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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.

Background and objective Sleep disruption has been shown to affect immune function and thus influence allergic disease manifestation. The specific effects of sleep on allergic diseases, however, are less well-established; hence, in a unique population of young Chinese adults, we investigated the association between sleep and allergic disease. Methods Young Chinese adults recruited from Singapore in the Singapore/Malaysia Cross-Sectional Genetic Epidemiology Study (SMCGES) were analyzed. We used the International Study of Asthma and Allergies in Childhood (ISAAC) protocol and a skin prick test to determine atopic dermatitis (AD), allergic rhinitis (AR), and asthma status. Information regarding total sleep time (TST) and sleep quality (SQ) was also obtained. Results Of 1558 participants with a mean age of 25.0 years (SD = 7.6), 61.4% were female, and the mean total sleep time (TST) was 6.8 h (SD = 1.1). The proportions of AD, AR, and asthma were 24.5% (393/1542), 36.4% (987/1551), and 14.7% (227/1547), respectively. 59.8% (235/393) of AD cases suffered from AD-related sleep disturbances, 37.1% (209/564) of AR cases suffered from AR-related sleep disturbances, and 25.1% (57/227) of asthma cases suffered from asthma-related sleep disturbances. Only asthma cases showed a significantly lower mean TST than those without asthma ( p  = 0.015). Longer TST was significantly associated with lower odds of AR (OR = 0.905, 95% CI = 0.820–0.999) and asthma (OR = 0.852, 95% CI = 0.746–0.972). Linear regression analyses showed that lower TST was significantly associated with asthma ( β  =  − 0.18, SE = 0.076, p -value = 0.017), and AR when adjusted for AR-related sleep disturbances ( β  =  − 0.157, SE = 0.065, p -value = 0.016). Only sleep disturbances due to AR were significantly associated with a poorer SQ (OR = 1.962, 95% CI = 1.245–3.089). Conclusions We found that sleep quality, but not sleep duration was significantly poorer among AD cases, although the exact direction of influence could not be determined. In consideration of the literature coupled with our findings, we posit that TST influences allergic rhinitis rather than vice versa. Finally, the association between TST and asthma is likely mediated by asthma-related sleep disturbances, since mean TST was significantly lower among those with nighttime asthma symptoms. Future studies could consider using objective sleep measurements coupled with differential expression analysis to investigate the pathophysiology of sleep and allergic diseases.

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. Next, we conducted a systematic review on all 44 Genome-wide Association Studies (GWAS) on skin ageing published to date and identified genetic risk factors (2349 SNPs and 366 genes) associated with skin ageing. We identified 19 promising SNPs found to be significantly (p-Value < 1E−05) associated with skin ageing phenotypes in two or more independent studies. Here we show, using enrichment analyses strategies and gene expression data, that (1) pleiotropy is a recurring theme among skin ageing genes, (2) SNPs associated with skin ageing phenotypes are mostly located in a small handful of 44 pleiotropic and hub genes (mostly on the chromosome band 16q24.3) and 32 skin colour genes. Since numerous genes on the chromosome band 16q24.3 and skin colour genes show pleiotropy, we propose that (1) genes traditionally identified to contribute to skin colour have more than just skin pigmentation roles, and (2) further progress towards understand the development of skin pigmentation requires understanding the contributions of genes on the chromosomal band 16q24.3. We anticipate our systematic review to serve as a hub to locate primary literature sources pertaining to the genetics of skin ageing and to be a starting point for more sophisticated work examining pleiotropic genes, hub genes, and skin ageing phenotypes.

