Antibodies (Abs) are a diverse family of proteins expressed by B cells, and are critical components of the adaptive immune system. They are encoded by hundreds of genes at three primary immunoglobulin (IG) gene regions: the IG heavy chain (IGH) locus, and two light chain loci, IG kappa (IGK) and IG lambda (IGL). The IGH locus, in particular, has been demonstrated by us and others to exhibit extreme genetic variability at both the individual and population levels. This extreme variation is characterized by the occurrence of single nucleotide polymorphisms (SNPs), as well as large insertions, deletions, and duplications spanning tens of thousands of kilobases, and resulting in losses or gains of functional genes (copy number variants, CNVs). Given its inherent locus sequence complexity and extreme genetic diversity, IGH remains a difficult genomic region to study, thus, little is known about the effects of IGH genetic polymorphism on the function of Abs, and the associated effects on disease pathologies and treatment outcomes. However, with the advent of high- throughput sequencing approaches for profiling the expressed Ab repertoire, it has become increasingly clear that IGH genetic variants, including coding and non-coding SNPs, as well as CNVs, likely play a role in the developing Ab response and may contribute to Ab biases observed in many disease contexts. This includes examples in cancer, autoimmunity, infectious disease, and vaccine responsiveness. These data strongly support the idea that not all individuals are poised to mount the same Ab response, and that this, at least in part, can be attributed to IGH genetic determinants. With this in mind, we propose that the integration of locus- wide IGH population genetic data can inform our understanding of the functional B cell response in disease processes, and help direct better clinical care, such as the design of more effective therapeutic and prophylactic strategies. However, no study to date has sought to comprehensively survey IGH variants locus- wide and identify key polymorphisms contributing to variability in the expressed Ab repertoires of healthy adults. Critically, for such an approach to be successful, new genomic tools are required that are capable of overcoming pitfalls associated with current approaches, and that allow for the comprehensive assaying of IGH variants locus-wide. The proposed project will seek to demonstrate the utility of novel IGH genotyping methods to comprehensively characterize, for the first time, associations between germline IGH haplotype variation and signatures in expressed antibody repertoires of healthy adult subjects. This project will yield basic insights into the effects of IGH polymorphisms on inter-individual Ab repertoire variation, with implications for the discovery of novel genomic factors and molecular mechanisms influencing Ab repertoire development and diversity. In addition, this work will lay a foundation for the future integration of IGH genomics into immunological studies seeking to more fully characterize the Ab response in disease and clinical phenotypes.

Public Health Relevance

Individual immune responses are known to track with signatures in the expressed antibody (Ab) repertoire, which we and others have recently demonstrated robustly associate with genetic variants in the immunoglobulin heavy chain locus (IGH); we propose that such findings have broad implications. Here, we apply novel genomic tools to leverage long-read sequencing for comprehensive IGH genotyping, which we use to characterize IGH variants with impacts on Ab repertoire variability in a multi-ethnic healthy adult population. This project will have outcomes with transformative impacts on B cell immunology and immunogenetics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AI142590-02
Application #
9823863
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Ferguson, Stacy E
Project Start
2018-11-15
Project End
2020-10-31
Budget Start
2019-11-01
Budget End
2020-10-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Louisville
Department
Biochemistry
Type
Schools of Medicine
DUNS #
057588857
City
Louisville
State
KY
Country
United States
Zip Code
40292