Identification of Two Novel Candidate Genetic Variants Associated With the Responsiveness to Influenza Vaccination

Impact of Newcastle disease virus vaccines and genetic variations on interleukin-4 activation in broiler chicken

Background

Newcastle disease virus is a virus that causes a significant economic impact on the poultry industry and is primarily controlled through vaccination. Most of the vaccinations with the LaSota strain are either live attenuated or inactivated vaccines, both of which are from the Lentogenic pathotype.

Aim

This study aimed to investigate the influence of vaccine type and genetic variations on Chicken Interleukin-4 (ChIL4) activation.

Methods

Three groups were examined: Group K received the killed vaccine, Group L received the live vaccine, and Group C served as the control. Blood samples were collected on days 15, 25, and 35 post-vaccinations to assess ChIL4 levels using Enzyme-Linked Immunosorbent Assay and for molecular analysis using polymerase chain reaction.

Results

Group K showed a gradual increase in ChIL4 levels from 11.19 ± 0.17 to 13.70 ± 0.38, while Group L exhibited an initial increase on day 15 followed by stabilization on days 25 and 35. In contrast, ChIL4 levels in Group C declined over time from 4.84 ± 0.39 to 4.32 ± 0.25. Molecular analysis revealed four genetic variations of the single nucleotide polymorphism (SNPs) type at locations (3044, 3132, 3261, 3499) bp, with the third SNP at location (3261 bp) resulting in an amino acid change from valine to isoleucine. Analysis indicated that variants for most of these SNPs occur more likely in Group K compared to the other two groups.

Conclusion

These findings suggest that genetic variations, particularly SNPs, may play a significant role in ChIL4 activation, potentially impacting vaccine efficacy and immune response.

Impact of Newcastle disease virus vaccines and genetic variations on interleukin-4 activation in broiler chicken

Background

Newcastle disease virus is a virus that causes a significant economic impact on the poultry industry and is primarily controlled through vaccination. Most of the vaccinations with the LaSota strain are either live attenuated or inactivated vaccines, both of which are from the Lentogenic pathotype.

Aim

This study aimed to investigate the influence of vaccine type and genetic variations on Chicken Interleukin-4 (ChIL4) activation.

Methods

Three groups were examined: Group K received the killed vaccine, Group L received the live vaccine, and Group C served as the control. Blood samples were collected on days 15, 25, and 35 post-vaccinations to assess ChIL4 levels using Enzyme-Linked Immunosorbent Assay and for molecular analysis using polymerase chain reaction.

Results

Group K showed a gradual increase in ChIL4 levels from 11.19 ± 0.17 to 13.70 ± 0.38, while Group L exhibited an initial increase on day 15 followed by stabilization on days 25 and 35. In contrast, ChIL4 levels in Group C declined over time from 4.84 ± 0.39 to 4.32 ± 0.25. Molecular analysis revealed four genetic variations of the single nucleotide polymorphism (SNPs) type at locations (3044, 3132, 3261, 3499) bp, with the third SNP at location (3261 bp) resulting in an amino acid change from valine to isoleucine. Analysis indicated that variants for most of these SNPs occur more likely in Group K compared to the other two groups.

Conclusion

These findings suggest that genetic variations, particularly SNPs, may play a significant role in ChIL4 activation, potentially impacting vaccine efficacy and immune response.

Vaccinomics and adversomics: key elements for a personalized vaccinology

Vaccines are one of the most important and effective tools in the prevention of infectious diseases and research about all the aspects of vaccinology are essential to increase the number of available vaccines more and more safe and effective. Despite the unquestionable value of vaccinations, vaccine hesitancy has spread worldwide compromising the success of vaccinations. Currently, the main purpose of vaccination campaigns is the immunization of whole populations with the same vaccine formulations and schedules for all individuals. A personalized vaccinology approach could improve modern vaccinology counteracting vaccine hesitancy and giving great benefits for human health. This ambitious purpose would be possible by facing and deepening the areas of vaccinomics and adversomics, two innovative areas of study investigating the role of a series of variables able to influence the immune response to vaccinations and the development of serious side effects, respectively. We reviewed the recent scientific knowledge about these innovative sciences focusing on genetic and non-genetic basis involved in the individual response to vaccines in terms of both immune response and side effects.

