WO2021193097A1

WO2021193097A1 - Method for determining factor of chemical substance influencing endocrine system

Info

Publication number: WO2021193097A1
Application number: PCT/JP2021/009779
Authority: WO
Inventors: 貴子清水; 文博山田; 駿河合
Original assignee: 住友化学株式会社
Priority date: 2020-03-23
Filing date: 2021-03-11
Publication date: 2021-09-30
Also published as: JP2021145635A

Abstract

The present invention provides a method for determining a factor of a chemical substance influencing the endocrine system in an organism, wherein the method includes (1) a step in which the expression amount of a gene serving as a marker and/or the amount of an endogenous metabolite serving as a marker in samples collected from a subject not brought into contact with the chemical substance and from a subject brought into contact with the chemical substance are measured, and (2) a step in which the expression amount of the gene and/or the amount of the endogenous metabolite measured in step (1) are subsequently analyzed and it is determined whether the chemical substance is a factor influencing the endocrine system as an endocrine disruptor or a factor influencing the endocrine system as stress.

Description

How to determine the factors that affect the endocrine system of chemical substances

This patent application claims the priority and interests under the Paris Convention based on Japanese Patent Application No. 2020-050701 (filed on March 23, 2020) and is described in the above application by reference here. The entire content of this is incorporated herein by reference.

The present invention relates to a method for determining factors affecting the endocrine system of a chemical substance and a kit for carrying out this method. The present invention also relates to a method for selecting a gene that serves as a specific marker and / or an endogenous metabolite that serves as a specific marker for determining factors that affect the endocrine system of a chemical substance.

With the growing awareness of safety regarding chemical substances, it has become an important issue worldwide to properly regulate endocrine disrupting chemicals (ED substances). Through the International Chemical Safety Cards (IPCS) in 2002, the World Health Organization (WHO) stated that "ED substances have a detrimental effect on the health of an individual or its offspring by altering the function of the endocrine system of the individual. It is an exogenous substance or a mixture thereof that causes Furthermore, in June 2018, guidance for ED substance determination was prepared by the European Food Safety Authority (EFSA), the European Chemicals Agency (ECHA), and the Joint Research Center (JRC). The guidance stipulates that "an ED substance is determined if three items are met: adverse effects on the endocrine system, mechanism of action that changes the endocrine system (MOA), and the relationship between MOA and toxic effects." More detailed evaluation of the effects on the endocrine system has come to be required.

The effects on the endocrine system include, for example, atrophy and weight gain of tissues related to sex hormones such as ovary, uterus, testis, prostate, adrenal gland and blood, and tissues that control the secretion of higher hormones that control sex hormones. The pituitary gland, hypothalamus, hormonal gland, etc. are enlarged and atrophic.

Under the influence of the above-mentioned tightening of regulations on endocrine disrupting effects, in animal tests using rats, etc. conducted to evaluate the safety of chemical substances, the endocrine system such as adrenal glands and testis derived from animals to which the chemical substances were administered Impact may be seen on related organizations. As one means of assessing the effects on the endocrine system, chemical substances such as having the same activity as sex hormones (male hormones and female hormones) or showing that the sex hormone synthesis pathway has been inhibited or induced. It is difficult to newly register or re-register the compound when it is considered that the compound acted directly in the living body.

In general, it is known that when stress is applied to the living body, the endocrine tissue and hormone concentration are affected (indirect action). Currently, the effects on some endocrine tissues are based on food reduction data (when a compound is mixed with food, it becomes starved as a result of avoiding food) rather than the direct effect of the compound (ED effect). As a result, it is presumed that it is an indirect effect due to the (hunger) stress state, but in the future, it is thought that a scientific basis indicating the stress state will be required.

Conventionally, neurotransmitters such as heart rate, blood pressure, adrenaline and noradrenaline of a test animal are known as stress markers, and among them, cortisol, which is an adrenocortical hormone, is well known (Non-Patent Document 1). .. However, cortisol has large diurnal fluctuations and individual differences, and cannot be analyzed accurately with good reproducibility. In animal experiments, the effects of multi-headed laboratory animals, stimulation during blood collection, movement between laboratory facilities, restraint by experimenters, etc. It was sensitive to the stimulus of the animal, and it was difficult to accurately indicate the stress state in animal experiments. Further, in the conventional technique, stress can be evaluated by quantifying the expression level of a stress evaluation marker gene in leukocytes (Patent Document 1), but the direct action of a chemical substance on the endocrine system is discriminated. I couldn't.

Japanese Unexamined Patent Publication No. 2013-110969

The problem to be solved by the present invention is to simultaneously determine whether the factor of the influence of a chemical substance on the endocrine system is a direct action as an endocrine disruptor or an indirect action as stress at the same time with high accuracy. To provide a way that can be done.

Therefore, in order to solve the above-mentioned problems, the present inventors have made a specific marker in an organism, tissue, or cell that is not in contact with the chemical substance to be tested and in the organism, tissue, or cell that is in contact with the chemical substance. By analyzing fluctuations in the expression level of a gene and / or the amount of an endogenous metabolite that serves as a specific marker, factors that affect the endocrine system of a chemical substance act directly as an endocrine disruptor. The present invention has been completed by finding that it is possible to determine whether the substance acts indirectly as stress.

