Diagnosis of early skin aging

Abstract

The present invention relates to a method for diagnosing early skin aging of a subject, in particular pollution-related, comprising step (a): determining the level of at least one marker in a skin sample of the subject, the at least one marker being selected from the group consisting of: a fungus comprising a nucleic acid encoding an ITS1 region sequence ("internal transcribed spacer 1") that is at least 90% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally a fungus comprising a nucleic acid encoding an ITS1 region sequence that is at least 90% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10.

Description

Technical Field

[0001] The present invention relates to a method for diagnosing early skin aging. Background Art

[0002] Some urban areas are often at pollution peaks. People, especially those in urban areas, may be exposed to a variety of harmful effects on keratin materials, especially on the skin, in their daily environment due to different air pollutants.

[0003] Among the known pollutants, mention is first of all the exhaust gases which have become a major concern in large towns and cities, which produce heavy metals but also fine particles containing molecules such as polycyclic aromatic hydrocarbons (for example benzo[a]pyrene or benz[a]anthracene).

[0004] In particular, these pollutants in the skin layers lead to the deposition of particles on the epidermal surface and cause, among other consequences, early skin aging characterized by the appearance of fine lines and / or wrinkles, large macules, freckles simplex, red patches, and / or a dull and / or uneven skin tone. Summary of the invention

[0005] The present inventors have shown that long-term exposure to atmospheric pollution is associated with changes in the skin fungal microbiome and premature skin aging.

[0006] By identifying exposure to pollution as a factor contributing to early skin aging via changes in the skin's fungal microbiome, this aging may be more effectively prevented and / or treated by specifically targeting changes in the fungal microbiome.

[0007] Therefore, diagnostic methods for early skin aging, especially pollution-related, are highly desirable.

[0008] The present invention satisfies this need.

[0009] The present invention arises from the unexpected discovery of the inventors that skin samples from individuals who exhibited premature aging of the skin and were exposed to chronic pollution (based on high levels of pollutants detected in their hair samples) had significantly different levels of certain fungi compared to individuals who did not exhibit premature aging and were not exposed to such pollution.

[0010] Therefore, the present invention relates to a method for diagnosing premature skin aging, in particular pollution-related, in a subject, comprising step (a): determining the level of at least one marker in a skin sample of the subject, in particular a skin sample from the skin surface of the subject, the at least one marker being selected from the group consisting of: a fungus comprising a nucleic acid encoding an ITS1 region ("internal transcribed spacer 1") sequence that is at least 90% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally a fungus comprising a nucleic acid encoding an ITS1 region sequence that is at least 90% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10.

[0011] In a specific embodiment, the at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Emericella, Hypocreales, Mucor, Sporobolomyces, and optionally Malassezia and Cryptococcus.

[0012] In a preferred embodiment, the at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Euglenoma, Hypocreales, Mucor and Sporobolomyces.

[0013] Markers

[0014] The markers used in the context of the present invention are selected from the group consisting of fungi containing a nucleic acid encoding an ITS1 region ("internal transcribed spacer 1") having a sequence at least 90% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally fungi containing a nucleic acid encoding an ITS1 region sequence at least 90% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10.

[0015] In a specific embodiment, the marker used in the context of the present invention is selected from the group consisting of fungi comprising a nucleic acid encoding an ITS1 region sequence that is at least 90% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6.

[0016] "ITS1 region" or "internal transcribed spacer 1" herein refers to the internal transcribed spacer (ITS) DNA sequence of the ribosomal RNA gene region between the gene of the small subunit of the ribosomal RNA (rRNA) and the gene of the large subunit of the ribosomal RNA (rRNA) in the chromosome or the corresponding transcription region in the polycistronic rRNA precursor transcript. More specifically, the ITS1 region is located between rRNA genes 18S and 5.8S in eukaryotes.

[0017] Therefore, the marker used in the context of the present invention can be selected from the group consisting of: a fungus comprising an ITS1 region sequence that is at least 90% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally a fungus comprising an ITS1 region sequence that is at least 90% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10.

