A marker for evaluating COVID-19 vaccine immune status and application thereof

Abstract

This invention discloses a biomarker for evaluating the immune status of COVID-19 vaccines and its application. The biomarker includes any one or a combination of at least two of the following SARS-CoV-2 viral peptides: M1, N16, N24, S15, S39, S44, S64, S82, S95, S104, or S115. This invention accurately identifies differences in peptide-specific antibody responses between asymptomatic and symptomatic patients. Through clustering heatmaps, it determines the differences in responses to peptides such as M1, N24, S15, S64, S82, S104, and S115 between vaccinated individuals and infected individuals. This effectively distinguishes between infected patients and vaccinated individuals, as well as between asymptomatic and symptomatic patients, providing a reference for COVID-19 treatment and peptide vaccine development.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology and relates to a biomarker for evaluating the immune status of COVID-19 vaccines and its application. Background Technology

[0002] COVID-19 is a novel respiratory infectious disease caused by SARS-CoV-2. SARS-CoV-2 is an RNA virus with an unstable, single-stranded positive strand that is prone to mutation, resulting in a series of novel coronavirus variants, such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). With the widespread attention given to the mutations of SARS-CoV-2, understanding the specificity of immunity to SARS-CoV-2 proteins is increasingly important for comprehending changes in antibody-reactive proteins in humans and their impact on acquired and vaccine-induced immunity.

[0003] Traditional antibody detection methods include serological testing and indirect immunofluorescence detection. In recent years, the use of protein microarrays has increased. This method immobilizes small molecules, such as peptides and proteins, on microfabricated surfaces for high-throughput screening studies. Protein chip technology allows for the screening of unknown antibodies against a specific antigen based on the affinity characteristics of different components of a protein. This rapid proteomics chip for the novel coronavirus is characterized by high accuracy, low sample consumption, simple operation, and speed, making it an effective diagnostic tool for novel coronavirus infection.

[0004] The increasing number of outbreaks caused by Severe Acute Respiratory Syndrome (SARS), Ebola, and coronavirus variants over the past decade has highlighted the importance of rapid disease diagnosis and vaccine development. Therefore, identifying biomarkers for diagnostic measures and antigenic targets for vaccine development has become increasingly crucial. Peptide microarrays can display a large number of putative target proteins that are rapidly translated into overlapping linear (and circulating) peptides, enabling multi-pathway high-throughput antibody analysis.

[0005] In conclusion, identifying and evaluating the immune status of COVID-19 vaccines is crucial for vaccine development. Summary of the Invention

[0006] To address the shortcomings of existing technologies and practical needs, this invention provides a biomarker for evaluating the immune status of COVID-19 vaccines and its application. This invention identifies antibody-binding peptide epitopes and uses SARS-CoV-2 specific antibody profiles to effectively analyze and evaluate the immune status of COVID-19 vaccines, with broad application prospects, such as distinguishing COVID-19 patients from vaccinated and asymptomatic individuals, and evaluating vaccine efficacy, etc.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a biomarker for evaluating the immune status of a COVID-19 vaccine, the biomarker comprising any one or a combination of at least two of the following peptides of SARS-CoV-2 virus: M1 peptide, N16 peptide, N24 peptide, S15 peptide, S39 peptide, S44 peptide, S64 peptide, S82 peptide, S95 peptide, S104 peptide, or S115 peptide.

[0009] This invention used cluster heatmaps to determine the differences in responses to peptides M1, N24, S15, S64, S82, S104, and S115 between vaccinated individuals and infected individuals. Recipient operating characteristic (ROC) curve analysis showed that the combined diagnostic efficacy of S15, S64, and S104 could distinguish infected patients from vaccinated individuals. Asymptomatic patients showed stronger specific antibody responses to S15, S64, and S104 peptides than symptomatic patients, while their specific antibody responses to M1, N24, S82, and S115 peptides were weaker. Furthermore, two peptides (N24 and S115) were correlated with neutralizing antibody levels.

