Method for revealing relationship among intestinal microorganisms, cerebrospinal fluid and major depressive disorder

Abstract

The invention discloses a method for revealing the relation between intestinal microorganisms, cerebrospinal fluid and major depressive disorder, and relates to the technical field of major depressive disorder. Comprising the following steps: step 1, constructing an intermediary Mendel randomization hypothesis; comprising an association hypothesis, an independence hypothesis and an exclusiveness hypothesis; the selected genetic variation is used as a tool variable IV; 2, acquiring whole-genome association research data related to the severe depressive disorder; the whole-genome association research data is obtained from a public database of an international epidemiology and genetics alliance. According to the invention, four intestinal microbe phenotypes are determined as MDD protection factors, 30 cerebrospinal fluid metabolites and MDD have a significant causal relationship, and 12 cerebrospinal fluids and MDD have positive correlation (ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt, ORgt and ORgt; 1) is a risk factor of MDD; the other 18 cerebrospinal fluid metabolites are MDD protection factors (ORlt; 1).

Description

Technical Field

[0001] The present invention relates to the technical field of major depressive disorder, and in particular to a method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder. Background Art

[0002] In recent years, depression has become one of the most common mental health disorders worldwide, and its pathogenesis is complex and has not yet been fully elucidated. With the in-depth study of microbiome, metabolomics and genetics, more and more evidence shows that there is a close relationship between intestinal microbiota, metabolite changes in cerebrospinal fluid (CSF) and depression.

[0003] Major depressive disorder (MDD) is a complex and diverse disease that involves interactions at multiple levels, including genetic susceptibility, environmental factors, neurobiological mechanisms, and psychosocial factors. These factors are intertwined and work together to affect the disease. Its clinical manifestations are extensive, not only limited to emotional depression, such as loss of happiness and abnormal reward mechanisms, but also profoundly affect the individual's motivation, cognitive ability, and even physiological balance, accompanied by subtle adjustments in memory patterns. Globally, this disease has a wide range of impacts, affecting the mental health of about 350 million people, with a lifetime prevalence of 10.8%, making it one of the most common mental health problems and an important factor leading to disability.

[0004] In recent years, the frontiers of scientific research have gradually revealed a subtle yet profound relationship between intestinal microbial communities and mental health. Although the specific role of microbial imbalance in the pathological process of depression is not yet fully understood, this discovery has undoubtedly opened up a new perspective for exploring innovative treatment approaches. The intestinal microbiome and its metabolites have shown a dual effect in the pathogenesis of depression. They may accelerate the progression of the disease and indicate potential opportunities for intervention. Therefore, in-depth exploration of the mechanism of microbial imbalance will not only deepen our understanding of the biological basis of depression, but also bring hope to the development of targeted therapies and precise regulation of microbial communities to alleviate depressive symptoms. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder, comprising the following steps:

[0008] Step 1: Construct the mediation Mendelian randomization hypothesis; including the association hypothesis, independence hypothesis and exclusivity hypothesis; the selected genetic variation is used as the instrumental variable IV;

[0009] Step 2: Obtain whole-genome association study data related to major depressive disorder; the whole-genome association study data were obtained from the public database of the International Epidemiology and Genetics Consortium, specifically including 59,851 patients diagnosed with major depressive disorder and 113,154 healthy controls;

[0010] Step 3: Obtain whole-genome association study data of intestinal microbes; the whole-genome association study data were obtained from the MiBioGen consortium, including 18,340 individuals from 24 cohorts, targeting the variable regions V4, V3-V4, and V1-V2 of the 16S rRNA gene to analyze the microbial composition and classify using direct classification sorting;

[0011] Step 4: Obtain genome-wide association study data for CSF metabolites from a subset of participants in the Wisconsin Alzheimer's Disease Research Center and the Wisconsin Alzheimer's Disease Prevention Registry study; CSF samples were collected by lumbar puncture;

[0012] Step 5: Instrumental variable IV selection: In the mediated Mendelian randomization analysis, single nucleotide polymorphisms that are closely related to IV exposure are used;

[0013] Step 6: Statistical analysis: Use the MRPRESSO and TwoSampleMR packages in R software to perform data analysis tasks.

