Method for detecting changes in severity of atopic dermatitis

Abstract

To detect changes in severity of atopic dermatitis.SOLUTION: Provided is a method for selecting a marker for detecting changes in the severity of atopic dermatitis in a test subject. Provided is a method for detecting changes in the severity of atopic dermatitis by using the marker.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method for selecting a marker for detecting changes in the severity of atopic dermatitis, a marker obtained by the selection method, and a method for detecting changes in the severity of atopic dermatitis using the marker. [Background technology]

[0002] Atopic dermatitis (hereinafter also referred to as "AD") is an eczematous skin disease that primarily affects individuals with an atopic predisposition. Typical symptoms of AD include chronic and recurrent itching, rashes, erythema, etc., occurring bilaterally on both sides of the body, as well as dyskeratosis, impaired barrier function, and dry skin. While most cases of AD develop in infants and show improvement with growth, adult-onset and refractory atopic dermatitis have been increasing in recent years. In AD, various etiologies are complexly involved, leading to diversity in symptoms and phenotypes, and it is known that exacerbations and remissions occur repeatedly (Non-Patent Literature 1). For example, it has been reported that if moisturizing is not continued after remission induction with topical medication, approximately 40% of AD patients experience a relapse of symptoms after 14 days, and approximately 60% after 28 days (Non-Patent Literature 2). Therefore, in treating AD, it is necessary to correctly understand the severity of AD, including the diversity of symptoms and phenotypes.

[0003] Traditional methods for evaluating the severity of Alzheimer's disease (AD) include assessments based on visual observation by physicians. These observations encompass a variety of features, including dryness, erythema, scaling, papules, scratch marks, edema, crusting, vesicles, erosions, and pruritic nodules. Scoring indices such as the Eczema Area and Severity Index (EASI) and the Severity Scoring of Atopic Dermatitis (SCORAD) exist to quantify these features. Furthermore, methods using high-performance cameras and probes to obtain objective numerical data on AD symptoms are also employed. On the other hand, patients themselves evaluate their AD based on visual observation and tactile sensations. Scoring indices for this include the Patient-Oriented Eczema Measure (POEM), Patient-Oriented SCORAD (PO-SCORAD), and Visual Analog Scaling (VAS).

[0004] In recent years, it has been proposed that the pathogenesis of Alzheimer's disease (AD) should be evaluated not only by phenotypes (phenotypes) that manifest as findings and subjective sensations, but also by endotypes (patent biological mechanisms), in order to aid in the selection of the optimal treatment. In other words, even among AD patients who exhibit similar phenotypes, there is a possibility that they are caused by different molecular mechanisms. It is increasingly believed that by subdividing the pathogenesis of AD patients by combining phenotypes and endotypes, it will be possible to lead to optimal treatment tailored to each individual patient. Currently, objective understanding of the pathogenesis of the disease, or understanding the pathogenesis considering endotypes, often involves using genes or their expression products contained in skin biopsies, blood, stratum corneum, etc., or the presence of specific cell types (these are sometimes collectively referred to as biomarkers). Conventionally, biomarkers proposed for evaluating the presence and severity of Alzheimer's disease (AD) include peripheral blood eosinophil count, serum total IgE levels, lactate dehydrogenase (LDH) levels, and serum thymus and activation-regulated chemokine (TARC) and squamous cell carcinoma antigen 2 (SCCA2) (Non-patent documents 3 and 4). However, there is insufficient data to show that the levels of these biomarkers fluctuate in accordance with changes in the severity of the disease in the same individual.

[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 sample for biological analysis (Patent Document 1). It has also been reported that marker genes for atopic dermatitis can be detected from SSL (Patent Document 2). [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] International Public Gazette No. 2018 / 008319 [Patent Document 2] Japanese Patent Publication No. 2020-074769 [Non-patent literature]

[0007] [Non-Patent Document 1] Kato et al., Journal of the Japanese Dermatological Association, 2018, 128:2431-2502. [Non-Patent Document 2] Lin et al., Adv Ther, 2017, 34:2601-2611 [Non-Patent Document 3] Sugawara et al., Allergy, 2002, 57:180-181 [Non-Patent Document 4] Ohta et al., Ann Clin Biochem, 2012, 49:277-284 [Overview of the project] [Problems that the invention aims to solve]

[0008] The present invention relates to a method for selecting a marker for detecting changes in the severity of atopic dermatitis, candidate markers used in the selection method, and a method for detecting changes in the severity of atopic dermatitis using the detection marker selected by the selection method. [Means for solving the problem]

[0009] The present invention relates to a method for selecting a marker for detecting changes in the severity of atopic dermatitis in a subject, 1) Based on the scores relating to the severity of atopic dermatitis in the subject at multiple time points separated by time, and the expression levels of one of the genes or their expression products shown in Table 1 below in the biological samples collected from the subject at those multiple time points, calculate P1 and P2 below.

number

[0010] [Table 1] [Effects of the Invention]

[0011] This invention provides candidate markers for detecting changes in the severity of atopic dermatitis. From these candidate markers, an appropriate marker for detecting changes in the severity of atopic dermatitis can be selected for each individual. These markers enable the simple and objective detection of changes in the severity of atopic dermatitis (e.g., exacerbation or improvement) in individual atopic dermatitis patients. Using these markers makes it possible to accurately understand the pathological condition of individual atopic dermatitis patients and to provide optimal treatment tailored to each individual patient. [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" refers to 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, and means any biological information contained within the sequence information of the bases that make up the DNA. Furthermore, in this specification, "gene" includes not only "genes" represented by a specific base sequence, but also their congeners (i.e., homologs or orthologs), variants such as gene 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] In this specification, "skin surface lipids (SSL)" refers to the lipid-soluble fraction present on the surface of the skin, and is sometimes called sebum. Generally, SSL mainly consists of secretions 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.

[0017] In this specification, unless otherwise specified, "skin" refers to the region including the stratum corneum, epidermis, dermis, hair follicles, and tissues such as sweat glands, sebaceous glands, and other glands.

[0018] In this specification, "atopic dermatitis (also referred to as "AD")" refers to a disease characterized by itchy eczema that repeatedly exacerbates and remits, and most patients with this disease are considered to have an atopic predisposition. Atopic predispositions include i) a family history or past medical history (one or more of the following diseases: bronchial asthma, allergic rhinitis / conjunctivitis, or atopic dermatitis), or ii) a predisposition to easily produce IgE antibodies.

[0019] In this specification, the "severity" of atopic dermatitis (AD) refers to the level of severity of AD symptoms, not the presence or absence of AD, and includes not only broad classifications such as mild, moderate, and severe, but also classifications based on more minor differences. The "severity" of AD can be determined, for example, based on various known evaluation scores that assess AD symptoms. In this specification, such evaluation scores are referred to as "scores related to the severity of atopic dermatitis (AD)." Examples of scores related to the severity of AD include the EASI score and POEM score for systemic skin rash due to AD, the VAS score for skin itching due to AD, the VAS score for dry skin due to AD (Atopic Dermatitis Treatment Guidelines, published by the Japanese Dermatological Association, Japanese Journal of Dermatology: 128(12), 2431-2502 (2018)), and the erythema index for facial erythema due to AD (see Japanese Patent Publication No. 2018-23756 and Dawson et al., Phys Med Biol, 25, 1980). Alternatively, a score determined by comprehensively evaluating any two or more of these scores and indices may be used. The score related to the severity of AD itself may also be used as the level of severity of AD symptoms.

[0020] In this specification, the term "detection" of changes in the severity of AD may be replaced with terms such as examination, measurement, determination, or evaluation support. However, the terms "detection," "examination," "measurement," "determination," or "evaluation" of changes in the severity of AD in this specification do not include a physician's diagnosis of changes in the severity of AD.

[0021] (1. Searching for candidate markers for detecting changes in the severity of atopic dermatitis) There is a need for biomarkers that can detect changes in the severity of Alzheimer's disease (AD). More precise detection of changes in AD severity would enable a more accurate understanding of the patient's condition and, consequently, the provision of optimal treatment tailored to each individual. Conventional markers for detecting the presence or absence and severity of AD have primarily been discovered through population analysis, i.e., comparisons between groups belonging to different severity levels (e.g., affected groups and normal groups, or severe groups and mild groups). However, these conventional markers discovered through population analysis do not always reflect the subtle differences in AD severity within each group, making it difficult to detect changes in AD severity using these conventional markers.

