Circulating ACE2 level and zinc/albumin ratio as potential biomarkers for a precision medicine approach to COVID-19.

Highly mutable influenza is successfully countered based on individual susceptibility and similar precision-like medicine approach should be effective against SARS-COV-2. Among predictive markers to bring precision medicine to COVID-19, circulating ACE2 has potential features being upregulated in both severe COVID-19 and predisposing comorbidities. Spike SARS-CoVs were shown to induce ADAM17-mediated shedding of enzymatic active ACE2, thus accounting for its increased activity that has also been suggested to induce positive feedback loops leading to COVID-19-like manifestations. For this reason, pre-existing ACE2 activity and inhibition of ACE2/ADAM17 zinc-metalloproteases through zinc chelating agents have been proposed to predict COVID-19 outcome before infection and to protect from COVID-19, respectively. Since most diagnostic laboratories are not equipped for enzymatic activity determination, other potential predictive markers of disease progression exploitable by diagnostic laboratories were explored. Concentrations of circulating albumin, zinc, ACE2 protein and its activity were investigated in healthy, diabetic (COVID-19-susceptible) and SARS-CoV-2-negative COVID-19 individuals. ACE2 both protein levels and activity significantly increased in COVID-19 and diabetic patients. Abnormal high levels of ACE2 characterised a subgroup (16-19%) of diabetics, while COVID-19 patients were characterised by significantly higher zinc/albumin ratios, pointing to a relative increase of albumin-unbound zinc species, such as free zinc ones. Data on circulating ACE2 levels are in line with the hypothesis that they can drive susceptibility to COVID-19 and elevated zinc/albumin ratios support the therapeutic use of zinc chelating inhibitors of ACE2/ADAM17 zinc-metalloproteases in a targeted therapy for COVID-19.

Ferritin as a predictive biomarker of severity in Covid-19 / La ferritine comme biomarqueur prédictif des formes sévères de Covid-19

Background: To prevent the crisis-level shortage of beds in hospitals and for a more efficient support, it's necessary to early identify coronavirus disease-19 (Covid-19) patients at risk to develop a severe form of the disease. Objective: The goal of our study was to determine whether biological markers, including the serum ferritin, could predict the severity of the Covid-19. Methods: One hundred and seventy-one patients, who were admitted to Caen University Hospital, were included retrospectively with a positive diagnosis of Covid-19 by RT-PCR. A serum ferritin measurement was performed for all patients. They were further classified either into a non-severe or a severe group based on their hospitalization in intense care unit (ICU) for mechanical ventilation or death. Results: Univariate analysis revealed a significant association between increased serum ferritin and CRP levels, obesity, CT scan lesions, pathological respiratory rate, decreased PaO2/FiO2 ratio, the NEWS-2 score and the severe (n = 59) vs the non-severe (n = 112) outcome of Covid-19 patients. However, in a multivariate analysis, only CRP and obesity were associated with the severe form of Covid-19. Conclusion: While pathological level of serum ferritin at admission is associated with severe form of Covid-19, combination of increased CRP level and obesity would better predict the severity of the disease.

Pour une meilleure prise en charge, il est nécessaire de pouvoir identifier précocement les patients atteints de la Covid-19 susceptibles de développer une forme sévère. L'objectif de notre étude était de déterminer si des marqueurs biologiques, notamment la ferritinémie, peuvent prédire la sévérité de la Covid-19. Nous avons inclus de manière rétrospective 171 patients au CHU de Caen avec un diagnostic de Covid-19. Les patients devaient avoir un bilan biologique incluant la ferritinémie à l'admission et ont été classés en formes sévères (n = 59, hospitalisation et ventilation invasive en soins intensifs ou en réanimation, et/ou décès) et non-sévères (n = 112, tous les autres patients). L'analyse univariée a montré une association entre les formes sévères de Covid-19 avec les niveaux élevés de ferritine et de CRP, l'obésité, les lésions pulmonaires, la fréquence respiratoire élevée, la diminution du ratio PaO2/FiO2 et le score de NEWS-2. Cependant, en analyse multivariée seules la CRP et l'obésité montraient une association avec les formes sévères. En conclusion, alors que la ferritinémie élevée est associée à un risque accru de développer une forme sévère de la Covid-19, la CRP et la présence d'une obésité seraient de meilleurs marqueurs prédictifs.

