1. Introduction
The human skin is a complex living ecosystem that hosts a rich variety of microorganisms, collectively known as the skin microbiota, which includes bacterial species, such as Cutibacterium, Corynebacterium, Staphylococcus, and Proteobacteria [1,2,3,4]. The skin microbiota is essential to skin barrier function, helping to protect the skin and the deeper organs from inflammation, infections, and environmental stressors, like UV radiation and pollution [1,5,6,7,8,9,10]. It also shares a bidirectional relationship with aging, both changing with age and influencing the skin aging process [11,12,13]. This bidirectional relationship is part of the skin interactome, a novel integration of the “genome-microbiome-exposome” that plays a significant role in skin aging and skin health [11,14].
Imbalances in the skin microbiota (i.e., dysbiosis) are often associated with skin conditions, such as acne vulgaris, rosacea, psoriasis ,and atopic dermatitis, as well as pathological conditions, including cutaneous wounds, ulceration, and melanoma [15,16,17,18,19,20,21,22,23,24]. This dysbiosis typically involves the increased colonization of pathogens, a reduced number of beneficial commensals, and a variation in both alpha (i.e., evenness and abundance of microbial species at the sample level) and beta diversity (i.e., similarity or difference in microbial communities between samples or conditions) [25,26,27]. The study of skin microbiota dysbiosis, as well as the normal microbiota, and skin aging is therefore of great interest for diagnosing skin diseases, identifying therapeutic options, and maintaining the skin barrier in an optimal condition [28].
Growing evidence also highlights a crucial role for the gut microbiota in supporting skin health by strengthening the skin barrier function [29,30]. Disruption of the gut integrity and imbalances in its microbiota can significantly impact skin homeostasis and allostasis, with a growing body of research highlighting a bidirectional interaction between the gut and the skin [29]. This interaction, termed the “gut–skin axis”, highlights the complex relationship between the gut and the skin [31,32].
The interaction between the skin and the gut microbiomes underpins the combined use of food supplements and cosmetic products (in and out approach) to address skin aging on multiple levels, helping to nourish the skin from within while providing topical benefits [33,34,35,36]. This trial aimed to assess the antiaging efficacy of a patented [37] “in & out” approach providing targeted microbiome support through a combination of oral probiotics containing Lactobacillus plantarum PBS067, Lactobacillus reuteri PBS072, and Lactobacillus rhamnosus LRH020, supported by adjuvant topical products containing ectoin (an amino acid derivative with osmoprotectant properties), fruit water, triglycerides, and a proprietary multi-molecular weight hyaluronate compound.
2. Materials and Methods
2.1. Trial Design and Ethics
The trial was a single-center, randomized (1:1:1:1 balanced randomization), double-blind, placebo-controlled trial with four treatment arms, conducted at Complife Italia S.r.l. facility in San Martino Siccomario (PV), Italy, from March to September 2023. It consisted of a screening visit, a baseline visit (W0), and two follow-up visits after 4 (W4) and 8 (W8) weeks of products use. During the baseline visit, the filler effect of the serum and the hydrating and glowing effect of the cream were tested 1 h after product application. After the enrollment, subjects were randomized to receive the active food supplement and the placebo cosmetic products (AFPC), the placebo food supplement and the placebo cosmetic products (PFPC), the active food supplement and the active cosmetic products (AFAC), and the placebo food supplement and the active cosmetic products (PFAC).
All trial procedures were conducted in accordance with the World Medical Association’s (WMA) Helsinki Declaration and its amendments. The study protocol and all trial-related documents were approved by the “Comitato Etico Indipendente per le Indagini Cliniche Non Farmacologiche” (ref. no. 2002/01 by 2 February 2022). Each participant provided written informed consent (ICF) prior to the initiation of any study-related procedures.
The trial was designed to demonstrate the test product claim(s) in the current framework proposed by Commission Regulation (EU) No 655/2013. Endpoints were measured using techniques currently accepted in the cosmetic field, while biases are minimized through procedure standardization according to the ISO 9001 Quality Management System.
2.2. Participants and Compliance with Treatment
Eligible participants included healthy male and female subjects aged 45 to 65 years with mild-to-moderate signs of facial aging and (self-declarative) sensitive skin. Exclusion criteria included natural or artificial UV exposure (e.g., tanning beds or facial lamps), dermatological skin conditions and medical histories that could interfere with study outcomes, pharmacological treatments interfering with the study outcomes (e.g., antibiotics), Botox treatment or intention to have Botox treatment during the study period, breastfeeding, pregnancy, and unwillingness to take the necessary precautions to avoid pregnancy (for women of childbearing potential). The complete inclusion and exclusion list is reported in the Supplementary Materials (Table S1).
Throughout the study period, participants were asked to maintain a journal documenting their food and drink consumption to ensure stability in their dietary habits. They were also instructed to report any adverse events. Additionally, the use of cosmetic products and food supplements other than the tested ones was not permitted. Compliance with treatment was evaluated by counting and recording the number of the remaining (not used) stick packs after 4 and 8 weeks of treatment, with a compliance threshold set at ≥80%.
2.3. Interventions and Randomization
The test item was a commercially available in and out patented (no. EP4151217) [37] treatment (“AWvi—The skin method”) supplied by AW Srl (Sesto Fiorentino, FI, Italy). The treatment consisted of a food supplement (AWvi—The Skin Biotic), a cleanser (AWvi—The Gentle Cleanser), a serum (AWvi—The Power of Serum), and a cream (AWvi—The Active Cream).
Each treatment arm consisted of 24 subjects receiving the active food supplement and the placebo cosmetic products (group AFPC), the placebo food supplement and the active cosmetic products (group PFAC), the active food supplement and the active cosmetic products (AFAC), and the placebo food supplement and the placebo cosmetic products (PFPC). The active food supplement treatment arm received 1 stick pack (1-g net content) containing 10 mg Lactobacillus plantarum (PBS067-DSM 24937), 25 mg Lactobacillus reuteri (PBS072-DSM 25175), Lactobacillus rhamnosus (LRH020-LMG P-29513/DSM 25568), 927.015 Sorbitol, 1000 mg Fructo-oligosaccharides, 1.476 mg Vitamin A Acetate, 0.009 mg Biotin, and 20 mg Silicon dioxide (E551) daily. The placebo product formula was identical to the active formula, except that lactobacilli were replaced by an equivalent amount (51.5 mg) of maltodextrin. All the ingredients used in the food supplement formula are safe for their use.
