Precision therapeutics in non-scarring alopecia: a systemic genomic and pathway-based framework for targeted interventions

非瘢痕性脱发的精准治疗:基于系统基因组学和通路分析的靶向干预框架

阅读:1

Abstract

BACKGROUND AND PURPOSE: Non-scarring alopecia, principally androgenetic alopecia and alopecia areata is highly prevalent and psychologically burdensome; androgenetic alopecia is androgen-driven, whereas alopecia areata is autoimmune. This review synthesizes genetic architecture and pathway biology to outline a precision framework for targeted interventions. EXPERIMENTAL APPROACH: We reviewed full-text studies from the past decade across PubMed, Web of Science and Google Scholar, applying explicit inclusion/exclusion criteria; emphasis was placed on Genome wide association studies and Next generation sequencing findings, immune and androgen-axis biology, environmental modifiers, and therapeutic evidence (conventional, targeted, and regenerative), alongside artificial Intelligence-enabled diagnostics. KEY RESULTS: Androgenetic alopecia risk converges on androgen-receptor signalling and related loci, with perifollicular inflammation and oxidative stress as modifiers; finasteride remains a cornerstone therapy. Alopecia areata reflects polygenic immune dysregulation (e.g. Human leukocyte antigen/cytokine axes) with Janus Kinase-pathway inhibition yielding robust regrowth; across phenotypes, wingless-related integration sit/β-catenin and stem-cell programs are central targets. Regenerative options (Protein Rich Plasma, stem-cell/exosome approaches) and artificial Intelligence-assisted stratification are emerging adjuncts. CONCLUSION: A pathway-guided, genotype and phenotype-informed strategy, targeting the androgen axis for androgenetic alopecia, immune circuits for alopecia areata, and adding regenerative or microenvironmental therapies where indicated-promises earlier diagnosis and more durable, individualized outcomes, especially as genome-wide association study/next-generation sequencing and artificial Intelligence tools are integrated into care.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。