What can naive lymphocytes tell us about our health?

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) analysis is a potent approach to study adaptive immune responses in health and disease. Many aspects of the analysis crucially depend on a reliable knowledge of the genomic loci encoding lymphocyte genes. These loci are extremely variable between individuals, and potentially play an important role in determining genetic predisposition to a wide range of diseases. Despite their importance, we do not know a lot about variations among people in these loci, mostly due to technical difficulties in aligning short reads to these highly repetitive regions. One approach to study these variations is to utilize AIRR-seq data of naive cells to infer individual genotype and haplotype. For this, we generated the largest multi individual data set of naive B-cell repertoires to date, and studied variations by applying a novel method for Bayesian genotyping and haplotyping. We revealed evidence for allele usage bias, as well as a mosaic, tiled pattern of IGHD and IGHV genes. Furthermore, we adapted a machine learning approach to classify celiac patients from healthy individuals based on their naive B cell repertories. The classification model showed very promising results for disease diagnosis based on B cell repertories. Our findings greatly expand the knowledge that can be extracted from lymphocyte repertoire sequencing data.