[0018] In a specific embodiment, the marker used in the context of the present invention is selected from the group consisting of fungi comprising an ITS1 region sequence that is at least 90% identical to the sequence SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6.

[0019] In the context of the present invention, "percent identity" is calculated using a global alignment (i.e. comparing two sequences over their entire sequences). Methods for comparing the identity of two or more sequences are well known to the skilled person. For example, the "assign taxonomy.py" command in QIIME (version 1.9) on a curated database as described in Findley et al., (2013) Nature 498: 367-370 can be used.

[0020] In a specific embodiment, the marker used in the context of the present invention is chosen from the group consisting of: a fungus comprising a nucleic acid encoding an ITS1 region, in particular a sequence of an ITS1 region that is at least 91% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally a fungus comprising a nucleic acid encoding an ITS1 region, in particular a sequence of an ITS1 region that is at least 91% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10, in particular at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 98%, at least 99%, at least 99.5%, at least 99.9% or at least 100% identical.

[0021] In a specific embodiment, the marker used in the context of the present invention is chosen from the group consisting of fungi containing a nucleic acid encoding the ITS1 region, in particular an ITS1 region sequence that is at least 91% identical to the sequence SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, in particular at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 98%, at least 99%, at least 99.5%, at least 99.9% or at least 100% identical.

[0022] Sequence SEQ ID NO: 1 is a representative sequence of ITS1 of Candida fungi.

[0023] Sequence SEQ ID NO: 2 is a representative sequence of ITS1 of the Sclerotiniaceae family.

[0024] Sequence SEQ ID NO: 3 is a representative sequence of ITS1 of the genus Euglena.

[0025] Sequence SEQ ID NO: 4 is a representative sequence of ITS1 of Hypocreales fungi.

[0026] Sequence SEQ ID NO: 5 is a representative sequence of ITS1 of the genus Mucor.

[0027] Sequence SEQ ID NO: 6 is a representative sequence of ITS1 of the genus Sporobolomyces.

[0028] Sequence SEQ ID NO: 7 is a representative sequence of ITS1 of the fungus genus Malassezia (OTU F11231).

[0029] Sequence SEQ ID NO: 8 is a representative sequence of ITS1 of the fungus genus Malassezia (OTU F4665).

[0030] Sequence SEQ ID NO: 9 is a representative sequence of ITS1 of the fungus genus Malassezia (OTU F495).

[0031] The sequence SEQ ID NO: 10 is a representative sequence of ITS1 of Cryptococcus fungi.

[0032] Thus, in a specific embodiment, the at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Euglenoma, Hypocreales, Mucor, Sporobolomyces, and optionally Malassezia and Cryptococcus.

[0033] In a preferred embodiment, the at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Euglenoma, Hypocreales, Mucor and Sporobolomyces.

[0034] "Candida fungi" herein refers to spherical or oval spore-forming yeasts usually accompanied by mycelial or pseudomycelial filaments, the representative species of which is Candida albicans, which, depending on the species, can form commensals in the oral cavity, skin, digestive system and vaginal flora of healthy humans.

[0035] "Sclerotiniaceae fungi" herein refers to fungi belonging to the order Helotiales, which reproduce by sclerotia or substrate.

[0036] "Eumectomyces fungi" herein refers to the sexual state of fungi of the genus Aspergillus.

[0037] "Hypocreales fungi" herein refers to fungi of the subclass Hypocreales, whose fruiting bodies are perithecia when the sexual state is known.

[0038] "Mucor" refers herein to fungi of the order Mucorales, typically forming fast-growing white to beige or gray colonies and having pores that may be simple or branched and form apical spherical sporangia.

[0039] "Sporidibolus fungi" herein refers to protean yeasts of the order Sporidibolales, the sexual forms of which are included in the genus Sporidibolus.

[0040] "Malassezia fungi" herein refers to yeasts of the Malassezia family that occur naturally on the skin surfaces of many animals, including humans.

[0041] "Cryptococcus fungi" herein refers to yeast of the Tremellaceae family, the sexual or sexual form of which is the genus Filobasidiella.

