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 a change in the severity of atopic dermatitis, a marker obtained by the selection method, and a method for detecting a change in the severity of atopic dermatitis using the marker. [Background technology]

[0002] Atopic dermatitis (AD) is an eczematous skin disease that primarily affects individuals with atopic predisposition. Typical symptoms of AD include chronic and recurrent itching, rash, erythema, etc., occurring bilaterally and contralaterally, as well as dyskeratosis, impaired barrier function, and dry skin. AD often develops in infants and young children and tends to improve with age. However, in recent years, adult-onset and refractory atopic dermatitis cases have been increasing. It is known that AD is characterized by a complex interplay of various etiologies, resulting in a diversity of symptoms and phenotypes, leading to repeated exacerbations and remissions (Non-Patent Document 1). For example, it has been reported that if topical medications are not continued to moisturize after induction of remission, approximately 40% of AD patients experience a relapse of symptoms within 14 days, and approximately 60% within 28 days (Non-Patent Document 2). Therefore, when treating AD, it is necessary to accurately understand the severity of the disease, including the diversity of symptoms and phenotypes.

[0003] Conventional methods for assessing the severity of AD include evaluation based on visual findings by physicians. These findings include dryness, erythema, scaling, papules, excoriations, edema, crusting, small blisters, erosions, and pruritic nodules. These findings are scored using indices such as the Eczema Area and Severity Index (EASI) and the Severity SCORing of Atopic Dermatitis (SCORAD). Other methods use high-performance cameras and probes to obtain objective numerical values ​​for AD symptoms. Patients can also assess AD themselves based on visual findings and subjective tactile perception. Scoring indices for this assessment 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 to evaluate AD pathology not only based on phenotypes (represented by symptoms and subjective symptoms) but also on pathobiological mechanisms (endotypes) to aid in the selection of optimal treatments. In other words, even among AD patients who exhibit similar phenotypes, these may be caused by different molecular mechanisms. It is believed that subdividing the pathology of AD patients by combining phenotypes and endotypes will lead to optimal treatment tailored to individual patients. Currently, objective understanding of disease pathology, or understanding of pathology taking endotypes into account, often relies on the presence of genes or their expression products in skin biopsies, blood, stratum corneum, etc., or the presence of specific cell types (collectively referred to as biomarkers). Previously, biomarkers proposed for assessing the presence or absence of AD and its severity include peripheral blood eosinophil count, serum total IgE level, lactate dehydrogenase (LDH) level, 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 demonstrate that the abundance of these biomarkers fluctuates with changes in the severity of the disease in the same individual.

[0005] In recent years, technologies have been developed to examine the current and future physiological state of the human body by analyzing nucleic acids such as DNA and RNA in biological samples. Biologically derived nucleic acids can be extracted from body fluids such as blood, secretions, tissues, etc. Furthermore, it has recently 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 Publication No. 2018 / 008319 [Patent Document 2] Japanese Patent Application Publication No. 2020-074769 [Non-patent literature]

[0007] [Non-Patent Document 1] Kato et al., Journal of the Japanese Society of Dermatology, 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 Summary of the Invention [Problem to be solved by the invention]

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

[0009] The present invention provides a method for selecting a marker for detecting a change in severity of atopic dermatitis in a subject, comprising the steps of: 1) Calculating P1 and P2 below based on the score relating to the severity of atopic dermatitis of the subject at multiple time points separated over 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;

number

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

[0011] The present invention provides candidate markers for detecting changes in the severity of atopic dermatitis. From these candidate markers, a marker for detecting changes in the severity of atopic dermatitis that is appropriate for each individual can be selected. This marker enables simple and objective detection of changes in the severity of atopic dermatitis (e.g., exacerbation or improvement) in individual atopic dermatitis patients. Use of this marker makes it possible to accurately understand the pathological condition of individual atopic dermatitis patients and provide optimal treatment tailored to each individual patient. DETAILED DESCRIPTION OF THE INVENTION

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

[0013] As used herein, the terms "nucleic acid" or "polynucleotide" refer to 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] As used herein, the term "gene" encompasses double-stranded DNA, including human genomic DNA, as well as single-stranded DNA (positive strand) including cDNA, single-stranded DNA (complementary strand) having a sequence complementary to the positive strand, and fragments thereof, and refers to DNA containing some biological information in the sequence information of the bases that make up the DNA. Furthermore, as used herein, "gene" encompasses not only "genes" represented by a specific base sequence, but also their homologs (i.e., homologs or orthologs), mutants such as genetic polymorphisms, and derivatives.

[0015] In the present invention, the term "expression product" of a gene encompasses both transcription products and translation products of the gene. A "transcription product" is RNA generated by transcription from a gene (DNA), and a "translation product" refers to a protein encoded by the gene that is translated and synthesized based on the RNA.

[0016] As used herein, "skin surface lipids (SSL)" refers to the fat-soluble fraction present on the surface of the skin, sometimes called sebum. Generally, SSL mainly contains 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, the term "skin" is a general term for an area including tissues such as the stratum corneum, epidermis, dermis, hair follicles, sweat glands, sebaceous glands and other glands.

[0018] As used herein, "atopic dermatitis (also referred to as "AD")" refers to a disease whose primary pathogenic factor is a pruritic eczema that repeatedly worsens and improves, and many patients are said to have a predisposition to atopy. Predisposition to atopy includes i) a family history or medical history (one or more of the following diseases: bronchial asthma, allergic rhinitis / conjunctivitis, and atopic dermatitis), or ii) a predisposition to produce IgE antibodies.

[0019] As used herein, the "severity" of atopic dermatitis (AD) refers not to the presence or absence of AD, but to the level of severity of AD symptoms, and includes not only broad classifications such as mild, moderate, and severe, but also classifications based on more subtle differences. The "severity" of AD can be determined, for example, based on various known evaluation scores for evaluating AD symptoms. In this specification, such evaluation scores are referred to as "scores related to the severity of atopic dermatitis (AD)." Examples of scores relating to the severity of AD include the EASI score and POEM score for whole-body skin rash due to AD, the VAS score for skin itching due to AD, and the VAS score for dry skin due to AD (Atopic Dermatitis Treatment Guidelines, published by the Japanese Dermatological Association, Journal of the Japanese Dermatological Association: 128(12), 2431-2502(2018)). The erythema index for facial erythema due to AD (see JP 2018-23756 A and Dawson et al., Phys Med Biol, 25, 1980) may also be used. Alternatively, a score determined by comprehensively evaluating two or more of these scores and indexes may also be used. The score relating to the severity of AD itself may be used as the "severity" of the AD symptoms.

[0020] As used herein, "detection" of a change in the severity of AD can also be expressed in other terms, such as examination, measurement, judgment, or evaluation support. Note that the terms "detection," "examination," "measurement," "judgment," or "evaluation" of a change in the severity of AD as used herein do not include a diagnosis of a change in the severity of AD by a physician.

[0021] (1. Search 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 AD. More accurate detection of changes in the severity of AD patients would enable a more accurate understanding of the patient's condition and ultimately the provision of optimal treatment tailored to each patient. Previous markers for detecting the presence or absence of AD and the severity of the disease have primarily been discovered based on population analyses, i.e., comparisons between groups with different severity levels (e.g., affected and normal groups, or severe and mild groups). However, these previous markers discovered through population analyses do not necessarily reflect subtle differences in the severity of AD in individuals within each group, making it difficult to detect changes in the severity of AD using these previous markers.

