CN110570903B - Medicine for improving activity of mesocerebral substantia nigra dopamine neurons and preventing and treating Parkinson's disease - Google Patents

Abstract

The invention provides a medicine for improving the activity of mesocerebral substantia nigra dopamine neurons and preventing and treating Parkinson's disease, which is fulvestrant. The invention also provides a method for screening and improving the activity of the mesocerebral substantia nigra dopamine neuron for preventing and treating the Parkinson disease, which adopts a bioinformatics method of weighting gene coexpression network analysis and identification of a biological related difference coexpression module to match genes closely related to the Parkinson disease into the gene network module to obtain the gene coexpression module related to the Parkinson disease, and screens and obtains the medicine capable of obviously reversing the abnormally expressed genes in the module through a correlation map database and difference gene expression spectrum data between samples of the brain substantia nigra brain region in a Parkinson disease person and a normal control group. The invention overcomes the limitation of a single channel or target spot, and utilizes the CMAP database to screen approved clinical drugs, thereby saving time, money and labor cost and being more beneficial to developing safe and effective drugs.

Description

Medicine for improving activity of mesocerebral substantia nigra dopamine neurons and preventing and treating Parkinson's disease

Technical Field

The invention belongs to the field of biological medicines, and particularly relates to a medicine for improving the activity of mesocerebral substantia nigra dopamine neurons and preventing and treating Parkinson's disease, which is screened out by a bioinformatics method.

Background

Parkinson's Disease (PD), a degenerative disease of the central nervous system characterized by degenerative necrosis of dopamine neurons of the mesoencephalic substantia nigra, is a common neurodegenerative disease of the middle and old aged, and is clinically manifested as resting tremor, increased muscle tone, bradykinesia, and the like. Although PD has been studied for nearly two hundred years, the pathogenesis of PD is unclear, and the disease can only be improved, cannot prevent the disease from developing and even cannot be cured by drug therapy or surgical therapy.

Pathological conditions of PD include degeneration loss of mesencephalic nigral reticuloid Dopaminergic (DA) neurons and reduction of striatal DA levels, so that replacement therapy with levodopa (L-dopa) is the most widely and effectively applied method. However, with the progressive development of PD and the continued administration of levodopa, the remaining dopaminergic neurons lose their ability to produce dopamine, and the buffering capacity for exogenous dopamine drugs is reduced. Meanwhile, the dopamine level in the striatum can not be maintained in a normal physiological state, and abnormal fluctuating stimulation is formed on dopamine receptors distributed on the surface of medium-sized spiny neurons in the striatum, so that various motor complications are caused, and the head, the face, the limbs, the trunk and the like are affected. Therefore, the search for new therapeutic targets and alternative therapies and the search for new non-dopaminergic drugs has become a hot research point for PD therapy.

Fulvestrant (fulvestrant) drugs are a novel class of estrogen receptor blockers and are used in the treatment of postmenopausal advanced breast cancer where anti-hormone therapy is ineffective and estrogen receptors are positive. At present, no report related to fulvestrant and Parkinson disease treatment exists.

Disclosure of Invention

The invention aims to provide a medicament capable of replacing levodopa to prevent and treat Parkinson's disease and similar symptoms.

In order to achieve the purpose, the invention adopts the following technical scheme:

a method for screening a medicine for improving the activity of mesoceric nigra dopamine neurons and preventing and treating Parkinson's disease comprises the following steps:

s1, gene expression data acquisition, downloading a whole genome gene expression data set; wherein the dataset comprises a gene expression dataset for 10 brain regions (GSE 60862);

s2, constructing a normal human brain co-expression network, and dividing genes of 10 brain areas into a co-recognition module and a difference module in a midbrain substantia nigra brain area by adopting a weighted gene co-expression method;

s3, checking the retention condition of a module generated by the gene expression data sets of 10 brain areas, and evaluating the module and other independent brain gene expression data sets;