The present invention is as follows.
[1]
It is a method for discriminating factors that affect the endocrine system in an organism possessed by a chemical substance. (1) Expression of a gene that serves as a marker in a subject to which the chemical substance is not in contact and a sample collected from a subject in contact with the chemical substance. The step of measuring the amount and / or the amount of the endocrine metabolite as a marker, and then (2) analyzing the expression level of the gene and / or the amount of the endocrine metabolite measured in the step (1). A method comprising the step of determining whether the chemical substance is a factor affecting the endocrine system as an endocrine disturbing substance or a factor affecting the endocrine system as stress.
[2]
The gene and / or the endogenous metabolite machine-learns and / or the amount of the gene expression and / or the amount of the endogenous metabolite in a sample taken from a subject not in contact with the chemical and a subject in contact with the chemical. Alternatively, the method according to [1], which is selected by applying to a statistical method.
[3]
The genes are guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen sterol binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subunit alpha gene, kelch-like family member 30 gene, carboxylase-like gene, migration and invasion inhibitory protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and A_64_P100513 One or more selected from the group consisting of (gene represented by SEQ ID NO: 5), wherein the endogenous metabolites are 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, One or more selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid, xylrose, succinic acid, dopamine, and mannitol, [1 ] Or the method according to [2].
[4]
The genes are from the lysine demethylase 8 gene, the microtubule-associated protein RP / EB family member 3 gene, the oxysterol binding protein-like 3 gene, the translocase of outer mitochondrial membrane 70 gene, and A_64_P100513 (the gene represented by SEQ ID NO: 5). One or more selected from the group, said endogenous metabolites are 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, benzoic acid, isoleucine, ellaidic acid, dopamine, and. The method according to any one of [1] to [3], which is one or more selected from the group consisting of mannitol.
[5]
The method according to any one of [1] to [4], wherein the analysis in the step (2) is performed using machine learning and / or a statistical method.
[6]
The machine learning and / or statistical method is linear regression, logistic regression, support vector machine, neural network, random forest, Lasso (LASSO) regression, ridge (Ridge) regression, elastic net regression, t test, ROC curve, The method according to [5], which is selected from the group consisting of and variance analysis (ANOVA).
[7]
The machine learning is based on the guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 gene, and translocase of outer mitochondrial membrane 70 gene. , A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subunit alpha gene, kelch-like family member 30 gene, carboxylesterase-like gene, migration and invasion inhibitory protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and One or more genes selected from the group consisting of A_64_P100513 (gene represented by SEQ ID NO: 5) and / or selected from the group consisting of 2-deoxyglucose, 3-hydroxyisobutyric acid, and 4-aminobutyric acid. The method according to [6], wherein when one or more endogenous metabolites are used, the support vector machine is used and the support vector machine is characterized by a radial basis function kernel. ..
[8]
One or more intrinsic factors in which the machine learning is selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisobutyric acid, benzoic acid, isoleucine, lassoyl, ellaic acid, xylulose, succinic acid, dopamine, and mannitol. The method according to [6], wherein when a sex metabolite is used, Lasso regression is used, and the Lasso regression uses logistic regression analysis to construct a model formula.
[9]
The method according to any one of [1] to [8], wherein the effect on the endocrine system is characterized by a decrease in testosterone concentration in blood.
[10]
Any one of [1] to [9], wherein the sample is a tissue related to the endocrine system, liver or blood, or a tissue related to the endocrine system, a cell isolated from the liver or blood, or a cultured cell thereof. The method described in.
[11]
The method of [10], wherein the tissue associated with the endocrine system is the thymus or pituitary gland.
[12]
The method according to any one of [1] to [11], wherein the subject is a mammal or a tissue or cell thereof.
[13]
The method according to [12], wherein the mammal is a human, rat or mouse.
[14]
A kit for determining a factor of a chemical substance that affects the endocrine system in an organism, and includes a means for carrying out the method according to any one of [1] to [13].
[15]
The means include the guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subunit alpha gene, kelch-like family member 30 gene, carboxylase-like gene, migration and invasion inhibitory protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and A_64_P100513 The expression level of one or more genes selected from the group consisting of (gene represented by SEQ ID NO: 5), and / or 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2-aminoiso. Measure the amount of one or more endogenous metabolites selected from the group consisting of butyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid, xylrose, succinic acid, dopamine, and mannitol. The kit according to [14], which is a means for the above.
[16]
A method for selecting genes and / or endogenous metabolites for determining factors that affect the endocrine system in organisms possessed by chemical substances. (1) Unstressed organisms and loaded organisms. Steps to measure gene expression and / or amount of endogenous metabolites in samples taken from, and (2) genes in samples taken from subjects not in contact with endocrine disruptors and those in contact. The step of measuring the expression level and / or the amount of the endogenous metabolite, (3) the expression level of the gene obtained in the steps (1) and (2), and / or the amount of the endogenous metabolite A step of selecting a gene and / or an endocrine metabolite by analysis using learning and / or statistical methods, and then (4) among the genes and endocrine metabolites selected in the step (3). Exclude duplicates of the gene and endocrine metabolite selected in step (1) and step (3) after step (1) and the gene and endocrine metabolite selected in step (3) after step (2). A method that includes the steps to be performed.

