MITOCHONDRIAL DYSFUNCTION OXIDATIVE STRESS AND THE NAD/SIRTUIN AXIS IN ANDROGENETIC ALOPECIA: EMERGING MECHANISMS AND THERAPEUTIC IMPLICATIONS

Abstract

Androgenetic Alopecia (AGA) is a widespread type of progressive non-scarring hair loss that has always been theorized to be caused by the mediation of follicular miniaturization by androgens. Nevertheless, failure to respond fully to androgen-targeted therapies and age-related AGA development indicates that other processes are involved in disease pathogenesis. Considering this, new evidence shows that mitochondrial dysfunction, oxidative stress, and defective quality control in the cell can also contribute significantly to follicular degeneration. This review utilizes a recent development (2020-2026) and analyzes the interconnection between oxidative stress, mitophagy, and the nicotinamide adenine dinucleotide (NAD+)/sirtuin axis in AGA. The evidence of experimental research proves that dermal papilla cells of the affected scalp have reduced respiratory activity of mitochondria, enhanced reactive oxygen species, and changes in the expression of mitochondrial regulators. One of them is SIRT3, which is altered and can damage follicular function and regenerative capacity. The therapeutic approaches that mitigate mitochondrial homeostasis, such as mitochondria-targeted antioxidants and NAD + precursor and sirtuin-regulating agents, have shown positive outcomes in preclinical models. Nevertheless, direct records of a connection between canonical mitophagy pathways and AGA in the human tissue, as well as the causal role of NAD+ depletion and sirtuin dysregulation, are not fully demonstrated. Taken together, such results indicate that mitochondrial dysfunction could be an element of AGA pathophysiology, which has been under-recognized previously, and that could be a therapeutic option. A better study of mitochondrial control in human hair follicles can be used to inform the further development of mechanism-based therapies and to understand intra-clinical discrepancies in predicting response to existing therapies.