Systems pharmacology identifies dermal papilla–specific transcriptomic reversal of androgenetic alopecia by lithium–zinc pathway convergence [Unfinished working draft]

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Authors: Ursachi Andrei
Cited by: 0

Abstract

UNFINISHED WORKING DRAFT — Author status notice, 26 October 2026 This manuscript is an unfinished, exploratory working draft. Its analyses and interpretations remain subject to source verification, reproducibility checks and substantive revision. Claims of validation, universality or mechanism in the original manuscript should be treated as provisional rather than established conclusions. Outstanding work: The reported combination is a computational sum of single-agent signatures, and clioquinol is used as a proxy for zinc. Source data, numerical summaries and matched combination controls require reconciliation. This draft does not establish clinical efficacy, treatment safety or an observed lithium-zinc combination effect. The original deposited file is retained for provenance. This notice updates the record status; it does not certify completion of a new analysis. Original description (historical; subject to the notice above) The lithium–zinc combination showed statistically significant transcriptomic rescue across all three datasets (GSE90594 z = 3.43, p = 0.0095; GSE36169 z = 3.99, p = 0.017; GSE66663 z = 9.79, p < 0.001). Z-scores reflect standardized displacement from permutation-derived null distributions; p-values are empirical permutation p-values rather than parametric Gaussian tail probabilities. Random-compound benchmarking placed lithium–zinc at the 99.5th percentile in the DP-specific dataset (empirical p = 0.010). Cross-dataset meta-analysis of permutation z-scores confirmed consistency (I² = 0%, Stouffer Z = 9.93, Fisher p < 10⁻⁵). The signal was strongest in the DP-enriched model (z = 9.79), consistent with the biological hypothesis that rescue targets DP-specific pathways. Leave-10%-out and bootstrap analyses confirmed a distributed, non-fragile rescue signal.

Fields of Study & Subjects

Hair Growth and Disorders Computational Drug Discovery Methods Prostate Cancer Treatment and Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 March 2026
Language
EN
Document type
Preprint