Application of glycolysis disorder biomarker as Alzheimer disease diagnosis target

Abstract

The invention relates to the technical field of biological medicine, in particular to application of a glycolysis obstacle biomarker as an Alzheimer disease diagnosis target, and glycolysis genes are a GPI gene, a PFKM gene and an LDHA gene respectively. The GPI gene sequence is as shown in SEQ ID NO. 1. 1, and the sequence of the PFKM gene is as shown in SEQ ID NO. 2. And the LDHA gene sequence is as shown in SEQ ID NO. 3. ROC analysis is carried out to assess the differentiation of potential biomarkers in the brain to AD or MCI patients from a control group, and the expression quantities of GPI, PFKM and LDHA are significantly reduced in a punctiform manner. ROC analysis shows that GPI, PFKM and LDHA have relatively high diagnosis efficiency in each brain region.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to the application of a glycolysis disorder biomarker as a diagnostic target for Alzheimer's disease. Background Art

[0002] Alzheimer's disease (AD) is a neurodegenerative disease that progresses with age. Patients often present with cognitive impairment, memory loss, psychiatric symptoms, and behavioral disorders.

[0003] At present, the clinical diagnosis of AD mainly relies on asking medical history, cognitive function scale scoring, and the use of MRI scans, blood, cerebrospinal fluid and other technologies to make a pathological diagnosis of AD. Relying on asking medical history and cognitive function scale scoring, these methods are time-consuming and labor-intensive, and the detection accuracy is not high. In addition, when AD patients are diagnosed clinically, the disease has developed to the middle and late stages, which greatly affects the effective treatment of patients. Based on this situation, finding effective diagnostic markers and treatment methods for early AD is the key to delaying the development of AD pathology.

[0004] Glucose-6-phosphate isomerase (GPI) is one of the key enzymes in the glycolysis pathway, involved in the reversible conversion between glucose-6-phosphate and fructose-6-phosphate, which is the second step reaction in the glycolysis process. Phosphofructokinase-muscle type (PFKM) is a key rate-limiting enzyme in the glycolysis process, catalyzing the conversion of fructose-6-phosphate and ATP into fructose-1,6-bisphosphate and ADP. Lactate dehydrogenase A (LDHA) is the last enzyme in the glycolysis pathway, catalyzing the conversion of pyruvate into lactate and producing NADH. Glucose metabolism disorders, especially glycolysis arrest, are closely related to Alzheimer's disease (AD), but its systemic changes in AD have not been clearly defined. Therefore, exploring the relationship between glycolysis-related genes and AD is of great significance for the diagnosis and treatment targets of AD. Summary of the invention

[0005] The purpose of the present invention is to address the problems existing in the background technology and propose an application of a glycolysis disorder biomarker as a diagnostic target for Alzheimer's disease.

[0006] The technical solution of the present invention is the application of glycolysis disorder biomarkers as diagnostic targets for Alzheimer's disease, characterized in that the glycolysis genes are GPI gene, PFKM gene and LDHA gene respectively.

[0007] The GPI gene sequence is shown in SEQ ID NO.1.

[0008] The PFKM gene sequence is shown in SEQ ID NO.2.

[0009] The LDHA gene sequence is shown in SEQ ID NO.3.

[0010] A reagent for diagnosing Alzheimer's disease, which is a reagent for detecting the content of glycolysis genes in a biological sample.

[0011] Preferably, the glycolysis gene includes one or more combinations of GPI gene, PFKM gene or LDHA gene.

[0012] A kit for diagnosing Alzheimer's disease, comprising the above-mentioned reagent for diagnosing Alzheimer's disease.

[0013] Preferably, the kit further comprises SDS gel, a fixing membrane, a blocking solution, a diluent, a washing buffer and a color developing reagent.

[0014] Compared with the prior art, the present invention has the following beneficial technical effects:

[0015] The present invention discovers the application of glycolysis-related genes GPI gene, PFKM gene and LDHA gene as markers for AD diagnosis targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The glycolysis-related genes in the examples are significantly differentially expressed in AD brain tissue.

[0017] Figure 2 In the examples, the GSE1297-AD brain tissue transcriptome dataset was used to validate the candidate biomarkers.

[0018] Figure 3 : is the correlation between the confirmatory biomarkers and MMSE in AD brain tissue in the example.

[0019] Figure 4 : Correlation between the confirmatory biomarkers and tau pathology in AD brain tissue in the Examples.

[0020] Figure 5 : The expression of confirmatory biomarkers in different cognitive levels and tau pathology in the examples.

[0021] Figure 6 The figure shows the efficacy of GPI, PFKM and LDHA in the early diagnosis of AD in the examples.

[0022] Figure 7 To verify the effectiveness of GPI, PFKM, and LDHA in the early diagnosis of AD in the cohort in the example. DETAILED DESCRIPTION

[0023] Example 1

[0024] This example is used to illustrate that in a population database, the expression levels of glycolysis-related genes GPI, PFKM and LDHA in multiple brain regions of AD are continuously downregulated, and the reduced expression of GPI, PFKM and LDHA is closely related to the aggravation of cognitive dysfunction.

[0025] The brain datasets of AD patients used in this study were accessed through the Gene Expression Omnibus (GEO) database of the National Center for Biotechnology Information (NCBI).

