Genetic variation of putative myokine signaling is dominated by biologic sex and sex hormones

Abstract
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Abstract

Skeletal muscle plays an integral role in coordinating physiologic homeostasis, where signaling to other tissues via myokines allows for coordination of complex processes. Here, we aimed to leverage natural genetic correlation structure of gene expression both within and across tissues to understand how muscle interacts with metabolic tissues. Specifically, we performed a survey of genetic correlations focused on myokine gene regulation, muscle cell composition, cross-tissue signaling and interactions with genetic sex in humans. While expression levels of a majority of myokines and cell proportions within skeletal muscle showed little relative differences between males and females, nearly all significant cross-tissue enrichments operated in a sex-specific or hormone-dependent fashion; in particular, with estradiol. These sex- and hormone-specific effects were consistent across key metabolic tissues: liver, pancreas, hypothalamus, intestine, heart, visceral and subcutaneous adipose tissue. To characterize the role of estradiol receptor signaling on myokine expression, we generated male and female mice which lack estrogen receptor α specifically in skeletal muscle (MERKO) and integrated with human data. These analyses highlighted potential mechanisms of sex-dependent myokine signaling conserved between species, such as myostatin enriched for divergent substrate utilization pathways between sexes. Several other putative sex-dependent mechanisms of myokine signaling were uncovered, such as muscle-derived TNFA enriched for stronger inflammatory signaling in females compared to males and GPX3 as a male-specific link between glycolytic fiber abundance and hepatic inflammation. Collectively, we provide a population genetics framework for inferring muscle signaling to metabolic tissues in humans. We further highlight sex and estradiol receptor signaling as critical variables when assaying myokine functions and how changes in cell composition are predicted to impact other metabolic organs.

Data availability

All Datasets and detailed analysis available at: https://github.com/marcus-seldin/myokine-signalingNew RNA-seq data generated as part of this study deposited in NIH sequence read archive (SRA) under the project accession: PRJNA785746

The following data sets were generated

1. Marcus Seldin and Andrea Hevener
(2021) MERKO RNA-seq
NIH sequence read archive, PRJNA785746.

https://www.ncbi.nlm.nih.gov/bioproject/PRJNA785746

The following previously published data sets were used

Article and author information

Author details

Leandro M Velez

Department of Biological Chemistry, University of California, Irvine, Irvine, United States

Competing interests
The authors declare that no competing interests exist.
Cassandra Van

Department of Biological Chemistry, University of California, Irvine, Irvine, United States

Competing interests
The authors declare that no competing interests exist.
Timothy M Moore

David Geffen School of Medicine at UCLA, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Zhenqi Zhou

David Geffen School of Medicine at UCLA, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Casey Johnson

Department of Biological Chemistry, University of California, Irvine, Irvine, United States

Competing interests
The authors declare that no competing interests exist.
Andrea L Hevener

David Geffen School of Medicine at UCLA, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Marcus M Seldin

Department of Biological Chemistry, University of California, Irvine, Irvine, United States

For correspondence
mseldin@uci.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-8026-4759

Funding

National Institutes of Health (R00: HL138193)

Marcus M Seldin

National Institutes of Health (DP1: DK130640)

Marcus M Seldin

National Institutes of Health (dkNET pilot grant: DK097771)

Marcus M Seldin

National Institutes of Health (UCLA Intercampus Medical Genetics Training Program: T32GM008243)

Timothy M Moore

National Institutes of Health (U54: DK120342)

Andrea L Hevener

National Institutes of Health (R01: DK109724)

Andrea L Hevener

National Institutes of Health (P30: DK063491)

Andrea L Hevener

National Institutes of Health (R01: DK125354)

Zhenqi Zhou

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All animal research was approved by the UCLA IACUC, where dare and procedures described in detail here: 10.1126/scitranslmed.aax8096

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.