Method for detecting deterioration of skin surface shape due to dryness

Abstract

To provide a method for detecting a deterioration of a skin surface shape due to dryness.SOLUTION: The present invention provides a marker for detecting a deterioration of a skin surface shape due to dryness, and a method for detecting a deterioration of a skin surface shape due to dryness using the marker.SELECTED DRAWING: None

Description

Technical Field

[0001] The present invention relates to a marker for detecting deterioration of the skin surface shape due to drying, and a method for detecting deterioration of the skin surface shape due to drying using the same.

Background Art

[0002] Normal skin has a function (moisturizing function) to retain moisture. With this moisturizing function, the skin can maintain flexibility, maintain its barrier function, and stay in good condition. On the other hand, when the skin is exposed to a low humidity environment or the skin moisturizing function deteriorates and the skin dries, the state of the skin deteriorates and rough skin occurs. The skin is located in the outermost layer of the human organs and is more easily affected by the surrounding environment than other organs. For example, when a healthy human stays in a thermo-hygrostat with a low humidity environment (relative humidity 20%, 23°C) for 6 hours, it has been reported that the indices of wrinkles and surface roughness on the facial area and the index of the amount of water in the stratum corneum deteriorate (Non-Patent Documents 1 and 2). Thus, even for a short time, exposure of the skin to a low humidity environment is considered to cause skin dryness and lead to skin problems in terms of beauty and health such as deterioration of the skin surface shape.

[0003] As conventional methods for evaluating skin dryness, there are methods of pressing a probe against the skin surface to obtain objective numerical values for the amount of water in the stratum corneum (Capacitance value, Conductance value) and the amount of transdermal water loss (Trans Epidermal Water Loss; TEWL value). Also, there are methods of obtaining numerical values of the skin surface shape (Surface Evaluation of Living Skin; SELS parameters) using a dedicated probe with a camera, methods of creating a replica of the skin surface using an impression material and digitizing wrinkles and surface roughness using an optical device, and methods of visually evaluating the degree of skin dryness by a professional panelist based on a predetermined index.

[0004] Furthermore, methods have been reported for evaluating skin dryness based on biological indicators such as nucleic acid and protein expression in biological samples, in addition to quantifying phenotypes (phenotypes) that appear in findings and subjective perceptions using instruments or visual inspection (Patent Document 1 and Non-Patent Document 3). This is expected to lead to highly accurate and efficient evaluation of dryness based on biological indicators and the provision of anti-dryness technologies.

[0005] In recent years, technologies have been developed to investigate the current and future physiological state of the human body by analyzing nucleic acids such as DNA and RNA in biological samples. Nucleic acids derived from living organisms can be extracted from bodily fluids such as blood, secretions, and tissues. More recently, it has been reported that RNA contained in skin surface lipids (SSL) can be used as a biological indicator for biological analysis (Patent Document 2). [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2015-227865 [Patent Document 2] International Public Gazette No. 2018 / 008319 [Non-patent literature]

[0007] [Non-Patent Document 1] Tsukahara et al. Skin Res Technol. 13:184-188, 2007. [Non-Patent Document 2] Egawa et al. Skin Res Technol. 8:212-218, 2002. [Non-Patent Document 3] Delattre et al. Exp Dermatol. 21:205-210, 2012. [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] The present invention relates to providing a marker for detecting deterioration of skin surface shape due to drying, and a method for detecting deterioration of skin surface shape due to drying using the same. [Means for solving the problem]

[0009] The present invention provides a method for detecting deterioration of skin surface shape due to dryness in a subject, comprising measuring the expression level of at least one selected from the group consisting of the following genes in the subject: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, OVCA2, COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes, and comparing it with a reference value. The present invention also provides a marker for detecting deterioration of skin surface shape due to drying, comprising at least one selected from the group consisting of the aforementioned gene and the expression product of the gene. [Effects of the Invention]

[0010] The marker for detecting deterioration of skin surface shape due to dryness according to the present invention provides an indicator for detecting deterioration of skin surface shape due to dryness. By using this marker, it becomes possible to easily detect deterioration of the skin surface shape due to dryness in a subject, and consequently, it becomes possible to accurately understand the subject's skin condition and provide skin condition improvement technology suitable for the subject. [Brief explanation of the drawing]

[0011] [Figure 1] Changes in SEsm values ​​before and after dryness stimulation in a low-humidity environment in subjects. [Modes for carrying out the invention]

[0012] All patent, non-patent, and other publications cited herein are incorporated herein by reference in their entirety.

[0013] In this specification, the terms “nucleic acid” or “polynucleotide” mean DNA or RNA. DNA includes cDNA, genomic DNA, and synthetic DNA, and RNA includes total RNA, mRNA, rRNA, tRNA, non-coding RNA, and synthetic RNA.

[0014] In this specification, "gene" means any double-stranded DNA including human genomic DNA, single-stranded DNA including cDNA (positive strand), single-stranded DNA having a sequence complementary to the positive strand (complementary strand), and fragments thereof, in which the sequence information of the bases constituting the DNA contains some kind of biological information. Furthermore, the term "gene" in this specification includes not only "genes" represented by a specific base sequence, but also their congeners (i.e., homologs or orthologs), variants such as genetic polymorphisms, and derivatives.

[0015] In this invention, the term "expression product" of a gene is a concept that encompasses both the transcript and the translation product of a gene. A "transcript" is RNA produced by transcription from a gene (DNA), and a "translation product" is a protein encoded by a gene that is synthesized through translation based on RNA.

[0016] The gene names (Gene Symbols) and Gene IDs disclosed herein follow the Official Symbols and Gene IDs listed on the NCBI ([www.ncbi.nlm.nih.gov / ]).

[0017] As used herein, "skin surface lipids (SSL)" refers to the lipid-soluble fraction present on the skin surface, and is sometimes referred to as sebum. Generally, SSL mainly contains secretions secreted from exocrine glands such as sebaceous glands in the skin, and exists on the skin surface in the form of a thin layer covering the skin surface.

[0018] As used herein, "skin" is a general term for a region including the stratum corneum, epidermis, dermis, hair follicles, and tissues such as sweat glands, sebaceous glands, and other glands, unless otherwise specified. Preferably, it is human skin.

[0019] As used herein, "dryness" can also be described in terms such as a dry environment, a low-humidity environment, a dry state, a low-humidity state, the dry state of the atmosphere, the dry state of the air, or the dry state of a space. Specifically, it refers to a state where the relative humidity is 40 ± 5% or less, preferably 30 ± 5% or less, and more preferably 20 ± 5% or less. Also, the relative humidity is preferably the relative humidity at a temperature of 23 ± 2°C.

[0020] As used herein, "skin surface shape" refers to the state of the skin surface that can be visually recognized by a subject or a judge, or the state of the skin surface that can be detected from a skin surface image taken by a device, and examples of indicators include "smoothness", "roughness", "wrinkles", and "scales". More specifically, "smoothness" is the height difference between the skin grooves and skin ridges detected from the skin surface image, "roughness" is the width of the skin grooves detected from the skin surface image, "wrinkles" is the average width of the wrinkles detected from the skin surface image, and "scales" is the ratio of the bright images derived from the dried and curled stratum corneum in the entire skin surface image. For example, the score values of SELS parameters calculated by subjecting a skin surface image taken by a commercially available device, VisioScan (Courage + Khazaha), to the SELS program can be used. Examples of such score values include "SEsm (smoothness)", "SEr (roughness)", "SEw (wrinkles)", and "SEsc (scales)". Here, "deterioration of the skin surface shape" means that the state of the above-mentioned skin surface or skin surface image changes in an unfavorable direction. Preferably, the height difference between the skin grooves and skin ridges detected from the skin surface image indicating "smoothness" increases, the width of the skin grooves detected from the skin surface image indicating "roughness" increases, the average width of the wrinkles detected from the skin surface image indicating "wrinkles" increases, and the ratio of the high-brightness images in the entire skin surface image indicating "scales" increases. For example, in the score values of the SELS parameters, it refers to the deterioration of the above indicators such as an increase in the SEsm value, an increase in the SEr value, an increase in the SEw value, and an increase in the SEsc value. In the present invention, "deterioration of the skin surface shape" more preferably means that the height difference between the skin grooves and skin ridges detected from the skin surface image indicating "smoothness" increases, and it refers to an increase in the SEsm value among the score values of the SELS parameters.