According to the present invention, when investigating the effects of chemical substances on the endocrine system of an organism, not only the feed reduction data, but also the expression level of genes that are specific markers in multiple tissues and / or specific endogenous metabolites. It is possible to determine the factors of influence on the endocrine system from the fluctuation data of the amount of. Furthermore, the present invention can easily determine the factors that affect the endocrine system of chemical substances with high versatility and accuracy.

When a microarray was performed on a sample collected from each tissue (liver, pituitary gland, adrenal gland, thyroid gland, and testis) for each test group using a gene as a specific marker as an index, and the expression level of the gene was analyzed. The prediction rate for each sample is shown. GC / MS analysis was performed on each test group using samples collected from each tissue (serum, testis, pituitary gland, adrenal gland, thoracic gland, thyroid gland, and liver) using endogenous metabolites as specific markers as indicators. Then, the prediction rate in each sample when the amount of the endogenous metabolite is analyzed is shown.

Unless otherwise defined, all technical and scientific terms used herein generally have the same meaning as understood by one of ordinary skill in the art to which the present invention belongs.

The present invention is a method for determining a factor of a chemical substance that affects the endocrine system in an organism, and (1) is specific in a subject to which the chemical substance is not in contact and a sample collected from a subject in contact with the chemical substance. A step of measuring the expression level of a gene as a marker and / or the amount of an endocrine metabolite as a specific marker, and then (2) the expression level of the gene and / or the endocrine metabolism measured in the step (1). It is characterized by including a step of analyzing the amount of a substance and determining whether the chemical substance is a factor affecting the endocrine system as an endocrine disturbing substance or a factor affecting the endocrine system as stress. Is to be. According to the method of the present invention, a chemical substance affects the endocrine system in an organism by measuring fluctuations in the expression level of a gene that serves as a specific marker and / or the amount of an endogenous metabolite that serves as a specific marker. Whether the factor acts directly as an endocrine disruptor or indirectly as a stress can be easily and simultaneously determined.

As a factor affecting the endocrine system in the present invention, it is assumed that a chemical substance affects the endocrine system of an organism as either an endocrine disruptor or stress. The effect as an endocrine disruptor on the endocrine system means that by altering the function of the endocrine system of an organism, it has a detrimental effect on the health of the individual or its offspring (direct action), for example, the adrenal gland. , Womb, testis, prostate, adrenal gland, blood and other sex hormone-related tissues such as atrophy or weight gain, or pituitary gland, hypothalamus, or thyroid gland, which are tissues that control the secretion of superior hormones that control sex hormones. Such as enlargement or atrophy. On the other hand, the effect as stress on the endocrine system means the effect (indirect action) due to the stress on the organism due to the administration of the chemical substance, and is distinguished from the effect as the endocrine disruptor. It is a thing. Examples of effects as stress include an increase in heart rate or blood pressure, an increase or decrease in neurotransmitters such as adrenaline and noradrenaline in the body, and atrophy of the thymus. According to the method of the present invention, it is possible to determine whether the factor in which the chemical substance of interest affects the endocrine system of an organism is an endocrine disruptor or a stress.

The endocrine disruptor in the present invention means an exogenous substance or a mixture thereof, which is known to change the function of the endocrine system of an individual organism. The stress in the present invention means a substance that causes an organism to imitate a stress state. Known markers for measuring stress include heart rate, blood pressure, neurotransmitters such as adrenaline and noradrenaline, and corticosteroids cortisol or corticosterone in test animals. The stress in the present invention includes, for example, those caused by starvation, restraint, swimming, electricity and the like.

The endocrine system in the present invention is also referred to as an endocrine system, and means an organ that secretes hormones in living organisms, especially animals. Examples include the body, adrenal glands, thyroid glands, parathyroid glands, and pancreas.

The chemical substance to which the method of the present invention can be applied is not particularly limited as long as it is a chemical substance for which it is necessary to investigate the factors of influence on the endocrine system of the organism. As such a chemical substance, for example, it may be a useful candidate substance developed as a novel compound developed in the fields of pesticides, medicines, veterinary medicine, the environment and the like. Alternatively, the chemical substance may include a known chemical substance, for example, one that may have an adverse effect on the endocrine system in an organism.

Organisms to which the present invention applies include any animal that may be affected by the endocrine system of chemicals, such as vertebrates, mammals, birds, reptiles, amphibians, fish, and pet animals. Examples include, but are not limited to, vertebrates, shellfish, insects, arthropods such as spiders, and invertebrates such as soft-bodied animals. Organisms applied to the present invention are preferably humans, monkeys, chimpanzees, mice, rats, rabbits, and more preferably humans, mice, or rats. For example, examples of the rat include the RccHan: Wist system.

The subject to which the present invention is applied may be the organism, or the tissue or cell of the organism. The tissue or cell of the organism may be, for example, a tissue or cell formed by in vitro differentiation induction from a pluripotent stem cell or somatic stem cell of the organism, or a tissue or cell created by direct reprogramming. good.

