Back

Loss of endogenous estrogen alters mitochondrial metabolism and muscle clock-related protein Rbm20 in female mdx mice

Timpani, C. A.; Debrincat, D.; Kourakis, S.; Boyer, R.; Formosa, L. E.; Steele, J. R.; Zhang, H.; Schittenhelm, R. B.; Russell, A. P.; Rybalka, E.; Lindsay, A.

2024-02-12 pathology
10.1101/2024.02.08.579567 bioRxiv
Show abstract

Female carriers of a Duchenne muscular dystrophy (DMD) gene mutation manifest exercise intolerance and metabolic anomalies that may be exacerbated following menopause due to the loss of estrogen, a known regulator of skeletal muscle function and metabolism. Here, we studied the impact of estrogen depletion (via ovariectomy) on exercise tolerance and muscle mitochondrial metabolism in female mdx mice and the potential of estrogen replacement therapy (using estradiol) to protect against functional and metabolic perturbations. We also investigated the effect of estrogen depletion, and replacement, on the skeletal muscle proteome through an untargeted proteomic approach with TMT-labelling. Our study confirms that loss of estrogen in female mdx mice reduces exercise capacity, tricarboxylic acid cycle intermediates and citrate synthase activity but that these deficits can be offset through estrogen replacement therapy. Furthermore, ovariectomy downregulated protein expression of RNA binding motif factor 20 (Rbm20), a critical regulator of sarcomeric and muscle homeostasis gene splicing, which impacted pathways involving ribosomal and mitochondrial translation. Estrogen replacement modulated Rbm20 protein expression and promoted metabolic processes and the upregulation of proteins involved in mitochondrial dynamics and metabolism. Our data suggests that estrogen mitigates dystrophinopathic features in female mdx mice and that estrogen replacement may be a potential therapy for post-menopausal DMD carriers.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.