[0022] The present inventors first attempted to search for candidate markers for detecting changes in AD severity. Specifically, the AD severity scores of subjects were obtained over time, and the expression levels of various genes in the subjects were also obtained over time. Next, the relationship between changes in AD severity scores and changes in gene expression levels in each subject was examined. As a result, genes were found whose expression levels changed in accordance with the changes in the AD severity scores of individual subjects over time, and whose expression level behavior was commonly observed in many subjects. These genes or their expression products were used as candidate markers for detecting changes in AD severity in subjects.

[0023] Specifically, as shown in the Examples below, 18 adults with atopic dermatitis were used as subjects in the search for candidate markers. First, the AD severity score for each subject was obtained four times every two weeks, and the RNA expression level in the skin surface lipids (SSL) as genes or their expression products was measured four times in the same manner. The time-dependent change profile of the indicator (hereinafter also referred to as the time-dependent change pattern of the severity score) and the time-dependent change profile of the RNA expression level (hereinafter also referred to as the time-dependent change pattern of the expression level) were obtained. As the AD severity score, the EASI score and POEM score for whole body rash caused by AD, the VAS score for skin itching caused by AD, the VAS score for skin dryness caused by AD, and the erythema index for facial erythema caused by AD were used. Next, the time-dependent change pattern of the severity score for each subject was compared with the time-dependent change pattern of the expression level to search for genes or their expression products whose time-dependent change pattern of the expression level was related to the time-dependent change pattern of the AD severity score.

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

[0025]

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[0026] In formula (1), j represents the subject ID, and 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 subject received a score related to the severity of AD; k represents the order in which the subject's AD severity score was obtained, i.e., the order in which the AD severity scores were obtained from the subject over time. k is an integer between 1 and n-1; S j,k represents the score related to the severity of AD obtained at the kth time for a subject with ID j.

[0027] P1 jThe value of P1 represents the transition pattern of the score related to the severity of the subject ID: j. j The number of digits of the value of depends on the number of times the score related to the severity was obtained and the change in severity (f(x) = 0 or 1), and P1 j The value of is 2 n-1 For example, if a subject's AD severity score was obtained four times (n=4), P1 j can have one of eight values: 0, 1, 10, 11, 100, 101, 110, 111. Here, P1 j = 0 means that the subject's AD severity did not worsen during the acquisition period compared to the previous time (10 2 * 0+10 1 * 0+10 0 * 0) represents P1 j =111 indicates that the subject's AD severity continued to worsen during the acquisition period compared to the previous period (10 2 * 1+10 1 * 1+10 0 * 1) Other P1 j The meaning of the value of P1 can be understood in the same way. j =11 indicates that the severity of symptoms obtained the second and third times was worse than the previous time, but the severity of symptoms obtained the fourth time was not worse than the previous time.

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

[0029]

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[0030] In formula (2), i represents the ID of a gene or its expression product, where 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, and 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 a gene or its expression product was obtained, in other words, the total number of times the biological sample from which the gene or its expression product was derived was collected; k represents the order in which the expression level of a gene or its expression product was obtained, in other words, the order in which the biological sample from which the gene or its expression product was derived was obtained, and k is an integer of 1 or more and n-1 or less; E i,j,k represents the expression level of the gene or its expression product with ID: i in the biological sample collected at the kth time from the subject with ID: j.

[0031] P2 i,j The value of P2 represents the transition pattern of the expression level of the gene with ID:i or its expression product in the subject (or sample) with ID:j. i,j The number of digits of the value of P2 depends on the number of times the expression level is obtained and the change in the expression level (f(x) = 0 or 1). i,j The value of is 2 n-1 For example, if the expression level of a subject's gene or its expression product is obtained four times (n=4), P2 i,j can have one of eight values: 0, 1, 10, 11, 100, 101, 110, 111. Here, P2 i,j = 0 means that the expression level of the target gene or its expression product did not show any increase compared to the previous time during the acquisition period (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 * 1) Other P2 i,j The meaning of the value of P2 can be understood in the same way. i,j =11 indicates that the expression levels obtained in the second and third rounds increased compared to the previous rounds, but the expression level obtained in the fourth round did not increase compared to the previous rounds.

[0032] The above formulas (1) and (2) can be used to calculate the transition patterns of the scores related to the severity of AD and the transition patterns of the expression levels of the genes or their expression products collectively for multiple subjects. However, more simply, the transition patterns of the scores related to the severity of AD and the transition patterns of the expression levels of the genes or their expression products for each individual subject can be calculated according to the following formulas (1a) and (2a), respectively.

[0033]

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

[0035] Next, it is determined whether the transition pattern of the expression level is related to the transition pattern of the score related to the severity of AD. ID: i gene or its expression product transition pattern P2 i The relationship between the pattern P1 of changes in scores related to the severity of AD and the pattern P2 of changes in scores related to the severity of AD can be evaluated by the following procedure. First, we define the null hypothesis H0 and alternative hypothesis H1 as follows: H0:P2 i Possible 2 n-1 Of the possible values, the probability of each value being taken is equal to 1 / 2 n-1 is; H1:P2 i Possible 2 n-1 Of the possible values, the probability of each value being taken is equal to 1 / 2 n-1 isn't it, If the null hypothesis holds, P2 iWith equal probability, 2 n-1 Take the values ​​of each of the streets and calculate 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 were obtained four times (n=4), P2 i Each of these has a probability of 1 / 8 and takes eight values: 0, 1, 10, 11, 100, 101, 110, 111. P1 = P2 i The probability that P1 = P2 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, P1 = P2 for the gene or its expression product with ID:i i The number of subjects who met this criteria is counted. The resulting number is used as the match count m for the gene with ID:i or its expression product. i (i represents the ID of a gene or its expression product). The null hypothesis H0(P1 = P2 i The probability of this happening is 1 / 2 n-1 ) is assumed to be true, m among all subjects (total number is J) i In humans, P1=P2 i The probability p i (where i represents the ID of the gene or its expression product) is calculated according to the following formula (3):

[0037]

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[0038] Number of matches m i The probability of obtaining p iis determined to be lower than the significance level, the null hypothesis H0 is rejected and the alternative hypothesis H1 is adopted. This suggests that there is a statistically significant correlation between an increase or non-increase in the expression level of the ID:i gene or its expression product and an exacerbation or non-exacerbation of AD severity. In this case, the ID:i gene or its expression product can be determined as a candidate marker for detecting changes in the severity of AD in a subject. As shown in the examples below, when the number of subjects is 18, P1 = P2 i If the number of subjects who met this criteria is 7 or more, it is determined that there is a significant correlation between the transition pattern of the score related to the severity of AD and the transition pattern of the expression level of the gene of ID:i or its expression product.

[0039] Genes or their expression products whose expression level transition patterns found by the above procedure have a significant correlation with the transition patterns of scores 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 these candidate markers, markers for detecting changes in the severity of AD can be selected for individual subjects.

[0040] (2. Candidate markers for detecting changes in severity of atopic dermatitis) The candidate markers discovered by 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 correspond to the official symbols and Gene IDs listed in NCBI ([www.ncbi.nlm.nih.gov / ]). These genes and their expression products are candidate markers provided by the present invention for selecting markers for detecting changes in the severity of atopic dermatitis.

[0041] [Table 2]

[0042] The genes listed in Table 2 include those consisting of nucleotide sequences registered with NCBI, as well as those consisting of sequences substantially identical to the registered sequences, so long as the genes themselves or their expression products function as markers for detecting changes in AD severity. Here, "substantially identical sequences" refers to sequences that share 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 when searched using the homology calculation algorithm NCBI BLAST under the following conditions: expectation value = 10; gaps allowed; filtering = ON; match score = 1; mismatch score = -3.