The sample used in the method of the invention may be part or all taken from any body tissue or organ in an organism, taken from an organ or tissue that reflects the effects of chemicals on the endocrine system. It may be the one that has been done. It may also be part or all of the tissue, organ or cell of the subject to which the present invention applies. The sample includes tissues, liver, or blood (or blood) related to the endocrine system including ovaries, uterus, placenta, testis, prostate, pituitary gland, hypothalamus, pineal gland, adrenal gland, thyroid gland, parathyroid gland, and pancreas. It may be collected from (serum), or cells isolated from these tissues or cultured cells thereof can be used, but is not limited thereto. The sample used in the method of the invention is preferably taken from blood (or serum), thymus, liver, or pituitary gland.

The method of the present invention includes (1) measuring the expression level of the gene and / or the amount of the endogenous metabolite in a subject not in contact with a chemical substance and a sample collected from the subject in contact with the chemical substance. included. When the subject is an organism, the method of contacting the chemical substance with the organism in the present invention may be any method as long as the chemical substance can be introduced into the body of the organism, and the method can be used orally or parenterally to the organism. It may be injected, for example, subcutaneously or intraperitoneally. Alternatively, the contact may be contact or exposure to the surface of the body of the organism. For sampling in the method of the present invention, a method common in the art can be used. The method of collecting the sample may differ depending on each tissue or organ, and includes, for example, collecting by surgically removing a part from the target tissue or organ. The method also includes collecting blood by injection into an organism. Alternatively, in the case of a non-human organism, a sample may be collected from the target tissue or organ by dissecting the target organism. The effect of the present invention on the endocrine system is preferably a decrease in testosterone concentration in the blood.

The specific marker gene and / or the specific marker endogenous metabolite used in the present invention is the expression level of the gene in a subject not in contact with a chemical substance and a sample collected from a subject in contact with the chemical substance. And / or may be selected by applying the amount of said endogenous metabolite to machine learning and / or statistical techniques. In addition, the gene used in the method of the present invention includes a guanine deaminase (sometimes referred to as Gda) gene, an interleukin-1 receptor-associated kinase (sometimes referred to as Irak3) gene, and lysine demethylase 8 (sometimes referred to as Irak3). Gene (sometimes called Kdm8), microtubule-associated protein RP / EB family member 3 (sometimes called Mapre3) gene, oxygensterol binding protein-like 3 (sometimes called Osbpl3) gene , Translocase of outer mitochondrial membrane 70 (sometimes called Tomm70) gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha Gene (sometimes called Gabpa), kelch-like family member 30 (sometimes called Klhl30) gene, carboxylesterase-like (sometimes called LOC291863) gene, migration and inhibition inhibition protein Gene (sometimes called Miip), signal-regulatory protein alpha (sometimes called Sirpa) gene, solute carrier family 7 member 7 (sometimes called Slc7a7) gene, vomeronasal 1 receptor From 77 (sometimes referred to as Vom1r77) gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and A_64_P100513 (gene represented by SEQ ID NO: 5) One or more selected from the group of The genes used in the present invention are preferably lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, and A_64_P100513 (SEQ ID NO:). The gene represented by 5). In order to carry out the method of the present invention with high accuracy, guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 Gene, translocase of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene , Quadresterase-like gene, migration and inhibition inhibition protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (SEQ ID NO: 3) It is preferable to measure the expression levels of (gene represented by 4) and A_64_P100513 (gene represented by SEQ ID NO: 5). Here, the gene described in the present specification means a nucleic acid molecule encoding an amino acid sequence of a specific protein.

The endogenous metabolites used in the method of the present invention are 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid. One or more selected from the group consisting of acid, xylulose, succinic acid, dopamine, and mannitol. The endogenous metabolite used in the present invention is preferably 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, benzoic acid, isoleucine, elaidic acid, dopamine, or mannitol. In order to carry out the method of the present invention with higher accuracy, 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, It is preferable to measure the amount of endogenous metabolites of elaidic acid, xylrose, succinic acid, dopamine, and mannitol. Here, the endogenous metabolite described in the present specification is a metabolite of a protein existing in the living body or composed in the living body, and means a general term for substances existing in blood or tissue. Examples include, but are not limited to, amino acids, nucleic acids, lipids, vitamins, hormones and the like.

The most preferred embodiment of the method of the present invention is the guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 gene, translocase. of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene, carboxylelesterase- like gene, migration and incubation protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (Table in SEQ ID NO: 4) , And the expression level of A_64_P100513 (gene represented by SEQ ID NO: 5), and 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, To measure the amount of endogenous metabolites of benzoic acid, isoleucine, uracil, elaidic acid, xylulose, succinic acid, dopamine, and mannitol.

As a method for measuring the expression level of the gene in the present invention, a known method for measuring the expression level of the gene in the art can be used, for example, a microarray method, a real-time PCR method, Northern blotting, or EST analysis. , SAGE (gene expression chain analysis) method, and sequencing method using NGS (next generation sequencer) and nanopore sequencer. Further, the data acquired by the measurement by the above method is subjected to gene ID conversion, deletion value processing, global normalization, logarithmic conversion and the like as pretreatment for comparing fluctuations in gene expression level. May be good.

As a method for measuring the amount of the endogenous metabolite in the present invention, a method known in the art for measuring the amount of the endogenous metabolite can be used, for example, gas chromatograph mass spectrometry (GC / MS). ), Liquid chromatograph mass spectrometry (LC / MS), capillary electrophoresis mass spectrometry (CE / MS), ion chromatograph mass spectrometry (IC / MS), supercritical fluid chromatograph mass spectrometry (SFC / MS), and NMR Etc. are included.

