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Genetic and functional insights into the fractal structure of the heart

Author

Listed:
  • Hannah V. Meyer

    (Cold Spring Harbor Laboratory
    European Bioinformatics Institute (EMBL-EBI))

  • Timothy J. W. Dawes

    (Imperial College London
    Imperial College London)

  • Marta Serrani

    (University of Cambridge
    Politecnico di Milano)

  • Wenjia Bai

    (Imperial College London)

  • Paweł Tokarczuk

    (Imperial College London)

  • Jiashen Cai

    (Duke–National University of Singapore
    Singapore Health Services)

  • Antonio Marvao

    (Imperial College London)

  • Albert Henry

    (University College London
    University College London)

  • R. Thomas Lumbers

    (University College London
    Health Data Research UK
    St Bartholomew’s Hospital)

  • Jakob Gierten

    (University Hospital Heidelberg
    Heidelberg University)

  • Thomas Thumberger

    (Heidelberg University)

  • Joachim Wittbrodt

    (Heidelberg University)

  • James S. Ware

    (Imperial College London
    Imperial College London
    Royal Brompton & Harefield NHS Foundation Trust)

  • Daniel Rueckert

    (Imperial College London)

  • Paul M. Matthews

    (Imperial College London
    Imperial College London)

  • Sanjay K. Prasad

    (Imperial College London
    Royal Brompton & Harefield NHS Foundation Trust)

  • Maria L. Costantino

    (Politecnico di Milano)

  • Stuart A. Cook

    (Imperial College London
    Imperial College London
    Duke–National University of Singapore
    National Heart Centre Singapore)

  • Ewan Birney

    (European Bioinformatics Institute (EMBL-EBI))

  • Declan P. O’Regan

    (Imperial College London)

Abstract

The inner surfaces of the human heart are covered by a complex network of muscular strands that is thought to be a remnant of embryonic development1,2. The function of these trabeculae in adults and their genetic architecture are unknown. Here we performed a genome-wide association study to investigate image-derived phenotypes of trabeculae using the fractal analysis of trabecular morphology in 18,096 participants of the UK Biobank. We identified 16 significant loci that contain genes associated with haemodynamic phenotypes and regulation of cytoskeletal arborization3,4. Using biomechanical simulations and observational data from human participants, we demonstrate that trabecular morphology is an important determinant of cardiac performance. Through genetic association studies with cardiac disease phenotypes and Mendelian randomization, we find a causal relationship between trabecular morphology and risk of cardiovascular disease. These findings suggest a previously unknown role for myocardial trabeculae in the function of the adult heart, identify conserved pathways that regulate structural complexity and reveal the influence of the myocardial trabeculae on susceptibility to cardiovascular disease.

Suggested Citation

  • Hannah V. Meyer & Timothy J. W. Dawes & Marta Serrani & Wenjia Bai & Paweł Tokarczuk & Jiashen Cai & Antonio Marvao & Albert Henry & R. Thomas Lumbers & Jakob Gierten & Thomas Thumberger & Joachim Wit, 2020. "Genetic and functional insights into the fractal structure of the heart," Nature, Nature, vol. 584(7822), pages 589-594, August.
  • Handle: RePEc:nat:nature:v:584:y:2020:i:7822:d:10.1038_s41586-020-2635-8
    DOI: 10.1038/s41586-020-2635-8
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    Cited by:

    1. Saaket Agrawal & Marcus D. R. Klarqvist & Nathaniel Diamant & Takara L. Stanley & Patrick T. Ellinor & Nehal N. Mehta & Anthony Philippakis & Kenney Ng & Melina Claussnitzer & Steven K. Grinspoon & Pu, 2023. "BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Mit Shah & Marco H. A. Inácio & Chang Lu & Pierre-Raphaël Schiratti & Sean L. Zheng & Adam Clement & Antonio Marvao & Wenjia Bai & Andrew P. King & James S. Ware & Martin R. Wilkins & Johanna Mielke &, 2023. "Environmental and genetic predictors of human cardiovascular ageing," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    3. Li, Zhiwei & Wang, Jianjian & Yuan, Meng & Wang, Zhongyu & Feng, Pingfa & Feng, Feng, 2022. "An indicator to quantify the complexity of signals and surfaces based on scaling behaviors transcending fractal," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).

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