ArticleImmunogenetics2022
Natural LILRB1 D1-D2 variants show frequency differences in populations and bind to HLA class I with various avidities.
Article in Immunogenetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Development and evaluation of an inhalable nanoemulsion system for enhancing NK cell function against osteosarcoma pulmonary metastases.Frontiers in immunology · 2026Article
- Profiling associations of interactive ligand-receptors (HLA class I and KIR gene products) with the progression to type 1 diabetes among seroconverted participants.Diabetologia · 2025Article
- Inhibitory leukocyte immunoglobulin-like receptors, subfamily B (LILRBs) in human diseases: structure, roles, mechanisms, and clinical applications.Theranostics · 2025Review
- Article
- Transcriptome profile analysis in spinal cord injury rats with transplantation of menstrual blood-derived stem cells.Frontiers in molecular neuroscience · 2024Article
- Deciphering the role of alternative splicing in neoplastic diseases for immune-oncological therapies.Frontiers in immunology · 2024Review
- Perspectives of targeting LILRB1 in innate and adaptive immune checkpoint therapy of cancer.Frontiers in immunology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Leukocyte immunoglobulin-like receptor B1 (LILRB1) is widely expressed on various immune cells and the engagement of LILRB1 to HLA class I and pathogen-derived proteins can modulate the immune response. In the current study, 108 LILRB1 alleles were identified by screening the LILRB1 locus from the 1000 Genomes Phase 3 database. Forty-six alleles that occurred in three or more individuals encode 28 LILRB1 allotypes, and the inferred LILRB1 allotypes were then grouped into 9 LILRB1 D1-D2 variants for further analysis. We found that variants 1, 2, and 3 represent the three most frequent LILRB1 D1-D2 variants and the nine variants show frequency differences in populations. The binding assay demonstrated that variant 1 bound to HLA class I with the highest avidity, and all tested LILRB1 D1-D2 variants bound to HLA-C with lower avidity than to HLA-A and -B. Locus-specific polymorphisms at positions 183, 189, and 268 in HLA class I and dimorphisms in HLA-A (positions 207 and 253) and in HLA-B (position 194) affect their binding to LILRB1. Notably, the electrostatic interaction plays a critical role in the binding of LILRB1 to HLA class I as revealed by electrostatic analysis and by comparison of different binding avidities caused by polymorphisms at positions 72 and 103 of LILRB1. In this paper, we present a comprehensive study of the population genetics and binding abilities of LILRB1. The data will help us better understand the LILRB1-related diversity of the immune system and lay a foundation for functional studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.