Skin ageing results in wrinkling. In this study, we discuss four types of facial wrinkles: Crow’s Feet wrinkles, forehead wrinkles, glabellar frown wrinkles, and nasolabial folds. These four phenotypes can be assessed either with a photo-numeric scale developed and validated on Caucasian skin (i.e., Caucasian scale) or with a photo-numeric scale developed and validated on Chinese skin (i.e., Chinese scale). As Caucasian and Chinese skin have inherent differences, the main objective of this study is to determine whether these inherent differences affect the suitability of evaluating facial wrinkles on ethnic Chinese skin with a Caucasian scale. Three trained assessors studied four types of wrinkles on the faces of 1,081 ethnic Chinese young adults from the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES). We found that Caucasian scales and Chinese scales are concordant (Spearman’s Rank Correlation (ρ) values: 0.53–0.80) and the level of agreement between the Caucasian scales and Chinese scales is moderately high (Cohen’s Kappa (κ) values: 0.40–0.49). When tested on ethnic Chinese skin, both the Caucasian scale and the Chinese scale are largely consistent in showing presence or absence of a given facial wrinkle (Area under curve (AUC) values: 0.79–0.90). All assessors are highly internally consistent (Weighted Kappa (κ w ) values: 0.686–0.992). Our results build confidence that four types of facial wrinkles on ethnic Chinese faces can be assessed with Caucasian scales. To the best of our knowledge, Chinese scales for facial wrinkles beyond the four types discussed here have yet to be developed. Caucasian scales for these other facial wrinkles will also need to be tested for their suitability to be used on ethnic Chinese skin as and when more Chinese scales are developed.

Background Nutrition is a modifiable factor in skin ageing, but its effects remain inconsistently quantified. This meta-analysis assessed human studies from the Web of Science on dietary intake and skin ageing, using pooled standardised mean differences (pSMD). Interventions included carotenoids, collagen, lipids and fatty acids, polyphenols, prebiotics and probiotics, and vitamins. We included full-text English articles and excluded non-human, disease-focused, topical or in vitro studies. Publication bias was assessed using Egger’s test and funnel plots. Results are shown as forest plots. Main body Sixty-one studies were meta-analysed. Collagen reduces wrinkles (pSMD = − 0.94 [− 1.39, − 0.49], p  = 4.82 × 10 −5 ). Lipids and fatty acids (pSMD = − 0.62 [− 0.92, − 0.31], p  = 7.89 × 10 −5 ) and polyphenols (pSMD = − 0.48 [− 0.74, − 0.21], p  = 3.96 × 10 −4 ) also reduce wrinkles without significant publication bias. Several interventions improve skin hydration, including collagen (pSMD = 0.66 [0.29, 1.04], p  = 5.99 × 10 −4 ), lipids and fatty acids (pSMD = 0.54 [0.28, 0.80], p  = 4.36 × 10 −5 ), polyphenols (pSMD = 0.59 [0.37, 0.80], p  = 6.43 × 10 −8 ), and prebiotics and probiotics (pSMD = 0.71 [0.25, 1.16], p  = 2.64 × 10 −3 ). Specific interventions target distinct ageing phenotypes. Carotenoids most effectively reduce redness (pSMD = − 0.53 [− 1.02, − 0.04], p  = 3.39 × 10 −2 ), and collagen reduces pigment spots (pSMD = − 0.16 [− 0.31, − 0.003], p  = 4.56 × 10 −2 ). Lipids and fatty acids improve elasticity (pSMD = 0.49 [0.14, 0.83], p  = 5.45 × 10 −3 ), while polyphenols strengthen barrier integrity (trans-epidermal water loss pSMD = − 0.50 [− 0.79, − 0.22], p  = 6.39 × 10 −4 ). Conclusion Dietary components target specific skin ageing phenotypes. Carotenoids, collagen, lipids and fatty acids, and polyphenols are particularly effective for redness, pigment spots, elasticity, and barrier integrity, respectively. Lipids, fatty acids, and polyphenols show broad benefits across multiple phenotypes. Shared mechanisms may contribute to overlapping effects. Evidence gaps remain, especially regarding carotenoids and vitamins. Future studies could explore combinatorial dietary interventions. This research is primarily supported by a Singapore National Medical Research Council grant.

