High-throughput data-driven analysis of myofiber composition reveals muscle-specific disease and age-associated patterns

Journal Article (2019)
Author(s)

Vered Raz (Leiden University Medical Center)

Yotam Raz (Leiden University Medical Center)

Davy van de Vijver (Leiden University Medical Center)

Davide Bindellini (Leiden University Medical Center)

Maaike van Putten (Leiden University Medical Center)

E.B. van den Akker (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)

Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1096/fj.201801714R
More Info
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Publication Year
2019
Language
English
Research Group
Pattern Recognition and Bioinformatics
Issue number
3
Volume number
33
Pages (from-to)
4046-4053

Abstract

Contractile properties of myofibers are dictated by the abundance of myosin heavy chain (MyHC) isoforms. MyHC composition designates muscle function, and its alterations could unravel differential muscle involvement in muscular dystrophies and aging. Current analyses are limited to visual assessments in which myofibers expressing multiple MyHC isoforms are prone to misclassification. As a result, complex patterns and subtle alterations are unidentified. We developed a high-throughput, data-driven myofiber analysis to quantitatively describe the variations in myofibers across the muscle. We investigated alterations in myofiber composition between genotypes, 2 muscles, and 2 age groups. We show that this analysis facilitates the discovery of complex myofiber compositions and its dependency on age, muscle type, and genetic conditions.—Raz, V., Raz, Y., van de Vijver, D., Bindellini, D., van Putten, M., van den Akker, E. B. High-throughput data-driven analysis of myofiber composition reveals muscle-specific disease and age-associated patterns. FASEB J. 33, 4046–4053 (2019). www.fasebj.org.

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