significance values represent the adjusted P value (FDR). (I) Genome browser views at Tbx5 (top) and Myh7b (bottom). Pseudo-bulk ATAC signal plotted for CM1 and CM2 with DARs highlighted. On the right, violin plots representing normalized RNA expression. (J) Top 3 differential motifs identified for CM1 DARs and CM2 DARs alongside the list of any differentially expressed transcription factors (DE TFs) corresponding to each identified motif family.

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ISSN 2379-3708

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