[0022] The inventors first attempted to search for candidate markers for detecting changes in the severity of Alzheimer's disease (AD). Specifically, they obtained the AD severity score of subjects over time, and also obtained the expression levels of various genes in those subjects over time. Next, they investigated the relationship between changes in the AD severity score and changes in gene expression levels in each subject. As a result, they found genes whose expression levels changed in accordance with the changes in the AD severity score of individual subjects over time, and whose expression level behavior was common to many subjects. These genes or their expression products were designated as candidate markers for detecting changes in the severity of AD in subjects.

[0023] Specifically, as shown in the examples described below, 18 adults with atopic dermatitis were used as subjects in the search for candidate markers. First, a score related to the severity of AD was obtained for each subject four times at two-week intervals, and the RNA expression level in surface lipids (SSL) as a gene or its expression product was similarly measured four times in the subject. The time-course change profile of this index (hereinafter also referred to as the progression pattern of the score related to the severity) and the time-course change profile of the RNA expression level (hereinafter also referred to as the progression pattern of the expression level) were obtained. As scores related to the severity of AD, the EASI score and POEM score for systemic skin rash due to AD, the VAS score for skin itching due to AD, the VAS score for dry skin due to AD, and the erythema index for facial erythema due to AD were used. Next, the progression patterns of the score related to the severity of AD and the progression patterns of the expression level were compared, and genes or their expression products whose expression level progression patterns were related to the progression patterns of the score related to the severity of AD were searched for.

[0024] The trend pattern of the score related to the severity of AD can be expressed according to the following formula (1).

[0025]

number

[0026] In formula (1), j represents the subject ID. j is an integer greater than or equal to 1 and less than or equal to the total number of subjects. n represents the total number of times a score related to the severity of the subject's AD was obtained; k represents the order in which the scores related to the severity of AD were obtained from the subjects; that is, the order in which the scores related to the severity of AD were obtained from the subjects over time. k is an integer between 1 and n-1; S j,k This represents the score related to the severity of AD obtained on the kth-th trial for a subject with ID j.

[0027] P1 jThe value of j represents the transition pattern of the score related to the severity of subject ID: j. P1 j The number of digits of the value of n-1 depends on the number of times the score related to the severity was obtained and the change in severity (f(x) = 0 or 1). P1 j The value of j can be one of the eight values of "0, 1, 10, 11, 100, 101, 110, 111": Here, P1 2 * 0 + 10 1 * 0 + 10 0 * 0) j = 111 represents that the severity of the subject's AD has continued to deteriorate compared to the previous time during the acquisition period (10 2 * 1 + 10 1 * 1 + 10 0 * 1). The meaning of other P1 j values can be understood similarly. For example, P1 j = 11 represents that the severity obtained in the second and third times has deteriorated compared to the previous time, but the severity obtained in the fourth time has not deteriorated compared to the previous time.

[0028] The transition pattern of the expression level of a gene or its expression product in a subject can be represented according to the following formula (2).

[0029]

Number

[0030] In formula (2), i represents the ID of the gene or its expression product. i is an integer greater than or equal to 1 and less than or equal to the total number of genes or their expression products examined; j represents the subject ID. j is an integer greater than or equal to 1 and less than or equal to the total number of subjects; n represents the number of times the expression level of the gene or its expression product was obtained, in other words, the total number of times a biological sample from which the gene or its expression product was derived was collected; k represents the order in which the expression levels of the gene or its expression product were obtained, in other words, the order in which the biological samples from which the gene or its expression product was derived were obtained. k is an integer between 1 and n-1; E i,j,k This represents the expression level of the gene or its expression product for ID:i in a biological sample taken for the kth time from subject ID:j.

[0031] P2 i,j The value represents the trend pattern of expression levels for the gene or its expression product of ID:i in the subject (or sample) of ID:j. P2 i,j The number of digits in the value depends on the number of times the expression level was obtained and the change in the expression level (f(x)=0 or 1), P2 i,j The value is 2 n-1 There can be multiple possibilities. For example, if the expression level of a subject's gene or its expression product is obtained four times (n=4), then P2 i,j P2 can be one of the following eight values: 0, 1, 10, 11, 100, 101, 110, 111. i,j =0 means that the expression level of the target gene or its expression product did not increase at any point during the acquisition period compared to the previous time (10 2 * 0+10 1 * 0+10 0 * 0) represents; P2 i,j =111 indicates that the expression level continued to increase during the acquisition period compared to the previous time (10 2 * 1+10 1 * 1+10 0 * Represents 1). Other P2 i,j The meaning of the value can be understood similarly. For example, P2 i,j A value of =11 indicates that the expression levels obtained in the second and third trials increased compared to the previous trial, but the expression level obtained in the fourth trial did not show an increase compared to the previous trial.

[0032] Using equations (1) and (2) above, the progression patterns of the score related to the severity of AD, and the progression patterns of the expression levels of genes or their expression products, can be calculated collectively for multiple subjects. However, more simply, the progression patterns of the score related to the severity of AD, and the progression patterns of the expression levels of genes or their expression products, for individual subjects can be determined according to equations (1a) and (2a) below, respectively.

[0033]

number

[0034] n, k, and S in equation (1a) k This is as defined in equation (1) above, except that j is not specified. i, n, k, and E in equation (2a) i,k This is as defined in formula (2) above, except that j is not specified. In the following specification, unless otherwise specified, P1 for any subject j j and P2 i,j These are P1 and P2, respectively. i It is expressed as follows.

[0035] Next, we determine whether the trend pattern of expression levels is related to the trend pattern of the score related to the severity of AD. P2: Trend pattern of expression levels of the ID:i gene or its expression product i The relationship between this and the trend pattern P1 of the score related to the severity of AD can be evaluated using the following procedure. First, we define the null hypothesis H0 and the alternative hypothesis H1 as follows: H0:P2 i 2 options n-1 Of the possible values, the probability of taking each value is equally 1 / 2. n-1 is; H1:P2 i 2 options n-1 Of the possible values, the probability of taking each value is equally 1 / 2. n-1 isn't it, If the null hypothesis is true, P2 i2 have equal probability of n-1 Take the value for each of the possibilities, and P1 = P2 i The probability of this happening is 1 / 2 n-1 For example, if the score related to the severity of AD and the expression level of the gene or its expression product are obtained four times (n=4), then P2 i Each of these values ​​has a probability of 1 / 8 and can take on one of eight values: "0, 1, 10, 11, 100, 101, 110, 111", and P1 = P2 i The probability of this happening is 1 / 8. On the other hand, if the null hypothesis is rejected, the alternative hypothesis is accepted, and P1=P2 i The probability of this happening is 1 / 2 n-1 isn't it.

[0036] Next, among all subjects, in the gene ID:i or its expression product, P1=P2 i Count the number of subjects who met the criteria. The number obtained is used to determine the number of matches for the gene or its expression product with ID:i. i (i represents the ID of the gene or its expression product) is obtained as follows: For the gene or its expression product with ID:i, the null hypothesis H0 (P1 = P2) is obtained. i The probability of this happening is 1 / 2 n-1 Assuming that the condition is met, among all subjects (total number and J), m i P1=P2 for humans i The probability p is that this happens. i (i represents the ID of the gene or its expression product) is calculated according to formula (3) below.

[0037]

number

[0038] Number of matches m i The probability p is obtained iIf the value is judged to be lower than the significance level, the null hypothesis H0 is rejected and the alternative hypothesis H1 is accepted. This suggests that there is a statistically significant relationship between the increase or non-increase in the expression level of the ID:i gene or its expression product and the exacerbation or non-exacerbation of AD symptoms. In this case, the ID:i gene or its expression product can be selected as a candidate marker for detecting changes in the subject's AD symptoms. As shown in the example described later, when there are 18 subjects, P1 = P2 i If the number of subjects who meet this condition is 7 or more, it is determined that there is a significant relationship between the trend pattern of the score related to the severity of AD and the trend pattern of the expression level of the ID:i gene or its expression product.