Genetic determinants of IgG antibody response to COVID-19 vaccination

Human humoral immune responses to SARS-CoV-2 vaccines exhibit substantial inter-individual variability and have been linked to vaccine efficacy. To elucidate the underlying mechanism behind this variability, we conducted a genome-wide association study (GWAS) on the anti-spike IgG serostatus of UK Biobank participants who were previously uninfected by SARS-CoV-2 and had received either the first dose (n = 54,066) or the second dose (n = 46,232) of COVID-19 vaccines. Our analysis revealed significant genome-wide associations between the IgG antibody serostatus following the initial vaccine and human leukocyte antigen (HLA) class II alleles. Specifically, the HLA-DRB1∗13:02 allele (MAF = 4.0%, OR = 0.75, p = 2.34e-16) demonstrated the most statistically significant protective effect against IgG seronegativity. This protective effect was driven by an alteration from arginine (Arg) to glutamic acid (Glu) at position 71 on HLA-DRβ1 (p = 1.88e-25), leading to a change in the electrostatic potential of pocket 4 of the peptide binding groove. Notably, the impact of HLA alleles on IgG responses was cell type specific, and we observed a shared genetic predisposition between IgG status and susceptibility/severity of COVID-19. These results were replicated within independent cohorts where IgG serostatus was assayed by two different antibody serology tests. Our findings provide insights into the biological mechanism underlying individual variation in responses to COVID-19 vaccines and highlight the need to consider the influence of constitutive genetics when designing vaccination strategies for optimizing protection and control of infectious disease across diverse populations.

The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer

The tumour microenvironment (TME) is vital to tumour development and influences the immunotherapy response. Abnormal nucleotide metabolism (NM) not only promotes tumour cell proliferation but also inhibits immune responses in the TME. Therefore, this study aimed to determine whether the combined signatures of NM and the TME could better predict the prognosis and treatment response in gastric cancer (GC). 97 NM-related genes and 22 TME cells were evaluated in TCGA-STAD samples, and predictive NM and TME characteristics were determined. Subsequent correlation analysis and single-cell data analysis illustrated a link between NM scores and TME cells. Thereafter, NM and TME characteristics were combined to construct an NM-TME classifier. Patients in the NMlow/TMEhigh group exhibited better clinical outcomes and treatment responses, which could be attributed to the differences in immune cell infiltration, immune checkpoint genes, tumour somatic mutations, immunophenoscore, immunotherapy response rate and proteomap. Additionally, the NMhigh/TMElow group benefited more from Imatinib, Midostaurin and Linsitinib, while patients in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin. Finally, a highly reliable nomogram was developed. In conclusion, the NM-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic responses, which may offer novel strategies for strategizing patients with optimal therapies.

Factors affecting the immunogenicity of influenza vaccines in human

BACKGROUND

The influenza viruses pose a threat to human health and medical services, and vaccination is an important way to prevent infection. However, the effectiveness of influenza vaccines is affected by various aspects. This study aimed to explore factors related to the immune response to influenza vaccines.

METHODS

The study was conducted from September 2019 to September 2021, and a total of 593 volunteers were recruited from the Center for Disease Control and Prevention in 3 provinces in China. The hemagglutination inhibition assay was used to measure antibody levels. The Chi-square test, multivariable logistic regression analysis, and sum-rank test were used to analyze the factors associated with influenza vaccine immune response.

RESULTS

The Chi-square test showed that seroconversion rates and response rate were associated with age group, vaccination history, chronic conditions, the frequency of colds, and region (P < 0.05). The multivariable logistic regression analysis showed that age was an important factor that affected participants' seroconversion rates for A/H1N1, A/H3N2, B/Victoria, and response status (18-64 vs. ≤5: OR = 2.77, P < 0.001; ≥65 vs. ≤5: OR = 0.38, P = 0.01; 18-64 vs. ≤5: OR = 2.64, P = 0.03). Vaccination history was also an affecting factor for A/H1N1, B/Victoria, and response status (yes vs. no: OR = 0.4 / 0.44 / 0.25, P < 0.001). The frequency of colds and chronic conditions were also affecting factors for participants' seroconversion rates and response levels to different degrees. The sum-rank test showed that the fold changes for A/H1N1, B/Victoria, and B/Yamagata were associated with age group and vaccination history (P < 0.01). The fold changes for A/H3N2 were associated with the frequency of colds (P < 0.05), and those for B/Victoria were associated with gender and chronic conditions (P < 0.05).

CONCLUSIONS

Vaccination history, age, health condition, and frequency of colds were important factors affecting the seroconversion rate of the influenza vaccine in human. There is a need for developing optimized vaccination strategies for vulnerable groups to improve the efficacy of influenza vaccines in human.

