Application of circulating protein IFI30 in risk prediction of long-term arrhythmia of epileptic and screening method of circulating protein IFI30

Abstract

The invention provides application of circulating protein IFI30 in predicting the long-term arrhythmia risk of an epilepsy patient and a screening method of the circulating protein IFI30, relates to the technical field of biology and medicine, proves the association between the circulating protein IFI30 and the long-term arrhythmia risk of the epilepsy patient, and can evaluate the long-term arrhythmia risk of the epilepsy patient by detecting the level of IFI30. The invention provides a novel thought and method for risk prediction, diagnosis, treatment and prognosis evaluation of the long-term arrhythmia of the epileptic.

Description

Technical Field

[0001] The present invention belongs to the field of biology and medicine technology, and specifically relates to an application of circulating protein IFI30 in predicting the long-term arrhythmia risk in epileptic patients and a screening method thereof. Background Art

[0002] Epilepsy is one of the most common serious brain diseases. Studies have found that people with epilepsy have a much higher risk of heart complications than the general population, especially arrhythmia. [1] Long-term epileptic seizures can cause patients to suffer from repeated myocardial ischemia, changes in cardiac structure, and imbalances in the function of the autonomic nervous system. This is defined as "epileptic heart", which means that due to repeated surges of catecholamines and hypoxemia, cardiac electrophysiological and mechanical dysfunction, as well as adverse reactions to certain anti-epileptic drugs, the heart and coronary artery system are damaged. [2] These pathophysiological changes form the basis for the development of arrhythmia in patients with epilepsy, leading to premature death in patients with epilepsy. [2] Therefore, early identification of epileptic people at high risk of arrhythmia, active early prevention and intervention, and reduction of the risk of premature death in epileptic people is a public health cause of great significance.

[0003] However, current studies have only confirmed that epilepsy patients have an increased risk of long-term arrhythmias, and no study has yet provided biomarkers that can be used to predict the long-term risk of arrhythmias in epilepsy patients. Exploring these possible biomarkers can promote early screening, early diagnosis and early intervention in high-risk groups, reduce the burden of cardiovascular disease in epilepsy patients, and improve the long-term prognosis of epilepsy patients.

[0004] [1] Wang J, Huang P, Yu Q, et al. Epilepsy and long-term risk of arrhythmias. Eur Heart J. 2023;44(35):3374-3382. doi:10.1093 / eurheartj / ehad523 [2] Verrier RL, Pang TD, Nearing BD, Schachter SC. Epileptic heart: Aclinical syndromic approach. Epilepsia. 2021;62(8):1780-1789. doi:10.1111 / epi.16966 Summary of the invention In order to solve the above problems, the present invention provides an application of circulating protein IFI30 in predicting the long-term arrhythmia risk in epileptic patients and a screening method thereof.

[0005] In one aspect, the present invention provides a biomarker for predicting the long-term risk of arrhythmia in patients with epilepsy.

[0006] Specifically, the biomarker is IFI30, having an amino acid sequence as shown in SEQ ID NO.1.

[0007] SEQ ID NO.1: MTLSPLLLFLPPLLLLLDVPTAAVQASPLQALDFFGNGPPVNYKTGNLYLRGPLKKSNAPLVNVTLYYEALCGGCRAFLIRELFPTWLLVMEILNVTLVPYGNAQEQNVSGRWEFKCQHGEEECK FNKVEACVLDELDMELAFLTIVCMEEFEDMERSLPLCLQLYAPGLSPDTIMECAMGDRGMQLMHANAQRTDALQPPHEYVPWVTVNGKPLEDQTQLLTLVCQLYQGKKPDVCPSSTSSLRSVCFK.

[0008] In another aspect, the present invention provides a method for screening biomarkers of long-term arrhythmia risk in patients with epilepsy, the screening method comprising the following steps: S1: Screening for circulating protein markers that are associated with both epilepsy and atrial fibrillation and have consistent effects in genomic and transcriptomic data; S2: Multiple linear regression models were used to test the association between epilepsy and circulating protein markers screened in S1; S3: Cox proportional hazard regression model was used to test the association between the circulating protein markers screened in S1 and the incidence of atrial fibrillation; The common circulating protein IFI30 screened out in S2 and S3 is a circulating protein marker associated with the long-term risk of arrhythmias in patients with epilepsy.

[0009] Specifically, in S1, the screening method includes linkage disequilibrium regression analysis and / or single-cell transcriptome analysis.

[0010] More specifically, the covariates of the multivariate linear regression model in S2 and the Cox proportional hazard regression model in S3 include, but are not limited to: demographic characteristics, lifestyle and / or routine clinical medical characteristics.

[0011] More specifically, the demographic characteristics include, but are not limited to, at least one of age, gender, race and / or income.

[0012] More specifically, the lifestyle characteristics include, but are not limited to: at least one of: smoking status, drinking status and / or physical activity.

[0013] More specifically, the routine clinical medical characteristics include, but are not limited to, at least one of body mass index, ischemic heart disease, heart failure, stroke, dementia, brain injury, hypertension, diabetes, hyperthyroidism and obstructive sleep apnea syndrome.