[0014] Preferably: in step 1, there is a correlation between the genetic variation and the exposure factor, the genetic variation and the potential confounding factors are independent of each other, and the genetic variation affects the outcome only through the exposure factor.

[0015] Furthermore: the diagnosis process of major depressive disorder in step 2 strictly follows standardized procedures, integrating structured clinical interviews, detailed electronic medical records and clinical diagnosis by professional physicians.

[0016] As a preferred embodiment of the present invention: in the step three, quantitative trait loci analysis is performed on the microbiome to identify host genetic variations located at genetic loci associated with the abundance level of bacterial taxa in the intestinal microbiome.

[0017] Based on the above scheme: the cerebrospinal fluid samples in step 4 include 689 types, of which 532 are from participants of the Wisconsin Alzheimer's Disease Research Center and 168 are from participants of the Wisconsin Alzheimer's Disease Prevention Registry.

[0018] Preferably: the selection criteria for participants of the cerebrospinal fluid sample of the Wisconsin Alzheimer's Disease Research Center are as follows: age greater than or equal to 45 years old, with decision-making ability, and fasting for 12 hours.

[0019] Furthermore: in step 5, a genome-wide significance threshold of P<1×10-5 is used to screen single nucleotide polymorphisms.

[0020] On the basis of the above scheme: in step six, the inverse variance weighted method is used to evaluate the potential causal relationship between exposure and outcome, and sensitivity analysis is implemented to enhance the robustness of the results. The sensitivity analysis specifically includes MR-Egger analysis, Mendelian randomization pleiotropic residuals and outlier detection.

[0021] As a preferred embodiment of the present invention: the MR-Egger analysis is used to evaluate the pleiotropy of instrumental variables; the outlier detection identifies horizontal pleiotropy through comprehensive detection, and when outliers are detected, corrects potential pleiotropy problems by eliminating outliers.

[0022] Preferably: in step 6, the Cochran Q test is used to evaluate heterogeneity, and a P value less than 0.05 indicates the presence of heterogeneity; an inverse variance weighted random effects model is used to estimate the causal effect; if no heterogeneity exists, an inverse variance weighted fixed effects model is used as the result of the inverse variance weighted method.

[0023] The beneficial effects of the present invention are:

[0024] The method of showing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder identified four intestinal microbial phenotypes as protective factors for MDD. A total of 30 cerebrospinal fluid metabolites were found to have a significant causal relationship with MDD, of which 12 cerebrospinal fluid metabolites were positively correlated with MDD (OR>1) and were risk factors for MDD; another 18 cerebrospinal fluid metabolites were protective factors for MDD (OR<1); mediation MR analysis showed that specific classification

[0025] class.Mollicutes.id.3920 and phylum.Tenericutes.id.3919 at the phylum level played a significant protective role against MDD by regulating the metabolic level of Methylmalonate (mma). BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The forest diagram of the causal effects of the five intestinal microbial phenotypes on MDD of the present invention;

[0027] Figure 2 The scatter points of Mr analysis of the present invention Figure 1 ;

[0028] Figure 3 The forest diagram of the causal effect of cerebrospinal fluid metabolite levels on MDD of the present invention;

[0029] Figure 4 A forest diagram showing the causal effect of intestinal microbial phenotype on cerebrospinal fluid metabolite levels according to the present invention;

[0030] Figure 5 The scatter points of Mr analysis of the present invention Figure 2 ;

[0031] Figure 6 The scatter points of Mr analysis of the present invention Figure 3 ;

[0032] Figure 7 Schematic diagram of Mr analysis according to the present invention.

