As global aging populations increase, understanding the histological and physiological effects of aging becomes crucial, and finding ways to counter these effects is a growing need. Skin, being the largest and most exposed organ, provides valuable insights into broader aging processes, including those at a genetic level. Skin aging manifests through various phenotypes like wrinkling, pigmentation changes, and sagging, varying across individuals. While genome-wide association studies (GWAS) and candidate gene studies have explored genetic links to skin aging, they often focus on one or a few phenotypes. This review addresses this limitation by summarizing genetic factors associated with a wide range of skin aging phenotypes identified in published GWAS and candidate gene studies. By performing a meta-analysis, the review assesses the association of selected significant loci with skin aging and identifies patterns in these associations to illustrate potential biological pathways that contribute to various skin aging phenotypes, offering a more holistic view of the genetic factors involved in skin aging.
Methods
A comprehensive literature search was conducted using Embase, PubMed, and Web of Science to identify relevant studies. The search included terms like ‘skin aging,’ ‘skin ageing,’ ‘gene*,’ ‘SNP,’ ‘GWAS,’ and ‘genotype’. Eligible articles examined the association of SNPs with skin aging phenotypes in human subjects via non-invasive methods in observational studies. Data extraction included author, year of publication, sample size, ethnicity, skin aging phenotype details, SNP information, p-values, odds ratios (OR), and confidence intervals (CIs). Statistical analysis involved generating forest plots and calculating overall ORs and CIs using the metafor package in R software. Functional enrichment analysis was performed using g:Profiler to identify biological pathways and processes associated with the identified loci.
Key Points by Section
•Overview of Data Analysis from Literature Search:
◦The review included 48 eligible studies.
◦A total of 2408 SNPs and 3844 SNP-phenotype associations with skin aging phenotypes were consolidated. These SNPs were located in 410 non-intergenic and intergenic loci, termed skin aging loci.
•Overview of Meta-Analysis:
◦Meta-analyses confirmed that 30 loci were significantly associated with skin aging across multiple studies. Forest plots for these loci are available in the supplementary materials.
◦The meta-analysis included a range of skin aging phenotypes, such as wrinkling, solar elastosis, pigmented spots, and skin cancer.
•Loci Associated with Skin Color-Related Phenotypes:
◦AFG3L1P: Associated with skin color-related phenotypes; its linkage disequilibrium with MC1R, a key gene in pigmentation, may drive this association.
◦Intergenic region between ASIP and ENSG00000287853: Associated with inability to tan and freckles; reduced ASIP expression affects pigmentation signaling.
◦CPNE7: Associated with facial pigmented spots and inability to tan; plays a role in intracellular processes related to cytoskeleton organization.
◦DEF8: Associated with skin wrinkling and sagging (solar lentigines), skin cancer (cutaneous squamous cell carcinoma), and skin pigmentation.
◦IRF4: rs12203592 was found to be associated with skin ageing, with most linking the same SNP on the gene to pigmentation-related phenotypes such as perceived skin darkness, inability to tan, and pigmentation spots. Increased expression of IRF4 may lead to elevated expression of TYR, a key gene in melanin production.
◦SPG7: Associated with facial pigmented spots and perceived skin darkness; its role in controlling mitochondrial function suggests a connection to the regulation of pigmentation processes through the influence of melatonin on melanin production.
◦TYR: Encodes an enzyme critical for the conversion of tyrosine to melanin, which directly links it to pigmentation-related skin aging phenotypes.
•Loci Associated with Wrinkling- and Sagging-Related Phenotypes:
◦BCAR3: Linked to wrinkling and Favre-Racouchot syndrome; plays a critical role in cell signaling pathways related to cell proliferation, migration, and extracellular matrix assembly.
◦MYO16: Linked to wrinkling- and sagging-related phenotypes; encodes a motor protein involved in signaling pathways regulating cell cycle progression25. Interacts with the PI3-kinase (PI3K) regulatory subunit p85, linking it to the activation of the WASp-family verprolin homologous protein (WAVE) signalling pathway, which regulates actin polymerisation.
◦PRDM16: Associated with general wrinkling; encodes a transcription factor that plays a key role in the differentiation of brown adipose tissue and the regulation of transcription and signalling pathways.
◦RORA: Linked to sagging eyelids and Melomental Folds; encodes a nuclear receptor involved in the regulation of embryonic development, immune responses, circadian rhythm, and the metabolism of various compounds.
◦SPTLC1: Associated with general wrinkling; encodes an enzyme crucial for sphingolipid biosynthesis, which plays a vital role in various cellular processes.
•Loci Associated with Skin Cancer-Related Phenotypes:
◦Intergenic region between BNC2 and ENSG00000237153: Associated with skin cancer-related phenotypes; BNC2 encodes a zinc finger protein that functions as a transcription factor and plays a role in skin pigmentation.
◦CLPTM1L: Linked to basal cell carcinoma; shows strong linkage disequilibrium with TERT, a gene critical for telomere synthesis.
◦LPP: Associated with skin cancer-related phenotypes; encodes a protein that plays a dual role in cellular structure and signaling, contributing to cell adhesion, motility, and permeability.
•Functional Enrichment:
◦Functional enrichment analysis revealed four main categories: pigmentation, development, cytoplasm and cytoskeleton, and others.
◦Genes related to pigmentation are crucial in offering protection of the skin against UV damage by regulating melanin production and skin tone, reducing genetic damage and risks of cancer.
Conclusion
This review highlights the complex genetic landscape of skin aging, consolidating data from 48 GWAS and candidate gene studies. The novelty of this research lies in its holistic approach, which integrates a wide range of skin aging phenotypes and identifies key genetic loci and biological pathways involved. The findings underscore the importance of fundamental biological processes like development, cellular organization, and pigmentation in skin aging. Future research should focus on validating these associations across diverse populations and delving deeper into the specific mechanisms through which these genetic factors influence skin aging. By studying the same SNP across multiple populations, future work could strengthen the overall association between some of these loci and skin ageing. Further investigation into these underlying biological processes would significantly advance our understanding of the pathogenesis of skin ageing phenotypes. This knowledge can pave the way for targeted interventions and personalized strategies to mitigate the effects of skin aging.
