A Systematic Simulation-Based Meta-Analytical Framework for Prediction of Physiological Biomarkers in Alopecia

In 2019, a study used a systematic simulation-based meta-analytical framework to predict physiological biomarkers in alopecia. The researchers analyzed eight publicly available microarray datasets and identified 12 potential biomarkers, including three extracellular proteins. These biomarkers were associated with proteins involved in major physiological reactions including protein metabolism, signal transduction, and pathways that regulate hair growth and follicle differentiation. The study also explored the role of potential biomarkers in associated pathways, such as protein metabolism, signal transduction, Wnt, BMP, Eda, Notch, and Shh pathways, which are related to hair follicle differentiation, morphogenesis, and pigmentation. The study concluded that regular expression patterns of these genes could affect the synthesis of bio-molecules and dysregulation of these pathways could lead to abnormalities in hair growth. However, the study did not mention the number of participants involved.