Parkinson's disease cognitive disorder early biomarker and application thereof, and Parkinson's disease intelligent analysis system

Abstract

The invention provides an early biomarker for cognitive impairment of Parkinson's disease, application of the early biomarker and an intelligent analysis system for Parkinson's disease. The biomarker is a GALC gene. The intelligent analysis system for the early biomarkers of the cognitive impairment of the Parkinson's disease comprises a data integration module and a data analysis module. The data integration module is used for acquiring a gene detection result, an olfactory test score and neuroimaging data of the Parkinson's disease biomarker; and the data analysis module is used for analyzing the influence of gene variation of the Parkinson's disease biomarker on olfactory dysfunction and cognitive decline of the Parkinson's disease patient by adopting a structural equation model SEM based on the multi-modal data set. According to the application, through confluence analysis of multi-modal data, by combining genetics, neuroimaging and clinical evaluation, the rs8005172 site variation of the GALC gene is taken as an early biomarker of cognitive impairment of Parkinson's disease, so that PD patients with high cognitive decline risk can be accurately identified.

Description

Technical Field

[0001] This invention relates to the field of intelligent diagnostic technology, and more particularly to the field of early non-invasive intelligent diagnostic technology for cognitive impairment in Parkinson's disease. Background Technology

[0002] Parkinson's disease (PD) is a complex neurodegenerative disease characterized by a variety of non-motor symptoms in addition to typical motor symptoms such as tremor, rigidity, and bradykinesia. Olfactory dysfunction and cognitive decline are common early manifestations. Olfactory dysfunction occurs in up to 90% of PD patients and often precedes motor symptoms, thus it is considered a potential early biomarker for PD progression and cognitive decline. However, the specific biological mechanisms underlying olfactory dysfunction and cognitive decline remain unclear.

[0003] In recent years, advancements in genetics and neuroimaging have provided new tools for elucidating the pathological mechanisms of Parkinson's disease (PD). The GALC gene encodes galactocerebrosidase (GalCase), which plays a crucial role in myelin metabolism and neuronal function, and its variations are associated with various neurodegenerative diseases. Previous studies have shown that GALC gene variations may lead to neuronal dysfunction, thereby affecting olfactory and cognitive functions. However, the specific mechanisms by which GALC gene variations contribute to olfactory dysfunction and cognitive decline in PD patients remain insufficiently understood. Summary of the Invention

[0004] To address the aforementioned technical problems, the first aspect of this application provides an early biomarker for cognitive impairment in Parkinson's disease, wherein the biomarker is the GALC gene.

[0005] Furthermore, the biomarker is the rs8005172 site of the GALC gene.

[0006] The second aspect of this application provides the application of the aforementioned early biomarkers of Parkinson's disease cognitive impairment in the preparation of early diagnostic kits for Parkinson's disease cognitive impairment.

[0007] Furthermore, the diagnostic kit includes reagents for detecting the expression level of the biomarker, the reagents including specific primers designed for the biomarker.

[0008] Furthermore, the sequence of the specific primer is as follows:

[0009] F: TGGCTTCTAGTTTGCCATAGA;

[0010] R:CAGAAGAAACATCTATGGCAAAC.

[0011] Furthermore, the diagnostic kit includes a kit for detecting the mRNA gene expression level of the biomarker or a kit for detecting the corresponding protein expression level of the biomarker.

[0012] The third aspect of this application provides an intelligent analysis system for the aforementioned early biomarkers of cognitive impairment in Parkinson's disease, comprising:

[0013] The data integration module is used to acquire gene detection results of Parkinson's disease biomarkers, olfactory test scores and neuroimaging data, and to standardize different data types to construct a multimodal dataset.

[0014] The data analysis module is used to analyze the impact of genetic variations of Parkinson's disease biomarkers on olfactory dysfunction and cognitive decline in Parkinson's disease patients using structural equation modeling (SEM) based on a multimodal dataset.

[0015] Furthermore, the Parkinson's disease biomarker is the GALC gene.

[0016] Furthermore, the Parkinson's disease biomarker is the rs8005172 site of the GALC gene.