[0014] In yet another aspect, the present invention provides use of the circulating protein IFI30 in the preparation of a product for predicting the long-term risk of arrhythmia in epilepsy patients.

[0015] Specifically, the products include but are not limited to: chips, test kits, test strips, test cards or microfluidic devices.

[0016] More specifically, the steps of using the product include: (1) Detect the content of circulating protein IFI30 in the sample; (2) Assess the long-term risk of arrhythmia in patients with epilepsy based on the level of circulating protein IFI30.

[0017] In yet another aspect, the present invention provides a kit for predicting the long-term risk of arrhythmia in epilepsy patients.

[0018] Specifically, the kit includes a reagent for detecting the content of IFI30 in a sample.

[0019] More specifically, the reagent includes an antibody and / or a ligand that specifically recognizes the IFI30 protein.

[0020] Specifically, the test samples include: plasma, PBMC, whole blood, serum and / or peripheral blood.

[0021] Specifically, the kit detects the IFI30 protein content by one of protein immunoblotting, immunohistochemistry, immunofluorescence or enzyme-linked immunosorbent assay.

[0022] Compared with the prior art, the present invention has the following advantages: The IFI30 circulating protein screened out in the present invention can be used to assess the long-term arrhythmia risk of epilepsy patients, which is conducive to improving the monitoring and assessment methods of the long-term arrhythmia risk of epilepsy patients, improving treatment strategies, and reducing premature deaths caused by arrhythmia in epilepsy patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Volcano plot for screening circulating protein markers associated with epilepsy using linkage disequilibrium regression analysis.

[0024] Figure 2Volcano plot for screening circulating protein markers associated with atrial fibrillation using linkage disequilibrium regression analysis.

[0025] Figure 3 A volcano plot showing differential expression between epileptic and non-epileptic patients using single-cell transcriptome data.

[0026] Figure 4 A volcano plot showing differential expression between patients with atrial fibrillation and those without atrial fibrillation using single-cell transcriptome data.

[0027] Figure 5 Population validation of circulating protein markers for predicting long-term arrhythmia risk in patients with epilepsy - forest plot of the association between epilepsy and circulating proteins.

[0028] Figure 6 To validate circulating protein markers for predicting long-term arrhythmia risk in patients with epilepsy - forest plot of the association between circulating proteins and the incidence of atrial fibrillation. DETAILED DESCRIPTION

[0029] The present invention will be further described in detail below in conjunction with specific examples. The following examples are not intended to limit the present invention, but are only intended to illustrate the present invention. The experimental methods used in the following examples are generally conventional, unless otherwise specified, and the materials, reagents, etc. used in the following examples are commercially available, unless otherwise specified.

[0030] Terms and Claims of the Present Invention: As used herein, the articles "a," "an," and "the" include plural referents unless expressly limited to one or more referents otherwise.

[0031] As used herein, numerical ranges: Unless otherwise expressly indicated, all ranges or ratios disclosed herein will be understood to include any and all sub-ranges or sub-ratios contained therein. For example, a stated range or ratio of 1 to 30 should be considered to be inclusive between a minimum of 1 and a maximum of 30, and any sub-ranges or sub-ratios, integers, decimals, or sub-ranges or sub-ratios consisting of integers or decimals, including the end points.

[0032] All disease diagnoses mentioned in the embodiments of the present invention are defined according to the 10th edition of the International Classification of Diseases (ICD-10), as shown in Table 1. The specific sources of the genome-wide association study data (Genome-Wide Association Studies, GWAS) used in the embodiments of the present invention are shown in Table 2.

[0033] Table 1 Disease diagnosis codes in the embodiments of the present invention

[0034] Table 2 Sources of GWAS data in this example

[0035] Example 1 Screening for candidate circulating protein markers for long-term arrhythmia risk in patients with epilepsy In order to screen candidate circulating protein markers that can be used to predict the risk of arrhythmias in patients with epilepsy, we extracted GWAS summary data of 2921 circulating proteins and used linkage disequilibrium score regression (LDSC) (https: / / github.com / bulik / ldsc / ) to evaluate the genetic correlation between epilepsy and circulating proteins, and between circulating proteins and atrial fibrillation, and screened out circulating proteins that were associated with both epilepsy and atrial fibrillation and had the same effect direction as candidate markers. The default parameters were used in the LDSC analysis process.

[0036] LDSC analysis revealed that 200 and 471 circulating proteins were associated with epilepsy and atrial fibrillation, respectively (P value < 0.05) ( Figure 1 and Figure 2 ). Among them, 145 circulating proteins were positively correlated with epilepsy, and 55 were negatively correlated with epilepsy; 336 circulating proteins were positively correlated with atrial fibrillation, and 135 were negatively correlated with atrial fibrillation. Combined with the above findings, a total of 96 circulating proteins were genetically associated with both epilepsy and atrial fibrillation, and the effect direction was consistent.