[0033] Figure 2 middle:

[0034] (A) Causal effect of class, Mollicutes.id.3920 on MDD;

[0035] (B) Causal effect of the genus, Alistipes.id.968 on MDD;

[0036] (C) Causal effect of the genus, Phascolarctobacterium.id.2168 on MDD;

[0037] (D) causal effect of order, Clostridiales.id.1863 on MDD;

[0038] (E) Causal effect of gate, Tenericutes.id.3919 on MDD;

[0039] Figure 5 middle:

[0040] (A) Causal effect of class, Mollicutes.id.3920 on methylmalonate (MMA) levels;

[0041] (B) Causal effect of class, Mollicutes.id.3920 on p -cresol sulfate levels;

[0042] (C) Causal effect of the genus, Alistipes.id.968, on 3-methyl-2-hydroxybutyrate levels;

[0043] (D) Causal effect of the genus, Phascolarctobacterium.id.2168 on -ketoglutarate levels;

[0044] (E) Causal effect of the genus, Phascolarctobacterium.id.2168 on n1-methylinosine levels;

[0045] (F) The causal effect of order, triangle line (n ' -methylnicotinamide) levels of Clostridiales.id.1863;

[0046] (G) The causal effect of order, Clostridiales.id.1863 at the level of X-24952;

[0047] (H) Causal effect of Phylum. Tenericutes.id.3919 on methylmalonate (MMA) levels;

[0048] (I) causal effect of the phylum, Tenericutes.id.3919 on p -cresol sulfate levels;

[0049] Figure 6 middle:

[0050] (A) The causal impact of 3-methyl-2-hydroxybutyrate levels on MDD.

[0051] (B) The causal impact of alpha-ketoglutarate levels on MDD;

[0052] (C) The causal impact of methylmalonic acid (MMA) levels on MDD;

[0053] (D) The causal impact of n1-methylglycan levels on MDD;

[0054] (E) Causal effect of p-cresol sulfate levels on MDD;

[0055] (F) Trigonal alkali (n ' -methylnicotinic acid) levels on MDD;

[0056] (G) Causal impact of sulfate levels on MDD by X-24952. DETAILED DESCRIPTION

[0057] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0058] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0059] A method to reveal the relationship between gut microbiota, cerebrospinal fluid and major depressive disorder, such as Figures 1 to 7 As shown, the following steps are included:

[0060] Step 1: Construct an intermediate Mendelian randomization (MR) hypothesis, including the association hypothesis, that there is a correlation between the selected genetic variants and the exposure factors, and the selected genetic variants serve as instrumental variables IV; the independence hypothesis, that the genetic variants are independent of potential confounding factors; and the exclusivity hypothesis, that the genetic variants affect the outcomes only through the exposure factors.

[0061] Step 2: Obtain the genome-wide association study (GWAS) data related to major depressive disorder (MDD); the GWAS data was obtained from the public database of the International Epidemiology and Genetics Union (IEU). The data set was carefully constructed by outstanding researchers such as Naomi R. Wray and covers a large sample size, including 59,851 patients diagnosed with major depressive disorder and 113,154 healthy controls.

[0062] The diagnosis process of MDD strictly follows standardized procedures, integrating structured clinical interviews, detailed electronic medical records and clinical diagnosis of professional physicians to ensure the high accuracy and reliability of the data.

[0063] Detailed information on the dataset and analysis methods can be obtained through a dedicated link at the following URL: https: / / gwas.mrcieu.ac.uk / datasets / ieu-a-1188 / .

[0064] Step 3: Obtain genome-wide association study (GWAS) data of intestinal microorganisms; the GWAS data were obtained from the MiBioGen Consortium, specifically including 18,340 individuals from 24 cohorts, most of whom were of European ancestry (n = 13,266), targeting the variable regions V4, V3-V4, and V1-V2 of the 16S rRNA gene to analyze the microbial composition and classify using direct classification sorting, and performing quantitative trait loci (mbQTL) mapping analysis on the microbiome to identify host genetic variations mapped to genetic loci associated with the abundance levels of bacterial taxa in the intestinal microbiota.

