Biomarker panel for evaluating sleep problems

Abstract

To provide a biomarker panel for objectively testing chronic sleep disorders in humans using saliva. [Solution] The present invention provides a biomarker panel containing at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine, lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid as biomarkers; a method and kit for evaluating sleep disorders using the same; a method for screening and / or evaluating substances effective in improving sleep disorders; and an evaluation program.

Description

Technical Field

[0001] The present invention relates to a biomarker panel for evaluating sleep disorders using saliva, a method and kit for evaluating sleep disorders using the same, a method for screening and / or evaluating substances effective for improving sleep disorders, and an evaluation program.

Background Art

[0002] Poor sleep is recognized as an important risk factor for mental and metabolic diseases and has become a global social problem.

[0003] Some biomarker candidate molecules for sleep disturbances in blood and feces have already been reported. For example, reports have been made on the relationship between the gut flora in feces and slow-wave sleep in mice (Non-Patent Document 1), biomarker candidate molecules for sleep deprivation in blood in rats and humans (Non-Patent Document 2), biomarkers related to sleep and circadian rhythm (Non-Patent Document 3), the effects of MRs on brain metabolites in insomniacs (Non-Patent Document 4), metabolomics analysis of sleep / insomnia in blood, feces, and urine (Non-Patent Documents 5 and 6), plasma metabolome analysis of sleep deprivation in humans (Non-Patent Document 7), and plasma metabolome analysis of sleep restriction in humans with a familial predisposition to diabetes (Non-Patent Document 8). However, all of these are reports on biomarkers in blood and feces.

[0004] The present inventors have previously developed a sleep disorder model mouse and have disclosed that salts, amino acids, lipids, carbohydrates, amines, amides, betaines, carbonyl compounds, hydroxycarbonyl compounds, glycerol, creatine, proteins, nucleic acids and their degradation products can be used as sleep disorder markers in the blood and urine of this sleep disorder model mouse (Patent Document 1), and that HSPA1a or its gene can be used as a sleep disorder marker in the blood or organs (Patent Document 2). Furthermore, the present inventors have disclosed metabolites and microRNAs in saliva that can serve as biomarkers for sleep disorder, based on metabolome analysis of saliva using the sleep disorder model mouse (Patent Document 3). [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2014-085214 [Patent Document 2] Japanese Patent Publication No. 2013-255481 [Patent Document 3] Japanese Patent Publication No. 2023-30558 [Non-patent literature]

[0006] [Non-Patent Document 1] Sci. Rep., 2020; 10(1): 19554 [Non-Patent Document 2] Proc Natl Acad Sci USA., 2015; 112(8): 2569-74 [Non-Patent Document 3] Current Sleep Medicine Reports, 2015; 1:38-46 [Non-Patent Document 4] PLOS One. 2016; 11(6): e0156771 [Non-Patent Document 5] Int J M01 Sci. 2020; 21(19): 7244 [Non-Patent Document 6] Curr Neurol Neurosci Rep., 2017; 17(11): 89 [Non-Patent Document 7] Proc Natl Acad Sci USA., 2014; 111(29): 10761-6 [Overview of the project] [Problems that the invention aims to solve]

[0007] Regarding chronic sleep problems, subjective assessments using questionnaires such as the Pittsburgh Sleep Quality Index (PSQI) are common, and there is no established method for objectively evaluating chronic sleep problems using biomarkers. Therefore, research is being conducted on biomarkers related to sleep problems, but most of them are detected in blood or feces. To perform tests more easily, there is a need for the development of a method to detect biomarkers using saliva, which can be collected non-invasively. Patent document 3 mentioned above discloses many metabolites and microRNAs that can serve as biomarkers for sleep problems in saliva, but all of them were detected from the saliva of sleep-prone model mice. Therefore, there is a need for the development of a method to objectively test for chronic sleep problems in humans using saliva, which can be collected non-invasively. [Means for solving the problem]

[0008] As a result of diligent research to solve the above problems, the inventors of the present invention discovered that certain metabolites present in saliva samples from humans with sleep disorders were increased or decreased compared to control human saliva samples, and thus completed the present invention.

