Modeling Oxidative Stress-Linked Telogen Effluvium Using Monte Carlo Simulation of Published Trichoscopy Norms and...

Area of Science:

• Dermatology and Trichology
• Computational Biology and Bioinformatics

Background:

• Increasing cannabis legalization correlates with rising exposure.
• The relationship between cannabis exposure and hair follicle biology, specifically diffuse shedding, is not well understood.

Purpose of the Study:

• To investigate the association between simulated cannabis exposure levels and markers of diffuse hair shedding.
• To utilize computational modeling to generate hypotheses regarding cannabis exposure and hair loss phenotypes.

Main Methods:

• A synthetic dataset of 140 subjects was generated using a Monte Carlo framework.
• Data were parameterized by published trichoscopic data, national cannabis exposure distributions, and quality-of-life instruments.
• Statistical analyses included Pearson correlations, linear regression, and ANCOVA with demographic covariates.

Main Results:

• Higher simulated cannabis exposure was linked to increased Self-Assessment of Hair Loss (SAHL) scores (r = 0.31, p < 0.01).
• Increased cannabis exposure was associated with reduced follicular density (r = -0.38, p < 0.05).
• These associations remained significant after covariate adjustment, with stronger effects in female-assigned profiles.

Conclusions:

• Modeled associations suggest potential links between cannabis exposure and hair shedding markers, warranting further investigation.
• This study demonstrates the utility of computational modeling in generating falsifiable hypotheses from existing data.
• Future clinical studies are needed to validate these findings with biological mediators and longitudinal data.