Core Framework & Diagram What Is Immunomics?
July 23, 20261 Min Read What Is Single-Cell Immunology?
July 23, 2026To truly understand the immune system, you need to read its genes, proteins, metabolites, and cells simultaneously
—— Immunomics: using multi-layer 'omics' technologies for a full-dimensional systematic analysis of the immune system.
I. Genomic immunology: reading your immune system's innate 'cards'
Every person's immune capacity is partly determined by genetics. Genomic-level immunology studies which genetic variants affect immune function — from susceptibility to specific pathogens, to autoimmune risk, to vaccine response capacity. Among all immunity-related genes, HLA (Human Leukocyte Antigen) is the highest-variability, most profound-influence gene region. HLA molecules are the core of antigen presentation: they 'hold' pathogen fragments to display for T cells, enabling T cells to recognize them and launch responses. HLA genes' extreme polymorphism (HLA-A, HLA-B, HLA-C, HLA-DR, HLA-DQ loci have thousands of alleles) means each person's HLA molecules can 'display' different antigen spectra — this is why the same vaccine can produce significantly different antibody and T cell responses in people with different HLA types.
One of the most important tools in genomic immunology is GWAS (Genome-Wide Association Studies). By comparing genomic differences between large-scale diseased and healthy populations, GWAS discovers genetic variants associated with specific immune-related disease risks. Nearly twenty years of GWAS research in immunology has been fruitful: discovering over 200 genetic loci associated with rheumatoid arthritis, over 100 associated with Crohn's disease, and numerous genetic variants associated with COVID-19 severe disease risk — including a gene cluster on chromosome 3 proven to significantly increase severe disease risk, originating from ancient Neanderthal gene fragments.
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Genomic-level immune information is each person's immune system's 'innate blueprint' — it tells us where a person has innate advantages and innate risks in immune responses. This is the genetic basis of individualized immunotherapy and precision prevention. |
2. Transcriptomic immunology: real-time reading of immune cells' 'work log'
The genome is static — your DNA essentially doesn't change from birth to death. The transcriptome is dynamic: it records which genes are being 'read' and transcribed into mRNA at a specific time point in immune cells — which genes are currently working. RNA-seq can simultaneously measure expression levels of tens of thousands of genes in one experiment, producing a detailed snapshot of immune cells' current 'working state.' Traditional bulk RNA-seq measures the average gene expression of a batch of cells — like recording a chorus, only hearing the overall effect, unable to distinguish what each voice part is singing. Single-cell RNA-seq (scRNA-seq) completely changed this situation — it can independently measure gene expression in each of thousands to tens of thousands of individual cells in the same experiment, then reconstruct each cell's 'solo' in the computer.
Transcriptomics' key immune applications: identifying new immune cell subsets (scRNA-seq has discovered large numbers of previously unknown T cell and macrophage subsets, each with unique functional characteristics and disease associations); tracking immune cell state changes (in disease progression or during treatment, transcriptomics can capture immune cells' dynamic trajectory from 'resting' to 'activated' to 'exhausted'); predicting immunotherapy response (tumor microenvironment scRNA-seq profiles can predict patient response to PD-1 inhibitors — whether infiltrating T cells are 'exhausted type' or 'functional type' determines whether immunotherapy can 'awaken' them).
3. Proteomic immunology: from gene instructions to actual action
mRNA is the gene's 'work instruction,' but proteins actually execute immune function. The same mRNA can translate into different amounts of protein under different conditions; proteins undergo phosphorylation, glycosylation, ubiquitination, and other post-translational modifications that profoundly affect function. Therefore, transcriptomics and proteomics don't simply 'correspond one-to-one' — you must directly measure proteins to know the immune system's 'execution results.' Mass spectrometry technology can simultaneously detect thousands of proteins' presence and relative abundance from one plasma or cell lysate sample. Swedish company Olink Proteomics' Proximity Extension Assay (PEA) can simultaneously and precisely quantify over 3,000 proteins in extremely small plasma volumes.
