Deciphering the cardiac neuron landscape in heart failure patients

TL;DR

This study maps heart neurons in heart failure patients, identifying a specific neuron type linked to disease progression and treatment response.

Contribution

The study identifies N4-ALK neurons as a novel heart failure-associated subset and reveals their role in disease mechanisms and predictive modeling.

Findings

N4-ALK neurons are significantly enriched in failing hearts and correlate with treatment response to left ventricular assist devices.

The RXRG transcription factor and PTN-PTPRZ1 axis mediate regulatory interactions in N4-ALK neurons during heart failure.

An N4-ALK-derived machine learning model improves heart failure patient identification at the population level.

Abstract

Neurons exert a pivotal role in the preservation of cardiac physiological function. However, there is a lack of explanation about the mechanism of cardiac neurons in the pathogenesis of cardiac dysfunction. Here, we generated a cardiac neuron landscape including 11,026 neuronal cells based on the integration of published single-nucleus RNA sequencing data from 75 patients with heart failure and 45 healthy donors. We determined ten distinct neuronal cell subsets differing in abundances, compositions, and biological functions in the heart. In particular, N4-ALK neurons were significantly enriched in failing hearts relative to healthy controls, and their abundance was associated with the response to left ventricular assist device implantation. RXRG, a transcription factor highly expressed in neuronal cells, participated in the transcriptional regulatory network of N4-ALK neurons and showed a positive correlation with the expression of their marker genes. Notably, in heart failure, the PTN-PTPRZ1 axis mediated specific crosstalk between cardiac fibroblasts and N4-ALK neurons. Finally, we used N4-ALK-related features to develop an optimized prediction model for identifying individuals with heart failure. Overall, our integrative cardiac neuron atlas comprehensively characterizes the molecular and functional diversity of neuronal cells, providing a new perspective for further exploration of the regulatory function of neurons in heart failure.

The heart is a highly innervated organ and is innervated by both sympathetic and parasympathetic nerves, which is crucial for cardiac contraction and electrical signal transduction. Single-cell RNA sequencing offers a powerful resolution for dissecting cardiac neuromodulation by enabling the high-resolution characterization of specific neuronal populations. However, a generalized landscape of neurons in heart failure still remains insufficient. Here, our study systematically integrated current resources of neurons across heart failure researches, providing a perspective on the heterogeneity of cardiac neurons. Our findings first identified a subset of neurons, named N4-ALK, as a heart failure-associated neuronal subset, elucidated their disease-promoting role via the RXRG-PTN-PTPRZ1 axis, and offered new insights into heart failure pathophysiology. Beyond dissecting the underlying molecular mechanisms, we developed an N4-ALK-derived signature within a machine-learning framework to identify heart failure patients at the population level.

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