[0010] In this invention, ROC analysis was performed on vaccinated patients and infected patients using three markers: S64, S15, and S104. The results showed that S64, S15, and S104 exhibited good sensitivity and specificity in distinguishing between patients and vaccine recipients, with a combined diagnostic sensitivity and specificity of 91.3% and 99.2%, respectively. ROC analysis was also performed on S64, S15, and S104 (highly expressed in AP) and M1, N24, S82, and S115 (lowly expressed). The sensitivities of S64, S15, and S104 in distinguishing between AP and symptomatic patients were 94.1%, 86.3%, and 96.1%, respectively. The specificities of M1, N24, S82, and S115 were 94.1%, 92.2%, 86.3%, and 98%, respectively. The predictive sensitivity and specificity for combined diagnosis were 94.1% and 85.3%, respectively, indicating that these markers can serve as biomarkers for distinguishing between AP and symptomatic patients.

[0011] S15:LGVYYHKNNKSWMESEFRVY.

[0012] S39: GVSPTKLNDLCFTNVYADSF.

[0013] S44:GCVIAWNSNNLDSKVGGNYN.

[0014] S64: PTWRVYSTGSNVFQTRAGCL.

[0015] S82: KPSKRSFIEDLLFNKVTLAD.

[0016] S95: TASALGKLQDVVNQNAQALN.

[0017] S104: ECVLGQSKRVDFCGKGYHLM.

[0018] S115: LQPELDSFKEELDKYFKNHT.

[0019] M1: MADSNGTITVEELKKLLEQW.

[0020] N16:PANNAAIVLQLPQGTTLPKG.

[0021] N24: ESKMSGKGQQQQGQTVTKKS.

[0022] In a second aspect, the present invention provides the application of the biomarkers for evaluating the immune status of COVID-19 vaccines described in the first aspect in the preparation of products for evaluating the immune status of COVID-19 vaccines.

[0023] Thirdly, the present invention provides a kit for evaluating the immune status of a COVID-19 vaccine, the kit comprising the biomarkers for evaluating the immune status of a COVID-19 vaccine as described in the first aspect.

[0024] Preferably, the kit further includes a peptide chip.

[0025] Preferably, the biomarker for evaluating the immune status of a COVID-19 vaccine is attached to the peptide chip.

[0026] Fourthly, the present invention provides the application of the biomarkers for evaluating COVID-19 vaccine immune status described in the first aspect in evaluating COVID-19 vaccine immune status for non-disease diagnosis purposes.

[0027] In this invention, by screening for antibody binding activity against SARS-CoV-2 antigens, the characteristics of existing potential epitopes and infection mechanisms can be explored, providing a reference for the treatment of COVID-19 and the development of peptide vaccines.

[0028] Fifthly, the present invention provides a method for evaluating COVID-19 vaccine immune status for non-disease diagnosis purposes, the method comprising:

[0029] Using the biomarkers for evaluating COVID-19 vaccine immune status as described in the first aspect as probes, antibody levels in the subjects' samples were detected, and the subjects' specific antibody response levels to the biomarkers were analyzed.

[0030] Preferably, the sample includes any one of serum, plasma, nasal swab, or pharyngeal swab.

[0031] Preferably, the markers include N24 peptide and S115 peptide.

[0032] In a sixth aspect, the present invention provides an apparatus for evaluating the immune status of a COVID-19 vaccine, the apparatus comprising a detection unit and an analysis unit;

[0033] The detection unit is used to perform the following:

[0034] Using the biomarkers for evaluating COVID-19 vaccine immune status described in the first aspect as probes, antibody levels in the subjects' samples were detected;

[0035] The analysis unit is used to perform the following:

[0036] Analyze the subject's specific antibody response level to the biomarker.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] This invention accurately identifies differences in peptide-specific antibody responses between asymptomatic and symptomatic patients. Cluster heatmaps were used to determine differences in responses to peptides M1, N24, S15, S64, S82, S104, and S115 between vaccinated and infected individuals. Recipient operating characteristic (ROC) curve analysis showed that the combined diagnostic use of S15, S64, and S104 can distinguish infected patients from vaccinated individuals. Asymptomatic patients showed stronger specific antibody responses to peptides S15, S64, and S104 than symptomatic patients, while their specific antibody responses to peptides M1, N24, S82, and S115 were weaker. Furthermore, two peptides (N24 and S115) were correlated with neutralizing antibody levels. Attached Figure Description

[0039] Figure 1 A timeline of patient follow-up visits;

[0040] Figure 2 Heatmaps of peptide-specific responses to inoculation with low and high immune responses;

[0041] Figure 3AA heatmap showing the distribution of peptide-specific responses between infected individuals and recipients;

[0042] Figure 3B A diagram showing the specific responses of healthy individuals, vaccinated individuals, and patients to specific peptides of S15.