The cosmetic product actives were sodium hyaluronate, ectoin, fruit water, and triglycerides. The complete ingredient (INCI) list is reported in the Supplementary Materials (Table S2). All the ingredients in the cosmetic products were included in the positive list of approved substances for use in cosmetic formulations. The products did not contain any ingredients listed in Annex II (prohibited substances) of Regulation (EC) No 1223/2009 [38]. Ingredients from Annex III (restricted substances) and Annex V (preservatives) were used within the permitted concentrations specified in the Regulation and had been evaluated for safety by the European Scientific Committee.
The placebo formulas (Supplementary Table S2) were the same as the active’s formulas without the following active ingredients: ectoin and sodium hyaluronate. Both the active and placebo products were applied as follows: massage the cleanser onto damp skin and rinse with water; apply the serum to dry and cleansed skin, and once the serum is absorbed, apply the cream. All the products were applied twice a day (morning and evening) all over the face (including the neck and the eye contour area). Participants were instructed to apply the cosmetic products according to their habitual daily routine, following an ad libitum application approach. However, the estimated quantities for application were 2.5 g for the cleanser and 0.8 mL/g for both the serum and the cream [39,40]. Given that the cosmetic products were applied twice daily, the estimated total usage was twice the specified amounts.
2.4. Outcomes
Primary and secondary outcomes were measured both in the short term (i.e., 1 h after a single application of the products) and the long term (i.e., after 4 and 8 weeks of daily, regular use of the products). Four and eight weeks were chosen for the study duration based on the following rationale: 4 weeks is a cosmetically acceptable timeframe, as subjects expect visible results within this period; otherwise, they are unlikely to continue using the product. Meanwhile, 8 weeks is an appropriate duration for a food supplement to demonstrate its effects on the skin [41,42].
2.4.1. Primary Outcomes
The primary outcomes of the trial were the measurement of the skin sebum content and the skin hydration (ability of the product to attract water when applied, humectant) and moisturization (increase in the water content based on an improvement in the skin barrier efficiency).
The skin sebum content (μg/cm2) measurement was based on the “grease spot photometry” technique with a Sebumeter® SM 815 (Courage + Khazaka electronic GmbH, Cologne, Germany).
The skin hydration (1 h after the cream application) and the skin moisturization (after 4 and 8 weeks of each tested treatment) were measured using the capacitance method using a Corneometer® CM 825 (Courage + Khazaka electronic GmbH, Cologne, Germany).
2.4.2. Secondary Outcomes
The secondary outcomes of the trial were related to the assessment of the efficacy of the products in improving skin signs related to aging. The secondary outcomes included the following measurements: wrinkle depth, skin smoothness, transepidermal water loss (TEWL), skin elasticity, skin radiance, pores (size and impurities), and skin microbiome.
The profilometric properties (wrinkle depth and skin smoothness) of the skin were measured in the “crow’s feet” area using a PRIMOSCR small field device (Canfield Scientific Europe, BV, Utrecht, The Netherlands). Subject repositioning between each visit was ensured using a stereotactic device (Canfield Scientific Europe, BV, Utrecht, The Netherlands).
Transepidermal water loss (TEWL) was measured with an open-chamber Tewameter® TM Hex (Courage + Khazaka electronic GmbH, Cologne, Germany) in the cheeks area.
The skin elasticity measurement was based on the suction method using a Cutometer® MPA 580 (Courage + Khazaka electronic GmbH, Cologne, Germany) equipped with a 2 mm-diameter probe. The measured parameters included R0 (Uf) and R2 (Ua/Uf). R0, referred to as skin firmness, represents the maximum skin deformation (Uf) observed during the suction phase, while R2, known as overall elasticity, is defined as the ratio of skin distension during the elongation phase (Ua) to the maximum skin deformation (Uf) during the suction phase. Both parameters were measured in the cheeks area.
Skin radiance was measured, in the cheeks area, based on the 8°gloss parameter taken with a colorimeter/spectrophotometer CM 700D (Konica Minolta, Milan, Italy).
The pore sizes and the protoporphyrin (microbial impurities) distribution were measured in the area near the nose via morphometric and colorimeter image analysis on digital pictures taken with a VISIA®-CR (Canfield Scientific Europe, BV, Utrecht, The Netherlands).
Microbiome samples were obtained by swabbing a 3.5 × 5.5 cm area on the volunteers’ face (cheek), outlined by a disposable adhesive template (Copan Spa, Brescia, Italy), by using a moistened FLOQswab® (Copan Spa, Brescia, Italy). For each participant, the collection site was brushed 10 times horizontally and 10 times vertically. Subsequently, the swabs were immersed in 1 mL of preservation medium (eNat®, Copan Spa, Brescia, Italy) and stored at room temperature for up to four weeks. Prior to isolating microbial DNA, the samples were prepared in accordance with the methodology previously described [43] and immediately stored at –20 °C until further use.
Bacterial DNA was isolated using the QIAamp® DNA Microbiome Kit (Qiagen, Hilden, Germany), in accordance with the manufacturer’s guidelines. The yield and quality of the extracted DNA were assessed using the QubitTM 1X dsDNA HS Assay Kit (Invitrogen Co., Carlsbad, CA, USA) on a QubitTM Flex Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). Polymerase chain reaction (PCR) amplification of the V1–V3 hypervariable regions of the bacterial 16S rRNA gene was performed using the Microbiota Solution A kit (Arrow Diagnostics, Genoa, Italy). The resulting products were purified using Agencourt AMPure XP magnetic beads (Beckman Coulter Inc., Brea, CA, USA). The amplicon size and purity of the PCR products, including a negative control, were determined via electrophoresis on a 1.5% agarose gel in TAE buffer (1×). A further measurement was performed to ascertain the DNA concentration of the libraries, and samples were pooled in equimolar concentrations. The final amplicon libraries were sequenced on a MiSeq Illumina® sequencing platform using a MiSeq Reagent Kit v2 cartridge for 2 × 250 paired-end sequencing (Illumina Inc., San Diego, CA, USA).