High circulating levels of the homeostatic chemokines CCL19 and CCL21 predict mortality and disease severity in Covid-19.

BACKGROUND: Immune dysregulation is a major factor in the development of severe Covid-19. The homeostatic chemokines CCL19 and CCL21 have been implicated as mediators of tissue inflammation, but data on their regulation in SARS-CoV-2 infection is limited. We thus investigated the levels of these chemokines in Covid-19 patients. METHODS: Serial blood samples were obtained from patients hospitalized with Covid-19 (n = 414). Circulating CCL19 and CCL21 levels during hospitalization and three-month follow-up were analyzed. In vitro assays and analysis of RNAseq data from public repositories were performed to further explore possible regulatory mechanisms. RESULTS: A consistent increase in circulating levels of CCL19 and CCL21 was observed, with high levels correlating with disease severity measures, including respiratory failure, need for intensive care, and 60-day all-cause mortality. High levels of CCL21 at admission were associated with persisting impairment of pulmonary function at the three-month follow-up. CONCLUSIONS: Our findings highlight CCL19 and CCL21 as markers of immune dysregulation in Covid-19. This may reflect aberrant regulation triggered by tissue inflammation, as observed in other chronic inflammatory and autoimmune conditions. Determination of the source and regulation of these chemokines and their effects on lung tissue is warranted to further clarify their role in Covid-19.

A rapid antibody screening haemagglutination test for predicting immunity to SARS-CoV-2 variants of concern.

Background: Evaluation of susceptibility to emerging SARS-CoV-2 variants of concern (VOC) requires rapid screening tests for neutralising antibodies which provide protection. Methods: Firstly, we developed a receptor-binding domain-specific haemagglutination test (HAT) to Wuhan and VOC (alpha, beta, gamma and delta) and compared to pseudotype, microneutralisation and virus neutralisation assays in 835 convalescent sera. Secondly, we investigated the antibody response using the HAT after two doses of mRNA (BNT162b2) vaccination. Sera were collected at baseline, three weeks after the first and second vaccinations from older (80-99 years, n = 89) and younger adults (23-77 years, n = 310) and compared to convalescent sera from naturally infected individuals (1-89 years, n = 307). Results: Here we show that HAT antibodies highly correlated with neutralising antibodies (R = 0.72-0.88) in convalescent sera. Home-dwelling older individuals have significantly lower antibodies to the Wuhan strain after one and two doses of BNT162b2 vaccine than younger adult vaccinees and naturally infected individuals. Moverover, a second vaccine dose boosts and broadens the antibody repertoire to VOC in naïve, not previously infected older and younger adults. Most (72-76%) older adults respond after two vaccinations to alpha and delta, but only 58-62% to beta and gamma, compared to 96-97% of younger vaccinees and 68-76% of infected individuals. Previously infected older individuals have, similarly to younger adults, high antibody titres after one vaccination. Conclusions: Overall, HAT provides a surrogate marker for neutralising antibodies, which can be used as a simple inexpensive, rapid test. HAT can be rapidly adaptable to emerging VOC for large-scale evaluation of potentially decreasing vaccine effectiveness.

Derivation and validation of the clinical prediction model for COVID-19.

The epidemic phase of Coronavirus disease 2019 (COVID-19) made the Worldwide health system struggle against a severe interstitial pneumonia requiring high-intensity care settings for respiratory failure. A rationalisation of resources and a specific treatment path were necessary. The study suggests a predictive model drawing on clinical data gathered by 119 consecutive patients with laboratory-confirmed COVID-19 admitted in Busto Arsizio hospital. We derived a score that identifies the risk of clinical evolution and in-hospital mortality clustering patients into four groups. The study outcomes have been compared across the derivation and validation samples. The prediction rule is based on eight simple patient characteristics that were independently associated with study outcomes. It is able to stratify COVID-19 patients into four severity classes, with in-hospital mortality rates of 0% in group 1, 6-12.5% in group 2, 7-20% in group 3 and 60-86% in group 4 across the derivation and validation sample. The prediction model derived in this study identifies COVID-19 patients with low risk of in-hospital mortality and ICU admission. The prediction model that the study presents identifies COVID-19 patients with low risk of in-hospital mortality and admission to ICU. Moreover, it establishes an intermediate portion of patients that should be treated accurately in order to avoid an unfavourable clinical evolution. A further validation of the model is important before its implementation as a decision-making tool to guide the initial management of patients.