[0065] During the above research process, a total of 211 taxa were generated: 131 genera, 35 families, 20 orders, 16 classes and 9 phyla, including 12 unknown genera; the website of the MiBioGen Alliance is: https: / / mibiogen.gcc.rug.nl / .

[0066] Step 4: Obtain genome-wide association study (GWAS) data of cerebrospinal fluid (CSF) metabolites; the GWAS data come from the GWAS summary dataset focusing on CSF metabolites, which is obtained from a subset of participants in the Wisconsin Alzheimer's Disease Research Center (WADRC) and the Wisconsin Alzheimer's Prevention Registry (WRAP) studies.

[0067] The above summary dataset collected CSF samples via lumbar punctures (LPs); 689 CSF samples were included, of which 532 were from participants in WADRC and 168 were from participants in WRAP; the collection and storage protocols of the above CSF samples were consistent in both studies.

[0068] The selection criteria for participants in the WADRC CSF sample were as follows: age ≥45 years, decision-making capacity, and fasting for 12 hours; exclusion criteria included a history of specific diseases, such as renal dysfunction, congestive heart failure, major neurological diseases (excluding dementia), etc.

[0069] The above study was part of the Generations of WRAP (GROW) study and was approved by the University of Wisconsin Health Sciences Institutional Review Board; the GWAS summary dataset focusing on CSF metabolites is available at:

[0070] https: / / gwas.mrcieu.ac.uk.

[0071] Step 5: Instrumental variable IV selection; In the mediated Mendelian randomization (MR) analysis, single nucleotide polymorphisms (SNPs) closely related to IV exposure were used; recent studies have shown that if a genome-wide significance threshold of P < 5 × 10-8 is used, the number of SNPs significantly associated with intestinal microbial phenotypes and CSF metabolite levels is relatively limited. Referring to previous studies, a genome-wide significance threshold of P < 1 × 10-5 was used to screen SNPs; linkage disequilibrium was eliminated within a genetic distance of kb = 10,000 (correlation coefficient r2 was less than 0.001) to ensure SNP independence.

[0072] In the reverse MR analysis, SNPs were selected from the MDD summary data, and the significance threshold of P < 1 × 10-5 and the same processing method (kb = 10,000, r2 less than 0.001) were used to eliminate linkage disequilibrium.

[0073] Palindromic SNPs have the same alleles on the forward and reverse strands, and this characteristic leads to uncertainty in the judgment of the effect allele strand and is therefore excluded; among each SNP that meets the established criteria, the SNP with an F statistic less than 10 is considered a weak IV, reflecting a relatively weak association between genetic variation and exposure factors and is therefore eliminated.

[0074] Step 6: Statistical analysis; data analysis tasks were performed using the MRPRESSO (version 1.0) and TwoSampleMR (version 0.6.4) packages in R software (version 4.4.0); the inverse variance weighted (IVW) method was used to evaluate the potential causal relationship between exposure and outcome, and sensitivity analysis was performed to enhance the robustness of the results. The sensitivity analysis specifically included MR-Egger analysis and Mendelian randomization pleiotropic residuals and outlier detection (MR-PRESSO). The above methods were based on different horizontal pleiotropic assumptions.

[0075] MR-Egger analysis is used to assess the pleiotropic effects of instrumental variables, and a non-zero intercept may mean that the IVW estimate is subject to some degree of bias.

[0076] MR-PRESSO identifies horizontal pleiotropy through comprehensive testing and corrects potential pleiotropy problems by removing outliers when they are detected.

[0077] A “leave-one-out” approach was also used to exclude outlier SNPs to prevent a single SNP from having an undue influence on the causal relationship between exposure and outcome.

[0078] Cochran Q test was used to assess heterogeneity, and a P value less than 0.05 indicated the presence of heterogeneity. The inverse variance weighted (IVW) random effects model was used to estimate the causal effect. If no heterogeneity existed, the inverse variance weighted (IVW) fixed effects model was used as the result of the inverse variance weighted (IVW) method.