[0042] Diagnostic Methods

[0043] The diagnostic method of the invention is a method for diagnosing premature skin aging, in particular pollution-related.

[0044] “Early skin aging” refers in particular to the first signs of skin aging that typically affect people in the age range of 25 to 45 years and can be interpreted in particular as the appearance of fine lines, dull skin tone and / or an uneven appearance.

[0045] Early aging of the skin is evidenced by the appearance of fine lines and / or wrinkles, large macules, freckles simplex, red patches, and / or a dull and / or uneven appearance.

[0046] Thus, in specific embodiments, early skin aging includes the presence of fine lines and / or wrinkles, large lentigos, freckles, red patches, and / or a dull complexion and / or uneven appearance.

[0047] The skin is more particularly the skin of the face, in particular the skin of the cheeks and / or forehead, the skin of the collar, the skin of the neck, the skin of the arms and forearms. More preferably, the skin is the skin of the face, in particular the skin of the cheeks and / or forehead.

[0048] In specific embodiments, the premature skin aging is associated with pollution, in particular premature skin aging caused by pollution.

[0049] "Pollution" in this context refers to long-term exposure to particulate matter, particularly polycyclic aromatic hydrocarbons (PAHs).

[0050] In specific embodiments, the pollution is exposure to particulate matter, particularly PAH, which results in the following levels of PAH and PAH metabolites in the subject's hair:

[0051] - 2-OH-phenanthrene at a level at least 1.8-fold higher than the control level;

[0052] - 3-OH-fluorene at a level at least 1.6-fold higher than the control level;

[0053] - 3-OH-phenanthrene at a level at least 1.7-fold higher than the control level;

[0054] - Bb-fluoranthene at a level at least 1.8-fold higher than the control level;

[0055] - Benzo-ghi-perylene at a level at least 1.7-fold higher than the control level;

[0056] - a level of fluoranthene at least 2-fold higher than the control level; and / or

[0057] - pyrene levels at least 1.6 times higher than the control level,

[0058] The control level is typically the level of the compound in the hair of a subject living in a low pollution city, particularly a city with fewer than 100 days (particularly fewer than 85 days) in a year with an air quality index below 100.

[0059] The diagnostic method of the invention comprises the step (a) of determining, in a skin sample, in particular a surface skin sample, of a subject, the level of said at least one marker selected from the group consisting of fungi as defined in the "Markers" section above.

[0060] In specific embodiments, the level of said at least one marker in the sample is the relative abundance of said at least one marker in the sample.

[0061] "Relative abundance" herein refers to the relative amount, expressed as a percentage, of a given taxon in a sample relative to the total number of taxa.

[0062] Any suitable technique may be used to determine the level of the at least one marker.

[0063] In a specific embodiment, the level of said at least one marker, in particular the relative abundance of said at least one marker is determined by measuring the level of the corresponding ITS1 DNA region.

[0064] Preferably, the level of said at least one marker is determined by PCR amplification combined with sequencing, in particular high throughput sequencing, of the ITS1 DNA region.

[0065] Typically, fungal genomic DNA present in the skin sample is extracted and then subjected to PCR using primers targeting the fungal ITS1 DNA region, in particular as described in Leung et al., (2016) Microbiome 4: 46. The obtained ITS1 DNA amplicons are sequenced to enable identification of the corresponding fungi and measurement of the relative abundance of each identified fungal ITS1 DNA.

[0066] In a specific embodiment, the diagnostic method of the present invention further comprises the steps consisting of:

[0067] (b) comparing the level of the at least one marker measured in step (a) with a control;

[0068] (c) determining, based on the comparison in step (b), whether the subject's skin exhibits premature aging, in particular pollution-related.

[0069] In specific embodiments, the control is a reference value.

[0070] In a specific embodiment, the reference value is determined by the mean value of the level of said marker in a defined population, such as a defined age group and / or a population with a defined skin type.

[0071] In a specific embodiment, the reference value is the average value of the marker level in a group of subjects living in a low-pollution city, in particular in a city with less than 100 days (in particular less than 85 days) in a year with an air quality index below 100, in particular as defined below.