In the method of the present invention, following the step (1), (2) the expression level of the gene and / or the amount of the endocrine disrupter measured in the step (1) is analyzed to obtain the chemical substance. A step of determining whether a substance is a factor affecting the endocrine system as an endocrine disruptor or a factor affecting the endocrine system as stress is included.

In the present invention, as a method for analyzing the expression level of the gene and the amount of the endogenous metabolite, after measuring the expression level of the gene and / or the amount of the endogenous metabolite, the measurement data is used. , Machine learning and statistical methods commonly used in the art can be applied. Here, machine learning as used herein is used by a computer system to efficiently perform a particular task without using explicit instructions, but instead relying on patterns and inferences. Algorithms and statistical models are referred to, and statistical methods are methods for quantitatively grasping trends and properties of collected data. Examples of the machine learning and statistical methods include linear regression, logistic regression, support vector machine, neural network, random forest, Lasso (LASSO) regression, ridge (Ridge) regression, elastic net regression, t-test, and ROC curve. , And methods such as analysis of variance (ANOVA) can be used, but are not limited thereto.

The machine learning in the method of the present invention includes a guanine deaminase gene, an interleukin-1 receptor-associated kinase gene, a lysine demethylase 8 gene, a microtubule-associated protein RP / EB family member 3 gene, an oxygensterol binding protein-like 3 gene, and a translocase of outer. mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene, carboxylelesterase-like gene , Migration and incubation protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (represented by SEQ ID NO: 4) Gene), and one or more of the genes selected from the group consisting of A_64_P100513 (gene represented by SEQ ID NO: 5), and / or 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, One or more of the endogenous metabolites selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid, xylrose, succinic acid, dopamine, and mannitol. When used, it is preferably carried out using a support vector machine. According to the method of the present invention, for example, the expression level of the gene and / or the amount of the endocrine metabolite in a subject not in contact with the target chemical substance and a sample collected from the contacted subject were measured. After that, the measured data is analyzed using a support vector machine to determine with high accuracy whether the chemical substance of interest acts directly on the endocrine system of the organism as an endocrine disturbing substance or indirectly as stress. Can be done. The support vector machine used in the method of the present invention may be characterized by a radial basis function kernel (Gaussian kernel).

Machine learning in the methods of the invention is one selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, lassoyl, elaidic acid, xylulose, succinic acid, dopamine, and mannitol. When any more of the endogenous metabolites are used, it is preferably carried out using lasso (LASSO) regression. According to the method of the present invention, for example, the expression level of the gene and / or the amount of the endocrine metabolite in a subject not in contact with the target chemical substance and a sample collected from the contacted subject were measured. Later, the measured data will be analyzed using LASSO regression, and logistic regression analysis will be used to construct the model formula, and whether the chemical substance of interest acts directly on the endocrine system of the organism as an endocrine disruptor. Alternatively, it can be determined with high accuracy whether it acts indirectly as stress.

The discrimination in the step (2) in the present invention uses the data of the amount of the endogenous metabolite measured in the step (1), linear regression, logistic regression, neural network, random forest, Lasso (LASSO) regression, ridge. It can be optimized by machine learning such as (Ridge) regression and elastic net regression, and then can be performed using logistic regression analysis, support vector machine and the like. In the method of the present invention, for example, a coefficient is calculated by Lasso regression, and logistic regression analysis can be used to determine that the chemical substance is a factor affecting the endocrine system as an endocrine disruptor or stress. The coefficient calculated by Lasso regression (corresponding to a in the following formula) is the formula (model formula) used in logistic regression analysis.

[In the equation, a indicates a coefficient calculated by machine learning such as Lasso regression, and x indicates a fluctuation ratio].
Can be applied to determine according to the value of y in the above equation. For example, when the value of y in the above formula is set to 0.5, if it is 0.5 or more, the target chemical substance acts directly as an endocrine disruptor, and if it is 0.5 or less, it indirectly acts as stress. It can be determined that it works.

The method of the present invention can, for example, measure the expression level of the gene and / or the amount of the endogenous metabolite, examine the fluctuation ratio, and then perform statistical methods and / or machine learning.

In another aspect of the invention, the invention is a kit for determining factors that affect an endocrine system in an organism possessed by a chemical, including means for carrying out the methods described herein. Provide a kit. The means used in the kits of the present invention include means for measuring the expression level and / or the amount of endogenous metabolites of the gene. Further, the means used in the kit of the present invention may include means for analyzing measurement data of the expression level of the gene and / or the amount of the endogenous metabolite.

As means for measuring the expression level of the gene used in the kit of the present invention, means generally used in the art, such as microarray, real-time PCR, NGS (next generation sequencer), Northern blotting, EST analysis, SAGE. (Gene expression chain analysis), nanopore sequencing, etc. are mentioned, and a microarray is preferable. Further, as a means for measuring the amount of the endogenous metabolite used in the kit of the present invention, a means generally used among those skilled in the art can be used, for example, a gas chromatograph mass spectrometer, a liquid chromatograph mass. Examples thereof include an analyzer, a capillary electrophoresis mass spectrometer, an ion chromatograph mass spectrometer, a supercritical fluid chromatograph mass spectrometer, and an NMR, and a gas chromatograph mass spectrometer is preferable. As a means for analyzing the measurement data of the expression level of the gene and / or the amount of the endogenous metabolite used in the kit of the present invention, statistical methods and machine learning generally used in the art, for example, , Linear Regression, Logistic Regression, Support Vector Machine, Neural Network, Random Forest, Lasso (LASSO) Regression, Ridge Regression, Elastic Net Regression, t Test, ROC Curve, and Dispersion Analysis (ANOVA) Is included.