2.4.3. Self-Assessment Questionnaire
At each checkpoint, subjects were asked to give their opinion on the tested product by answering a questionnaire about the product’s perceived effects and satisfaction. The questionnaire was taken before any outcome measurement so as not to influence the participants’ answers. Possible answers were “fully agree”, “agree”, “neither agree nor disagree”, “rather don’t agree”, or “don’t agree al all”. Both “fully agree” and “agree” were included in the calculation of the responders.
2.5. Sample Size
The sample size was determined using a two-sided significance level of 5% and a power of 80%. The calculation accounted for a 20% variation in the primary endpoints, attributable to both inter-individual variability and measurement technique errors. The sample size was calculated using PASS 11 statistical software (version 11.0.8, PASS, LLC, Kaysville, UT, USA). A sample size of 20 subjects per group was obtained. Four additional subjects were added in each panel to anticipate a dropout rate of 20%.
2.6. Randomization and Blinding
Subjects were randomized in a 1:1:1:1 ratio to receive either active or placebo treatments using a computer-generated randomization list (PASS 11, version 11.0.8, PASS, LLC, Kaysville, UT, USA) based on the “Efron’s biased coin” algorithm. The randomization list was securely concealed within sequentially numbered, sealed, and opaque envelopes. The study followed established protocols to ensure a clear separation between the investigator and their collaborators and the staff administering the intervention. All the products were identical in size and shape.
2.7. Statistical Analysis
2.7.1. Analysis of Clinical Endpoints
The intragroup (vs. baseline) statistical analysis was performed on the raw data via repeated measures analysis of variance (RM-ANOVA) followed by the Tukey–Kramer post hoc test or by a t test of Student. The intergroup (active vs. placebo) statistical analysis was performed on the percentage variations via one-way analysis of variance followed by the Tukey–Kramer post hoc test. Statistically significant data were reported as follows: * p < 0.05, ** p < 0.01, and *** p < 0.001.
2.7.2. Analysis of Microbiome Data
Raw sequencing data were processed using MicrobAT (Microbiota Analysis Tool) v.1.1.0 software (SmartSeq Srl, Novara, Italy) based on a comparison with the Ribosomal Database Project (RDP) database. Once filtered for read length (<200 nt) and quality (average Phred quality score < 25) [44], the resulting sequences were aligned with a similarity threshold of ≥97% and assigned to taxonomic levels with a query coverage of 80% [45]. Features without taxa designation were ascribed to the corresponding unclassified group. A secondary analysis of the results was performed using MicrobiomeAnalyst Software [46,47], where features with low counts and variance were identified and removed, while the remainder were analyzed according to their median abundance levels (minimum count of 4) across samples.
Sample biodiversity was calculated as the alpha diversity (diversity within the group) and the beta diversity (diversity between groups). For alpha diversity, two indices were employed: the Shannon index, which estimates the overall number of different taxa present; a higher Shannon index indicates a greater diversity of individual taxa. The Simpson index, often referred to as the “evenness” index, is based on a logarithmic scale and evaluates whether a few taxa dominate the microbiome (values close to 1) or if the abundance distribution is more balanced (values closer to 0). Beta diversity analysis was performed to evaluate differences in the overall taxonomic compositions between groups. The distance matrix, generated by using the Bray–Curtis dissimilarity method, was visualized in two plots through principal coordinate analysis (PCoA). In these plots, each point represents the entire microbiota of a single sample. The statistical significance of the observed differences between microbial communities of each group was assessed using permutational analysis of variance (PERMANOVA) and reported as follows: * p < 0.05, ** p < 0.01, and *** p < 0.001.
3. Results
3.1. Participant Characteristics, Tolerability, and Compliance with Treatment
A total of 121 (n = 121) subjects were screened; 25 were excluded, with 16 not meeting the inclusion criteria and 9 declining to participate. The trial successfully randomized 96 subjects with 24 subjects per group. Ninety-four subjects completed the study, while two subjects in the AFAC group dropped out for personal reasons not related to products use. The participant flow chart is reported in Figure 1.
The enrolled subjects were male and female Caucasians aged between 45 and 65 years old with mild-to-moderate signs of facial aging and sensitive skin. Additional demographics and the baseline characteristics of the participants are shown in Table 1 and clearly indicate the absence of covariates. Baseline values did not differ significantly between groups (p > 0.05, Student’s t-test). The analysis of the dietary journals, which documented food and drink consumption, revealed no significant changes in the participants’ dietary habits since baseline. Similarly, participants did not report any changes in their lifestyle during the study duration.
All tested products were well tolerated, with no adverse effects reported either by the investigator or the participant. Dietary habits remained consistent throughout the study period and did not represent a covariate between the groups.
Compliance with treatment was above 90% in each group (AFPC: 97.4 ± 0.5%; PFAC: 97.8 ± 0.5%; AFAC: 97.2 ± 0.5%; PFPC: 97.3 ± 0.4%).
3.2. Short-Term Results with Topical Product Application
The wrinkle depth in the “crow’s feet area” (Figure 2a) was 293.1 ± 14.1 μm in the active group (n = 48) and 290.5 ± 14.2 μm in the placebo group (n = 48). One hour after applying the active serum, the wrinkle depth statistically significantly (p < 0.001) decreased by 9.2% compared to a 3.9% reduction (p < 0.01) in the placebo group. The effect size of the serum in reducing the wrinkle depth was then 2.4 times greater in the active group compared to the placebo group (p < 0.05).
The skin hydration 1 h after the application (Figure 2b) of the active cream was statistically significantly (p < 0.001) increased by 16.6% (55.2 ± 0.9 c.u. at T1h vs. 47.6 ± 1.0 at T0 cu). The placebo group also showed a statistically significant increase in skin hydration of 9.2% (p < 0.001), with the effect of the active cream being 1.8 times greater (p < 0.001).
