Kit for screening dilated cardiomyopathy

Abstract

The invention relates to a kit for screening dilated cardiomyopathy. The kit comprises a reagent for detecting one or more of genes of TP53, TNF, IL1beta, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8 and NFKBIA. The kit provided by the invention is high in detection efficiency and low in detection cost, provides important reference basis for diagnosis and prognosis judgment of patients with dilated cardiomyopathy, and can remarkably improve the survival rate of the patients.

Description

Technical Field

[0001] This invention relates to the field of biological detection, and more specifically to a kit for screening dilated cardiomyopathy. Background Technology

[0002] Dilated cardiomyopathy (DCM) is a myocardial disease of unknown etiology, characterized by left ventricular dilation and / or systolic dysfunction in the absence of abnormal stress conditions and severe coronary artery disease. Epidemiological studies indicate a global prevalence of approximately 1 / 2500-1 / 150, primarily affecting young adults, with a male-to-female ratio of 3:1. Current guidelines diagnose DCM clinically based primarily on the patient's clinical symptoms and signs, as well as electrocardiogram (ECG), echocardiogram, and cardiac MRI. DCM is a diagnosis of exclusion, ruling out hypertension, ischemic cardiomyopathy, valvular heart disease, etc., and lacks specific diagnostic methods for rapid early identification of DCM.

[0003] The widespread application of high-throughput sequencing technology in clinical practice has greatly accelerated the understanding of diabetic cerebral palsy (DCM) at the genetic level. To date, more than 60 genes encoding myosin, cytoskeletal proteins, and sarcolemma proteins have been identified as being associated with DCM. Although numerous studies have confirmed that many molecular markers are closely related to the occurrence and development of DCM, none have been applied to routine clinical testing to date, and most studies have not conducted clinical relevance analysis or prognostic analysis of genetic associations. Further experimental research is urgently needed to explore the early diagnosis and prognostic analysis of DCM.

[0004] There are currently no reports of kits that can efficiently screen for dilated cardiomyopathy. Summary of the Invention

[0005] To solve the above-mentioned technical problems, the present invention includes the following aspects:

[0006] A first aspect of the present invention provides a kit for screening dilated cardiomyopathy, the kit comprising reagents for detecting one or more of the genes TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8, and NFKBIA.

[0007] Preferably, the kit includes reagents for detecting one or more of the TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, and CXCL8 genes.

[0008] More preferably, the kit includes reagents for detecting one or more of the TNF, IL1β, TLR4 and UBB genes.

[0009] More preferably, the kit includes reagents for simultaneously detecting TNF, IL1β, TLR4 and UBB genes.

[0010] Preferably, the reagent for detecting the TP53 gene includes primer pairs as shown in SEQ ID NO. 1 and SEQ ID NO. 2; the reagent for detecting the TNF gene includes primer pairs as shown in SEQ ID NO. 3 and SEQ ID NO. 4; the reagent for detecting the IL1β gene includes primer pairs as shown in SEQ ID NO. 5 and SEQ ID NO. 6; the reagent for detecting the JUN gene includes primer pairs as shown in SEQ ID NO. 7 and SEQ ID NO. 8; the reagent for detecting the CD8A gene includes primer pairs as shown in SEQ ID NO. 9 and SEQ ID NO. 10; the reagent for detecting the TLR4 gene includes primer pairs as shown in SEQ ID NO. 11 and SEQ ID NO. 12; the reagent for detecting the UBB gene includes primer pairs as shown in SEQ ID NO. 13 and SEQ ID NO. 14; the reagent for detecting the CTLA4 gene includes primer pairs as shown in SEQ ID NO. 15 and SEQ ID NO. 16; and the reagent for detecting the CXCL8 gene includes primer pairs as shown in SEQ ID NO. 17 and SEQ ID NO. 18. The primer pair shown in NO.18, and the reagent for detecting the NFKBIA gene include the primer pairs shown in SEQ ID NO.19 and SEQ ID NO.20, and the specific primer sequences are shown in Table 2.