[0072] In specific embodiments, the subject's skin is diagnosed as exhibiting premature aging, particularly related to pollution, if:

[0073] - the level of Candida fungi measured in the subject's skin sample, in particular its relative abundance is higher than a control level (in particular significantly higher than a control level);

[0074] - the level of Sclerotiniaceae fungi measured in the subject's skin sample, in particular its relative abundance is higher than a control level (in particular significantly higher than a control level);

[0075] - the level of Euglena spp. fungi measured in the subject's skin sample, in particular its relative abundance is higher than a control level (in particular significantly higher than a control level);

[0076] - the level of Hypocreales fungi measured in the subject's skin sample, in particular the relative abundance thereof is higher than a control level (in particular significantly higher than a control level);

[0077] - the level of Mucor fungi measured in the subject's skin sample, in particular its relative abundance is higher than a control level (in particular significantly higher than a control level);

[0078] - the level of Sporobolomyces fungi measured in the subject's skin sample, in particular its relative abundance is higher than a control level (in particular significantly higher than a control level);

[0079] - the level of Malassezia fungus measured in the subject's skin sample, in particular its relative abundance is lower than a control level (in particular significantly lower than a control level); and / or

[0080] - the level of Cryptococcus fungi measured in the skin sample of the subject, in particular its relative abundance is lower than the control level (in particular significantly higher than the control level),

[0081] The control level is typically the level of the marker (particularly the relative abundance of the marker) in skin samples from subjects living in low-pollution cities, particularly cities with fewer than 100 days (particularly fewer than 85 days) in a year with an air quality index below 100.

[0082] The marker level is usually determined by measuring the level of the corresponding ITS1 DNA region, in particular by PCR amplification combined with sequencing of the ITS1 DNA region, typically as described above.

[0083] In the meaning of the present invention, "significantly lower than" means that the marker level is statistically significantly reduced compared to the control level.

[0084] In the meaning of the present invention, "significantly higher than" means that the marker level is increased statistically significantly compared to the control level.

[0085] In a preferred embodiment, the skin sample of the subject used in the diagnostic method of the present invention is a sample collected (preferably non-invasively) from the subject's skin, preferably the subject's face, especially the subject's cheek and / or forehead. Preferably, the skin sample is from the stratum corneum, especially from the surface of the stratum corneum.

[0086] The stratum corneum is the layer farthest from the epidermis and includes the surface of the skin. It is composed mainly of dead cells.

[0087] In one embodiment, the diagnostic method of the present invention comprises the step of collecting a skin sample from a subject, in particular from the surface of the subject's skin. This step is preferably performed in a non-invasive manner, in particular without the need for local anesthesia.

[0088] In a preferred embodiment, the sample collection step is performed by rubbing the skin surface, in particular with a wet cotton swab.

[0089] In a specific embodiment, the skin sample is therefore collected by abrading the skin surface.

[0090] "Subject" herein refers to a human being, preferably a human being between the ages of 25 and 45. Preferably, the subject is a female. Preferably, the subject is of Asian type.

[0091] In a specific embodiment, the subject is between 25 and 45 years old.

[0092] The present invention also relates to a method for the cosmetic treatment of skin in a subject showing premature aging, in particular pollution-related, comprising the following steps:

[0093] A) diagnosing a subject as exhibiting premature skin aging, in particular associated with pollution, by implementing the diagnostic method of the present invention;

[0094] B) If the subject is diagnosed as showing premature skin ageing, in particular related to pollution, treating the skin of said subject with a cosmetic composition capable of reducing and / or slowing down premature skin ageing.

[0095] In a particular embodiment, the cosmetic composition used in the treatment method of the present invention comprises probiotics and / or prebiotics, in particular probiotics and / or prebiotics capable of promoting the presence of commensal flora.

[0096] The invention is described in more detail in the figures and examples given below.