[0021] In this specification, "detection" of the deterioration of the skin surface shape can also be paraphrased using terms such as inspection, measurement, determination, or evaluation support. Note that the terms "detection", "inspection", "measurement", "determination", or "evaluation" of the deterioration of the skin surface shape in this specification do not include the diagnosis of the deterioration of the skin surface shape by a doctor.

[0022] (1. Marker for detecting deterioration of skin surface shape due to dryness) As shown in the examples described later, the inventors examined the skin surface morphology (SEsm value) of subjects with healthy skin conditions before and after dryness stimulation in a low-humidity environment. As a result, it was confirmed that the SEsm value significantly increased after dryness stimulation compared to before, indicating a deterioration in skin surface morphology. Furthermore, when the changes in skin surface morphology and RNA expression levels in SSL before and after dryness stimulation in a low-humidity environment were analyzed, genes were found that showed a negative or positive correlation between the change in expression level before and after stimulation and the change (increase) in the subject's skin surface morphology index (SEsm value). Such genes or their expression products reflect the deterioration of skin surface morphology due to dryness and can be used as markers to detect the deterioration of skin surface morphology due to dryness in subjects. For example, it becomes possible to detect whether or not a subject's skin surface morphology has deteriorated using the change in expression level of the gene or its expression product as an indicator, or to detect the degree of deterioration of skin surface morphology using the amount of change in the expression level as an indicator.

[0023] Accordingly, in one embodiment, the present invention provides a marker for detecting deterioration of skin surface shape due to dryness. In one embodiment, the marker for detecting deterioration of skin surface shape due to dryness provided in the present invention (hereinafter also referred to as the marker of the present invention) makes it possible to detect whether or not a subject has deteriorated or the degree of deterioration of skin surface shape due to dryness by comparing its expression level, measured for the subject, with a reference value, as will be described later. In a preferred example of this embodiment, the skin surface shape in which deterioration is detected by the marker of the present invention is a skin surface shape corresponding to an index of the height difference between skin furrows and skin ridges detected from a skin surface image, for example, the SEsm value.

[0024] The markers of the present invention may include at least one selected from the group consisting of 21 genes in total, namely the 16 genes shown in Table 1A and the 5 genes shown in Table 1B, and their expression products. Hereinafter, the genes and expression products shown in Table 1A will be collectively referred to as the markers of Table 1A, and the genes and expression products shown in Table 1B will be collectively referred to as the markers of Table 1B. The markers of the present invention may be the genes shown in Table 1A or Table 1B below, their expression products, or a combination thereof. In one embodiment, the marker of the present invention is a nucleic acid marker such as the DNA of the gene or its transcript, RNA. In another embodiment, the marker of the present invention is a protein marker which is the translation product of the gene. Preferably, the marker of the present invention is a nucleic acid marker.

[0025] [Table 1]

[0026] The genes shown in Tables 1A and 1B include those consisting of nucleotide sequences registered in NCBI, as well as those consisting of sequences substantially identical to those registered, insofar as the expression products themselves or derived therefrom function as markers for detecting deterioration of skin surface shape due to dryness. Here, substantially identical sequences mean sequences that, for example, when searching using the homology calculation algorithm NCBI BLAST with the conditions expected value = 10; gap allowed; filtering = ON; match score = 1; mismatch score = -3, have 90% or more, preferably 95% or more, more preferably 98% or more, and even more preferably 99% or more identity with the nucleotide sequence of the gene in question.

[0027] As shown in the examples described later, the markers in Table 1A showed a negative correlation between the change in expression level before and after dryness stimulation in a low-humidity environment and the change (increase) in SEsm value before and after dryness stimulation in a low-humidity environment. In other words, the markers in Table 1A are negative markers in which the change in expression level is negatively correlated with the amount of deterioration of skin surface shape due to dryness. On the other hand, the markers in Table 1B showed a positive correlation between the change in expression level before and after dryness stimulation in a low-humidity environment and the change (increase) in SEsm value before and after dryness stimulation. In other words, the markers in Table 1B are positive markers in which the change in expression level is positively correlated with the amount of deterioration of skin surface shape due to dryness. In the present invention, either the former negative markers or the latter positive markers may be used, or both may be used in combination.

[0028] As shown in the examples described later, when we searched for literature information using Elsevier Text Mining, none of the markers in Tables 1A and 1B had been previously reported to be associated with dry skin (a word registered in the taxonomy of "dry skin" or "xerosis"). On the other hand, it is known that in dry skin (or a state of dry skin), the expression or function of genes related to epidermal keratinization or their expression products decreases (J Am Acad Dermatol. 55:263-8, 2006., J Invest Dermatol. 124:1099-110, 2005.), and that reactive oxygen species scavenging agents improve dry skin (Skin Pharmacol Physiol. 31:188-197, 2018.). However, as shown in the examples described later, not all genes involved in epidermal keratinization or reactive oxygen species stress response necessarily experience decreased expression in dry skin. Therefore, it is difficult to predict which specific genes will experience decreased expression when healthy skin is subjected to dryness. Considering the conventional knowledge regarding skin dryness, epidermal keratinization, and reactive oxygen species stress response, the technology provided by the present invention, which uses at least one marker selected from Tables 1A and 1B as a detection marker for deterioration of skin surface shape due to dryness, is entirely unexpected and difficult to discover. Furthermore, among these markers, FLOT2, which is involved in epidermal keratinization, and CFLAR, which is involved in the reactive oxygen species stress response, have not been previously reported to be associated with skin dryness, and are related to known molecular mechanisms such as epidermal keratinization and the reactive oxygen species stress response. Therefore, they are considered to be more useful as detection markers for deterioration of skin surface shape due to dryness.

[0029] In a preferred embodiment, the marker of the present invention is a marker for detecting the presence or absence of deterioration of the skin surface shape due to dryness. The marker comprises at least one selected from the group consisting of the following genes: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, and OVCA2, and the expression products of these genes, preferably at least one selected from the group consisting of FLOT2 and CFLAR, and the expression products of these genes. These markers are negative markers included in Table 1A. Changes in the expression levels of these negative markers show a negative correlation with the presence or absence of deterioration of skin surface morphology due to dryness, for example, changes in SEsm values.

[0030] In another preferred embodiment, the marker of the present invention is a marker for detecting the presence or absence of deterioration of the skin surface shape due to dryness. The marker comprises at least one selected from the group consisting of the following genes: COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes. These markers are positive markers included in Table 1B. Changes in the expression levels of these positive markers show a positive correlation with the presence or absence of deterioration of skin surface shape due to dryness, for example, changes in SEsm values.

[0031] In another preferred embodiment, the marker of the present invention is a marker for detecting the degree of deterioration of skin surface shape due to dryness. The marker comprises at least one selected from the group consisting of the following genes: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, and OVCA2, and the expression products of these genes, preferably at least one selected from the group consisting of FLOT2 and CFLAR, and the expression products of these genes. These markers are negative markers included in Table 1A. The change in the expression level of these negative markers shows a negative correlation with the degree of deterioration of skin surface morphology due to dryness, for example, the change in SEsm value.

[0032] In another preferred embodiment, the marker of the present invention is a marker for detecting the degree of deterioration of skin surface shape due to dryness. The marker comprises at least one selected from the group consisting of the following genes: COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes. These markers are positive markers included in Table 1B. The change in the expression level of these positive markers shows a positive correlation with the degree of deterioration of skin surface morphology due to dryness, for example, the change in SEsm value.

[0033] The markers of the present invention can be prepared by conventional methods from biological samples collected from subjects, such as cells, stratum corneum, skin, tissue (biopsy, etc.), body fluids (blood, tissue exudate, etc.), urine, secretions (saliva, sweat, surface lipids (SSL), etc.), preferably skin, stratum corneum, or SSL, more preferably SSL. For example, commercially available kits can be used to prepare nucleic acids or proteins from biological samples. Preferably, the markers of the present invention are nucleic acid markers, and preferred examples of nucleic acids prepared from biological samples include DNA such as genomic DNA and RNA such as mRNA.

