CHICAGO—During the 2017 annual Federation of Clinical Immunology Societies (FOCIS) meeting, a session focused on precision immunology and its advances. Precision immunology describes the identification of host, immune system and tumor factors that can be used to select an immunotherapy approach. Thus, the first step in precision immunology is to identify soluble factors, immune cell characteristics and genome immune signatures that may correlate with clinical outcomes. The work in precision immunology is just beginning, but several approaches and several biomarkers are coming to the forefront.
Precision Controls
Advances in precision immunology will ultimately require precision controls. “To the degree that we have standards for immunology, they are from a pretty homogeneous population,” explained Kelly Zalocusky, PhD, a postdoctoral fellow from the University of California, San Francisco, during the session.
To counter that, she and her colleagues created the 10,000 Immunomes Project, a reference of diverse immune measurements from general population controls entered into the National Institute of Allergy and Infectious Diseases (NIAID) ImmPort database. The inaugural version of the reference contains 10,344 unique subjects and more than 42,000 samples (51% female and 49% male). Data types include secreted proteins (Luminex), flow cytometry, mass cytometry via Cytometry by Time of Flight, gene expression, clinical lab tests, hemagglutination inhibition assay titers, human leukocyte antigen type and others. The researchers filtered through the subjects and studies in the ImmPort database and extracted the responses from healthy subjects, thereby creating custom control cohorts.
Specifically, the 10,000 Immunomes Project contains high-throughput analysis of secreted proteins in 2,776 distinct subjects, with up to 63 proteins per subject. The investigators adapted an Empirical Bayes algorithm correct the significant batch effects in the gene expression arrays. Before correcting for the batch effect, they found that protein measurements clustered by study accession. However, the clustering disappeared after batch correction.
The investigators performed a meta-analysis of Luminex data captured and identified known and novel associations between secreted protein levels, age, sex and ethnicity. Their analysis confirmed that leptin levels are higher in female than in male subjects. The researchers also documented numerous novel findings, including elevated serum CXCL5 levels in African-American subjects relative to other races.
The research by Dr. Zalocusky and colleagues also includes a meta-analysis of cytometry data from 1,415 distinct subjects, with up to 24 identified cell subsets per subject.1 The investigators developed an algorithm to automatically find cell subset percentages and name them according to the Human Immune Monitoring Center ontology. Their analysis revealed associations between cell subset percentages, age, sex and ethnicity. Example: They found that age had a strong effect on many cell subsets, including a decrease in naive CD8+ T cells with age and an increase in central memory CD4+ T cells with age.
The data underscore the fact that “We need to take a broader view on what a normal functional immune system is,” emphasized Dr. Zalocusky.
Example: The 10,000 Immunomes Project made it possible to power a pregnant-woman analysis. When they performed this analysis, the investigators found that, during pregnancy, women have a distinct immunological profile when compared with a matched population of non-pregnant women. The results are especially significant in the first trimester, when pregnant women experience a large shift in cytokine expression. The analysis also revealed a pro-inflammatory response from CD4+ T cells and a concomitant anti-inflammatory response from natural killer cells during the first trimester of pregnancy.
The researchers hope the 10,000 Immunomes Project can help advance precision immunology by serving as a source of references that can be used as common controls for comparison with molecular and cellular immune system responses in specific populations.
Single-Cell Gene Expression in RA
Theresa L. Wampler Muskardin, MD, a rheumatologist and pediatrician at the Mayo Clinic Inflammatory Arthritis Clinic in Rochester, Minn., presented results from the first study to examine gene expression in single monocytes from patients with seropositive rheumatoid arthritis (RA) prior to treatment.2 The investigators hope their work will help the development of a more individualized approach to therapy in patients with RA.
Researchers found marked differences in the ratio of expression of interferon (IFN) β/α genes in monocytes of patients with RA. Specifically, a ratio >1.3 of IFN β to IFN α predicted nonresponse to anti-tumor necrosis α (anti-TNFα) therapy. When the investigators analyzed each monocyte subset separately, they identified distinct expression signatures that suggested that further study of monocyte subsets may illuminate molecular differences that determine treatment response to anti-TNFα therapy in these patients.
Response to Infection
Darragh Duffy, PhD, research manager at the Institute Pasteur in France, presented his team’s work on the effect of age, sex and genetics on transcriptional immune responses to bacterial, viral and fungal challenges.3 The researchers hope their results will lay a foundation for new patient stratification strategies that consider the effects of age, sex and genetics on variable immune response outcomes. The investigators found that age affects gene expression in a stimuli-specific manner and that sex had a similar effect across all challenges.
Their analysis identified hundreds of expression quantitative trait loci that were regulated in both cis and trans manners for all stimuli-induced responses. They also confirmed the presence of a toll-like receptor 1 master regulator that has recently been shown to be an important factor that controls variable immunity in European populations. The investigators were able to integrate this transcriptomic and cellular data in a model that describes how age and sex mediate their effects through different immune populations.
Lara C. Pullen, PhD, is a medical writer based in the Chicago area.
References
- Hu Z, Jujjavarapu C, Hughey JJ, et al. Meta-analysis of cytometry data reveals racial differences in immune cells. [pre-print, not peer reviewed].
- Wampler Muskardin TL, Fan W, Jin Z, et al. Distinct single cell gene expression signatures of monocyte subsets differentiate between TNF-alpha inhibitor treatment response groups in rheumatoid arthritis [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10).
- Duffy D, Piasecka B, Urrutia A, et al. Impact of age, sex and genetics on transcriptional immune responses to bacterial, viral and fungal challenges [abstract]. FOCIS 2017 Abstract Supplement. 2017 Jun; p. 61. 2017 Jun:61.