enrichment of PD genes in a consensus module and a difference module in gene expression data sets of 10 brain regions, collecting genes related to Parkinson's disease from a PD related gene data set and a human gene mutation data set, evaluating the enrichment degree of the Parkinson's disease related genes in each module, and comparing the number of genes overlapped with the Parkinson's disease related genes in the modules with the number of genes overlapped with a control gene;

s5, neuron specificity analysis, namely detecting whether the stored gene modules are enriched in specific cell types by using a public cell type marker gene database;

s6, drug discovery analysis is performed by a correlation map database, and the compound is selected as a candidate drug according to a connectivity score provided by the correlation map data;

s7, verifying the effect of the screened medicine by adopting a rotenone-induced Parkinson disease model, and detecting the capability of the medicine for reversing the expression of relevant genes of the Parkinson disease by adopting a real-time quantitative PCR technology.

Preferably, the genome-wide gene expression data set downloaded in step S1 further includes spatio-temporal gene expression data (GSE25219), normal human brain tissue gene expression data (GSE45878, GSE34865), parkinson' S disease case control group gene expression data (GSE8397), and mouse brain gene expression data (GSE 16496).

Preferably, the weighted gene co-expression method adopted in step S2 includes network analysis (WGCNA) and DiffCoex; in which WGCNA was used to detect a co-expression module common to all ten brain regions ("consensus module"), and DiffCoex was used to identify a gene module that was differentially expressed in the mesencephalic substantia nigra brain region compared to the other 9 brain regions ("difference module").

Preferably, the other independent brain gene expression data sets in step S3 include: spatiotemporal gene expression data (GSE25219), normal human brain tissue gene expression data (GSE45878, GSE34865), Parkinson's disease case control group gene expression data (GSE8397) and mouse brain gene expression data (GSE 16496); wherein samples older than 13 years are screened through the GSE25219 dataset; analyzing the storage condition of co-expression modules of different brain regions by using a GSE45878 data set; using the GSE34865 dataset to detect the extent of modular preservation of substantia nigra brain regions, including 57 substantia nigra samples of postmortem brains of 57 neurologically and neuropathologically normal persons; the GSE8397 data set is used for detecting module preservation of the substantia nigra brain region of the PD patient, and the GSE16496 data set is used for evaluating whether the modules are preserved in other species.

Preferably, the step of collecting genes related to parkinson' S disease from the PD-associated gene dataset and the human gene mutation dataset in step S4 further comprises collecting other genes from the HGMD dataset as a control group, which genes have not been reported to be related to neurological diseases in any study.

Preferably, the neurological disease comprises parkinson's disease, alzheimer's disease, huntington's disease, stroke, amyotrophic lateral sclerosis, spinocerebellar atrophy, spinal muscular atrophy, bovine spongiform encephalopathy, creutzfeldt-jakob disease, and primary lateral sclerosis.

Preferably, the cell type marker gene database in step S5 is a single cell RNA sequence database from human ventral midbrain, comprising 13 cell types and 25 cell subtypes.

Preferably, the step S6 is executed by a relevance graph database, and is implemented by the following method: using samples of the substantia nigra brain region of PD patients and healthy controls in the gene expression dataset of GSE8397, gene differential expression analysis was performed using limma R package, and then these genes were input into a correlation map database (CMAP), and compounds having a function of reversing a significant difference in gene expression between PD patients and controls were found as candidate compounds.

Preferably, the rotenone-induced parkinson' S disease model in step S7 is prepared by the following method: on day 15 of the embryo (E15), primary neuronal cells were isolated from the cortical layer of C57B/L mice, cultured for 6 days, and Mitochondrial Membrane Potential (MMP) was used to determine whether or not successful induction of the PD model was achieved.

Preferably, the parkinson' S disease related genes of step S7 include SLC6A3, SLC18a2, GCH1, TH, DCC, SNCA, UCHL1, VPS35, GPRIN3, DRD2, NR4a2, and DNAJC 6.