[0017] After adopting the above technical solution, this application has the following technical effects:

[0018] This application, through integrated analysis of multimodal data, combining genetics, neuroimaging, and clinical assessment, reveals the role of GALC gene variants in olfactory dysfunction and cognitive decline in PD patients. The GALC gene encodes galactocerebrosidase (GalCase), which plays a crucial role in myelin metabolism and neuronal function; variants in GALC lead to neuronal dysfunction, thereby affecting olfactory and cognitive functions. The technical solution presented in this application can more accurately identify PD patients at high risk of cognitive decline and provide a scientific basis for personalized treatment. The non-invasive nature of this technology makes it easy to promote and apply in clinical practice, and it has broad application prospects. Specifically, it has the following advantages:

[0019] (1) Early diagnosis: By detecting GALC gene variants and olfactory dysfunction, the risk of cognitive decline in Parkinson's disease patients can be predicted at an early stage. Early diagnosis is crucial for the treatment and intervention of Parkinson's disease, enabling measures to be taken in the early stages of the disease to slow disease progression and improve patients' quality of life.

[0020] (2) Multimodal integrated analysis: Combining gene testing, neuroimaging and olfactory function assessment, it provides more accurate and comprehensive diagnostic prediction and prognostic information.

[0021] (3) Personalized medicine: Provides a basis for individualized treatment of Parkinson's disease patients, which helps in early intervention and delaying disease progression. Based on the patient's genetic characteristics and clinical manifestations, a personalized treatment plan is developed to improve treatment effectiveness.

[0022] (4) Non-invasive testing: Olfactory function testing and neuroimaging examination are both non-invasive methods, which are easy to apply in clinical practice. Non-invasive testing methods reduce patient pain and risks, and improve the feasibility and acceptance of testing.

[0023] (5) Scientific rigor and innovation: This invention is based on the latest research findings and combines multidisciplinary technical methods, thus possessing high scientific rigor and innovation. By revealing the link between GALC gene variations and olfactory dysfunction and cognitive decline, it provides a new direction for the research and treatment of Parkinson's disease. Attached Figure Description

[0024] Figure 1 The results of the association analysis (forest plot) and eQTL analysis between GALC gene variants and olfactory dysfunction;

[0025] Figure 2 Changes in gray matter volume in the brains of patients with different GALC genotypes (right superior temporal pole).

[0026] Figure 3 Comparison of dopamine transporter (DAT) binding rates among patients with different GALC genotypes;

[0027] Figure 4 The cognitive decline risk curves (Kaplan-Meier curves) for PD patients with different levels of olfactory function.

[0028] Figure 5 The results of structural equation modeling (SEM) analysis of GALC gene variants, brain gray matter volume, olfactory function, and cognitive function. Detailed Implementation

[0029] The advantages of the present invention are further illustrated below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that the following detailed description is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0030] This embodiment provides an intelligent analysis system for early biomarkers of cognitive impairment in Parkinson's disease, comprising a data integration module and a data analysis module. Based on the association between GALC gene variants and olfactory decline and cognitive deterioration in Parkinson's disease (PD) patients, this system reveals the biological mechanisms between olfactory and cognitive functions through multimodal data analysis (including genetics, neuroimaging, and clinical assessment). Specifically, the rs8005172 variant of the GALC gene is significantly associated with olfactory dysfunction, and this variant indirectly affects cognitive function by influencing the gray matter volume of the right superior temporal pole (STP) of the brain. Through structural equation modeling (SEM) analysis, this system reveals the direct and indirect effects of GALC gene variants on olfactory and cognitive functions, providing new biomarkers and therapeutic targets for early diagnosis and intervention.

[0031] The integration module is used to acquire genetic testing results for Parkinson's disease biomarkers, olfactory test scores, and neuroimaging data. It standardizes different data types to ensure comparability and constructs a multimodal dataset. Multimodal data can be acquired through manual input or directly from third-party information systems such as the hospital's HIS. The multimodal data includes three aspects: genetic testing, neuroimaging analysis, and olfactory function assessment.

