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Visual representation of the pleiotropic diversity of genes on the chromosomal band 16q24.3. Each gene shown in this figure is associated with morphologically distinct phenotypes from different phenotypic categories (e.g., Phenotype Category A, B, C, and D colour coded in yellow, blue, orange, and green respectively).
Source publication
Skin ageing is the result of intrinsic genetic and extrinsic lifestyle factors. However, there is no consensus on skin ageing phenotypes and ways to quantify them. In this systematic review, we first carefully identified 56 skin ageing phenotypes from multiple literature sources and sought the best photo-numeric grading scales to evaluate them. Nex...
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Background
Type 2 diabetes mellitus (DM2) and osteoporosis (OP) are currently the two most significant causes of mortality and morbidity in older adults, according to clinical evidence. The intrinsic link between them is yet unknown, despite reports of their coexistence. By utilizing the two-sample Mendelian randomization (MR) approach, we sought t...
Citations
... A recent study found that self-reported skin colour using a photonumeric scale is concordant with objective measurements [15]. Localised changes in skin pigmentation are one of the key hallmarks of ageing skin [17]. Furthermore, Chinese skin is known to become dyspigmented more easily with age [21]. ...
Background
Changes develop on the facial skin as a person ages. Other than chronological time, it has been discovered that gender, ethnicity, air pollution, smoking, nutrition, and sun exposure are notable risk factors that influence the development of skin ageing phenotypes such as wrinkles and photo-ageing. These risk factors can be quantified through epidemiological collection methods. We previously studied wrinkles and photo-ageing in detail using photo-numeric scales. The analysis was performed on the ethnic Chinese skin by three trained assessors. Recent studies have shown that it is possible to use self-reported data to identify skin-related changes including skin colour and skin cancer. In order to investigate the association between risk factors and skin ageing phenotypic outcomes in large-scale epidemiological studies, it would be useful to evaluate whether it is also possible for participants to self-report signs of ageing on their skin.
Aim
We have previously identified several validated photo-numeric scales for wrinkling and photo-ageing to use on ethnic Chinese skin. Using these scales, our trained assessors grade wrinkling and photo-ageing with moderately high inter-assessor concordance and agreement. The main objective of this study involves letting participants grade self-reported wrinkling and photo-ageing using these same scales. We aim to compare the concordance and agreement between signs of skin ageing by the participant and signs of ageing identified by our assessors.
Method
Three trained assessors studied facial photo-ageing on 1081 ethnic Chinese young adults from the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES) cohort. Self-reported facial photo-ageing data by the same 1081 participants were also collated and the two sets of data are compared.
Results
Here, we found that self-reported signs of photo-ageing are concordant with photo-ageing detected by our assessors. This finding is consistent whether photo-ageing is evaluated through studying wrinkle variations (Spearman’s rank correlation (ρ) value: 0.246–0.329) or through studying dyspigmentation patterns (Spearman’s rank correlation (ρ) value 0.203–0.278). When studying individual wrinkles, both participants and assessors often detect the presence of the same wrinkle (Spearman’s rank correlation (ρ) value 0.249–0.366). A weak-to-fair level of agreement between both participants and assessors (Cohen’s kappa (κ) values: 0.041–0.233) persists and is statistically significant after accounting for agreements due to chance. Both the participant and the assessor are largely consistent in evaluating the extent of photo-ageing (area under curve (AUC) values 0.689–0.769) and in discerning between the presence or absence of a given facial wrinkle (area under curve (AUC) values 0.601–0.856).
Conclusion
When we analyse the overall appearance of the face, our results show that signs of photo-ageing identified by the participant are concordant with signs of photo-ageing identified by our assessors. When we focused our analysis on specific areas of the face, we found that participants were more likely to identify and self-report the same wrinkles that our assessors have also detected. Here, we found that self-reported signs of skin ageing provide a satisfactory approximation to the signs of skin ageing identified by our assessors. The ability to use self-reported signs of skin ageing should also be evaluated on scales beyond the ones discussed in this study. Currently, there are not as many photo-numeric scales for quantifying dyspigmentation patterns as there are for quantifying wrinkle variations. As Chinese skin is known to become dyspigmented more easily with age, more photo-numeric scales need to be developed and properly validated.