[0039] Genes or their expression products whose expression level transition patterns, explored through the above procedure, show a significant relationship with the transition patterns of the score related to the severity of AD, are extracted as candidate markers for detecting changes in the severity of AD. Therefore, the present invention provides candidate markers for selecting markers for detecting changes in the severity of AD. From among these candidate markers, a marker for detecting changes in the severity of AD can be selected for individual subjects.

[0040] (2. Candidate markers for detecting changes in the severity of atopic dermatitis) The candidate markers explored using the above procedure are the 122 genes and their expression products shown in Table 2 below. The gene names (Gene Symbols) and Gene IDs shown in Table 2 follow the Official Symbols and Gene IDs listed in NCBI ([www.ncbi.nlm.nih.gov / ]). These genes and their expression products are candidate markers for selecting markers for detecting changes in the severity of atopic dermatitis, as provided by the present invention.

[0041] [Table 2]

[0042] The genes shown in Table 2 include those consisting of nucleotide sequences registered in NCBI, as well as those consisting of sequences substantially identical to those registered, insofar as they themselves or their derived expression products function as markers for detecting changes in AD severity. Here, substantially identical sequences mean sequences that, for example, when searched using the homology calculation algorithm NCBI BLAST under the conditions of expect 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.

[0043] Of the candidate markers mentioned above, the 20 genes and their expression products shown in Table 3 (hereinafter also referred to as the candidate markers in Table 3) are related to changes in the EASI score. Therefore, the candidate markers in Table 3 are candidates for detecting changes in the severity of systemic skin lesions caused by AD, for example, they are candidates for detecting changes in the severity of AD corresponding to the EASI score. More specifically, the expression levels of the candidate markers in Table 3 show increases and decreases in accordance with increases and decreases in the EASI score. Therefore, the candidate markers in Table 3 are candidates for representing the exacerbation and non-exacerbation of the severity of systemic skin lesions caused by AD, for example, they are candidates for representing the exacerbation and non-exacerbation of AD corresponding to the EASI score.

[0044] Of the candidate markers mentioned above, the six genes and their expression products shown in Table 4 (hereinafter also referred to as the candidate markers in Table 4) are related to changes in the POEM score. Therefore, the candidate markers in Table 4 are candidates for detecting changes in the severity of systemic skin lesions caused by AD, for example, they are candidates for detecting changes in the severity of AD corresponding to the POEM score. More specifically, the expression levels of the candidate markers in Table 4 show increases and decreases in accordance with increases and decreases in the POEM score. Therefore, the candidate markers in Table 4 are candidates for representing the exacerbation and non-exacerbation of the severity of systemic skin lesions caused by AD, for example, they are candidates for representing the exacerbation and non-exacerbation of AD corresponding to the POEM score.

[0045] Of the candidate markers listed above, the 24 genes and their expression products shown in Table 5 (hereinafter also referred to as the candidate markers in Table 5) are related to changes in the VAS score for skin itching due to Alzheimer's disease (AD). Therefore, the candidate markers in Table 5 are candidates for detecting changes in the severity of skin itching due to AD, for example, they are candidates for detecting changes in the severity of AD corresponding to the VAS score for skin itching. More specifically, the expression levels of the candidate markers in Table 5 show increases and decreases in accordance with increases and decreases in the VAS score for skin itching. Therefore, the candidate markers in Table 5 are candidates for representing the exacerbation and non-exacerbation of the severity of skin itching due to AD, for example, they are candidates for representing the exacerbation and non-exacerbation of AD corresponding to the VAS score for skin itching.

[0046] Of the candidate markers listed above, the 26 genes and their expression products shown in Table 6 (hereinafter also referred to as the candidate markers in Table 6) are related to changes in the VAS score for skin dryness due to Alzheimer's disease (AD). Therefore, the candidate markers in Table 6 are candidates for detecting changes in the severity of skin dryness due to AD, for example, they are candidates for detecting changes in the severity of AD corresponding to the VAS score for skin dryness. More specifically, the expression levels of the candidate markers in Table 6 show increases and decreases in accordance with increases and decreases in the VAS score for skin dryness. Therefore, the candidate markers in Table 6 are candidates for representing the exacerbation and non-exacerbation of the severity of skin dryness due to AD, for example, they are candidates for representing the exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score for skin dryness.

[0047] Of the candidate markers listed above, the 46 genes and their expression products shown in Table 7 (hereinafter also referred to as the candidate markers in Table 7) are related to changes in the erythema index of facial erythema caused by Alzheimer's disease (AD). Therefore, the candidate markers in Table 7 are candidates for detecting changes in the severity of facial erythema caused by AD, for example, they are candidates for detecting changes in the severity of AD corresponding to the erythema index of facial erythema. More specifically, the expression levels of the candidate markers in Table 7 show increases and decreases in accordance with increases and decreases in the erythema index of facial erythema. Therefore, the candidate markers in Table 7 are candidates for representing exacerbations and decreases in the severity of facial erythema caused by AD, for example, they are candidates for representing exacerbations and decreases in the severity of AD corresponding to the erythema index of facial erythema.

[0048] [Table 3]

[0049] [Table 4]

[0050] [Table 5]

[0051] [Table 6]

[0052] [Table 7]

[0053] (3. Selection of markers for detecting changes in the severity of atopic dermatitis for individual subjects) The present invention provides a method for selecting a marker for detecting changes in the severity of Alzheimer's disease (AD) for an individual subject from the candidate markers explored above. Specifically, the method involves obtaining the progression pattern of the AD severity score for a given subject, as well as the progression pattern of the expression level of the candidate markers in that subject. Then, a marker whose expression level progression pattern matches the progression pattern of the AD severity score is selected. The selected marker can be used as a marker for detecting changes in the severity of AD in that subject.

[0054] The specific procedure for selecting a marker for detecting changes in the severity of Alzheimer's disease (AD) in a subject according to the present invention is described below. In one embodiment, this method involves the following steps: 1) Based on the score relating to the severity of the subject's AD at multiple time points separated by time, and the expression level of any one of the candidate markers in the biological samples taken from the subject at those multiple time points, P1 and P2 below are calculated. 2) When P1 = P2, the candidate marker is determined to be used as a marker for detecting changes in the severity of AD in the subject. It includes. P1 and P2 are represented by the following formulas (1a) and (2b).

[0055]

number

[0056] n, k, and S in equation (1a) k As defined above, n, k, and E in equation (2b) k This is as defined in formula (2) above, except that i and j are not specified. That is, n represents the total number of times the subject's score and biological sample were obtained; k represents the order in which the subject's score and biological sample were obtained; S k This represents the score related to the severity of AD in the subject obtained on the kth attempt; E k n represents the expression level of the candidate marker in the biological sample collected at the k-th time. n in formula (1a) and n in formula (2b) are the same value and should be 2 or greater, preferably 3 or greater, more preferably 4 or greater, preferably 10 or less, and more preferably 8 or less.

[0057] The subjects in this method are those who wish to identify markers for detecting changes in their own AD (Almost Diabetic) severity. Examples include individuals who need or wish to detect changes in their AD severity, such as those who have already developed AD.

[0058] In this method, the score relating to the severity of AD in the subject is obtained at multiple time points separated by time. The expression level of the candidate marker is obtained from biological samples taken from the subject at multiple time points separated by time. Therefore, the obtained expression level reflects the expression level of the candidate marker in the subject at the multiple time points separated by time.

[0059] Therefore, in one embodiment, the method may further include the following steps a) and b) before step 1): a) Obtain scores related to the severity of the subject's AD at multiple time intervals, and collect biological samples from the subject. b) Measure the expression level of any one of the candidate markers from the collected biological sample.

[0060] In this specification, "separated in time" means that each of the multiple time periods is separated from the adjacent time period to such an extent that a change in the subject's AD severity score can be expected to appear. The number of times the subject's AD severity score and biological sample are obtained may be multiple (two or more), but preferably three or more, and more preferably four or more. There is no particular upper limit to the number of acquisitions. Simply from the standpoint of saving time and cost, the number of acquisitions may preferably be 10 or less, and more preferably 8 or less.

[0061] For example, the subject's AD severity score and biological sample can be obtained at multiple intervals of 1 day or more, preferably 3 days or more, more preferably 1 week or more, even more preferably 1 week to 4 weeks, and even more preferably 12 days to 16 days. Alternatively, the subject's AD severity score and biological sample can be obtained every 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14 days, or at intervals of 1 week to 4 weeks or 12 days to 16 days, repeated two or more times, preferably three or more times, more preferably 10 or fewer times, and more preferably 8 or fewer times.