A key proteomics finding in immune aging research comes from Benoit Lehallier et al.'s 2019 Nature Medicine study: systematically analyzing plasma proteomes of nearly 3,000 people at different ages, they found the human proteome doesn't change linearly but shows significant fluctuating transitions at ages thirty-four, sixty, and seventy-eight. In the sixty-year transition, large amounts of immune-related proteins change — highly matching the clinical timepoint of immune aging. This is a milestone dataset in immunomics, providing the most complete description to date of systemic proteome changes during human aging.
4. Metabolomic immunology: energy state determines immune combat power
Metabolomics systematically measures all small-molecule metabolites (amino acids, fatty acids, sugars, nucleotide intermediates, etc.) in a biological sample. Its core insights for immune function have appeared repeatedly in this series: resting T cells and activated T cells use completely different energy metabolism (OXPHOS vs. aerobic glycolysis), with metabolic switching speed and efficiency directly affecting T cell activation speed and intensity; tumor microenvironment's metabolic characteristics (low glucose, high lactate, adenosine accumulation) systematically suppress infiltrating T cell and NK cell metabolic function; and gut microbiota-fermented short-chain fatty acids (butyrate, propionate) as metabolic signaling molecules directly regulate T cell (especially Treg) differentiation and function.
An important metabolomics finding in immune aging research: with advancing age, immune cell mitochondrial oxidative phosphorylation efficiency declines, while oxidative stress products accumulate in tissues, directly damaging immune cell membrane structures and DNA. Harvard University's Bruce Spiegelman team's research, through metabolomics analysis before and after exercise, identified multiple beneficial exercise-induced metabolites (including β-aminoisobutyric acid, BAIBA) that can directly enhance NK cells' mitochondrial function and killing activity — tracking exercise's immune system benefits to the specific metabolite level.
5. Immune repertoire omics: mapping the immune system's 'recognition record'
T cell receptor (TCR) and B cell receptor (BCR, i.e., antibodies) diversity determines how many different antigens the immune system can 'recognize.' Immune Repertoire Sequencing (TCR/BCR-seq), through high-throughput sequencing, systematically measures all T cell and B cell receptor sequences in a person's body, mapping their immune 'recognition record.' TCR library characteristics record the entire history of your immune system: diversity (the breadth of naive T cell diversity, reflecting potential capacity to respond to 'never-before-seen threats'); clonality (the degree of expansion of specific T cell clones, reflecting recent immune activation events); and the CMV imprint (in CMV-infected people, approximately fifty to eighty percent globally, large numbers of CMV-specific T cell clones continuously expand with age, 'occupying' library space and reducing reserves against other threats).
As age advances, TCR library diversity significantly declines — one of immune aging's most direct molecular manifestations. Stanford University's Mark Davis team found that elderly people's TCR library diversity is only approximately ten to twenty percent of young people's. This means that when equally exposed to a new virus, older adults' probability of having T cells that 'happen to recognize it' may be only a fraction of young people's. TCR library diversity is one of immune aging's most quantifiable indicators, and the most direct molecular explanation for why older adults are more susceptible to severe disease from new pathogens like COVID-19.
6. Multi-omics integration: how do five layers of data harmonize?
Five omics layers each provide a perspective, but true insight comes from integration. Stanford's Snyder team's 'Integrative Personal Omics Profiling' study (iPOP, published in Cell 2012): performing fourteen months of monthly genome, transcriptome, proteome, metabolome integrated analysis on one subject (Snyder himself) during health and disease (two viral infections), found each omics layer responds to disease states at different times and in different ways — metabolomics responds first after infection, proteomics follows, transcriptomics last. This suggests disease's earliest warning signals most likely come from the metabolomics level. The COVID-19 systems immunology research illustrated multi-omics integration's speed advantage: within weeks, multiple teams described multi-layer immune differences between severe and mild COVID-19 — a volume of research impossible to complete in years with 'single technology' approaches.
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