[0043] Figure 3C A diagram showing the specific responses of healthy individuals, vaccinated individuals, and patients to specific peptides of S64.

[0044] Figure 3D A diagram showing the specific responses of healthy individuals, vaccinated individuals, and patients to a specific peptide of S104.

[0045] Figure 4A A heatmap of peptide-specific responses between infected and healthy individuals;

[0046] Figure 4B Graphs showing specific IgG responses to S15-specific peptides in asymptomatic, mild, and severe patients;

[0047] Figure 4C Graphs showing specific IgG responses to S64-specific peptides in asymptomatic, mild, and severe patients;

[0048] Figure 4D Graphs showing the specific IgG responses to S104-specific peptides in asymptomatic, mild, and severe patients;

[0049] Figure 5A A graph showing the correlation analysis between peptides and neutralizing antibodies in infected individuals;

[0050] Figure 5B To visualize peptide-specific IgG responses at different time points after vaccination, four peptides (M1, N24, S82, and S115) with the highest correlation coefficients with PRNT50 were selected.

[0051] Figure 6A ROC curves for infected and vaccinated individuals; S15, S64, and S104 curves for different short peptides show the prediction results using the predictive model.

[0052] Figure 6B ROC curves for different single peptides are used to predict outcomes for asymptomatic patients and those with high immune responses.

[0053] Figure 6C ROC curves for different single peptides are used to predict outcomes for asymptomatic patients and those with low immune responses.

[0054] Figure 6D ROC curves for asymptomatic and symptomatic patients predicted using a predictive model. Detailed Implementation

[0055] To further illustrate the technical means and effects of this invention, the following description, in conjunction with embodiments and accompanying drawings, provides a further explanation of the invention. It is understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it.

[0056] Where specific techniques or conditions are not specified in the examples, they shall be performed in accordance with the techniques or conditions described in the literature in this field, or in accordance with the product instructions. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased through legitimate channels.

[0057] The research method in a specific embodiment of the present invention is as follows.

[0058] 1. Data on the research subjects:

[0059] Healthy adult volunteers (n=44) who received three doses of the inactivated COVID-19 vaccine BBIBP-CorV were randomly selected for follow-up at the following times: before immunization (first dose, i.e., healthy subject V1), one month after the first dose (V2+30), one month after the second dose (V1+30), and one month after the booster dose (V3+30). Of the 44 volunteers, 22 showed a low immune response, defined as the absence of effective neutralizing antibodies (NAb ≤ 61.77 AU / mL or VNT < 8) one month after the second dose, while the remaining 22 volunteers showed a high immune response (VNT ≥ 16). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. This study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Ethics Approval No.: gyfy-2021-31) and the Eighth People's Hospital of Guangzhou (202002135). Written informed consent was obtained from all participants.

[0060] 2. Sample Collection and Preparation

[0061] After fasting overnight, peripheral blood samples were collected from the antecubital vein using gel tubes containing 10 ml EDTA and 5 ml serum. Plasma and serum were centrifuged at 3000 RPM for 10 min at 4°C, respectively. All samples were placed in 0.5 mL tubes and stored at -80°C until further processing. Plasma was used for live virus neutralization assays, and serum was used for antibody and peptide microarray detection.