[0009] Therefore, the first embodiment of the present invention is the following biomarker panel for evaluating sleep disorders using saliva. [1] A biomarker panel for evaluating sleep disorders using saliva, A biomarker panel comprising at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid, as biomarkers. [2] The biomarker panel according to [1], comprising at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), and rumazine as biomarkers. [3] The biomarker panel according to [1], comprising at least three substances selected from the group consisting of trimethylamine, glycerol, hippuric acid, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid as biomarkers.

[0010] A second embodiment of the present invention is a method for evaluating sleep disorders using a biomarker panel. [4] A method for evaluating sleep disorders using a biomarker panel described in any one of [1] to [3], comprising the steps of: quantifying the biomarkers contained in the biomarker panel from a saliva sample derived from a subject; and comparing a reference value based on the amount of biomarkers present in a control saliva sample with the quantitative value of the biomarkers in the saliva sample derived from the subject, wherein the significant difference between the reference value and the quantitative value of the biomarkers is used as an indicator to evaluate sleep disorders. [5] The method according to [4], wherein the control saliva sample is derived from a person with good sleep quality, with a Pittsburgh Sleep Quality Index (PSQI) score of 2 or less.

[0011] A third embodiment of the present invention is a kit for evaluating sleep disorders using a biomarker panel. [6] A kit for evaluating sleep disorders using a biomarker panel described in any one of [1] to [3], comprising a reagent for quantifying biomarkers contained in the biomarker panel from a saliva sample derived from a subject.

[0012] A fourth embodiment of the present invention is a method for screening and / or evaluating substances effective in improving sleep disorders using a biomarker panel. [7] A method for screening and / or evaluating substances effective in improving sleep disorders using a biomarker panel described in any one of [1] to [3], comprising the steps of: quantifying the biomarkers contained in the biomarker panel in a saliva sample from a subject before administration of a candidate substance and obtaining a quantitative value 1; quantifying the biomarkers contained in the biomarker panel in a saliva sample from a subject after administration of a candidate substance and obtaining a quantitative value 2; and comparing quantitative value 1 and quantitative value 2, wherein the statistical significance of the difference between quantitative value 1 and quantitative value 2 is used as an indicator to screen and / or evaluate substances effective in improving sleep disorders. [8] The method described in [7], in which subjects are poor sleepers with a Pittsburgh Sleep Quality Index (PSQI) score of 6 or higher. [9] The method according to [7], wherein the substance is a treatment for sleep disorders.

[0013] A fifth embodiment of the present invention is a program for evaluating sleep disorders using a biomarker panel.

[10] A program for evaluating sleep disorders, which causes a computer to perform the following steps (1) and (2): (1) A procedure for calculating whether there is a significant difference between the measurement data from the subject and the reference value, based on the measurement data including the quantitative value of a biomarker contained in any one of the biomarker panels described in [1] to [3] in the saliva sample from the subject, and the reference value based on the amount of biomarker present in the control saliva sample. (2) When there is a significant difference between the calculated result and the measurement data and the reference value, a procedure for displaying an evaluation result using the significant difference as an index.

Effect of the Invention

[0014] By using the biomarker panel of the present invention, it becomes possible to objectively evaluate chronic sleep disorders using saliva that can be non-invasively collected. Furthermore, by using the biomarker panel of the present invention, it also becomes possible to screen and / or evaluate substances effective for improving sleep disorders.

Brief Description of the Drawings

[0015] [Figure 1] A dot plot of the variable importance of the top 6 substances in the random forest variable importance. [Figure 2] A diagram showing the ROC curve and AUC of the random forest model. [Figure 3] Box plots of each of the top 6 substances in the random forest variable importance. [Figure 4A] A box plot of substances for which a significant difference was recognized in the Mann-Whitney U test. [Figure 4B] A box plot of substances for which a significant difference was recognized in the Mann-Whitney U test. [Figure 4C] A box plot of substances for which a significant difference was recognized in the Mann-Whitney U test.

Mode for Carrying Out the Invention

[0016] 1. A biomarker panel for evaluating sleep disorders A first embodiment of the present invention is a biomarker panel for evaluating sleep disorders using saliva, comprising at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid as biomarkers.