Supplementary Information
The online version contains supplementary material available at 10.1186/s40101-024-00361-8.
... In our recent systematic review of skin ageing, 10 we found that the quantification of skin ageing phenotypes in the field can be broadly classified into two categories: quantification using a Written descriptive measurements can take the form of dichotomous questions (e.g., 'Have you ever been diagnosed with basal cell carcinoma? 2 ) or multiple-choice questions with increasing levels of severity (e.g., Does your face often become red at times (temperature differences, tension) other than alcohol consumption? Three choices are provided: 1. ...
Background
We evaluate skin sagging phenotypes (eyebags, droopy eyelids, low eyebrow positioning) using written descriptive scales and photo‐numeric scales. We also study how anti‐ageing interventions and digital screen time influence skin sagging.
Aim
We compare the two phenotype assessment methods with each other.
Method
Skin sagging and personal lifestyle data obtained from 2885 ethnic Chinese young adults from the Singapore/Malaysia cross‐sectional genetics epidemiology study (SMCGES) cohort were collated and compared.
Results
Significant correlations (p‐value < 0.001) between written descriptive scales and photo‐numeric scales were observed for eyebags (0.25) and eyebrow positioning (0.08). Significant correlations (p‐value < 0.001) were observed after combining both scales for eyebags (0.38), droopy eyelids (0.30), and eyebrow positioning (0.30). Anti‐ageing interventions are associated with delayed progression of eyebags from 18–45 years old, droopy eyelids from 31–45 years old, and eyebrow positioning from 35–40 years old. Significantly lower (p‐value < 0.02) eyebrow positioning is associated with both <1 and 1–3 h of screen time stratified by age.
Conclusion
Written descriptive scales provide comparable results to photo‐numeric scales. However, validating and adapting photo‐numeric scales for different populations identifies phenotypes better. Anti‐ageing interventions are beneficial at different age ranges. Screen time is associated with skin sagging in young (18–30 years old) participants.
... Remarkably, the region chr16q24.3 was identified to be associated with skin pigmentation and skin aging in a recent comprehensive meta-analysis of 44 GWAS and gene expression studies [36]. This region is also overrepresented in genes associated with protective genes ( p = 0.0002 ) [see Additional file 3: Table S3C]. ...
Facial aging is the most visible manifestation of aging. People desire to look younger than others of the same chronological age. Hence, perceived age is often used as a visible marker of aging, while biological age, often estimated by methylation markers, is used as an objective measure of age. Multiple epigenetics-based clocks have been developed for accurate estimation of general biological age and the age of specific organs, including the skin. However, it is not clear whether the epigenetic biomarkers (CpGs) used in these clocks are drivers of aging processes or consequences of aging. In this proof-of-concept study, we integrate data from GWAS on perceived facial aging and EWAS on CpGs measured in blood. By running EW Mendelian randomization, we identify hundreds of putative CpGs that are potentially causal to perceived facial aging with similar numbers of damaging markers that causally drive or accelerate facial aging and protective methylation markers that causally slow down or protect from aging. We further demonstrate that while candidate causal CpGs have little overlap with known epigenetics-based clocks, they affect genes or proteins with known functions in skin aging, such as skin pigmentation, elastin, and collagen levels. Overall, our results suggest that blood methylation markers reflect facial aging processes, and thus can be used to quantify skin aging and develop anti-aging solutions that target the root causes of aging.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13148-023-01590-x.