A statistically significant increase in skin radiance (Figure 2c) was recorded with both the active (+19.1%, p < 0.001) and the placebo cream (+13.1%, p < 0.001) after 1 h, with a 1.5 times greater effect for the active cream (p < 0.05).
3.3. Primary Endpoints
In the AFPC group, skin moisturization statistically significantly increased by 10.7% (p < 0.001) and 17.0% (p < 0.001), after 4 and 8 weeks of treatment, respectively (Table 2). A similar (p < 0.05) increase in skin moisturization was observed in the PFAC group, with 12.8% (p < 0.001) at W4 and 14.5% at W8 (p < 0.001). In the AFAC group, the increase in skin moisturization was higher both at W4 (+15.5%, p < 0.001) and W8 (+21.4%, p < 0.001), although the differences were not statistically significant (p < 0.05) compared to the AFPC and the PFAC groups. These variations were 2.9 and 3.2 times greater than the results obtained in the PFPC placebo group. A slight but statistically significant increase was also observed in the PFPC placebo group, with increases of +5.4% (p < 0.01) at 4 weeks and +6.6% (p < 0.001) at 8 weeks. Although the increase in skin moisturization peaked at W4 in the PFAC and PFPC groups, it was further increased at W8 in both the AFPC (p < 0.05) and AFAC (p < 0.001) groups. Statistical differences between the PFPC placebo group and the active groups were as follows: p < 0.05 for AFPC at week 8, p < 0.05 for AFAC at week 4, and p < 0.01 for AFAC at week 8.
All the products did not alter (p > 0.05) the skin sebum content either at W4 and W8 (Table 2). A small but statistically significant decrease in the skin sebum content (p < 0.01) was observed in the AFAC group at week 8, with sebum levels remaining within the normal range.
3.4. Secondary Endpoints
3.4.1. Skin Profilometry
The wrinkle depth in the “crow’s feet” area decreased in all subjects treated with active products (Table 3). In the AFPC group, the wrinkle depth decreased by 9.3% (p < 0.01) after 4 weeks and 13.8% (p < 0.001) after 8 weeks of treatment. A similar reduction was observed in the PFAC group, with an 8.1% decrease at week 4 (p < 0.01) and 9.9% decrease at week 8 (p < 0.01). In the AFAC group, wrinkle depth reduction at week 4 (−10.3%, p < 0.01) was comparable to that observed in the AFPC and PFAC groups, but at week 8, it was significantly greater (−16.5%, p < 0.001) and showed a significant increase compared to week 4 (p < 0.05). In the PFPC placebo group, winkle depth was slightly reduced, although this change was not statistically significant (p < 0.05). Compared to the PFPC placebo group, the change in wrinkle depth in the AFAC group was 3.8 times greater at week 4 and 5.1 times greater at week 8 (p < 0.05 vs. PFPC at W8).
An improvement in skin smoothness (Sa parameter, Table 3) was observed only in the AFAC group, with a reduction of 5.1% at week 4 (p < 0.05) and 5.8% at week 8 (p < 0.01). Although the Sa parameter was also decreased in the AFPC and the PFAC group, this variation was not statistically significant (p > 0.05). In contrast, the PFPC placebo group showed a statistically significant worsening of +1.6% in skin smoothness at week 8 (p < 0.05).
3.4.2. Transepidermal Water Loss (TEWL)
A statistically significant decrease of TEWL (Table 3) was recorded in both the PFAC (−5.3%, p < 0.05 at W4; −7.2%, p < 0.01 at W8) and AFAC (−6.6%, p < 0.01 at W4; −10.8%, p < 0.001 at W8) groups after 4 and 8 weeks of treatment. Moreover, a statistically significant (p < 0.01) decrease of 6.1% in TEWL was observed in the AFPC group at week 8. TEWL remained unchanged (p < 0.05) in the PFPC placebo group. At week 8, the TEWL reduction in the AFAC group was 5.8 times greater compared to the change in TEWL in the PFPC placebo group.
3.4.3. Skin Elasticity
Treatment with the active products positively affected skin firmness (R0 parameter) and elasticity (R2 parameter), with improvements observed after both 4 and 8 weeks of treatment (Table 4). The R0 parameter in the AFPC group decreased by 2.1% (p < 0.05) at week 4 and was further decreased by 4.7% (p < 0.001 vs. baseline and p < 0.05 vs. placebo PCPC group) after 8 weeks of treatment, respectively. The 8-week reduction was statistically significantly higher than the 4-week variation (p < 0.05). In the PFAC group, the decrease was 3.9% (p < 0.01) at week 4 and 6.5% (p < 0.001) at week 8, while in the AFAC group, it decreased by 5.1% (p < 0.001) at week 4 ad 7.7% (p < 0.001) at week 8. Skin firmness in the placebo PFPC group remained unchanged (p < 0.05) after both 4 and 8 weeks of treatment. At week 8, the reduction in the R0 parameter was statistically significantly higher in the PFAC (p < 0.01) and AFAC (p < 0.001) groups compared to the PFPC placebo group. At week 8, the reduction in the R0 parameter in the PFAC group was 38.6 times greater compared to the change in the R0 parameter in the PFPC placebo group, while it was 45.5 times greater in the AFAC group.
A similar trend was observed for the R2 parameter, which improved across all active groups (AFPC, PFAC, and AFAC) after both 4 and 8 weeks of treatment (Table 4). The results in the AFAC group were 9.4 times (p < 0.05 vs. PFPC group) higher than those in the placebo group at week 4 and 5.5 times (p < 0.001 vs. PFPC group) higher at week 8. Interestingly, the R2 parameter at week 8 showed a further increase compared to week 4 in both the AFPC (+5.4% at W8 vs. +2.4% at W4, p < 0.001) and AFAC (+4.7% at W8 vs. +7.1% at W4, p < 0.05) groups. The R2 parameter was unchanged (p > 0.05) in the placebo PFPC group.