The present invention is a bioinformatics method for analyzing and identifying differential co-expression modules associated with organisms by employing a weighted gene co-expression network. 277 genes closely related to the Parkinson disease are matched into a gene network module by means of statistical test to obtain a gene co-expression module related to the Parkinson disease, and a drug-fulvestrant (fulvestrant) capable of obviously reversing abnormally expressed genes in the module is obtained through a correlation Map (CMap) database and differential gene expression profile data between brain substantia nigra brain region samples in a Parkinson patient and a normal control group. The real-time quantitative polymerase chain reaction (qt-PCR) experiment proves the ability of fulvestrant (fulvestrant) to reverse abnormal gene expression, and the experiment shows that fulvestrant drugs can increase the number of primary neurons with normal mitochondrial membrane potential and restore the neuron activity in rotenone-induced Parkinson disease model primary nerves. Therefore, fulvestrant has the capacity of reversing the abnormal gene expression of the Parkinson disease and recovering the activity of the mesocerebral substantia nigra dopamine neuron.

Another purpose of the invention is to provide a new application of the known fulvestrant medicine, mainly an application in preparing the medicine for improving the activity of the mesocerebral substantia nigra dopamine neuron.

Preferably, the new use of the known fulvestrant is in the preparation of a medicament for the treatment or prevention of parkinson's disease.

The invention has the beneficial effects that: the invention discovers a plurality of pathways and risk genes related to the Parkinson disease by using a bioinformatics method of system analysis, and has important significance for biological targeted therapy, biological drug development, risk prediction and the like of the Parkinson disease. On the basis, a method for multi-target drug development is applied to find potential drugs. At present, the drugs for treating the Parkinson's disease are all based on a single target and a single channel. In the invention, the pathogenesis of the Parkinson disease is determined by analyzing the integrated systems of different databases, and the limitation of a single path or a target point is overcome. And the CMAP database is also used for screening approved clinical drugs, so that the time, money and labor cost are saved, and the safe and effective drugs can be developed.

Drawings

FIG. 1 is a schematic diagram showing the inhibitory effect of fulvestrant on the down-regulation of the PD gene.

Figure 2 is a schematic representation of the effect of fulvestrant on recovery of neuronal activity.

Detailed Description

In order to more concisely and clearly demonstrate technical solutions, objects and advantages of the present invention, the following detailed description of the present invention is provided with reference to specific embodiments and accompanying drawings.

Example 1

The embodiment provides a method for screening a medicine for improving the activity of mesocerebral substantia nigra dopamine neurons and preventing and treating the Parkinson's disease, which comprises the following steps:

s1, gene expression data acquisition:

gene expression data are from public GEO data. The GEO dataset contains microarrays, next generation sequencing, and other forms of high throughput genomic data submitted by researchers. From GEO, we downloaded 6 whole genome gene expression datasets, which are gene expression data of 10 brain regions (GSE60862), spatiotemporal gene expression data (GSE25219), normal human brain tissue gene expression data (GSE45878, GSE34865), parkinson disease case control group gene expression data (GSE8397), and mouse brain gene expression data (GSE 16496).

S2, constructing a normal human brain co-expression network:

the GSE60862 dataset was used to construct a gene co-expression network. Genes of 10 brain regions were divided into co-expression modules using two methods, weighted gene co-expression network analysis (WGCNA) and DiffCoex. WGCNA was used to detect a co-expression module ("consensus module") common to all ten brain regions; DiffCoex was used to identify gene modules that were differentially expressed in the mesencephalic substantia nigra brain regions compared to the other 9 brain regions ("difference modules").