[0043] Among the candidate markers, 20 genes and their expression products shown in Table 3 below (hereinafter also referred to as the candidate markers of Table 3) are associated with changes in EASI score. Therefore, the candidate markers in Table 3 are candidate markers for detecting changes in the severity of systemic skin rash due to AD, for example, candidate markers 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 changes in whether the EASI score increases or decreases with increases or decreases in the EASI score. Therefore, the candidate markers in Table 3 are candidate markers that indicate an increase or decrease in the severity of systemic skin rash due to AD, for example, candidate markers that indicate an increase or decrease in the severity of AD corresponding to the EASI score.

[0044] Among the candidate markers, the six genes and their expression products shown in Table 4 below (hereinafter also referred to as the candidate markers of Table 4) are associated with changes in POEM score. Therefore, the candidate markers in Table 4 are candidate markers for detecting changes in the severity of systemic skin rash due to AD, for example, candidate markers 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 change from increasing to not increasing in association with increases and decreases in the POEM score. Therefore, the candidate markers in Table 4 are candidate markers that indicate an increase or decrease in the severity of systemic skin rash due to AD, for example, candidate markers that indicate an increase or decrease in the severity of AD corresponding to the POEM score.

[0045] Among the above candidate markers, the 24 genes and their expression products shown in Table 5 below (hereinafter also referred to as the candidate markers of Table 5) are associated with changes in the VAS score of skin itch due to AD. Therefore, the candidate markers in Table 5 are candidate markers for detecting changes in the severity of skin itch due to AD, for example, candidate markers for detecting changes in the severity of AD corresponding to the VAS score of skin itch. More specifically, the candidate markers in Table 5 show a transition in which their expression levels increase or decrease with increases or decreases in the VAS score of skin itch. Therefore, the candidate markers in Table 5 are candidate markers for indicating the aggravation or non-aggravation of the severity of skin itch due to AD, for example, candidate markers for indicating the aggravation or non-aggravation of the severity of AD corresponding to the VAS score of skin itch.

[0046] Among the above candidate markers, 26 genes and their expression products shown in Table 6 below (hereinafter also referred to as the candidate markers of Table 6) are associated with changes in the VAS score of dry skin due to AD. Therefore, the candidate markers in Table 6 are candidate markers for detecting changes in the severity of dry skin due to AD, for example, candidate markers for detecting changes in the severity of AD corresponding to the VAS score of dry skin. More specifically, the expression levels of the candidate markers in Table 6 show a transition of increase and decrease with increases and decreases in the VAS score of dry skin. Therefore, the candidate markers in Table 6 are candidate markers indicating exacerbation and non-exacerbation of the severity of dry skin due to AD, for example, candidate markers indicating exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score of dry skin.

[0047] Among the above candidate markers, the 46 genes and their expression products shown in Table 7 below (hereinafter also referred to as the candidate markers of Table 7) are associated with changes in the erythema index of facial erythema due to AD. Therefore, the candidate markers in Table 7 are candidate markers for detecting changes in the severity of facial erythema due to AD, for example, candidate markers for detecting changes in the severity of AD corresponding to the erythema index of facial erythema. More specifically, the candidate markers in Table 7 exhibit a transition of increasing and not increasing expression levels in association with increases and not increasing in the erythema index of facial erythema. Therefore, the candidate markers in Table 7 are candidate markers for indicating the exacerbation and non-exacerbation of the severity of facial erythema due to AD, for example, candidate markers for indicating the exacerbation and non-exacerbation of 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 Severity of Atopic Dermatitis for Individual Subjects) The present invention provides a method for selecting a marker for detecting changes in the severity of AD for an individual subject from the candidate markers identified above. Specifically, the transition pattern of the score related to the severity of AD for a given subject is obtained, and the transition pattern of the expression level of the candidate marker in the subject is also obtained. Then, a marker whose transition pattern of the expression level matches the transition pattern of the score related to the severity of AD is selected. The selected marker can be used as a marker for detecting changes in the severity of AD in the subject.

[0054] A specific procedure for the method of selecting a marker for detecting a change in the severity of AD in a subject according to the present invention will be described below. In one embodiment, the method comprises the steps of: 1) calculating P1 and P2 below based on the AD severity scores of the subject at multiple time points separated over time and the expression level of any one of the candidate markers in biological samples collected from the subject at the multiple time points; 2) When P1=P2, determining the candidate marker as a marker for detecting a change in the severity of AD in the subject; P1 and P2 are represented by the following formulas (1a) and (2b).

[0055]

number

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

[0057] The subject in this method is a person for whom it is desired to identify a marker for detecting changes in the severity of AD, such as a person who needs or desires to detect changes in the severity of AD, for example, a person who has developed AD.

[0058] In this method, a score for the severity of AD of a subject is obtained at multiple time intervals. The expression levels of the candidate markers are obtained from biological samples collected from the subject at multiple time intervals. Thus, the obtained expression levels reflect the expression levels of the candidate markers in the subject at the multiple time intervals.

[0059] Therefore, in one embodiment, the method may further comprise the following steps a) and b) before the above step 1): a) obtaining a score for the severity of AD from a subject and collecting a biological sample from the subject at multiple time points separated by a time period; b) measuring the expression level of any one of the candidate markers from the collected biological sample;

[0060] As used herein, the phrase "separated over time" means that each of the multiple periods is sufficiently distant from the adjacent period that a change in the subject's AD severity score can be expected. The subject's AD severity score and biological sample may be obtained multiple times (two or more), preferably three or more, and more preferably four or more. There is no particular upper limit to the number of times they can be obtained. Simply from the standpoint of saving time and cost, the number of times they can be obtained may be preferably 10 or less, more preferably eight or less.

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

[0062] The score relating to the severity of AD in a subject can be any score capable of detecting AD symptoms, such as one or more selected from the EASI score and POEM score relating to systemic skin rash caused by AD, the VAS score for skin itching caused by AD, the VAS score for dry skin caused by AD, the erythema index for facial erythema caused by AD, and a skin condition score based on observation with a camera or probe, or a score determined by comprehensively evaluating any two or more selected from these scores and indices. Preferably, one or more selected from the EASI score and POEM score relating to systemic skin rash caused by AD, the VAS score for skin itching caused by AD, the VAS score for dry skin caused by AD, and the erythema index for facial erythema caused by AD can be used.

[0063] The candidate markers used in this method are those for which the null hypothesis H0 explained above in (1. Search for candidate markers for detecting changes in the severity of atopic dermatitis) is rejected. If P1 = P2 is obtained for any candidate marker selected from the candidate markers, an increase in the expression level of the candidate marker is considered to represent an exacerbation of the severity of AD in the subject, and no increase in the expression level of the candidate marker is considered to represent a non-exacerbation of the severity of AD in the subject, and 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 personalized marker).

[0064] In this method, it can be determined whether one or more of the candidate markers described above can be used as a marker (personal marker) for detecting a change in the severity of AD in a subject, respectively, according to the above steps 1) and 2). In this case, the above steps 1) and 2) can be performed repeatedly for each candidate marker, or the above steps 1) and 2) can be performed in parallel for each candidate marker.

[0065] The candidate markers used in the present method are preferably those that are related to the severity of AD that is desired to be detected by the personalized markers selected for the subject by the present method (in other words, the severity of AD that is desired to be detected in the subject subjected to the present method).