[0034] Examples of subjects from whom biological samples containing the marker of the present invention are collected include individuals who need to detect deterioration of skin surface shape due to dryness, and individuals who desire to detect deterioration of skin surface shape due to dryness. Preferably, these are healthy individuals who need to detect deterioration of skin surface shape due to dryness, and healthy individuals who desire to detect deterioration of skin surface shape due to dryness. Here, a healthy individual refers to a person who does not have a skin disease such as atopic dermatitis.

[0035] More preferably, the marker of the present invention is a nucleic acid or protein prepared from the subject's SSL, and even more preferably mRNA. The skin site from which SSL is collected can be any part of the body, such as the head, face, neck, trunk, hands and feet, and areas with high sebum secretion, such as the skin of the head or face, are preferred, and facial skin is more preferred.

[0036] Any means used for the recovery or removal of SSL from the skin can be employed to collect SSL from the subject's skin. Preferably, an SSL absorbent material, an SSL adhesive material, or an instrument for scraping off SSL from the skin, as described later, can be used. The SSL absorbent material or SSL adhesive material is not particularly limited as long as it is a material that has an affinity for SSL, and examples include polypropylene and pulp. More detailed examples of procedures for collecting SSL from the skin include methods of absorbing SSL onto a sheet material such as oil-blotting paper or oil-blotting film, methods of adhering SSL to a glass plate or tape, and methods of scraping off and recovering SSL with a spatula, scraper, etc. To improve the adsorption of SSL, an SSL absorbent material containing a highly lipid-soluble solvent beforehand may be used. On the other hand, since the adsorption of SSL is inhibited if the SSL absorbent material contains a highly water-soluble solvent or water, it is preferable that the content of highly water-soluble solvents or water is low. It is preferable to use the SSL absorbent material in a dry state.

[0037] The collected SSL may be used immediately in the nucleic acid or protein extraction process described later, or it may be stored until it is used in the nucleic acid or protein extraction process. If stored, the SSL is preferably stored under low temperature conditions. The storage temperature of the SSL may be 0°C or lower, preferably -20±20°C to -80±20°C, more preferably -20±10°C to -80±10°C, even more preferably -20±20°C to -40±20°C, even more preferably -20±10°C to -40±10°C, even more preferably -20±10°C, and even more preferably -20±5°C. The storage period of the SSL is not particularly limited, but is preferably 12 months or less, for example 6 hours to 12 months, more preferably 6 months or less, for example 1 day to 6 months, and even more preferably 3 months or less, for example 3 days to 3 months.

[0038] For the extraction of nucleic acids or proteins from collected SSL, methods commonly used for the extraction or purification of nucleic acids or proteins from biological samples can be used. Examples of nucleic acid extraction or purification methods include the phenol / chloroform method, the AGPC (acid guanidinium thiocyanate-phenol-chloroform extraction) method, or methods using columns such as TRIzol®, RNeasy®, or QIAzol®, methods using special magnetic particles coated with silica, methods using Solid Phase Reversible Immobilization magnetic particles, and extraction using commercially available RNA extraction reagents such as ISOGEN. For protein extraction or purification, commercially available protein extraction reagents such as QIAzol Lysis Reagent (Qiagen) can be used.

[0039] (2. Method for detecting deterioration of skin surface shape due to dryness) In another embodiment, the present invention provides a method for detecting deterioration of skin surface shape due to dryness using the marker of the present invention described in 1. above. The method for detecting deterioration of skin surface shape due to dryness according to the present invention (hereinafter referred to as the method of the present invention) detects deterioration of skin surface shape due to dryness in a subject based on a comparison of the expression level of the marker of the present invention in the subject with a reference value. Here, the reference value can be the expression level of the same marker measured in advance at any interval. The period is not particularly limited and should be a period sufficient to receive the dryness stimulus that causes deterioration of skin surface shape. For example, it can be selected between 1 hour and 1 year, preferably 2 hours to 6 months, more preferably 3 hours to 3 months, and even more preferably 3 hours to 1 month. It is preferable to use the expression level of the same subject as the reference value, but it may be replaced with the expression level of another person who is the same or similar in gender, age, age group, race, etc. as the subject, or the average value of the expression level in a group of other people who are the same or similar in gender, age, age group, race, etc. as the subject may be used. In one embodiment, the method of the present invention measures the expression level of the marker of the present invention and compares the expression level with a reference value to detect whether or not there is deterioration of the skin surface shape due to dryness in the subject. In another embodiment, the method of the present invention measures the expression level of the marker of the present invention and compares the expression level with a reference value to detect the degree of deterioration of the skin surface shape due to dryness in the subject.

[0040] Another embodiment provides a method for detecting deterioration of skin surface shape due to dryness, which includes measuring the expression level of the marker of the present invention at at least two time periods apart and setting the expression level measured at the earlier time as a reference value.

[0041] (2.1 Analysis of marker expression) The subjects subjected to the method of the present invention are the same as the subjects from whom biological samples containing the markers of the present invention described above are collected. In a preferred embodiment, the method of the present invention includes measuring the expression level of the markers of the present invention in a biological sample collected from the subject. The type of the biological sample is as described above, and is preferably an SSL. In one embodiment, the method of the present invention may further include collecting the SSL from the subject. The procedure for collecting the SSL and the procedure for extracting the marker from the SSL are as described above.

[0042] The expression level of the marker of the present invention can be measured according to methods for quantifying nucleic acids or proteins commonly used in the art. The expression level of the marker to be measured may be an expression level based on the absolute amount of the target marker in a biological sample, or a relative expression level to other standards or to the expression level of all nucleic acids or all proteins.

[0043] For example, the expression level of nucleic acid markers can be measured according to the gene expression analysis procedures commonly used in the field. Examples of gene expression analysis methods include PCR, multiplex PCR, real-time PCR, hybridization (DNA chip, DNA microarray, dot blot hybridization, slot blot hybridization, Northern blot hybridization, etc.), sequencing, and chromatography, which are methods for quantifying nucleic acids or their amplified products. If the nucleic acid is RNA, it is preferable to convert the RNA to cDNA by reverse transcription before quantifying it using the methods described above.

[0044] The expression level of the protein marker can be measured using protein quantification methods commonly used in the field, such as immunoassays (e.g., Western blotting, ELISA, immunostaining, etc.), fluorescence methods, electrophoresis, protein chips, chromatography, mass spectrometry (e.g., LC-MS / MS, MALDI-TOF / MS), 1-hybrid methods (PNAS 100, 12271-12276 (2003)), and 2-hybrid methods (Biol. Reprod. 58, 302-311 (1998)). Alternatively, the expression level of the marker of the present invention may be measured by measuring molecules that interact with the nucleic acid or protein that is the marker of the present invention. Examples of molecules that interact with the marker of the present invention include DNA, RNA, proteins, polysaccharides, oligosaccharides, monosaccharides, lipids, fatty acids, and their phosphorylated, alkylated, and glycosidic compounds, as well as complexes of any of the above.

[0045] Preferably, the marker used in the method of the present invention is SSL-derived RNA. In this case, the expression level of RNA contained in SSL is measured. Preferably, the expression level of the SSL-derived RNA is measured by converting the RNA extracted from SSL into cDNA by reverse transcription, and then quantifying the cDNA or its amplification product using the method described above.

[0046] For RNA reverse transcription, primers targeting specific RNAs to be analyzed may be used, but for more comprehensive nucleic acid preservation and analysis, random primers are preferable. General reverse transcriptases or reverse transcription reagent kits can be used for this reverse transcription. Preferably, highly accurate and efficient reverse transcriptases or reverse transcription reagent kits are used, examples of which include M-MLV Reverse Transcriptase and its variants, or commercially available reverse transcriptases or reverse transcription reagent kits, such as the PrimeScript® Reverse Transcriptase series (Takara Bio Inc.), the SuperScript® Reverse Transcriptase series (Thermo Scientific Inc.), SuperScript® III Reverse Transcriptase, and the SuperScript® VILO cDNA Synthesis kit (both from Thermo Scientific Inc.) are also suitable. In the extension reaction of the reverse transcription, it is preferable to adjust the temperature to preferably 42°C ± 1°C, more preferably 42°C ± 0.5°C, and even more preferably 42°C ± 0.25°C, while adjusting the reaction time to preferably 60 minutes or more, more preferably 80 to 120 minutes.