[0097] Sequence Description

[0098]

[0099]

[0100] BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 Fungal clusters and early aging are shown. Grey circles correspond to individuals with wrinkles and pigmentation spots. The ellipse on the left corresponds to the cluster: "Early aging": n (total) = 90 (53 Baoding / 37 Dalian) 59% vs. 41%. DETAILED DESCRIPTION

[0102] Example

[0103] The following example illustrates the identification of a signature comprising eight fungi that were significantly regulated in skin samples from individuals exposed to chronic pollution (based on high levels of pollutants detected in hair samples from the individuals).

[0104] Materials and methods

[0105] Main steps:

[0106] - Skin sampling

[0107] - Analysis of ITS1 rDNA of fungi

[0108] - Determine the relative abundance of microbiome markers

[0109] -Statistical research

[0110] -Diagnosis of early skin aging.

[0111] Subject Description

[0112] In Baoding and Dalian (China), all subjects in each city came to the facility. Skin samples were collected from 204 Chinese women aged 25 to 45 years in good health, of whom 102 lived in Hebei Province and recorded high levels of air pollution (about 90 μg PM 2.5 / m 3 The 102 residents living in Liaoning province recorded lower levels of air pollution (about 30 μg PM 2.5 / m 3 Air) and the modern city of Dalian (a city in northern China). These cities are located in the same latitude zone and have shared similar climates and equal UV exposure (UV index) over the past 15 years.

[0113] The exposure to PAH (polycyclic aromatic hydrocarbons) in 12 cm hair samples of participants living in the two cities was assessed (reflecting exposure over a one-year period) (Palazzi et al., (2018) Env. Int. 121: 1341-1354). Specifically, in Baoding, the median concentration of parent PAHs was 1.5 to 2.8 times that of Dalian and the median concentration of PAH metabolites was 1.1 to 2.3 times that of Dalian. Among the quantified parent PAHs, higher levels of phenanthrene, fluoranthene, pyrene, fluorene, acenaphthene, and anthracene were observed, while for PAH metabolites, higher levels of 9-OH fluorene, 2-OH-naphthalene, and 1-OH-anthracene were observed (Palazzi et al., (2018) Env. Int. 121: 1341-1354).

[0114] At the clinical level, an increase in the severity of almost all facial symptoms (including wrinkles and pigmentary disorders) was observed in individuals living in Baoding. In addition, a discriminant analysis of the subjects was performed using dermatological assessment data (Bourokba et al., poster presented at the 76th Annual Meeting of the Society for Investigative Dermatology, April 26-29, 2017, Portland, Oregon). This analysis resulted in the definition of an "early aging" cluster, corresponding to n = 90 women out of 204 (53 in Baoding and 37 in Dalian). The average age of these women was 36 years, and they showed increased levels of wrinkles and pigmentary diseases (macro-rashes, simple freckles, red plaques).

[0115] Subjects and sample collection

[0116] Participants had not taken systemic antibiotics or antifungal drugs within 1 month before sampling, had no serious skin diseases, had not used skin or systemic depigmentation / whitening treatments within 3 months before sampling, or had not used exfoliating products within 1 month before sampling. They were asked to wash their faces (once a day) with the provided neutral soap without any antibacterial compounds 3 days before sampling. The last hair washing and the last face washing were 48 hours and 24 hours before sampling, respectively. No other products were allowed on the scalp, hair, and face before sampling.

[0117] Microbiome sampling was performed at 22°C and 60% humidity in a room with a controlled atmosphere. Samples for microbiome analysis were collected using dry sterile cotton swabs heated to 150°C and pre-moistened with ST solution (0.15M NaCl containing 0.1% Tween 20). For cheek samples, the swab was immersed in the collection buffer and rubbed vigorously on the cheek for 60 seconds to cover a surface of 1 cm × 2 cm. After sampling, each cotton swab was placed in a microtube, immediately frozen in liquid nitrogen, and stored at -80°C before genomic DNA (gDNA) extraction.

[0118] Analysis of fungal ITS1 rDNA

[0119] - Preparation of amplicon samples for ITS sequencing.