[0032] 1. Genetic testing

[0033] Sample collection is a fundamental step in this invention; ensuring the quality and quantity of samples is crucial for the accuracy and reliability of subsequent testing. The specific steps for sample collection are as follows:

[0034] (1) Sample source: Peripheral blood samples are collected from patients with Parkinson's disease, usually in the form of 5-10 ml. It is necessary to ensure that the samples are free from hemolysis and contamination during collection and to process them within 2 hours after collection.

[0035] (2) Sample processing: The collected blood samples were placed in anticoagulant tubes and centrifuged to separate plasma and blood cells. Subsequently, leukocytes were extracted for DNA extraction. The extraction process must be carried out in a sterile environment to avoid external contamination of the samples.

[0036] (3) Sample preservation: Extracted DNA samples must be preserved at -80°C to ensure their stability. When preserving samples, the sample number, collection date, and patient information must be labeled for subsequent traceability and analysis.

[0037] (4) Genetic testing: The risk of olfactory dysfunction in patients is assessed by detecting variations at the rs8005172 locus of the GALC gene. The GALC gene encodes galactosylceramide enzyme (GalCase), which plays a crucial role in myelin metabolism and neural function; variations in this enzyme may lead to neurodegenerative diseases. Specific variations at the rs8005172 locus are significantly associated with olfactory dysfunction, suggesting that this gene variation leads to olfactory dysfunction by affecting neural metabolism and the integrity of the olfactory pathway. Genetic testing is the core component of this invention, assessing the risk of olfactory dysfunction and cognitive decline in patients by detecting variations at the rs8005172 locus of the GALC gene. The specific steps of genetic testing are as follows:

[0038] (4.1) DNA Extraction: High-quality DNA was extracted from leukocytes using a commercially available DNA extraction kit (such as the Qiagen DNA Extraction Kit). The kit's operating procedures must be strictly followed during extraction to ensure the purity and concentration of the DNA.

[0039] (4.2) Genotyping: Genotyping of the GALC gene at the rs8005172 locus was performed using high-throughput sequencing technology (such as the Illumina platform). Prior to sequencing, DNA samples underwent quality control, including concentration determination, purity testing, and fragment length analysis. During sequencing, multiplex PCR amplification technology was employed, and specific primers were designed for the rs8005172 locus to ensure the specificity and accuracy of the amplification products.

[0040] (4.3) Data Analysis: After sequencing, the sequencing data were analyzed using bioinformatics software (such as PLINK and GATK). First, the raw sequencing data underwent quality control to remove low-quality reads and potential contamination sequences. Then, genotyping was performed on the target loci to determine the genotype of the samples (e.g., wild-type CC, heterozygous CT, homozygous TT). During the analysis, statistical analysis of the genotyping results was performed to calculate allele frequencies and genotype frequencies, and to assess their correlation with olfactory dysfunction and cognitive decline. Results are shown in [link to results]. Figure 1 .

[0041] 2. Neuroimaging analysis

[0042] Neuroimaging analysis is a key aspect of this invention. MRI and DAT-SPECT imaging techniques were used to assess the impact of GALC gene variants on brain structure and dopamine transport function. Specifically, MRI and DAT-SPECT imaging were employed to analyze the effects of GALC gene variants on brain structures (such as the right superior temporal gyrus) and dopamine transport function. Parkinson's disease patients carrying GALC gene variants exhibited gray matter atrophy in the right superior temporal gyrus, an area closely related to olfactory information processing and cognitive function. Furthermore, DAT-SPECT imaging results showed that the GALC gene variants had a limited impact on dopamine transport function, suggesting that its impact on cognitive decline is primarily achieved through non-dopaminergic mechanisms.

[0043] The specific steps of neuroimaging analysis are as follows:

[0044] (1) MRI imaging:

[0045] (1.1) Equipment selection: Use a 3.0T magnetic resonance imaging system (such as Siemens Magnetom Skyra) to ensure high resolution and high signal-to-noise ratio of the imaging.