[0011] Preferably, the kit further includes Ficoll separation solution, RNA extraction reagent, reverse transcription reagent, and PCR system reagent.

[0012] Preferably, the RNA extraction reagent includes RNA lysis buffer, washbuffer, and solutionbuffer.

[0013] More preferably, the RNA extraction reagent is the RNA-Quick Purification Kit purchased from Shanghai Yishan Biotechnology Co., Ltd.

[0014] Preferably, the reverse transcription reagent includes EasyQuick RT MasterMix and enzyme-free water, wherein EasyQuick RT MasterMix contains Oligo(dT), Randomprimer, RNase Inhibitor, dNTP Mixture, and EQ-RT Buffer.

[0015] Preferably, the PCR system reagents include UltraSYBR Mixture and enzyme-free water.

[0016] Preferably, the sample used for testing with the kit is human venous blood.

[0017] A second aspect of the invention provides the use of a kit for detecting one or more of the genes TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8, and NFKBIA in the preparation of reagents for screening dilated cardiomyopathy.

[0018] Preferably, the present invention provides a kit for detecting one or more of the genes TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB and CXCL8 in the preparation of reagents for screening dilated cardiomyopathy.

[0019] More preferably, the present invention provides the use of a kit for detecting one or more of the TNF, IL1β, TLR4 and UBB genes in the preparation of reagents for screening dilated cardiomyopathy.

[0020] More preferably, the present invention provides a kit for simultaneously detecting TNF, IL1β, TLR4 and UBB genes, which is used in the preparation of reagents for screening dilated cardiomyopathy.

[0021] Preferably, the reagent for detecting the TP53 gene includes primer pairs as shown in SEQ ID NO. 1 and SEQ ID NO. 2; the reagent for detecting the TNF gene includes primer pairs as shown in SEQ ID NO. 3 and SEQ ID NO. 4; the reagent for detecting the IL1β gene includes primer pairs as shown in SEQ ID NO. 5 and SEQ ID NO. 6; the reagent for detecting the JUN gene includes primer pairs as shown in SEQ ID NO. 7 and SEQ ID NO. 8; the reagent for detecting the CD8A gene includes primer pairs as shown in SEQ ID NO. 9 and SEQ ID NO. 10; the reagent for detecting the TLR4 gene includes primer pairs as shown in SEQ ID NO. 11 and SEQ ID NO. 12; the reagent for detecting the UBB gene includes primer pairs as shown in SEQ ID NO. 13 and SEQ ID NO. 14; the reagent for detecting the CTLA4 gene includes primer pairs as shown in SEQ ID NO. 15 and SEQ ID NO. 16; and the reagent for detecting the CXCL8 gene includes primer pairs as shown in SEQ ID NO. 17 and SEQ ID NO. 18. The primer pair shown in NO.18, and the reagent for detecting the NFKBIA gene include the primer pairs shown in SEQ ID NO.19 and SEQ ID NO.20, and the specific primer sequences are shown in Table 2.

[0022] Preferably, the kit further includes Ficoll separation solution, RNA extraction reagent, reverse transcription reagent, and PCR system reagent.

[0023] Preferably, the RNA extraction reagent includes RNA lysis buffer, washbuffer, and solutionbuffer.

[0024] More preferably, the RNA extraction reagent is the RNA-Quick Purification Kit purchased from Shanghai Yishan Biotechnology Co., Ltd.

[0025] Preferably, the reverse transcription reagent includes EasyQuick RT MasterMix and enzyme-free water, wherein EasyQuick RT MasterMix contains Oligo(dT), Randomprimer, RNase Inhibitor, dNTP Mixture, and EQ-RT Buffer.

[0026] Preferably, the PCR system reagents include UltraSYBR Mixture and enzyme-free water.

[0027] Preferably, the sample used for testing with the kit is human venous blood.