[0047] When measuring the expression level of nucleic acid markers using PCR, RNA derived from a biological sample is reverse transcribed into cDNA as needed, and then the DNA derived from the biological sample is amplified using a primer pair. In PCR, only one specific DNA to be analyzed may be amplified using a primer pair that targets that specific DNA, or multiple specific DNAs may be amplified simultaneously using multiple primer pairs. Preferably, the PCR is multiplex PCR. Multiplex PCR is a method of simultaneously amplifying multiple gene regions by using multiple primer pairs simultaneously in the PCR reaction system. Multiplex PCR can be performed using commercially available kits (for example, the Ion AmpliSeqTranscriptome Human Gene Expression Kit; Life Technologies Japan Co., Ltd., etc.). The temperature for the annealing and extension reactions in the PCR cannot be generalized as it depends on the primers used, but when using the above-mentioned multiplex PCR kit, it is preferably 62°C ± 1°C, more preferably 62°C ± 0.5°C, and even more preferably 62°C ± 0.25°C. Therefore, in the PCR, the annealing and extension reactions are preferably performed in one step. The duration of the annealing and extension reaction steps can be adjusted depending on the size of the DNA to be amplified, but is preferably 14 to 18 minutes. The conditions for the denaturation reaction in the PCR can be adjusted depending on the DNA to be amplified, but is preferably 95 to 99°C for 10 to 60 seconds. Reverse transcription and PCR at the above temperatures and times can be performed using a thermal cycler commonly used for PCR.

[0048] The purification of the reaction product obtained by the PCR is preferably carried out by size separation of the reaction product. Size separation allows the target PCR reaction product to be separated from primers and other impurities contained in the PCR reaction mixture. DNA size separation can be carried out, for example, by a size separation column, a size separation chip, or magnetic beads that can be used for size separation. Preferred examples of magnetic beads that can be used for size separation include Solid Phase Reversible Immobilization (SPRI) magnetic beads such as Ampure XP.

[0049] The purified PCR reaction product may be subjected to further processing necessary for subsequent quantitative analysis. For example, the purified PCR reaction product may be prepared into a suitable buffer solution for DNA sequencing, the PCR primer region in the PCR-amplified DNA may be cleaved, or adapter sequences may be further added to the amplified DNA. For instance, the purified PCR reaction product can be prepared into a buffer solution, the amplified DNA can be subjected to removal of PCR primer sequences and adapter ligation, and the resulting reaction product can be amplified as needed to prepare a library for quantitative analysis. These operations can be performed, for example, using the 5×VILO RT Reaction Mix included with the SuperScript® VILO cDNA Synthesis kit (Life Technologies Japan Co., Ltd.), the 5×Ion AmpliSeq HiFi Mix included with the Ion AmpliSeq Transcriptome Human Gene Expression Kit (Life Technologies Japan Co., Ltd.), and the Ion AmpliSeq Transcriptome Human Gene Expression Core Panel, according to the protocols included with each kit.

[0050] When measuring the expression level of nucleic acid markers using real-time PCR, if necessary, RNA derived from a biological sample is reverse transcribed into cDNA, and then PCR is performed using primers that have been pre-labeled with radioisotopes (RI), fluorescent substances, etc. The resulting labeled double-stranded DNA is detected and quantified.

[0051] When measuring the expression level of nucleic acid markers using Northern blot hybridization, for example, RNA derived from a biological sample is transferred onto a membrane according to a standard procedure, and then probe DNA labeled with an RI, fluorescent substance, etc., is hybridized to the RNA. By detecting the signal derived from the label from the double helix of the formed labeled probe DNA and RNA, the expression level of the nucleic acid marker can be measured.

[0052] When measuring the expression level of nucleic acid markers using DNA microarrays, for example, a microarray is used in which nucleic acids (cDNA or DNA) that specifically hybridize to the target nucleic acid marker are immobilized on a support. By binding nucleic acids (cDNA or cRNA) prepared from a biological sample onto the microarray and detecting the label on the microarray, the expression level of the nucleic acid marker in the biological sample can be measured. The nucleic acid immobilized on the microarray can be any nucleic acid that hybridizes specifically to the target nucleic acid marker (i.e., substantially only to the target nucleic acid marker) under stringent conditions, and may be a nucleic acid having the entire sequence of the nucleic acid marker of the present invention, or a nucleic acid consisting of a partial sequence. Examples of such "partial sequences" include nucleic acids consisting of at least 15 to 25 bases. Here, stringent conditions can be washing conditions of approximately "1×SSC, 0.1%SDS, 37°C", preferably conditions of approximately "0.5×SSC, 0.1%SDS, 42°C", and even more preferably conditions of approximately "0.1×SSC, 0.1%SDS, 65°C". Stringent hybridization conditions are described, for example, in J. Sambrook et al., Molecular Cloning: A Laboratory Manual, Third Edition, Cold Spring Harbor Laboratory Press (2001).

[0053] When measuring the expression levels of nucleic acid markers using sequencing, a next-generation sequencer (e.g., Ion S5 / XL system, Life Technologies Japan Co., Ltd.) can preferably be used. The expression level of DNA or RNA can be measured based on the number of reads (read count) generated by sequencing.

[0054] When measuring the expression levels of multiple nucleic acid markers by sequencing, the read count described above can be used as expression level data. Alternatively, the RPM (Reads per million mapped reads) value of the read count, corrected for differences in the total number of reads between samples, the logarithm of the RPM value (Log2RPM value, or Log2(RPM+1) value), the count value corrected using DESeq2 (Love MI et al., Genome Biol, 2014) (Normalized count value), or its logarithm (Log2(Normalized count+1) value) can be used as expression level data. Alternatively, as expression level data, commonly used quantitative values ​​for RNA-seq, such as Fragments per kilobase of exon per million reads mapped (FPKM), reads per kilobase of exon per million reads mapped (RPKM), and transcripts per million (TPM), can be used.

[0055] Probes or primers used for measuring nucleic acid markers may, for example, be primers for specifically amplifying the nucleic acid markers of the present invention, or probes for specifically detecting the nucleic acid markers. Here, "specific" means that the nucleic acid can be recognized or detected in such a way that substantially only the markers of the present invention are detected, for example, in Northern blotting, or substantially only the markers of the present invention are amplified in PCR, thereby generating products or detectables substantially derived from the markers of the present invention. These probes or primers can be designed based on the nucleotide sequence of the nucleic acid markers. Specific examples of the probe or primer include oligonucleotides or complementary strands thereof consisting of the entire or partial sequence of the nucleic acid marker of the present invention. The "complementary strand" is not limited to a perfectly complementary sequence, as long as it specifically recognizes the target marker, and may preferably have 80% or more, more preferably 90% or more, even more preferably 95% or more, and even more preferably 99% or more sequence identity. Sequence identity can be determined by algorithms such as NCBI BLAST described above. Examples of primers used for measuring the nucleic acid marker include those that can perform specific annealing and chain extension for the target nucleic acid marker, and which have a chain length of preferably 10 bases or more, more preferably 15 bases or more, even more preferably 20 bases or more, preferably 100 bases or less, more preferably 50 bases or less, and even more preferably 35 bases or less. Examples of probes used for measuring the nucleic acid marker include those capable of specific hybridization with the target nucleic acid marker, preferably having a chain length of 10 bases or more, more preferably 15 bases or more, preferably 100 bases or less, more preferably 50 bases or less, and even more preferably 25 bases or less. The probe or primer can be DNA or RNA, and may be synthetic or natural. Probes used for hybridization are usually labeled.