Background Skin ageing is influenced by genetics, chronological age, and Sun exposure. Nasolabial folds are wrinkles prevalent among young ethnic Chinese participants in the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES). Methods We analysed data from 4421 SMCGES ethnic Chinese young adults. Collected data included demographics, Sun exposure, Fitzpatrick Skin Type, and nasolabial fold presence, assessed using validated questionnaires and photo-numeric scales. Genetic data were obtained through SNP genotyping, imputation, and whole transcriptome sequencing. Buccal cell samples from 2776 participants across three sites (National University of Singapore [NUS], University of Tunku Abdul Rahman [UTAR], and Sunway University [SU]) were used for SNP genotyping, and peripheral blood mononuclear cell samples from 658 participants at NUS and UTAR for sequencing. Analyses were performed using HaploView, RStudio, and PLINK, integrating data from the Genotype-Tissue Expression (GTEx) portal, eQTLGen consortium, and NCBI Gene Expression Omnibus. Results Our GWAS identified SAMD5 as associated with nasolabial folds among individuals with regular Sun exposure. SAMD5 SNPs might modulate binding of microRNAs hsa-miR-216a and hsa-miR-485-5p, suppressing SAMD5 expression and promoting nasolabial folds. rs844607 increased odds of nasolabial folds (AOR = 2.67 [1.89–3.77], p  = 2.27 × 10 −8 ) and forms a risk haplotype with 3′-end SNPs predicted as miRNA binding sites. The likely causal SNP, rs702344, strengthens miRNA binding (hsa-miR-216a: score 151, ΔG = − 19.64 kcal/mol; hsa-miR-485-5p: score 157, ΔG = − 22.36 kcal/mol), suppressing SAMD5 expression. eQTL data from GTEx (NES = − 0.72, p  = 2.79 × 10 −52 ) and eQTLGen ( Z  = 6.16, p  = 6.59 × 10 −6 ) supported this model. Lower SAMD5 expression was observed among chronologically aged individuals (GEO GSE200002, logFC = − 0.639, adj. p  = 7.57 × 10 −3 ) and in untreated photo-aged dermal fibroblasts relative to retinoid-treated ones (GEO GSE294121, adj. p  = 3.00 × 10 −2 ). SAMD5 promotes melanogenesis and UV protection; t-allele carriers showed 1.6-fold higher odds of melanin-poor burning skin types (95% CI 1.11–2.28; p  = 0.012). Regular Sun exposure increased odds of nasolabial folds 1.26-fold (95% CI 1.08–1.46; p  = 0.0028), whereas melanin-rich tanning skin types reduced the odds (AOR = 0.68; 95% CI 0.47–0.98; p  = 0.048). Conclusion These findings support a model where rs702344 enhances miRNA binding, downregulates SAMD5 , reduces melanogenesis, and promotes nasolabial folds in Sun-exposed young adults.

Background Skin ageing is influenced by complex genetic factors. Various phenotypes such as wrinkling, pigmentation changes, and skin cancers have been linked to specific genetic loci. However, the underlying genetic mechanisms and pathways remain poorly understood. This systematic review and meta-analysis aims to summarise the genetic loci found to be associated with skin ageing phenotypes by published genome-wide association studies (GWAS) and candidate gene studies. We also evaluated the overall association of loci via meta-analysis and identified the association patterns to explore potential biological pathways contributing to skin ageing. The Web of Science, Embase, and PubMed databases were searched on January 2024 using specific exclusion criteria (e.g., study of non-human subjects, focus on skin diseases, or treatments) to identify relevant articles. There did not appear to be any significant publication bias observed across the all phenotypes. Main body A total of 48 studies were included, revealing 30 loci that were confirmed to be associated with skin ageing by multiple studies (e.g., AFG3L1P : odds ratio 1.133 95% confidence interval [1.044, 1.222]; BPIFA3 : 1.859 [1.567, 2.151]; CLPTML1 : 1.164 [1.0.99, 1.229]; CPNE7 : 0.905 [0.852–0.958]; DEF8 : 1.186 [1.042, 1.331]; IRF4 : 1.260 [1.025, 1.495]; MYO16 : 2.303 [1.697, 2.908]; PRDM16 : 1.105 [1.084, 1.127]; RORA : 1.391 [1.206, 1.577]; SPG7 : 0.922 [0.897, 0.947]; SPON1 : 2.214 [1.204, 3.225]; SPTLC1 : 1.464 [1.432, 1.495]; TYR : 1.175 [1.007, 1.343]). The lack of significance for many loci may be due to studies analysing different SNPs within the same locus, weakening the overall associations. Several loci were associated with specific phenotypic categories (e.g., skin colour related, skin cancer related, wrinkling and sagging related), suggesting shared biological pathways are involved in the pathogenesis of different skin ageing phenotypes. This pattern was also observed in several of the loci that do not have a significant overall association with skin ageing. Conclusion Despite significant heterogeneity among the included studies and the use of subjective visual methods for phenotype assessment, our review highlights the critical role of fundamental biological processes, such as development and cellular organisation, in skin ageing. Future research that targets the same SNP across multiple populations could strengthen the association of additional loci with skin ageing. Further investigation into these underlying biological processes would significantly advance our understanding of the pathogenesis of skin ageing phenotypes.