S3, checking the retention condition of a module generated by a GSE60862 data set:

several independent brain gene expression datasets were used to assess the preservation of co-expression modules obtained from GSE60862 samples. Samples older than 13 years were screened by using the GSE25219 dataset. The retention of the co-expression modules of different brain regions was analyzed using the GSE45878 dataset. The GSE34865 dataset was used to examine the extent of modular preservation of substantia nigra brain regions, including 57 substantia nigra samples of the postmortem brain of 57 neurological and neuropathological normal persons. In addition, the GSE8397 data set is also used for detecting module preservation of the substantia nigra brain area of a PD patient. Finally, to assess whether these modules were preserved in other species, analysis was performed in the data set GSE16496, which includes the 51 mouse brain region. Using R package: biomart Bioconductor records the mouse gene "one-to-one" matches with human homologous genes.

S4. enrichment of PD genes in consensus and difference modules in GSE60862 dataset:

we collected 277 genes associated with Parkinson's disease in two databases, the PD-associated gene set (PDgset) and the human gene mutation data set (HGMD, http:// www.hgmd.cf.ac.uk/ac/index. php). PDgset is a panel of 242 genes that were significantly associated with PD and was collected by hu et al from over 200 studies. HGMD is a data set that collects mutant genes associated with disease. In this data set, 46 genes associated with PD were collected. In addition, we created a control dataset comprising 4825 genes from the HGMD dataset. These genes have not been reported to be associated with neurological diseases in any study, including Parkinson's disease, Alzheimer's disease, Huntington's disease, stroke, amyotrophic lateral sclerosis, spinocerebellar atrophy, spinal muscular atrophy, bovine spongiform encephalopathy, Creutzfeldt-Jakob disease, and primary lateral sclerosis, among others. The enrichment of the Parkinson-associated genes in each module was estimated by using FET (Fisher Exact test), by comparing the number of genes overlapping with the PD-associated genes in the module with the number of genes overlapping with the control genes.

S5, neuron specificity analysis:

a common set of cell type marker genes is used to detect whether the stored gene modules are enriched in a particular cell type. Single cell RNA sequence data was from the human ventral midbrain, including 13 cell types and 25 cell subtypes. The degree of gene enrichment for each cell type was evaluated using FETs, and the statistical significance of the number of genes overlapping with cell type marker genes was experimentally evaluated.

S6, drug discovery and analysis:

drug discovery analysis was performed by a correlation map (CMAP, http:// www.broadistitute.org/CMAP /) database. The CMAP database consisted of 1309 drug-treated 4 cell lines, comprising over 7000 gene expression profiles in total. To identify genes that expressed significantly differently in PD patients and controls, we performed gene differential expression analysis using limma R package using samples of the nigro brain region of 24 PD patients and 11 healthy controls in the gene expression dataset for GSE8397, as shown in table 1. These genes were imported into CMAP, and compounds having a function of reversing abnormal expression of genes in PD patients and controls in highly conserved modules were found as candidate compounds, as shown in table 2. According to the Connectivity score provided by the CMAP, the compound is selected as a candidate drug and is compared with a reference gene table method spectrum in the CMAP to obtain a correlation coefficient (Connectivity score) with a ratio of-1 to-1. And dividing the gene expression profile data into a positive regulation gene group and a negative regulation gene group for analysis, calculating the similarity degree of the gene profiles, and finally giving a score average value. Score is positive, which means that small molecule compounds or drugs have similar or homodromous connection with a special biological process or state, and the researched drugs and certain small molecule compounds can positively promote the expression of genes; score is negative and indicates that the small molecule compound or drug is inversely or antagonistically associated with a particular biological process or state, and that the drug under study can reverse the expression of these divergent genes. The fraction [0, 1] represents that the drug molecules of the two are in Positive correlation and is called Positive; the fraction [ -1, 0] represents that the drug molecules of both are negatively correlated, called Negative; larger absolute values indicate greater correlation.

Table 1: limma R package performs gene differential expression analysis

Table 2: candidate compounds

S7, verifying the effect of the screened medicine by adopting a rotenone-induced Parkinson disease model, and detecting the capability of the medicine for reversing the expression of relevant genes of the Parkinson disease by adopting a real-time quantitative PCR technology.

