The biological progression of aging encompasses complex physiological processes. As individuals grow older, their physiological functions gradually decline, including compromised immune responses, leading to immunosenescence. Immunosenescence significantly elevates disease susceptibility and severity in older populations while concurrently compromising vaccine-induced immune responses. This comprehensive review aims to elucidate the implications of immunosenescence for vaccine-induced immunity and facilitate the development of optimized vaccination strategies for geriatric populations, with specific focus on COVID-19, influenza, pneumococcal, herpes zoster, and respiratory syncytial virus (RSV) vaccines. This review further elucidates the relationship between immunosenescence and vaccine-induced immunity. This review presents a systematic evaluation of intervention strategies designed to enhance vaccine responses in older populations, encompassing adjuvant utilization, antigen doses, vaccination frequency modification, inflammatory response modulation, and lifestyle interventions, including physical activity and nutritional modifications. These strategies are explored for their potential to improve current vaccine efficacy and inform the development of next-generation vaccines for geriatric populations.

Mutations may cause changes in the structure and function of immune-related proteins, thereby affecting the operation of the immune system. Deep mutational scanning combines saturation mutagenesis, functional selection, and high-throughput sequencing to evaluate the effects of mutations on a large scale and with high resolution. By systematically and comprehensively analyzing the impact of mutations on the functions of immune-related proteins, the immune response mechanism can be better understood. However, each stage in deep mutation scanning has its limits, and the approach remains constrained in several ways. These include data and selection biases that affect the robustness of effect estimates, insufficient library coverage and editability leading to uneven representation of sites and alleles, system-induced biased signals that deviate phenotypes from their true physiological state, and imperfect models and statistical processing that limit extrapolation capabilities. Therefore, this technology still needs further development. Herein, we summarize the principles and methods of deep mutational scanning and discuss its application in immunological research. The aim is to provide insights into the broader application prospects of deep mutational scanning technology in immunology.

Population immune pressure from vaccination and prior infection continues to drive the evolution of SARS-CoV-2. Systematic characterization of RBD mutations under complex immune backgrounds is essential for understanding viral adaptation and evolutionary trajectories. Here, we applied a deep mutational scanning (DMS) to comprehensively map the neutralization escape landscape of the Omicron variant JN.1 and its descendant lineage XEC, under immune pressure from individuals who experienced Omicron breakthrough infections following three doses of inactivated vaccines. A neutralization escape map for the single amino acid substitutions in the RBD of JN.1 or XEC was generated, and the escape efficiency of each mutation was determined. The results show that RBD escape mutations are hierarchically organized: low-intensity signals are widespread, whereas high-intensity escape is confined to a few key sites. These escape mutations are not confined solely to the receptor-binding motif (RBM) but are broadly distributed across the entire RBD. Many escape sites could accommodate multiple amino acid substitutions. Integration of DMS data with genomic surveillance of circulating variants from 2024 to 2025 revealed significant overlap between experimentally identified escape sites and mutations observed in natural isolates. This overlap increased substantially in 2025, with site concordance rising from 27.17% and 26.81% to 45.09% and 47.10% for JN.1 and XEC, respectively. The natural prevalence of these escape mutations is further shaped by factors such as receptor-binding affinity, protein stability, and epistatic interactions. Overall, our findings suggest that SARS-CoV-2 antigenic evolution follows the pattern of multiple pathways within a constrained space, providing new insights into the adaptive mechanisms of Omicron-derived variants under hybrid immune pressure.