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Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy

  • Ruheen Wali , Hang Xu , Cleophas Cheruiyot , Hafiza Nosheen Saleem , Andreas Janshoff , Michael Habeck and Antje Ebert ORCID logo EMAIL logo
Published/Copyright: April 24, 2024
Biological Chemistry
From the journal Biological Chemistry Volume 405 Issue 6

Abstract

Integration of multiple data sources presents a challenge for accurate prediction of molecular patho-phenotypic features in automated analysis of data from human model systems. Here, we applied a machine learning-based data integration to distinguish patho-phenotypic features at the subcellular level for dilated cardiomyopathy (DCM). We employed a human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) model of a DCM mutation in the sarcomere protein troponin T (TnT), TnT-R141W, compared to isogenic healthy (WT) control iPSC-CMs. We established a multimodal data fusion (MDF)-based analysis to integrate source datasets for Ca2+ transients, force measurements, and contractility recordings. Data were acquired for three additional layer types, single cells, cell monolayers, and 3D spheroid iPSC-CM models. For data analysis, numerical conversion as well as fusion of data from Ca2+ transients, force measurements, and contractility recordings, a non-negative blind deconvolution (NNBD)-based method was applied. Using an XGBoost algorithm, we found a high prediction accuracy for fused single cell, monolayer, and 3D spheroid iPSC-CM models (≥92 ± 0.08 %), as well as for fused Ca2+ transient, beating force, and contractility models (>96 ± 0.04 %). Integrating MDF and XGBoost provides a highly effective analysis tool for prediction of patho-phenotypic features in complex human disease models such as DCM iPSC-CMs.

Keywords: atomic force microscopy; machine learning; multimodal data integration; human iPSC-derived cardiomyocytes; CRISPR-Cas9; dilated cardiomyopathy
Corresponding author: Antje Ebert, Department of Cardiology and Pneumology, Heart Research Center, University Medical Center, Göttingen University, Robert-Koch-Strasse 40, D-37075 Göttingen, Germany; and Partner Site Göttingen, DZHK (German Center for Cardiovascular Research), Robert-Koch-Strasse 40, D-37075 Göttingen, Germany, E-mail:
Ruheen Wali and Hang Xu contributed equally to this work.

Funding source: DZHK German Center for Cardiovascular Research

Award Identifier / Grant number: 81X2300194 (AE), 81X4300123 (AE)

Funding source: Universitätsmedizin Göttingen

Award Identifier / Grant number: Clinic for Cardiology and Pneumology (AE)

Funding source: Carl Zeiss Foundation

Award Identifier / Grant number: CZS Stiftungsprofessuren (MH)

Funding source: Deutsche Forschungsgemeinschaft

Award Identifier / Grant number: SFB 1002 Projekt A12 (AE)

Funding source: Germany’s Excellence Strategy

Award Identifier / Grant number: EXC 2067/1-390729940 (AE, AJ)

Acknowledgments

This study was supported by the Deutsche Forschungsgemeinschaft (German Research Foundation), Sonderforschungsbereich 1002, project A12 (A.E.), and under Germany’s Excellence Strategy – EXC 2067/1–390729940. We are grateful for support by the DZHK (German Center for Cardiovascular Research), partner site Goettingen, Germany, project IDs 81X2300194, 81X4300123. We thank for funding by the Clinic for Cardiology and Pneumology at the University Medical Center, Goettingen University and support by the Central Service Unit for Cell Sorting at the University Medical Center, Goettingen University. M. H. gratefully acknowledges funding by the Carl Zeiss Foundation within the program “CZS Stiftungsprofessuren”.

  1. Research ethics: All protocols for studies with human iPSCs were approved by the Goettingen University Ethical Board (IDs 15/2/20 and 20/9/16).

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. Ruheen Wali, data analysis and visualization, manuscript writing; Hang Xu, performed experiments, data analysis, manuscript writing; Cleophas Cheruiyot, performed experiments; Nosheen Saleem, performed experiments; Andreas Janshoff, provided essential infrastructure and advise; Michael Habeck, provided essential methods and advise; Antje Ebert, project management, supervision, manuscript writing.

  3. Competing interests: The authors declare no conflict of interest.

  4. Research funding: Deutsche Forschungsgemeinschaft (German Research Foundation), Sonderforschungsbereich 1002, project A12 (A.E.), Under Germany’s Excellence Strategy – EXC 2067/1–390729940 (A.E., A.J.), DZHK (German Center for Cardiovascular Research), partner site Goettingen, Germany, project IDs 81X2300194, 81X4300123 (A.E.), Clinic for Cardiology and Pneumology at the University Medical Center, Goettingen University (A.E.), Carl Zeiss Foundation within the program “CZS Stiftungsprofessuren” (M.H.).

  5. Data availability: The raw data can be obtained on request from the corresponding author upon reasonable request.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/hsz-2024-0023).

Received: 2024-02-07
Accepted: 2024-03-27
Published Online: 2024-04-24
Published in Print: 2024-06-25

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/hsz-2024-0023
Keywords for this article
atomic force microscopy; machine learning; multimodal data integration; human iPSC-derived cardiomyocytes; CRISPR-Cas9; dilated cardiomyopathy

Articles in the same Issue

  1. Frontmatter
  2. Research Articles/Short Communications
  3. Protein Structure and Function
  4. Structural homology of mite profilins to plant profilins is not indicative of allergic cross-reactivity
  5. Membranes, Lipids, Glycobiology
  6. Apolipoprotein E-containing lipoproteins and their extracellular interactions with LRP1 affect LPS-induced inflammation
  7. Cell Biology and Signaling
  8. Inhibition of Chk1 stimulates cytotoxic action of platinum-based drugs and TRAIL combination in human prostate cancer cells
  9. 18β-glycyrrhetinic acid alleviates radiation-induced skin injury by activating the Nrf2/HO-1 signaling pathway
  10. Yeast Bxi1/Ybh3 mediates conserved mitophagy and apoptosis in yeast and mammalian cells: convergence in Bcl-2 family
  11. Novel Techniques
  12. Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy
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