3.4.4. Skin Radiance
The skin radiance (Table 5) showed a positive increase across all active products, with a slight improvement also observed in the PFPC placebo group. In the AFPC group, the skin radiance was improved by 10.4% (p < 0.001) after 4 weeks and by 19.2% (p < 0.001) after 8 weeks of treatment. Skin radiance demonstrated a steady improvement from week 4 to week 8 in both the AFPC group (+19.2% at W8 vs. +10.4% at W4, p < 0.001) and the PFAC group (+22.5% at W8 vs. +12.3% at W4, p < 0.01). The results obtained in the AFAC group were 5.3 times (p < 0.001 vs. PFPC group) higher than those in the placebo group (p < 0.001 vs. PFPC group) at week 4 and 5.0 times higher at week 8. While the change in skin radiance was statistically significant in the PFPC group, it was smaller (+5.0% at W4, p < 0.05 and + 6.3% at W8, p < 0.001) than that observed in all active groups.
3.4.5. Pores Size and Impurities (Protoporphyrin Distribution)
The size of skin pores did not show any statistically significant change (p > 0.05) in any study group, either after 4 weeks or 8 weeks of treatment (Table 5).
The protoporphyrin distribution decreased in all the active study groups (Table 5). In the AFPC group, the distribution of protoporphyrin was decreased by 8.7% (p < 0.05) after 4 weeks and by 8.8% (p < 0.05) after 8 weeks. A similar decrease was also observed in the PFAC group (−4.9% at W4, p < 0.05; −6.0% at W8, p < 0.05) and in the AFAC group (−9.6% at W4, p < 0.05; −9.8% at W8, p < 0.01), while no change was noted in the placebo PFPC group.
3.4.6. Skin Microbiome
The microbial composition of the most abundant genera and their parent taxa included Cutibacterium (52.4%), Corynebacterium (3.2%), Kocuria (0.5%), Acetobacter (0.6%), Achromobacter (0.3%), Staphylococcus (21.0%), Gemella (0.3%), Streptococcus (2.0%), and Anaerococcus (0.9%).
Both the alpha (Shannon and Simpson index) and beta diversity indexes remained unchanged (p > 0.05) in the AFPC, PFAC, and PFPC groups (Figure 3). In contrast, a statistically significant difference between week 4 and 8 was observed in the AFAC group for both the Shannon (p < 0.01 at phylum level) and the Simpson index (p < 0.01 at phylum and p < 0.05 at genus level) but not for the beta diversity index (p > 0.05).
In the AFPC group, the linear discriminant analysis effect size (LDA LEfSe) at week 8 revealed a statistically significant decrease in Achromobacter (−0.37%, LDA score = 4.23, p < 0.001) and an increase in Gemella (+0.26%, LDA score = −4.16, p < 0.05) relative abundances. In the PFAC group there was an increase in the relative abundance of Acetobacter (+0.70%, LDA score = −4.23, p < 0.05) and Acinetobacter (+0.59%, LDA score = −4.48, p < 0.05). In the AFAC group there was an increase of Cutibacterium (+10.32%, LDA score = −5.65), even if not statistically significant (p > 0.05). This variation should be related to the increase in the Simpson index value (both at the genus and phylum level). In the PFPC group, the microbiome was unchanged.
3.4.7. Self-Assessment Questionnaire Output
All the active products, both topical and oral, received positive evaluations from the study participants. Detailed results for each group are provided in the Supplementary Material (Table S3).
4. Discussion
Skin aging is a complex and multifactorial process in which cellular senescence (i.e., cellular proliferation arrest) and skin inflammaging are driven by the alteration of the skin barrier properties [48,49,50,51]. In recent years the alteration of the skin barrier wawas also correlated with skin microbiota alterations [1,5,6,7,8,9,10]. Supporting the skin barrier, respecting its hydrolipidic film, and protecting the skin microbiota are then crucial to maintain skin longevity and well-being over time [52,53,54].
The results of this randomized, double-blind, placebo-controlled trial involving 96 subjects showed that product use has a high level of compliance with treatment without adverse effects during an eight-week period of use.
The short-term effects observed one hour after a single application of the cosmetic products revealed statistically significant improvements: the wrinkle depth decreased by 9.2% with serum application, while skin hydration and radiance increased by 16.6% and 19.1%, respectively, with cream application.
In the long term, all active products effectively maintained the skin hydrolipidic film. The skin sebum content remained stable, except for a slight decrease observed in the AFAC group at week 8, likely due to a sebum-normalizing effect in subjects with oily skin. On the contrary, skin moisturization was increased in all the groups, including the placebo PFCP group. Interestingly, skin moisturization showed a consistent improvement from week 4 to week 8 in the active food supplement groups (AFPC and AFAC), while it reached its maximum efficacy in both the active cosmetic product (PFAC) and placebo (PFPC) groups. These findings clearly highlight the synergistic effect of the food supplement and its role in enhancing the efficacy of the cosmetic product.
The product’s efficacy in preserving skin lipids while enhancing the hydric component of the skin’s hydrolipidic film was reflected by its positive impact on the skin microbiome. In the active cosmetic product (PFAC) group, increased skin moisturization correlated with a rise in the relative abundance of transient microbiota members, specifically Proteobacteria (Acetobacter and Acinetobacter), which are associated with a higher epidermal water content [1,4]. Interestingly the active food supplement group (AFPC) showed an increase in fermentative bacteria from the Gemella genus, which may reflect a manifestation of the gut–skin axis [55]. These findings were evident in the active food supplement and cosmetic product (AFAC) group as a promotion of better bacterial distribution.
Long-term effects observed at 4 and 8 weeks post-treatment initiation revealed statistically significant improvements from baseline to the 8-week follow-up in the active-active group. These included reductions in the wrinkle depth, transepidermal water loss (indicating an improved skin barrier function and condition), protoporphyrin distribution (associated with impurity removal), and skin sebum content. Concurrently, enhancements were noted in skin smoothness, moisturization, radiance/brightness, elasticity, and firmness.
