Prospects of integrated multi-omics-driven biomarkers for efficient hair loss therapy from systems biology perspective

Yilmaz D. N., Aydogan O. O., Kori M., Aydin B., Rahman M. R., Moni M. A., ...Daha Fazla

GENE REPORTS, cilt.28, 2022 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.genrep.2022.101657
  • Dergi Adı: GENE REPORTS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, BIOSIS, EMBASE
  • Anahtar Kelimeler: Hair loss, alopecia, Systems biology, Omics signatures, Biomarkers, Drug repositioning, Therapy, Personalized medicine, GENOME-WIDE ASSOCIATION, MALE-PATTERN BALDNESS, ANDROGENETIC ALOPECIA, GENE-EXPRESSION, 1 MG, FINASTERIDE, MEN, AREATA, MECHANISMS, FOLLICLE
  • Marmara Üniversitesi Adresli: Evet

Özet

The term "alopecia" is used for abnormal hair loss and it is a chronic dermatological condition observed in both genders and all races. Androgenetic alopecia (AGA) or male pattern baldness is the most common type of alopecia; however, it may be observed in females. Alopecia areata (AA) is the second most common non-scarring alopecia or hair loss around the world. Beyond the fact that alopecia is a disease itself, sometimes it might be one of the major side effects of many drugs including chemotherapeutics. Since healthy hair has been a symbol of well-being, youth, and vitality for centuries, the treatment of alopecia has essential importance to increasing life quality of the individuals that have faced hair loss. Regarding the progressively generated high-throughput data at various omics levels, systems biology has gained importance to better understand biologic processes by utilizing high-throughput data from multiple sources to develop models of biologic processes In this review, we overviewed AGA and AA via systems biology with the aid of omics technologies point of view to highlight not only the molecular mechanisms of the hair loss phenomenon but also potential preventive and therapeutic avenues. We discussed the findings in light of the multi-omics data integration that converges the future of uncovering personalized therapeutic options targeting hair loss.