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Integrate Imaging Flow Cytometry and Transcriptomic Profiling to Evaluate Altered Endocytic CD1d Trafficking
Published on: October 29, 2018
Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac
Christian L Egly1, Lea Barny2,3, Suah Woo1
1Vanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center.
Abstract:
Polygenic scores (PGS) summarize the combined effects of common single-nucleotide polymorphisms and contribute to predictions of disease severity, but biological consequences linked to these common variants remain poorly defined. Here, we focused on polygenic liability for a measurable electrophysiologic trait (the QT interval). Prolonged QT interval, measured on patient electrocardiograms, is associated with an increased risk for cardiac arrhythmia. We investigated human induced pluripotent stem cell cardiomyocytes (hiPSC-CMs) from donors with extreme PGS (i.e., high and low) related to QT interval duration. We paired global proteomics with multiplexed affinity purification mass spectrometry (AP-MS) centered on Kv11.1 (hERG), a major determinant of QT-interval repolarization. Global proteomics indicated increased mitochondrial protein abundance in high-PGS cardiomyocytes, but this did not explain the Kv11.1 interactome. In high-PGS cells, Kv11.1 showed increased associations with myosin motor proteins and endosomal recycling machinery, consistent with altered (and potentially increased) recycling/trafficking dynamics rather than trafficking deficiency observed with most pathogenic Kv11.1 variants. This proof-of-concept study underscores a framework for linking polygenic factors to tractable biological consequences by combining patient-specific hiPSCs, proteomics and affinity-purification. Linking polygenic scores to changes in protein networks provides testable mechanisms that can be applied across many diseases.
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