The mechanism behind ectoin antiaging efficacy can be related to its cellular protective effect but also to a skin protective barrier effect. In an in vitro study on human skin fibroblasts, Cheng et al. demonstrated that ectoin protects cells from UVA and H2O2-induced damage by regulating antioxidant-related enzymes and upregulating genes involved in the PI3K/AKT signaling pathway [56]. Research also highlights ectoin’s role in stabilizing the cell membrane, reducing inflammation, and mitigating the DNA damage caused by ultraviolet, visible, and infrared radiation [57,58]. On the other hand, the antiaging properties of hyaluronic acid are associated with its ability to inhibit the expression of metalloproteinases, enhance type I collagen production, and promote the expression of dermal–epidermal junction (DEJ) proteins and wound healing [59,60].
The beneficial role of probiotics, particularly for their skin antiaging properties, is increasingly acknowledged in the scientific literature. In a recent clinical trial on Lactobacillus plantarum HY7714, Lee et al. reported its efficacy in reducing epidermal moisture loss and the wrinkle depth while enhancing skin gloss and elasticity [61]. Our results also confirm the beneficial effects of probiotics for antiaging properties. The mechanism behind this effect remains unclear; however, it appears that interplay between the microorganism and the host immune system helps to maintain skin homeostasis [30,32,62].
The synergistic effect of probiotic intake and cosmetic product use could be related to the positive effect of probiotics in improving the same skin parameters that are targeted by the cosmetic product application. In particular, the increased relative abundance of Gemella, Cutibacterium, and Acinetobacter that we observed in the active groups has been associated with attributes of younger skin [11,63,64]. This in turn can be correlated with the improvement of the skin parameters measured in this trial with a positive effect of a balanced microbiome in improving the skin barrier, in maintaining the skin’s natural moisturizing factor (NMF) and in modulating the skin immune response [65,66].
This study has several notable strengths but also some limitations. Firstly, its randomized, double-blind, placebo-controlled design minimizes bias and enhances the reliability of the findings. The inclusion of both topical and oral interventions allowed for a comprehensive evaluation of their synergistic effects on skin health and aging parameters. Additionally, the use of objective skin measurement techniques, such as profilometry for wrinkle depth, corneometry for hydration, and TEWL for the barrier function, ensures robust and quantifiable outcome assessment. Another key strength is the integration of the skin microbiome analysis, providing insights into the biological mechanisms underlying the observed clinical effects. The study also employed self-assessment questionnaires, which complement the instrumental data with user-reported satisfaction and perception of efficacy to align the measured efficacy and the perceived efficacy. Furthermore, the high compliance rate (>90%) and absence of adverse effects reinforce the feasibility and safety of the interventions over an extended period. Despite these strengths, the study has some limitations. The study population consisted predominantly of Caucasian individuals aged 45–65 with mild to moderate signs of aging, which may not fully represent younger or more diverse demographics. These homogeneous characteristics were intentionally selected to minimize the bias and confounding factors that could affect the assessed parameters. Another limitation was the lack of a post-treatment follow-up period to assess the sustainability of the product’s effects after discontinuation. Future research could extend these limitations with new insights.
5. Conclusions
The results of this randomized, double-blinded, placebo-controlled study of the Skin Method show positive short-term and long-term results in the active cosmetic products of serum and cream (which contain the proprietary hyaluronate, ectoin, active waters, and triglycerides) compared with the placebo group (active waters and triglycerides only).
The effects are seen as early as 1 h after a single application, including an improvement in wrinkles and an increase in hydration and radiance. The effects on primary and secondary outcomes were significantly improved at 4 and 8 weeks after commencing treatment.
There were superior improvements in skin moisturization, wrinkles, smoothness, radiance, elasticity and firmness ,and transepidermal water loss in the active cosmetic and food supplement group compared with the other three groups. The sebum content and impurity removal improved at 8 weeks only in the active cosmetic and food supplement group. There were no differences noticed regarding the pore size in any group.
A strong increase in the efficacy of the cosmetic products was seen with the addition of the active food supplement, which contains L. plantarum, L. reuteri and L. rhamnosus, D-biotin, and Vitamin A, compared with the placebo food supplement, which contains the active components of D-biotin and Vitamin A only. This finding confirms the efficacy of probiotics (AFPC group) in improving the measured skin health parameters and highlights their synergistic interaction with cosmetic products.
Improvements were self-reported by many subjects, up to 95%, for all parameters, and the proportion of subjects reporting improvements was higher in the active cosmetics and active supplement group compared with the other groups.
The combined use of oral probiotics and topic products is fully supported by the results of this study, with a food supplement supporting active topical products, resulting in significant improvements as early as 1 h, with further improvements over 8 weeks, and with superior results than using the food supplement or topical products individually.
Conceptualization, C.H., G.S. and V.N.; methodology, C.H., V.N. and F.C.; validation, V.N. and F.C.; formal analysis, V.N. and F.C.; investigation, E.C. and F.C.; resources, G.S.; data curation, V.N.; writing—original draft preparation, C.H. and V.N.; writing—review and editing, C.H., V.N. and G.S.; visualization, V.N.; supervision C.H. and V.N.; project administration, V.N. and G.S.; funding acquisition, G.S. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by “Comitato Etico Indipendente per le Indagini Cliniche Non Farmacologiche” (ref. no. 2002/01 by 2 February 2022).
Informed consent was obtained from all subjects involved in the study.
The data presented in this study are available on request from the corresponding author. The data are not publicly available since they are the property of the sponsor of the study (ROELMI HPC Srl, 21040 Origgio, VA, Italy).
The authors would like to express their gratitude to the Complife Italia staff, who contributed to the study and recruited the subjects, for their professionalism and support during study development.
C.H. acts as the Lead for Health and Wellness with financial interests for AWvi.life, the company that manufactures and sells products based on this research output. G.S. is the President of ROELMI Holding, the parent company of the company that sponsored this study. This does not alter the author’s adherence to all the journal policies on sharing data and materials. The other authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Footnotes
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Figure 1 Participant flow chart. AFPC is the active food supplement and the placebo cosmetic product group; PFAC is the placebo food supplement and the active cosmetic product group; AFAC is the active food supplement and the active cosmetic product group; PFPC is the placebo food supplement and placebo cosmetic product group.