[0028] The technical effects of this invention are as follows:

[0029] 1. This invention provides a kit for real-time quantitative PCR detection of mRNAs of genes such as TNF, TLR4, IL1β, and UBB in peripheral blood. This kit obtains cDNA from mRNA through reverse transcription, and then, combined with real-time quantitative PCR detection technology, can quantitatively detect the expression levels of the aforementioned gene mRNAs. This kit offers high detection efficiency and low cost.

[0030] 2. The kit provided by this invention can be used in clinical and scientific research to detect the expression of mRNA of genes such as TNF, TLR4, IL1β, and UBB in the peripheral blood of patients, providing an important reference for the diagnosis and prognosis of patients with dilated cardiomyopathy (DCM) and improving the survival rate of patients. Attached Figure Description

[0031] Figure 1 This is a graph showing the data processing and identification results of differentially expressed genes in this invention. Figure 1 A shows the PCA plots of the DCM group and the control group after removing the batch effect; Figure 1 B shows the results of the number of upregulated and downregulated genes in differentially expressed genes; Figure 1 C represents the volcano diagram of differentially expressed genes; Figure 1 D is a heatmap of differentially expressed genes; Figure 1 E is a bubble chart of the results of the differential gene GO enrichment analysis; Figure 1 F is a bubble chart of the differential gene KEGG analysis results;

[0032] Figure 2 PPI network diagram of ten key differentially expressed genes: TP53, TNF, IL1β, TLR4, JUN, CD8A, UBB, CTLA4, CXCL8, and NFKBIA.

[0033] Figure 3 The relative expression levels of TP53, TNF, IL1β, TLR4, JUN, CD8A, UBB, CTLA4, CXCL8, and NFKBIA in peripheral blood of the dilated cardiomyopathy group and the control group (CON: control group; DCM: dilated cardiomyopathy group. *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001).

[0034] Figure 4 The results are ROC curve analysis of TP53, TNF, IL1β, TLR4, JUN, CD8A, UBB, CTLA4, CXCL8, and NFKBIA.

[0035] Figure 5 This is the result of ROC curve analysis of four genes: TNF, IL1β, TLR4, and UBB. Figure 5 A is a graph showing the relationship between the number of decision trees and the error rate; Figure 5 B is a gene importance ranking diagram based on the MeanDecreaseGini method; Figure 5 C represents the overall ROC curves for TNF, IL1β, TLR4, and UBB. Detailed Implementation

[0036] Experimental Example 1: Screening for predictive genes for dilated cardiomyopathy

[0037] 1. Research Subjects

[0038] Four patients with dilated cardiomyopathy (DCM) who were hospitalized in the Department of Cardiology of Hangzhou First People's Hospital in December 2020 were randomly selected as the DCM group, and five healthy individuals who underwent physical examinations at the same hospital during the same period and were matched for age and sex with the DCM group were selected as the control group. RNA transcriptome sequencing was performed on both groups. Furthermore, 52 DCM patients and 20 healthy controls who visited Hangzhou First People's Hospital from May 2021 to January 2022 were subsequently selected for validation. The diagnostic criteria for dilated cardiomyopathy were based on the 2016 European Society of Cardiology (ESC) and American Heart Association (AHA) recommendations and the 2018 Chinese Guidelines for the Diagnosis and Treatment of Dilated Cardiomyopathy: objective evidence of ventricular enlargement and reduced myocardial systolic function on echocardiography: ① Left ventricular end-diastolic (LVEDd) > 5.0 cm in women and LVEDd > 5.5 cm in men (or greater than 117% of the predicted value based on age and body surface area, i.e., 2 times the predicted value SD + 5%); ② Left ventricular ejection fraction (LVEF) The study criteria included: left ventricular fractional shortening (LVFS) <25% (Simpsons method); exclusion criteria: long-term heavy drinkers (men >80g / day, women >40g / day, for more than 5 years), those with rapid and persistent supraventricular arrhythmias, those with pericardial disease, those with coronary atherosclerotic heart disease, those with congenital cardiovascular disease, those with pulmonary heart disease, those with hypertension, those with valvular heart disease, and others including various secondary cardiomyopathies such as perinatal cardiomyopathy, cardiomyopathy caused by endocrine and metabolic diseases, and those with malignant tumors. This study followed the ethical standards outlined in the Declaration of Helsinki of the World Health Organization, was approved by the Ethics Committee of Hangzhou First People's Hospital, and all participants signed informed consent forms.