[0062] For the score relating to the severity of the subject's Alzheimer's disease (AD), any score capable of detecting AD symptoms can be used. For example, one or more scores selected from the following may be used: EASI score and POEM score for generalized skin rash due to AD, VAS score for skin itching due to AD, VAS score for dry skin due to AD, erythema index for facial erythema due to AD, skin condition score based on observation with a camera or probe, etc. Alternatively, a score determined by comprehensively evaluating any two or more of these scores and indices may be used. Preferably, one or more scores selected from the following may be used: EASI score and POEM score for generalized skin rash due to AD, VAS score for skin itching due to AD, VAS score for dry skin due to AD, and erythema index for facial erythema due to AD.

[0063] The candidate markers used in this method are those for which the null hypothesis H0, as explained in (1. Searching for candidate markers for detecting changes in the severity of atopic dermatitis) above, is rejected. If P1=P2 is obtained for any of the candidate markers selected, an increase in the expression level of the candidate marker is considered to represent an exacerbation of the subject's AD severity, and no increase in the expression level of the candidate marker is considered to represent no exacerbation of the subject's AD severity. In this case, the candidate marker can be determined as a marker for detecting changes in the severity of AD in the subject (hereinafter also referred to as a personal marker).

[0064] In this method, one or more of the candidate markers mentioned above can be used as markers (personal markers) for detecting changes in the severity of AD in subjects, according to steps 1) and 2) above. In this case, steps 1) and 2) above may be repeated for each candidate marker, or steps 1) and 2) above may be performed in parallel for each candidate marker.

[0065] The candidate markers used in this method are preferably related to the severity of AD that we want to detect using the personal markers selected for the subject in this method (in other words, the severity of AD that we want to detect in the subject subjected to this method).

[0066] In one embodiment, the candidate markers used in this method are one or more, preferably all, selected from the group consisting of the candidate markers in Table 3, and the personal markers selected in this method are markers for detecting changes in the severity of systemic skin lesions due to AD, for example, markers for detecting changes in the severity of AD corresponding to the EASI score, and more specifically, markers that represent exacerbation and non-exacerbation of the severity of systemic skin lesions due to AD, for example, markers that represent exacerbation and non-exacerbation of AD corresponding to the EASI score. In one embodiment, the candidate markers used in this method are one or more, preferably all, selected from the group consisting of the candidate markers in Table 4, and the personal markers selected in this method are markers for detecting changes in the severity of systemic skin lesions due to AD, for example, markers for detecting changes in the severity of AD corresponding to the POEM score, and more specifically, markers that represent exacerbation and non-exacerbation of the severity of systemic skin lesions due to AD, for example, markers that represent exacerbation and non-exacerbation of AD corresponding to the POEM score. In one embodiment, the candidate markers used in the method are one or more, preferably all, selected from the group consisting of the candidate markers in Table 5, and the personal markers selected in the method are markers for detecting changes in the severity of skin itching due to AD, for example, markers for detecting changes in the severity of AD corresponding to the VAS score for skin itching, and more specifically, markers that represent exacerbation and non-exacerbation of the severity of skin itching due to AD, for example, markers that represent exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score for skin itching. In one embodiment, the candidate markers used in the method are one or more, preferably all, selected from the group consisting of the candidate markers in Table 6, and the personal markers selected in the method are markers for detecting changes in the severity of skin dryness due to AD, for example, markers for detecting changes in the severity of AD corresponding to the VAS score for skin dryness, and more specifically, markers that indicate exacerbation and non-exacerbation of the severity of skin dryness due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score for skin dryness. In one embodiment, the candidate markers used in the method are one or more, preferably all, selected from the group consisting of the candidate markers in Table 7, and the personal markers selected in the method are markers for detecting changes in the severity of facial erythema due to AD, for example, markers for detecting changes in the severity of AD corresponding to the erythema index of facial erythema, and more specifically, markers that indicate exacerbation and non-exacerbation of the severity of facial erythema due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the erythema index of facial erythema. In one embodiment, the candidate marker used in the method is at least one selected from the group consisting of the candidate markers in Table 2, and the personal marker selected in the method is a marker for detecting changes in the severity of systemic rash, pruritus, dry skin, or facial erythema due to AD, for example, a marker for detecting changes in the severity of AD corresponding to the EASI score, POEM score, VAS score for pruritus, VAS score for dry skin, or erythema index for facial erythema. More specifically, it is a marker representing exacerbation and non-exacerbation of the severity of systemic rash, pruritus, dry skin, or facial erythema due to AD, for example, a marker representing exacerbation and non-exacerbation of AD corresponding to the EASI score, POEM score, VAS score for pruritus, VAS score for dry skin, or erythema index for facial erythema.

[0067] The expression levels of candidate marker genes or their expression products in subjects can be measured by conventional methods from biological samples collected from subjects, such as cells, tissues (biopsy, etc.), body fluids (body fluids such as tissue exudate, blood, serum prepared from blood, plasma, etc.), organs, skin, urine, saliva, sweat, stratum corneum, surface lipids (SSL), stool, and hair. Commercially available kits can be used to prepare nucleic acids or proteins from biological samples. Preferred examples of nucleic acids prepared from biological samples include DNA such as genomic DNA and RNA such as mRNA.

[0068] There are no particular restrictions on the number or types of genes or their expression products whose expression levels are measured. Preferably, the expression levels of genes or their expression products corresponding to candidate markers contained in the collected biological sample can be comprehensively measured.

[0069] More preferably, the gene or its expression product whose expression level is measured is a nucleic acid or protein prepared from the subject's SSL, more preferably RNA. The site of skin from which SSL is collected is not particularly specified, and examples include skin from any part of the body such as the head, face, neck, trunk, hands and feet. Areas with high sebum secretion, such as the skin of the head or face, are preferred, and facial skin is more preferred. Furthermore, the site of skin from which SSL is collected may be either a lesion area where AD has developed or an unaffected area, but preferably, a lesion area or an unaffected area near a lesion area is preferred. Here, "near a lesion area" refers to an area within 10 cm adjacent to the lesion area.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] The expression level of nucleic acids or proteins can be measured according to the quantitative methods for nucleic acids or proteins commonly used in the field. The expression level of nucleic acids or proteins to be measured may be an expression level based on the absolute amount of nucleic acids or proteins in a biological sample, or a relative expression level relative to other standards or the total expression level of all nucleic acids or proteins.

[0074] For example, nucleic acid expression levels 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.

[0075] Protein expression levels can be measured using protein quantification methods commonly used in this 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 a target nucleic acid or protein may be measured by measuring molecules that interact with the target nucleic acid or protein. Examples of molecules that interact with nucleic acids or proteins 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.

[0076] Preferably, the expression level of SSL-derived RNA is measured. Preferably, the expression level of 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.

[0077] 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, such as 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.), the SuperScript® III Reverse Transcriptase, and the SuperScript® VILO cDNA Synthesis kit (all from Thermo Scientific Inc.). 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.

[0078] When measuring nucleic acid expression levels 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.).

[0079] 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.

[0080] 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.

[0081] 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.

[0082] When measuring nucleic acid expression levels 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.

[0083] When measuring nucleic acid expression levels 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 nucleic acid expression level can be measured.

[0084] When measuring nucleic acid expression levels using DNA microarrays, for example, a microarray is used in which nucleic acids (cDNA or DNA) that specifically hybridize to the target nucleic acid 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 nucleic acids 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 (i.e., substantially only to the target nucleic acid) under stringent conditions, and may be a nucleic acid having the entire sequence of the target nucleic acid 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 described as 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).

[0085] When measuring the expression level of a target nucleic acid 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.

[0086] When measuring the expression levels of multiple nucleic acids 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.