Figure 2 (a) Wrinkle depth in the “crow’s feet area”. (b) Skin hydration. (c) Skin radiance. The intragroup (vs. T0) statistical analysis is indicated inside the bars with the symbol *, while the intergroup (between treatment groups) statistical analysis is shown above the bars with the symbol #. The significance levels are as follows: # p < 0.05, ** p < 0.01, and ***/### p < 0.001.
Figure 3 (a) Shannon index. (b) Simpson index. The intragroup (vs. T0) statistical analysis is indicated above the bars with the symbol * as follows: * p < 0.05 and ** p < 0.01.
Baseline and demographic characteristics.
| AFPC (n = 24) | PFAC (n = 24) | AFAC (n = 22) | PFPC (n = 24) | Units | |
|---|---|---|---|---|---|
| Age | 55.9 ± 1.1 | 55.4 ± 1.2 | 53.3 ± 1.3 | 56.3 ± 1.3 | Years |
| Sex | |||||
| Male | 8.3% (2) | 4.2% (1) | 4.5% (1) | 8.3% (2) | % (no.) |
| Female | 91.7% (22) | 95.8% (23) | 95.5% (21) | 91.7% (22) | % (no.) |
| Skin sebum content | 83.5 ± 8.3 | 88.8 ± 8.0 | 96.5 ± 11.1 | 88.9 ± 8.2 | μg/cm2 |
| Skin moisturization | 46.0 ± 1.0 | 47.2 ± 1.5 | 47.9 ± 1.3 | 46.5 ± 1.4 | cu |
| Skin profilometry | |||||
| Wrinkle depth | 305.8 ± 24.3 | 300.9 ± 22.7 | 283.2 ± 17.8 | 275.2 ± 14.6 | μm |
| Skin smoothness (Sa) | 34.4 ± 1.7 | 36.0 ± 1.4 | 36.6 ± 2.0 | 33.8 ± 1.6 | μm |
| TEWL | 13.1 ± 0.8 | 13.9 ± 0.8 | 13.7 ± 0.6 | 12.2 ± 0.5 | g × h−1 × m−2 |
| Skin elasticity | |||||
| Skin firmness, R0 | 0.3910 ± 0.0119 | 0.3833 ± 0.0103 | 0.3880 ± 0.0096 | 0.3689 ± 0.0102 | mm |
| Overall elasticity, R2 | 0.5975 ± 0.0106 | 0.6135 ± 0.097 | 0.6152 ± 0.086 | 0.6273 ± 0.0084 | au |
| Skin radiance | 10.18 ± 0.45 | 10.25 ± 0.42 | 9.78 ± 0.49 | 10.50 ± 0.44 | au |
| Pores | |||||
| Size | 233.8 ± 3.5 | 222.5 ± 1.9 | 227.6 ± 3.6 | 226.2 ± 4.0 | pixel no. |
| Impurities | 57,924.2 ± 12,357.7 | 88,589 ± 16,729.5 | 91,527.6 ± 18,868.7 | 71,706.5 ± 20,629.9 | pixel no. |
Continuous data are expressed as the mean ± SEM; categorical data are expressed as counts and percentages. cu, corneometric units; au, arbitrary units.
Primary endpoints. Data are the mean ± SEM. The intragroup (vs. baseline) statistical analysis is denoted by the symbol * and is reported near the raw data, while the intergroup (active groups vs. PFPC placebo group) statistical analysis is denoted by the symbol # and is reported near the percentage variation, as follows: # p < 0.05, **/## p < 0.01, ***/p < 0.001.
| T0 | T4 | T8 | |
|---|---|---|---|
| Skin moisturization (cu) | |||
| AFPC (n = 24) | 46.0 ± 1.0 | 50.7 ± 1.0 *** | 53.4 ± 1.3 *** |
| PFAC (n = 24) | 47.2 ± 1.5 | 52.8 ± 1.7 *** | 53.6 ± 1.4 *** |
| AFAC (n = 22) | 47.9 ± 1.3 | 55.0 ± 1.3 *** | 57.9 ± 1.4 *** |
| PFPC (n = 24) | 46.5 ± 1.4 | 48.9 ± 1.5 ** | 49.5 ± 1.4 *** |
| Skin sebum content (μg/cm2) | |||
| AFPC (n = 24) | 83.5 ± 8.3 | 77.2 ± 8.2 | 76.5 ± 7.6 |
| PFAC (n = 24) | 88.8 ± 8.0 | 80.6 ± 7.0 | 81.3 ± 6.5 |
| AFAC (n = 22) | 96.5 ± 11.1 | 87.7 ± 10.3 | 77.6 ± 7.2 ** |
| PFPC (n = 24) | 88.9 ± 8.2 | 81.4 ± 6.6 | 81.4 ± 6.8 |
AFPC is the active food supplement and the placebo cosmetic product group; PFAC is the placebo food supplement and the active cosmetic product group; AFAC is the active food supplement and the active cosmetic product group; PFPC is the placebo food supplement and placebo cosmetic product group.