[0039] 2. Test methods

[0040] 2.1 Clinical Data Collection

[0041] The hospital's electronic medical record system meticulously recorded the clinical data of each research subject, including age, gender, body mass index, smoking, alcohol consumption, systolic blood pressure, diastolic blood pressure, heart rate, NYHA functional classification, history of diabetes, family history; blood routine, liver function, kidney function, blood glucose, coagulation function, N-terminal pro-B-type natriuretic peptide (NT-ProBNP) and other laboratory indicators; echocardiographic indicators such as left ventricular ejection fraction (LVEF), left ventricular end-systolic diameter (LVIDS), left ventricular end-diastolic diameter (LVIDD), left atrial diameter (LAD) and other indicators; as well as information on drug treatment, surgery and device implantation.

[0042] 2.2 Echocardiography

[0043] After admission, study participants underwent routine transthoracic color Doppler echocardiography under double-blind conditions by two senior ultrasound physicians. Ultrasound was performed according to guidelines: patients were placed in the left lateral decubitus position, and left ventricular end-systolic diameter (LVIDS), left ventricular end-diastolic diameter (LVIDD), and left atrial diameter (LAD) were measured in a standard parasternal long-axis view. Left ventricular ejection fraction (LVEF) was measured using the biplane Simpson method. The Simpson method is defined as follows: the endocardial boundary is delineated in the apical four-chamber and apical two-chamber views, and the chamber length L (from the mitral annulus plane to the apex) is measured simultaneously. The system automatically calculates the LVEF value. All measurements are averages of three consecutive cardiac cycles.

[0044] 2.3 Peripheral blood collection and processing

[0045] All enrolled participants were fasting (12 hours) and approximately 4 ml of venous blood was drawn from their elbows by a nurse and placed in an anticoagulant tube containing EDTA.

[0046] (1) Take 4 ml of lymphocyte separation medium (Ficoll) and add it to a 15 ml centrifuge tube.

[0047] (2) Take an equal volume of PBS buffer to dilute the whole blood. Use a 1000ml pipette to slowly add the diluted blood sample along the inner wall of a 15ml centrifuge tube. Be careful to tilt the test tube and be gentle to ensure a clear interface between the Ficoll and the blood sample.

[0048] (3) Centrifuge at 25°C for 30 minutes at 300g speed.

[0049] (4) After centrifugation, the cells are separated into three layers. The middle layer, which is white and cloudy, is the peripheral blood mononuclear cells (PBMCs). Transfer the PBMCs to another 15ml centrifuge tube, add an equal volume of PBS buffer, and invert the tube to mix.

[0050] (5) Centrifuge at 25°C for 10 minutes at 500g speed.

[0051] (6) Discard the supernatant and keep the white precipitate. Add 1 ml of red blood cell lysis buffer, mix well by pipetting with a 1 ml pipette, and let stand for 5 minutes.

[0052] (7) Centrifuge at 25°C for 5 minutes at 300g. Discard the supernatant and keep the white precipitate. Add 500μl of LysisBuffer, label the precipitate, and store at -80°C.

[0053] (8) The above process shall be carried out within 2 hours after blood is drawn.

[0054] 2.4 Total RNA Extraction

[0055] Total RNA was extracted using the RNA-QuickPurification Kit (including RNA lysis buffer, wash buffer, and solution buffer) from Shanghai Yishan Biotechnology Co., Ltd., following these steps:

[0056] (1) Take a PBMC sample, add 500 μl of anhydrous ethanol, mix thoroughly by blowing and spitting 10 times, and transfer the liquid to a centrifuge column.

