Evidence map›Paper›PMID 42722292›Full record

ArticleMolecular & cellular proteomics : MCP2026

Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac Repolarization.

Christian L Egly, Lea A Barny, Suah Woo, Devyn Mitchell, Matthew Ku, Björn C Knollmann, Lars Plate, Brett M Kroncke

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Article in Molecular & cellular proteomics : MCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Christian L EglyVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center. Electronic address: christian.l.egly@vumc.org.
Lea A BarnyProgram in Chemical and Physical Biology, Vanderbilt University; Department of Chemistry, Vanderbilt University.
Suah WooVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center.
Devyn MitchellVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center.
Matthew KuVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center.
Björn C KnollmannVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center.
Lars PlateDepartment of Chemistry, Vanderbilt University; Department of Biological Sciences, Vanderbilt University; Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center.
Brett M KronckeVanderbilt Center for Arrhythmia Research and Therapeutics, Department of Medicine, Vanderbilt University Medical Center. Electronic address: brett.m.kroncke.1@vumc.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.

Indexed as

AP-MShERGKv11.1polygenic scoresproteomics

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.