[0120] Using PowerSoil gDNA was extracted using the ITS1 isolation kit (MO BIO Laboratories, Carlsbad, CA, USA) following modified manufacturer instructions (as described in Leung et al., (2014) Appl. Environ. Microbiol. 80:6760-6770). In addition, after C6 elution, the eluate was passed through the same column filter for an additional time to increase yield. A negative water control containing no DNA was extracted in parallel. PCR was performed in triplicate for each gDNA sample using primers targeting the ITS1 region as described in Leung et al., (2016) Microbiome 4:46. For analysis of the ITS1 region, amplicon PCR and index PCR were prepared on a PCR 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA), and the amplicons were purified using DNA / RNA purification beads (SeqMatic, Fremont, CA, USA). Library preparation and 250 bp of fungal nucleic acid were analyzed on an Illumina Paired-end sequencing on the platform was performed by SeqMatic LLC (Fremont, CA, USA).

[0121] - Processing and bioinformatics analysis of ITS sequences

[0122] Fungal reads paired separately in fastq format were merged using the "-fastq_mergeairs" command in USEARCH. The merged reads were filtered for quality control using the "-fastq_filter" command in USEARCH with a maximum expected error rate of 0.01. The merged reads were cut off at 450 bp and the shortest reads were discarded. The filtered reads were OTU grouped using the UPARSE algorithm at 97% sequence identity (Edgar (2013) Nature Methods 10: 996-998). Fungal OTUs were queried on an organized fungal database designed to monitor the skin microbiome (Findley et al., (2013) Nature 498: 367-370). Chimeras were detected using UCHIME2 (Edgar (2016) bioRxiv 074252) in high confidence mode. OTUs from taxonomic lines present in more than 5% of negative controls were considered potential contaminants (Leung et al., (2018) Microbiome 6:26) and removed from the dataset. In addition, chimeric OTUs, chloroplasts, and mitochondria were removed. After quality control and removal of undesirable reads, a total of 14,649,172 fungal reads were retained.

[0123] Statistical analysis

[0124] Two statistical methods were used: hypothesis testing on OTU abundance and multivariate analysis using hierarchical multiblock analysis (MAXVAR-A).

[0125] The results of these tests are qualitative: normal skin or skin showing early aging.

[0126] - Method 1: Compare the abundance of OTUs for each marker or combination.

[0127] In the processing of relative abundance data, the relative abundance of OTUs was pre-filtered. OTUs with a relative abundance of less than 0.1% in all individuals were discarded. In addition, CSS ("Cumulative Sum Scale") normalization was applied, which corrected the bias in differential abundance assessment caused by TSS ("Total Sum Scale") normalization. CSS normalization of data was implemented using the R package metagenomeSeq (http: / / www.cbcb.umd.edu / software / metagenomeSeq).

[0128] The mean difference in OTU abundance between the two groups was evaluated by a statistical test procedure using the v-test. The v-test value corresponds to the comparison between the mean OTU abundance in the group of interest (i.e., early aging) (column: mean of the class) and the mean OTU abundance of the total population (column: overall mean). Positive values ​​indicate a higher abundance of OTUs in the group of interest, and negative values ​​indicate a lower abundance. The p-value associated with each v-test value was also calculated (column: p-value).

[0129] The mean OTU abundance was calculated for subjects outside the “early aging” group (column: mean of cluster 1.3.4). The CSS-normalized OTU abundance and thresholds for each group are given in the table below.

[0130]

[0131] - Method 2: The relative abundance profiles of fungi associated with the historical grouping of subjects were compared with PAH compounds (Baoding / Dalian database).

