Ultra-Performance Liquid Chromatography-Quadrupole-Time-of-Flight-Mass Spectrometry-Based Analysis of Facial Physiological Parameters and Lipid Composition of Between Sensitive Skin of Women Aged 36-42 and 43-49 Year

Abstract

Background: UPLC-Q-TOF-MS (Ultra-Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry) is a high-precision, high-density technology for lipid analysis. Sensitive skin is a sub-stable condition, and it has been reported that the population of sensitive skin in China is predominantly female. Meanwhile, women with sensitive skin have different physiological parameters as well as lipid compositions at different ages. The Yellow Emperor's Classic of Internal Medicine states that the number of women's life cycles is seven, that major changes are manifested every 7 years, and that aging begins at age 35. At present, the correlation between facial lipid composition and aging indicators of sensitive skin in women aged 36-42 and 43-49 years has not been reported.

Objective: This study reveals the relationship between key lipid composition of the facial skin and the aging of sensitive skin in women aged 36-42 and 43-49 years.

Methods: We used UPLC-Q-TOF-MS technology to study the changes in lipid composition in the sensitive skin of woman aged 36-42 and 43-49 years, using a multi-probe adapter system with different types of skin-testing probes to test physiological parameters. Three types of multivariate data-questionnaires, physiological indicators, and lipid composition-were used together to assess differences in aging in a population of women with sensitive skin at different ages.

Results: 1. In the questionnaire part, the T1 group was more susceptible to sunburn and the T2 group was more susceptible to tanning. 2. In the physiological index part, the aging characteristics of facial skin in the T2 group were obvious, with the b-value, as well as the brown area size, being significantly higher than the T1 group, while the TWEL, sebum, R2 value, ITA value, pore count, and concentration of the red area were significantly lower than the T1 group. 3. In the lipid part, the total facial lipid content was higher in the T2 group, with a significantly higher GP lipid, and the 47 VIP lipids obtained were analyzed by ROC curves, narrowing down to six lipids, PS(2-OMe-21:0/0:0), PS(O-18:0/20:5 (5Z,8Z,11Z,14Z,17Z)), PA(O-16:0/20:5 (5Z,8Z,11Z,14Z,17Z)), PS (P-16:0/12:0, PA (O-16:0/22:2 (13Z,16Z)), and PC (19:3 (10Z,13Z,16Z)/0:0)), and all six lipids were higher in the T2 group. 4. In Spearman correlation analysis, PS(O-18:0/20:5(5Z,8Z,11Z,14Z,17Z)), PS(P-16:0/12:0), PS(2-OMe-21:0/0:0), PA(O-16:0/20:5(5Z,8Z,11Z,14Z,17Z)), and PC(19:3( 10Z,13Z,16Z)/0:0), which are five lipids and skin aging indicators (TWEL, sebum, ITA value, b-value, pore count, concentration of red area, and brown area size) were significantly correlated.

Conclusions: Through correlation analysis, it was found that changes in the composition of skin surface lipids (SSLs) in both age groups have an important influence on facial physiological indicators (aging manifestations) and played an important role in furthering the understanding of sensitive skin aging. Therefore, these lipid components also provide theoretical support for the development of cosmetic ingredients that slow down the aging of sensitive skin.

Keywords: age; correlation analysis; lipid; sensitive skin; skin aging.

Figure 1

Subjects’ lifestyle habits (research questionnaires); (A) post-sun-exposure characteristics; (B) daily sun exposure hours; (C) sunscreen use in T1 and T2 groups.

Figure 2

Facial physiological parameters: (A) skin hydration; (B) TWEL, (C) sebum; (D) pH; (E) skin elasticity Q1 value; (F) skin elasticity R2 value in T1 and T2 groups (* p < 0.05, ** p < 0.01).

Figure 3

Facial physiological parameters: (A) ITA value; (B) L-value; (C) a-value; (D) b-value in T1 and T2 groups ( *** p < 0.001, **** p < 0.0001).

Figure 4

Facial physiological parameters: (A) pore counts; (B) red area size (mm²); (C) concentration of red area; (D) brown area size (mm²); (E) surface pigment (mm²); (F) deep pigment (mm²) in T1 and T2 groups (* p < 0.05, **** p < 0.0001).

Figure 5

OPLS-DA score of facial skin surface lipids of subjects in T1 (red squares) and T2 (blue triangles ) groups.

Figure 6

Comparison of the relative mean contents of the eight major types of lipids in T1 and T2 groups. (A) FA relative abundance; (B) GL relative abundance; (C) GP relative abundance; (D) PK relative abundance; (E) PR relative abundance; (F) SL relative abundance; (G) SP relative abundance; (H) ST relative abundance. (**** p < 0.0001).

Figure 7

Comparison of the relative average content of facial GP subclass lipids in subjects in T1 and T2 groups. (A) GP00 lipids; (B) GP01 lipids; (C) GP02 lipids; (D) GP03 lipids; (E) GP04 lipids; (F) GP06 lipids; (G) GP10 lipids. (**** p < 0.0001).

Figure 8

VLCM lipid screening in T1 and T2 groups.

Figure 9

Graph of ROC analysis results of VLCM lipids in T1 and T2 groups.

Figure 10

Spearman’s correlation analysis of subjects’ post-sun exposure characteristics and skin aging parameters. (A) correlation analysis of subjects’ post-sun exposure characteristics and physiological parameters; (B) correlation analysis of subjects’ physiological parameters and facial image parameters. (* p < 0.05, ** p < 0.01).

Figure 11

Spearman correlation analysis of key lipids and statistically significant physiological parameters. (* p < 0.05, ** p < 0.01).