Food allergy associated immune remodelling during OIT
Sequencing bulk cell populations such as whole blood or peripheral blood
mononuclear cells (PBMC) to identify biomarkers of allergy or treatment
success is an attractive endeavour due to the relative ease of
collecting this type of specimen in clinical settings. Blood is
routinely collected in these settings and a marker measured directly
with little to no need for cell culture would be practical for ease of
implementation into clinical practice. This “baseline predicts
outcome” approach has been successfully applied to predict the immune
response to vaccination using systems biology
methods14. However, one important limitation to this
approach is lack of resolution since allergen reactive cells make up
only a tiny fraction of the overall whole blood or PBMC population and
do not persist for very long in the peripheral
circulation15. A second challenge is that the cellular
composition of these fractions can be highly variable between
individuals and across different age groups, limiting the likelihood of
identifying a universal biomarker 16. Despite these
challenges, transcriptional studies have identified immune changes in
whole blood and PBMC that are linked to peanut or egg allergy, acute
allergic reactions, and OIT treatment effects.
In egg OIT, downregulation of genes involved in TREM1 signaling, IL-6
and IL-17 were identified in PBMC after eight months of
treatment17. Changes were linked to regulation of
innate immunity and inflammation: Toll-like receptors (TLRs),
interferons (IFNs), chemokines, cytokines, and adhesion molecules; and
regulation of T cell genes including Th17 cells, regulatory T cells, and
Th2 cells. Comparing outcome groups, expression profiles were largely
overlapping between groups, however there was some evidence of delayed
immunological remodelling in the group who did not reach the target dose
(n=23; partially desensitised) versus those who reached the target
maintenance dose (n=22). Characterised by persistence of Th2 responses
and lack of upstream regulator engagement in the partially desensitised
group. Interpretation of this study in the context of lasting outcomes
following OIT was limited as outcomes were defined by the ability of
participants to reach the target dose of 1g following 8 months of
build-up. Because there is no longitudinal assessment of clinical
outcome following treatment it is not possible to delineate whether
molecular changes were linked to remission or desensitisation without
remission.
Several differentially regulated genes have been reported following OIT
with omalizumab in whole blood18. Of interest, 108 of
the 680 differentially expressed genes (DEG) associated with peanut OIT
+ omalizumab overlapped with DEG linked to acute allergic reactions to
peanut in another study19. The common DEG between the
two studies primarily had opposing direction of effect, indicating that
treatment effects were in part mediated through modulation of downstream
events that occur during an acute allergic reaction. There were no
consistent transcriptional changes linked to omalizumab alone prior to
peanut OIT. However, the cohort was a mix of those who managed to
tolerate the maintenance dose (n=11), and those who failed to tolerate
the maintenance dose (n=6). Transcriptional changes were not analysed
based on clinical outcomes. Instead, the analysis was adjusted to
account for changes associated with specific outcomes. Therefore, the
detected immune changes are not linked to treatment success but rather
to treatment independent of outcome18. Comparing DEG
between the egg and peanut OIT transcriptional studies, there was little
overlap between the early transcriptional signals detected in the egg
study (3 months into OIT) compared to the genes associated with
omalizumab + peanut OIT (measured after 2-3 years on treatment). Of the
genes that did overlap between the two studies, the majority were not
detected with the same direction of effect. This finding may be due to
the considerably distant windows at which DEG was measured in each
study, each possibly capturing distinct phases of immunological
activity. Alternatively, differences may be due to other variable
factors between the two populations, such as differences in treatment
regime, genetic background of individuals, age or other demographic
factors. Genes that were consistent between the two studies were not
immune genes but rather genes associated with cellular processes such as
transport proteins, protein synthesis, mitochondrial function.
Although there has been interest in the potential role of T follicular
helper 2-like cells in allergy pathogenesis20, a study
applying single-cell sequencing reported that OIT did not modify this
population21. The T follicular helper 2-like cell
population was, however, positively associated with peanut sIgE
production in the same OIT population. Another study identified that
changes in gamma delta Tregs (γδTregs) may play a role in immunological
mechanisms of OIT. Reduced numbers, comparable to those of health
controls were observed by week 6 of OIT22. However,
data are only available within a limited window of time and no food
challenges were performed to determine clinical outcomes.
B and T cell receptor profiling may also provide further mechanistic
insight. A novel method using gene expression profiling was recently
developed and applied to study how OIT modifies the B cell repertoire in
n=17 peanut allergic individuals before and after
treatment23. Enrichment of selected immunoglobulin
heavy chain alpha and gamma clones was identified following OIT. TCR
beta-chain profiling showed that peanut allergy was associated with a
pool of convergent activated clones, with 17% of the sequences shared
between individuals. The frequency of these clones in the effector cell,
but not regulatory cell compartment was higher in those with more
reactive phenotypes24. Application of methods to study
allergen-specific B and T cell receptors, alongside gene expression
profiling, in larger cohorts may reveal insights into selective clonal
anergy or other patterns linked with clinical outcomes following OIT.
Key findings from studies applying techniques to study genes within
co-expression networks have identified genes that are predicted to be
drivers of the allergic response. By examining the transcriptional
profile of whole blood samples (n=19) across a time course (baseline,
2hr, 4hr) following food challenge, researchers were able to identify
six genes LTB4R, PADI4, IL1R2, PPP1R3D, KLHL2, and ECHDC3 as having
causal roles during peanut reactions19. Using similar
methods to examine whole blood collected from children with (n=23) or
without (n=7) nut allergy, another group identified three gene drivers
of nut allergy; IFIH1, DRAM1 and ZNF512B. A module enriched for type I
interferon genes, with IFIH1 as the key driver, was most positively
associated with nut allergy25.