Kuo, H. | bioRxiv Science

bioRxiv2026

Functional High Throughput Drug Screening Reveals Cyproheptadine as a Novel Treatment for LMNA -related Cardiomyopathy

ObjectivesTo define shared and variant-specific mechanisms underlying LMNA-associated dilated cardiomyopathy (DCM) and identify therapeutic candidates using human stem cell-based models. BackgroundVariants in the gene LMNA, encoding lamin A/C, cause 5-10% of dilated cardiomyopathies (DCM) and are strongly associated with heart failure and arrhythmias. Yet, the mechanisms by which LMNA variants drive disease and the distinction between shared and variant-specific phenotypes remain unclear. MethodsTo address this, we generated human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from six LMNA-DCM patients carrying three pathogenic variants (T150A, E381Afs*39, R527H) and from five healthy control patients. ResultsLMNA hiPSC-CMs exhibited nuclear membrane deformation, reduced beat rate, arrhythmias, and prolonged calcium transients. Transcriptomic and electrophysiological analyses revealed downregulation of cardiac genes and ion channels, with abnormal Ca{superscript 2} handling emerging as a shared disease mechanism. Leveraging a high-throughput functional assay, we performed an unbiased drug screen and identified cyproheptadine, an FDA-approved antihistamine, as the only compound to alleviate abnormal function across all LMNA variants. ConclusionOur findings reveal a shared disease mechanism across multiple LMNA variants driven by dysregulated Ca{superscript 2} handling. This work establishes a patient-specific drug discovery platform and identifies cyproheptadine as a promising therapeutic candidate for LMNA-associated dilated cardiomyopathy. HighlightsO_LIPatient-specific LMNA hiPSC-cardiomyocytes robustly recapitulate disease phenotypes, including nuclear defects, arrhythmias, and contractile dysfunction. C_LIO_LIDysregulated calcium handling emerges as a unifying mechanism driving pathology across distinct LMNA variants. C_LIO_LIVariant-resolved analysis reveals both shared and mutation-specific molecular and functional signatures. C_LIO_LIHigh-throughput screening identifies cyproheptadine as a potent, broadly effective rescue agent across all tested LMNA variants. C_LIO_LIThis work establishes a scalable precision medicine platform for rapid therapeutic discovery in inherited cardiomyopathies. C_LI

Cell Biology↗

bioRxiv2023

Connecting single neuron transcriptomes to the projectome in mouse visual cortex

The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neurons role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morphoelectric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.

neuroscience↗