Abstract
There is increasing appreciation that the immune system plays critical roles not only in the traditional domains of infection and inflammation but also in many areas of biology, including tumorigenesis, metabolism, and even neurobiology. However, one of the major barriers for understanding human immunological mechanisms is that immune assays have not been reproducibly characterized for a sufficiently large and diverse healthy human cohort. Here, we present the 10,000 Immunomes Project (10KIP), aframework for growing a diverse human immunology reference, from ImmPort, a publicly available resource of subject-level immunology data. Although some measurement types are sparse in the presently deposited ImmPort database, the extant data allow for a diversity of robust comparisons. Using 10KIP, we describe variations in serum cytokines and leukocytes by age, race, and sex; define a baseline cell-cytokine network; and describe immunologic changes in pregnancy. All data in the resource are available for visualization and download at http://10kimmunomes.org/.
Highlights
The advancement of technologies in preclinical immunology (Elshal and McCoy, 2006; Leng et al, 2008; Maecker et al, 2010; Saeys et al, 2016; Spitzer and Nolan, 2016) and the promise of precision therapeutics in immunology (Ashley, 2015; Collins and Varmus, 2015; Friedman et al, 2015), have together propelled a rapid increase in the production of large-scale immunological data
An exhaustive list of all studies, arms, and planned visits that qualified for inclusion is available as Table S1. This dataset consists of 10 distinct data types
Individual-Level Cell-Subset Measurements across the Population even within this reference population, we find a high degree of variability in the proportion of immune cell subsets from PBMCs as measured by mass cytometry
Summary
The advancement of technologies in preclinical immunology (Elshal and McCoy, 2006; Leng et al, 2008; Maecker et al, 2010; Saeys et al, 2016; Spitzer and Nolan, 2016) and the promise of precision therapeutics in immunology (Ashley, 2015; Collins and Varmus, 2015; Friedman et al, 2015), have together propelled a rapid increase in the production of large-scale immunological data. Similar advancements in other fields, such as genomics, where high-throughput assays spurred a swell of data, have demonstrated the need and benefit of common reference datasets. Resources such as the 1000 Genomes Project (1000 Genomes Project Consortium, 2010, 2012; Sudmant et al, 2015), Health and Retirement Study For the experimental or clinical immunologist, the cost of generating the necessary data from scratch—or the temporal and computational costs associated with standardizing and harmonizing data from publicly available cohorts across platforms, time points, and institutions—is prohibitive without significant resources. The benefit of a common reference population is clear, and large-scale data are publicly available, this need has not yet been met
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