Background Skin ageing takes on many different forms. Despite this diversity in skin ageing phenotypes, literature published to date is limited in scope, as many research studies either focus on one single phenotype or just a few specific phenotypes. Presently, phenotypes such as wrinkles, pigment spots, and photo-ageing are receiving most of the research attention. We therefore wonder whether the current discourse on skin ageing places a disproportionate amount of focus on a few selected phenotypes, leaving other skin ageing phenotypes underexplored. Methods In this cross-sectional study, we performed a broad assessment of forty-one signs of skin ageing and characterised the phenotypes that constituted key components of skin ageing. We also explored the interrelationship among forty-one skin ageing phenotypes using Spearman’s Correlation and Principal Component Analysis. Results We analysed our study population, which is composed of 3281 ethnic Chinese participants from the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES). The first ten principal components cumulatively explain 46.88% of the variance of skin ageing phenotypes in our study population. We discovered that the commonly discussed forms of skin ageing (i.e., wrinkles, pigmentation, and photo-ageing) only accounted for a small portion (24.39%) of the variance of all skin ageing phenotypes in our study population. Telangiectasia, a poor lip fullness, a lighter skin colour, xerosis, ephelides (freckles), ptosis of eyelids (droopy eyelids), eyebags, and a low eyebrow positioning were other key components of skin ageing, accounting for a further 22.49% of the variance of skin ageing phenotypes in our study population. We found that each of these ten skin ageing phenotypes characterises a key and important aspect of skin ageing. In this broad assessment of skin ageing, we first described the prevalence of forty-one signs of skin ageing and then characterised in detail both the prevalence and severity distribution of ten key skin ageing phenotypes. Conclusions We presented clear evidence that skin ageing is much more than just wrinkles, pigmentation and photo-ageing. The addition of telangiectasia, poor lip fullness, a lighter skin colour, xerosis, ephelides, ptosis of eyelids, eyebags, and a low eyebrow positioning added more dimensions to skin ageing phenotype presentations.

ObjectivesQuality improvement (QI) is critical in facilitating advancements in patient outcomes, system efficiency and professional growth. This paper aimed to elucidate the underlying rationale and framework guiding JurongHealth Campus (JHC), a nascent Regional Health System, in developing its QI capacity and capability at all levels of the organisation.MethodsAn exhaustive analysis of high-performance management systems and effective improvement frameworks was conducted, and the principles were customised to suit the local context.A three-phased approach was applied: (1) developing the JHC QI framework; (2) building capacity through a dosing approach and (3) building capability through QI projects and initiatives using the model for improvement (MFI). Three components of the RE-AIM implementation strategy were assessed: (1) Reach—overall percentage of staff trained; (2) Effectiveness—outcomes from organisation-wide improvement projects and (3) Adoption—number of QI projects collated and presented.ResultsThe percentage of staff trained in QI increased from 11.3% to 22.0% between January 2020 and March 2024, with over 350 projects documented in the central repository. The effectiveness of the MFI was demonstrated by improving inpatient discharges before 12pm performance from 21.52% to 25.84% and reducing the 30-day inpatient readmission rate from 13.92% to 12.96%.ConclusionFour critical factors for an effective QI framework were identified: (1) establishing a common language for improvement; (2) defining distinct roles and skills for improvement at different levels of the organisation; (3) adopting a dosing approach to QI training according to the defined roles and skills and (4) building a critical mass of committed staff trained in QI practice. The pragmatic approach to developing QI capability is both scalable and applicable to emerging healthcare institutions.

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.