[0026] The Alzdata database provides mRNA expression data of glycolysis-related genes in 269 AD patients (AD group) and 271 normal aging individuals (Ctrl group). The database contains four regions of the brain: medial cortex, hippocampus, temporal cortex, and frontal cortex. The detailed trend is represented by a heat map, with red indicating upregulation and blue indicating downregulation. Except for PGAM2, glycolysis-related genes were continuously downregulated in AD brains, and HK1, GPI, PFKM, ALDOA, PGK1, BPGM, ENO2, PKM, and LDHA were significantly reduced in multiple brain regions of AD ( Figure 1 ).

[0027] The candidate biomarkers were validated and analyzed using GSE1297-AD (Ctrl=9, inci-specific AD=7, Moderate AD=8, Severe AD=7) brain tissue transcriptomics, which was consistent with the Alzdata dataset and found that GPI, PFKM, PGK1, ENO2, and LDHA were significantly decreased in AD brain tissue ( Figure 2 ).

[0028] Pearson correlation analysis was performed on candidate biomarkers using the GSE1297-AD (Ctrl=9, inci-specific AD=7, ModerateAD=8, SevereAD=7) brain tissue transcriptomics dataset to explore the relationship between the mRNA expression of related genes and MMSE scores. We found that GPI, PFKM, and LDHA were positively correlated with MMSE scores (r=0.474-0.537, p<0.01; Figure 3 ).

[0029] Example 2

[0030] This example is used to illustrate that the reduction in the expression of glycolysis-related genes GPI, PFKM and LDHA accelerates tau pathology and participates in the whole process of AD cognitive dysfunction and tau pathology aggravation.

[0031] Pearson correlation analysis of candidate biomarkers using GSE84422 (Ctrl=214, AD=328) revealed that GPI, PFKM, ENO2, and LDHA were significantly negatively correlated with tau pathological grade, neurofibrillary tangles (NFT), and Braak stage (|r|=0.410-0.644, p<0.05, GSE1297, Figure 4 ;|r|=0.203-0.278,p<0.0001,GSE84422, Figure 4 ).

[0032] Verification of multiple GEO databases showed that GPI, PFKM and LDHA are key genes for brain glycolysis disorder in AD patients, and are closely related to cognitive dysfunction and tau pathology. Analysis of AlzCode (MSBB: Unclassified = 8, Ctrl = 40, MCI = 43, AD = 22) data revealed that the expression of GPI, PFKM and LDHA decreased significantly with the increase of CDR score and tau pathology stage ( Figure 5 ).

[0033] Example 3

[0034] This example is used to illustrate that GPI, PFKM and LDHA have high diagnostic efficiency in distinguishing AD or MCI patients from the control group, and can be used as potential biomarkers for early diagnosis of AD.

[0035] ROC analysis was performed to evaluate the potential biomarkers in the brain for distinguishing AD or MCI patients from the control group. In the HIP (Ctrl=66, AD=74), TC (Ctrl=39, AD=52), and AD (Ctrl=39, AD=39) regions of AD, the expression levels of GPI, PFKM, and LDHA were significantly decreased in a dot-like manner ( Figure 6 AC). ROC analysis showed that GPI, PFKM, and LDHA had high diagnostic efficiency in each brain region (HIP: AUC = 0.679-0.737, p < 0.001; TC: AUC = 0.754-0.7803, p < 0.0001; EC: AUC = 0.766-0.795, p < 0.0001; Figure 6 DF).

[0036] Example 4

[0037] By using the Minimum Cognitive Scale (MMSE) score on the normal aging population, 78 elderly people with cognitive impairment (MCI group, MMSE = 21-24, MCI is the early stage of AD) were identified, and 83 normal aging people of corresponding age matching (Ctrl group, MMSE = 28-30) were used to extract and separate monocytes from fresh blood samples using a monocyte extraction kit for subsequent gene level testing. Fluorescence quantitative PCR detection found that GPI, PFKM and LDHA were significantly reduced in monocytes of the MCI population ( Figure 7 AC). ROC analysis showed that GPI, PFKM and LDHA all had high diagnostic efficiency (GPI: AUC = 0.872, p < 0.0001; PFKM: AUC = 0.864, p < 0.0001; LDHA: AUC = 0.847, p < 0.0001; Figure 7 DF).

[0038] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. Application of glycolysis disorder biomarkers as diagnostic targets for Alzheimer's disease, characterized in that: The glycolysis genes are respectively GPI gene, PFKM gene and LDHA gene.

2. The use of the glycolysis disorder biomarker according to claim 1 as a diagnostic target for Alzheimer's disease, characterized in that: The GPI gene sequence is shown in SEQ ID NO.

1.

3. The use of the glycolysis disorder biomarker according to claim 1 as a diagnostic target for Alzheimer's disease, characterized in that: The PFKM gene sequence is shown in SEQ ID NO.

2.

4. The use of the glycolysis disorder biomarker according to claim 1 as a diagnostic target for Alzheimer's disease, characterized in that: The LDHA gene sequence is shown in SEQ ID NO.

3.

5. A reagent for diagnosing Alzheimer's disease, characterized in that: The reagent is a reagent for detecting the content of glycolysis genes in a biological sample.

6. The reagent for diagnosing Alzheimer's disease according to claim 5, characterized in that: The glycolysis gene includes one or more combinations of GPI gene, PFKM gene or LDHA gene.

7. A kit for diagnosing Alzheimer's disease, characterized in that: A reagent for diagnosing Alzheimer's disease comprising claim 5 or 6.

8. The kit for diagnosing Alzheimer's disease according to claim 7, characterized in that: The kit also includes SDS gel, a fixing membrane, a blocking solution, a diluent, a washing buffer solution and a color developing reagent.

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