HLA Typing Application: Antoimmune Susceptibility, Lung Cancer, Crohn's Diseases and Transplantation

The human leukocyte antigen (HLA) system is an important part of MHC, and its gene polymorphism constitutes the molecular basis of human immune recognition. HLA Typing with the help of high-throughput sequencing technology can not only analyze the genetic basis of disease susceptibility at the molecular level but also provide a key basis for clinical decision-making such as predicting the efficacy of inhibitors at immune checkpoints and optimizing the matching of hematopoietic stem cell transplantation. This paper will explain the functional effect of HLA gene polymorphism in the pathological mechanism of diseases through systematic case analysis, and provide theoretical support for exploring precise immune intervention strategies.

Focusing on HLA system, this paper expounds the important role and value of HLA typing in diseases, as well as its application in precise immune intervention strategy.

Analysis of Relationship Between Pathogen Adaptation and Autoimmune Diseases

Recently, researchers, based on the genome resources of Nuwa, combined with advanced HLA genotyping tools, genotyped 31 HLA genes of 8278 individuals worldwide with a resolution of 6-digit, and achieved an accuracy rate of 94%~97% at the amino acid sequence level. This HLA gene data resource (http://bigdata.ibp.ac.cn/HLAtyping) provides a reference for the HLA gene diversity of the world population. Based on HLA data resources, this research system explored the genetic relationship between the pathogen adaptability of the HLA gene and the susceptibility to autoimmune diseases, which provided an evolutionary medicine perspective for understanding the origin and development of diseases.

Overview of HLA data resources and its application in HLA gene evolution (Liu et al., 2025)

The antigenic peptides produced by each pathogen (such as viruses, bacteria, and parasites) have unique sequence characteristics, and different HLA will have different binding abilities to antigenic peptides because of their sequence and structure differences. From the perspective of evolutionary medicine, in the long-term evolution process, individuals carrying specific HLA alleles are naturally selected and retained because they can effectively eliminate certain pathogens.

Different HLA alleles are gradually specialized to combine antigen peptides of particular pathogens, forming a "pathogen -HLA allele" matching relationship. Based on the nature of the HLA molecule presenting antigen, the binding affinity scores of all HLA gene types in the sample population for 31 common pathogen antigen peptides were predicted by using NetMHCpan-4.1 and NetMHCpanII-4.0 tools.

The results showed that the HLA-DRB1 gene had a stronger binding ability to common pathogen antigens than other HLA genes. Among them, HLA-DRB1*07:01 (population frequency AF=8.1%) showed a strong binding ability to diphtheria, HLA-DRB1*08:03(AF = 6.2%) showed a strong binding ability to Clostridium tetanus and Bacillus anthracis, and HLA-DRB1*14:54(AF = 2.7%). In addition, HLA-DQB1*03:01(AF = 22%) showed strong binding ability to Mycobacterium tuberculosis, and HLA-DQB1*06:01(AF = 10%) showed strong binding ability to Bordetella pertussis.

Pathogenic antigen binding map of HLA gene (Liu et al., 2025)

Because of the pleiotropy of the gene and linkage imbalance of the HLA region, the HLA gene not only helps the population to resist exogenous pathogens but also affects the evolution track of autoimmune disease susceptibility in the population. By further analyzing the genetic association between HLA genes adapted by pathogens and HLA genes related to autoimmune diseases, it was found that many pathogens adapted to HLA genes would increase the risk of autoimmune diseases. For example:

• The HLA-DRB1*07:01 gene with adaptability to common pathogens, especially diphtheria Bacillus, will increase the risk of inflammatory enteritis, celiac disease, and psoriasis.
• The HLA-DRB1*08:03 gene, which has adaptability to common pathogens, especially Clostridium albuterol and Bacillus anthracis, will increase the risk of rheumatoid arthritis and multiple sclerosis.
• HLA-DQB1*06:01 gene with strong adaptability to Bordetella pertussis will increase the risk of multiple sclerosis.
• However, the HLA-DQB1*03:01 gene with strong adaptability to Mycobacterium tuberculosis will reduce the risk of multiple sclerosis.

Association map of pathogen adaptation HLA and autoimmune diseases (Liu et al., 2025)

To sum up, NuWa HLA gene data resources show the diversity and difference of HLA gene information by providing high-precision HLA gene data covering large-scale populations and multi-races around the world, and will also provide a reference for HLA gene research in the long term. Based on the application of this HLA data resource in the study of pathogen adaptation and the evolution of autoimmune diseases, the close relationship between the long-term evolution of the population in a pathogenic microbial environment and the occurrence and development of autoimmune diseases is revealed.

This shows that the evolution of genes will be restricted by many factors in the process of human population evolution. On the basis of an existing "imperfect" gene pool, taking population continuation as the core principle, the strategy of "weighing advantages and disadvantages" is adopted for various phenotypes to maximize the advantages of population evolution. Looking at the evolution law of diseases in the population from the perspective of population evolution not only provides new ideas for deeply understanding the origin of diseases and population evolution but also provides important support for optimizing medical practice and coping with modern health crises in the future.