[0046] (1.2) Imaging sequence: Three-dimensional T1-weighted imaging (3D T1WI) sequence was used. The scanning parameters included: repetition time (TR) = 2300ms, echo time (TE) = 2.98ms, flip angle = 9°, matrix size = 256×256, and voxel size = 1×1×1mm³. The scanning range covered the entire brain, ensuring that olfactory-related brain regions (such as the olfactory bulb and superior temporal gyrus) and cognitive-related brain regions (such as the hippocampus and prefrontal cortex) were included.

[0047] (1.3) Image preprocessing: MRI images were preprocessed using SPM8 software, including image quality check, tissue classification (gray matter, white matter, cerebrospinal fluid), spatial normalization (DARTEL method), and gray matter volume extraction. The preprocessed images were then smoothed using an 8mm FWHM Gaussian filter to reduce noise and improve the sensitivity of statistical analysis.

[0048] (1.4) Data Analysis: Voxel-based morphological analysis (VBM) was used to compare gray matter volume differences among patients with different genotypes. ANOVA analysis was used to identify gray matter volume variation regions associated with GALC gene variants, and gray matter volume values ​​from regions of interest (ROIs) were extracted for further analysis. During the analysis, confounding factors such as age, sex, years of education, and total intracranial volume were adjusted. Results are shown below. Figure 2 .

[0049] (2) DAT-SPECT imaging:

[0050] (2.1) Equipment selection: Single photon emission computed tomography (SPECT) equipment is used, combined with a high-resolution detector to ensure high sensitivity and high resolution of imaging.

[0051] (2.2) Imaging Procedure: Patients underwent SPECT scans 120 minutes after injection of the radiotracer [^123^I]-FP-CIT. Scan parameters included: matrix size = 128 × 128, acquisition time = 30 minutes. After scanning, images were iteratively reconstructed and normalized using the Montreal Neuroscience Institute (MNI) standard space.

[0052] (2.3) Data Analysis: DAT-SPECT images were analyzed using PMOD software to identify regions of interest (ROIs) in the bilateral caudate nucleus, putamen, and occipital cortex. The striatal binding ratio (SBR) for each ROI was calculated, and the differences in SBR values ​​among patients with different genotypes were compared. Figure 3 The analysis results indicate that the GALC gene variant has a limited impact on dopamine transport function, suggesting that its impact on cognitive decline is mainly achieved through non-dopaminergic mechanisms.

[0053] 3. Olfactory function assessment:

[0054] Olfactory function assessment is a crucial component of this invention. It quantifies a patient's olfactory function status through standardized olfactory tests. By combining standardized olfactory tests (such as UPSIT or SS-16), the patient's olfactory function level is assessed. These olfactory tests provide an accurate assessment of the patient's olfactory function status, offering a basis for early diagnosis and risk assessment.

[0055] The specific steps for assessing olfactory function are as follows:

[0056] (3.1) Selection of testing tools: Appropriate olfactory testing tools are selected based on the patient's specific condition and research needs. In this invention, two standardized olfactory testing tools are primarily used: the University of Pennsylvania Olfactory Identification Test (UPSIT) and the 16-item olfactory bar test (SS-16). The UPSIT test includes 40 odors and assesses the patient's ability to identify odors, classifying olfactory function into three levels: normal olfaction (normosmia), hyposmia, and anosmia. The SS-16 test assesses the patient's ability to identify and distinguish 16 odors, classifying olfactory function into two levels: normal olfaction (≥8 points) and olfactory dysfunction (<8 points).

[0057] (3.2) Testing Procedure: Before the test, the patient should be given detailed instructions and guidance to ensure that they understand the testing procedure and requirements. During the test, the patient needs to identify and distinguish different odors within a specified time and record the results in the test form. After the test, the patient's olfactory function status is assessed based on the patient's score.

[0058] (3.3) Results Analysis: The olfactory test results were combined with the gene detection results to analyze the association between olfactory dysfunction and GALC gene variants. The results are shown in [link to results]. Figure 1 Statistical analysis, using longitudinal data, revealed the correlation between olfactory dysfunction and cognitive decline. The results are detailed in [link to relevant documentation]. Figure 4 .

