Evidence map›Paper›PMID 41446209›Full record

ArticlebioRxiv : the preprint server for biology2025

Multiparametric Assessment of TNNI3 Variant Phenotypes in Human iPSC-Cardiomyocytes Correlates with Disease Severity in Patients.

David W Staudt, Peter Pq Tran, Brendan J Floyd, Kyla Dunn, Dongju Han, Xiomara Carhuamaca, Ricardo Serrano, Anna P Hnatiuk, Seyun Bang, Victoria N Parikh and 2 more

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

David W StaudtDivision of Pediatric Cardiology, Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0002-3399-9311
Peter Pq TranStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Brendan J FloydDivision of Pediatric Cardiology, Department of Pediatrics, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0003-3185-0174
Kyla DunnStanford Center for Inherited Cardiovascular Disease, Stanford Medicine, Stanford CA 94305.
Dongju HanStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Xiomara CarhuamacaStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Ricardo SerranoStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Anna P HnatiukStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Seyun BangStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Victoria N ParikhStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Euan A AshleyStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.
Mark MercolaStanford Cardiovascular Institute and Department of Medicine, Stanford University, Stanford, CA 94305, USA.

Funding

Project 3 (Mercola)P01HL141084 · NHLBI · STANFORD UNIVERSITY · PI Joseph C. Wu · 2019 to 2026
$21.1M
Pathogenic hotspots illuminate mechanism and therapeutic potential in arrhythmogenic cardiomyopathyR01HL168059 · NHLBI · STANFORD UNIVERSITY · PI Victoria Parikh · 2023 to 2026
$3.0M
Structure function relationships from deep mutational scanning in human cardiomyopathyR01HL144843 · NHLBI · STANFORD UNIVERSITY · PI ASHLEY, EUAN A · 2020 to 2023
$2.8M
hiPSC Modeling of Restrictive Cardiomyopathy for Drug TestingR01HL169340 · NHLBI · STANFORD UNIVERSITY · PI MARK MERCOLA · 2023 to 2026
$2.3M
Probing the Molecular Mechanisms of Diastolic Dysfunction Using Patient-Specific Stem CellsK08HL165094 · NHLBI · STANFORD UNIVERSITY · PI David Wells Staudt · 2023 to 2026
$664k
Defining kinase interaction pathways to enhance anti-cancer efficacy and minimize associated morbidities of kinase inhibitor drugs.K99CA279895 · NCI · STANFORD UNIVERSITY · PI HNATIUK HNATIUK, ANNA PAVLOVNA · 2023 to 2024
$276k
NCI NIH HHS K99 CA279895NHLBI NIH HHS K08 HL165094NHLBI NIH HHS P01 HL141084NHLBI NIH HHS R01 HL144843NHLBI NIH HHS R01 HL168059NHLBI NIH HHS R01 HL169340
6 · The paper itself

Abstract

Background: The routine genetic testing of cardiomyopathy patients has significantly accelerated the identification of causative cardiomyopathy variants. However, translating these genetic insights into effective patient management poses significant challenges, since the impact of gene variants on physiological function and clinical outcomes is not yet fully understood. Therefore, there is an urgent need for large-scale methods to assess the effects of genetic variants on cardiomyocyte physiology and to establish correlations between functional phenotypes and clinical severity. Methods: We developed a high throughput imaging platform to measure force generation and calcium handling throughout the cardiac cycle of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). By expressing variants of a sarcomeric protein [cardiac Troponin-I (TNNI3)] in a healthy genetic background, we were able to assess sarcomeric calcium sensitivity as well as systolic and diastolic function. Analysis of these parameters distinguished subgroups of variants, and permitted the correlation of Results: Combining contractile force and calcium cycling measurements accurately distinguished known pathogenic from non-pathogenic Conclusions: A high throughput

Identifiers

PMID41446209
PMCPMC12724546

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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.