[0056] When measuring the expression level of a protein marker using an immunoassay, for example, an antibody against the protein marker can be brought into contact with a biological sample, and the protein marker bound to the antibody can be quantified. For example, in Western blotting, a primary antibody against the protein marker is used, followed by labeling the primary antibody with a secondary antibody labeled with an RI, fluorescent substance, enzyme, etc., and then the expression level of the protein marker can be measured by measuring the signal derived from the label. The antibody against the protein marker may be a polyclonal antibody or a monoclonal antibody. These antibodies can be manufactured according to known methods.

[0057] (2.2 Detection of skin surface morphology deterioration due to dryness based on marker expression levels) In one embodiment of the method of the present invention, the expression level of a marker of the present invention derived from a subject (a marker of the present invention contained in a biological sample taken from the subject) is measured, and the expression level of the measured target marker is compared with a reference value to detect deterioration (e.g., deterioration or non-deterioration) of the skin surface shape due to dryness in the subject.

[0058] As described above, the markers in Tables 1A and 1B are markers whose expression levels fluctuate in response to deterioration of skin surface shape due to dryness, specifically the difference in elevation between skin furrows and ridges detected from skin surface images, such as the SEsm value. More specifically, the markers in Table 1A are negative markers, whose changes in expression level show a negative correlation with deterioration of skin surface shape due to dryness, while the markers in Table 1B are positive markers, whose changes in expression level show a positive correlation with deterioration of skin surface shape due to dryness. Therefore, the presence or absence of deterioration of skin surface shape due to dryness in a subject can be detected using the change in expression level of the negative or positive marker as an indicator.

[0059] In a preferred example of this embodiment, the presence or absence of deterioration of skin surface shape due to dryness detected by the method of the present invention refers to the presence or absence of deterioration of the smoothness of the skin surface due to dryness, for example, the presence or absence of deterioration of skin surface shape corresponding to the difference in height between skin furrows and skin ridges detected from a skin surface image, specifically an increase in the SEsm value. The target marker used for this detection is a marker for detecting the deterioration of skin surface shape due to dryness as described above, for example, a marker that can detect deterioration of skin surface shape corresponding to the SEsm value. These markers are negative markers or positive markers, and the amount of change in their expression level shows a negative or positive correlation with, for example, the amount of increase in the SEsm value. By comparing the expression level of the marker with a reference value and using the change as an indicator, the presence or absence of deterioration of skin surface shape due to dryness in a subject can be detected.

[0060] In this embodiment, one or more markers selected from the negative marker and the positive marker in a biological sample taken from a subject can be used as target markers for detection as described above. As described above, the negative marker and the positive marker are markers that correlate with the SEsm value. In this embodiment, it is sufficient to use at least one marker that correlates with the SEsm value as a target marker. In the method of the present invention, either one of the negative marker and the positive marker may be used as a target marker, or two or more markers selected from the negative marker and the positive marker may be used in combination as target markers. Alternatively, a nucleic acid marker or protein marker consisting of all of the negative marker and the positive marker may be used as a target marker in combination.

[0061] When using negative markers, a decrease in their expression level over time indicates deterioration of the skin surface morphology due to dryness in the subject, while an increase or no change in the expression level over time indicates no deterioration of the skin surface morphology due to dryness in the subject. Therefore, if the expression level of the negative marker measured from a subject is lower than the reference expression level, it is detected that the subject's skin surface morphology has deteriorated due to dryness. On the other hand, if the expression level is higher than the reference expression level or remains unchanged, it is detected that the subject's skin surface morphology has not deteriorated due to dryness.

[0062] When using a positive marker, an increase in its expression level over time indicates deterioration of the skin surface morphology due to dryness in the subject, while a decrease or no change in the expression level over time indicates no deterioration of the skin surface morphology due to dryness in the subject. Therefore, if the expression level of the positive marker measured from a subject is higher than the reference expression level, it is detected that the subject's skin surface morphology has deteriorated due to dryness. On the other hand, if the expression level is lower than the reference expression level or remains unchanged, it is detected that the subject's skin surface morphology has not deteriorated due to dryness.

[0063] In the above, as a criterion for determining whether the expression level of a marker is lower or higher than the reference value, for example, if the expression level of the marker of the present invention derived from a subject is preferably 99% or less, more preferably 95% or less, and even more preferably 90% or less of the reference value, then the expression level of the marker may be judged to be lower than the reference value. If the expression level of the marker of the present invention is preferably 101% or more, more preferably 105% or more, and even more preferably 110% or more of the reference value, then the expression level of the marker may be judged to be higher than the reference value. Alternatively, the difference between the expression level of the marker derived from a subject and the reference value can be determined, for example, by whether the two are statistically significant or not. When multiple markers are used as target markers, the presence or absence of deterioration of skin surface shape due to dryness can be detected by comparing the expression level of each target marker with the reference value and checking whether the expression level of a certain percentage, for example, 50% or more, preferably 70% or more, more preferably 90% or more, and even more preferably 100%, of the markers differs from the reference value.

[0064] In another embodiment of the method of the present invention, the degree of deterioration of the skin surface shape due to dryness in a subject can be detected based on a comparison of the expression level of a target marker in the subject with a reference value. If the target marker is one or more selected from the negative markers described above, the lower the expression level of the negative marker in the subject compared to the reference expression level, the more the subject's skin surface morphology is detected as having worsened due to dryness. On the other hand, if the target marker is one or more selected from the positive markers described above, the higher the expression level of the positive marker in the subject compared to the reference expression level, the more the subject's skin surface morphology is detected as having worsened due to dryness.

[0065] In another embodiment of the method of the present invention, the expression level of a target marker in a subject can be measured, and the degree of deterioration of the skin surface shape due to dryness in the subject can be detected based on the difference between the measured expression level of the target marker and a reference value.

[0066] In a preferred example of this embodiment, the degree of deterioration of skin surface shape due to dryness detected by the method of the present invention is the degree of deterioration of the smoothness of the skin surface due to dryness, for example, the degree of deterioration of skin surface shape corresponding to the difference in height between skin furrows and skin ridges detected from a skin surface image, specifically the increase in the SEsm value. The target marker used as an indicator for this detection is the same as the target marker described above, and the degree of deterioration of skin surface shape due to dryness in a subject can be detected using the amount of change (Δ expression level) calculated by subtracting a reference value from the expression level of the marker as an indicator.

[0067] When using a negative marker, if its Δ expression level is negative, its absolute value represents the degree of deterioration of the skin surface shape due to dryness in the subject. On the other hand, if the Δ expression level is 0 or positive, it represents no deterioration of the skin surface shape due to dryness in the subject. Therefore, the greater the negative value of the change in the expression level of the negative marker measured from the reference value (Δ expression level) and the larger its absolute value, the more the subject's skin surface shape is detected to have deteriorated due to dryness. Conversely, if the Δ expression level is 0 or positive, it is detected that the subject's skin surface shape has not deteriorated due to dryness. Also, for example, when the Δ expression level is measured over time two or more times, if the Δ expression level of the negative marker remains negative from the first measurement onwards, it is detected that the deterioration of the subject's skin surface shape due to dryness is progressing.

[0068] When using a positive marker, a positive Δ expression level indicates the degree of deterioration of the subject's skin surface shape due to dryness. Conversely, a Δ expression level of 0 or a negative value indicates no deterioration of the subject's skin surface shape due to dryness. Therefore, a positive change in the expression level of the positive marker measured from the subject (Δ expression level) from the reference value, especially a larger value, indicates that the subject's skin surface shape has deteriorated more due to dryness. On the other hand, a Δ expression level of 0 or a negative value indicates that the subject's skin surface shape has not deteriorated due to dryness. Furthermore, for example, when the Δ expression level is measured over time two or more times, if the Δ expression level of the positive marker remains positive from the first measurement onward, it indicates that the deterioration of the subject's skin surface shape due to dryness is progressing.

[0069] In detecting deterioration of skin surface shape due to dryness in subjects using the aforementioned Δ expression level as an indicator, the degree of deterioration detected can be divided into several degrees of deterioration, such as "mild deterioration," "moderate deterioration," and "severe deterioration," based on the absolute value of the Δ expression level. The boundary values ​​for each of these degrees can be appropriately determined from reference values ​​derived in advance from the relationship between the degree of deterioration of skin surface shape due to dryness and the Δ expression level in any given population.