[0057] (2) Centrifuge at 25°C for 1 minute at 12000g speed and discard the waste liquid.

[0058] (3) Add 500 μl of Wash Buffer to the RNA column, centrifuge at 12000 g for 1 minute at room temperature (25°C). When taking the column, avoid contact between the waste liquid in the collection solution and the RNA column to prevent contamination. Discard the waste liquid and put the RNA column back into the collection tube. Centrifuge at 12000 g for 1 minute at room temperature (25°C).

[0059] (4) Place the RNA column on a clean, RNase-free 1.5ml centrifuge tube and let it air dry for 2 minutes.

[0060] (5) Add 20 μl of Elution Buffer to the center of the RNA column membrane and let stand at room temperature for 2 minutes.

[0061] (6) Centrifuge at 25°C for 1 minute at 12000g. Add the eluted RNA solution back into the RNA column, place on ice for 5 minutes, and centrifuge again for 1 minute to improve elution efficiency.

[0062] (7) The OD260 / 280 ratio was measured using a Nanodrop micro spectrophotometer, and the RNA concentration was determined. Samples with an OD260 / 280 ratio between 1.90 and 2.20 and an RNA concentration >30 ng / μl were retained.

[0063] 2.5 cDNA library construction and sequencing

[0064] (1) Use magnetic beads with Oligo(dt) to capture mRNA in total RNA.

[0065] (2) Add Fragmentation Buffer to randomly break the mRNA to obtain fragmented mRNA.

[0066] (3) Using mRNA as a template, the first cDNA chain was synthesized using a six-base random primer. Then, buffer, dNTPs, RNase H and DNA polymerase I were added to synthesize the second cDNA chain. The cDNA was purified using AMPure XP magnetic beads.

[0067] (4) The purified double-stranded cDNA was end-repaired, A-tailed and ligated with Illumina sequencing-specific adapters, and then fragment size was selected using AMPure XP beads;

[0068] (5) Obtain cDNA library by PCR enrichment.

[0069] (6) High-throughput sequencing was performed on an Illumina HiSeqX sequencer.

[0070] 2.6 Reverse transcription into cDNA

[0071] (1) Thaw the extracted RNA and EasyQuick RT MasterMix kit components on ice, vortex each solution to mix well and then briefly centrifuge before use.

[0072] (2) Prepare the reverse transcription reaction system according to the following table (all operations are performed on ice).

[0073] Table 1 RNA reverse transcription reaction system

[0074] reagents 10 μl reaction system Final concentration RNA template 2μl 50 ng / μl 5×EasyQuick RT MasterMix 2μl 1× RNase-Free Water up to 10μl

[0075] Note: 5×EasyQuick RT MasterMix contains Oligo(dT), Random primer, RNaseInhibitor, dNTP Mixture, EQ-RT Buffer, etc.

[0076] (3) Reverse transcription reaction conditions: incubate at 37℃ for 15 minutes; incubate at 85℃ for 5 seconds to inactivate reverse transcriptase.

[0077] 2.7 qRT-PCR

[0078] (1) Target genes: TP53, TNF, IL1β, JUN, CD8A, TLR, UBB, CTLA4, CXCL8, NFKBIA.

[0079] (2) Primer design for target gene

[0080] Table 2 Primer sequences

[0081]

[0082] (3) PCR reaction system

[0083] Table 3 PCR reaction system

[0084] reagents 25μl reaction system 2×UltraSYBR Mixture (Low ROX) 12.5μl forward primer 0.5μl reverse primer 0.5μl Template DNA 1μl <![CDATA[ddH2O]]> Add to 25 μl

[0085] (4) Reaction conditions

[0086] Table 4 PCR reaction conditions

[0087]

[0088] (5) PCR data processing

[0089] The reliability of the data was determined based on the differences in CT values ​​and the analysis of dissolution curves; using 2 -ΔΔct The formula is used to calculate the relative expression level of each gene; △△ct=(CT value of target gene in DCM group - CT value of internal reference gene in DCM group) -(CT value of target gene in control group - CT value of internal reference gene in control group).