In addition to the above means, the kit of the present invention includes various means for carrying out the methods described herein, such as personal computers, wells, containers, trays, kit instruction manuals, and reagents for extracting RNA. A set, a nucleic acid concentration measuring device, a nucleic acid quality checker, a set of endogenous metabolite extraction reagents, a mathematical formula for discrimination, and the like may be included, but the present invention is not limited thereto.

In yet another aspect of the invention, the invention is a method for selecting the gene and / or the endogenous metabolite for determining factors that affect the endocrine system in an organism possessed by a chemical substance. , (1) Steps to measure gene expression and / or endogenous metabolites in samples taken from unstressed and loaded organisms, and (2) endocrine disruptors are in contact. Steps of measuring gene expression and / or endocrine metabolites in samples taken from non-subjects and contacted subjects, followed by (3) obtained in steps (1) and (2) above. Provided is a method comprising the step of analyzing the expression level of a gene and / or the amount of an endocrine metabolite using machine learning and / or statistical techniques and selecting the gene and / or the endocrine metabolite. .. Further, in the method of the present invention, among the gene and the endogenous metabolite selected in the step (3), the gene and the endogenous metabolite selected in the step (3) after the step (1). A step of excluding duplicates of the metabolite with the gene selected in step (3) after step (2) and said endogenous metabolite is further included.

The machine learning and statistical methods used in the method of the present invention may be those generally used in the art, for example, linear regression, logistic regression, support vector machine, neural network, random forest, lasso. (Lasso) regression, Ridge regression, elastic net regression, t-test, ROC curve, analysis of variance (ANOVA), etc., but are not limited thereto. In step (3) of the present invention, the gene is subjected to t-test and support vector machine-recursive feature elimination method (SVM-RFE) based on the expression level obtained in step (2), and the probability is 0. If it is larger than .5, it can be judged that it has a direct action as an endocrine disruptor and can be selected. Further, in the step (3) of the present invention, for the endogenous metabolite, the formula of logistic regression analysis is applied based on the amount obtained in the step (2), and the calculation result is 0.5 or more. Calculate the regression coefficient by Lasso, and if the coefficient is 0 or more, or create an ROC curve, and if the log ₂ ratio of the AUC value is 0 or more, it is judged that it has a direct action as an endocrine disruptor and is selected. be able to.

Hereinafter, the present invention will be described in detail with reference to Examples, but the present invention is not limited thereto.

Example 1
(1) Preparation of model animals (stress loading group / ED substance administration group) using male rats Use male rats (RccHan: Wist system) that will be 9 weeks old at the end of the test so that there will be 8 animals in each group. I made a test design. The number of administration days is 8 days unless otherwise specified. The stress-loaded group includes a 3-hour restraint group, a severe starvation stress group (average feeding 20 g / day 60% feeding), a moderate starvation stress group (average feeding 20 g / day 70% feeding), and stress hormones. Five groups, a corticosterone 50 mg / kg administration group and an adrenergic receptor agonist isoproterenol 1 mg / kg administration group, were prepared together with a control group under each condition. In addition, as the ED substance administration group, 3 mg / kg and 0.6 mg / kg administration group of leuprorelin, which is a gonadotropin-releasing hormone receptor agonist having a testosterone lowering effect, and 25 mg of ketoconazole, which is an oxidative metabolizing enzyme CYP3A4 inhibitor. Four groups, a / kg group and a 12.5 mg / kg administration group, were prepared together with a control group under each condition.

(2) Analysis of serum testosterone concentration and determination of individual for marker extraction The testosterone concentration of serum collected from animals after the test was measured using a liquid chromatograph-mass spectrometer (LC / MS). The top three individuals with low testosterone concentration were selected from the treatment group, and the three animals showing near the median testosterone concentration were selected from the control group and determined as individuals for marker extraction.

(3) Acquisition of data on genes and endogenous metabolites in individual animals (microarray / GC / MS analysis)
A comprehensive gene expression level analysis was performed using RNA extracted from the testis, adrenal gland, thyroid gland, pituitary gland, thymus, and liver of the individual determined above using a microarray (Agilent Technology) (about the number of analysis subjects). The number of detections was about 30,000 for 40,000). In addition, the testis, adrenal gland, thyroid gland, pituitary gland, thymus, liver, and serum metabolites were comprehensively analyzed by GC / MS (TQ-8030, Shimadzu Corporation), and data were obtained (the number of analysis targets was approximately 500). On the other hand, the number of detections was about 200).