[0066] In one embodiment, the candidate markers used in the method are any one or more, preferably all, selected from the group consisting of the candidate markers in Table 3, and the personalized markers selected in the method are markers for detecting changes in the severity of systemic skin rash due to AD, for example, markers for detecting changes in the severity of AD corresponding to the EASI score, more specifically, markers that indicate exacerbation and non-exacerbation of the severity of systemic skin rash due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the EASI score. In one embodiment, the candidate markers used in the method are any one or more, preferably all, selected from the group consisting of the candidate markers in Table 4, and the personalized markers selected in the method are markers for detecting changes in the severity of systemic skin rash due to AD, for example, markers for detecting changes in the severity of AD corresponding to the POEM score, more specifically, markers that indicate exacerbation and non-exacerbation of the severity of systemic skin rash due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the POEM score. In one embodiment, the candidate markers used in this method are any one or more, preferably all, selected from the group consisting of the candidate markers in Table 5, and the personalized markers selected in this method are markers for detecting changes in the severity of skin itch due to AD, for example, markers for detecting changes in the severity of AD corresponding to the VAS score of skin itch, more specifically, markers that indicate exacerbation and non-exacerbation of the severity of skin itch due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score of skin itch. In one embodiment, the candidate markers used in the method are any one or more, preferably all, selected from the group consisting of the candidate markers in Table 6, and the personalized markers selected in the method are markers for detecting changes in the severity of dry skin due to AD, for example, markers for detecting changes in the severity of AD corresponding to the VAS score of dry skin, more specifically, markers that indicate exacerbation and non-exacerbation of the severity of dry skin due to AD, for example, markers that indicate exacerbation and non-exacerbation of the severity of AD corresponding to the VAS score of dry skin. In one embodiment, the candidate markers used in this method are any one or more, preferably all, selected from the group consisting of the candidate markers in Table 7, and the personalized markers selected in this 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, 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 personalized marker selected in the method is a marker for detecting a change in the severity of systemic skin rash, skin itching, skin dryness, or facial erythema caused by AD, such as a marker for detecting a change in the severity of AD corresponding to the EASI score, POEM score, VAS score for skin itching, VAS score for skin dryness, or erythema index for facial erythema, more specifically, a marker indicating exacerbation or non-exacerbation of the severity of systemic skin rash, skin itching, skin dryness, or facial erythema caused by AD, such as a marker indicating exacerbation or non-exacerbation of the severity of AD corresponding to the EASI score, POEM score, VAS score for skin itching, VAS score for skin dryness, or erythema index for facial erythema.

[0067] The expression level of a candidate marker gene or its expression product in a subject may be measured in accordance with standard methods from a biological sample collected from the subject, such as cells, tissues (biopsy, etc.), body fluids (body fluids such as tissue exudates, blood, serum prepared from blood, plasma, etc.), organs, skin, urine, saliva, sweat, stratum corneum, skin surface lipids (SSL), stool, hair, etc. 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 limitations on the number or types of genes or their expression products whose expression levels are measured, and 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, even more preferably RNA, prepared from the subject's SSL. The site of skin from which the SSL is collected is not particularly specified, and may include skin from any part of the body, such as the head, face, neck, trunk, limbs, etc., with sites with high sebum secretion, such as the skin of the head or face, being preferred, and facial skin being more preferred. Furthermore, the site of skin from which the SSL is collected may be either a rash area where AD has developed or a non-rash area where AD has not developed, but preferably a rash area or a non-rash area near the rash area. Here, "near the rash area" refers to an area within 10 cm adjacent to the rash area.

[0070] Any method commonly used for recovering or removing SSL from skin can be used to collect SSL from a subject's skin. Preferably, SSL absorbent materials, SSL adhesive materials, or devices for scraping SSL from skin, as described below, can be used. The SSL absorbent material or SSL adhesive material can be any material that has affinity for SSL, including polypropylene and pulp. More detailed examples of procedures for collecting SSL from skin include absorbing SSL into sheet-like materials such as oil blotting paper or oil blotting film, adhering SSL to glass plates or tape, or scraping SSL off with a spatula or scraper. To improve SSL adsorption, SSL absorbent materials pre-soaked with a highly lipid-soluble solvent may be used. However, SSL absorbent materials preferably contain low amounts of highly water-soluble solvents or moisture, since the presence of highly water-soluble solvents or moisture inhibits SSL adsorption. It is preferable to use SSL absorbent materials in a dry state.

[0071] The collected SSL may be used immediately in the nucleic acid or protein extraction step described below, or may be stored until used in the nucleic acid or protein extraction step. When stored, the SSL is preferably stored under low-temperature conditions. The temperature condition for storing the SSL may be 0°C or below, 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, even more preferably 3 months or less, for example, 3 days to 3 months.

[0072] Nucleic acids or proteins can be extracted from the collected SSL using methods commonly used for extracting or purifying nucleic acids or proteins from biological samples. Examples of nucleic acid extraction or purification methods include the phenol / chloroform method, the acid guanidinium thiocyanate-phenol-chloroform extraction (AGPC) method, methods using columns such as TRIzol®, RNeasy®, and QIAzol®, methods using special silica-coated magnetic particles, methods using solid phase reversible immobilization magnetic particles, and extraction using commercially available RNA extraction reagents such as ISOGEN. Protein extraction or purification can be performed using commercially available protein extraction reagents such as QIAzol Lysis Reagent (Qiagen).

[0073] The expression level of a nucleic acid or protein can be measured according to a nucleic acid or protein quantification method commonly used in the art. The expression level of a nucleic acid or protein to be measured may be an expression level based on the absolute amount of the nucleic acid or protein in a biological sample, or may be an expression level relative to the expression level of another standard substance or the total nucleic acid or total protein.

[0074] For example, the expression level of a nucleic acid may be measured according to a gene expression analysis procedure commonly used in the field. Examples of gene expression analysis techniques include methods for quantifying nucleic acids or their amplification products, such as PCR, multiplex PCR, real-time PCR, hybridization (DNA chips, DNA microarrays, dot blot hybridization, slot blot hybridization, Northern blot hybridization, etc.), sequencing, and chromatography. When the nucleic acid is RNA, it is preferable to convert the RNA into cDNA by reverse transcription and then quantify it using the above method.

[0075] Protein expression levels can be measured using protein quantification methods commonly used in the art, such as immunoassays (e.g., Western blot, ELISA, immunostaining, etc.), fluorescence, electrophoresis, protein chips, chromatography, mass spectrometry (e.g., LC-MS / MS, MALDI-TOF / MS), one-hybrid methods (PNAS, 100:12271-12276 (2003)), and two-hybrid methods (Biol Reprod, 58:302-311 (1998)). Alternatively, the expression levels of target nucleic acids or proteins can be measured by measuring molecules that interact with the target nucleic acids or proteins. Examples of molecules that interact with nucleic acids or proteins include DNA, RNA, proteins, polysaccharides, oligosaccharides, monosaccharides, lipids, fatty acids, and phosphorylations, alkylations, and sugar adducts thereof, as well as complexes of any of the above.

[0076] Preferably, the expression level of SSL-derived RNA is measured by converting RNA extracted from the SSL into cDNA by reverse transcription, and then quantifying the cDNA or its amplification product by the above-mentioned method.