[0079] This study strictly followed the guidelines in the STROBE-MR statement, the GWAS summary-level data used were publicly accessible, and all subjects participating in a single study obtained written informed consent from the ethics committee of their institutional review board.

[0080] Since this study involved only a secondary analysis of previously published data, no additional ethical approval was sought. There was no sample overlap in this study, as the samples of MDD, gut microbiota, and CSF metabolites were obtained from different research consortia.

[0081] Visualize your analysis with forest, funnel, scatter, and leave-one-out plots.

[0082] The specific results are as follows;

[0083] (1) Exploring the causal effect of gut microbial phenotype on MDD

[0084] According to the established significance threshold standard, IVs were screened and adopted, and their F statistics were all over 10, which strongly indicated that the influence of weak instrumental variable bias was not significant. The IVW method was mainly used to perform MR analysis, and a two-sample MR analysis was further conducted to explore the potential association between intestinal microbial phenotype and major depressive disorder (MDD), and heterogeneity and pleiotropy tests were implemented. The research results are as follows Figure 1 and Figure 2 As shown, a significant causal relationship was confirmed between the five intestinal microbial phenotypes and MDD (P<0.05).

[0085] Four phenotypes were protective against MDD, including:

[0086] phylum.Tenericutes.id.3919 (OR=0.92, 95% CI: 0.86-0.99, P=0.02);

[0087] class.Mollicutes.id.3920 (OR=0.92, 95% CI: 0.86-0.99, P=0.02);

[0088] genus.Phascolarctobacterium.id.2168

[0089] (OR=0.92, 95% CI: 0.85-1.00, P=0.04);

[0090] order.Clostridiales.id.1863 (OR=0.91, 95% CI: 0.82-1.00, P=0.04).

[0091] genus.Alistipes.id.968 (OR=1.10, 95%CI: 1.00-1.22, P=0.045) was considered as a risk factor for MDD.

[0092] Neither MR-Egger nor MR-PRESSO analysis found evidence of heterogeneity and horizontal pleiotropy (P value>0.05), further verifying the robustness and reliability of the analysis results.

[0093] (2) Exploring the causal relationship between MDD and gut microbial phenotype

[0094] In order to meet the requirements of mediation MR studies, we further used MDD as the exposure and the above five gut microbial phenotypes as the outcomes, and performed a reverse MR analysis with IVW as the main method. No matching SNPs were found during the reverse MR study. No SNPs matching MDD and gut microbial phenotypes were found during the reverse Mendelian randomization analysis, which may be due to data limitations, insufficient statistical power, or the influence of specific biological mechanisms.

[0095] The main MR analysis results showed a potential causal relationship between gut microbiota and MDD, a conclusion supported by the consistent results of multiple MR methods; based on current research results and biological knowledge, it is believed that the impact of gut microbiota on MDD may be unidirectional.

[0096] (3) Exploring the causal impact of CSF metabolite levels on MDD

[0097] Two-sample Mendelian randomization (MR) analysis was performed with cerebrospinal fluid (CSF) metabolite levels as exposure factors and major depressive disorder (MDD) as study outcomes, and inverse variance weighting (IVW) as the main analysis method.

[0098] Based on the significance threshold of P < 0.05, Figure 3 As shown, the study revealed a clear causal relationship between 30 CSF metabolites and MDD; among them, 12 CSF metabolites were positively correlated with MDD (OR>1) and were considered as potential risk factors for MDD; the other 18 CSF metabolites were negatively correlated with MDD (OR<1), showing a protective effect against MDD.

[0099] (4) Exploring the causal impact of gut microbial phenotype on CSF metabolite levels

[0100] After confirming the causal relationship between gut microbial phenotype and CSF metabolite levels and MDD, a two-sample MR analysis was performed, using IVW as the main analysis method to explore in detail the potential associations between five gut microorganisms and 30 CSF metabolites.