[0062] 3. RT-PCR-based detection and detection of SARS-CoV-2 infection

[0063] Nucleic acid was extracted primarily from nasopharyngeal tissue specimens, and RNA extraction was performed according to the instructions of a commercial viral RNA extraction kit (Sun Yat-sen University Da'an Gene Co., Ltd.). Reverse transcription polymerase chain reaction (RT-PCR) detection kits targeting the SARS-CoV-2 open reading frame 1ab (ORFlab) and nucleocapsid (N) gene regions were purchased from Guangzhou Da'an Gene Co., Ltd.

[0064] 4. Polypeptide segment

[0065] The amino acid sequence of SARS-CoV-2 strain (MN908947) was analyzed, and 20-mer peptides were chemically synthesized using GenScript (Jiangsu, China). These peptides contained 10 overlapping amino acid residues, partially covering the four structural proteins of SARS-CoV-2: spike (S), envelope (E), membrane (M), and N. A total of 131 peptides were synthesized. Each well of the peptide chip was a 4×4 rectangular microarray, with three human IgG positive controls and one negative control at the four corners. The probes included in the center were M1 peptide, N16 peptide, N24 peptide, S15 peptide, S39 peptide, S44 peptide, S64 peptide, S82 peptide, S95 peptide, S104 peptide, and S115 peptide (sequences shown in Table 1).

[0066] Table 1

[0067]

[0068]

[0069] 5. Detection of peptide-binding antibodies in serum using microarray method

[0070] The screening process is basically the same as described above, but with slight modifications. Serum screening follows the principles of indirect enzyme-linked immunosorbent assay (indirect ELISA).

[0071] First, diluted serum (100-fold) was prepared using 0.01M phosphate-buffered saline (PBS, pH 7.4) containing 1% bovine serum albumin, 1% casein, 0.5% sucrose, 0.2% polyvinylpyrrolidone, and 0.5% Tween 20. Then, 100 μL of the diluted serum sample was added to each microarray well and incubated with the peptide microarray for 30 minutes on a shaker (500 rpm, 37°C). Microarray wells incubated with serum dilution buffer served as negative controls. The microarray was then washed three times with 0.01M PBS-Tween (PBST, pH 7.4) and incubated for 30 minutes on a shaker (500 rpm, 37°C) with 100 μL of horseradish peroxidase (HRP)-conjugated anti-human IgG (ZSGB-BIO, Beijing, China). Subsequently, any unbound HRP-bound anti-human IgG was washed away with PBST, and the signal of IgG against the peptide probe was detected using a microarray imager (Epitope, Suzhou, China) with 100 μL of 1-step Ultra TMB-Blotting Solution (Thermo Scientific). Finally, the data were processed using UVC instrument V1.0 software (Epitope, Suzhou, China). The signal at each point was calculated by subtracting the background signal from the readout signal. Signal point = Readout signal - Background signal. The cutoff value for each probe was set to 10.

[0072] 6. Focus Reduction Neutralization Test (FRNT)

[0073] FRNT conducts live virus neutralization tests in a certified biosafety laboratory.

[0074] 7. Subject Data

[0075] Figure 1 The x-axis represents the patient's registration number, and the y-axis represents the date of onset. AP indicates asymptomatic patients; MP indicates mild patients; and SP indicates severe patients.

[0076] Healthy volunteers (n=44) were randomly assigned to the study. All of them completed three doses of BBIBP-CorV vaccination and were followed up for approximately one month after each dose (as shown in Table 2). Among these patients, 22 had a high immune response and 22 had a low immune response, with mean ages of 36.14±9.14 years and 41.32±5.96 years, respectively.

[0077] Table 2

[0078]

[0079] Example 1

[0080] This embodiment analyzes the differences in peptide-specific responses between high and low immune responses.

[0081] First, cluster heatmap analysis was used to analyze the distribution of peptide-specific antibody responses in 22 participants with high and 22 participants with low immune responses. Figure 2 Patients were divided into two groups: those with low immunity and those with high immunity. For group 1, light to dark (purple) represent time points before immunization, 30 days after the first injection, 30 days after the second injection, and 30 days after the third injection. The results showed that the distribution of these 11 peptides was consistent between the two groups, with no statistical difference (p≤0.05). Therefore, it is speculated that healthy individuals will produce similar specific antibody response profiles after receiving the inactivated vaccine. In further research, these two groups of patients will be combined for subsequent analysis.