[0087] Probes or primers used to measure nucleic acid expression levels may be, for example, primers for specifically amplifying a target nucleic acid, or probes for specifically detecting a target nucleic acid. Here, "specific" means that the nucleic acid can be recognized or detected in such a way that substantially only the target nucleic acid is detected, for example, in Northern blotting, or substantially only the target nucleic acid is amplified in PCR, thereby generating a product or detectable substantially derived from the target nucleic acid. These probes or primers can be designed based on the nucleotide sequence of the target nucleic acid. Specific examples of the probe or primer include oligonucleotides or their complementary strands consisting of the entire or partial sequence of the target nucleic acid. The "complementary strand" is not limited to a perfectly complementary sequence, as long as it specifically recognizes the target nucleic acid; preferably it has 80% or more, more preferably 90% or more, and even more preferably 95% or more sequence identity. Sequence identity can be determined by algorithms such as NCBI BLAST as described above. Examples of primers used to measure the expression level of the nucleic acid include those that can perform specific annealing and chain elongation with respect to the target nucleic acid, 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 to measure the expression level of the nucleic acid include those that can perform specific hybridization with the target nucleic acid and have a chain length of preferably 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.

[0088] When measuring the expression level of a protein using an immunoassay, for example, an antibody against the target protein can be brought into contact with a biological sample, and the target protein bound to the antibody can be quantified. For example, in Western blotting, a primary antibody against the target protein is used, then the primary antibody is labeled with a secondary antibody labeled with a radioisotope, fluorescent substance, enzyme, etc., and the expression level of the target protein can be measured by then measuring the signal derived from the label. The antibody against the target protein may be a polyclonal antibody or a monoclonal antibody. These antibodies can be manufactured according to known methods.

[0089] (4. Method for detecting changes in the severity of atopic dermatitis) Furthermore, the present invention provides a method for detecting changes in the severity of AD in an individual subject selected in 3. above, using a marker for detecting changes in the severity of AD in the subject (a personal marker for the subject). In the method for detecting changes in the severity of AD according to the present invention (hereinafter referred to as "this detection method"), changes in the severity of AD in the subject (e.g., exacerbation or non-exacerbation of symptoms) are detected based on changes in the expression level of a personal marker for the subject. An increase in the expression level of the personal marker represents an exacerbation of the subject's AD severity, while no increase in the expression level represents no exacerbation of the subject's AD severity.

[0090] This detection method includes measuring the expression level of a personal marker for a subject in a biological sample taken from that subject. This detection method may further include taking a biological sample from a subject.

[0091] Examples of subjects to be used in this detection method include mammals, including humans and non-human mammals, with humans being preferred. If the subject is human, their sex, age, and race are not particularly limited and may include infants to the elderly. For example, this could include individuals who need or wish to detect changes in the severity of AD, such as those who have developed AD. The personal marker for the subject is a marker selected for the subject from the candidate markers described in section 2 above, based on the method for selecting markers to detect changes in the severity of AD in the subject, as described in section 3 above. The personal marker for the subject may be identified in advance before the detection method, or it may be identified during the procedure of the detection method. The type of biological sample collected and the procedure for measuring the expression level of the marker are the same as in the method for selecting the personal marker. There are no particular restrictions on the number of personal markers whose expression levels are measured; there may be one or more. The personal marker may be a nucleic acid marker or a protein marker. Alternatively, a combination of nucleic acid markers and protein markers may be used. Preferably, the biological sample is SSL, and the marker is SSL-derived RNA. The procedures for collecting SSL, extracting markers from SSL, and measuring the expression level of SSL-derived RNA are as described above.

[0092] In this detection method, the expression level of the same marker measured in the same subject at a certain time (reference time) can be set as the reference value. For example, if the measured expression level of the personal marker is higher than the reference value, it can be detected that the subject's AD severity has worsened compared to the reference time. On the other hand, if the expression level of the personal marker is lower than the reference value or there is no difference, it can be detected that the subject's AD severity has not worsened compared to the reference time. In one embodiment, the expression level of the personal marker in a subject is measured over time, and the expression level at any of the second or subsequent measurement sessions is compared to the expression level at the previous or earlier measurement session (which serves as the reference value). An expression level higher than the reference value indicates an exacerbation of the severity of AD in the subject, while an expression level lower than the reference value or with no difference indicates no exacerbation of the severity of AD in the subject. In another embodiment, the severity of a subject's AD is determined at a certain point in time (reference time), and the expression level of the personal marker in the subject is measured and set as a reference value. Subsequently, the expression level of the personal marker in the subject is measured and compared with the reference value. An expression level higher than the reference value indicates an exacerbation of the subject's AD severity from the reference time, while an expression level lower than the reference value or with no difference indicates no exacerbation of the subject's AD severity from the reference time.

[0093] In one embodiment, if the expression level of a personal marker is statistically significantly lower than the reference value, the expression level of the marker may be judged to be lower than the reference value, and if the expression level of a personal marker is statistically significantly higher than the reference value, the expression level of the marker may be judged to be higher than the reference value. In another embodiment, if the expression level of a personal marker is preferably 99% or less, more preferably 95% or less, and even more preferably 91% or less of the reference value, the expression level of the marker may be judged to be lower than the reference value, and if the expression level of a personal marker is preferably 101% or more, more preferably 105% or more, and even more preferably 110% or more of the reference value, the expression level of the marker may be judged to be higher than the reference value. When using multiple markers as personal markers, changes in the severity of AD can be detected by comparing the expression levels of each marker with reference values ​​and checking whether a certain percentage, for example, 50% or more, preferably 70% or more, more preferably 90% or more, and even more preferably 100%, of the marker expression levels differ from the reference values.

[0094] In a preferred embodiment, the severity of AD detected by this detection method is at least one selected from the group consisting of the severity of generalized rash due to AD, the severity of itching, the severity of dry skin, and the severity of facial erythema. In another preferred embodiment, the severity of AD detected by this detection method is at least one selected from the group consisting of the EASI score and POEM score for generalized rash due to AD, the VAS score for itching due to AD, the VAS score for dry skin due to AD, and the erythema index for facial erythema due to AD. The types of AD severity detected by this detection method may vary depending on the type of personal marker used. In one example, if the personal marker used in this detection method includes at least one gene or its expression product shown in Table 3, it is possible to detect changes in the severity of systemic skin lesions due to AD, for example, changes in the severity of AD corresponding to the EASI score. In another example, if the personal marker used in this detection method includes at least one gene or its expression product shown in Table 4, it is possible to detect changes in the severity of systemic skin lesions due to AD, for example, changes in the severity of AD corresponding to the POEM score. In another example, if the personal marker used in this detection method includes at least one gene or its expression product shown in Table 5, it is possible to detect changes in the severity of skin itching due to AD, for example, changes in the severity of AD corresponding to the VAS score for skin itching. In another example, if the personal marker used in this detection method includes at least one gene or its expression product shown in Table 6, it is possible to detect changes in the severity of skin dryness due to AD, for example, changes in the severity of AD corresponding to the VAS score for skin dryness. In another example, if the personal marker used in this detection method includes at least one gene or its expression product shown in Table 7, it is possible to detect changes in the severity of facial erythema due to AD, for example, changes in the severity of AD corresponding to the facial erythema index. In another example, if the personal markers used in this detection method include the genes or their expression products shown in Tables 3-7, it is possible to detect changes in the severity of systemic skin rash, itchiness, dryness, and facial erythema caused by AD, including changes in the severity of AD corresponding to the EASI score, POEM score, VAS score for itchiness, VAS score for dryness, and erythema index for facial erythema.

[0095] (5. Kit for detecting changes in AD symptoms) In a further embodiment, the present invention provides a kit for detecting changes in the severity of AD in a subject according to the method for detecting changes in the severity of AD according to the present invention as described in Section 4 above. In one embodiment, the kit of the present invention comprises reagents or instruments for measuring the expression levels of the markers shown in Table 2 above. For example, the kit of the present invention may comprise reagents for amplifying or quantifying nucleic acid markers (e.g., reverse transcriptase, PCR reagents, primers, probes, sequencing adapter sequences, etc.) or reagents for quantifying protein markers (e.g., reagents for immunological measurements, antibodies, etc.). Preferably, the kit of the present invention contains oligonucleotides that specifically hybridize with nucleic acid markers (e.g., primers or probes for PCR) or antibodies that recognize protein markers. Preferably, the kit of the present invention comprises indicators or guidance for detecting the expression levels of the markers. For example, the kit of the present invention may comprise guidance describing the symptoms of AD associated with each marker (e.g., rash, itching, dry skin, facial erythema). 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 a marker from the biological sample (for example, a nucleic acid purification reagent), a preservative for the sample collection device after biological sample collection, and a storage container.