[0070] In one example, the reference value can be predetermined based on the relationship between the degree of deterioration of skin surface shape (the level of deterioration of skin surface shape classified based on conventional evaluation of skin surface shape, or a score value related to skin surface shape) and the change in the expression level of the target marker (Δ expression level). For example, a certain population can be divided into several groups with different degrees of deterioration based on the degree of deterioration of skin surface shape before and after a predetermined period, and a reference value can be determined to determine whether or not a person belongs to each group by referring to the statistical value (e.g., mean value) of the change in the expression level of the target marker (Δ expression level) measured in each group before and after the same period. When multiple types of markers are used as target markers, it is preferable to determine a reference value for each marker. The population is not particularly limited, and groups may be created by age, generation, sex, or race, depending on the subjects to be detected. Examples of groups used to calculate the reference value include groups with mild skin surface morphological deterioration (mild group), moderate skin surface deterioration (moderate group), and severe skin surface deterioration (severe group). A control group that has not been irritated by dryness may also be included. In one example, a reference value can be calculated from two or more groups having a specific degree of deterioration in skin surface shape, which are grouped based on the change in the SEsm value, one of the indicators of skin surface shape.

[0071] The setting of reference values ​​and the specific methods for classifying the severity of symptoms based on said reference values ​​can be carried out appropriately in accordance with the common technical knowledge of those skilled in the art.

[0072] (2.3 Detection of the degree of deterioration of skin surface shape due to dryness based on a predictive model) In another embodiment of the method of the present invention, the degree of deterioration of the skin surface shape due to dryness in a subject is detected based on a predictive model constructed using data (hereinafter referred to as an expression profile) on the change in the expression level of the marker of the present invention derived from the subject (the marker of the present invention contained in a biological sample taken from the subject) from a reference value (Δ expression level). Examples of expression profiles include data related to expression levels such as sequencing read counts.

[0073] For example, a predictive model (e.g., a discriminant) for detecting the degree of deterioration of skin surface shape due to dryness in any subject can be constructed using machine learning, where the expression profiles of one or more markers (genes or their expression products) obtained from each person in a training sample population (e.g., a population including multiple groups with different degrees of deterioration) are used as explanatory variables, and a variable representing which degree of deterioration group each person in the population belongs to is used as the dependent variable. Using the constructed predictive model, the degree of deterioration of skin surface shape due to dryness in a subject, specifically which degree of deterioration group they belong to, can be detected. Here, instead of dividing subjects into groups by degree of deterioration, a score value, which is an indicator of the degree of deterioration, can be used directly as the dependent variable, and a score value indicating the degree of deterioration of skin surface shape due to dryness in a subject can be detected.

[0074] In this specification, "feature" is synonymous with "explanatory variable" in machine learning. In this specification, markers whose expression profiles are used as explanatory variables (features) in machine learning may be referred to as "feature markers (group)." Furthermore, if a feature marker is a gene or its transcript, it may be referred to as a feature gene.

[0075] The feature marker(s) used in this embodiment may be at least one selected from the group consisting of the genes shown in Tables 1A and 1B and their expression products. The expression profiles of the feature markers may be absolute values, relative values, or normalized. When using multiple markers as the feature marker group, for example, several markers from the present invention that have a high correlation with the degree of deterioration of skin surface shape due to dryness can be selected, and their expression profiles can be used as explanatory variables.

[0076] In one embodiment, all of the genes or their expression products listed in Table 1A are combined and used as a feature marker group. In another embodiment, all of the genes or their expression products listed in Table 1B are combined and used as a feature marker group. In yet another embodiment, all of the genes or their expression products listed in Tables 1A and 1B are combined and used as a feature marker group.

[0077] In a preferred embodiment, the expression profiles of feature markers (groups) in a population containing two or more groups of subjects with different degrees of deterioration (e.g., no deterioration of skin surface shape, and two or more groups selected from groups with mild, moderate, and severe deterioration of skin surface shape) are used as training samples for machine learning. Using these training samples, a discriminant formula (predictive model) is constructed to differentiate the degree of skin surface shape deterioration due to dryness in subjects. The expression profiles of feature markers (groups) can be used as explanatory variables in constructing the discriminant formula. As the dependent variable, for example, a variable representing which degree of deterioration group the subject from which the feature markers (groups) originates can belong can be used. Based on the constructed discriminant formula, a cutoff value for determining the degree of deterioration can be determined. Next, the expression profiles of the feature markers (groups) originating from subjects are measured, the obtained measurements are substituted into the discriminant formula, and the results obtained from the discriminant formula are compared with the cutoff value to determine the degree of skin surface shape deterioration due to dryness in the subject. The cutoff value can be determined according to known methods. For example, the constructed discriminant can be used to obtain the ROC (Receiver Operating Characteristic Curve) curve, and its Youden index can be determined as the cutoff value.

[0078] Alternatively, when using marker expression profiles to build a predictive model, the data may be compressed by dimensionality reduction as needed before building the predictive model. For example, multiple markers can be extracted from the gene groups or their expression products shown in Tables 1A and 1B. Then, principal component analysis can be performed on the expression profiles of the extracted markers. A predictive model for determining the degree of deterioration of skin surface shape due to dryness in a subject can be constructed using machine learning, with one or more principal components calculated by the principal component analysis as explanatory variables and a variable representing which group of deterioration (e.g., mild group or severe group) the subject from which the explanatory variables originate belong as the dependent variable.

[0079] Algorithms used in building predictive models can be publicly known, such as those used in machine learning. Examples of machine learning algorithms, though not limited to them, include linear regression models, Lasso regression, Random Forests, Neural Networks, Support Vector Machines (SVM (linear)) with linear kernels, Support Vector Machines (SVM (rbf)) with rbf kernels, Regularized linear discriminant analysis, and Regularized logistic regression.

[0080] The constructed predictive model is populated with validation data to calculate the predicted value (degree of deterioration of skin surface shape). The model that best matches the predicted value to the measured value (actual degree of deterioration of skin surface shape), for example, the model with the highest accuracy of the predicted value relative to the measured value, can be selected as the optimal model. Alternatively, the detection rate (Recall), precision, and the harmonic mean (F-score) can be calculated from the predicted and measured values, and the model with the highest F-score can be selected as the optimal model. By inputting the expression profiles of feature markers (groups) measured from the subject into the constructed predictive model, the degree of deterioration of skin surface shape due to dryness in the subject can be detected.

[0081] (3. Kit for detecting deterioration of skin surface shape due to dryness) In a further embodiment, the present invention provides a kit for detecting deterioration of skin surface shape due to dryness in a subject according to the method of the present invention described in Section 2 above. In one embodiment, the kit of the present invention comprises reagents or instruments for measuring the expression levels of the markers of the present invention described above. For example, the kit of the present invention may comprise reagents for amplifying or quantifying the nucleic acid markers of the present invention (e.g., reverse transcriptase, PCR reagents, primers, probes, sequencing adapter sequences, etc.), or reagents for quantifying the protein markers of the present invention (e.g., reagents for immunological measurement, antibodies, etc.). Preferably, the kit of the present invention contains oligonucleotides that specifically hybridize with the nucleic acid markers of the present invention (e.g., primers or probes for PCR), or antibodies that recognize the protein markers of the present invention. Preferably, the kit of the present invention comprises an index or guidance for evaluating the expression levels of the markers of the present invention. For example, the kit of the present invention may comprise guidance describing reference values ​​for the change in the expression level of each marker for detecting the degree of deterioration of skin surface shape due to dryness, or guidance on a discriminant formula based on a predictive model and feature markers to input thereto. The kit of the present invention may further include a biological sample collection device (for example, the SSL absorbent material or SSL adhesive material described above), a reagent for extracting the marker of the present invention from a biological sample (for example, a nucleic acid purification reagent), a preservative for the sample collection device after biological sample collection, a storage container, and the like.

[0082] Exemplary embodiments of the present invention are further disclosed herein, including the following substances, manufacturing methods, uses, and methods. However, the present invention is not limited to these embodiments.