[0017] In this invention, "sleep disorder" can be defined according to the description in the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (1994), of the International Classification of Sleep Disorders: Diagnostic and Coding an Psychiatric Association, published by the American Sleep Disorders Association.

[0018] Examples of sleep disorders in this invention include circadian rhythm sleep disorders and stress-induced sleep disorders. A "stress-induced sleep disorder" is a sleep disorder caused by stress on the brain. A "circadian rhythm sleep disorder" is a sleep disorder in which the body clock is thought to be involved in its onset, and lifestyle habits such as jet lag, irregular eating habits, and mental stress are thought to be the cause. Examples of "circadian rhythm sleep disorders" include jet lag syndrome, shift work sleep disorders, irregular sleep-wake patterns, delayed sleep phase syndrome, advanced sleep phase syndrome, non-24-hour sleep-wake disorders, and unspecified circadian rhythm sleep disorders.

[0019] Sleep disorders can be diagnosed based on the results of questionnaires that have been used for a long time, such as the Japanese version of the Pittsburgh Sleep Quality Index (PSQI).

[0020] In this invention, a "biomarker" is a substance that serves as an indicator of the presence of a specific disease or disorder, and its concentration can usually represent the state or progression of the disease or disorder. In this invention, the substance used as a biomarker is a substance that correlates with the presence and degree of sleep disturbance.

[0021] In the present invention, "biomarker panel" means a collection of multiple biomarkers (panelized) in order to improve the accuracy of evaluation compared to evaluation using a single biomarker. The biomarker panel of the present invention is a panel containing at least three, preferably at least four, more preferably five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, fifteen, sixteen, or all seventeen substances selected from the group consisting of the following 17 substances: glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid.

[0022] The 17 substances listed above are metabolites identified through metabolome analysis of human saliva, and were found to correlate with either a PSQI score of 2 or less (good group, i.e., group with good sleep) or a PSQI score of 6 or more (bad group, i.e., group with poor sleep). Specifically, in random forest (RF) analysis, the following six substances were found to have high Mean Decrease Accuracy (variable importance): trimethylamine, glycerol, hippuric acid, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid. Therefore, the biomarker panel of the present invention preferably contains at least three, preferably at least four, more preferably five, or all six substances selected from the group consisting of the above six substances. As shown in the examples described later, poor sleep could be determined with an accuracy of 86.6% by measuring the above six substances in saliva. In particular, the relative variable importance of trimethylamine and glycerol exceeded 90, suggesting that a biomarker panel containing these two substances can be used to evaluate poor sleep.

[0023] Furthermore, in this invention, the Mann-Whitney U test was performed on substances that showed a correlation with the good group (PSQI score of 2 or less) or the bad group (PSQI score of 6 or more), and the following 13 substances showed a significant difference: glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), and rumazine. Therefore, the biomarker panel of this invention preferably contains at least 3, preferably at least 4, more preferably 5, 6, 7, 8, 9, 10, 11, 12, or all 13 substances selected from the group consisting of the above 13 substances. As shown in the examples described later, the 13 substances that showed significant differences are thought to reflect the state of sleep deprivation, and it is believed that sleep deprivation can be evaluated by measuring the concentration of three or more of these substances in saliva.

[0024] 2. Methods for evaluating sleep problems A second embodiment of the present invention is a method for evaluating sleep disorders using the biomarker panel of the present invention. This method includes the steps of quantifying the biomarkers contained in the biomarker panel from a saliva sample derived from a subject, and comparing a reference value based on the amount of biomarkers present in a control saliva sample with the quantified value of the biomarkers in the saliva sample derived from the subject, and evaluating sleep disorders using the significant difference between the reference value and the quantified value of the biomarkers as an indicator.

[0025] The subjects of the sleep disorder evaluation method of the present invention are not particularly limited, as long as they are subjects capable of developing sleep disorders. While the subjects are typically humans, they may be any mammal, such as pets like dogs and cats, livestock animals like cows, horses, and pigs, or laboratory animals like mice and rats.

