CN115094128A - Method for diagnosing curative effect of antidepressant through intestinal microbial analysis - Google Patents
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Abstract
The invention belongs to the technical field of evaluation of curative effects of depression drugs, in particular to a method for diagnosing curative effects of antidepressants through intestinal microbial analysis, which aims at solving the problem that the curative effects of the existing depression drugs cannot be effectively evaluated after treatment, so that the use of the drugs in the later period is influenced, and provides the following scheme, which comprises the following steps: s1, data acquisition: collecting feces of a plurality of different patients in different time periods after taking the medicine; s2, DNA extraction: performing activity detection on different microorganisms in the excrement and simultaneously performing DNA extraction; s3, PCR specific amplification: the extracted DNA is copied and amplified, and classified placement and storage are carried out; s4, gene sequencing: detecting DNA sequences within a plurality of microorganisms; s5, data analysis: and analyzing the data after DNA sequence detection. The invention can accurately evaluate the anti-depression drug, has low application cost and quick evaluation time, and is convenient for people to use.
Description
Technical Field
The invention relates to the technical field of curative effect evaluation of depression drugs, in particular to a method for diagnosing curative effect of an antidepressant through intestinal microorganism analysis.
Background
Depression is a common disease that causes "negative mood" due to altered brain function that controls mood. Worldwide, more than 1 million people suffer from depression. The essence of depression comes from physiological and anatomical problems, while negative emotions are the result of changes in the human structure. Depression can be classified into mild and severe according to its degree. Mild depression is depression that is diagnosed but has no problems in social activities (e.g., occupational activities, etc.). Major depression is also called "depressive disorder" when various depressive symptoms persist in the mental health system, and "major depression" when various specific symptoms persist for a considerable time.
Serotonin and melatonin are recognized as representative substances causing depression, and several neuro-related hormones such as dopamine and norepinephrine also affect depression. 5-hydroxytryptamine (serotonin) is a neuro-metabolite found in cerebrospinal fluid, circulates throughout the brain and functions as a neurotransmitter. 5-hydroxytryptamine is closely related to expression of emotion, and when this substance is insufficient, emotion becomes unstable, resulting in increased anxiety, anxiety and impulsiveness. In the 1970 s, scientists found that 5-hydroxytryptamine deficiency was closely related to depression. Among the drugs currently used as a therapeutic agent for depression, there are many drugs that can prevent reabsorption of 5-hydroxytryptamine, thereby allowing it to stay in the brain for a longer time.
In addition, the number of symbiotic microorganisms in human body is large, and the gene number of the microorganisms exceeds the gene number of human by hundreds of times. Microbiota (microbiota) includes bacteria, archaea, eukaryotes, etc. present in a given habitat. The intestinal microbiota plays a crucial role in human physiology and has a major impact on human health and disease through interaction with human cells.
Metagenomics can analyze the obtained microbial genome data from collected samples (korean patent publication No. 2011-0073049). Recently, a 16s ribosomal DNA (16srdna) base sequence based method lists bacterial composition of human microbiota and 16srdna base sequence, which is a gene of 16s ribosomal rna, was analyzed using next generation sequencing (ngs) platform.
The existing depression drugs can not effectively evaluate the curative effect of the depression drugs after treatment, so that the later use of the drugs is influenced, and a method for diagnosing the curative effect of the antidepressant drugs through intestinal tract microbiological analysis is provided.
Disclosure of Invention
The invention aims to solve the defect that the curative effect of the existing depression drug cannot be effectively evaluated after treatment, so that the later use of the drug is influenced, and provides a method for diagnosing the curative effect of the antidepressant by intestinal microbial analysis.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis comprising the steps of:
s1, data acquisition: the method comprises the steps of marking anti-depression drugs by an enzyme labeling method, carrying out marking detection by feces, observing the marks after detection, judging whether normal absorption and digestion are carried out or not, continuing flow detection in normal time, carrying out digestive tract inspection treatment in abnormal time, judging the types of intestinal flora in different patients according to the digestion conditions of the drugs, matching different drugs to the patients, collecting the feces of the patients for multiple times, wherein the time is respectively 8 hours, 16 hours and 24 hours, carrying out quick-freezing sterile storage on the collected feces, and controlling the diet of the patients before sampling;
s2, DNA extraction: rapidly extracting microbial DNA from excrement by using an autonomously developed kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: and filtering and purifying data according to the special index identification to obtain an effective microorganism sequence, and comparing the effective microorganism sequence with the established microorganism database. Drawing a trend line of the change of the abundance of the microorganisms in different time periods, and comparing the trend line with the data of the patient before the administration of the medicament in combination with the metabolic rate of the medicament to judge the types of the microorganisms influencing the curative effect of the medicament;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend line of the abundance change of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
Compared with the prior art, the invention has the advantages that:
(1) according to the scheme, the anti-depression drug is marked by an enzyme labeling method, and the detection and marking are carried out through excrement, so that the absorption condition of a patient on the drug can be effectively reflected;
(2) the excrement collection and detection are carried out in different time periods after a plurality of patients take the medicine, so that the effective time of the medicine can be fully reflected, the medicine effect formed by intestinal flora in different patients can be reflected, and the curative effect of the medicine can be reflected through data comparison.
