Assessing T cell clonal size distribution: a non-parametric approach

TL;DR

This paper introduces a non-parametric statistical method to analyze T cell clonal size distributions from sequencing data, revealing power law scaling and differences between healthy individuals and an autoimmune patient.

Contribution

It presents a novel non-parametric approach for assessing T cell clonal distributions and provides quantitative analysis of power law decay exponents in health and disease.

Findings

Power law scaling observed in T cell distributions across individuals.

Decay exponents differ significantly between healthy and autoimmune states.

Post-therapy distributions converge towards typical healthy values.

Abstract

Clonal structure of the human peripheral T-cell repertoire is shaped by a number of homeostatic mechanisms, including antigen presentation, cytokine and cell regulation. Its accurate tuning leads to a remarkable ability to combat pathogens in all their variety, while systemic failures may lead to severe consequences like autoimmune diseases. Here we develop and make use of a non-parametric statistical approach to assess T cell clonal size distributions from recent next generation sequencing data. For 41 healthy individuals and a patient with ankylosing spondylitis, who undergone treatment, we invariably find power law scaling over several decades and for the first time calculate quantitatively meaningful values of decay exponent. It has proved to be much the same among healthy donors, significantly different for an autoimmune patient before the therapy, and converging towards a typical value afterwards. We discuss implications of the findings for theoretical understanding and mathematical modeling of adaptive immunity.