Autoantibodies in Long COVID patients affect cell proliferation rate and metabolic function of skeletal muscle cells

Abstract

Long COVID is a chronic disease affecting at least 65 million people worldwide. Patients suffer from a wide range of symptoms, such as cardiac impairment, neurological disorders, and muscle complaints. Recent evidence points to the potential role of autoantibodies in the pathophysiological process. However, the exact mechanism behind this remains unknown. In this study, we investigated the effect of a selection of autoantibodies found in Long COVID patients on skeletal muscle cells. The five antibodies whose antigen should be expressed in skeletal muscle cells, were selected based on the function of their corresponding antigen. As a model, we used C2C12, a mouse skeletal muscle cell line. We first performed localization experiments to verify whether the selected target antigens were expressed and bound by the antibodies in mice, using mouse skeletal muscle slices along with C2C12 cells. Then, we pooled the five selected antibodies to assess their effect on cell proliferation, utilizing xCELLigence, and on mitochondrial function. Moreover, we examined the effect of incubation with the antibody pool on the gene expression of transcriptional cofactor PGC1α, a master regulator of mitochondrial biogenesis. Firstly, our localization experiments confirmed the gene and protein expression of the antigens in vitro and in vivo. Secondly, we observed that cells incubated with the antibody pool demonstrated reduced proliferation, increased hyperpolarization of the mitochondrial membrane and an increased ROS production. Our results provide more clues as to what extent autoantibodies play a role in causing Long COVID, especially regarding the effect on skeletal muscle. In addition, this research proves C2C12 mice cells as a valid model system for exploration of the effects of a subset of autoantibodies found in long COVID. This broad study establishes a base for future research on the pathophysiology behind Long COVID.

Graphical abstract:

Students involved:

Safaa Alshalli (2954416), Liselotte Burger (0996866), Valke Hoekstra (2384232), Renate Keller (4395719), Demi Morauw (7084404), Koen Overbeek (6990304), Melisa Özcan (6392156), Jochem ten Pas (6435890), Marieke van Schaik (5199301), Daphne Zeedijk (2325926)