The invention can accurately evaluate the anti-depression drug, has low application cost and quick evaluation time, and is convenient for people to use.
Drawings
FIG. 1 is a schematic flow chart of a method for diagnosing the efficacy of an antidepressant by intestinal microbial analysis in accordance with the present invention;
Detailed Description
The technical solution in this embodiment will be clearly and completely described below with reference to the drawings in this embodiment, and it is obvious that the described embodiment is only a part of the embodiment, but not all of the embodiment.
Example one
Referring to fig. 1, a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis, comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: and filtering and purifying data according to the special index identification to obtain an effective microorganism sequence, and comparing the effective microorganism sequence with the established microorganism database. And (4) drawing microbial abundance change trend lines in different time periods, and comparing the trend lines with the data before the medicine is taken by the patient in combination with the medicine metabolism rate to judge the microbial species influencing the curative effect of the medicine. Thereby predicting the state of the patient after taking the medicine;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
In this example, in S1, the patient stools were collected for a plurality of times, which were 8 hours, 16 hours and 24 hours, respectively.
In this embodiment, in S1, the collected feces are stored in a quick-frozen sterile manner, and the diet of the patient is controlled before sampling.
In this example, in S2, the DNA of the microorganism was rapidly extracted from the feces by using a self-developed kit.
In this embodiment, in S3, a specific primer is designed for a microorganism, and a marker index is added to amplify an enriched microorganism gene fragment, so as to construct a microorganism gene set.
In this example, in S1, the antidepressant is labeled by an enzyme labeling method, and the label is detected by feces.
In this embodiment, the detected mark is observed, and whether normal absorption and digestion are performed is judged, the flow detection is continued in a normal case, the digestive tract examination and treatment are performed in an abnormal case, and the types of intestinal flora in different patients are judged according to the digestion conditions of the drugs, so that different drugs are prepared for the patients.
In this embodiment, in S5, the effective microbial sequence is obtained by filtering and purifying data according to the specific index identifier, and the effective microbial sequence is compared with the established microbial database. And (3) drawing a trend line of the change of the abundance of the microorganisms in different time periods, comparing the trend line with the data before the administration of the medicament by combining the metabolic rate of the medicament and the data before the administration of the medicament by a patient, judging the types of the microorganisms which influence the curative effect of the medicament, and finally giving a comparison conclusion.
Example two
Referring to fig. 1, a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis, comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: and filtering and purifying data according to the special index identification to obtain an effective microorganism sequence, and comparing the effective microorganism sequence with the established microorganism database. And (4) drawing microbial abundance change trend lines in different time periods, and comparing the trend lines with the data before the medicine is taken by the patient in combination with the medicine metabolism rate to judge the microbial species influencing the curative effect of the medicine. Thereby predicting the state of the patient after taking the medicine;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
In this embodiment, the stools of the patient in S1 are collected for a plurality of times, wherein the times are respectively 8 hours, 16 hours and 24 hours, and the times can reflect the action time of the drug through different time periods.
In this embodiment, the feces collected in S1 are frozen and aseptically stored, and the diet of the patient is controlled before sampling, thereby preventing the influence of external factors on the drug effect.
In this embodiment, in the DNA extraction in S2, the DNA of the microorganism is rapidly extracted from the stool by a self-developed kit.
In this embodiment, in S3, a specific primer is designed for a microorganism, and a marker index is added to amplify an enriched microorganism gene fragment, so as to construct a microorganism gene set.
In this embodiment, in S5, the effective microbial sequence is obtained by filtering and purifying data according to the special index identifier, and the established microbial database is aligned. And (3) drawing a trend line of the change of the abundance of the microorganisms in different time periods, comparing the trend line with the data before the administration of the medicament by combining the metabolic rate of the medicament and the data before the administration of the medicament by a patient, judging the types of the microorganisms which influence the curative effect of the medicament, and finally giving a comparison conclusion.
EXAMPLE III
Referring to fig. 1, a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis, comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: and filtering and purifying data according to the special index identification to obtain an effective microorganism sequence, and comparing the effective microorganism sequence with the established microorganism database. And (4) drawing a trend line of the change of the abundance of the microorganisms in different time periods, and comparing the trend line with the data before the administration of the medicament by combining the metabolism rate of the medicament and the data before the administration of the patient to judge the types of the microorganisms influencing the curative effect of the medicament. Thereby predicting the state of the patient after taking the medicine;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
In this embodiment, the stools of the patient in S1 are collected for a plurality of times, respectively 8 hours, 16 hours and 24 hours, and the time period can reflect the action time of the drug.
