IncellDx Launches First Diagnostic Test For Long COVID-19 In Europe

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 IncellDx, a company based in California-USA specializing in a precision medicine and an array of advanced novel diagnostics and prognostics for the treatment of various infectious disease and cancer is officially launching the world’s first diagnostic test for Long COVID in Europe this month after securing the CE-IVD marking in Europe.

The company’s utilized its innovative technology platforms that enables simultaneous cell classification and single cell analysis of proteomic and genomic biomarkers to develop the IncellDx incellKINE Long COVID In Vitro Diagnostic test kit that is intended for hospital or clinic use only.

Accordingly, the CE marking is supported by data from a validation study conducted by one of the world’s largest providers of diagnostic services, showing the test provides greater than 90 percent accuracy across COVID strains.
 
The validation test was developed based on clinical studies published in the peer reviewed journal Frontiers in Immunology, which showed that IncellDx researchers generated credible, objective disease scores for long COVID using machine learning and artificial intelligence to measure and analyze sets of inflammatory markers called cytokines and chemokines.
https://www.frontiersin.org/articles/10.3389/fimmu.2021.700782/full

Individuals infected with SARS-CoV-2 exhibit distinct severity patterns which have been associated with different immune activation profiles. Interestingly, in some cases longer times are required to experience full recovery, representing a particular pathological type recently described as long-COVID or PASC.

The scientific evidence generated during the last months strongly supports that the different outcomes on COVID-19 patients are determined by the immune mechanisms activated in response to the viral infection (20).

The immune response to SARS-CoV-2 induces a release of different molecules with inflammatory properties such as cytokines including interleukins and chemokines. This event, known as cytokine storm (20), is an immunopathological feature of COVID-19 and it has been associated with the severity of the disease.

The increase in blood concentrations of different cytokines such as interleukins and chemokines such as IL-6, IL-8, IL-10, TNF-α, IL-1β, IL-2, IP-10, MCP-1, CCL3, CCL4, and CCL5 has been described for COVID-19 patients (4). Some of these molecules have been proposed as biomarkers to monitor the clinical evolution and to determine treatment selection for COVID-19 patients (21–23). Nevertheless, it is important to consider that some of these molecules function in a context dependent manner, therefore the clinical relevance of analyzing single cytokine changes is limited.

One of the most important challenges during the pandemics is to avoid the saturation of the health systems, therefore the determination of predictive biomarkers that allow a better stratification of the patients is paramount. Even though cytokines such as IL-6 and IL-8 have been proposed as indicators of the disease severity, and in some studies they were strong and independent predictors of patient survival (24), their predictive value when analyzed alone is debatable (24). The generation of scores considering blood levels of cytokines such as interleukins and chemokines with different immunological functions incorporates the importance of the context-dependent function of these molecules.

In order to predict Severe cases, a score was generated considering blood concentrations of inflammation-associated factors such as IL-10, IL-6, IL-2, and IL-8, as well as sCD40L and VEGF which are associated with vascular homeostasis (25, 26). In this classification, Severe cases are characterized by high IL-6 and IL-10 levels, both cytokines previously attributed to increase the immunopathogenesis of COVID-19 and predictive value in Severe cases (22, 23).

In different backgrounds, IL-6 has been associated with oxidative stress, inflammation, endothelial dysfunction, and thrombogenesis (25–28) which are characteristic features of Severe COVID-19 cases caused by excessive myeloid cell activation (29). Consistently, increased IL-10 levels interfere with appropriate T-cell responses, inducing T-cell exhaustion and regulatory T cell polarization leading to an evasion of the antiviral immune response (30).

Furthermore, besides its anti-inflammatory function on T cells, in some backgrounds IL-10 induces STAT1 activation and a pro-inflammatory response in type I IFN-primed myeloid cells (30, 31). Therefore, elevated levels of IL-6 and IL-10 promote myeloid cell activation, oxidative stress, endothelial damage, which might affect an adequate antiviral T cell activation (26–30).

Furthermore, Severe cases show high levels of sCD40L and VEGF, which are associated with vasculitis and vascular remodeling. The cytokine storm observed in SARS-CoV-2 infection is accompanied by hemostatic alterations and thrombosis. sCD40L is a platelet activation marker, which has been associated with increase severity in COVID-19 patients (32–34).

Moreover, sCD40L levels are higher in male patients compared with females and it is the sex-associated differences in the severity of the disease (33). Another vascular alteration associated to SARS-CoV-2 infection is endothelial hyperactivation. According to the proposed severity score, VEGF levels were significantly elevated in hospitalized COVID-19 patients when compared to Mild-Moderate cases. Additionally, to strengthen the classification presented here, the score differentiates the Severe cases by the denominator of IL-2 and IL-8, which are cytokines related to proper T cell activation (IL-2) and recruitment (IL-8) (35, 36).

According to the score generated for distinguishing PASC, these patients are characterized by an increased IFN-γ and IL-2 and a reduced CCL4 production. In the context of a viral infection, the combination of IFN-γ and IL-2 would induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus. However, PASC are characterized by longer periods of time with clinical signs and symptoms such as fatigue and lung damage.

This suggests that the inflammatory context created by these cytokines that leads to T cell activation is not enough to generate an adequate anti-viral response without the proper recruitment signals to attract activated T cells. CCL4 signals through the receptor CCR5 to attract T cells to the site of inflammation and depending on the immune context, this molecule recruits differently activated T cells (37, 38).