Skin profilometry and TEWL. Data are the mean ± SEM. The intragroup (vs. baseline) statistical analysis is denoted by the symbol * and is reported near the raw data, while the intergroup (active groups vs. PFPC placebo group) statistical analysis is denoted by the symbol # and is reported near the percentage variation, as follows: */# p < 0.05, ** p < 0.01, *** p < 0.001.
| T0 | T4 | T8 | |
|---|---|---|---|
| Wrinkle depth (μm) | |||
| AFPC (n = 24) | 305.8 ± 24.3 | 273.1 ± 20.0 ** | 258.4 ± 19.3 *** |
| PFAC (n = 24) | 300.9 ± 22.7 | 271.6 ± 19.3 ** | 266.0 ± 19.9 ** |
| AFAC (n = 22) | 283.2 ± 17.8 | 253.5 ± 17.6 ** | 233.0 ± 15.3 *** |
| PFPC (n = 24) | 275.2 ± 14.6 | 266.6 ± 14.4 | 263.8 ± 13.5 |
| Skin smoothness (μm) | |||
| AFPC (n = 24) | 34.4 ± 1.7 | 32.9 ± 1.3 | 33.3 ± 1.5 |
| PFAC (n = 24) | 36.0 ± 1.4 | 34.5 ± 1.2 | 34.2 ± 1.4 |
| AFAC (n = 22) | 36.6 ± 2.0 | 34.7 ± 1.9 * | 34.4 ± 2.0 ** |
| PFPC (n = 24) | 33.8 ± 1.6 | 34.3 ± 1.7 | 34.2 ± 1.7 * |
| TEWL (g × h−1 × m−2) | |||
| AFPC (n = 24) | 13.1 ± 0.8 | 12.8 ± 0.7 | 12.1 ± 0.6 ** |
| PFAC (n = 24) | 13.9 ± 0.8 | 13.0 ± 0.7 * | 12.7 ± 0.7 ** |
| AFAC (n = 22) | 13.7 ± 0.6 | 12.7 ± 0.5 ** | 12.2 ± 0.5 *** |
| PFPC (n = 24) | 12.2 ± 0.5 | 12.3 ± 0.6 | 11.9 ± 0.5 |
Skin elasticity. Data are the mean ± SEM. The intragroup (vs. baseline) statistical analysis is denoted by the symbol * and is reported near the raw data, while the intergroup (active groups vs. PFPC placebo group) statistical analysis is denoted by the symbol # and is reported near the percentage variation, as follows: */# p < 0.05, **/## p < 0.01, ***/### p < 0.001.
| T0 | T4 | T8 | |
|---|---|---|---|
| Skin firmness—R0 (mm) | |||
| AFPC (n = 24) | 0.3910 ± 0.0119 | 0.3816 ± 0.0100 * | 0.3719 ± 0.0110 *** |
| PFAC (n = 24) | 0.3833 ± 0.0103 | 0.3683 ± 0.0108 ** | 0.3590 ± 0.0121 *** |
| AFAC (n = 22) | 0.3880 ± 0.0096 | 0.3679 ± 0.0100 *** | 0.3576 ± 0.0093 *** |
| PFPC (n = 24) | 0.3689 ± 0.0102 | 0.3660 ± 0.0098 | 0.3682 ± 0.0113 |
| Overall elasticity—R2 (au) | |||
| AFPC (n = 24) | 0.5975 ± 0.0106 | 0.6107 ± 0.0088 * | 0.6286 ± 0.0094 *** |
| PFAC (n = 24) | 0.6135 ± 0.0097 | 0.6295 ± 0.0101 * | 0.6393 ± 0.0117 *** |
| AFAC (n = 22) | 0.6152 ± 0.0086 | 0.6434 ± 0.0077 *** | 0.6573 ± 0.0066 *** |
| PFPC (n = 24) | 0.6273 ± 0.0084 | 0.6300 ± 0.0087 | 0.6345 ± 0.0097 |
Skin radiance and pores (size and impurities). Data are the mean ± SEM. The intragroup (vs. baseline) statistical analysis is denoted by the symbol * and is reported near the raw data, while the intergroup (active groups vs. PFPC placebo group) statistical analysis is denoted by the symbol # and is reported near the percentage variation, as follows: * p < 0.05, **/## p < 0.01, ***/### p < 0.001.
| T0 | T4 | T8 | |
|---|---|---|---|
| Skin radiance (au) | |||
| AFPC (n = 24) | 10.18 ± 0.45 | 11.11 ± 0.41 *** | 11.93 ± 0.43 *** |
| PFAC (n = 24) | 10.25 ± 0.42 | 11.39 ± 0.41 ** | 12.46 ± 0.57 *** |
| AFAC (n = 22) | 9.78 ± 0.49 | 12.18 ± 0.61 *** | 12.70 ± 0.66 *** |
| PFPC (n = 24) | 10.50 ± 0.44 | 11.00 ± 0.47 * | 11.09 ± 0.45 *** |
| Pore size (pixel no.) | |||
| AFPC (n = 24) | 233.8 ± 3.5 | 229.6 ± 3.4 | 231.6 ± 3.8 |
| PFAC (n = 24) | 222.5 ± 1.9 | 220.7 ± 2.7 | 229.7 ± 3.5 |
| AFAC (n = 22) | 227.6 ± 3.6 | 224.4 ± 3.3 | 225.7 ± 3.1 |
| PFPC (n = 24) | 226.2 ± 4.0 | 230.4 ± 4.2 | 226.3 ± 3.4 |
| Impurities (pixel no.) | |||
| AFPC (n = 24) | 57,924.2 ± 12,357.7 | 50,363.4 ± 8999.1 * | 51,013.1 ± 10,155.9 * |
| PFAC (n = 24) | 88,589.3 ± 16,729.5 | 81,241.0 ± 14,329.2 * | 82,071.6 ± 15,742.2 * |
| AFAC (n = 22) | 91,527.6 ± 18,868.7 | 81,647.6 ± 17,474.8 * | 78,297.3 ± 15,552.1 ** |
| PFPC (n = 23) | 71,706.5 ± 20,629.9 | 66,015.2 ± 18,190.0 | 68,071.7 ± 20,090.5 |
Supplementary Materials
The following supporting information can be downloaded at:
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; Cother, Hajat 2
; Cestone Enza 3
; Cascella Federica 4 ; Santus Giacomo 5 1 R&D Department, Complife Italia S.r.l., 27028 San Martino Siccomario, PV, Italy; [email protected]
2 Real World Health, London SW1 98EF, UK
3 Clinical Trial Department, Complife Italia, 27028 San Martino Siccomario, PV, Italy
4 R&D Department, Complife Italia S.r.l., 27028 San Martino Siccomario, PV, Italy; [email protected], Department of Health Sciences, University of Piemonte Orientale, 28100 Novara, NO, Italy
5 ROELMI Holding, 20020 Solaro, MI, Italy