In this embodiment, the feces collected in S1 are frozen and aseptically stored, and the diet of the patient is controlled before sampling, thereby preventing the influence of external factors on the drug effect.
In this example, the DNA extraction in S2 is performed by using a self-developed kit to rapidly extract microbial DNA from feces.
In this embodiment, in S3, a specific primer is designed for a microorganism, and a marker index is added to amplify an enriched microorganism gene fragment, so as to construct a microorganism gene set.
In this embodiment, in S5, the effective microbial sequence is obtained by filtering and purifying data according to the specific index identifier, and the effective microbial sequence is compared with the established microbial database. And (3) drawing a trend line of the change of the abundance of the microorganisms in different time periods, comparing the trend line with the data before the administration of the medicament by combining the metabolic rate of the medicament and the data before the administration of the medicament by a patient, judging the types of the microorganisms which influence the curative effect of the medicament, and finally giving a comparison conclusion.
Example four
Referring to fig. 1, a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis, comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: according to the special index identification, filtering and purifying data to obtain an effective microorganism sequence, comparing an established microorganism database, drawing a microorganism abundance change trend line in different time periods, and comparing the microorganism abundance change trend line with data before the medicine is taken by a patient in combination with the medicine metabolic rate to judge the microorganism types influencing the curative effect of the medicine, so that the state of the patient after the medicine is taken is predicted;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
In this embodiment, the stools of the patient in S1 are collected for a plurality of times, respectively 8 hours, 16 hours and 24 hours, and the time period can reflect the action time of the drug.
In this embodiment, the feces collected in S1 are frozen and aseptically stored, and the diet of the patient is controlled before sampling, thereby preventing the influence of external factors on the drug effect.
In this example, the DNA extraction in S2 is performed by using a self-developed kit to rapidly extract microbial DNA from feces.
In this embodiment, in S3, a specific primer is designed for a microorganism, and a marker index is added to amplify an enriched microorganism gene fragment, so as to construct a microorganism gene set.
In this embodiment, in S5, the effective microbial sequence is obtained by filtering and purifying data according to the special index identifier, and the established microbial database is aligned. And (3) drawing a trend line of the change of the abundance of the microorganisms in different time periods, comparing the trend line with the data before the administration of the medicament by combining the metabolic rate of the medicament and the data before the administration of the medicament by a patient, judging the types of the microorganisms which influence the curative effect of the medicament, and finally giving a comparison conclusion.
EXAMPLE five
Referring to fig. 1, a method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis, comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: filtering and purifying data according to a special index identification to obtain an effective microorganism sequence, comparing an established microorganism database, drawing a microorganism abundance change trend line in different time periods, and comparing with data before a patient takes the medicine in combination with the medicine metabolism rate to judge the types of microorganisms affecting the curative effect of the medicine, thereby predicting the state of the patient after taking the medicine;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
In this embodiment, the stools of the patient in S1 are collected for a plurality of times, respectively 8 hours, 16 hours and 24 hours, and the time period can reflect the action time of the drug.
In this embodiment, the feces collected in S1 are frozen and aseptically stored, and the diet of the patient is controlled before sampling, thereby preventing the influence of external factors on the drug effect.
In this embodiment, in the DNA extraction in S2, the DNA of the microorganism is rapidly extracted from the stool by a self-developed kit.
In this embodiment, in S3, a specific primer is designed for a microorganism, and a marker index is added to amplify an enriched microorganism gene fragment, so as to construct a microorganism gene set.
In this embodiment, in S5, the effective microbial sequence is obtained by filtering and purifying data according to the specific index identifier, and the effective microbial sequence is compared with the established microbial database. And (3) drawing a trend line of the change of the abundance of the microorganisms in different time periods, comparing the trend line with the data before the administration of the medicament by combining the metabolic rate of the medicament and the data before the administration of the medicament by a patient, judging the types of the microorganisms which influence the curative effect of the medicament, and finally giving a comparison conclusion.
The method for diagnosing the curative effect of the antidepressant through the intestinal microbial analysis in the first to fifth embodiments is tested, and the test result is as follows:
| detailed description of the preferred embodiments | Index abundance | Evaluating drug metabolism efficiency |
| Example one | 96％ | 99％ |
| Example two | 46％ | 60％ |
| EXAMPLE III | 64％ | 82％ |
| Example four | 58％ | 74％ |
| ExamplesFive are | 89％ | 91％ |
Therefore, the more the content of the marked microorganisms is, the better the curative effect of the medicine is. The first embodiment is the best method of this evaluation method.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention in the technical scope of the present invention.