... The past century has witnessed significant advancements in genetic discoveries and the elucidation of molecular secrets, which have recently culminated in a transformative impact on the field of medicine, particularly in the realms of treatment advancements and personalized approaches [1,2]. Moreover, a comprehensive understanding of intrinsic and extrinsic factors impacting the body has played a crucial role in the interesting findings of genetic pleiotropy and clear mechanisms of skin aging, which is an inevitable process, and all attempts to search for individualized diagnostics and treatment procedures could give the best results [3]. When examining variations in biological and social age across different racial or ethnic groups, investigators found that the influence of intrinsic factors supported the concept of a personalized medicine approach to aging, without exceptions for skin aging [4]. ...
... Last decade, significant advancements in genome-wide association studies (GWASs) focusing on skin aging made considerable progress in analyzing various mechanisms and identifying the underlying reasons for skin aging [3,10,11]. Building upon these works, we conducted a collaborative cross-sectional research study to create the groundwork for personalized solutions and develop a reference skin. This test utilizes genetic and general laboratory data to predict individual susceptibility to weak skin characteristics, leveraging the research on genetic polymorphisms related to skin functional properties. ...
... Recently performed genome-wide association studies (GWASs) and other original research works laid the groundwork for a personalized approach to healthcare, where a niche for more effective skincare approaches certainly exists [20][21][22]. In the literature, there are different types of investigations with different objectives, where some of them are orientated to a thorough pathophysiological and genetical analysis [3,22], while others are focused on a more practical approach, trying to find the best way to utilize scientific findings for clinical use [6,10,11]. Our work stands out from both categories by combining routine laboratory investigations with molecular genotyping results offering regular blood tests that would depend on individual skinassociated genotypes. ...
We conducted a research study to create the groundwork for personalized solutions within a skin aging segment. This test utilizes genetic and general laboratory data to predict individual susceptibility to weak skin characteristics, leveraging the research on genetic polymorphisms related to skin functional properties. A cross-sectional study was conducted in a collaboration between the Private Clinic Medicina Practica Laboratory (Vilnius, Lithuania) and the Public Institution Lithuanian University of Health Sciences (Kaunas, Lithuania). A total of 370 participants agreed to participate in the project. The median age of the respondents was 40, with a range of 19 to 74 years. After the literature search, we selected 15 polymorphisms of the genes related to skin aging, which were subsequently categorized in terms of different skin functions: SOD2 (rs4880), GPX1 (rs1050450), NQO1 (rs1800566), CAT (rs1001179), TYR (rs1126809), SLC45A2 (rs26722), SLC45A2 (rs16891982), MMP1 (rs1799750), ELN (rs7787362), COL1A1 (rs1800012), AHR (rs2066853), IL6 (rs1800795), IL1Beta (rs1143634), TNF-α (rs1800629), and AQP3 (rs17553719). RT genotyping, blood count, and immunochemistry results were analyzed using statistical methods. The obtained results show significant associations between genotyping models and routine blood screens. These findings demonstrate the personalized medicine approach for the aging segment and further add to the growing literature. Further investigation is warranted to fully understand the complex interplay between genetic factors, environmental influences, and skin aging.
... The past century has witnessed significant advancements in genetic discoveries and elucidation of molecular secrets, which have recently culminated in a transformative impact on the field of medicine, particularly in the realms of treatment advancements and personalized approaches [1,2]. Moreover, the comprehensive understanding of intrinsic and extrinsic factors impacting the body played the crucial role for interesting findings of genetic pleiotropy and clear mechanisms of skin aging, which is an inevitable process, and all attempts to search for individualised diagnostics and treatment procedures could give the best results [3]. When examining variations in biological and social age across different racial or ethnic groups, investigators found that the influence of intrinsic factors supported the concept of a personalized medicine approach to aging, without exceptions for skin aging [4]. 2 Considering the current trends toward longevity and the prioritization of a precision medicine approach, research studies are ongoing on a very wide spectrum of medicine topics, such as genomic correlation with cardiovascular and neurogenerative disease [5], as well as various prediction models in cancer or rare disease treatment [6]. ...