[0077] For reverse transcription of RNA, a primer targeting the specific RNA to be analyzed may be used, but for more comprehensive nucleic acid storage and analysis, random primers are preferably used. A general reverse transcriptase or reverse transcription reagent kit can be used for the reverse transcription. Preferably, a highly accurate and efficient reverse transcriptase or reverse transcription reagent kit is used, such as M-MLV Reverse Transcriptase and its variants, or a commercially available reverse transcriptase or reverse transcription reagent kit, such as the PrimeScript® Reverse Transcriptase series (Takara Bio Inc.), the SuperScript® Reverse Transcriptase series (Thermo Scientific), SuperScript® III Reverse Transcriptase, or the SuperScript® VILO cDNA Synthesis kit (all from Thermo Scientific). In the extension reaction in the reverse transcription, the temperature is preferably adjusted to 42°C±1°C, more preferably 42°C±0.5°C, and even more preferably 42°C±0.25°C, while the reaction time is preferably adjusted to 60 minutes or more, more preferably 80 to 120 minutes.

[0078] When measuring the expression level of a nucleic acid using PCR, RNA derived from a biological sample is reverse transcribed into cDNA as needed, and then DNA derived from the biological sample is amplified using a primer pair. PCR may amplify only one specific DNA to be analyzed using a primer pair targeting the specific DNA, or multiple primer pairs may be used to simultaneously amplify multiple specific DNAs. Preferably, the PCR is multiplex PCR. Multiplex PCR is a method in which multiple gene regions are simultaneously amplified by simultaneously using multiple primer pairs in a PCR reaction system. Multiplex PCR can be performed using a commercially available kit (e.g., Ion AmpliSeq Transcriptome Human Gene Expression Kit; Life Technologies Japan, Inc., etc.).

[0079] The temperatures for the annealing and extension reactions in the PCR depend on the primers used and cannot be generalized; however, when using the multiplex PCR kit described above, the temperatures are 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 carried out in one step. The time for 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 are preferably 95 to 99°C for 10 to 60 seconds. Reverse transcription and PCR at the temperatures and times described above can be carried out 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. By size separation, the target PCR reaction product can be separated from primers and other impurities contained in the PCR reaction solution. Size separation of DNA can be carried out using, for example, a size separation column, a size separation chip, magnetic beads usable for size separation, etc. Preferred examples of magnetic beads usable for size separation include Solid Phase Reversible Immobilization (SPRI) magnetic beads such as Ampure XP.

[0081] The purified PCR reaction product may be further processed as necessary for subsequent quantitative analysis. For example, for DNA sequencing, the purified PCR reaction product may be prepared in an appropriate buffer solution, the PCR primer region contained in the PCR-amplified DNA may be cleaved, or an adapter sequence may be added to the amplified DNA. For example, the purified PCR reaction product may be prepared in a buffer solution, and the amplified DNA may be subjected to PCR primer sequence removal and adapter ligation. The resulting reaction product may then be amplified as needed to prepare a library for quantitative analysis. These operations may be performed, for example, using the 5x VILO RT Reaction Mix included with the SuperScript® VILO cDNA Synthesis kit (Life Technologies Japan, Inc.), and the 5x Ion AmpliSeq HiFi Mix and Ion AmpliSeq Transcriptome Human Gene Expression Core Panel included with the Ion AmpliSeq Transcriptome Human Gene Expression Kit (Life Technologies Japan, Inc.), according to the protocols included with each kit.

[0082] When measuring the expression level of a nucleic acid using real-time PCR, RNA derived from a biological sample is reverse transcribed into cDNA as needed, and then PCR is performed using primers that have been pre-labeled with a radioisotope (RI), fluorescent substance, etc., and the resulting labeled double-stranded DNA is detected and quantified.

[0083] When measuring the expression level of a nucleic acid using Northern blot hybridization, for example, RNA derived from a biological sample is transferred onto a membrane according to a standard method, and then probe DNA labeled with RI, a fluorescent substance, or the like is hybridized to the RNA. The expression level of the nucleic acid can be measured by detecting a signal derived from the label in the formed double strand of the labeled probe DNA and RNA.

[0084] When measuring the expression level of a nucleic acid using a DNA microarray, for example, a microarray is used in which a nucleic acid (cDNA or DNA) that specifically hybridizes with a target nucleic acid is immobilized on a support. The nucleic acid (cDNA or cRNA) prepared from a biological sample is bound to the microarray, and the label on the microarray is detected, thereby measuring the expression level of the nucleic acid in the biological sample. The nucleic acid immobilized on the microarray may be any nucleic acid that hybridizes specifically to the target nucleic acid (i.e., substantially only to the target nucleic acid) under stringent conditions. It 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 a "partial sequence" include nucleic acids consisting of at least 15 to 25 bases. Stringent conditions include washing conditions such as 1×SSC, 0.1% SDS, and 37°C, preferably 0.5×SSC, 0.1% SDS, and 42°C, and more preferably 0.1×SSC, 0.1% SDS, and 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, Inc.) can be preferably 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 counts described above can be used as expression level data. Alternatively, the RPM (Reads per million mapped reads) value of the read counts, 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), etc., can be used as expression level data. Alternatively, common 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 as expression level data.

[0087] The probe or primer used to measure the expression level of a nucleic acid may be, for example, a primer for specifically amplifying a target nucleic acid or a probe for specifically detecting a target nucleic acid. Here, "specific" means that the nucleic acid can be recognized or detected so as to generate a product or detection substance substantially derived from the target nucleic acid, such as, for example, in Northern blotting, substantially only the target nucleic acid is detected, or in PCR, substantially only the target nucleic acid is amplified. These probes or primers can be designed based on the nucleotide sequence of the target nucleic acid. Specific examples of such probes or primers include oligonucleotides consisting of the entire or partial sequence of a target nucleic acid, or their complementary strands. The "complementary strand" is not limited to a completely complementary sequence, as long as it specifically recognizes the target nucleic acid, and may be a sequence having preferably 80% or more, more preferably 90% or more, and even more preferably 95% or more sequence identity. Sequence identity can be determined using an algorithm such as the NCBI BLAST described above. Examples of primers used to measure the expression level of the nucleic acid include those that are capable of specific annealing and chain extension to the target nucleic acid, and have a chain length of preferably 10 bases or more, more preferably 15 bases or more, even more preferably 20 bases or more, and preferably 100 bases or less, more preferably 50 bases or less, even more preferably 35 bases or less. Examples of probes used to measure the expression level of the nucleic acid include those capable of specific hybridization to the target nucleic acid, and having a chain length of preferably 10 bases or more, more preferably 15 bases or more, and preferably 100 bases or less, more preferably 50 bases or less, and even more preferably 25 bases or less. The probe or primer may be DNA or RNA, and may be synthetic or natural. The probe used in hybridization is usually labeled.

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

[0089] (4. Method for detecting changes in severity of atopic dermatitis) Furthermore, the present invention provides a method for detecting a change in the severity of AD in an individual subject selected in 3 above, using a marker for detecting a change in the severity of AD in the subject (a personalized marker for the subject). In the method for detecting a change in the severity of AD according to the present invention (hereinafter referred to as the present detection method), a change in the severity of AD in the subject (e.g., worsening or non-worsening of symptoms) is detected based on a change in the expression level of the personalized marker for the subject. An increase in the expression level of the personalized marker indicates a worsening of the severity of AD in the subject, while a non-increase in the expression level indicates a non-worsening of the severity of AD in the subject.

[0090] The detection method comprises measuring the expression level of a personalized marker for a subject in a biological sample taken from the subject. The detection method may further comprise taking the biological sample from the subject.