[0096] 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.

[0097] [1] A method for selecting a marker for detecting changes in the severity of atopic dermatitis in a subject, 1) Based on the scores relating to the severity of atopic dermatitis in the subject at multiple time points separated by time, and the expression levels of one of the genes or their expression products shown in Table 1 above in the biological samples collected from the subject at those multiple time points, calculate P1 and P2 as follows:

number

[10] Preferably, the method according to [9], wherein the severity of the atopic dermatitis is the severity of the atopic dermatitis corresponding to the VAS score for dry skin.

[11] Preferably, the gene or its expression product is one of the genes and their expression products shown in Table 7, and the severity of the atopic dermatitis is the severity of facial erythema due to atopic dermatitis, according to [1] or [2].

[12] Preferably, the method according to

[11] , wherein the severity of the atopic dermatitis is the severity of the atopic dermatitis corresponding to the erythema index related to facial erythema.

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

[12] , wherein the multiple periods separated over time are preferably separated by an interval of 1 day or more, more preferably 3 days or more, even more preferably 1 week or more, even more preferably 1 week to 4 weeks or even more preferably 12 days to 16 days or even more.

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

[13] , wherein n is preferably 3 or more, more preferably 4 or more, and preferably 10 or less, more preferably 8 or less.

[15] Preferably, the method according to any one of [1] to

[14] , wherein the biological sample is a lipid on the surface of the skin.

[16] Preferably, the method according to

[15] , wherein the expression level of the gene or its expression product is the expression level of RNA contained in lipids on the skin surface.

[0098]

[17] A method for detecting changes in the severity of atopic dermatitis in a subject, To measure the expression level of a marker for detecting changes in the severity of atopic dermatitis, determined by any one of the methods described in [1] to

[16] , in biological samples taken from subjects, Based on changes in the expression level of the marker, the severity of atopic dermatitis in the subject is detected. Methods that include...

[18] Preferably, the method according to

[17] , wherein the severity of the atopic dermatitis is the severity of generalized skin lesions due to atopic dermatitis, the severity of itching of the skin due to atopic dermatitis, the severity of dry skin due to atopic dermatitis, or the severity of facial erythema due to atopic dermatitis.

[19] Preferably, the marker comprises at least one selected from the group consisting of genes and their expression products shown in Table 3, The severity of the atopic dermatitis is preferably the severity of systemic skin lesions due to atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the EASI scale. The method described in

[17] or

[18] .

[20] Preferably, the marker comprises at least one selected from the group consisting of genes and their expression products shown in Table 4, The severity of the atopic dermatitis is preferably the severity of systemic skin lesions due to atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to POEM. The method described in

[17] or

[18] .

[21] Preferably, the marker comprises at least one selected from the group consisting of genes and their expression products shown in Table 5, The severity of the atopic dermatitis is preferably the severity of skin itching due to atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the VAS score for skin itching. The method described in

[17] or

[18] .

[22] Preferably, the marker includes at least one selected from the group consisting of genes and their expression products shown in Table 6, The severity of the atopic dermatitis is preferably the severity of skin dryness due to atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the VAS score for skin dryness. The method described in

[17] or

[18] .

[23] Preferably, the marker comprises at least one selected from the group consisting of genes and their expression products shown in Table 7, The severity of the atopic dermatitis is preferably the severity of facial erythema due to atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the erythema index related to facial erythema. The method described in

[17] or

[18] .

[24] Preferably, the markers include the genes or expression products thereof shown in Tables 3 to 7, The severity of atopic dermatitis is preferably the severity of systemic skin lesions due to atopic dermatitis, the severity of itching due to atopic dermatitis, the severity of dry skin due to atopic dermatitis, and the severity of facial erythema due to atopic dermatitis; more preferably, the severity of atopic dermatitis corresponds to the EASI score, the severity of atopic dermatitis corresponds to the POEM score, the VAS score for itching, the VAS score for dry skin, and the severity of atopic dermatitis corresponds to the erythema index related to facial erythema. The method described in

[17] or

[18] .

[25] Preferably, if the expression level of the marker is higher than a reference value, it is detected that the severity of the subject's atopic dermatitis has worsened compared to the time when the reference value was measured, while if the expression level of the marker is lower than a reference value or there is no difference, it is detected that the severity of the subject's atopic dermatitis has not worsened compared to the time when the reference value was measured, according to any one of

[17] to

[24] .

[26] Preferably, the reference value is The expression level of the marker in the subject measured at a specific time, The expression level of the marker in the subject measured in the past, The method described in

[25] .

[27] Preferably, the method according to

[25] or

[26] , wherein if the expression level of the marker is statistically significantly higher than the reference value, the expression level of the marker is determined to be higher than the reference value.

[28] The method according to

[25] or

[26] , wherein preferably, if the expression level of the marker is 101% or more, more preferably 105% or more, and even more preferably 110% or more of the reference value, the expression level of the marker is determined to be higher than the reference value.

[0099] A kit for detecting changes in the severity of atopic dermatitis, used in any one of the methods described in any one of the items [1] to

[28] , comprising an oligonucleotide that specifically hybridizes with a gene or nucleic acid derived therefrom used in any one of the methods described in any one of the items [1] to

[16] , or an antibody that recognizes the expression product of a gene used in any one of the methods described in any one of the items [1] to

[16] .

[30] A kit for detecting changes in the severity of atopic dermatitis, used in any one of the methods described in

[17] to

[28] , comprising an oligonucleotide that specifically hybridizes with the gene shown in Table 1 above or nucleic acids derived therefrom, or an antibody that recognizes the expression product of the gene shown in Table 1 above.

[31] Candidate markers for selecting markers for detecting changes in the severity of atopic dermatitis, consisting of the genes or expression products shown in Table 1 above.

[32] Preferably, the candidate marker according to

[31] , wherein the severity of atopic dermatitis is the severity of generalized skin rash due to atopic dermatitis, the severity of itching of the skin due to atopic dermatitis, the severity of dry skin due to atopic dermatitis, or the severity of facial erythema due to atopic dermatitis.

[33] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of systemic skin lesions due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 3 above, as described in

[31] or

[32] .

[34] Preferably, the candidate marker according to

[33] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to EASI (Eczema Area and Severity Index).

[35] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of systemic skin lesions due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 4 above, as described in

[31] or

[32] .

[36] Preferably, the candidate marker according to

[35] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to POEM (Patient Oriented Eczema Measure).

[37] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of skin itching due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 5 above, as described in

[31] or

[32] .

[38] Preferably, the candidate marker according to

[37] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score of skin itchiness.

[39] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of skin dryness due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 6 above, as described in

[31] or

[32] .

[40] Preferably, the candidate marker according to

[39] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score for skin dryness.

[41] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of facial erythema due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 7 above, as described in

[31] or

[32] .

[42] Preferably, the candidate marker according to

[41] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to an erythema index related to facial erythema.

[43] Use of the genes or expression products thereof shown in Table 1 above as candidate markers for selecting markers for detecting changes in the severity of atopic dermatitis, or use in the manufacture of candidate markers for selecting markers for detecting changes in the severity of atopic dermatitis.

[44] Preferably, the use according to

[43] , wherein the severity of the atopic dermatitis is the severity of generalized skin rash due to atopic dermatitis, the severity of itching of the skin due to atopic dermatitis, the severity of dry skin due to atopic dermatitis, or the severity of facial erythema due to atopic dermatitis.

[45] Preferably, the use according to

[43] or

[44] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of systemic skin lesions due to atopic dermatitis, and the candidate marker is a gene or expression product thereof as shown in Table 3 above.

[46] Preferably, the use according to

[45] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to EASI (Eczema Area and Severity Index).

[47] Preferably, the use according to

[43] or

[44] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of systemic skin lesions due to atopic dermatitis, and the candidate marker is a gene or expression product thereof as shown in Table 4 above.

[48] ​​Preferably, the use according to

[47] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to POEM (Patient Oriented Eczema Measure).

[49] Preferably, the use according to

[43] or

[44] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of skin itching due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 5 above.

[50] Preferably, the use according to

[49] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score of skin itchiness.

[51] Preferably, the use according to

[43] or

[44] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of skin dryness due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 6 above.