[0101] The results are as follows Figure 4 As shown:

[0102] class.Mollicutes.id.3920 was positively correlated with Methylmalonate (mma) levels (OR=1.23, 95%CI: 1.02-1.47, p=0.025), and negatively correlated with P-cresol sulfate levels (OR=0.73, 95%CI: 0.56-0.95, p=0.021);

[0103] genus.Alistipes.id.968 was negatively correlated with 3-methyl-2-oxobutyrate levels (OR=0.91, 95%CI: 0.84-0.99, p=0.024);

[0104] genus.Phascolarctobacterium.id.2168 was negatively correlated with Alpha-ketoglutarate levels (OR0.90, 95%CI0.82to0.99, andp=0.04) and N1-methylinosine levels (OR0.88, 95%CI0.79to0.97, andp=0.014);

[0105] order.Clostridiales.id.1863 was positively correlated with Trigonelline (n'-methylnicotinate) levels (OR1.51, 95%CI1.05to2.18, andp=0.027) and X-24952 levels (OR1.21, 95%CI1.02to1.43, andp=0.025);

[0106] phylum.Tenericutes.id.3919 and Methylmalonate(mma)

[0107] It was positively correlated with cresol sulfate levels (OR 1.23, 95% CI 1.03 to 1.47, and p = 0.025) and negatively correlated with P-cresol sulfate levels (OR 0.73, 95% CI 0.56 to 0.95, and p = 0.021).

[0108] Both MR-Egger and MR-PRESSO analyses showed that there was no horizontal pleiotropy (P values ​​were greater than 0.05), thus verifying the robustness of the above results.

[0109] MR analysis was performed on the relationship between the levels of seven cerebrospinal fluid metabolites and MDD. Figure 6As shown; five metabolites showed a protective effect against MDD, namely: Methylmalonate (mma) levels, P-cresol sulfate levels, Alpha-ketoglutarate levels, N1-methylinosine levels, and X-24952 levels; the other two metabolites, namely 3-methyl-2-oxobutyrate levels and Trigonelline (n'-methylnicotinate) levels, were identified as risk factors for MDD.

[0110] MR-Egger and MR-PRESSO analyses also confirmed that these results were not affected by horizontal pleiotropy (all P values>0.05). Figure 5 and Figure 6 shown.

[0111] (5) CSF metabolite levels mediate the association between gut microbiota and MDD

[0112] The results of mediation multivariate regression analysis (MR) were systematically summarized and key mediating variables were precisely identified; Figure 7 Intuitively display the process framework of mediation MR analysis.

[0113] class.Mollicutes.id.3920 Methylmalonic acid (MMA)

[0114] Methylmalonate (mma) levels showed a significant promoting effect (β=0.207, P=0.025), while MMA levels were confirmed to be a protective factor for major depressive disorder (MDD) (β=-0.014, P=0.0095).

[0115] Further analysis showed that class.Mollicutes.id.3920 itself was also a protective factor for MDD (β=-0.081, P=0.020). It indirectly exerted a protective effect on MDD by improving the level of MMA. The mediating effect size was -0.003, accounting for 3.64% of the total effect, and the direct effect was -0.078.

[0116] It can be inferred that class.Mollicutes.id.3920 enhances the defense mechanism against MDD by increasing the level of MMA.

[0117] order.Clostridiales.id.1863 was found to have a positive regulatory effect on the level of the unknown metabolite X-24952 (β=0.191, P=0.025), which was also identified as a protective factor for MDD (β=-0.060, P=0.041).

[0118] order.Clostridiales.id.1863 also exists independently as a protective factor for MDD (β=-0.099, P=0.042), which indirectly contributes to the protection of MDD by increasing the level of X-24952. The mediating effect is -0.011, accounting for 11.6% of the total effect, and the direct effect is -0.087.

[0119] It can be inferred that order.Clostridiales.id.1863 has a significant protective effect on MDD by regulating the level of X-24952.

