The polymorphism within the HLA, KIR (killer-cell immunoglobulin-like receptor), and LILR (leukocyte immunoglobulin-like receptor) gene families profoundly influences the evolution of the human immune system. This genetic polymorphism influences disease susceptibility, immune regulation, evolutionary mechanisms, and drug response. This Research Topic brings together a collection of the latest research that delves into the complexity of these gene families, providing novel insights into their associations with diseases and the fundamental knowledge for future investigation.

This Research Topic features three papers exploring HLA associations with distinct diseases—HIV(Rahmouni et al.), dengue (Ghosh et al.), and type 1 diabetes (Noble et al.). Using data from the International Collaboration for the Genomics of HIV, Rahmouni et al. revisited the association of SNPs (single nucleotide polymorphisms) and HLA alleles with HIV-1 elite control. This study reported that HLA-B*57:01, which is part of a very large HLA haplotype block, is significantly associated with HIV-1 elite control in European and African American cohorts. The authors suggested that, in addition to the conventional antigen-presenting role of HLA molecules, HLA class I may provide an alternative molecular mechanism for HIV-1 elite control that involves changes in immune gene expression that could be mediated by transcription factors encoded in this haploblock. Meanwhile, considering the dynamic climate change-associated expansion of vector-borne diseases, Ghosh et al. examined the association of HLA alleles with different stages of dengue across worldwide populations. This review (2) highlighted the complex, often contrasting, and varied nature of HLA-dengue associations worldwide, eliciting the urgent need for further studies among understudied populations to inform public health strategies and combat this emergent threat. Additionally, research by Aharon et al. into macrophage migration inhibitory factor (MIF) functional polymorphism revealed associations with the progression of acute graft-versus-host disease (GVHD) and steroid refractoriness in patients who underwent allogeneic hematopoietic stem cell transplantation (HSCT). The review of HLA-associated type 1 diabetes risk by Noble et al. summarizes work that has evolved since the mid-1970s, presents modern association analysis strategies, and suggests that, while traditional antigen presentation by HLA remains the strongest contributor to disease risk, additional mechanisms are likely to modify risk.

The LILR genes encode for both inhibitory and activating receptors on myeloid and lymphoid cells and are a highly understudied component of the immune system. Hirayasu et al. reported a novel hybrid gene between LILRB5 and LILRB3, namely LILRB5-3. The hybrid gene was detected using the JoGo-LILR (1) tool from a combination of short-read whole genome sequencing (srWGS) and a dataset generated with long-read sequencing. Another study from the same group (Li et al.) demonstrated that fibrinogen induces inflammatory responses via the immune-activating receptor LILRA2 gene, and may represent a novel therapeutic target for inflammatory disease. On a similar note, Khor et al. introduced the development of the software LILR genotype imputation with attribute bagging (LIBAG), which enables copy number imputation for LILRB3, LILRA6, and LILRA3. This approach will enhance the ability to study LILR gene variations and their associations with diseases.

Similarly, a paper by Lancaster et al. describes the major release of Python for Population Genomics (PyPop) version 1.0.0. This specialized software package is designed to process HLA genotype and allele data for large-scale population genetic analyses, specifically for highly-polymorphic gene systems. A highlight of PyPop 1.0.0 is the addition of the asymmetric linkage disequilibrium (ALD) test to the package’s analytic suite. ALD extends historical LD measures, which assumed equal numbers of variants at each locus, for highly polymorphic gene systems, which frequently display different numbers of variants at each locus.

Klussmeier et al. investigate the prevalence and origins of MICA (MHC class I polypeptide-related sequence A) gene copy number variations (CNVs) in more than 2 million individuals. The study found that high-frequency CNVs result from independent nonallelic homologous recombination events between segmental duplications upstream of MICA and MICB.

Lastly, Mora-Bitria and Asquith provide a comprehensive review of how inherited natural killer (NK) cell receptors, particularly KIR molecules, influence T-cell responses. The authors discuss the mechanisms, including NK cell-mediated elimination of activated T cells and the modulation of antigen-presenting cells.