[0083] [1] A method for detecting deterioration of skin surface shape due to dryness in a subject, comprising measuring the expression level of at least one selected from the group consisting of the following genes in the subject: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, OVCA2, COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes, and comparing it with a reference value. [2] A method for obtaining data to detect deterioration of skin surface shape due to dryness in a subject, comprising measuring the expression level of at least one selected from the group consisting of the following genes in the subject: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, OVCA2, COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes, and comparing it with a reference value. [3] The method according to [1] or [2], comprising measuring the expression level of the gene or expression product at at least two different time points and setting the expression level measured at the earlier time point as the reference value. [4] The method according to any one of [1] to [3], wherein the skin surface shape is the surface shape relating to the smoothness of the skin, indicated by the difference in height between skin furrows and skin ridges detected from a skin surface image, more specifically, the skin surface shape corresponding to the SEsm value among the Surface Evaluation of Living Skin (SELS) parameters. [5] The method according to any one of [1], [3], and [4], wherein the gene or expression product is at least one selected from the group consisting of the following genes: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, and OVCA2, and the expression products of said gene, and if the expression level of said gene or expression product measured from said subject is lower than a reference value expression level, it is detected that the subject's skin surface shape has deteriorated due to dryness, or if the expression level of said gene or expression product measured from said subject is higher than or unchanged from the reference value expression level, it is detected that the subject's skin surface shape has not deteriorated due to dryness. [6] The method according to [5], wherein the lower the expression level of the gene or expression product measured from the subject is compared to a reference expression level, the more the subject's skin surface shape is detected to have worsened due to dryness. [7] The method according to any one of [1], [3], and [4], wherein the gene or expression product is at least one selected from the group consisting of the following genes: COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes, and if the expression level of said gene or expression product measured from said subject is higher than a reference expression level, it is detected that the skin surface shape of said subject has deteriorated due to dryness, or if the expression level of said gene or expression product measured from said subject is lower than or unchanged from the reference expression level, it is detected that the skin surface shape of said subject has not deteriorated due to dryness. [8] The method according to [7], wherein the higher the expression level of the gene or expression product measured from the subject is compared to a reference expression level, the more the subject's skin surface shape is detected to have worsened due to dryness. [9] The method according to any one of [1], [3], and [4], comprising calculating a Δexpression level by subtracting a reference value expression level from the expression level of the gene or expression product.

[10] The method according to [9], wherein the gene or expression product is at least one selected from the group consisting of the following genes: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, and OVCA2, and the expression products of said gene, and when the Δ expression level is a negative value, the greater the absolute value of said Δ expression level, the more the subject's skin surface shape is detected to have worsened due to dryness.

[11] The method according to [9], wherein the gene or expression product is at least one selected from the group consisting of the following genes: COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes, and when the Δ expression level is a positive value, the greater the value of said Δ expression level, the more the subject's skin surface shape is detected to have worsened due to dryness.

[12] The method according to any one of [1] to [6], [9] and

[10] , wherein the gene or expression product is at least one selected from the group consisting of CFLAR and FLOT2 and the expression product of the gene.

[13] The method according to any one of [1] to

[12] , wherein the expression level of the gene or expression product is equal to the expression level of the gene or mRNA.

[14] The method according to any one of [1] to

[13] , wherein the expression level of the gene or expression product is the expression level of mRNA collected from lipids on the skin surface.

[15] The method described in any one of paragraphs [1] to

[14] , wherein the subject is a healthy individual.

[16] A marker for detecting deterioration of skin surface shape due to drying, comprising at least one selected from the group consisting of the following genes: FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, OVCA2, COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and the expression products of said genes.

[17] The marker according to

[16] , comprising at least one selected from the group consisting of FLOT2 and CFLAR, and the expression products of the genes.

[18] A nucleic acid marker, as described in

[16] or

[17] .

[19] The marker according to

[18] , wherein the nucleic acid is mRNA collected from lipids on the skin surface. A kit for detecting deterioration of skin surface shape due to drying, used in any one of the methods described in [1] to

[15] , comprising an oligonucleotide that specifically hybridizes with a nucleic acid that is a marker as described in

[20] ,

[16] , or

[17] , or an antibody that recognizes a protein that is a marker as described in

[16] or

[17] . [Examples]

[0084] The present invention will be described in more detail below based on examples, but the present invention is not limited thereto. Example 1: Exploration of detection markers for skin surface morphology deterioration caused by dryness irritation using SSL-derived RNA. 1) Dryness irritation and SSL collection due to exposure to a low humidity environment Twenty-three adult females (22-57 years old) with healthy skin were included as subjects. Each subject entered constant temperature and humidity chamber 1 (relative humidity 50±5%, 23±2℃), and sebum was collected from the left half of each subject's face (including forehead, nose, cheek, and jawline) using an oil-absorbing film (5×8cm, polypropylene, 3M), after which their face was washed. After a 30-minute acclimatization period, each subject moved to constant temperature and humidity chamber 2 (relative humidity 20±5%, 23±2℃), where the skin surface morphology (SEsm value) of the left cheek was measured using VisioScan (VC98, Courage+Khazaha), and exposure to a low-humidity environment (drying stimulus) was initiated. Three hours after the start of exposure to the low-humidity environment, sebum was collected from the left half of each subject's face. Six hours after the start of exposure to the low-humidity environment, sebum was collected from the left half of each subject's face and the SEsm value of the left cheek was measured.

[0085] The oil-absorbing film was transferred to a vial and stored at -80°C for approximately one month until use for RNA extraction. In the following, RNA prepared from SSL collected with the oil-absorbing film immediately after entering constant temperature and humidity chamber 1 was considered pre-drying stimulation RNA. Furthermore, RNA prepared from SSL collected with the oil-absorbing film 3 hours after the start of exposure to the low humidity environment and RNA prepared from SSL collected with the oil-absorbing film 6 hours after the start of exposure were mixed and considered post-drying stimulation RNA.

[0086] 2) RNA preparation and sequencing The oil-absorbing film described in 1) above was cut to an appropriate size, and RNA was transferred to the aqueous layer using QIAzol Lysis Reagent (Qiagen) according to the included protocol. RNA was extracted from the aqueous layer using a commercially available RNA extraction kit with an RNA extraction spin column, according to the included protocol. The extracted RNA was reverse transcribed using the SuperScript VILO cDNA Synthesis kit (Life Technologies Japan Co., Ltd.) at 42°C for 90 minutes to synthesize cDNA. Random primers included in the kit were used as primers for the reverse transcription reaction. From the obtained cDNA, a library containing DNA derived from the 20802 gene was prepared by multiplex PCR. Multiplex PCR was performed using the Ion AmpliSeqTranscriptome Human Gene Expression Kit (Life Technologies Japan Co., Ltd.) under the conditions [99°C, 2 min → (99°C, 15 sec → 62°C, 16 min) × 20 cycles → 4°C, Hold]. The obtained PCR products were purified using Ampure XP (Beckman Coulter, Inc.), followed by buffer reconstitution, primer sequence digestion, adapter ligation and purification, and amplification to prepare the library. The prepared library was loaded onto an Ion 540 Chip and sequenced using the Ion S5 / XL system (Life Technologies Japan, Inc.). The genes from which each read sequence originated were determined by gene mapping using the human genome reference sequence, hg19 AmpliSeq Transcriptome ERCC v1.

[0087] 3) Data Analysis i) Data used The RNA expression data (read count values) from each subject measured in 2) above were corrected using the DESeq2 method. However, only 4112 genes for which expression data without missing values ​​was obtained for more than 90% of the sample subjects were used for the following analysis. The normalized count values ​​corrected using the DESeq2 method were used for the analysis.

[0088] ii) RNA expression analysis Based on the SSL-derived RNA expression levels (Normalized count values) measured in i) above for each subject before and after drying stimulation, RNAs (differentially expressed genes) were identified in which the corrected value (FDR) of the p-value by the paired likelihood ratio test was less than 0.05 after drying stimulation compared to before drying stimulation, and in which the Log2 (FoldChange) was less than -1 or greater than 1. As a result, 296 RNAs showed decreased expression (DOWN) after drying stimulation, and 116 RNAs showed increased expression (UP) after drying stimulation.