[0026] In the sleep disorder evaluation method of the present invention, first, biomarkers included in the biomarker panel of the present invention are quantified from a saliva sample derived from the subject. Since the saliva sample can be collected non-invasively from the subject, it has the advantage of reducing the physical and / or mental burden on the subject. The saliva sample may be collected at any time of day, for example, at the time the subject falls asleep or wakes up. The time of falling asleep and waking up will vary depending on the type of animal, living environment, and experimental environment of the subject.

[0027] The method of saliva collection is not particularly limited and can be carried out by methods known to those skilled in the art. Commercially available saliva collection kits can also be used.

[0028] Saliva samples may be frozen and stored after being collected from the subjects, or they may be prepared as needed. Pretreatment may be performed as desired, for example, by adjusting the concentration of an arbitrary internal standard substance in the saliva samples to be constant across all samples. Such adjustment may be performed by ultrafiltration or other methods.

[0029] The biomarkers included in the biomarker panel of the present invention are metabolites present in human saliva and are all substances disclosed in databases such as PubChem and HMDB (The Human Metabolome Database). The method for quantifying each biomarker is not particularly limited as long as it can quantify the biomarker, but can be performed, for example, by metabolome analysis. Metabolome analysis can be performed by CE-FTMS (capillary electrophoresis-Fourier transform mass spectrometry).

[0030] Next, a reference value based on the amount of biomarker present in the control saliva sample is compared with the quantitative value of the biomarker in the saliva sample derived from the subject, and the significant difference between the reference value and the quantitative value of the biomarker is used as an indicator to evaluate sleep deprivation. Here, the "control saliva sample" is a saliva sample collected from a healthy mammal of the same species as the subject, i.e., a mammal that does not have sleep deprivation. In particular, when the subject is human, it is preferable that the control saliva sample is a saliva sample derived from a person with good sleep, whose PSQI score is 2 or less.

[0031] The amount of biomarkers present in a control saliva sample can be quantified in the same way as the biomarkers present in the subject's saliva sample. This quantification can be performed when quantifying the biomarkers present in the subject's saliva sample to determine the reference value, or the reference value can be set in advance by quantifying the biomarkers present in the control saliva sample.

[0032] The evaluation of sleep disorders is performed using the significant difference between the reference value and the quantitative value of the biomarker in the subject's saliva sample as an indicator. The significance test can be performed using a test method known to those skilled in the art, such as Welch's t-test or Student's t-test. A significant difference is not particularly limited, but for example, a p-value of less than 0.05, less than 0.01, or less than 0.001 may be considered significant.

[0033] The presence or severity of sleep problems is determined by whether the amount of a biomarker in a saliva sample collected from the subject is significantly increased or significantly decreased compared to the reference value. Here, whether an increase or decrease relative to the reference value is considered sleep problems depends on the type of biomarker. In either case, if there is a significant difference between the reference value and the quantitative value of the subject, the subject can be evaluated as having and / or having severe sleep problems. Alternatively, by setting a reference value in advance, sleep problems can be diagnosed if the amount of a biomarker in a saliva sample collected from the subject exceeds or falls below that reference value.

[0034] The biomarker panel used in the sleep disorder evaluation method of the present invention contains at least three substances as biomarkers. Therefore, by combining the measurement results of at least three biomarkers, a more accurate evaluation of sleep disorders can be performed compared to an evaluation method that measures only one biomarker. In addition, a risk score can be calculated based on the measurement results of at least three biomarkers included in the biomarker panel of the present invention, and the evaluation can be performed using that risk score.

[0035] 3. Kit for evaluating sleep problems A third embodiment of the present invention is a kit for evaluating sleep disorders using the biomarker panel of the present invention. Specifically, the kit includes reagents for quantifying biomarkers contained in the biomarker panel from a saliva sample derived from a test subject.

[0036] As described above in relation to the biomarker panel of the present invention, the biomarkers included in the biomarker panel of the present invention are at least three substances selected from the group consisting of the following 17 metabolites present in human saliva: glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid. All of these substances are disclosed in databases such as PubChem and HMDB (The Human Metabolome Database), and information on their quantification methods is also known in the industry. Therefore, the reagents included in the kit of the present invention are not particularly limited as long as they are reagents that can be used to quantify any of the above 17 substances.

