-Human immunology studies typically examine how immune exposures associated with vaccinations, infectious, allergic or autoimmune diseases, or transplantations perturb the immune system with the goal to develop diagnostic tools and therapeutic interventions. While there are established approaches to formally represent the experimental data generated in such studies, which often comprises gene expression data, flow cytometry data, or serology data, the description of the immune exposures themselves is not well standardized. We here present a formal approach to represent immune exposures at a high level of granularity. We capture the exposure process (e.g. 'vaccination' or 'occurrence of allergic disease'), exposure material (e.g. 'Tdap vaccine' or 'House dust mite'), and the associated disease name and stage (e.g. 'allergic rhinitis' and 'chronic'). This representation scheme has been used successfully in the IEDB and an extended version has been adopted by HIPC to capture studies in ImmPort. We are reporting here on this scheme, our ongoing attempts to map the terms used to existing ontologies, and the challenges encountered.
The Immunology Database and Analysis Portal (ImmPort)
[
In particular, ImmPort is the designated repository for data
from studies performed by the Human Immunology Project
Consortium (HIPC) [
New Haven, Connecticut, U.S.A. and
Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New
Haven, Connecticut, USA of centers aimed at performing large scale human immunology studies with a focus on profiling the human immune response to natural infection and vaccination. A key goal of the HIPC consortium is to cross-compare results from different centers. To facilitate this, we set out to develop a standardized representation of immune exposures for HIPC studies that can be stored in ImmPort to represent their central elements in a structured format.
The need to represent immune exposures extends beyond
the HIPC program. Most human immunology studies examine
how the immune system responds to perturbations. Subjects are
compared across cohorts and/or at defined time points that are
intended to isolate the effect of immune exposures. The
Immune Epitope Database (IEDB) [
All HIPC centers funded by the middle of 2017 were asked to supply textual descriptions of study designs that they planned on submitting to ImmPort. We then examined the immune exposures that were part of these study designs and how they would be entered into the IEDB format. As a result of this process, we found that the broader scope of HIPC compared to the IEDB required extension of the IEDB structured representation. In the following, we present the resulting expanded schema to represent immune exposures for HIPC, of which the IEDB immune exposures are a subset. This schema has been implemented by adding columns to the ‘Human Subject Template’ spreadsheet that is used to submit information to ImmPort.
We consider four elements critical to the description of an immune exposure, as listed as the column headers in Table I. The ‘Exposure process’ identifies the type of process through which a host was exposed and the type of evidence for that exposure to have happened, which are tightly intertwined. This is the only element of the four that was deemed mandatory. Based on the choice made for ‘Exposure process’, other elements are required or not applicable as listed in Table I. The ‘Exposure material’ describes what substance(s) the host was exposed to and/or developed immune reactions to as part of the exposure process. The ‘Disease name’ indicates the specific disease of the host associated with the exposure being described and lastly, the ‘Disease stage’ provides a broad classification of how the disease progressed at the time of the study.
To illustrate how this representation was used in practice, Table II shows three examples of studies by actual HIPC centers that involved immune exposures, described in free text (first column to the left), and how these were modeled using the four elements of the exposure scheme (columns to the right). These examples illustrate the three main types of exposure processes, namely ‘administration’, ‘disease’, and ‘exposure without disease’.
Thus, “Adults receiving a Varicella-zoster shot” would be the result of a vaccination ‘Exposure process’ which delivered the ‘Exposure material’ that was the Varicella-zoster virus vaccine. No disease resulted from this immune exposure.
Our intent is to map each of the four data elements
described above to ontology terms with textual and logical
definitions, ideally derived from established ontologies
covering the various domain. For ‘Exposure process’, all
allowed values are listed in the first column of Table I. This
collection of options has been assembled by the IEDB team
over the past 13 years and has been proven to be robust and
stable, with minimal modifications occurring in the last 5
years. Each of the options come with a definition and rules
when it should be applied. These terms will be mapped to
formal external ontology terms, as initiated in Supplementary
Table S1 (https://doi.org/10.6084/m9.figshare.6741791.v1).
