Discussion
In addition to re-establishing the hypo- and hyper-inflammatory COVID-19
ARDS phenotypes, our results segregate the hypoinflammatory group into
low and high viral load subphenotypes. We have also transitioned to a
more accurate clustering by sampling the lung compartment as opposed to
the plasma. The potential advantage of our approach is obtaining
hypothesis-driven clusters by linking the semi-quantitative viral loads
and immune activation status. This may permit the treating physician to
utilize a different balance between immune modulators and antiviral
therapies as patients in the hypoinflammatory high viral load group may
exhibit pathophysiology secondary to direct viral cytopathic effects
rather than immunopathology. Inhibiting the immune responses further in
these patients may ultimately prove detrimental.
Few studies have comprehensively described the clinical phenotypes in
COVID-19 ARDS. Sinha et al confirmed the traditional hypo- and
hyperinflammatory phenotypes in a cohort of 39 patients by using
clinical variables and plasma IL-6 and TNFR1 concentrations (4). Cluster
2, the hyperinflammatory phenotype, was observed in 10-21% of the
patients and was characterized by higher organ failure and mortality. In
a subsequent study, the authors overlapped the ARDS phenotypes defined
by systemic inflammation and multiorgan failure to severe COVID-19 and
reassessed the presence of the 2 phenotypes by using latent class
analysis (5). 14% and 19% of patients from the 2 clusters were
misclassified pointing towards noteworthy overlap between the clusters.
The hyperinflammatory phenotype had higher proinflammatory markers,
lactate and lower bicarbonate. The response to corticosteroids
(nonrandomized, various formulations) was more prominent in the
hyperinflammatory group. Interestingly, the nasopharyngeal SARS-CoV-2
RT-PCR Ct was associated with mortality only in the hypoinflammatory
phenotype. Our study defines the high viral load subgroup part of the
hypoinflammatory phenotype which may be a contributor to detrimental
outcomes.
Bos et al employed group - based trajectory models to define COVID-19
ARDS phenotypes by looking at longitudinal data (12). Subphenotype 2
(33% of the patients) was characterized by higher minute ventilation -
a marker of increased dead-space-, more venous thrombotic events, acute
kidney injury and higher mortality. Cytokine concentrations were not
available, but IL-6 has been linked with endothelial dysfunction and
thrombosis in previous studies.
The main debate in severe COVID-19 remains: what is the driver of ARDS
and bad outcomes? An exaggerated immune response or uncontrolled viral
replication similar to other respiratory viral infections such as
RSV?(13) It is known that coronaviruses have the capability to inhibit
and delay the type I IFN immune response. In turn, this will promote
continued viral replication and possibly immunopathology (14). Several
autopsy reports have contributed to this debate: studies confirmed the
presence of SARS-CoV-2 in lung specimens while others failed to find
significant direct viral cytopathic effects (6–8).
The immune inflammatory response has been sought as a viable explanation
and potential treatment target in severe COVID-19. Yet, numerous studies
failed to detect a “cytokine” storm fingerprint in the plasma of
patients with severe COVID-19 (3, 15). Usually, the plasma cytokine
concentrations were similar or even 10 times lower in COVID-19 patients
than in septic or ARDS patients (3). In a comprehensive study, Wauters
et al analyzed the interplay between the innate and adaptative immune
responses using single cell transcriptomics on BALs and found abundant
and dysregulated T cells along with hyperinflammatory monocytes in
critical COVID-19 (16). Viral- RNA tracking demonstrated infected lung
epithelial cells along with neutrophils and macrophages involved in
viral clearance.
Several other authors have argued instead for stimulating the immune
response in critically ill patients with COVID-19 and not suppressing
it. Remy et al compared the T cell subsets and quantified the T cell
IFN-γ and monocyte TNF-α production in patients with severe COVID-19,
sepsis, critically ill non-septic and healthy volunteers (2). Patients
with severe COVID-19 were characterized by impaired immune effector cell
function which was partially restored ex vivo by administering
IL-7. Analyzing these discrepancies and also the improved mortality with
several immune modulators prompted our second hypothesis that using the
bronchoalveolar lavage will give us a more accurate image of the
lung-centric immunity.
In our previous study, we described the inflammatory immune
dysregulation occurring in the lower airways where 28/35 cytokines had
elevated levels. Among those only IP-10 BAL levels correlated with
plasma levels (11). Therefore, most peripheral blood cytokine
concentrations serve as inaccurate/ weak markers in quantifying the
intensity of the immune response during severe COVID-19. This may
contribute to the discrepancy between low blood cytokine concentrations
but positive clinical response to corticosteroids and other immune
modulators. The RECOVERY trial was the first randomized controlled trial
to show a significant mortality reduction in patients treated with
dexamethasone (17). A randomized Bayesian trial showing a trend towards
improved organ support- free days was stopped early after the results of
the RECOVERY trial were released (18). Given these results and the fact
that the hyperinflammatory phenotype characterizes only a minority of
patients (4), it results that dexamethasone improved mortality in
patients with hypoinflammatory phenotype as well. This opens the
hypothesis of treatment heterogeneity within the phenotypes,
hypothesis that our study tried to ellucidate.