... Last decade, significant advancements in Genome wide association studies (GWAS) focusing on skin aging made considerable progress in analysing various mechanisms and identifying the underlying reasons for skin aging [3,10,11]. Building upon these works, we conducted a collaborative cross-sectional research study to create groundwork for personalized solutions and developing a reference skin. This test utilises genetic and general laboratory data to predict individual susceptibility of weak skin characteristics, leveraging on the research on genetic polymorphisms related to skin functional properties. ...
... This is the first stage of the study to obtain initial results to explore further research with extended team of investigators. 3 ...
We conducted a research study to create groundwork for personalized solutions within skin aging segment. This test utilises genetic and general laboratory data to predict individual susceptibility of weak skin characteristics, leveraging on the research on genetic polymorphisms related to skin functional properties. A cross-sectional study was conducted in collaboration between the Private Clinic Medicina Practica Laboratory (Vilnius, Lithuania) and the Public Institution Lithuanian University of Health Sciences (Kaunas, Lithuania). 370 participants agreed to participate in the project. The median age of respondents was 40, with a range of 19 to 74 years. After the literature search, we selected 15 polymorphisms of the genes related to skin aging subsequently distributed for different skin functions: SOD2(rs4880), GPX1(rs1050450), NQO1(rs1800566), CAT (rs1001179), TYR (rs1126809), SLC45A2 (rs26722), SLC45A2 (rs16891982), MMP1(rs1799750), ELN (rs7787362), COL1A1(rs1800012), AHR (rs2066853), IL6 (rs1800795), IL1Beta (rs1143634), TNF-α (rs1800629), AQP3(rs17553719). RT genotyping, blood count and immunochemistry results have been analysed using statistical methods. Obtained results showed significant associations among genotyping models and routine blood screens. These findings demonstrate the personalized medicine approach for aging segment and further add onto the growing field of literature. Further investigation is warranted to fully understand the complex interplay between genetic factors, environmental influences, and skin aging.
... Remarkably, the region chr16q24.3 was identified to be associated with skin pigmentation and skin aging in a recent comprehensive meta-analysis of 44 GWAS and gene expression studies [33]. This region is also over-represented in genes associated with protective genes (p = 0.0002) [ Table S3]. ...
Facial aging is the most visible manifestation of aging. People desire to look younger than others of the same chronological age. Hence, perceived age is often used as a visible marker of aging, while biological age, often estimated by methylation markers, is used as an objective measure of age. Multiple epigenetics-based clocks have been developed for accurate estimation of general biological age and the age of specific organs, including the skin. However, it is not clear whether the epigenetic biomarkers (CpGs) used in these clocks are drivers of aging processes or consequences of aging.
In this proof-of-concept study, we integrate data from GWAS on perceived facial aging, and EWAS on CpGs measured in blood. By running EW Mendelian randomization, we identify hundreds of putative CpGs that are potentially causal to perceived facial aging with similar numbers of damaging markers that causally drive or accelerate facial aging and protective methylation markers that causally slow down or protect from aging. We further demonstrate that while candidate causal CpGs have little overlap with known epigenetics-based clocks, they affect genes or proteins with known functions in skin aging such as skin pigmentation, elastin, and collagen levels. Overall, our results suggest that blood methylation markers reflect facial aging processes, and thus can be used to quantify skin aging and develop anti-aging solutions that target the root causes of aging.
... Skin aging compared to other organs is a complex process influenced by two main factors: intrinsic, or genetic; and extrinsic, or environmental [1,2] . Since skin aging suffers from both genetic and environmental influences, the study of these variables is extremely important for precision medicine, in which treatments can be customized according to individual needs [3,4] . ...
... Additionally, Ng & Chew (2022) [3] performed a systematic review of 44 GWAS studies on skin aging and identified 19 ...
