Heritability of Spondyloarthritis (SpA) is highlighted by several familial studies and a high association with the presence of human leukocyte antigen (HLA)-B^*27. Though it has been over four decades since the association of HLA-B^*27 with SpA was first determined, the pathophysiological roles played by specific HLA-B^*27 allotypes are not fully understood. Popular hypotheses include the presentation of arthritogenic peptides, triggering of endoplasmic reticulum (ER) stress by misfolded HLA-B^*27, and the interaction between free heavy chains or heavy chain homodimers of HLA-B^*27 and immune receptors to drive IL-17 responses. Several non-HLA susceptibility loci have also been identified for SpA, including endoplasmic reticulum aminopeptidases (ERAP) and those related to the IL-23/IL-17 axes. In this review, we summarize clinical aspects of SpA including known characteristics of gut inflammation, enthesitis and new bone formation and the existing models for understanding the association of HLA-B^*27 with disease pathogenesis. We also examine newer insights into the biology of HLA class I (HLA-I) proteins and their implications for expanding our understanding of HLA-B^*27 contributions to SpA pathogenesis.

An incomplete ascertainment of genetic variation within the highly polymorphic immunoglobulin heavy chain locus (IGH) has hindered our ability to define genetic factors that influence antibody-mediated processes. Due to locus complexity, standard high-throughput approaches have failed to accurately and comprehensively capture IGH polymorphism. As a result, the locus has only been fully characterized two times, severely limiting our knowledge of human IGH diversity. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize IGH variation in a haplotype-specific manner. We apply this approach to eight human samples, including a haploid cell line and two mother-father-child trios, and demonstrate the ability to generate high-quality assemblies (>98% complete and >99% accurate), genotypes, and gene annotations, identifying 2 novel structural variants and 15 novel IGH alleles. We show multiplexing allows for scaling of the approach without impacting data quality, and that our genotype call sets are more accurate than short-read (>35% increase in true positives and >97% decrease in false-positives) and array/imputation-based datasets. This framework establishes a desperately needed foundation for leveraging IG genomic data to study population-level variation in antibody-mediated immunity, critical for bettering our understanding of disease risk, and responses to vaccines and therapeutics.