Evidence map›Paper›PMID 38677172›Full record

ArticleComputers in biology and medicine2024

Modeling cardiomyocyte signaling and metabolism predicts genotype-to-phenotype mechanisms in hypertrophic cardiomyopathy.

A Khalilimeybodi, Jeffrey J Saucerman, P Rangamani

Open access · greenAbstract read
In one paragraph

Article in Computers in biology and medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Immature and mature myocardium in the pathophysiology of hypertrophic cardiomyopathy.Journal of molecular and cellular cardiology plus · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

A KhalilimeybodiDepartment of Mechanical and Aerospace Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla CA 92093, United States of America.
Jeffrey J SaucermanDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America; Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, VA, United States of America.
P RangamaniDepartment of Mechanical and Aerospace Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla CA 92093, United States of America. Electronic address: prangamani@ucsd.edu.
University of California San Diego · USUniversity of Virginia · US

Funding

Systems Pharmacology Model of Cardiac HypertrophyR01HL162925 · NHLBI · UNIVERSITY OF VIRGINIA · PI SAUCERMAN, JEFFREY J., WOLF, MATTHEW J · 2022 to 2025
$3.1M
CRCNS: Biophysical modeling of axonal morphology and functionR01MH139350 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Padmini Rangamani · 2024 to 2026
$1.1M
American Heart Association-American Stroke Association 898850NHLBI NIH HHS R01 HL162925NIMH NIH HHS R01 MH139350
6 · The paper itself

Abstract

Familial hypertrophic cardiomyopathy (HCM) is a significant precursor of heart failure and sudden cardiac death, primarily caused by mutations in sarcomeric and structural proteins. Despite the extensive research on the HCM genotype, the complex and context-specific nature of many signaling and metabolic pathways linking the HCM genotype to phenotype has hindered therapeutic advancements for patients. Here, we have developed a computational model of HCM encompassing cardiomyocyte signaling and metabolic networks and their associated interactions. Utilizing a stochastic logic-based ODE approach, we linked cardiomyocyte signaling to the metabolic network through a gene regulatory network and post-translational modifications. We validated the model against published data on activities of signaling species in the HCM context and transcriptomes of two HCM mouse models (i.e., R403Q-αMyHC and R92W-TnT). Our model predicts that HCM mutation induces changes in metabolic functions such as ATP synthase deficiency and a transition from fatty acids to carbohydrate metabolism. The model indicated major shifts in glutamine-related metabolism and increased apoptosis after HCM-induced ATP synthase deficiency. We predicted that the transcription factors STAT, SRF, GATA4, TP53, and FoxO are the key regulators of cardiomyocyte hypertrophy and apoptosis in HCM in alignment with experiments. Moreover, we identified shared (e.g., activation of PGC1α by AMPK, and FHL1 by titin) and context-specific mechanisms (e.g., regulation of Ca2+ sensitivity by titin in HCM patients) that may control genotype-to-phenotype transition in HCM across different species or mutations. We also predicted potential combination drug targets for HCM (e.g., mavacamten plus ROS inhibitors) preventing or reversing HCM phenotype (i.e., hypertrophic growth, apoptosis, and metabolic remodeling) in cardiomyocytes. This study provides new insights into mechanisms linking genotype to phenotype in familial hypertrophic cardiomyopathy and offers a framework for assessing new treatments and exploring variations in HCM experimental models.

Indexed as

Cardiomyopathy, HypertrophicMyocytes, CardiacAnimalsGenotypeHumansMiceModels, CardiovascularPhenotypeSignal TransductionCardiac metabolismCardiac signalingGenotype-to-phenotypeHypertrophic cardiomyopathyNetwork modelingSystems biology

Identifiers

PMID38677172
PMCPMC11175993
OpenAlexW4395115470

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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 Socratic graph.