[0037] 4. Methods for screening and / or evaluating substances effective in improving sleep disorders. A fourth embodiment of the present invention is a method for screening and / or evaluating substances effective in improving sleep disorders using the biomarker panel of the present invention. The method includes the steps of: obtaining a quantitative value 1 by quantifying the biomarkers contained in the biomarker panel of the present invention in a saliva sample from a subject before administration of a candidate substance; obtaining a quantitative value 2 by quantifying the biomarkers contained in the biomarker panel in a saliva sample from a subject after administration of the candidate substance; and comparing quantitative value 1 and quantitative value 2. The method screens and / or evaluates substances effective in improving sleep disorders using the significant difference between quantitative value 1 and quantitative value 2 as an indicator.

[0038] There are no particular limitations on the candidate substances to be screened and / or evaluated by the method of the present invention, but it is preferable that they be substances whose safety to the organism and / or human body of the subject being tested has been confirmed.

[0039] The subjects used in the method of the present invention are not particularly limited, as long as they are capable of developing sleep disorders. The subjects may be any mammal, such as pets like dogs and cats, livestock animals like cattle, horses, and pigs, laboratory animals like mice and rats, or humans. In particular, by using sleep disorder model animals or individuals with sleep disorders who have a PSQI score of 6 or higher as subjects, it is possible to screen and / or evaluate substances that are effective in improving sleep disorders.

[0040] There are no particular limitations on the method of administering the candidate substance to the test subject, but administration methods such as oral, intravenous, or topical application can be used. If the test subject is an animal, the test substance can also be added to feed or water for ingestion.

[0041] The method for collecting saliva from subjects and the method for quantifying biomarkers are as described in "2. Evaluation Method for Sleep Disorders" above.

[0042] Furthermore, in the method of the present invention, a "saliva sample derived from the subject before administration of the candidate substance" is required to obtain quantitative value 1, and a "saliva sample derived from the subject after administration of the candidate substance" is required to obtain quantitative value 2. These two saliva samples may be collected from a single individual or from separate individuals.

[0043] An example of a specific procedure for carrying out the method of the present invention is described below. Saliva samples are collected from subjects before and after administration of the candidate substance. The quantitative value of the biomarker in the saliva sample before administration is designated as quantitative value 1, and the quantitative value of the biomarker in the saliva sample after administration is designated as quantitative value 2. Quantitative value 1 and quantitative value 2 are then compared. If a significant difference is found between quantitative value 1 before administration of the candidate substance and quantitative value 2 after administration of the candidate substance, the candidate substance can be screened and / or evaluated as a substance effective in improving sleep disorders.

[0044] Furthermore, multiple subjects are divided into two groups: one group receives no candidate substance, and the other group receives the candidate substance. Saliva samples are collected from each of the two groups, and the biomarkers included in the biomarker panel are quantified from the collected saliva samples. The biomarker quantification value for the group that did not receive the candidate substance is designated as Quantitative Value 1, and the biomarker quantification value for the group that received the candidate substance is designated as Quantitative Value 2. Next, Quantitative Value 1 and Quantitative Value 2 are compared. If, as a result of the comparison, there is a significant difference between Quantitative Value 1 for the group that did not receive the candidate substance and Quantitative Value 2 for the group that received the candidate substance, the candidate substance can be screened and / or evaluated as a substance effective in improving sleep disorders.

[0045] In particular, even when the test subjects have sleep problems, it is possible to quantify biomarkers from saliva samples of healthy individuals without sleep problems (for example, a group of individuals with good sleep who have a PSQI score of 2 or less) to obtain quantitative value 3, and then compare quantitative value 2 (the value after administration of the candidate substance) with quantitative value 3 to confirm that there is no significant difference. If there is no significant difference between quantitative value 2 and quantitative value 3, it can be confirmed that the candidate substance improved sleep problems to a healthy state.

[0046] Furthermore, while quantitative value 3 can be measured at the same time as quantitative values ​​1 and 2, it is also possible to quantify the biomarkers present in saliva samples from healthy control groups beforehand and set reference values.