[0132] Regarding the global correlation analysis with PAH, the relative abundance of OTUs was pre-filtered. OTUs with a relative abundance lower than 0.1% in all individuals were removed. In addition, CSS normalization (“cumulative sum scaling”) was applied, which corrects the bias of differential abundance assessment caused by TSS (“sum scaling”) normalization. Among the OTUs, 69 were selected for fungi. PAH measurements were log-transformed to follow a Gaussian distribution. A total of 202 individuals with OTU and PAH data were included in the analysis. Taking into account the variable selection, sparse canonical correlation analysis (sCCA) was performed to select OTUs and PAH descriptors that were active in the relationship between blocks. The sparsity parameters of sCCA were selected by a permutation procedure using the MutiCCA.permute function of the PMD R package (Witten et al., (2009) Biostatistics 10:515-534; Tenenhaus et al., (2014) Biostatistics15:569-583). Finally, to obtain a common representation of individuals in the two blocks, hierarchical multi-block analysis (MAXVAR-A) was performed using the RGCCA R package (Tenenhaus et al., (2017) Psychometrika 82:737-777). Figure 1 Circle the middle.

[0133] For diagnosis, the new spectrum must be compared to the grouping. If the new spectrum is contained within the ellipse on the left, the subject tests positive and exhibits early skin aging. Sequence Listing <110> L'Oreal <120> Diagnosis of early skin aging <130> BET 20P1981 <150> FR19 06830 <151> 2019-06-24 <160> 10 <170> PatentIn 3.5 <210> 1 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequences of Candida species <400> 1 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcatta cagaatgaaa 60 agtgcttaac tgcatttttt cttacacatg tgtttttctt tttttgaaaa ctttgctttg 120 gtaggccttc tatatggggc ctgccagaga ttaaactcaa ccaaatttta tttaatgtca 180 accgattatt taatagtcaa aactttcaac aacggatctc ttggttctcg catcgatgaa 240 gaacgcagcg 250 <210> 2 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Sclerotiniaceae <400> 2 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcatta cagagttcat 60 gcccgaaagg gtagacctcc cacccttgtg tattattact ttgttgcttt ggcgagctgc 120 cttcgggcct tgtatgctcg ccagagaata ccaaaactct ttttattaat gtcgtctgag 180 tactatataa tagttaaaac tttcaacaac ggatctcttg gttctggcat cgatgaagaa 240 cgcagcgaaa 250 <210> 3 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Emericella <400> 3 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcattg tcgtgaccct 60 gaccaaaaca gaccgcgcac gcgtcatcca atccgtcggc gacggcaccg tccgtcgctc 120 ggccaatgcc tcgaccacct cccctcctcg gagcgggtgg gggctcgggg taaaagaacc 180 cacggcgccg aaggcgtcaa ggaacactgt gcctaacccg ggggcatgtc tagcttgcta 240 gccgtccctc 250 <210> 4 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Hypocreales <400> 4 gtaaaagtcg taacaaggtt tccgttggtg aaccagcgga gggatcatta tagagtgtaa 60 actccctaac ctttgtgaac atacctgttg cttcggcggt cctcaccggc cgccgaaggc 120 ctatattctt gaatttacat gaatttctga gtatcaaaca aaaataaata aaaactttca 180 gcaacggatc tcttggctct ggcatcgatg aagaacgcag cgaaatgcga taagtaatgt 240 gaattgcaga 250 <210> 5 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Mucor <400> 5 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcatta aataatcaat 60 aattttggct tgtccatcat tatctattta ctgtgaaacg tattattact tgacgcctga 120 gggatgttcc actgctataa ggataggcag cggaaatgtt aaccgagtca taatcaagct 180 taggcttggt atcctattat tatttaccaa aagaattcag aattaatatt gtaacataga 240 cgtaaaaaat 250 <210> 6 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Sporobolomyces <400> 6 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcatta gtgaataaat 60 agggtgtcca atttaacttg gaacccgacc ttctcacatc taaccctgtg catctgtata 120 taatggcgag caattttcga attgtgagcc atttcacttt ataaacacta gtctatgaat 180 gtaaaatttt tataacaata aaaactttca acaacggatc tcttggctct cgcatcgatg 240 aagaacgcag 250 <210> 7 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequence of Malassezia (OTU F11231) <400> 7 gtaaaagtcg taacaaggtt tctgtaggtg aatctgcagg aggatcatca gtgatgattt 60 gggcaggcca tacggacgcc aaaaagtgtc cctggccgcc tacacccact atacatccac 120 aaacccgtgt gcactgcctt ggagaaaggc ttcagagaag tttttgtggc ctctcttggg 180 gtctttcttc gctacagact cgaatggtta gtatgaacgt ggaacttggt tggaccgtca 240 ctggccaaaa 250 <210> 8 <211> 250 <212> DNA <213> Artificial sequence <220> <223> Another ITS1 sequence of Malassezia (OTU F4665) <400> 8 gtaaagtcgt aacaaggttt ctgtaggtga acctgcagaa ggatcattag tgaagatttg 60 ggctggccat acggacgcca aaaagtgtcc ctggccgcct ccgcccacta tacctccaca 120 aacccgtgtt cactgtcttg gagaaaggct tcagagaagt tttttgtggc ctctcttggg 180 gtctttcttc gctacaaaat cgaatggtta gtatgaacgt ggaacttggt tggaccgtca 240 ctggccaaca 250 <210> 9 <211> 250 <212> DNA <213> Artificial sequence <220> <223> Another ITS1 sequence of Malassezia (OTU F495) <400> 9 gtaaaagtcg taacaaggtt tctgtaggtg aacctgcaga aggatcatta gtgaagattt 60 gggcaggcca tacggacgcc acaaagtgtc cctggccgcc tacacccact atacatccac 120 aaacccgtgt gcactgtctt ggagaaaggc ttcttgagaa gttttgtggc ctctcttggg 180 gtctttcttc ttcgctacaa actcgaatgg ttagtatgaa cgtggaactt ggttggaccg 240 tcactggcca 250 <210> 10 <211> 250 <212> DNA <213> Artificial sequence <220> <223> ITS1 sequences of Cryptococcus <400> 10 gtaaaagtcg taacaaggtt tccgtaggtg aacctgcgga aggatcatta atgaatttag 60 attgaaccat aggcgaaagc cagtggttct tctttcatat ccataacacc tgtgcactgt 120 tggatgcttg catccacttt taaactaaac attattgtaa caaatgtagt cttattataa 180 cataataaaa ctttcaacaa cggatctctt ggctctcgca tcgatgaaga acgcagcgaa 240 atgcgataag 250