The second most studied class of immune modulators in COVID-19 are the
IL-6 blockers. Many studies missed to detect a significant IL-6
concentration in plasma (5, 15, 19–21). Multiple non-randomized studies
of IL-6 blockade suggested a benefit in reducing intubation rates and
even mortality (22, 23) yet the initial randomized controlled trials
failed to prove a benefit in moderate/ severe COVID-19 pneumonia (24,
25). Meta-analyses found that IL-6 blockers decreased the need for
mechanical ventilation and mortality in both critically ill and
non-critically ill patients albeit with a small effect size with
mortality risk ratio of 0.89, (95% CI 0.82 to 0.96) (26, 27).
After dexamethasone became the standard of care in patients diagnosed
with COVID-19 requiring oxygen, several studies tried to quantify the
benefit of adding a second immune modulator agent to corticosteroids.
Despite the debate on systemic inflammation, several other immune
modulators acting on distinct pathways have shown additional benefits in
hospitalized patients with COVID-19 treated with steroids, mainly in
reducing rates of intubation. These include tocilizumab, an antagonist
of the IL-6 receptor (28), baricitinib, a JAK 2 inhibitor (29),
lenzilumab, a Granulocyte-macrophage colony-stimulating factor (GM-CSF)
blocking antibody (30) and anakinra, an IL-1 blocker (31).
Similar to the small signal to harm in the hypoinflammatory phenotype
(5), the small effect sizes and partial lack of replication point
towards lack of power or heterogeneity of treatment effects and mixing
responders and non-responders as possible causes (32). This may be
explained by differences in semi-quantitative SARS-CoV-2 RT-PCR. So far,
the SARS-CoV-2 RT-PCR tests have been developed as qualitative tests and
the relationship between Ct and viral load at very low and very high
viral loads is not linear. Ct thresholds have been linked to severity of
illness, transmissibility and differentiating replicating virus from
persistent shedding after a resolved infection (33, 34). We used the
same test in all of our patients and also a very standardized
bronchoscopy procedure and sampling technique. The results for theS and Orf gene targets were very similar in our sample
with less than 0.5 variation in Ct. While the qualitative outputs of the
nasopharyngeal swabs and BAL correlate in terms of positive and
negative, no published reports establish the correspondence between Ct
values in the upper vs lower airways (35, 36). As such, we elected to
use SARS-CoV-2 RT-PCR Ct in the BAL as a surrogate marker for the amount
of virus.
The most important limitation of our study is the small sample size. It
is possible that differences between groups may have been missed. The
similar distribution and signal described in other published related
studies lends external validity to our results. As it has been noted,
identifying groups based on theory should take precedence since
clustering/ phenotyping techniques will always find groups in the data
(37). A recent study by Sinha et al questions the use of machine
learning without biomarker data in grouping patients to explain
heterogeneity of treatment effects (38). When analyzing 3 RCT in ARDS by
using 9 clustering methodologies, the authors found a wide variation to
identify clusters which was only exacerbated in the absence of
biomarkers. Our study pushes phenotyping one step further by using a
biologically plausible hypothesis (i.e. the infection matters in
explaining heterogeneity of treatment effects) and providing a
measurable marker in semi-quantitative SARS-CoV-2 in BAL. Our results
expand on previous studies by showing the role of SARS-CoV-2 RT-PCR in
phenotyping patients with COVID-19 ARDS and providing evidence that the
lower airways are the best compartment to sample for accurately
assessing the intensity of the immune response. Since we do not have BAL
or plasma samples prior to dexamethasone to verify the “native”
clusters, it is possible that more patients could have been grouped
under the “hyperinflammatory” phenotype earlier in the disease
process. We provide a homogenous cohort of mechanically ventilated
patients with COVID-19 ARDS but this may also be labelled as a
convenience sample since these were patients undergoing bronchoscopy
based on clinical reasons. Yet, only 1 patient in cluster 1 had
cryptococcal pneumonia and 1 in cluster 2 had Staphylococcus
aureus pneumonia, no patients in cluster 3 exhibited positive BAL
cultures. It is unlikely that the use of remdesivir altered our results
as previous reports did not find a difference in nasopharygeal Ct values
when patients were treated with remdesivir (39). We counteracted the
different timeline of sampling by standardizing all variables per week.
Conclusion: Our hypothesis-driven study adds the infection
dimension to ARDS phenotypes. We identified a unique group of
hypoinflammatory with high viral load patients that is biologically
plausible and where additional immune modulators may have a detrimental
role. Future studies are needed to establish a threshold for SARS-CoV-2
RT-PCR and to assess the immune cascade before and after administration
of additional immune-modulating therapies.