[0047] A significant difference between quantitative value 1 and quantitative value 2, or between quantitative value 2 and quantitative value 3, can be determined by statistical tests known to those skilled in the art, such as Welch's t-test or Student's t-test. A significant difference is not particularly limited, but for example, a p-value less than 0.05, less than 0.01, or less than 0.001 may be considered significant.

[0048] Substances screened and / or evaluated as "substances effective in improving sleep disorders" by the method of the present invention may be used as active ingredients in pharmaceuticals, supplements, and health foods (including Foods for Specified Health Uses and Foods with Function Claims) for sleep disorders, or as feed additives. In particular, substances in which a significant difference is observed between quantitative value 1 and quantitative value 2, when the test subjects are sleep disorder model mice or individuals suffering from severe sleep disorders such as those with a PSQI score of 6 or higher, are considered promising as active ingredients for sleep disorder treatments.

[0049] 5. Programs for evaluating sleep disorders A fifth embodiment of the present invention is a program for evaluating sleep disorders, which causes a computer to perform the following steps (1) and (2). (1) A procedure for calculating whether there is a significant difference between the measurement data from the subject and the reference value, based on measurement data including quantitative values ​​of biomarkers included in the biomarker panel of the present invention in a saliva sample from the subject, and a reference value based on the amount of biomarkers present in a control saliva sample. (2) A procedure for displaying evaluation results using the statistical significance as an indicator when there is a statistically significant difference between the calculated measurement data and the reference value.

[0050] The method for calculating whether there is a significant difference between the measurement data including the quantitative value of the biomarker, the reference value based on the amount of biomarker present in the control saliva sample, and the measurement data from the subject and the reference value in the above procedure (1), as well as the method for obtaining the evaluation result using the significant difference as an indicator in procedure (2), are as described in "2. Evaluation Method for Sleep Disorders" above.

[0051] The program of the present invention may further include a step for inputting measurement data.

[0052] The program of the present invention can be implemented on a computer by methods known to those skilled in the art. For example, it can be implemented on a computer via a computer-readable recording medium on which the program of the present invention is stored.

[0053] The program of the present invention can be used in the above-mentioned "2. Method for evaluating sleep disorders" and "4. Method for screening and / or evaluating substances effective in improving sleep disorders." [Examples]

[0054] The present invention will be described below using examples, but the present invention is not limited to these examples.

[0055] The following trials are registered in the clinical trial registry system. Registration body: UMIN-CTR Registration number: UMIN000053021

[0056] Participants in the study were selected based on the following criteria. i. Japanese ii. Male iii. Middle-aged and older adults (45 years old and over, under 60 years old) iv. Healthy individuals v. Persons working consecutive shifts (5 consecutive days) with a full two-day weekend system. vi. Of the persons described in i. to v. above, those who meet either condition a. or b. below 365 people each, 730 people in total a. Those who have trouble with the quality of their sleep b. Those who do not have problems with sleep quality vii. Of those listed in i. to vi. above, those who underwent the screening in Pittsburgh during the screening period. Based on the results of the Japanese version of the Sleep Quality Index (PSQI), either a. or b. below 50 people each who meet the conditions, for a total of 100 people. a. Individuals with a PSQI score (PSQIG) of 2 or less (good group) b. Individuals with a PSQI score (PSQIG) of 6 or higher (bad group)

[0057] Furthermore, individuals who met the following exclusion criteria were excluded from participating in the study. i. Individuals currently receiving treatment for or with a history of malignant tumors, heart failure, or myocardial infarction. ii. Individuals with implanted pacemakers or cardioverter-defibrillators. iii. Individuals currently receiving treatment for any of the following chronic diseases arrhythmia, liver damage, chronic kidney disease, cerebrovascular disease, rheumatic disease, diabetes, Dyslipidemia, hypertension, and other chronic diseases iv. Individuals who consume Foods for Specified Health Uses or Foods with Function Claims v. Individuals taking pharmaceuticals (including herbal medicines) or supplements. vi. Individuals with allergies (to medications) vii. Pregnant, breastfeeding, or intending to become pregnant during the examination period. viii. Individuals who participated in other clinical trials within the 28 days prior to the date of obtaining consent. or those who plan to participate during the exam period ix. Any other person whom the principal investigator deems unsuitable to be included in this study.