[0090] 2.8 Bioinformatics Analysis

[0091] 2.8.1 Processing of raw sequencing data

[0092] According to NCBI's data standards, the raw data was quality controlled and low-quality reads were filtered out. The NCBI standards are as follows: (1) For a given read, at least 50% of the bases must have a sequencing quality value higher than Q30 (i.e., the sequencing error rate of a single base does not exceed 0.1%); (2) The number of base types in the read that did not accurately detect the target site must be less than 10% of the read length; (3) The number of consecutive base types that did not accurately detect the target site does not exceed 14. High-quality reads were aligned to the human reference genome (hg38) using Bowtie and Tophat2 software.

[0093] 2.8.2 Differential Gene Screening

[0094] Principal component analysis (PCA) was performed on gene expression levels in the DCM group and the control group using R language to verify whether there were differences between the two groups. The original expression matrix was analyzed using the "DESeq2" package to obtain differentially expressed genes, with default parameters: p-adjust < 0.01 and |log2(fold change)| >= 1. The distribution of differentially expressed genes was visualized using the "ggplot" package to create volcano plots and heatmaps.

[0095] 2.8.3 Enrichment analysis of differentially expressed genes

[0096] Using DAVID online tools ( https: / / david.nciferf.gov / GO analysis and KEGG pathway enrichment analysis were performed on differentially expressed genes. A false discovery rate (FDR) <0.01 was considered statistically significant. The GO and KEGG pathway enrichment analyses were visualized using the "ggplot" package in R, and bubble charts were generated.

[0097] 2.8.4 Construction of Protein-Protein Interaction Networks

[0098] Protein network interaction analysis was performed on differentially expressed genes using the STRING online database (https: / / cn.string-db.org / ). With a confidence level of 0.9, discrete proteins were removed to obtain the PPI network. Then, the CytoHubba plugin in Cytoscape software was used to sort the genes according to their degree values ​​to obtain the top 10 key genes.

[0099] 2.8.5 Random Forest

[0100] The "random Forest" package was used to perform random forest analysis on the ten key genes obtained to address the problem of insufficient sample size. Random forest is one of the most widely used machine learning algorithms. It can handle input samples with high-dimensional features without dimensionality reduction and can evaluate the importance of each feature in classification problems.

[0101] 2.8.6 Subgroup Analysis of Patients with Dilated Cardiomyopathy

[0102] Unsupervised consensus clustering was performed using the "ConsensusClusterPlus" package to group DCM patients based on the expression levels of key genes. Principal component analysis was used to determine whether the groups were independent, and heatmaps were generated for visualization.

[0103] 3. Follow-up

[0104] Patients in the DCM group were followed up continuously by telephone or outpatient visits for 12 months. The primary endpoint in this trial was cardiac readmission or cardiac death during the follow-up period; events not occurring during the follow-up period were defined as censored. Readmission and death were defined as follows: ① Readmission was defined as hospitalization due to a cardiac event (such as heart failure, angina, myocardial infarction, cardiac embolism, various arrhythmias, etc.); ② Death was defined as death caused by a cardiac event (including worsening heart failure, sudden cardiac death, etc.).

