Biological insights from self-perceived facial aging data of the UKBB participants

Abstract

Genetic underpinnings of facial aging are still largely unknown. In this study, we leverage the statistical power of large-scale data from the UK Biobank and perform insilico analysis of genome-wide self-perceived facial aging. Functional analysis reveals significant over-representation of skin pigmentation and immune related pathways that are correlated with facial aging. For males, hair loss is one of the top categories that is highly significantly over-represented in the genetics data associated with self-reported facial aging. Our analysis confirms that genes coding for the extracellular matrix play important roles in aging. Overall, our results provide evidence that while somewhat biased, large-scale self-reported data on aging can be utilized for extracting useful insights into underlying biology, provide candidate skin aging biomarkers, and advance anti-aging skincare. 856 female twins [32]. Gene overlap between data sets is shown in bold font. Xu et al [18]Glass et al [32] UKBB facial aging CILP, CRISPLD2,

Epigenetics Insights from Perceived Facial Aging

“…The NEK6 subnetwork helps govern the initiation of mitosis and progression through the cell cycle and prevents cell senescence. Functional analysis of genes associated with self-perceived facial age revealed a significant over-representation of skin pigmentation, extracellular matrix, and immune-related pathways that are correlated with facial aging [17].…”