[0058] The PXQI score mentioned above was calculated as follows: Implementation details: Participants were asked to answer questions about their subjective sleep symptoms using the PSQI (Periodically Stressed Quality Index). Survey items: PSQI score (PSQIG), sleep quality, time to fall asleep, sleep duration, Sleep efficiency, difficulty sleeping, use of sleeping pills, difficulty staying awake during the day Survey period: Screening period Evaluation details: Measured values Evaluation methods: Sleep quality, time to fall asleep, sleep duration, sleep efficiency, difficulty sleeping, use of sleeping pills. The scores for daytime wakefulness were totaled to calculate the PSQI score.

[0059] Furthermore, saliva tests were conducted for each subject. Specifically, saliva was collected from subjects who visited the clinic on the morning of their first day off after a series of consecutive workdays. Saliva was collected using saliva collection tubes (LSI Medience, Japan) according to the prescribed procedure. The collected saliva samples were aliquoted into two bottles for metabolome analysis and protein measurement, and stored in a -80°C freezer until shipment. The analysis was outsourced to Human Metabolome Technologies, Inc., which performed metabolome analysis (ωScan 100 samples + 353 substances quantified) using CE-FTMS (capillary electrophoresis-Fourier transform mass spectrometry) and saliva protein measurement. When shipping the saliva samples to Human Metabolome Technologies, Inc., they were packaged with dry ice and shipped frozen.

[0060] Metabolome analysis detected 683 substances in saliva. Of these, 435 substances were selected as the metabolites for analysis, as they were detected in more than 50% of subjects in either the good group (PSQI score of 2 or less, N=50) or the bad group (PSQI score of 6 or more, N=50). For these 435 substances, the relative area value before correction for salivary protein content was calculated according to the following formula. Relative area value before correction for salivary protein content = Relative area value of candidate compound sheet × Sample amount (mg)

[0061] Random Forest (RF) Analysis Using the relative area values ​​of the above 435 substances before correction for salivary protein content, a random forest (RF) analysis was performed under the following conditions to create a random forest model. Missing values ​​are substituted with a value close to 0 (2.2204e-016). Cross-validation method: Leave-One-Out Cross Validation Next, after creating a random forest model using all metabolites, the model was recalculated using the top 6 substances in Mean Decrease Accuracy (variable importance) to create a two-group discriminant model. Table 1 shows the top 6 substances in random forest variable importance and their variable importance scaled from 0 to 100, and Figure 1 shows a dot plot of the scaled variable importance.

[0062] [Table 1]

[0063] Of the substances listed in Table 1 above, glycerol was also selected in a random forest analysis (data not shown) performed after correcting for salivary protein levels. Furthermore, hippuric acid and iminodiacetic acid are substances related to glycine metabolism.

[0064] Furthermore, the ROC curve and AUC of the random forest model are shown in Figure 2, and the box plots of the six substances mentioned above are shown in Figure 3. Note that "MW test p<0.05" in the figures indicates that the p-value in the Mann-Whitney U test, which will be discussed later, was less than 0.05.

[0065] As is clear from Figure 2, by measuring the six substances listed above in saliva, sleep problems could be diagnosed with an accuracy of 86.6%. In particular, the relative importance of trimethylamine and glycerol exceeded 90. Therefore, it is considered possible to evaluate sleep problems using a biomarker panel that includes these two substances.

[0066] Mann-Whitney U test The Mann-Whitney U test was also performed on the 435 substances mentioned above. The top 30 substances in the Mann-Whitney U test, along with their p-values ​​and q-values, are shown in Table 2 below.

[0067] [Table 2]

[0068] As is clear from Table 2 above, the top 13 substances—glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenylglycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), and lumazine—all had p-values ​​less than 0.05, indicating statistically significant differences. Box plots of these 13 substances are shown in Figures 4A, 4B, and 4C.

[0069] The 13 substances that showed significant differences in the Mann-Whitney U test are thought to reflect the state of sleep deprivation. Therefore, it is possible to assess sleep deprivation by measuring the concentration of three or more of these substances in saliva.