[0037] At the same time, to further clarify the association between the above-screened circulating proteins and epilepsy and atrial fibrillation, we obtained two single-cell transcriptome sequencing data related to epilepsy and atrial fibrillation in the Gene Expression Omnibus (GEO) database (GSE190452, GSE224959). After data processing and quality control according to Seurat standards (epilepsy: nFeature_RNA>200; nFeature_RNA<12,000; percent.mt<25; atrial fibrillation: nFeature_RNA>200; nFeature_RNA<6,000; percent.mt<25) to exclude low-quality cells, 69,599 and 41,544 cells were retained in the epilepsy and atrial fibrillation datasets, respectively, and then single-cell differential expression analysis was performed (log2FC>0.5, Bonferroni-corrected P value<0.05).

[0038] The results showed that epilepsy and atrial fibrillation had 279 common differentially expressed genes, of which 255 were up-regulated and 24 were down-regulated ( Figure 3 and Figure 4 ).

[0039] Combining the results of LDSC and single-cell differential expression analysis, we found that 11 circulating proteins were associated with epilepsy and atrial fibrillation at both the genomic and transcriptomic levels ( Figure 1-Figure 4 ), may be a candidate marker for the occurrence of arrhythmias in patients with epilepsy.

[0040] Example 2 Validation of candidate circulating protein markers in the human population In this example, UK Biobank (UKB) population data were used. Participants with circulating protein data in UKB were included in this example, and participants who met any of the following conditions were excluded: (1) participants with atrial fibrillation at or before baseline; (2) participants who developed epilepsy during follow-up; (3) participants with missing covariates.

[0041] Exposure definition: Epilepsy was identified based on the date of first occurrence of epilepsy (ICD-10: G40, G41) in the UKB database.

[0042] Outcome Definitions: Atrial fibrillation was identified based on ICD-10 diagnosis data (I48). The follow-up endpoint was defined as the time of atrial fibrillation onset, death, or October 31, 2022, whichever occurred first.

[0043] Covariates: age, sex, race, body mass index, smoking status, alcohol drinking status, physical activity, income, and comorbidities diagnosed according to ICD-10 codes (ischemic heart disease, heart failure, stroke, dementia, brain injury, hypertension, diabetes, hyperthyroidism, and obstructive sleep apnea syndrome).

[0044] First, we tested the association between epilepsy and the above-screened circulating protein markers using a multivariate linear regression model. Then, we used a Cox proportional hazards regression model to study the relationship between the screened circulating protein markers and the onset of atrial fibrillation. Circulating proteins that are associated with both epilepsy and atrial fibrillation and have the same effect direction are considered to be circulating protein markers that predict the long-term risk of arrhythmias in patients with epilepsy.

[0045] The results of multivariate linear regression analysis showed that 4 of the 11 candidate circulating proteins were related to epilepsy, and after Bonferroni multiple calibration, only IFI30 was related to epilepsy. At the same time, Cox proportional hazard regression analysis showed that 8 of the 11 candidate circulating protein markers were associated with an increased risk of atrial fibrillation, and circulating protein IFI30 was the only circulating protein associated with both epilepsy and atrial fibrillation ( Figure 5 and Figure 6), which can be applied to predict the long-term risk of arrhythmias in patients with epilepsy.

[0046] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A biomarker for predicting the long-term risk of arrhythmia in patients with epilepsy, characterized in that: The biomarker is IFI30, which has an amino acid sequence as shown in SEQ ID NO.

1.

2. The biomarker screening method according to claim 1, characterized in that: The following steps are involved: S1: Screening for circulating protein markers that are associated with both epilepsy and atrial fibrillation and have consistent effects in genomic and transcriptomic data; S2: Multiple linear regression models were used to test the association between epilepsy and circulating protein markers screened in S1; S3: Cox proportional hazard regression model was used to test the association between the circulating protein markers screened in S1 and the incidence of atrial fibrillation; The common circulating protein IFI30 screened out in S2 and S3 is a circulating protein marker associated with the long-term risk of arrhythmias in patients with epilepsy.

3. The screening method according to claim 2, characterized in that In S1, the screening method includes linkage disequilibrium regression analysis and / or single cell transcriptome analysis.

4. The screening method according to claim 2, characterized in that The covariates of the multivariate linear regression model in S2 and the Cox proportional hazards regression model in S3 included demographic characteristics, lifestyle behaviors and / or routine clinical medical characteristics.

5. The screening method according to claim 4, characterized in that The demographic characteristics include at least one of age, gender, race and / or income.

6. The screening method according to claim 4, characterized in that The lifestyle characteristics include at least one of smoking status, drinking status and / or physical activity.

7. The screening method according to claim 4, characterized in that The clinical medical routine characteristics include at least one of body mass index, ischemic heart disease, heart failure, stroke, dementia, brain injury, hypertension, diabetes, hyperthyroidism and / or obstructive sleep apnea syndrome.

8. Use of circulating protein IFI30 in the preparation of a product for predicting the long-term risk of arrhythmia in epilepsy patients, characterized in that: The products include: chips, test kits, test strips, test cards or microfluidic devices.

9. The use according to claim 8, characterized in that: The steps for using the product include: (1) Detect the content of circulating protein IFI30 in the sample; (2) Assess the long-term risk of arrhythmia in patients with epilepsy based on the level of circulating protein IFI30.

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