[52] Preferably, the use according to

[51] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score for skin dryness.

[53] Preferably, the use according to

[43] or

[44] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of facial erythema due to atopic dermatitis, and the candidate marker is a gene or expression product thereof shown in Table 7 above.

[54] Preferably, the use according to

[53] , wherein the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis corresponding to an erythema index related to facial erythema. [Examples]

[0100] The present invention will be described in more detail below based on examples, but the present invention is not limited thereto. Example 1: Searching for genes related to changes in the severity of atopic dermatitis using SSL-derived RNA. 1) Acquisition of a score related to the severity of atopic dermatitis and SSL collection The study included 18 adult males (ages 23-57) with atopic dermatitis (AD). At the time of the initial measurement, the subjects were diagnosed by a dermatologist as having mild to moderate atopic dermatitis. The subjects visited the facility four times, every 14 days, to have their AD severity scores and SSL samples collected. Hereafter, the collected AD severity scores and SSL samples will be referred to as the 1st, 2nd, 3rd, and 4th AD severity scores and SSL samples, respectively, based on the order of their visits. As AD severity scores, the following were used: a physician's systemic EASI score (Hanifin et al., Exp Dermatol, 10, 2001, scoring symptoms from 0 to 72 based on systemic skin rash); a subject's own systemic POEM score (Charman et al., Arch Dermatol, 140, 2004, scoring symptoms from 0 to 28 based on systemic skin rash); a systemic VAS score for itchiness (scoring the intensity of itchiness from 0 to 100); a systemic VAS score for dryness (scoring the intensity of dryness from 0 to 100); and a facial erythema index based on facial images taken with a hyperspectral imaging device (Hyperspectral Camera NH-7, Eva Japan Co., Ltd.) (see Japanese Patent Publication No. 2018-23756 and Dawson et al., Phys Med Biol, 25, 1980). In calculating the facial erythema index, the erythema index was calculated for each pixel on the frontal facial image obtained using a hyperspectral imaging device according to formula (4) below. Arbitrary ROIs (Regions of Interest) were defined on the image corresponding to the forehead, above both eyes, and both cheeks, and the average value of the erythema indices at the five ROIs was used as the facial erythema index.

[0101]

number

[0102] Sebum was collected from the entire face of each subject using an oil-absorbing film (5 x 8 cm, made of polypropylene, 3M). The oil-absorbing films were transferred to vials and stored at -80°C for approximately one month until use for RNA extraction.

[0103] 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.

[0104] 3) Data used The read counts of each read obtained by sequencing the SSL-derived RNA of the subjects measured in 2) above were used as data for the expression level of each RNA. Genes whose amplification region in sequencing spanned at least two or more exons were selected as the genes to be analyzed. To correct for differences in total read counts between samples, the read counts of the genes to be analyzed were converted to RPM (Reads per million mapped reads) values. Of these, 4845 genes for which a read count of 20 or more was obtained in more than 90% of the samples were used for the following analysis. Furthermore, to approximate the RPM values ​​to a normal distribution, they were converted to base 2 logarithms (Log2(RPM+1) values) by adding the integer 1. Following the above procedure, expression level data (Log2(RPM+1) values) for 4845 genes were created for the first, second, third, and fourth SSL samples from 18 subjects. These are referred to as the 1st, 2nd, 3rd, and 4th expression levels, respectively, based on the order from the first visit.

[0105] 4) Data Analysis For each of the 18 AD patients obtained in 1) above, P1 is an index that shows the trend of changes in disease severity every 14 days, based on the AD disease severity scores from the 1st to the 4th time. j P1 was calculated according to the following formula (1)'. j Based on the progression pattern of the AD severity score, the value will be one of eight possible values: "0, 1, 10, 11, 100, 101, 110, 111".

[0106]

number

[0107] In formula (1)', j represents the sample (or subject) ID, and in this embodiment, j is an integer from 1 to 18. k represents the order in which the AD severity score was obtained. In this example, the score was obtained four times, so k is an integer from 1 to 3. S j,k This represents the k-th AD severity score for a subject with ID j.

[0108] Next, based on the expression level data (Log2(RPM+1) values) from the 1st to 4th cycles for each of the 18 AD patients calculated in 3) above, P2 is an index that shows the change in gene expression levels every 14 days. i,j This was calculated according to equation (2)' below. P2 i,j Based on the pattern of changes in gene expression levels, this value will be one of eight possible values: "0, 1, 10, 11, 100, 101, 110, 111".

[0109]

number

[0110] In formula (2)', i represents the gene ID, and in this embodiment, i is an integer between 1 and 4845. j represents the subject ID, and in this embodiment, j is an integer from 1 to 18. k represents the SSL sample acquisition order, and in this example, k is an integer from 1 to 3. E i,j,k This represents the expression level of the gene with ID i in the SSL sample taken for the kth time from the subject with ID j.

[0111] At this time, from the sample (or subjects) with ID j (j=1~18), a fixed P1 for each ID is selected. j And, for the gene with ID i (i=1~4845) in the sample, P2 i,j This is obtained. Here, we defined the null hypothesis H0 and the alternative hypothesis H1 as follows. H0:P2 i,j The probability of taking one of the eight values ​​"0, 1, 10, 11, 100, 101, 110, 111" is equally 1 / 8 for each. H1:P2 i,j The probability of taking one of the eight values ​​"0, 1, 10, 11, 100, 101, 110, 111" is not equal to 1 / 8 for each. If the null hypothesis is true, P2 i,jEach has a probability of 1 / 8 of taking on one of the eight values of "0, 1, 10, 11, 100, 101, 110, 111", and P1 j = P2 i,j is assumed to have a probability of 1 / 8. When the null hypothesis can be rejected, the alternative hypothesis is adopted. If P1 j = P2 i,j is assumed to have a probability other than 1 / 8.

[0112] Next, for the 4845 genes, the number of samples where P1 j = P2 i,j in the gene with ID i was counted, and this number was taken as the number of matches m i . Assuming that the null hypothesis H0 (the probability that P1 j = P2 i,j is 1 / 8) holds, the probability p i that P1 j = P2 i,j in m i samples out of 18 samples was calculated from the following equation (3)'. If p i is less than the one-sided significance level of 0.005, the null hypothesis H0 was rejected and the alternative hypothesis H1 was adopted.

[0113]

Number

[0114] 5) Genes associated with the AD severity score i) Genes associated with the EASI score As a result of the analysis in 4) using the EASI score as the AD severity score, in the 23 genes shown in Table 8, P1 j and P2 i,j matched in 7 or more out of 18 samples, and p i was below the significance level. That is, P1 j = P2 i,jThe probability of this occurring is not 1 / 8, and therefore, it was suggested that these 23 genes may be linked to the EASI score, not by chance. Furthermore, regarding 20 of the 23 genes shown in Table 8 (indicated by * in the table), there have been no previous reports suggesting an association with atopic dermatitis. Therefore, it was judged that these genes could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of skin lesions due to atopic dermatitis that are reflected in the EASI score.

[0115] [Table 8]

[0116] ii) Genes linked to POEM score Analysis using the POEM score as the AD severity score4) showed that in the seven genes shown in Table 9, P1 was present in 7 or more out of 18 samples. j and P2 i,j They match, p i The P1 level in the seven genes shown in Table 9 was below the significance level. j =P2 i,j The probability of this occurring is not 1 / 8, and therefore, it was suggested that these seven genes may be linked to the POEM score, not by chance. Furthermore, regarding six of the seven genes shown in Table 9 (indicated by * in the table), there have been no previous reports suggesting an association with atopic dermatitis, so it was judged that they could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of skin lesions due to atopic dermatitis that are reflected in the POEM score.

[0117] [Table 9]

[0118] iii) Genes linked to itching VAS score Analysis using the VAS score for skin pruritus as the AD severity score4) showed that in 27 genes shown in Table 10, P1 was present in 7 or more out of 18 samples. j and P2 i,j They match, pi The P1 level in the 27 genes shown in Table 10 was below the significance level. j =P2 i,j The probability of this occurring is not 1 / 8, and therefore, it was suggested that these 27 genes may be linked to the VAS score for skin itching, not by chance. Furthermore, since there have been no previous reports suggesting an association between 24 of the 27 genes shown in Table 10 (indicated by * in the table), it was judged that they could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of skin itching symptoms due to atopic dermatitis that are reflected in the VAS score for skin itching.