[0091] Examples of subjects subjected to this detection method include mammals, including humans and non-human mammals, preferably humans. When the subject is a human, the gender, age, race, etc., of the subject are not particularly limited and can range from infants to the elderly. Examples include those who need or wish to detect changes in the severity of AD, such as those who have developed AD. The personalized 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 a marker for detecting changes in the severity of AD in a subject described in Section 3 above. The personalized marker for the subject may be identified in advance before the detection method or during the procedure of the detection method. The type of biological sample to be collected and the procedure for measuring the expression level of the marker are the same as those for the method for selecting a personalized marker. The number of personalized markers whose expression levels are measured is not particularly limited and may be one or more. The personalized marker may be a nucleic acid marker or a protein marker. Alternatively, a nucleic acid marker and a protein marker may be used in combination. Preferably, the biological sample is SSL, and the marker is SSL-derived RNA. The procedures for collecting SSLs, extracting markers from SSLs, 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 in the same subject measured at a certain time (baseline) 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 severity of AD in the subject has worsened compared to the baseline, while 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 severity of AD in the subject has not worsened compared to the baseline. In one embodiment, the expression level of the personalized marker in a subject is measured over time, and the expression level at any measurement after the first measurement is compared with the expression level at the previous or previous measurement (which serves as a reference value). An expression level higher than the reference value indicates an increase in the severity of AD in the subject, and an expression level lower than or no difference from the reference value indicates a non-exacerbation of the severity of AD in the subject. In another embodiment, the degree of AD of the subject is determined at a certain time (baseline time), and the expression level of the personal marker in the subject is measured and set as a reference value.Then, the expression level of the personal marker in the subject is measured and compared with the reference value.The expression level higher than the reference value represents the worsening of the AD severity in the subject from the baseline time, and the expression level lower than the reference value or no difference represents the non-worsening of the AD severity in the subject from the baseline 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 determined 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 determined 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 standard value, the expression level of the marker can be determined to be lower than the standard 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 standard value, the expression level of the marker can be determined to be higher than the standard value. When multiple markers are used as personal markers, changes in the severity of AD can be detected by comparing the expression levels of each marker with a reference value and examining whether the expression levels of a certain percentage of the markers, for example, 50% or more, preferably 70% or more, more preferably 90% or more, and even more preferably 100%, differ from the reference value.

[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 systemic skin rash due to AD, the severity of skin itching, the severity of skin dryness, 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 systemic skin rash due to AD, the VAS score for skin itching due to AD, the VAS score for skin dryness due to AD, and the erythema index for facial erythema due to AD. The type of severity of AD detected by this detection method may vary depending on the type of personalized marker used. In one example, when the personalized marker used in this detection method includes at least one gene or its expression product shown in Table 3, it is possible to detect a change in the severity of systemic skin rash caused by AD, for example, a change in the severity of AD corresponding to the EASI score. In another example, when the personalized marker used in this detection method includes at least one gene shown in Table 4 or its expression product, a change in the severity of systemic skin rash caused by AD, for example, a change in the severity of AD corresponding to the POEM score, can be detected. In another example, when the personalized marker used in this detection method includes at least one gene listed in Table 5 or its expression product, a change in the severity of skin itching caused by AD, for example, a change in the severity of AD corresponding to the VAS score of skin itching, can be detected. In another example, when the personalized marker used in the present detection method includes at least one gene shown in Table 6 or its expression product, a change in the severity of dry skin due to AD, for example, a change in the severity of AD corresponding to the VAS score of dry skin, can be detected. In another example, when the personalized marker used in this detection method includes at least one gene shown in Table 7 or its expression product, a change in the severity of facial erythema caused by AD, for example, a change in the severity of AD corresponding to the erythema index of facial erythema, can be detected. In another example, when the personalized markers used in this detection method contain the genes or their expression products shown in Tables 3 to 7, respectively, it is possible to detect changes in the severity of systemic skin rash, skin itching, skin dryness, and facial erythema caused by AD, for example, changes in the severity of AD corresponding to the EASI score, POEM score, VAS score for skin itching, VAS score for skin dryness, and erythema index for facial erythema, respectively.

[0095] (5. AD severity change detection kit) In a further aspect, the present invention provides a kit for detecting a change in the severity of AD in a subject according to the method for detecting a change in the severity of AD according to the present invention described in 4. above. In one embodiment, the kit of the present invention comprises reagents or instruments for measuring the expression levels of markers listed 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, adapter sequences for sequencing, etc.) or reagents for quantifying protein markers (e.g., reagents for immunoassays, antibodies, etc.). Preferably, the kit of the present invention contains oligonucleotides (e.g., PCR primers or probes) that specifically hybridize with nucleic acid markers or antibodies that recognize protein markers. Preferably, the kit of the present invention comprises indicators or guidance for detecting the expression levels of markers. For example, the kit of the present invention may comprise guidance describing AD symptoms associated with each marker (e.g., skin rash, itchy skin, dry skin, facial erythema). The kit of the present invention may further include a biological sample collection device (e.g., the above-mentioned SSL absorbent material or SSL adhesive material), reagents for extracting markers from the biological sample (e.g., reagents for nucleic acid purification), a preservative or storage container for the sample collection device after collection of the biological sample, etc.

[0096] As exemplary embodiments of the present invention, the following substances, manufacturing methods, uses, methods, etc. are further disclosed herein, but the present invention is not limited to these embodiments.

[0097] [1] A method for selecting a marker for detecting a change in the severity of atopic dermatitis in a subject, comprising: 1) Calculating P1 and P2 below based on the score relating to the severity of atopic dermatitis of the subject at multiple time points separated over time and the expression level of any one of the genes or expression products thereof shown in Table 1 above in biological samples collected from the subject at the multiple time points;

number

[10] The method described in [9], wherein the severity of atopic dermatitis is preferably a severity of atopic dermatitis corresponding to the VAS score for dry skin.

[11] The method according to [1] or [2], wherein the gene or its expression product is any one of the genes and their expression products shown in Table 7, and the severity of atopic dermatitis is the severity of facial erythema caused by atopic dermatitis.

[12] The method according to

[11] , wherein the severity of atopic dermatitis is preferably a severity of atopic dermatitis corresponding to an erythema index for facial erythema.

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

[12] , wherein the multiple periods separated by a time interval are preferably at least one day, more preferably at least three days, even more preferably at least one week, even more preferably at least one week and no more than four weeks, and even more preferably at least 12 days and no more than 16 days.

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

[14] , wherein the biological sample is preferably lipids on the skin surface.

[16] The method described in

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

[0098]

[17] A method for detecting a change in severity of atopic dermatitis in a subject, comprising: measuring the expression level of a marker for detecting a change in the severity of atopic dermatitis, determined by the method described in any one of [1] to

[16] , in a biological sample collected from the subject; detecting a change in the severity of atopic dermatitis in the subject based on a change in the expression level of the marker; A method comprising:

[18] Preferably, 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.

[17] The method of

[17] .

[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 atopic dermatitis is preferably a severity of a systemic rash caused by atopic dermatitis, and more preferably a severity of atopic dermatitis corresponding to EASI. 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 atopic dermatitis is preferably a severity of a systemic rash caused by atopic dermatitis, and more preferably a 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 atopic dermatitis is preferably the severity of skin itching caused by atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the VAS score of skin itching. The method described in

[17] or

[18] .

[22] Preferably, the marker comprises at least one selected from the group consisting of genes and their expression products shown in Table 6; The severity of atopic dermatitis is preferably the severity of dry skin caused by atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the VAS score of dry skin. 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 atopic dermatitis is preferably the severity of facial erythema caused by atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to an erythema index related to facial erythema. The method described in

[17] or

[18] .