[0105] 4. Data statistical analysis

[0106] SPSS 25.0, GraphPad Prism 8, and R 4.2.1 software were used for analysis of the experimental cases. Normally distributed continuous data were expressed as mean ± standard deviation, and independent samples t-tests were used for comparisons between groups (NT-proBNP was non-normally distributed, but became normally distributed after logarithmic transformation); categorical data were expressed as frequency and percentage, and chi-square tests were used for comparisons between groups; ROC analysis was used to calculate the area under the curve (AUC) to evaluate specificity and sensitivity; binary logistic regression analysis was used to analyze the diagnostic value of key genes for dilated cardiomyopathy; Spearman correlation analysis and nonparametric tests were used to assess the clinical relevance of genes; Kaplan-Meier estimation was used to analyze the prognosis of patients with dilated cardiomyopathy for survival analysis, and the hazard ratio for the corresponding 95% confidence interval was calculated using the Log-Rank test, with P < 0.05 considered statistically significant.

[0107] 5. Test Results

[0108] 5.1 RNA Sequencing Data Processing and Identification

[0109] Peripheral blood RNA was sequenced from 4 DCM patients and 5 healthy controls. Principal component analysis (PCA) was used to reduce the dimensionality of the RNA sequencing data, confirming the existence of differences between the DCM group and the control group, which can be used for subsequent analysis. Figure 1 A). Using the "DESeq2" package, a total of 1918 differentially expressed genes were screened between the DCM group and the control group, of which 994 genes were upregulated and 924 genes were downregulated. The screening parameters were: p-adjust < 0.01 and |log2(fold change)| > 1. Figure 1 B, 1C). Cluster analysis showed that there were differences in the overall gene expression levels between the two groups ( Figure 1 D).

[0110] 5.2 Functional enrichment analysis of differentially expressed genes

[0111] To further elucidate the biological functions and signaling pathways associated with dilated cardiomyopathy, differentially expressed genes were analyzed using GO and KEGG signaling pathway analyses. GO analysis included three levels: biological processes (BP), cellular components (CC), and molecular functions (MF). In BP, genes were primarily associated with processes such as regulation of hematopoiesis, positive feedback cytokine production, T cell activation, adaptive immune responses, viral responses, cellular immunity to biological stimuli, positive regulation of leukocyte-cell adhesion, cellular immunity to lipopolysaccharide, and tRNA metabolism. In CC, genes were mainly enriched in the mitochondrial matrix, vacuolar membrane, early endosomes, lysosomal membrane, lysomnographic vacuolar membrane, tertiary granules, and specific granules. In MF, genes were mainly enriched in RNA catalytic activity, aminoacyl-tRNA ligase activity, C-oxygen bond ligase activity, and NAD+. + and NAD(P) + Nucleoside enzyme activity ( Figure 1 E). Furthermore, the enriched KEGG pathways mainly include herpes simplex virus type 1 infection, NOD-like receptor signaling pathway, lipid and atherosclerosis, transcriptional dysregulation in cancer, H1N1 infection, apoptosis, Toll-like receptor signaling pathway, C-type lectin receptor signaling pathway, viral protein interactions with cytokines and cytokine receptors, and the IL-17 signaling pathway (…). Figure 1 F).

[0112] 5.3 Construction of gene interaction networks and screening of key genes

[0113] Protein-protein network interaction analysis was performed on 1918 differentially expressed genes, resulting in a PPI network with 1627 nodes and 1543 lines. The network was then enhanced using Cytoscape software, and the Cyhubba plugin was used to select the 10 most associated hub genes: TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8, and NFKBIA. Figure 2 ).

[0114] 5.4. Verify the expression levels of key genes in the peripheral blood of patients with dilated cardiomyopathy.

[0115] To verify the reliability of the RNA sequencing data, this study collected peripheral blood samples from 52 patients with diabetic cerebral palsy (DCM) and 20 controls for qRT-PCR analysis. The qRT-PCR results showed that, consistent with high-throughput sequencing, the expression levels of TP53, TNF, IL1β, and TLR4 in the peripheral blood samples of DCM patients were significantly higher than those in the control group, while the expression levels of JUN, CD8A, UBB, CTLA4, CXCL8, and NFKBIA were significantly decreased. Figure 3 ).

