Oral Presentation Australasian Cytometry Society 43rd Annual Conference and Workshop

Leveraging high-dimensional flow cytometry to assess human immune homeostasis in 3000 individuals (#37)

Thomas Liechti 1 , Sofie Van Gassen 2 3 , Margaret Beddall 1 , David Novak 2 3 , Thiagarajan Venkataraman 4 , Reid Ballard 1 , Yaser Iftikhar 1 , Massimo Mangino 5 6 , Benjamin H Larman 4 , Yvan Saeys 3 , Tim Spector 5 , Mario Roederer 1
  1. ImmunoTechnology Section, Vaccine Research Center, National Institutes of Health, Bethesda, Maryland, USA
  2. Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
  3. VIB-UGent Center for Inflammation Research, Ghent
  4. Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA
  5. Department of Twin Research & Genetic Epidemiology, King's College London, London, UK
  6. NIHR Biomedical Research Centre at Guy's and St. Thomas' NHS Foundation Trust, London, UK

The composition of the immune system varies substantially between individuals while the immune system remains astonishingly stable within an individual over decades. Immune dysregulation can cause autoimmunity and susceptibility to other diseases. However, to date we lack detailed knowledge about the regulation of immune homeostasis which is critical to gain more in-depth insights into the etiology of human diseases.

Here, we describe our collaborative effort to elucidate the regulatory mechanisms of immune homeostasis in 3000 individuals enrolled in the VRC and TwinsUK cohort. To this end, we used 28-color flow cytometry to make a comprehensive assessment of the composition of the peripheral human immune system. We will discuss our thoroughly optimized sample processing and data analysis pipeline, developed with the goal of controlling for technical and experimental errors. To reduce inter-assay variability, we increased the throughput to 200 samples per batch to reduce the number of experiments needed.  We also applied unsupervised data analysis approaches suitable to tackle these large and complex datasets.

We aim to integrate our high-dimensional flow cytometry dataset with genomic, microbiome, systems serology and metabolomics data to assess the genetic and environmental contribution to immune variation. We will demonstrate preliminary analysis of our genome-wide association studies which revealed the genetic regulation of immune traits. In addition, we will show how common chronic viral infections such as CMV drive changes in the immune composition.

Overall, our study enables the precise analysis of regulatory mechanisms of immune homeostasis and assesses the contribution of several genetic and environmental factors in thousands of individuals. Our dataset is the largest and most comprehensive flow cytometry-based effort to analyze the human immune system at steady-state; we will present the lessons learned regarding high-dimensional flow cytometry in large human immunophenotyping studies.