Vaccinomics: A scoping review

BACKGROUND

This scoping review summarizes a key aspect of vaccinomics by collating known associations between heterogeneity in human genetics and vaccine immunogenicity and safety.

METHODS

We searched PubMed for articles in English using terms covering vaccines routinely recommended to the general US population, their effects, and genetics/genomics. Included studies were controlled and demonstrated statistically significant associations with vaccine immunogenicity or safety. Studies of Pandemrix®, an influenza vaccine previously used in Europe, were also included, due to its widely publicized genetically mediated association with narcolepsy.

FINDINGS

Of the 2,300 articles manually screened, 214 were included for data extraction. Six included articles examined genetic influences on vaccine safety; the rest examined vaccine immunogenicity. Hepatitis B vaccine immunogenicity was reported in 92 articles and associated with 277 genetic determinants across 117 genes. Thirty-three articles identified 291 genetic determinants across 118 genes associated with measles vaccine immunogenicity, 22 articles identified 311 genetic determinants across 110 genes associated with rubella vaccine immunogenicity, and 25 articles identified 48 genetic determinants across 34 genes associated with influenza vaccine immunogenicity. Other vaccines had fewer than 10 studies each identifying genetic determinants of their immunogenicity. Genetic associations were reported with 4 adverse events following influenza vaccination (narcolepsy, GBS, GCA/PMR, high temperature) and 2 adverse events following measles vaccination (fever, febrile seizure).

CONCLUSION

This scoping review identified numerous genetic associations with vaccine immunogenicity and several genetic associations with vaccine safety. Most associations were only reported in one study. This illustrates both the potential of and need for investment in vaccinomics. Current research in this field is focused on systems and genetic-based studies designed to identify risk signatures for serious vaccine reactions or diminished vaccine immunogenicity. Such research could bolster our ability to develop safer and more effective vaccines.

Mendelian randomization suggests a potential causal effect of eosinophil count on influenza vaccination responsiveness

Currently, the clinical factors affecting immune responses to influenza vaccines have not been systematically explored. The mechanism of low responsiveness to influenza vaccination (LRIV) is complicated and not thoroughly elucidated. Thus, we integrate our in-house genome-wide association studies (GWAS) analysis result of LRIV (N = 111, Ncase [Low Responders] = 34, Ncontrol [Responders] = 77) with the GWAS summary of 10 blood-based biomarkers (sample size ranging from 62 076-108 794) deposited in BioBank Japan (BBJ) to comprehensively explore the shared genetics between LRIV and blood-based biomarkers to investigate the causal relationships between blood-based biomarkers and LRIV by Mendelian randomization (MR). The applications of four MR approaches (inverse-variance-weighted [IVW], weighted median, weighted mode, and generalized summary-data-based MR [GSMR]) suggested that the genetically instrumented LRIV was associated with decreased eosinophil count (β = -5.517 to -4.422, p = 0.004-0.039). Finally, we conclude that the low level of eosinophil count is a suggestive risk factor for LRIV.

Poor Vaccine Effectiveness against Influenza B-Related Severe Acute Respiratory Infection in a Temperate North Indian State (2019-2020): A Call for Further Data for Possible Vaccines with Closer Match

Background: Influenza vaccine uptake in India is poor, and scant data exist regarding the effectiveness of influenza vaccine against hospitalization. Methods: From October 2019 to March 2020, vaccination status of 1219 patients (males n = 571, aged 5–107 years; median, 50 years) hospitalized with severe acute respiratory illness (SARI) was assessed. The patients were tested for influenza viruses and their subtypes by RT PCR. Sequencing of the HA gene was performed. Vaccine effectiveness (VE) against influenza subtypes was estimated by the test negative design. Results: A total of 336 (27.5%) patients were influenza-positive, with influenza B/Victoria accounting for 49.7% (n = 167), followed by influenza A/H1N1 (47.6%; n = 155) and influenza A/H3N2 (4.4%; n = 15). About 6.8% and 8.6% of the influenza-positive and influenza-negative patients, respectively, had been vaccinated. Adjusted VE for any influenza strain was 13% (95% CI −42 to 47), which for influenza B was 0%. HA sequencing revealed that influenza B samples mainly belonged to subclade V1A.3/133R with deletion of residues 163–165, as against the 2-aa deletion in influenza B/Colorado/06/2017 strain, contained in the vaccine. VE for influenza A/H1N1 was 55%. Conclusions: Poor VE due to a genetic mismatch between the circulating strain and the vaccine strain calls for efforts to reduce the mismatch.