Claims (8)
1. A method for diagnosing the efficacy of an antidepressant by intestinal microbial analysis comprising the steps of:
s1, data acquisition: collecting the feces of the patient in different time periods after the drug treatment;
s2, DNA extraction: rapidly extracting microbial genome DNA in excrement by adopting an autonomous research and development kit;
s3, PCR specific amplification: designing a specific primer aiming at the microorganism, adding a mark index to amplify and enrich a microorganism gene segment, and constructing a microorganism gene set;
s4, gene sequencing: carrying out micro-macro genome sequencing on the constructed microbial gene set;
s5, data analysis: filtering and purifying data according to the special index identification to obtain an effective microorganism sequence, and comparing the effective microorganism sequence with the established microorganism database;
s6, drug effect observation: detecting the drug metabolism rate by an enzyme labeling method;
s7, result prediction: and (4) drawing the trend lines of the abundance changes of the microorganisms in different time periods, and judging the types of the microorganisms influencing the curative effect of the medicament by combining the metabolism rate of the medicament.
2. The method of claim 1, wherein in step S1, the patient' S stool is collected for a plurality of time periods, each of 8 hours, 16 hours and 24 hours.
3. The method for diagnosing the curative effect of an antidepressant through intestinal microbial analysis as claimed in claim 1, wherein in said S1, the collected stools are frozen and aseptically preserved, and the diet of the patient is controlled before sampling.
4. The method for diagnosing the curative effect of antidepressant drugs by intestinal microbiological analysis as claimed in claim 1, wherein in S3, the microbial genomic DNA and the designed index-labeled primer are extracted rapidly to enrich the specific microbial gene sequence.
5. The method for diagnosing the efficacy of an antidepressant by intestinal microbiological analysis as claimed in claim 1, wherein in S1, the microorganisms and their contents are identified by micro-macro-genomic technique.
6. The method of claim 5, wherein the detected drugs are observed to determine whether they are normally absorbed and digested, the procedure is continued when they are normal, the digestive tract is examined and treated when they are abnormal, and the type of intestinal flora in different patients is determined by the digestion of the drugs, so that different drugs can be formulated to the patients.
7. The method for diagnosing the curative effect of antidepressant drug by intestinal microbial analysis of claim 1, wherein in said S2, the DNA extraction is performed by a self-developed kit to rapidly extract the DNA in the stool.
8. The method of claim 1, wherein in S5, the sequence data of the microbes are identified and classified, and compared with the data of the patients before administration, and finally the comparison result is given.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110157793A (en) * | 2019-04-29 | 2019-08-23 | 广州海思医疗科技有限公司 | For detecting the kit and method of depressed individuals medication related gene |
| WO2019205188A1 (en) * | 2018-04-24 | 2019-10-31 | 深圳华大生命科学研究院 | Biomarker for depression and use thereof |
| US20200192889A1 (en) * | 2017-08-16 | 2020-06-18 | GenoRx Co.,Ltd | A method of building gut microbiota database and a detection system of gut microbiota |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200192889A1 (en) * | 2017-08-16 | 2020-06-18 | GenoRx Co.,Ltd | A method of building gut microbiota database and a detection system of gut microbiota |
| WO2019205188A1 (en) * | 2018-04-24 | 2019-10-31 | 深圳华大生命科学研究院 | Biomarker for depression and use thereof |
| CN110157793A (en) * | 2019-04-29 | 2019-08-23 | 广州海思医疗科技有限公司 | For detecting the kit and method of depressed individuals medication related gene |
Non-Patent Citations (5)
| Title |
|---|
| WEIJIE ZHANG等: "Antidepressants fluoxetine and amitriptyline induce alterations in intestinal microbiota and gut microbiome function in rats exposed to chronic unpredictable mild stress", 《 TRANSLATIONAL PSYCHIATRY》, vol. 11, 18 February 2021 (2021-02-18), pages 131 * |
| YASMINA AIT CHAIT等: "Unravelling the antimicrobial action of antidepressants on gut commensal microbes", 《SCIENTIFIC REPORTS》, vol. 10, 21 October 2020 (2020-10-21), pages 17878 * |
| 漆靖;蔡溢;肖剑英;孙李晴;: "抑郁症患者肠道菌群研究", 中国微生态学杂志, no. 09, 15 September 2018 (2018-09-15), pages 1 - 057 * |
| 袁霞红等: "肠道菌群调节抑郁症机制及中医药防治研究进展", 《中华中医药学刊》, vol. 40, no. 09, 8 March 2022 (2022-03-08), pages 167 - 170 * |
| 韩光顺;李雪斌;: "肠道微生物与抑郁症的关系研究进展", 右江医学, no. 05, 28 May 2020 (2020-05-28), pages 321 - 325 * |
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