(4) Extraction of discriminant marker candidates (each gene and endogenous metabolites)
[Genetic marker]
Genes with large fluctuations in gene expression were ranked by performing a t-test and selecting with a p-value <0.05, and then the genes were narrowed down by a support vector machine-recursive feature elimination method (SVM-RFE).
[Intrinsic metabolite marker]
1) A model was constructed by LASSO, and the regression coefficient for each endogenous metabolite was calculated.
2) An ROC curve was created, and _{endogenous metabolites having a log 2} ratio of AUC value of 0 or 1 were selected. The number of marker candidates in the samples collected from each tissue is shown in Table 1 below.
<Table 1. Number of marker candidates in each tissue>

(5) Implementation of a new animal experiment for the purpose of verifying marker accuracy In order to verify the prediction accuracy of the discrimination marker candidates extracted in Example 1 (4), the point of action is the animal test of Example 1 (1). A novel animal study was conducted in which different compounds were administered. As a stress-bearing group, a single dose of fenfluramine 25 mg / kg, which has an appetite-suppressing effect, was administered, and as an ED substance-administered group, 1000 mg / kg of dibutyl phthalate, which has been reported to inhibit testosterone biosynthesis, was administered for 15 days. Control of each condition was divided into 4 groups, 3 days and 8 days after a single dose of avilateron 50 mg / kg, which is an oxidative metabolizing enzyme CYP17A1 inhibitor, and degarelix 2 mg / kg, which is a gonad stimulating hormone-releasing hormone receptor antagonist. It was set up with the group and animal tests were performed.

(6) Marker verification (identification of marker sets with high prediction rate)
The samples obtained in the test of Example 1 (5) were analyzed in the same manner as in Example 1 (2) and Example 1 (3). Using the obtained gene and endogenous metabolite data, the correct answer rate by the marker candidates extracted in Example 1 (4) was obtained, and the correct answer rate was 80% or more for the gene and 93% or more for the endogenous metabolite. Those were determined as markers for discriminating between direct action by chemical substances and indirect action by stress (FIGS. 1, FIG. 2, and Table 2 below). For genetic markers, high predictive accuracy was confirmed in the liver and pituitary gland (Fig. 1 and Table 2), and for endogenous metabolite markers, high predictive accuracy was confirmed in the thymus and serum (Fig. 2 and Table 2). ..
<Table 2. Prediction rate of stress / ED discrimination marker>

Example 2
Examples for the test compound Serum, thymus, liver, and pituitary gland are collected from animals such as rats to which the test compound has not been administered and animals such as rats to which the test compound has been administered for about 1 week. Endogenous metabolites of serum and thymus are measured with a gas chromatograph mass spectrometer. Gene expression in the liver and pituitary gland is measured on a microarray. Using the gene of the present invention and the endogenous metabolite, the variation data of the administration group when compared with the control group was compared with the variation of the discriminant marker, and the method shown in Example 1 (6) was used. Classify as direct action or indirect action, and determine the factors of endocrine influence of the test compound.

Verification example determined using Lasso and logistic regression analysis RccHan: Wist male rat male not in contact with 3 types of assumed test compounds A, B, and C (corresponding to Examples 1 to 3 in Table 3 below, respectively) Lasso (LASSO) using data of 10 endogenous metabolites (arbitrarily set the fluctuation ratio of the endogenous metabolites) that are assumed to be measured from a sample collected from the serum of the rat male that has been contacted with the lasso. ) The coefficient a was calculated by regression and discriminated as either stress or ED by logistic regression analysis. Specifically, the following formula (logistic regression analysis formula) is used using data (Examples 1 to 3 in Table 3 below) of three types of fluctuation ratios (the fluctuation ratios of the endocrine disrupters are arbitrarily set). Among them, a is the coefficient of each endogenous metabolite marker, x is the fluctuation ratio of the treatment group with respect to the control group, and if y is larger than 0.5, the endocrine disruptor (ED) is better than 0.5. If it was small, it was determined to be stress. The coefficient a was calculated by Lasso regression and classified as stress or ED by logistic regression analysis.

Verification example determined using a support vector machine RccHan: Wist rat male and contact not in contact with 3 types of assumed test compounds A, B, and C (corresponding to Examples 1 to 3 in Table 4 below, respectively) The probability was calculated by applying a support vector machine using data of 8 kinds of genes assumed to be measured from a sample collected from the liver of the rat male (arbitrarily setting the fluctuation ratio of the gene). Determined as either stress or ED. If the probability is greater than 0.5, it is determined to be ED, and if the probability is less than 0.5, it is determined to be stress. Specifically, the R package e1071 is executed using the log2-converted data (Examples 1 to 3 in Table 4 below) of three types of fluctuation ratios (the fluctuation ratios of the genes are arbitrarily set), and radial. A support vector machine of the basis function kernel (Gaussian kernel) was applied to calculate the probability and classify it as stress or ED.

The present invention can be used in fields where it is necessary to identify factors that affect the endocrine system of living organisms, including the fields of pesticides, pharmaceuticals, veterinary medicine, livestock, and the environment. According to the discrimination method of the present invention, chemical substances whose effects on the endocrine system act directly as endocrine disruptors must be excluded, and chemical substances whose effects on the endocrine system act indirectly as stress must be excluded. Can be discriminated at the same time.