[0070] Of the 13 substances listed above, glycerol and hippuric acid are among the substances with the highest variable importance in random forest analysis. The following 17 substances also have high variable importance in random forest analysis and / or show significant differences in the Mann-Whitney U test: glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenylglycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid are all effective biomarkers for evaluating sleep disorders using saliva. Compared to measuring a single biomarker, measuring multiple effective biomarkers can improve diagnostic accuracy. Therefore, a biomarker panel containing at least three substances selected from this group of substances is considered effective for objectively testing chronic sleep disorders using saliva. [Industrial applicability]

[0071] This invention provides a biomarker panel for objectively testing chronic sleep disorders in humans using saliva. Using this biomarker panel, it becomes possible to create a method and kit for evaluating sleep disorders, a method for screening and / or evaluating substances effective in improving sleep disorders, and an evaluation program.

Claims

1. A biomarker panel for evaluating sleep problems using saliva, A biomarker panel comprising at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), lumazine, trimethylamine, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid as biomarkers.

2. The biomarker panel according to claim 1, comprising at least three substances selected from the group consisting of glycerol, 5,6-dihydroxyindole, 3,4-dihydroxyphenyl glycol, N-acetylvaline, hippuric acid, succinylcarnitine, 4-acetamidobutanoic acid, carboxymethyllysine, alginic acid, O-succinylhomoserine, 2-hydroxybutyric acid, γ-glutamic acid-threonine (γ-Glu-Thr), and lumazine as biomarkers.

3. The biomarker panel according to claim 1, comprising at least three substances selected from the group consisting of trimethylamine, glycerol, hippuric acid, creatine phosphate, 3-phenylpropionic acid, and iminodiacetic acid as biomarkers.

4. A method for evaluating sleep disorders using a biomarker panel according to any one of claims 1 to 3, A step of quantifying the biomarkers included in the biomarker panel from a saliva sample derived from the subject, A step of comparing a reference value based on the amount of the biomarker present in a control saliva sample with a quantitative value of the biomarker in a saliva sample derived from the subject being tested. A method for evaluating sleep disorders, including the above-mentioned reference value and the quantitative value of the biomarker, using the significant difference between the reference value and the quantitative value of the biomarker as an indicator.

5. The method according to claim 4, wherein the control saliva sample is a saliva sample derived from a person with good sleep quality, whose Pittsburgh Sleep Quality Index (PSQI) score is 2 or less.

6. A kit for evaluating sleep disorders using a biomarker panel according to any one of claims 1 to 3, Reagents for quantifying biomarkers included in the biomarker panel from saliva samples derived from the test subject A kit that includes this.

7. A method for screening and / or evaluating substances effective in improving sleep disorders using a biomarker panel according to any one of claims 1 to 3, A step of quantifying the biomarkers contained in the biomarker panel in a saliva sample derived from a subject before administration of the candidate substance, and obtaining a quantitative value 1, The process involves quantifying the biomarkers contained in the biomarker panel in a saliva sample derived from a subject after administration of a candidate substance, and obtaining a quantitative value 2. A step of comparing the quantitative value 1 with the quantitative value 2. A method for screening and / or evaluating substances effective in improving sleep disorders, including the above, using the significant difference between quantitative value 1 and quantitative value 2 as an indicator.

8. The method according to claim 7, wherein the subject being tested is a person with poor sleep quality whose Pittsburgh Sleep Quality Index (PSQI) score is 6 or higher.

9. The method according to claim 7, wherein the substance is a therapeutic agent for sleep disorders.

10. This is a program for evaluating sleep problems. A program to instruct the computer to perform the following steps (1) and (2): (1) A procedure for calculating whether there is a significant difference between the measurement data from the subject and the reference value, based on measurement data including quantitative values ​​of biomarkers contained in the biomarker panel described in any one of claims 1 to 3 in a saliva sample derived from the subject, and a reference value based on the amount of the biomarker present in a control saliva sample. (2) A procedure for displaying an evaluation result using the significant difference as an indicator when there is a significant difference between the measurement data and the reference value as a result of the calculation described above.

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