S7, drug effect verification, namely a rotenone-induced Parkinson disease model:

(1) establishing a Parkinson disease model: on embryonic day 15 (E15), primary neuronal cells were isolated from the cortical layer of C57B/L mice. Using a solution with 2% B27

Culture medium (Gibco BRL, 17504) Primary neuronal cells were cultured in 6-well plates coated with poly-D-lysine (Sigma, p 6407). Primary neurons were cultured for 6 days for normal development and refinement of neuritis. Then, different concentrations of rotenone were applied directly to the medium to establish the PD model. All experiments were repeated at least 3 times. We used Mitochondrial Membrane Potential (MMP) to determine whether the PD model was successfully induced. If MMP of the neuron cells after rotenone treatment is lower than that of the control group, the cells are induced to be a PD model.

(2) Real-time quantitative PCR:

to test the ability of the drug to reverse gene expression, real-time quantitative PCR technology was used. Total RNA was isolated using conventional methods and quantified using a Nanodropper (Thermo Fisher Scientific). The cDNA was prepared using 300-500 ng/. mu.l total RNA reverse transcription polymerase chain reaction (RT-PCR) using the high capacity cDNA reverse transcription kit (Takara, RR047A) according to the manufacturer's instructions. Real-time quantitative PCR (qPCR) was performed on the cDNA using a tb greentm premix ex taqtm II kit (Takara, RR820A) for SLC6A3, SLC18A2, GCH1, TH, DCC, SNCA, UCHL1, VPS35, GPRIN3, DRD2, NR4A2 and DNAJC6 using the primers shown in Table 3. qPCR was performed on a fast real-time PCR system (applied to Roche Lightcycler 480 ii). Folding changes in expression were calculated using Delta CT with mouse GAPDH as an endogenous control for gene expression. The effect of different treatments on gene expression was determined using the two-tailed t-test using the graph pad prism 7.0 software (graph pad software, San Diego, Calif., USA). Data are presented as mean ± SEM. A p-value <0.05 is considered statistically significant.

Table 3: primers for real-time quantitative PCR (qPCR)

(3) Mitochondrial function assay:

the Mitochondrial Membrane Potential (MMP) of the cells was measured using JC-1 mitochondrial membrane potential measurement kit (Yeasen, 40706ES60), a fluorometric method for measuring the mitochondrial membrane potential of viable cells. MMP kits showed low mitochondrial function assays. The kit shows blue fluorescent monomers at low MMPs and red fluorescence at high MMPs. The MMP kit comprises cationic dye TMRE (tetramethyl rhodamine ethyl ester perchlorate) and mitochondrial membrane potential interfering agent CCCP (carbonyl cyanide 3-chlorophenylhydrazine). CCCP transports protons from the inter-membrane space back to the mitochondrial matrix, thereby transferring protons from the ATP synthase. This transfer of protons causes depolarization of mitochondria, thereby increasing the rate of respiration, allowing MMP to circulate for short periods of time, and separating electron transport from ATP synthesis. TMRE is a cell membrane permeable fluorescent dye that accumulates in intact mitochondria. Depolarized or inactive mitochondria show a decrease in membrane potential, resulting in a decrease in TMRE accumulation. In the present invention, cells in a 6-well plate were cultured at 37 ℃ for 30 minutes in a medium containing 1ml of JC-1 working buffer and washed with PBS buffer. Fluorescence was then measured with a bd-celesta flow cytometer and the output analyzed with flowjo 10.0 software. Finally, mitochondrial membrane potential was measured using fluorescence ratios of 488/530nm (green) and 549/595nm (red). In untreated control cultures, these ratios are expressed as a percentage of the ratio. Blue fluorescent monomers at low MMPs and red fluorescence at high MMPs.