Claims

It is a method for discriminating factors that affect the endocrine system in an organism possessed by a chemical substance. (1) Expression of a gene that serves as a marker in a subject to which the chemical substance is not in contact and a sample collected from a subject in contact with the chemical substance. The step of measuring the amount and / or the amount of the endocrine metabolite as a marker, and then (2) analyzing the expression level of the gene and / or the amount of the endocrine metabolite measured in the step (1). A method comprising the step of determining whether the chemical substance is a factor affecting the endocrine system as an endocrine disturbing substance or a factor affecting the endocrine system as stress.
The gene and / or the endogenous metabolite machine-learns and / or the amount of the gene expression and / or the amount of the endogenous metabolite in a sample taken from a subject not in contact with the chemical and a subject in contact with the chemical. Or the method of claim 1, which is selected by applying to a statistical method.
The genes are guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygensterol binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene, carboxylesterase-like gene, migration and inhibition inhibition protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and A_64_P100513 One or more selected from the group consisting of (gene represented by SEQ ID NO: 5), wherein the endogenous metabolites are 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2. One or more selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid, xylrose, succinic acid, dopamine, and mannitol. The method according to 1 or 2.
The genes are from lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygen binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, and A_64_P100513 (gene represented by SEQ ID NO: 5). The endogenous metabolite is selected from the group consisting of 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, benzoic acid, isoleucine, ellaidic acid, dopamine, and mannitol. The method according to any one of claims 1 to 3, wherein the method is one or more.
The method according to any one of claims 1 to 4, wherein the analysis in the step (2) is performed using machine learning and / or a statistical method.
The machine learning and / or statistical method includes linear regression, logistic regression, support vector machine, neural network, random forest, lasso regression, ridge regression, elastic net regression, t-test, ROC curve, etc. The method of claim 5, wherein the method is selected from the group consisting of and variance analysis (ANOVA).
The machine learning is guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygensterol binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene. , A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene, carboxylesterase-like gene, migration and invasion inhibitory protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and One or more genes selected from the group consisting of A_64_P100513 (gene represented by SEQ ID NO: 5) and / or selected from the group consisting of 2-deoxyglucose, 3-hydroxyisobutyric acid, and 4-aminobutyric acid. The method of claim 6, wherein when one or more endogenous metabolites are used, the support vector machine is used and the support vector machine is characterized by a radial basal function kernel. ..
One or more intrinsic factors in which the machine learning is selected from the group consisting of 2-aminoisobutyric acid, 3-hydroxyisobutyric acid, benzoic acid, isoleucine, lassoyl, ellaic acid, xylulose, succinic acid, dopamine, and mannitol. The method according to claim 6, wherein when a sex metabolite is used, Lasso regression is used, and the Lasso regression uses logistic regression analysis to construct a model formula.
The method according to any one of claims 1 to 8, wherein the effect on the endocrine system is characterized by a decrease in testosterone concentration in blood.
6. the method of.
The method of claim 10, wherein the tissue associated with the endocrine system is the thymus or pituitary gland.
The method according to any one of claims 1 to 11, wherein the subject is a mammal or a tissue or cell thereof.
The method of claim 12, wherein the mammal is a human, rat or mouse.
A kit for determining factors that affect the endocrine system in an organism possessed by a chemical substance, and includes means for carrying out the method according to any one of claims 1 to 13.
The means are guanine deaminase gene, interleukin-1 receptor-associated kinase gene, lysine demethylase 8 gene, microtubule-associated protein RP / EB family member 3 gene, oxygensterol binding protein-like 3 gene, translocase of outer mitochondrial membrane 70 gene, A_44_P1058703 (gene represented by SEQ ID NO: 1), A_64_P039501 (gene represented by SEQ ID NO: 2), GA binding protein transcription factor subsystem alpha gene, kelch-like family member 30 gene, carboxylesterase-like gene, migration and inhibition inhibition protein gene, signal-regulatory protein alpha gene, solute carrier family 7 member 7 gene, vomeronasal 1 receptor 77 gene, A_44_P323754 (gene represented by SEQ ID NO: 3), A_64_P032023 (gene represented by SEQ ID NO: 4), and A_64_P100513 The expression level of one or more genes selected from the group consisting of (gene represented by SEQ ID NO: 5), and / or 2-deoxyglucose, 3-hydroxyisobutyric acid, 4-aminobutyric acid, 2-aminoiso. Measure the amount of one or more endogenous metabolites selected from the group consisting of butyric acid, 3-hydroxyisovaleric acid, benzoic acid, isoleucine, uracil, elaidic acid, xylrose, succinic acid, dopamine, and mannitol. The kit according to claim 14, which is a means for the above.
A method for selecting genes and / or endogenous metabolites for determining factors that affect the endocrine system in organisms possessed by chemical substances. (1) Unstressed organisms and loaded organisms. Steps to measure gene expression and / or amount of endogenous metabolites in samples taken from, and (2) genes in samples taken from subjects not in contact with endocrine disruptors and those in contact. The step of measuring the expression level and / or the amount of the endogenous metabolite, (3) the expression level of the gene obtained in the steps (1) and (2), and / or the amount of the endogenous metabolite A step of selecting a gene and / or an endocrine metabolite by analysis using learning and / or statistical methods, and then (4) among the genes and endocrine metabolites selected in the step (3). Exclude duplicates of the gene and endocrine metabolite selected in step (1) and step (3) after step (1) and the gene and endocrine metabolite selected in step (3) after step (2). A method that includes the steps to be performed.