[0059] Data analysis is the core component of this invention. By comprehensively analyzing gene testing results, olfactory function assessments, and neuroimaging data, it reveals the impact of GALC gene variations on olfactory function and cognitive performance. The data analysis module, based on a multimodal dataset, employs structural equation modeling (SEM) to analyze the influence of gene variations in Parkinson's disease biomarkers on olfactory dysfunction and cognitive decline in Parkinson's disease patients. The specific components of the SEM are detailed below. Figure 5 This study uses structural equation modeling (SEM) to comprehensively analyze the complex relationships between GALC gene variations, brain structural changes, olfactory function, and cognitive performance, providing a basis for the early diagnosis and intervention of Parkinson's disease. SEM analysis reveals the direct impact of GALC gene variations on olfactory function, as well as the indirect impact on cognitive performance through brain structural changes, offering a new perspective for understanding the pathological mechanisms of Parkinson's disease.

[0060] The specific steps of data analysis are as follows:

[0061] (1) Statistical analysis: Structural equation modeling (SEM) was used to analyze the complex relationships between GALC gene variations, brain structural changes, olfactory function, and cognitive performance. The SEM model can simultaneously assess both direct pathways (such as the direct impact of gene variations on olfactory function) and indirect pathways (such as the indirect impact of gene variations on cognitive performance through brain structural changes). The standardized path coefficients and their statistical significance (P-value) of each pathway were calculated using the Wald test to assess the causal relationships among the variables.

[0062] (2) Interpretation of results: See Figure 5The analysis showed that variations at the rs8005172 locus of the GALC gene have a significant direct impact on olfactory function (path coefficient = -0.2, P < 0.01), and indirectly affect cognitive performance through changes in gray matter volume in the right superior temporal gyrus (path coefficient = -0.339, P < 0.001). These results indicate that variations in the GALC gene not only affect olfactory function but also influence cognitive performance by altering brain structure, providing a novel biomarker for the early diagnosis and intervention of Parkinson's disease.

[0063] It should be noted that the embodiments of the present invention have better implementability and are not intended to limit the present invention in any way. Any person skilled in the art may use the above-disclosed technical content to change or modify it into equivalent effective embodiments. However, any modifications or equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. Early biomarkers for cognitive impairment in Parkinson's disease, characterized in that, The biomarker is the GALC gene.

2. The early biomarker for cognitive impairment in Parkinson's disease as described in claim 1, characterized in that, The biomarker is the rs8005172 site of the GALC gene.

3. The application of the early biomarkers of Parkinson's disease cognitive impairment as described in claim 1 or 2 in the preparation of early diagnostic kits for Parkinson's disease cognitive impairment.

4. The application as described in claim 3, characterized in that, The diagnostic kit includes reagents for detecting the expression level of the biomarker, and the reagents include specific primers designed for the biomarker.

5. The application as described in claim 4, characterized in that, The sequence of the specific primer is as follows: F: TGGCTTCTAGTTTGCCATAGA; R:CAGAAGAAACATCTATGGCAAAC.

6. The application as described in claim 4, characterized in that, The diagnostic kit includes a kit for detecting the mRNA gene expression level of the biomarker or a kit for detecting the corresponding protein expression level of the biomarker.

7. The intelligent analysis system for early biomarkers of cognitive impairment in Parkinson's disease as described in claim 1 or 2, characterized in that, include: The data integration module is used to acquire gene detection results of Parkinson's disease biomarkers, olfactory test scores and neuroimaging data, and to standardize different data types to construct a multimodal dataset. The data analysis module is used to analyze the impact of genetic variations of Parkinson's disease biomarkers on olfactory dysfunction and cognitive decline in Parkinson's disease patients using structural equation modeling (SEM) based on a multimodal dataset.

8. The Parkinson's disease intelligent analysis system as described in claim 7, characterized in that, The Parkinson's disease biomarker is the GALC gene.

9. The Parkinson's disease intelligent analysis system as described in claim 8, characterized in that, The Parkinson's disease biomarker is the rs8005172 site of the GALC gene.

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