Prediction of HLA Class II Specific Epitopes of Intestinal Flora

The interaction between host T helper cells and intestinal microorganisms plays an important role in maintaining local immune tolerance and regulating parenteral immunity. However, the understanding of microbiome-specific antigens is still limited, and the adaptive immune system actively maintains tolerance to intestinal symbiotic bacteria and interacts with microbiome antigens continuously.

The researchers developed a systematic method to predict HLA class II-specific epitopes by using a humanized bacterial origin T cell antigen (hBOTA) algorithm and identified a group of microbiota epitopes compatible with various HLA-II alleles, covering all major taxonomic units. In particular, an immunodominant epitope from TonB-dependent receptor SusC was found, which was widely recognized and existed in Bacteroidales. In healthy human subjects, the T cell response to SusC was mainly characterized by IL-10, while in patients with active Crohn's disease, the response was related to the increase of IL-17A.

Immunodominant microbiome T cell epitope SusC (Pedersen et al., 2022)

The researchers use the hBOTA algorithm to extract the regions that may have topological accessibility in the original state of phagocytes, and prioritize the symbiotic peptides. A set of predefined HLA class II alleles were used to predict MHCII binding and the corresponding symbiotic immune peptide group was determined. HBOTA is applied to define candidate symbiotic epitopes in population-level microbiomes. Based on the published data from HMP2, hBOTA is applied to the population-level microbiome, which greatly decomposes the search space into smaller MHCII-restricted candidate epitopes.

Considering the huge scale and heterogeneity of the protein group of symbionts, besides the accessibility of epitopes and MHCII binding, the gene expression and popularity of intestinal microbiota are also a basic feature of symbiont epitopes exposed to host immune cells. By selecting at least one epitope core with an expression rate of at least 85% in the sample groups of non-IBD, ulcerative colitis (UC) and CD in HMP2, high-abundance and high-prevalence epitopes were determined, thus the epitope map was further reduced from 948,241 epitope cores to 571 epitope cores, and most of the corresponding 15-mer epitopes showed binding specificity with multiple HLA class II alleles. In a word, a small number of predicted strong binding and universally recognized epitopes were preferentially selected from intestinal microbiota by hBOTA for experimental verification.

hBOTA predicts candidate commensal epitopes from the human microbiome (Pedersen et al., 2022)

In order to verify the immune recognition of epitopes predicted by hBOTA, a group of 48 15-mer peptides was constructed, which encoded highly popular epitope cores and were called microbiome-associated peptides (MAPs). MAPs with high abundance in the HMP2 population and binding specificity with many different HLA class II alleles were finally obtained after screening, and the predicted human microbiota epitopes from major categories were included in general, covering many genera and species.

Given the peripheral circulation of microbial-specific memory Th cells in a stable state, PBMCs were isolated from 40 healthy people and stimulated in vitro with synthetic MAPs to verify their immune reactivity. The intestinal Th cell pool is mainly dominated by T helper cell 1 (Th1), Th17, and regulatory T (Treg) cell phenotypes. All MAPs induced significant cytokine responses in at least one subject, while MAPs(70.8%) induced significant immune responses in more than five subjects, indicating that most hBOTA predicted that MAPs had antigen-specific immune reactivity.

Most MAPs come from multiple species, spanning genera and, in some cases, phylum. Therefore, the change of microbial-specific immune response depends on the host, which may be related to the dynamics of T cell activation and differentiation caused by host-microbiome interaction and the high dependence on environmental adjustment.

T cell responses to microbiome epitopes are widespread in healthy subjects andelicit diverse cytokine profiles (Pedersen et al., 2022)

The Relationship Between HLA and Lung Cancer

Tuberculosis seriously affects human health, and genetic factors have an important impact on its susceptibility. It is known that genetic defects mainly affect IFNγ-mediated immunity, and TNF is essential to control Mycobacterium tuberculosis infection, but the relationship between TNF deficiency and tuberculosis is not clear.

The purpose of this study is to reveal the relationship and mechanism between hereditary TNF deficiency and pulmonary tuberculosis and to provide a new perspective and potential target for the prevention and treatment of pulmonary tuberculosis.

Firstly, the patients were analyzed by WES and genome linkage analysis to determine TNF variation. Secondly, the effects of this mutation on TNF protein and function were detected by Western blot and other experiments. Then, immunophenotype analysis and scRNA-seq were carried out on patients' white blood cells to explore the effect of TNF deficiency on immune cells. Finally, macrophages were differentiated and infection experiments were carried out to analyze the relationship between TNF deficiency and pulmonary tuberculosis.