O envelhecimento da pele é um processo natural, causado tanto por fatores intrínsecos ou genéticos, como por fatores extrínsecos. Mundialmente, a demanda por produtos que previnam o aparecimento das características de envelhecimento da pele, tem aumentado acentuadamente. Contudo, é fundamental entender a etiologia do envelhecimento para o desenvolvimento de tratamentos cada vez mais personalizados. O objetivo dessa revisão é discutir como o conhecimento sobre o envelhecimento biológico, os polimorfismos genéticos e as vias metabólicas celulares, podem contribuir na formulação de cosméticos personalizados com ação antienvelhecimento. Estudos em diferentes populações mundiais estão procurando associar polimorfismos de nucleotídeo único (SNPs) com envelhecimento. Pesquisas de SNPs usando a ferramenta de Genome-Wide Association Study (GWAS) mostram resultados heterogêneos, o que dificulta a validação desses biomarcadores. Para superar essas dificuldades, estudos recentes usando a ferramenta Gene Set Enrichment Analysis (GSEA) têm tentado associar modelos biológicos com parâmetros de envelhecimento, o que pode fornecer um conhecimento biológico mais integrado e abrangente. Apesar dos esforços, os marcadores moleculares, com foco dermatológico, ainda não foram validados, sendo necessários estudos em larga escala. Contudo, essas tentativas de avaliação abrangentes dos aspectos genéticos relacionados ao envelhecimento cutâneo em diferentes populações estão permitindo que o setor de cosméticos esteja cada vez mais próximo da ciência, o que beneficia tanto os consumidores quanto as empresas do setor.
Background
Photo‐ageing is a form of skin ageing which affects the entire face. A photo‐aged skin has a diverse variety of wrinkles and dyspigmentation all over the face. Here, we discuss photo‐ageing on the Chinese skin evaluated using a photo‐numeric scale developed and validated on Caucasian skin (i.e., Caucasian scale) and evaluated using a photo‐numeric scale developed and validated on Korean skin (i.e., Korean scale). The Korean scale can be subdivided into two scales that separately address the wrinkling and dyspigmentation constituents of photo‐ageing.
Aim
As there are currently no photo‐ageing scales for Chinese skin, the main objective of this study is to adapt existing photo‐ageing photo‐numeric scales for use on ethnic Chinese skin.
Method
Three trained assessors studied facial photo‐ageing on 1,081 ethnic Chinese young adults from the Singapore/Malaysia Cross‐sectional Genetics Epidemiology Study (SMCGES) cohort.
Results
All assessors are highly internally consistent (Weighted Kappa (κw) values≥0.952). We found that the Caucasian scale and Korean scale give nearly synonymous results for the wrinkling constituent of photo‐ageing (R² = 0.9386). The two scales are strongly concordant (Spearman's Rank Correlation (ρ) value: 0.62 ± 0.06, p = 1.31×10⁻⁸⁴). A weak‐to‐moderate inter‐scalar level of agreement (Cohen's Kappa (κ) values: 0.38 ± 0.05, p = 8.87×10⁻⁵³) persists and is statistically significant after accounting for agreements due to chance. When tested on ethnic Chinese skin, both scales detect photo‐ageing consistently (Area under curve [AUC] values: 0.76‐0.84). Additionally, the Korean scale for the dyspigmentation constituent of photo‐ageing is concordant with both the Caucasian scale (R² = 0.7888) and the Korean scale for the wrinkling constituent of photo‐ageing (R² = 0.7734).
Conclusion
Our results show that the Caucasian scale is suitable for capturing photo‐ageing on Chinese skin, especially wrinkle variations. The Korean dyspigmentation scale supplements the Caucasian scale to capture dyspigmentation patterns on Chinese skin that may be absent on Caucasian skin. Currently, photo‐ageing scales for Chinese skin are absent. When developed, these photo‐ageing scales must be properly validated for their ability to capture photo‐ageing of the entire face.