[0082] Example 2

[0083] This embodiment analyzes the differences in peptide-specific responses between vaccine recipients and infected individuals.

[0084] The peptide-specific responses of 44 vaccine recipients (V1, V1+30, V2+30, and V3+30) and 61 patients (AP, MP, and SP) are distributed in the cluster heatmap as shown below. Figure 3A As shown. The specific IgG response to the antigenic epitope was significantly weaker in all vaccinated populations than in all types of patients. Further analysis revealed statistically significant differences in the distribution of specific IgG responses to S64, S15, and S104 peptides among healthy individuals, infected individuals, and vaccinated individuals (e.g., ...). Figures 3B-3D As shown, *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001).

[0085] Example 3

[0086] This embodiment analyzes the differences in peptide-specific responses among AP, MP, and SP.

[0087] Peptide-specific responses differ not only between vaccinated individuals and patients, but also significantly among patients with different disease grades. This example includes 18 AP patients, 33 MP patients, and 10 SP patients, and cluster analysis was performed on the results for different patient types. Figure 4A As shown, the specific activities of peptides S64, S15, and S104 in AP were significantly higher than those in MP and SP (p≤0.001), but there was no statistically significant difference between MP and SP. Figures 4B-4DFurthermore, it was found that the expression of M1, N24, S82, and S115 in AP was significantly lower than that in MP and SP (P≤0.05), while there was no significant difference between MP and SP. *p≤0.05; **p≤0.01; ***p≤0.001; ****p≤0.0001.

[0088] Example 4

[0089] This embodiment analyzes the correlation between SARS-CoV-2 peptides and their neutralizing activity against the virus.

[0090] Screening for antibody-binding activity against SARS-CoV-2 antigens can help explore existing potential epitopes and the characteristics of infection mechanisms, providing a reference for COVID-19 treatment and peptide vaccine development. Therefore, Spearman correlation analysis was used to examine the correlation between SARS-CoV-2 peptide-specific IgG responses and PRNT50 during infection. According to the correlation heatmap, the correlations between peptide-specific IgG and PRNT50 for M1, N24, S82, and S115 were 0.55, 0.58, 0.58, and 0.73 (p≤0.05), respectively. Figure 5A Multiple linear regression analysis showed F = 47.758, p ≤ 0.001, R = 0.649. The effects of N24 and S115 peptides on the PRNT50 results were statistically significant in the model (p ≤ 0.05).

[0091] Antibody levels in vaccinated individuals typically peak one month after vaccination; therefore, antibody levels increased one month after the first, second, and third injections. Further analysis of the trends in these four peptides after vaccination revealed that N24 and S115 showed the strongest correlation with antibody level changes. Figure 5B ), that is, N24 and S115 are associated with neutralizing antibody levels.

[0092] Example 5

[0093] This embodiment identifies polypeptide combinations that can distinguish between infected individuals and recipients.

[0094] Within 1-2 weeks of symptom onset, viral load can reach undetectable levels, making the diagnosis of acute pancreatitis (AP) crucial for epidemic control. Antigen testing is currently hampered by sensitivity and specificity issues; therefore, identifying differences in peptide-specific IgG antibody responses among vaccinated individuals, AP patients, and symptomatic patients (MP and SP) is essential for disease detection, diagnosis, and treatment. Based on the above discussion and analysis, this embodiment uses three markers, S64, S15, and S104, to perform ROC analysis on vaccinated and infected patients. The results are as follows: Figure 6AAs shown, S64, S15 and S104 were found to have good sensitivity and specificity in distinguishing between patients and vaccine recipients, with a sensitivity and specificity of 91.3% and 99.2% respectively for combined diagnosis (Table 3).