Example 2 fulvestrant cell experiments demonstrate

1. Fulvestrant can inhibit down-regulation of PD gene

The effect of fulvestrant on the PD gene was verified using the rotenone-induced parkinson's disease model of step 7 of example 1. In rotenone-induced parkinson's disease model, the inventors performed five treatments of DMSO, CCCP, ROT400nM, ROT400nM + FUL200nM, and FUL200nM on cortical neurons. First, cortical neurons were pretreated with 200nm rotenone for 2 hours, then with fulvestrant at different concentrations (100nm,200nm and 300nm) for 24 hours. Cortical neurons treated with CN (control), DMSO (2%), rotenone and fulvestrant at different concentrations (100nM,200nM and 300nM) were tested by RT-qPCR method. The purpose of the DMSO treatment was to examine the effect of the solvent. Statistical analysis was performed using GraphPad Prism 7.0 software.

The results are shown in figure 1, and after the Parkinson disease model is treated by fulvestrant with the concentrations of 100nM,200nM and 300nM respectively for 24 hours, fulvestrant with different concentrations can inhibit the down-regulation of TH, SLC6A3, SNCA and UCHL-1, and can reverse the PD gene abnormally expressed by cortical neurons after rotenone treatment. The mRNA expression of four PD genes (TH, SLC6A3, SNCA and UCHL-1) is obviously improved.

2. Fulvestrant can restore neuronal activity

The inventor designs five treatment methods aiming at cortical neurons, namely DMSO, CCCP, ROT400nM, ROT400nM + FUL200nM and FUL200nM, for detecting the change of MMP after fulvestrant treatment. The change in MMP between these treated groups and the control group (CN) was determined by the JC-1 method. The calculation results were analyzed using Flowjo 10.0 software, and the statistical results were analyzed using GraphPad Prism 7.0 software. Low neuron number for MMPs (blue) and normal neuron number for MMPs (red). CN is a control group, DMSO is a solvent control group, and CCCP is an MMP positive control group. Cortical neurons were stained with 1ml JC-1 working buffer. The cells were stained for 30 minutes at 37 ℃, 5% carbon dioxide, then washed with PBS, and analyzed by measuring and analyzing the ratio of 488/530nm (green) and 549/595nm (red) on a flow cytometric analyzer. An increase in green fluorescence indicates decreased MMP, and an increase in red fluorescence indicates normal MMP.

Results as shown in fig. 2, fig. 2A shows the low neuron number (blue) and normal neuron number (red) for MMPs in the different treatment groups, where the full 200nM treatment group (fulvestrant at a concentration of 200 nM) increased the number of primary neurons, normalized MMPs and restored the activity of primary neurons. FIG. 2B shows that the FUL200nM treated group was able to significantly reduce mitochondrial membrane potential.

In summary, the following steps: the results show that the fulvestrant drug can effectively reverse genes abnormally expressed in Parkinson and diseases, improve the activity of dopamine neurons and achieve the effect of treating Parkinson diseases and similar symptoms thereof.

The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A method for screening a medicine for improving the activity of mesocerebral substantia nigra dopamine neurons and preventing and treating Parkinson's disease is characterized by comprising the following steps:

s1, gene expression data acquisition: downloading a whole genome gene expression data set; wherein the dataset comprises gene expression datasets for 10 brain regions;

s2, constructing a normal human brain co-expression network: dividing genes of 10 brain areas into a consensus module and a difference module in a midbrain substantia nigra brain area by adopting a weighted gene co-expression method;

s3, checking the retention of the modules generated by the gene expression data sets of 10 brain regions: evaluating it with other independent brain gene expression data sets;

s4. enrichment of PD genes in consensus modules and difference modules in gene expression data sets of 10 brain regions: collecting genes related to the Parkinson's disease from the PD-related gene dataset and the human gene mutation dataset, evaluating the enrichment degree of the Parkinson's disease-related genes in each module, and enriching by comparing the number of the genes overlapped with the Parkinson's disease-related genes in the modules with the number of the genes overlapped with the control group genes;

s5, neuron specificity analysis: using a common cell type marker gene database to detect whether the stored gene modules are enriched in a particular cell type;

s6, drug discovery and analysis: selecting, performed by the association profile database, a drug candidate based on the connectivity score provided by the association profile data;

s7, verifying the effect of the screened medicine by adopting a rotenone-induced Parkinson disease model: the real-time quantitative PCR technology is adopted to detect the capability of the drug for reversing the expression of genes related to the Parkinson's disease.

