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Updated: Jan 9, 2026

A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis
Published on: March 9, 2015
Association between SQSTM1 dysregulation and risk in alopecia areata: a Mendelian randomization study
Lifang Hu1, Sheng Wan1, Xiuzu Song1
1Department of Dermatology, Hangzhou Third People's Hospital, Hangzhou, China.
Background:
Alopecia areata (AA) is an autoimmune disease typified by nonscarring hair loss. It manifests as a heterogeneous disorder with diverse clinical presentations and variable treatment responses, underscoring the significance of identifying novel biomarkers for precision management.
Objective:
This study aims to explore the relationship between metabolic reprogramming-related genes (MRRGs) and the risk of developing AA.
Methods:
MRRGs were identified through the GeneCards database and existing literature. Genetic instruments were obtained from the eQTLGen database, and AA-related data were retrieved from the OpenGWAS database. The TwoSampleMR R package was applied for statistical analysis. Additionally, RT-qPCR and immunofluorescence assays were performed to validate the expression of target genes in AA-affected hair follicles and healthy controls.
Results:
Six MRRGs (DLD, NFE2L2, SDHB, SLC2A1, PSAT1, and SQSTM1) showed significant causal associations with AA. RT-qPCR analysis revealed markedly elevated SQSTM1 mRNA levels in AA-affected hair follicles compared with healthy controls. Immunofluorescence confirmed increased SQSTM1 protein accumulation alongside reduced LC3B-II expression in AA-affected hair follicles.
Conclusions:
This study underscores the significant association between SQSTM1 and AA, advancing our understanding of AA pathophysiology.
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