[0120] phylum.Tenericutes.id.3919 showed a positive promoting effect on MMA level (β=0.207, P=0.025). In view of the protective effect of MMA level on MDD (β=-0.016, P=0.0095), phylum.Tenericutes.id.3919 also exists as a protective factor for MDD (β=-0.081, P=0.020).

[0121] The indirect protective effect of MMA on MDD through enhancing MMA levels was -0.003, accounting for 3.63% of the total effect, and the direct effect was -0.078.

[0122] In summary, phylum.Tenericutes.id.3919 plays a positive role in the prevention and relief of MDD by increasing the level of MMA.

[0123] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder, characterized in that: The steps include: Step 1: Construct the mediation Mendelian randomization hypothesis; including the association hypothesis, independence hypothesis and exclusivity hypothesis; the selected genetic variation is used as the instrumental variable IV; Step 2: Obtain whole-genome association study data related to major depressive disorder; the whole-genome association study data were obtained from the public database of the International Epidemiology and Genetics Consortium, specifically including 59,851 patients diagnosed with major depressive disorder and 113,154 healthy controls; Step 3: Obtain whole-genome association study data of intestinal microbes; the whole-genome association study data were obtained from the MiBioGen consortium, including 18,340 individuals from 24 cohorts, targeting the variable regions V4, V3-V4, and V1-V2 of the 16S rRNA gene to analyze the microbial composition and classify using direct classification sorting; Step 4: Obtain genome-wide association study data for CSF metabolites from a subset of participants in the Wisconsin Alzheimer's Disease Research Center and the Wisconsin Alzheimer's Disease Prevention Registry study; CSF samples were collected by lumbar puncture; Step 5: Instrumental variable IV selection: In the mediated Mendelian randomization analysis, single nucleotide polymorphisms that are closely related to IV exposure are used; Step 6: Statistical analysis: Use the MRPRESSO and TwoSampleMR packages in R software to perform data analysis tasks.

2. A method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: In the step 1, there is a correlation between genetic variation and exposure factors, genetic variation and potential confounding factors are independent of each other, and genetic variation only affects the outcome through exposure factors.

3. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: The diagnostic process for major depressive disorder in step 2 strictly follows standardized procedures, integrating structured clinical interviews, detailed electronic medical records and clinical diagnosis by professional physicians.

4. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: In step three, quantitative trait loci analysis is performed on the microbiome to identify host genetic variations located at genetic loci associated with the abundance levels of bacterial taxa in the intestinal microbiome.

5. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: The cerebrospinal fluid samples in step 4 included 689 types, of which 532 were from participants of the Wisconsin Alzheimer's Disease Research Center and 168 were from participants of the Wisconsin Alzheimer's Disease Prevention Registry.

6. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 5, characterized in that: The selection criteria for participants of the Wisconsin Alzheimer's Disease Research Center's cerebrospinal fluid samples were as follows: age 45 years or older, decision-making ability, and fasting for 12 hours.

7. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: In step 5, a genome-wide significance threshold of P<1×10-5 is used to screen single nucleotide polymorphisms.

8. The method of revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: In step six, the inverse variance weighted method is used to evaluate the potential causal relationship between exposure and outcome, and sensitivity analysis is performed to enhance the robustness of the results. The sensitivity analysis specifically includes MR-Egger analysis, Mendelian randomization pleiotropic residuals, and outlier detection.

9. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 8, characterized in that: The MR-Egger analysis is used to evaluate the pleiotropy of instrumental variables; the outlier detection identifies horizontal pleiotropy through comprehensive detection, and corrects potential pleiotropy problems by eliminating outliers when they are detected.

10. The method for revealing the relationship between intestinal microorganisms, cerebrospinal fluid and major depressive disorder according to claim 1, characterized in that: In step six, the Cochran Q test is used to assess heterogeneity, and a P value less than 0.05 indicates the presence of heterogeneity; the inverse variance weighted random effects model is used to estimate the causal effect; if no heterogeneity exists, the inverse variance weighted fixed effects model is used as the result of the inverse variance weighting method.

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