2. The method for screening drugs for improving the activity of mesodermal dopamine neurons for the prevention and treatment of parkinson 'S disease according to claim 1, wherein the genome-wide gene expression data set downloaded in step S1 further comprises spatiotemporal gene expression data, normal human brain tissue gene expression data, parkinson' S disease case control group gene expression data, and mouse brain gene expression data.

3. The method for screening drugs for improving the activity of dopamine neurons in the substantia nigra of the middle brain for preventing and treating Parkinson' S disease according to claim 1, wherein the weighted gene co-expression method adopted in step S2 comprises network analysis and DiffCoex; where network analysis was used to detect co-expression modules common to all ten brain regions, DiffCoex was used to identify gene modules that were differentially expressed in the mesencephalic substantia nigra brain regions compared to the other 9 brain regions.

4. The method for screening a drug for improving the activity of mesoncephalic nigral dopamine neurons for the prevention and treatment of parkinson' S disease according to claim 1, wherein the other independent sets of brain gene expression data in step S3 comprise: time-space gene expression data, normal human brain tissue gene expression data, Parkinson disease case control group gene expression data and mouse brain gene expression data; wherein a sample older than 13 years is screened through the spatiotemporal gene expression dataset; analyzing the storage condition of the co-expression modules in different brain regions by using a normal human brain tissue gene expression data set; detecting module preservation degree of substantia nigra brain region by using a normal human brain tissue gene expression data set, wherein the module preservation degree comprises 57 substantia nigra samples of the postmortem brain of 57 nervous and neuropathological normal persons; the gene expression data set of the Parkinson disease case control group is used for detecting module storage conditions of the substantia nigra brain region of a PD patient, and the gene expression data set of the mouse brain is used for evaluating whether the modules are stored in other species.

5. The method for screening a drug for improving the activity of dopaminergic neurons in the mesencephalon, preventing and treating parkinson 'S disease of claim 1, wherein the step of collecting genes associated with parkinson' S disease from the PD-associated gene dataset and the human gene mutation dataset in step S4 further comprises collecting other genes from the HGMD dataset, which have not been reported to be associated with other neurological diseases in any study.

6. The method for screening a drug for improving the activity of dopaminergic neurons in the mesencephalon, preventing and treating the parkinson' S disease of claim 1, wherein the database of cell type marker genes in step S5 is a database of single-cell RNA sequences from the human ventral mesencephalon, comprising 13 cell types and 25 cell subtypes.

7. The method for screening a drug for improving the activity of dopamine neurons in the substantia nigra of the middle brain for preventing and treating Parkinson' S disease according to claim 1, wherein the step S6 is performed by a correlation spectrum database and is implemented by the following steps: the gene expression data of the Parkinson disease case control group gene expression data are utilized to collect samples of the substantia nigra brain area of PD patients and healthy control groups, limma R package is adopted to perform gene differential expression analysis, then the genes are input into a correlation map database, and compounds with the function of reversing the significant difference of the gene expression of the PD patients and the control groups are found to be candidate compounds.

8. The method for screening a drug for improving the activity of dopamine neurons in the substantia nigra of the midbrain to prevent and treat parkinson 'S disease according to claim 1, wherein the parkinson' S disease-associated genes in step S7 comprise SLC6A3, SLC18a2, GCH1, TH, DCC, SNCA, UCHL1, VPS35, GPRIN3, DRD2, NR4a2, and DNAJC 6.

9. Use of fulvestrant in the preparation of a medicament for improving the activity of mesocerebral substantia nigra dopamine neurons.

10. Use of fulvestrant in the manufacture of a medicament for the treatment or prevention of parkinson's disease.

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