Immune response stability to the SARS-CoV-2 mRNA vaccine booster is influenced by differential splicing of HLA genes

Abstract

Many molecular mechanisms that lead to the host antibody response to COVID-19 vaccines remain largely unknown. In this study, we used serum antibody detection combined with whole blood RNA-based transcriptome analysis to investigate variability in vaccine response in healthy recipients of a booster (third) dose schedule of the mRNA BNT162b2 vaccine against COVID-19. The cohort was divided into two groups: (1) low-stable individuals, with antibody concentration anti-SARS-CoV IgG S1 below 0.4 percentile at 180 days after boosting vaccination; and (2) high-stable individuals, with antibody values greater than 0.6 percentile of the range in the same period (median 9525 [185-80,000] AU/mL). Differential gene expression, expressed single nucleotide variants and insertions/deletions, differential splicing events, and allelic imbalance were explored to broaden our understanding of the immune response sustenance. Our analysis revealed a differential expression of genes with immunological functions in individuals with low antibody titers, compared to those with higher antibody titers, underscoring the fundamental importance of the innate immune response for boosting immunity. Our findings also provide new insights into the determinants of the immune response variability to the SARS-CoV-2 mRNA vaccine booster, highlighting the significance of differential splicing regulatory mechanisms, mainly concerning HLA alleles, in delineating vaccine immunogenicity.

Keywords: Admixed population; Human leukocyte antigen; Immune response variability; SARS-CoV-2; Vaccine response; Whole blood transcriptome.

Figure 1

An illustrative representation of experimental design: vaccine characteristics, temporal blood sampling points, and discriminatory antibody profiles for categorizing investigated cohorts.

Figure 2

Enrichment analysis conducted on the enrichment of 36 DEGs and DASE genes. The y-axis shows the categories, while the x-axis shows the proportion of genes mapped against the total. Classes are represented by colours and statistical significance by circle size.

Figure 3

SARS-CoV-2 interactome analysis with DEGs and DASE genes. (a) Interactions with all SARS-CoV-2 viral proteins; (b) Interactions with SARS-CoV-2 spike protein. The green circles represent genes from SARS-CoV-2, the yellow circles represent DASE genes, and the blue circles indicate the three up-regulated genes. Circle size is proportional to degree (number of interactions), and edge color reflects type: red for interactions between human proteins and SARS-CoV-2, and black for interactions between human proteins.

Figure 4

Genomic distribution of eSNVs across the human genome. The outermost layer displays the chromosomal arrangement, followed by the cytoband organization. Within the chromosome layout, all eSNVs with a read count over 12, found in the variant calling step, were represented by black dots. Furthermore, eSNVs shared between the two study groups are represented by red dots. The innermost layer illustrates the distribution of the DASE genes with colored bars. The dots beneath the arrow symbolize the eSNVs located within the DASE genes.

Figure 5

Distribution of the splice site alterations across HLA-A and HLA-B genes. The structure of HLA-A and HLA-B genes with exon identification is depicted in dark blue. The sequence context of splice site alterations is visually presented across the genes. eSNVs within the sequence (black bold) are identified by colored dots. Additionally, splice sites (read bold) and their specific alterations are indicated by red arrows.