# The Functional Connectome of the Mechanically Loaded Cardiomyocyte

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2023 · $670,458

## Abstract

Mechanical load on the heart profoundly affects cardiac excitation-contraction (E-C) coupling that governs
heart function. Recent experimental studies have revealed that mechanotransduction mechanisms link to
multiple signaling pathways to modulate the activities of many ion channels, Ca2+ handling molecules, and
contractile proteins, which work in concert to regulate contractile force to compensate for external load
changes. Such autoregulation of contractility requires highly coordinated modulation of many molecules by
mechanotransduction. PROBLEM: Current mathematical modeling of cardiomyocytes often uses one-at-a-
time parameter changes in model simulations. To understand how multiple parameters and molecules change
in a coordinated pattern, however, will require a new mathematical strategy. One-at-a-time parameter changes
cannot address how multiple parameters change in a coordinated way. Studying the coordinated changes
requires simultaneously changing many model parameters but even this does not, by itself, reveal how the
changes are coordinated. INNOVATION: We will develop a new Functional Connectome approach by the
following strategy. (a) Randomly change parameters of many subsystems. Because we make few a priori
assumptions on what subsystems might be involved, this approach can reduce exclusion of some subsystems,
which is important because cellular processes are highly interconnected. (b) From many simulated parameter
combinations, we use experimental data to filter out a small number of subsets that fit all the data. Such a
subset is called an Acceptable Parameter Set (APS). (c) To determine the coordinated changes of
subsystems, we use the Singular Value Decomposition (SVD). SVD factorization of the parameter matrix
shows that the APS often lies in a low-dimensional subspace of the entire high-dimension parameter space.
The linear structure of this subspace gives both the map of connected subsystems and how the subsystems
are modulated coordinately to produce the functional output. We call this connection map the Functional
Connectome. Our interdisciplinary team will combine mathematical modeling with state-of-the-art
experiments to achieve three specific aims: (1) Extend the cardiomyocyte mathematical model to include
mechano-chemo-transduction feedback loop for studying autoregulation of Ca2+ and contractility in response to
mechanical load changes. (2) Develop the Functional Connectome modeling platform to find patterns in myriad
molecular changes. (3) Experimental test of the Functional Connectome predictions in mechanically loaded
cardiomyocytes. SIGNIFICANCE: The outcome of this project will provide a new mathematical platform for
studying coordinated changes in biological cells, which enables finding patterns in myriad molecular changes
by various stimuli, and piece together many data to form a big picture. We will apply the Functional
Connectome to study how mechanical load on cardiomyocyte causes coordinated molecular chang...

## Key facts

- **NIH application ID:** 10534247
- **Project number:** 5R01HL149431-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** Ye Chen-Izu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $670,458
- **Award type:** 5
- **Project period:** 2019-12-10 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10534247

## Citation

> US National Institutes of Health, RePORTER application 10534247, The Functional Connectome of the Mechanically Loaded Cardiomyocyte (5R01HL149431-04). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10534247. Licensed CC0.

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