The main challenge in this process is that terms for e.g.
‘vaccination’, ‘infectious disease’ and ‘transplantation’ come
from different external ontologies, and presenting users their
definitions side-by-side is not helpful. We are planning to
engage representatives of different ontology communities, and
harmonize their definitions. Until this is done, we proceeded
with implementation of temporary terms for this immune
exposure model in ONTIE [
In addition to the main three categories of immune exposure (administration, disease, exposure without disease) and their subtypes, there are two options (no exposure and unknown) which are not actual types of exposures but rather values to signify two different reasons why it is not possible or meaningful to fill out the exposure type for a given study subject. The value ‘no exposure’ is intended to be used for subjects that are enrolled as negative controls, and indicates specifically that these subjects are *not* be exposed to something. The value ‘unknown’ is used when samples are from subjects for which no relevant exposure information is available. This is applicable when, for example, a study utilizes samples from anonymous blood bank donors in order to establish a ‘normal range’.
For ‘Exposure material’, the vast majority of HIPC studies
submitted to us required specifying an organism that was either
the causative agent of an infection, exposure without infection,
or utilized to vaccinate to protect against future infection.
Organisms can be specified by the broadly utilized NCBI
Taxonomy [
Not all ‘Exposure materials’ in HIPC studies submitted to
us were whole organisms. In the case of vaccinations, specific
antigens are often utilized over whole organisms such as in the
case of subunit vaccines. Also, in the case of multi-valent
vaccines, multiple organisms or antigens of organisms are
combined into one vaccine. We plan to specify vaccines
through the Vaccine Ontology
(http://www.violinet.org/vaccineontology/) [
To specify the ‘Disease name’, the IEDB utilizes values
from the Disease Ontology (DO) (http://disease-ontology.org/)
[
In terms of ‘Disease stage’, the IEDB has defined three values that in combination with disease name clarify some typical major distinctions how a disease manifests in different study subjects: (1) ‘acute/recent onset’ is utilized for subjects that currently have symptomatic disease and may or may not clear it. (2) ‘chronic’ is utilized for subjects that persistently have a disease and it is not considered highly likely that they will soon clear the disease without intervention. (3) ‘post’ is utilized for subjects that have cleared a disease which they had in the past. So far, these broad categories have proven sufficient to also describe HIPC needs, although more detailed description of disease specific stages could be desirable in the future and we are open to further discussion.
The ability to formalize what otherwise would be free-text
is a significant accomplishment to improve the integration of
data across HIPC studies. More importantly, as this model was
adopted by HIPC by adding columns to the Human Subject
data submission template, all studies submitted to ImmPort can
now include the same fields to describe immune exposures, the
HIPC studies will be better connected to other studies in
ImmPort. To ease data entry for these fields and others into
ImmPort spreadsheet templates, work is ongoing through the
CEDAR [
Now that newly entered data will be formalized, improved query and comparisons will be possible due to standardized terminology. We fully expect that as more data gets submitted to ImmPort using this scheme for HIPC, questions will continue to arise, and based on our experience with the IEDB, we expect to handle them by consulting domain expects for the disease of interest. Controversial cases will be presented to the Clinical Subcommittee, to ensure that decisions are made uniformly across the HIPC program. Overall, it has to be stressed that the structured representation of immune exposures is not intended to fully represent every nuance of each study, but rather achieve its intended function to enable a computable high level comparison of immune exposures across studies. Reassessment of how well this model meets the needs of the community and how it improves the quality of the data after several months of use would be beneficial.
This work was supported by the National Institute of Allergy And Infectious Diseases of the National Institutes of Health under Award Number NIH U19 AI118610 and U19AI089992. It would not have been possible without strong support by the ImmPort team, and Patrick Dunn in particular.