[24] Preferably, the marker comprises a gene or an expression product thereof shown in Tables 3 to 7, The severity of atopic dermatitis is preferably the severity of a systemic skin rash caused by atopic dermatitis, the severity of skin itching caused by atopic dermatitis, the severity of skin dryness caused by atopic dermatitis, and the severity of facial erythema caused by atopic dermatitis, and more preferably the severity of atopic dermatitis corresponding to the EASI score, the severity of atopic dermatitis corresponding to the POEM, the VAS score for skin itching, the VAS score for skin dryness, and the severity of atopic dermatitis corresponding to the erythema index for facial erythema. The method described in

[17] or

[18] .

[25] Preferably, when the expression level of the marker is higher than the reference value, the severity of the subject's atopic dermatitis is detected as having worsened compared to the time when the reference value was measured, whereas when the expression level of the marker is lower than the reference value or there is no difference, the severity of the subject's atopic dermatitis is detected as having not worsened compared to the time when the reference value was measured.

[17] to

[24] The method of any one of

[17] to

[24] .

[26] Preferably, the reference value is the expression level of the marker in the subject measured at a particular time; the expression level of the marker in the subject as previously measured;

[25] The method described in.

[27] Preferably, the method described in

[25] or

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

[28] The method described in

[25] or

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

[0099]

[29] A kit for detecting a change in the severity of atopic dermatitis, which is used in the method according to any one of

[17] to

[28] , and which contains an oligonucleotide that specifically hybridizes with the gene used in the method according to any one of [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 [1] to

[16] .

[30] A kit for detecting a change in the severity of atopic dermatitis, which is used in the method described in any one of

[17] to

[28] , and which contains an oligonucleotide that specifically hybridizes with a gene shown in Table 1 above or a nucleic acid derived therefrom, or an antibody that recognizes the expression product of a gene shown in Table 1 above.

[31] A candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis, which comprises a gene shown in Table 1 above or its expression product.

[32] Preferably, 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. The candidate marker described in

[31] .

[33] Preferably, the candidate marker is a candidate marker for selecting a marker for detecting changes in the severity of a systemic skin rash caused by atopic dermatitis, and the candidate marker is a gene or its expression product shown in Table 3 above.

[34] Preferably, the candidate marker described in

[33] 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 a systemic skin rash caused by atopic dermatitis, and the candidate marker is a gene or its expression product shown in Table 4 above.

[36] Preferably, the candidate marker described in

[35] 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 its expression product shown in Table 5 above.

[38] Preferably, the candidate marker described in

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

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

[40] Preferably, the candidate marker described in

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

[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 its expression product shown in Table 7 above.

[42] Preferably, the candidate marker described in

[41] 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 a gene or its expression product shown in Table 1 above as a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis, or use in producing a candidate marker for selecting a marker for detecting changes in the severity of atopic dermatitis.

[44] Preferably, 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. The use of

[43] .

[45] The use according to

[43] or

[44] , wherein the candidate marker is preferably a candidate marker for selecting a marker for detecting changes in the severity of a systemic skin rash caused by atopic dermatitis, and the candidate marker is a gene or its expression product shown in Table 3 above.

[46] The use according to

[45] , wherein the candidate marker is preferably 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] The use according to

[43] or

[44] , wherein the candidate marker is preferably a candidate marker for selecting a marker for detecting changes in the severity of a systemic skin rash caused by atopic dermatitis, and the candidate marker is a gene or its expression product shown in Table 4 above.

[48] ​​The use according to

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

[49] The use according to

[43] or

[44] , wherein the candidate marker is preferably 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 its expression product shown in Table 5 above.

[50] The use described in

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

[51] The use of

[43] or

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

[52] The use described in

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

[53] The use according to

[43] or

[44] , wherein the candidate marker is preferably 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 its expression product shown in Table 7 above.

[54] The use described in

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

[0100] The present invention will be described in more detail below based on examples, but the present invention is not limited to these examples. Example 1: Search for genes related to the severity of atopic dermatitis using SSL-derived RNA 1) Obtaining scores related to the severity of atopic dermatitis patients and collecting SSL data The subjects were 18 adult males (aged 23-57 years) with atopic dermatitis (AD). The subjects were AD patients who had been diagnosed with mild to moderate atopic dermatitis by a dermatologist at the time of the initial measurement. The subjects visited the clinic four times, every 14 days, to receive a score for their AD severity and to have their SSL samples collected. Hereinafter, the collected AD severity scores and SSL samples will be referred to as the first, second, third, and fourth AD severity scores and SSL samples, respectively, based on the order of their visit from the first visit. The AD severity scores used were the physician-administered EASI score (Hanifin et al., Exp Dermatol, 10, 2001, scoring from 0 to 72 based on symptoms of the entire body skin rash), the subject-administered POEM score (Charman et al., Arch Dermatol, 140, 2004, scoring from 0 to 28 based on symptoms of the entire body skin rash), the VAS scores for whole body skin itching (scoring from 0 to 100 based on the intensity of itching), and the VAS scores for whole body skin dryness (scoring from 0 to 100 based on the intensity of dryness), and the facial erythema index (see JP 2018-23756 A and Dawson et al., Phys Med Biol, 25, 1980) based on facial images taken with a hyperspectral imaging device (Hyperspectral Camera NH-7, Eva Japan Co., Ltd.). The facial erythema index was calculated for each pixel on a frontal facial image taken by a hyperspectral imaging device according to the following formula (4): Arbitrary ROIs (Regions of Interest) were defined on the image in areas corresponding to the forehead, above both eyes, and both cheeks, and the average value of the erythema index in 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 blotting film (5 x 8 cm, polypropylene, 3M). The oil blotting film was transferred to a vial and stored at -80°C for approximately one month until use in RNA extraction.

[0103] 2) RNA preparation and sequencing The oil-blotting film (1) above was cut to an appropriate size, and RNA was transferred to the aqueous layer using QIAzol Lysis Reagent (Qiagen) according to the attached protocol. RNA was extracted from the aqueous layer using a commercially available RNA extraction kit with an RNA extraction spin column according to the attached protocol. The extracted RNA was reverse transcribed at 42°C for 90 minutes using a SuperScript VILO cDNA Synthesis kit (Life Technologies Japan, Inc.) to synthesize cDNA. The random primers included in the kit were used as primers for the reverse transcription reaction. A library containing DNA derived from the 20802 gene was prepared from the resulting cDNA by multiplex PCR. Multiplex PCR was performed using an Ion AmpliSeq Transcriptome Human Gene Expression Kit (Life Technologies Japan, Inc.) under the following conditions: 99°C, 2 minutes → (99°C, 15 seconds → 62°C, 16 minutes) × 20 cycles → 4°C hold. The resulting PCR products were purified using Ampure XP (Beckman Coulter, Inc.), followed by buffer reconstitution, primer digestion, adapter ligation, purification, and amplification to prepare libraries. The prepared libraries were loaded onto an Ion 540 chip and sequenced using an Ion S5 / XL system (Life Technologies Japan, Inc.). The gene from which each read sequence originated was determined by genetic mapping using the hg19 AmpliSeq Transcriptome ERCC v1, the reference sequence for the human genome.

