Discussion
This study aimed to identify biomarker patterns corresponding to the
disease and the extent of clinical improvement upon systemic anti-IL4Rα
treatment. We report on known (CCL17), but also somewhat novel (CCL13,
E-selectin, CCL22, and CCL27) proteomic biomarkers in severe AD
patients. Exploring these biomarkers upon systemic dupilumab treatment
CCL17, CCL13, E-selectin CCL22, and CCL27 protein levels decreased in
our patients, whereas the BDNF increased. Skin microbial composition
showed a decrease in S. aureus colonization upon treatment,
following the clinical improvement. By contrast, miRNAs could not be
classified as potential biomarkers of therapy response.
Our data has led us to propose a panel of composite biomarkers which may
assist in predicting clinical responses, defined as a decrease of less
than 75% in initial SCORAD values and body surface area affected by
atopic dermatitis. Despite the overall positive clinical efficacy of
dupilumab, as demonstrated by the high percentage of patients who
experienced substantial improvement, a subpopulation of non-responders
who may benefit from other treatment options remains.
A report by Hamilton et al. also described changes in biomarkers after
initiation of dupilumab systemic therapy in various atopic diseases and
found that dupilumab suppressed multiple Th2 mediators such as CCL17,
total IgE, periostin, and eotaxin-3, consistent with our
findings20. Our study adds to the literature by
identifying additional biomarker candidates through proteomic screening.
Observed changes of CCL17, CCL13, CCL27, and CCL22 after dupilumab
therapy reflect a Th2-inflammation-dependent response. We also observed
an increase in the levels of BDNF after 6 months of therapy. BDNF is a
protein that is not directly dependent on Th2-pathway and is secreted
from eosinophils in patients with atopic dermatitis21.
Our study found that levels of BDNF were higher in patients with atopic
dermatitis compared to non-atopic individuals, which is consistent with
previous reports in both children22 and
adults21. The observed increase in BDNF after
dupilumab treatment may be a consequence of transient
dupilumab-dependent blood eosinophilia but its relevance remains
elusive23.
E-selectin was identified as a potential candidate for a good response
to dupilumab therapy in our proteomic screening. E-selectin has been
previously reported to be increased in atopic dermatitis and correlated
with disease severity24. The decrease in both CCL17
and E-selectin may be a result of decreased inflammation in the skin, as
these molecules are known to be coexpressed in dermal
microvessels25. Like CCL17, E-selectin plays an
important role in leukocyte migration into inflamed skin. Soluble
E-selectin may result from the proteolytic cleavage of its
membrane-bound form, and its presence in the serum could reflect the
general state of skin inflammation24.
It is important to note that the observed changes in biomarker levels in
our study may be the result of the decrease in clinical severity rather
than a direct effect of dupilumab therapy. Other systemic therapeutics
have also been shown to decrease cytokines downstream in the
inflammatory cascade. For example, previous studies have reported
reductions in CCL17, IL13, and IL22 levels after treatment with
cyclosporine A (CyA)26,
tralokinumab27, or fezakinumab28 in
patients with atopic dermatitis. The identification of biomarkers
specific to a particular therapy may offer insights into the mechanisms
of the disease. However, it is arguably more important to identify
biomarkers that specifically represent the severity of the condition for
effective clinical management.
Many groups demonstrated a correlation between CCL17 levels and the
SCORAD score29–31. However, atopic dermatitis is a
complex and heterogeneous disease, with multiple contributing factors
such as intrinsic and extrinsic pathways, skin barrier defects, and
genetic background, involving multiple cell types. This heterogeneity
makes it difficult to rely on a single biomarker as an objective
indicator of disease severity.
Limitations have been identified with commonly used clinical scores such
as SCORAD and EASI32 for assessing atopic dermatitis,
which undermines their use in clinical studies33,34.
These scores are often semi-quantitative and subjective, leading to a
lack of objective indicators for disease severity, making it challenging
to monitor the disease in a longitudinal manner35,36.
Therefore, a set of biomarkers (serological and/or histological) may be
needed to objectively address the severity of the disease, as it might
be more suitable as a baseline truth than widely used subjective
clinical scoring systems37.
A recently published study by Nakahara et al. underlined the
difficulties to identify a biomarker that correlated with the severity
of AD as measured by the EASI score during a 16-week therapy
period38. Notably, the study suggested that two
biomarkers, CCL17 and CD25s, have the potential to predict response to
dupilumab therapy as measured by POEM and pruritus NRS scales. These
findings align with the results of our study, in which CCL17 and CD25s
were included in our composite classification model (along with Notch1
and E-selectin) and performed as the best predictors of a good response
to therapy.
We did not observe significant changes in miRNA expression after
treatment with dupilumab. miRNA levels in the blood change quickly in
acute conditions14 and may reach a state of
equilibrium in a relatively short time, which could explain observed
similar levels of miRNA before and after therapy. Alternatively, the
similarities of miRNome before and after treatment may reflect the fact
that dupilumab is managing the downstream effects of Th2 inflammation
which does not play a major role in miRNA expression. Nevertheless, we
were able to identify differences in miRNA levels between atopic
dermatitis, psoriasis, and healthy individuals that may be disease
dependent.
In a recent study, miRNA expression levels in the skin and serum of AD
and psoriasis patients were compared to healthy
individuals39. The authors reported differentially
expressed levels of (among others): hsa-miR-378a-3p, hsa-miR-146b, and
hsa-miR-25-3p in skin and hsa-miR-122-5p in serum. These results are in
line with our findings, although the authors used different analytical
methods (Affymetrix arrays) and different biomaterials. However, the
authors report significantly more differentially expressed miRNA from
skin samples than from serum, suggesting that skin biopsies are a more
suitable material for identifying mechanistically relevant miRNA
biomarkers.
In our study, we identified a treatment-related shift in the composition
of microorganisms colonizing the skin of AD patients, which was
associated with the severity of the disease (IGA, SCORAD, and BSA). The
use of the microbiome as a biomarker for AD severity has been proposed
in recent literature11, but there is currently a lack
of consensus on standardized methodology and a need for further
large-scale, longitudinal clinical studies to establish its usefulness.
A previous study reported that dupilumab treatment decreased skin
colonization with S. aureus and increased skin microbial
diversity in children with AD40. Our findings extend
these observations to adults. However, we did not find a clear
correlation between baseline skin microbial composition and treatment
outcomes.
Taken together we identified several proteomic and microbial, but no
miRNA, biomarkers in AD patients receiving systemic IL-4Ra targeted
treatment. Based on our clinical data, we were able to identify a set of
protein-based biomarkers associated with a good clinical response.
Nevertheless, these biomarkers need to be validated in a larger cohort
during a longer follow-up period. Although the lack of skin based
analysis might be regarded as a weakness of our study, the measurement
of biomarkers in a patient’s serum is more suitable in daily clinical
practice and should be further explored to select the optimal treatment
in a currently broadening spectrum of targeted therapies.