Claims

1. A method for determining pollution-related premature skin aging in a subject, the method being directed to non-diagnostic purposes, comprising the step (a): determining the level of at least one marker in a skin sample of the subject, the at least one marker being selected from the group consisting of a fungus comprising a nucleic acid encoding an ITS1 region ("internal transcribed spacer 1") sequence that is at least 95% identical to the sequence of SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5 or SEQ ID NO: 6, and optionally a fungus comprising a nucleic acid encoding an ITS1 region sequence that is at least 95% identical to the sequence of SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9 or SEQ ID NO: 10, in, The pollution refers to long-term exposure to polycyclic aromatic hydrocarbons (PAHs).

2. The method according to claim 1, wherein: The at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Euglenoma, Hypocreales, Mucor, Sporobolomyces, and optionally Malassezia and Cryptococcus.

3. The method according to claim 1, wherein: The at least one marker is selected from the group consisting of Candida, Sclerotiniaceae, Euglenoma, Hypocreales, Mucor and Sporobolomyces.

4. The method according to claim 1, wherein: The method further comprises the steps consisting of: (b) comparing the level of the at least one marker measured in step (a) with a control; and (c) determining whether the subject's skin exhibits early aging based on the comparison in step (b).

5. The method according to any one of claims 1 to 4, wherein: The level of the at least one marker is determined by measuring the level of the corresponding ITS1 DNA region.

6. The method according to claim 5, wherein: The level of said at least one marker is determined by PCR amplification combined with sequencing of said ITS1 DNA region.

7. The method according to any one of claims 1 to 4, wherein: The skin sample is collected by rubbing the skin surface.

8. The method according to any one of claims 1 to 4, wherein: The subjects were between 25 and 45 years old.

9. The method according to any one of claims 1 to 4, wherein: Early aging includes the presence of fine lines and / or wrinkles, and / or a dull and / or uneven skin tone.

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