[0116] 5.5 Diagnostic value of key genes in patients with dilated cardiomyopathy

[0117] ROC curve analysis was used to assess whether the peripheral blood expression levels of these key genes could distinguish between DCM patients and controls. The AUC values ​​of TP53, TNF, IL1β, TLR4, JUN, CD8A, UBB, CTLA4, CXCL8, and NFKBIA were 0.711, 0.716, 0.748, 0.735, 0.751, 0.762, 0.703, 0.652, 0.714, and 0.636, respectively. Figure 4 Except for CTLA4 and NFKBIA, the AUC values ​​of the other genes were all greater than 0.7, indicating good diagnostic predictive value.

[0118] Random forest analysis was used to screen for the more important genes among ten key genes. An optimal random forest model was constructed using mtry=3 and ntree=500, at which point the model error tended to plateau. Figure 5 A). Based on the MeanDecreaseGini method, seven key genes with MeanDecreaseGini > 2 (TNF, IL1β, TLR4, JUN, CD8A, UBB, CXCL8) were considered to have greater diagnostic value. Figure 5 B). These seven genes were then included in a multivariate logistic regression analysis. The p-values ​​for TNF, IL1β, TLR4, and UBB were less than 0.05 (Table 5), indicating that TNF, IL1β, TLR4, and UBB can serve as independent predictors for DCM diagnosis. The overall AUC value for these four genes was as high as 0.951 (…). Figure 5 C) suggests that they have high diagnostic value as a whole.

[0119] Table 5 Multivariate logistic regression of key genes

[0120] variable B SE WaldX2 P OR 95% CI TNF 2.70 1.02 7.09 0.008 14.92 2.04-109.20 IL1β 2.08 0.83 6.25 0.012 8.00 1.57-40.74 JUN -0.92 0.61 2.27 0.132 0.40 0.12-1.32 CD8A -1.24 1.00 1.56 0.212 0.29 0.04-2.03 TLR4 1.53 0.72 4.49 0.034 4.62 1.12-19.05 UBB -2.19 0.81 7.33 0.007 0.11 0.02-0.55 CXCL8 -1.62 0.88 3.37 0.066 0.20 0.04-1.12

[0121] Although specific embodiments of the invention have been described, those skilled in the art will recognize that various changes and modifications can be made to the invention without departing from its scope or spirit. Therefore, the invention is intended to cover all such changes and modifications falling within the scope of the appended claims and their equivalents.

Claims

1. A kit for screening dilated cardiomyopathy, characterized in that, The kit includes reagents for detecting one or more of the following genes: TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8, and NFKBIA.

2. The reagent kit according to claim 1, characterized in that, The kit includes reagents for detecting one or more of the TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, and CXCL8 genes.

3. The reagent kit according to claim 2, characterized in that, The kit includes reagents for detecting one or more of the TNF, IL1β, TLR4, and UBB genes.

4. The reagent kit according to claim 3, characterized in that, The kit includes reagents for the simultaneous detection of TNF, IL1β, TLR4 and UBB genes.

5. The reagent kit according to any one of claims 1-4, characterized in that, The kit is used to test human venous blood samples.

6. Application of kits for detecting one or more of the following genes: TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, CTLA4, CXCL8, and NFKBIA, in the preparation of reagents for screening dilated cardiomyopathy.

7. The application according to claim 6, characterized in that, The application is the use of a kit for detecting one or more of the TP53, TNF, IL1β, JUN, CD8A, TLR4, UBB, and CXCL8 genes in the preparation of reagents for screening dilated cardiomyopathy.

8. The application according to claim 7, characterized in that, The application is the use of a kit for detecting one or more of the TNF, IL1β, TLR4 and UBB genes in the preparation of reagents for screening dilated cardiomyopathy.

9. The application according to claim 8, characterized in that, The application described is the use of a kit for simultaneously detecting TNF, IL1β, TLR4 and UBB genes in the preparation of reagents for screening dilated cardiomyopathy.

10. The application according to any one of claims 6-9, characterized in that, The kit is used to test human venous blood samples.

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