HLA-II heterozygosity protects against lunh cancer in smokers (Krishna et al., 2024)

By analyzing the genetic, clinical, environmental, and longitudinal clinical data of the UK Biobank and Finland Genome, it is found that HLA-II heterozygosity is related to reducing the risk of lung cancer. In the UK Biobank, HLA-II heterozygosity is significantly enriched in the control population, which is related to the reduction of lung cancer risk, and this protective effect is more obvious in smokers. Similar results were observed in FinnGen. In addition, the association between HLA-II heterozygosity and lung cancer risk is not affected by other clinical and genetic risk factors, including genome-wide polygene risk score.

HLA genotype and associations with lung cancer risk in UK Biobank and FinnGen (Krishna et al., 2024)

By calculating the follow-up time and censoring of lung cancer patients in UK Biobank, it is found that smokers have the highest risk of lung cancer at present, followed by former smokers. At present, HLA-II heterozygosity is associated with reducing the incidence of lung cancer in former smokers, and this protective effect has been observed at different HLA-II loci. In addition, the association between HLA-II heterozygosity and lung cancer risk has also been verified in different lung cancer subtypes.

Maximal HLA-|l heterozygosity is associated with reduced lung cancer incidenceamong smokers in UK Biobank and FinnGen (Krishna et al., 2024)

Fine localization analysis of the amino acid sequence of the HLA-II peptide binding groove showed that about 33% of amino acid positions were polymorphic. Through multivariate logistic regression analysis, it was determined that five positions in the DRB1 peptide binding groove and seven positions in the DQB1 peptide binding groove were significantly related to the risk of lung cancer. Some of these loci are associated with other diseases, such as P70 associated with rheumatoid arthritis and Parkinson's disease in DRB1, and P57 associated with type 1 diabetes in DQB1.

Heterozygosity fine-mapping and structural analyses of peptide binding groove amino acid sequences (Krishna et al., 2024)

By analyzing the single-cell RNA sequencing data of normal lung tissues from three independent cohorts, it was found that smoking could lead to the up-regulation of HLA-II gene expression in alveolar macrophages and the increase of other inflammatory markers. In addition, smoking can also lead to the up-regulation of HLA-DRB1 expression in epithelial cells. These results suggest that smoking may affect the risk of lung cancer by regulating the expression of the HLA-II gene and inflammatory pathway.

Tobacco smoking-induced inflammatory programs identified via single-cell RNA-sequencing analysis of the normal lung from three independent cohorts (Krishna et al., 2024)

Through the analysis of the lung cancer tumor genome, it is found that HLA-II LOH is very common in non-small cell lung cancer (NSCLC), which is equivalent to the incidence of HLA-I LOH. HLA-II LOH is related to tumor mutation load (TMB) and the size of the new peptide library, and LOH tends to lose HLA-II alleles with a large new peptide library. In addition, HLA-II LOH can also affect the expression of HLA-II in NSCLC epithelial cells.

HLA-I and HLA-ll loss of heterozygosity andimmunopeptidome dynamics inlung cancer (Krishna et al., 2024)

Provide Population Genetic Data for Transplantation

Non-classical HLA class I genes and MICA/MICB play an important role in the immune system, and their association with various diseases is attracting more and more attention from scientists. Using the second-generation sequencing (NGS) method based on Hybrid Capture, the researchers detected the genotypes of 17 HLA-related loci in 598 healthy people in China, Shenzhen, calculated the frequencies of alleles and haplotypes, and analyzed the linkage disequilibrium (LD) of alleles between all adjacent loci and the overall linkage disequilibrium of all allele pairs. These results may provide useful resources for population genetics research, and provide important reference for the study of the relationship between HLA polymorphism and many diseases.

A total of 358 human leukocyte antigen (HLA) alleles were identified, including 177 Class I alleles (142 classical and 35 non-classical alleles) 137 Class II alleles, as well as 29 MICA alleles, and 15 MICB alleles. Among the identified HLA loci, HLA-B has the highest polymorphism, with 66 different alleles, followed by -DRB1 (42 alleles), -A (41), -C (35), -DPB1 (30), -MICA (29), -DQB1 (20) and -DQA1. DRB3 (9), -DPA1(8), -DRB5 (8), -G (8), -E (6), -F (5), -DRB4 (4). HLA haplotype frequency analysis may be helpful to predict the genotype of unknown HLA loci based on known loci, thus improving the probability of finding a perfect match donor in the registry.

The number of distinct alleles observed in 17 HLA- related loci (Liu et al., 2025)

Conclusion

With the development of precision medicine, HLA typing is evolving from simple genetic marker analysis to a comprehensive evaluation system integrating multi-dimensional data such as immune microenvironment and tumor mutation load. This interdisciplinary application paradigm not only deepens our understanding of the mechanism of disease occurrence and development but also opens up a more forward-looking path for the prognosis judgment of immune diseases and the formulation of individualized treatment plans for cancer.

In the future, with the combination of single-cell HLA typing technology and AI prediction model, this field may release greater clinical value in disease early warning, curative effect monitoring, and new immunotherapy development.