Principal component analysis of seven skin-ageing features identifies three main types of skin ageing.

BACKGROUND: The underlying phenotypic correlations between wrinkles, pigmented spots (PS), telangiectasia and other related facial-ageing subphenotypes are not well understood. OBJECTIVES: To analyse the underlying phenotypic correlation structure between seven features for facial ageing: global wrinkling, perceived age (PA), Griffiths photodamage grading, PS, telangiectasia, actinic keratosis (AK) and keratinocyte cancer (KC). METHODS: This was a cross-sectional study. Facial photographs and a full-body skin examination were used. We used principal component analysis (PCA) to derive principal components (PCs) of common variation between the features. We performed multivariable linear regressions between age, sex, body mass index, smoking and ultraviolet radiation exposure and the PC scores derived from PCA. We also tested the association between the main PC scores and 140 single-nucleotide polymorphisms (SNPs) previously associated with skin-ageing phenotypes. RESULTS: We analysed data from 1790 individuals with complete data on seven features of skin ageing. Three main PCs explained 73% of the total variance of the ageing phenotypes: a hypertrophic/wrinkling component (PC1: global wrinkling, PA and Griffiths grading), an atrophic/skin colour component (PC2: PS and telangiectasia) and a cancerous component (PC3: AK and KC). The associations between lifestyle and host factors differed per PC. The strength of SNP associations also differed per component with the most SNP associations found with the atrophic component [e.g. the IRF4 SNP (rs12203592); P-value = 1·84 × 10-22 ]. CONCLUSIONS: Using a hypothesis-free approach, we identified three major underlying phenotypes associated with extrinsic ageing. Associations between determinants for skin ageing differed in magnitude and direction per component. What's already known about this topic? Facial ageing is a complex phenotype consisting of different features including wrinkles, pigmented changes, telangiectasia and cancerous-related growths; it is not clear how these phenotypes are related to each other and to other phenotypes. A few studies have described two main clinical phenotypes for photoageing, namely hypertrophic ageing and atrophic ageing, which have been based solely on the clinical assessment of photoageing characteristics. What does this study add? We are the first to use epidemiology data to identify three main components associated with photoageing, namely a hypertrophic component (global wrinkling; perceived age; Griffiths grading) and atrophic component (pigmented spots; telangiectasia) and a cancer component (actinic keratosis; keratinocyte cancer). Association analysis showed different effects and direction of environmental determinants and genetic associations with the three components, with the most significant gene variants associations found for the atrophic component.

Epidemiology and determinants of facial telangiectasia: a cross-sectional study.

BACKGROUND: Telangiectasia or red veins are one of the prominent features of facial skin ageing. To date, there are few studies investigating the determinants of telangiectasia. OBJECTIVES: We investigated lifestyle and physiological factors associated with facial telangiectasia in a large prospective Dutch cohort study. METHODS: Telangiectasia was quantified digitally from standardized facial photographs of 2842 North European participants (56.8% female, median age 66.9) from the Rotterdam Study, collected in 2010-2013. Effect estimates from multivariable linear regressions are presented as the percentage difference in the mean value of telangiectasia area per unit increase of a determinant (%Δ) with corresponding 95% CI. RESULTS: Significant determinants were older age [1.7%Δ per year (95% CI 1.4, 2.0)], female sex [18.3%Δ (95% CI 13.2, 23.6)], smoking [current versus never 38.4%Δ (95% CI 30.3, 47.0); former versus never 11.6%Δ (95% CI 6.6, 16.9)], a high susceptibility to sunburn [10.2%Δ (95% CI 5.4, 15.3)] and light skin colour [pale versus white-to-olive 31.4%Δ (95% CI 19.7, 44.1]; white vs. white-to-olive 9.2%Δ (95% CI 2.8, 16.0)]. CONCLUSIONS: In this large cohort study, we confirmed known and described new determinants of facial telangiectasia.

Validation of image analysis techniques to measure skin aging features from facial photographs.

BACKGROUND: Accurate measurement of the extent skin has aged is crucial for skin aging research. Image analysis offers a quick and consistent approach for quantifying skin aging features from photographs, but is prone to technical bias and requires proper validation. METHODS: Facial photographs of 75 male and 75 female North-European participants, randomly selected from the Rotterdam Study, were graded by two physicians using photonumeric scales for wrinkles (full face, forehead, crow's feet, nasolabial fold and upper lip), pigmented spots and telangiectasia. Image analysis measurements of the same features were optimized using photonumeric grades from 50 participants, then compared to photonumeric grading in the 100 remaining participants stratified by sex. RESULTS: The inter-rater reliability of the photonumeric grades was good to excellent (intraclass correlation coefficients 0.65-0.93). Correlations between the digital measures and the photonumeric grading were moderate to excellent for all the wrinkle comparisons (Spearman's rho ρ = 0.52-0.89) bar the upper lip wrinkles in the men (fair, ρ = 0.30). Correlations were moderate to good for pigmented spots and telangiectasia (ρ = 0.60-0.75). CONCLUSION: These comparisons demonstrate that all the image analysis measures, bar the upper lip measure in the men, are suitable for use in skin aging research and highlight areas of improvement for future refinements of the techniques.

Modulation of cholinergic airway reactivity and nitric oxide production by endogenous arginase activity.

Cholinergic airway constriction is functionally antagonized by agonist-induced constitutive nitric oxide synthase (cNOS)-derived nitric oxide (NO). Since cNOS and arginase, which hydrolyzes L-arginine to L-ornithine and urea, use L-arginine as a common substrate, competition between both enzymes for the substrate could be involved in the regulation of cholinergic airway reactivity. Using a perfused guinea-pig tracheal tube preparation, we investigated the modulation of methacholine-induced airway constriction by the recently developed, potent and specific arginase inhibitor N(Omega)-hydroxy-nor-L-arginine (nor-NOHA). Intraluminal (IL) administration of nor-NOHA caused a concentration-dependent inhibition of the maximal effect (E(max)) in response to IL methacholine, which was maximal in the presence of 5 microM nor-NOHA (E(max)=31.2+/-1.6% of extraluminal (EL) 40 mM KCl-induced constriction versus 51.6+/-2.1% in controls, P<0.001). In addition, the pEC(50) (-log(10) EC(50)) was slightly but significantly reduced in the presence of 5 microM nor-NOHA. The inhibition of E(max) by 5 microM nor-NOHA was concentration-dependently reversed by the NOS inhibitor N(Omega)-nitro-L-arginine methyl ester (L-NAME), reaching an E(max) of 89.4+/-7.7% in the presence of 0.5 mM L-NAME (P<0.01). A similar E(max) in the presence of 0.5 mM L-NAME was obtained in control preparations (85.2+/-9.7%, n.s.). In the presence of excess of exogenously applied L-arginine (5 mM), 5 microM nor-NOHA was ineffective (E(max)=33.1+/-5.8 versus 31.1+/-7.5% in controls, n.s.). The results indicate that endogenous arginase activity potentiates methacholine-induced airway constriction by inhibition of NO production, presumably by competition with cNOS for the common substrate, L-arginine. This finding may represent an important novel regulation mechanism of airway reactivity.