Moreover, it was recently shown, by single cell analysis, down regulation of CCL4 expression in peripheral myeloid cell compartments in patients with Mild and Severe COVID-19 (39). In PASC, IFN-γ and IL-2 would create an immune context favoring the Th1 polarization, but the low levels of CCL4 affect the recruitment of these cells thus impairing the antiviral response should SARS-CoV-2 RNA or protein persist.

The effect of increased IFN-γ and IL-2 on T cell activation is evident in the reduction of the frequency of exhausted (CD4+PD1+/CD8+PD1+) and total regulatory T cells (FoxP3+) compared to healthy donors. Therefore, proper T cell activation (high IFN-γ+IL-2) but ineffective T cell recruitment (low CCL4) are characteristic features of the failed anti-viral response observed in the PASC group supporting virus persistence.

The significant increase of B cells in the PASC group is associated with high IL-2 levels promoting B cell proliferation and differentiation (40). Interestingly, increased IFN-γ affects B-cell homing to lymph nodes (41), reduces total IgG production, and inhibits pre-activated B cells (42). This could be associated with virus persistence in the PASC group as supported by the low CCL4 levels observed in these patients, since CCL4 has been proposed as a biomarker for B cell receptor pathway activation (43).

Additionally, increased IFN-γ promotes myeloid cell activation which is observed in the augmented frequency of inflammatory CD14+, CD16+, CCR5+ monocytes in the PASC group compared to healthy donors, supporting lymphopenia and virus persistence in these patients. This is in line with recent findings describing increased gene expression in response to IFN-γ in Mild and Severe COVID-19 patients in peripheral myeloid cells (39) and the dysregulation in the balance of monocyte populations by the expansion of the monocyte subsets described in COVID-19 patients (39).

Finally, we propose that long-lasting pulmonary damage observed in PASC, is caused by a combination of factors including

1) virus persistence influenced by the PASC immune profile as characterized by high IFN-γ and IL-2 levels. This in turn induces Th1 polarization which is ineffective with low CCL4-induced T cell recruitment, leading to an inflammatory myeloid cell activation; and

2) the immunopathological pulmonary effects of this PASC immune profile. Regarding the immunopathological effects of the PASC immune profile, it has been shown using murine models that high IFN-γ levels could affect the kinetics of the resolution of inflammation-induced lung injury as well as thrombus resolution (44–46), which could be related to long-lasting symptoms of PASC associated to pulmonary coagulopathy and immune-mediated tissue damage.

Interestingly, COVID-19 individuals (including PASC, Mild, Severe) show high levels of CCL5, a chemokine that like CCL4 signals through CCR5. Indeed, the disruption of the CCL5-CCR5 pathway restores immune balance in critical COVID-19 patients (4). In the specific case of PASC, despite the statistically significant elevation of CCL5 compared to healthy controls, a reduction in the CCL4-mediated recruitment of activated T cells is proposed. This could be related to different factors:

(1) Reduction of total recruitment signals in PASC with low CCL4 concentrations.

(2) Different functional responses of CCL4 and CCL5 to polymorphic variants of the CCR5 gene. Distinct functional features have been reported in CCR5 variants regarding binding avidity, receptor internalization, Ca++ influx and chemotactic activity (47). Even though, clear mechanistic differences between CCL4 and CCL5 interaction with CCR5 are missing, even considering the knowledge gained on CCR5 polymorphisms in HIV/AIDS context (48).

(3) Signaling through alternative receptors for CCL5. Besides CCR5, CCL5 can signal through the receptors CCR1 and CCR3 (49) whereas CCL4 effects are restricted to CCR5. It has been shown that CCL4 can bind to CCR1 but is not able to induce the intracellular pathway necessary for activating the chemoattractant stimulus (49). Therefore, CCL4 has been proposed as an antagonist of CCR1 (50), however further analysis of this needs to be performed. Interestingly, CCR1 is expressed on blood myeloid cells such as monocytes and neutrophils, and it is upregulated on COVID-19 patients (51). Additionally, high levels of IFN-γ (a feature of PASC) have been associated with an increase in CCR1 expression on human neutrophils (52). Therefore, in PASC, high levels of CCL5 (combined with low levels of potential CCR1-antagonist CCL4) leads to a higher recruitment of myeloid cells expressing CCR1.

Conclusion
In conclusion, we developed a bioinformatics pipeline that analyzed cytokines of the immunological landscape of COVID-19 using machine learning methods to discriminate between PASC and Severe individuals from other classes. The implementation of random forest classifiers allowed for the identification of the critical cytokines for this discrimination, which in turn was used to calculate highly sensitive heuristics for PASC and Severe individuals.

These models, which can be incorporated into clinical laboratory information systems, enabled a highly accurate, immune-based classification of severe COVID-19 infection and PASC. This workflow could greatly aid the triage, treatment, and prognosis of those affected. An interesting caveat affecting the specificity of the PASC classification was that 7 Severe COVID-19 patients classified as PASC that, while affecting the specificity of PASC classification, may represent a subset of acute COVID-19 patients destined to become affected by PASC.

These data also indicate that with an effective classification of severe and PASC individuals based on cytokine profiles, precision therapies guided by the machine learning output may result in lower severity and PASC scores and possibly in more favorable clinical outcomes. CCR5 antagonism has already been demonstrated to reduce IL-6, and VEGF (4, 53), numerators in the severity score, and to reduce IFN-γ, a numerator in the PASC score (54).

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