Evaluating hair growth promoting effects of candidate substance: A review of research methods. Issue 3 (March 2019)

• Record Type: Journal Article
• Authors: Ohn, Jungyoon; Kim, Kyu Han; Kwon, Ohsang
• Is Part Of: Journal of dermatological science. Volume 93:Issue 3(2019)
• Page Start: 144
• Page End: 149
• Publication Date: 2019-03
• Subjects: AGA androgenetic alopecia -- DP dermal papilla -- HF hair follicle -- HFSC hair follicle stem cell -- ORS outer root sheath; Androgenetic alopecia -- Animal model -- Dermal papilla cells -- Outer root sheath cells -- Hair follicle; Dermatology -- Periodicals; Skin Diseases -- Periodicals; Dermatologie -- Périodiques; 616.5005
• DOI: 10.1016/j.jdermsci.2019.02.004
• Languages: English
• ISSNs: 0923-1811

Abstract

Abstract: Androgenetic alopecia (AGA) is the most common form of hair loss disorder. As the prevalence of AGA rises, the demand for AGA treatments is rising accordingly, prompting research to identify therapeutic candidates to treat AGA. Because AGA is caused by crosstalk among multiple hair follicle (HF) cell components, understanding the effects of candidate molecules on HF cells is essential to determining therapeutic candidates for treatment. To date, research has centered on HF dermal papilla and outer root sheath cells and has indicated that the hair growth effects of candidate substances may be mediated via alterations in several signaling pathways and signature genes in these HF cells. In more integrative evaluations, the HF unit is used as an ex vivo organ culture model to verify the effects of therapeutic candidates. Animal models have also been used to evaluate the effects of candidate substances. The main outcomes used to evaluate the effects of candidate substances are 1) changes in HF growth rates in vitro, 2) anagen induction capabilities, and 3) the effects of androgen modulation. This article reviews a series of methods used to evaluate the hair growth-promoting effects of candidate substances, providing an overview of cell assays, organs, and animal models used in AGA research in order to facilitate AGA research moving forward.