[0119] [Table 10]

[0120] iv) Genes linked to dry VAS score Analysis using the VAS score for skin dryness as the AD severity score4) showed that in the 26 genes shown in Table 11, P1 was present in 7 or more out of 18 samples. j and P2 i,j They match, p i The P1 level in the 26 genes shown in Table 11 was below the significance level. j =P2 i,j The probability of this occurring is not 1 / 8, and therefore, it was suggested that these 26 genes may be linked to the VAS score for skin dryness, not by chance. Furthermore, since there have been no previous reports suggesting an association between all 26 of the 26 genes shown in Table 11 (indicated by * in the table), it was judged that they could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of skin dryness symptoms due to atopic dermatitis that are reflected in the VAS score for skin dryness.

[0121] [Table 11]

[0122] v) Genes linked to the erythema index Analysis using the facial erythema index as an AD severity score4) showed that in 54 genes shown in Table 12, P1 was present in 7 or more out of 18 samples. j and P2 i,j They match, p i The P1 level in the 54 genes shown in Table 12 was below the significance level. j =P2 i,j The probability of this occurring is not 1 / 8, and therefore, it was suggested that these 54 genes may be linked to the facial erythema index, not by chance. Furthermore, for 46 of the 54 genes shown in Table 12 (indicated by * in the table), there have been no previous reports suggesting an association with atopic dermatitis. Therefore, it was judged that these genes could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of facial erythema due to atopic dermatitis that are reflected in the facial erythema index.

[0123] [Table 12]

[0124] Example 2: Selection of markers for detecting changes in the severity of atopic dermatitis For each candidate marker gene linked to the EASI score identified in Example 1, the agreement between the trend patterns of gene expression levels and the trend patterns of EASI scores in 18 subjects was examined. Genes whose trend patterns of expression levels matched the trend patterns of the subjects' EASI scores are indicated with a circle in Table 13.

[0125] [Table 13]

[0126] In each subject shown in Table 13, the genes or their expression products marked with a circle (○) can be selected as markers for detecting changes in the severity of atopic dermatitis in that subject, particularly changes in the severity of skin lesions as indicated by the EASI score. Similarly, when POEM, itchiness VAS, dryness VAS, and erythema index are used as AD severity scores, genes or their expression products with matching progression patterns can be selected as markers for detecting changes in the severity of atopic dermatitis in that subject.

Claims

1. 1. A method for selecting a marker for detecting a change in severity of atopic dermatitis in a subject, comprising: 1) calculating P1 and P2 based on the score relating to the severity of atopic dermatitis of the subject at multiple time points separated by time and the expression level of any one of the genes or expression products thereof shown in Table 1 below in biological samples collected from the subject at the multiple time points; [0010] Where: n represents the total number of times the subject's atopic dermatitis severity score and biological samples were obtained, k represents the score related to the severity of atopic dermatitis of the subject and the order of acquisition of the biological sample, S k represents the score related to the severity of atopic dermatitis of the subject measured at the kth time, E k represents the expression level of the gene or its expression product in the biological sample collected at the kth time; 2) when P1=P2, determining the gene or its expression product as a marker for detecting a change in severity of atopic dermatitis in the subject; A method comprising: 【number】

2. The method according to claim 1, wherein the severity of atopic dermatitis is the severity of a systemic skin rash caused by atopic dermatitis, the severity of skin itching caused by atopic dermatitis, the severity of dry skin caused by atopic dermatitis, or the severity of facial erythema caused by atopic dermatitis.

3. The method of claim 1 or 2, wherein the gene or its expression product is any one of the following genes: CLTC, PDZD8, CEACAM1, CRISPLD2, EFTUD2, GTF2H1, LDHA, NSFP1, PKP1, PSMA1, RABGGTB, SERPINB1, SF3B1, SIGLEC5, STEAP4, TMED10, TMED5, TPMT, YWHAB, and ZDHHC12, and their expression products, and the severity of atopic dermatitis is the severity of a systemic skin rash caused by atopic dermatitis.

4. 4. The method according to claim 3, wherein the severity of the atopic dermatitis is a severity of the atopic dermatitis corresponding to EASI (Eczema Area and Severity Index).

5. The method according to claim 1 or 2, wherein the gene or its expression product is any one of the following genes: BNIP3L, CD1E, DDHD1, MLF2, NPC1, and SCNN1B, and their expression products, and the severity of atopic dermatitis is the severity of a systemic skin rash caused by atopic dermatitis.

6. 6. The method according to claim 5, wherein the severity of the atopic dermatitis is a severity of the atopic dermatitis corresponding to POEM (Patient Oriented Eczema Measure).

7. The method of claim 1 or 2, wherein the gene or its expression product is any one of the following genes: KDM5D, RBM7, CCDC125, CDKAL1, CERS5, DAD1, EMC2, FAM210A, GBP1, GHITM, HSBP1, IGSF6, LSM1, MOSPD2, MXD1, NUDC, NUP58, PDXK, PRDX3, PRKAR1A, PTPN1, SERINC1, SRRM2, and TM2D1, and their expression products, and the severity of atopic dermatitis is the severity of skin itch caused by atopic dermatitis.

8. 8. The method according to claim 7, wherein the severity of atopic dermatitis is a severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score of skin itching.

9. The method of claim 1 or 2, wherein the gene or its expression product is any one of the following genes: RPLP0, MRPL23, RPL10A, CNKSR3, ECHS1, GPATCH2, GSR, HTATSF1, MPC2, MRPL42, MRPS22, MRPS24, NDUFS6, NFYC, PHB, RPL22, RPL37A, RPS12, RPS4X, SLC25A3, SLIRP, TBC1D9, TOMM20, TTC14, UBE2K, and ZNF791, and their expression products, and the severity of atopic dermatitis is the severity of dry skin caused by atopic dermatitis.

10. 10. The method according to claim 9, wherein the severity of atopic dermatitis is a severity of atopic dermatitis corresponding to a VAS (Visual Analog Scaling) score of dry skin.

11. The gene or its expression product is one of the following genes: CCDC186, NCOA2, A2ML1, BSPRY, CHAC1, DNAJA1, FCHSD1, IFI27, MAPK13, OSBP2, RXRB, SLC22A23, SPRR2F, ACAT2, AFTPH, CLTB, CPEB4, CTNNBIP1, DNAJA3, DOP1A, FRMPD1, GAN, GDPD3, GJB5, HIP1R, IFFO2, ING4, and KPN The method of claim 1 or 2, wherein the atopic dermatitis severity is any one of B1, LRATD2, MED31, NUAK2, PAN3, PDCD6, SASH1, SCNN1G, SDR9C7, SEC61A1, SERPINA9, SMIM5, TINCR, TMED7, TMEM123, TRPC4AP, TUFT1, VCP, and ZFPL1, and their expression products, and the severity of the atopic dermatitis is the severity of facial erythema caused by atopic dermatitis.

12. The method according to claim 11, wherein the severity of the atopic dermatitis is a severity of the atopic dermatitis corresponding to an erythema index for facial erythema.

13. The method according to any one of claims 1 to 12, wherein the multiple time periods separated by chronological intervals are multiple time periods spaced at least 12 days apart and no more than 16 days apart.

14. The method according to any one of claims 1 to 13, wherein n is 3 or more.

15. The method according to any one of claims 1 to 14, wherein the biological sample is lipids on the surface of the skin.

16. The method according to claim 15 , wherein the expression level of the gene or its expression product is the expression level of RNA contained in lipids on the skin surface.

17. A method for measuring an expression level of a marker to detect a change in severity of atopic dermatitis in a subject based on a change in the expression level of the marker, comprising: A method comprising measuring the expression level of a marker for detecting a change in the severity of atopic dermatitis, determined by the method according to any one of claims 1 to 16, in a biological sample collected from a subject.

18. A kit for detecting a change in severity of atopic dermatitis, which is used in the method according to claim 17, comprising an oligonucleotide that specifically hybridizes with the gene used in the method according to any one of claims 1 to 16 or a nucleic acid derived therefrom, or an antibody that recognizes the expression product of the gene used in the method according to any one of claims 1 to 16.

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