[0095] Table 3

[0096]

[0097]

[0098] In contrast, to differentiate AP from symptomatic patients, ROC analysis was performed on S64, S15, and S104, which are highly expressed in AP, and M1, N24, S82, and S115, which are lowly expressed. Figure 6C The sensitivities of S64, S15, and S104 in differentiating AP from symptomatic patients were 94.1%, 86.3%, and 96.1%, respectively. The specificities of M1, N24, S82, and S115 were 94.1%, 92.2%, 86.3%, and 98%, respectively (Table 4), while the predictive sensitivity and specificity for combined diagnosis were 94.1% and 85.3%, respectively. Figure 6D (and Table 4), indicating that it can be used as a biomarker to distinguish AP from symptomatic patients.

[0099] Table 4

[0100]

[0101] In summary, this invention uses a SARS-CoV-2 peptide microarray containing 11 peptides to identify peptide epitopes. Forty-four volunteers vaccinated with the BBIBP-CorV inactivated virus vaccine were distinguished from 61 patients infected with SARS-CoV-2, and differences in peptide-specific antibody responses between asymptomatic and symptomatic patients were accurately identified. Cluster heatmaps determined differences in responses to peptides M1, N24, S15, S64, S82, S104, and S115 between vaccinated and infected individuals. Recipient operating characteristic (ROC) curve analysis showed that the combined diagnostic use of S15, S64, and S104 could distinguish infected patients from vaccinated individuals. Asymptomatic patients showed stronger specific antibody responses to peptides S15, S64, and S104 than symptomatic patients, while their specific antibody responses to peptides M1, N24, S82, and S115 were weaker. Furthermore, two peptides (N24 and S115) were correlated with neutralizing antibody levels.

[0102] The applicant declares that the detailed method of the present invention is illustrated by the above embodiments, but the present invention is not limited to the above detailed method, that is, it does not mean that the present invention must rely on the above detailed method to be implemented. Those skilled in the art should understand that any improvements to the present invention, equivalent substitutions of the raw materials of the product of the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

Claims

1. A marker for differentiating COVID-19 infected patients from vaccinated population, characterized in that, The biomarker is a combination of the S15, S64, and S104 peptides of the SARS-CoV-2 virus.

2. A marker for differentiating between asymptomatic and symptomatic patients infected with COVID-19, characterized in that, The biomarkers are a combination of the S15, S64, and S104 peptides of the SARS-CoV-2 virus; and / or a combination of the M1, N24, S82, and S115 peptides of the SARS-CoV-2 virus.

3. A biomarker for evaluating COVID-19 vaccine immunity status, characterized in that, The biomarkers include a combination of the S15, S64, and S104 peptides of the SARS-CoV-2 virus; or A combination of the M1, N24, S82, and S115 peptides of the SARS-CoV-2 virus; or The combination of M1 peptide, N24 peptide, S15 peptide, S64 peptide, S82 peptide, S104 peptide and S115 peptide of SARS-CoV-2 virus.

4. The use of the marker according to any one of claims 1-3 in the preparation of products for evaluating the immune status of COVID-19 vaccines.

5. A kit for evaluating the immune status of COVID-19 vaccine, characterized by, The kit includes the markers described in any one of claims 1-3.

6. The kit for evaluating the immune status of COVID-19 vaccine according to claim 5, characterized by, The kit also includes a peptide chip.

7. The kit for evaluating the immune status of COVID-19 vaccine according to claim 6, characterized by, The marker is attached to the peptide chip.

8. The use of the biomarker according to any one of claims 1-3 in evaluating COVID-19 vaccine immune status for non-disease diagnosis purposes.

9. A method for evaluating COVID-19 vaccine immunity status for non-disease diagnosis purposes, characterized in that, The method includes: Using the biomarker described in any one of claims 1-3 as a probe, the antibody level in the subject's sample is detected, and the subject's specific antibody response level to the biomarker is analyzed.

10. The method of evaluating COVID-19 vaccine immune status for non-disease diagnostic purposes according to claim 9, characterized in that, The sample may include any one of serum, plasma, nasal swab, or throat swab.

11. An apparatus for evaluating COVID-19 vaccine immune status, characterized by, The device includes a detection unit and an analysis unit; The detection unit is used to perform the following: Using the biomarker described in any one of claims 1-3 as a probe, the antibody level in the subject's sample was detected; The analysis unit is used to perform the following: Analyze the subject's specific antibody response level to the biomarker.

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