[0089] iii) Functional analysis of downexpressed genes In ii) above, for 296 genes whose expression decreased after desiccation stimulation, we searched for biological processes (BPs) using gene ontology (GO) enrichment analysis with the public database STRING (https: / / string-db.org / ), and extracted terms with an FDR of less than 0.05. As a result, 319 BPs associated with the gene group whose expression decreased after desiccation stimulation were obtained, of which 5 terms related to epidermal keratinization (Table 2-1) and 6 terms related to reactive oxygen species stress response (Table 2-2). Furthermore, of the 296 genes whose expression decreased after desiccation stimulation, 14 genes that constitute at least one of the 5 terms related to epidermal keratinization in Table 2-1 are shown in Table 3-1, and 18 genes that constitute at least one of the 6 terms related to reactive oxygen species stress response in Table 2-2 are shown in Table 3-2. Of the 32 genes shown in Table 3-1 or Table 3-2, those that have not been previously reported to be associated with dry skin (a word registered in the taxonomy of "dry skin" or "xerosis") using Elsevier Text Mining are marked with an asterisk (*).

[0090] [Table 2-1]

[0091] [Table 2-2]

[0092] [Table 3-1]

[0093] [Table 3-2]

[0094] iv) Functional analysis of genes with increased expression In ii) above, for 116 genes whose expression increased after desiccation stimulation, we searched for biological processes (BPs) using gene ontology (GO) enrichment analysis with STRING, and extracted terms with an FDR of less than 0.05. As a result, no BPs associated with the gene groups whose expression increased after desiccation stimulation were obtained.

[0095] v) Skin phenotypic changes due to dryness irritation In step 1) above, we analyzed whether the SEsm value changed after the drying stimulus compared to before the stimulus, using the SEsm value measured immediately after entering the constant temperature and humidity chamber 2 (SEsm value before drying stimulus) and the SEsm value measured 6 hours after the start of exposure to the low humidity environment (SEsm value after drying stimulus). A paired t-test was performed based on the SEsm value (unitless) of each of the 23 subjects, and it was confirmed that the SEsm value increased significantly after the stimulus compared to before the drying stimulus, indicating that the skin surface shape deteriorated due to drying (Figure 1, p<0.01).

[0096] vi) Extraction of genes whose expression is decreased in association with deterioration of skin surface shape due to dryness. In ii) above, we searched for 296 genes whose expression decreased after dryness stimulation, specifically those whose change in expression before and after dryness stimulation correlated with the change in SEsm value before and after dryness stimulation. For each subject, we calculated the Spearman correlation coefficient Rs and its p-value between the change in expression level and the change in SEsm value for each of the 296 genes. As a result, the 16 genes shown in Table 4 showed a negative correlation between the change in expression level and the change in SEsm value, and their p-values ​​were less than 0.1. We confirmed that none of these 16 genes had been previously reported to be associated with dry skin (a term registered in the taxonomy of "dry skin" or "xerosis") using Elsevier Text Mining (indicated by an asterisk "*" in the table). Furthermore, of these 16 genes, FLOT2 is a gene that constitutes at least one of the terms related to epidermal keratinization shown in Table 2-1 in iii) above, and CFLAR is a gene that constitutes at least one of the terms related to reactive oxygen species stress response shown in Table 2-2 in iii) above (both shown in bold in the table). Therefore, these 16 genes were determined to be potential markers for detecting novel deterioration of skin surface shape due to dryness.

[0097] [Table 4]

[0098] vii) Extraction of genes whose expression is increased in association with deterioration of skin surface shape due to dryness. In ii) above, we searched for 116 genes whose expression increased after dryness stimulation, specifically those whose change in expression before and after dryness stimulation correlated with the change in SEsm value before and after dryness stimulation. For each subject, we calculated the Spearman correlation coefficient Rs and its p-value between the change in expression level and the change in SEsm value for each of the 116 genes. As a result, the five genes shown in Table 5 showed a positive correlation between the change in expression level and the change in SEsm value, and their p-values ​​were less than 0.1. We confirmed that none of these five genes had been previously reported to be associated with dry skin (a word registered in the taxonomy of "dry skin" or "xerosis") using Elsevier Text Mining (indicated by an asterisk in the table). Therefore, these five genes were judged to be potential detection markers for deterioration of skin surface shape due to dryness.

[0099] [Table 5]

[0100] It is well known that in dry skin (or a state of dry skin), the expression or function of genes related to epidermal keratinization or their expression products decreases (J Am Acad Dermatol. 55:263-8, 2006., J Invest Dermatol. 124:1099-110, 2005.), and that reactive oxygen species scavenging agents improve dry skin (Skin Pharmacol Physiol. 31:188-197, 2018.). On the other hand, as shown in Tables 3-1 and 3-2, not all genes constituting at least one term related to epidermal keratinization and at least one term related to reactive oxygen species stress response necessarily show decreased expression in dry skin. The results of such experiments mean that it is difficult to predict which specific genes will decrease in expression when healthy skin is subjected to dryness. Furthermore, since FLOT2 and CFLAR have not been previously reported to be associated with skin dryness, and are genes related to known molecular mechanisms such as epidermal keratinization and reactive oxygen species stress response, they are considered useful as indicators for detecting deterioration of skin surface shape due to dryness. The above-mentioned conventional knowledge regarding skin dryness, epidermal keratinization, and reactive oxygen species stress response, as well as the results of this experiment, demonstrate that the technology provided by the present invention, which uses at least one selected from the group consisting of 21 genes in SSL, namely FLOT2, CFLAR, EGR1, LRG1, RNF187, CPPED1, SLC35A4, SNORA2C, EEF1D, TENT5C, NELFE, PHLDA1, DEDD, SNORA71A, EID1, OVCA2, COQ10B, MCTS1, ELOVL7, STT3B, and BZW2, and their expression products, as a detection marker for deterioration of skin surface shape due to dryness, is entirely unexpected and difficult to discover.

Claims

1. A method for detecting deterioration of skin surface smoothness due to dryness, as indicated by the difference in height between skin furrows and ridges on the skin surface of a subject, comprising: measuring the expression level of at least one selected from the group consisting of the following gene: FLOT2 and the expression product of said gene in the subject, and comparing it with a reference expression level; and detecting that if the expression level of said gene or expression product is lower than the reference expression level, the smoothness of the subject's skin surface has deteriorated due to dryness; or detecting that if the expression level of said gene or expression product is higher than or unchanged from the reference expression level, the smoothness of the subject's skin surface has not deteriorated due to dryness.

2. The method according to claim 1, comprising measuring the expression level of the gene or expression product at at least two time points, and setting the expression level measured at the earlier time point as a reference value.

3. The method according to claim 1 or 2, wherein the lower the expression level of the gene or expression product is compared to the reference value expression level, the more it is detected that the smoothness of the subject's skin surface has worsened due to dryness.

4. A method for detecting deterioration of skin surface smoothness due to dryness, as indicated by the difference in height between skin furrows and skin ridges on the skin surface of a subject, comprising: measuring the expression level of at least one selected from the group consisting of the following gene: FLOT2 and the expression product of said gene in the subject; calculating the change in expression level by subtracting a reference value expression level from said expression level; and if the change in expression level is a negative value, the greater the absolute value of the change in expression level, the more the smoothness of the subject's skin surface is detected to have deteriorated due to dryness; or if the change in expression level is 0 or a positive value, the smoothness of the subject's skin surface is detected not to have deteriorated due to dryness.

5. The method according to claim 4, further comprising measuring the expression level of the gene or expression product at at least two time points, and setting the expression level measured at the earlier time point as a reference value.

6. The method according to any one of claims 1 to 5, wherein the smoothness of the skin surface is the smoothness of the skin surface corresponding to the SEsm value among the Surface Evaluation of Living Skin (SELS) parameters.

7. The method according to any one of claims 1 to 6, wherein the expression level of the gene or expression product is the expression level of the gene or mRNA.

8. The method according to any one of claims 1 to 7, wherein the expression level of the gene or expression product is the expression level of mRNA collected from lipids on the skin surface.

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