[0104] 3) Usage data The read counts of each read obtained by sequencing the subjects' SSL-derived RNA measured in 2) above were used as expression level data for each RNA. Genes whose amplified regions in sequencing spanned at least two exons were selected as target genes. To correct for differences in total read counts between samples, the read counts of the target genes were converted to RPM (reads per million mapped reads). Of these, 4845 genes with read counts of 20 or more in 90% or more of the samples were used for the following analysis. Furthermore, to approximate a normal distribution, the RPM values ​​were converted to base 2 logarithmic values ​​(Log2(RPM+1) values) by adding an integer 1. Using these procedures, expression level data (Log2(RPM+1) values) of 4845 genes were generated for the first, second, third, and fourth SSL samples from 18 subjects. These are referred to as the first, second, third, and fourth visit expression levels, respectively, based on the order of the subjects' initial visit.

[0105] 4) Data analysis For each of the 18 AD patients obtained in 1) above, based on the AD severity scores from the 1st to 4th time points, P1, an index showing the progression of the severity change every 14 days, was calculated. j was calculated according to the following formula (1)'. j is one of eight values: 0, 1, 10, 11, 100, 101, 110, 111, based on the progression pattern of the AD severity score.

[0106]

number

[0107] In formula (1)', j represents a sample (or subject) ID, and in this embodiment, j is an integer between 1 and 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 between 1 and 3. S j,k represents the kth AD severity score for subject with ID j.

[0108] Next, for each of the 18 AD patients calculated in 3), the expression level data (Log2(RPM+1) values) from the first to fourth times were used to calculate P2, an index showing the transition of gene expression levels every 14 days. i,j was calculated according to the following formula (2)'. i,j is one of eight values: 0, 1, 10, 11, 100, 101, 110, 111, based on the transition pattern of gene expression levels.

[0109]

number

[0110] In formula (2)', i represents a gene ID, and in this example, i is an integer between 1 and 4845. j represents the subject ID, and in this embodiment, j is an integer between 1 and 18. k represents the order in which SSL samples are acquired, and in this embodiment, k is an integer between 1 and 3. E i,j,k represents the expression level of a gene with ID i in an SSL sample collected at the kth time from a subject with ID j.

[0111] In this case, from the sample (or subject) with ID j (j = 1 to 18), a fixed P1 j and P2 for the gene with ID i (i = 1 to 4845) in the sample. i,j is obtained. Here, the null hypothesis H0 and alternative hypothesis H1 are defined as follows: H0:P2 i,j The probability that the number takes on eight possible values, "0, 1, 10, 11, 100, 101, 110, 111", is 1 / 8. H1:P2 i,j The probability that the number takes on eight possible values ​​(0, 1, 10, 11, 100, 101, 110, 111) is not equal to 1 / 8. If the null hypothesis holds, P2 i,jEach of these can take on eight possible values: 0, 1, 10, 11, 100, 101, 110, and 111, with a probability of 1 / 8. j =P2 i,j The probability of this happening is 1 / 8, and if the null hypothesis can be rejected, the alternative hypothesis is adopted. j =P2 i,j Assume that the probability of this is not 1 / 8.

[0112] Next, for 4845 genes, P1 j =P2 i,j Count the number of samples that match, and count that number as the match count m i The null hypothesis H0(P1 j =P2 i,j The probability of this happening is 1 / 8. If we assume that m out of 18 samples i Sample P1 j =P2 i,j The probability p i was calculated using the following formula (3)'. i If was below the one-sided significance level of 0.005, the null hypothesis H0 was rejected and the alternative hypothesis H1 was accepted.

[0113]

number

[0114] 5) Genes associated with AD severity scores i) Genes associated with EASI score As a result of the analysis using the EASI score as the AD severity score 4), 23 genes shown in Table 8 were found to be P1 in 7 or more samples out of 18 samples. j and P2 i,j matches, and p i In other words, the P1 in the 23 genes shown in Table 8 was below the significance level. 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 rather than by chance. Furthermore, for 20 of the 23 genes shown in Table 8 (indicated with an * in the table), there have been no reports to date suggesting a relationship with atopic dermatitis, and therefore it was determined that these genes could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of atopic dermatitis rash reflected in the EASI score.

[0115] [Table 8]

[0116] ii) Genes associated with POEM score As a result of the analysis using the POEM score as an AD severity score 4), P1 was detected in 7 or more samples out of 18 samples for the 7 genes shown in Table 9. j and P2 i,j matches, and p i In other words, the P1 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 rather than by chance. Furthermore, for six of the seven genes shown in Table 9 (indicated with an * in the table), there have been no reports to date suggesting a relationship with atopic dermatitis, and therefore it was determined that these six genes could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of atopic dermatitis rash reflected in the POEM score.

[0117] [Table 9]

[0118] iii) Genes associated with itching VAS scores As a result of the analysis using the VAS score of skin itching as the AD severity score 4), 27 genes shown in Table 10 were found to be P1 in 7 or more of the 18 samples. j and P2 i,j matches, and pi In other words, the P1 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 of skin itch, rather than by chance. Furthermore, for 24 of the 27 genes shown in Table 10 (indicated with * in the table), there have been no reports to date suggesting a relationship with atopic dermatitis, and therefore it was determined that these genes could serve as novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of skin itch symptoms caused by atopic dermatitis, as reflected in the VAS score of skin itch.

[0119] [Table 10]

[0120] iv) Genes associated with dryness VAS score As a result of the analysis using the VAS score of dry skin as the AD severity score 4), 26 genes shown in Table 11 were found to be P1 in 7 or more samples out of 18 samples. j and P2 i,j matches, and p i In other words, the P1 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 of dry skin, rather than by chance. Furthermore, for all 26 of the 26 genes shown in Table 11 (indicated with * in the table), there have been no reports to date suggesting a relationship with atopic dermatitis, and therefore it was determined that these genes could be novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of dry skin symptoms due to atopic dermatitis reflected in the VAS score of dry skin.

[0121] [Table 11]

[0122] v) Genes associated with erythema index As a result of the analysis using the facial erythema index as an AD severity score 4), 54 genes shown in Table 12 were P1 in 7 or more samples out of 18 samples. j and P2 i,j matches, and p i In other words, the P1 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, rather than by chance. Furthermore, for 46 of the 54 genes shown in Table 12 (indicated with * in the table), there have been no reports to date suggesting a relationship with atopic dermatitis, and therefore it was determined that these genes could be novel markers for changes in the severity of atopic dermatitis, preferably changes in the severity of facial erythema due to atopic dermatitis as reflected in the facial erythema index.

[0123] [Table 12]

[0124] Example 2 Selection of markers for detecting changes in severity of atopic dermatitis For each of the candidate marker genes linked to EASI score found in Example 1, the consistency between the time course pattern of the expression level of each gene and the time course pattern of the EASI score in 18 subjects was examined. Genes whose time course pattern of expression level matched the time course pattern of the EASI score of the subjects are circled in Table 13.

[0125] [Table 13]

[0126] For each subject 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 rash as indicated by the EASI score. Similarly, when POEM, itch VAS, dryness VAS, and erythema index are used as the AD severity score, genes or their expression products with matching transition 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 below based on the score relating to the severity of atopic dermatitis of a subject at multiple time points separated over 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; [Equation 1] 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 in which the biological sample was obtained; 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 the 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 rash caused by atopic dermatitis.

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

5. The method of 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 the Patient Oriented Eczema Measure (POEM).

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 itching caused by atopic dermatitis.

8. 8. The method according to claim 7, wherein the severity of atopic dermatitis corresponds to a visual analog scaling (VAS) 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 selected from the group consisting 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 KP The method of claim 1 or 2, wherein the atopic dermatitis severity is any one of NB1, 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 atopic dermatitis severity is the 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 intervals of at least 12 days and not more than 16 days.

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 surface of the skin.

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