Skeletal muscle proteome differs between young APOE3 and APOE4 targeted replacement mice in a sex-dependent manner

Front Aging Neurosci. 2024 Nov 20:16:1486762. doi: 10.3389/fnagi.2024.1486762. eCollection 2024.

Abstract

Introduction: Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for Alzheimer's disease (AD), yet it's unclear how this allele mediates risk. APOE4 carriers experience reduced mobility and faster decline in muscle strength, suggesting skeletal muscle involvement. Mitochondria are critical for muscle function and although we have reported defects in muscle mitochondrial respiration during early cognitive decline, APOE4-mediated effects on muscle mitochondria are unknown.

Methods: Here, we sought to determine the impact of APOE4 on skeletal muscle bioenergetics using young, male and female APOE3 (control) and APOE4 targeted replacement mice (n = 8 per genotype/sex combination). We examined the proteome, mitochondrial respiration, fiber size, and fiber-type distribution in skeletal muscle.

Results: We found that APOE4 alters mitochondrial pathway expression in young mouse muscle in a sex-dependent manner without affecting respiration and fiber size or composition relative to APOE3. In both sexes, the expression of mitochondrial pathways involved in electron transport, ATP synthesis, and heat production by uncoupling proteins and mitochondrial dysfunction significantly differed between APOE4 and APOE3 muscle. For pathways with predicted direction of activation, electron transport and oxidative phosphorylation were upregulated while mitochondrial dysfunction and sirtuin signaling were downregulated in female APOE4 vs. APOE3 muscle. In males, sulfur amino acid metabolism was upregulated in APOE4 vs. APOE3 muscle.

Discussion: This work highlights early involvement of skeletal muscle in a mouse model of APOE4-linked AD, which may contribute to AD pathogenesis or serve as a biomarker for brain health.

Keywords: APOE4; Alzheimer's disease; mice; mitochondria; proteomics; skeletal muscle.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the KU ADRC Brain Health Training Program P30 AG072973. Additional author support was provided through R01 AG056062 (JM), T32 AG078114 (CJ), and the University of Kansas Medical Center Biomedical Research Training Program (CJ). Proteomics at UAMS was supported by IDeA National Resource for Quantitative Proteomics and NIH/NIGMS Grant: R24GM137786. The IPA software used in this publication was supported by the Biostatistics and Informatics Shared Resource, funded by the National Cancer Institute Cancer Center Support Grant: P30 CA168524, and the Kansas IDeA Network of Biomedical Research Excellence Bioinformatics Core, supported in part by the National Institute of General Medical Science award: P20GM103418. In addition, respiration studies were supported by the Metabolism Core within the Kansas Center for Metabolism and Obesity Research, supported by a National Institute of General Medicine COBRE award: (P20GM144269). Equipment within the Metabolism Core was purchased with NIH S10OD028598.