Influenza is a significant health burden on global health, with an estimated 1 billion cases annually [https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)]. Each year, seasonal influenza is responsible for an estimated 290,000-650,000 respiratory-related deaths, not including other influenza-related outcomes [PMID: 29248255]. In addition, antigenic shifts lead to new viral strains, resulting in widespread illness, as evidenced by five devastating pandemics in the past 100 years or so (in 1918, 1957, 1968, 1977, and 2009).

Influenza symptoms can include fever, cough, sore throat, fatigue, and more. While anyone can get the flu and experience complications, certain groups are at higher risk for severe illness. These include adults 65 and older, people with chronic medical conditions, pregnant women, and children under age 5 [https://www.cdc.gov/flu/signs-symptoms/index.html].

Vaccination represents an efficient and cost-effective way to contain influenza epidemics and preserve public health. Since their introduction in the 1940s, seasonal influenza vaccines have saved countless lives and limited pandemic spread. Influenza viruses nonetheless continue to evolve through genetic mutation and escape from natural immunity, and vaccines must be updated yearly. However, vaccine effectiveness varies significantly between individuals and across seasons (Figure x), largely due to the virus’s high mutation rate and antigenic drift [PMID: 32060419].

Licensed influenza vaccines (Table 1) are primarily of two types: inactivated influenza vaccines (IIV) and live attenuated influenza vaccines (LAIV). IIVs include both split-virus and subunit formulations. Split-virus vaccines are generated by chemically disrupting whole viruses, whereas subunit vaccines contain purified components such as hemagglutinin (HA) and neuraminidase (NA), which are the main targets of neutralizing antibodies. These vaccines are administered intramuscularly and represent the majority of flu vaccinations globally. LAIVs, on the other hand, consist of cold-adapted viruses capable of limited replication in the upper respiratory tract, administered intranasally, and capable of inducing both systemic and mucosal immunity. LAIVs are typically recommended for healthy individuals aged 2 to 49 years [PMID: 10669363, 9580647, 8106789].

Most vaccines are quadrivalent, meaning one vaccine protects against four strains of the virus, including two influenza A subtypes and two influenza B lineages [PMID: 30057283, 24022123], although trivalent formulations, which protect against three strains, are still in use in some settings [PMID: 31635976].

Annual reformulation of the flu vaccine is necessary due to the continuous evolution of circulating strains. Global surveillance networks coordinated by the World Health Organization monitor influenza activity to inform strain selection. Nonetheless, mismatches between vaccine strains and circulating viruses remain a major limitation of current vaccines. Moreover, host factors such as age, immunological history, and genetic background also influence vaccine responsiveness, further complicating the prediction of individual outcomes.

These challenges underscore the need for next-generation influenza vaccines with broader and more durable protection. Several strategies are under investigation. Such strategies include targeting of conserved viral regions such as the HA stalk, M2 ectodomain, and internal proteins like NP and M1 to elicit cross-protective T cell responses. Platforms under development include mRNA-based vaccines, DNA vaccines, viral vectors, and virus-like particles (VLPs), many of which are designed to induce both humoral and cellular immunity [PMID: 27847366, 22318394, 28296763].

Universal influenza vaccines, capable of providing multi-year, strain-transcending protection, represent a long-term goal that would fundamentally change the landscape of influenza prevention. Until then, seasonal vaccination remains a critical tool, and improving its predictive value through computational modeling and systems-level analysis, as pursued in the CMI-Flu project, is an essential step toward more personalized and effective influenza immunization strategies.

Here we discuss the temporal dynamics of immune activation, the role of both innate and adaptive responses, and the factors contributing to inter-individual variability in response to influenza vaccination. Vaccination primes the adaptive immune system to rapidly respond to future pathogens encounters. A detailed schematic (Figure X) outlines the key immune pathways involved in protective responses following influenza vaccination.

Serological readouts of vaccine-induced responses (which are indicators of protection) are the outcome of a complex interplay of different arms of the immune system that are further impacted by genetic factors and an individual's exposure history. Immediately after vaccination, an innate immune response is activated that includes monocytes, dendritic cells (DCs), and natural killer (NK) cells intended to inhibit pathogens and stimulate adaptive immune responses. Antigen-presenting cells (APCs) take up influenza antigens at the vaccination site and migrate to the local draining lymph nodes, where they present antigens to resident T and B cells and those recruited via innate activation signals.

When B cell receptors (BCRs) recognize influenza antigens, they drive both influenza-specific naive and pre-existing memory B cells to activate and differentiate into plasmablasts that produce a surge of influenza-specific antibodies. This B cell activation and differentiation process can be ‘helped’ by influenza-specific CD4+ T cells that recognize influenza T cell epitopes presented on the surface of APCs and B cells that have taken up influenza antigens, processed and presented them via human leukocyte antigen (HLA) class II molecules to T cell receptors (TCRs). Memory B and T cells pre-existing at the time of vaccination massively impact the induced response, providing faster and stronger activation than naive B or T cells when encountering antigen.

These memory populations heavily depend upon an individual’s exposure history from prior influenza vaccinations and infections. Finally, genetic factors drive several key elements of this response [PMID: 35332318, 27479906]. Both HLA molecules and BCRs/TCRs are encoded by genes in the most genetically diverse loci of the human genome, and their expression and function are dictated by complex cis and trans effects. For example, HLA molecules determine what T cell epitopes an individual can recognize and influence the frequency of observed TCRs in the expressed repertoire [PMID: 35332318 , 27479906]. In addition, BCRs and TCRs are encoded by families of Variable (V), Diversity (D), and Joining (J) genes that are somatically recombined through a process unique to B and T cells. Both coding and non-coding polymorphisms within the immunoglobulin (IG) and TCR gene loci (TR) also determine what receptors an individual can produce [PMID: 37479682, 35315770]. For example, polymorphisms within the gene IGHV1-69 have been linked to whether an individual can generate broadly neutralizing antibodies against influenza hemagglutinin (HA) stem epitopes [PMID: 35315770, 35952670]. Additional genetic factors distributed throughout the genome can impact the development of vaccination responses. Several single nucleotide polymorphisms (SNPs) have been linked to the expression of genes (eQTLs) involved in membrane trafficking and antigen processing that significantly impact the immune response to influenza vaccination [PMID: 23878721] .

CMI-Flu will examine elements that span across all of these key factors: innate and adaptive immune responses, pre-existing memory responses, exposure history, and genetic factors (HLA/TCR/BCR/eQTL), employing computational models to integrate this data for a more holistic view of the immune response.

The history of influenza vaccination reflects ongoing innovations and challenges, from early inactivated vaccines to modern recombinant and mRNA platforms. This section reviews the evolution of influenza vaccines, highlighting landmark studies and pivotal shifts in vaccine design. Understanding this historical context is essential for appreciating the current challenges in predicting vaccine efficacy and the need for next-generation computational models.