sMR and PTX3 levels associate with COVID-19 outcome and survival but not with Long COVID.

Biomarkers for monitoring COVID-19 disease course are lacking. Study aim was to identify biomarkers associated with disease severity, survival, long-term outcome, and Long COVID. As excessive macrophages activation is a hallmark of COVID-19 and complement activation is key in this, we selected the following proteins involved in these processes: PTX3, C1q, C1-INH, C1s/C1-INH, and sMR. EDTA-plasma concentrations were measured in 215 patients and 47 controls using ELISA. PTX3, sMR, C1-INH, and C1s/C1-INH levels were associated with disease severity. PTX3 and sMR were also associated with survival and long-term immune recovery. Lastly, sMR levels associate with ICU admittance. sMR (AUC 0.85) and PTX3 (AUC 0.78) are good markers for disease severity, especially when used in combination (AUC 0.88). No association between biomarker levels and Long COVID was observed. sMR has not previously been associated with COVID-19 disease severity, ICU admittance or survival and may serve as marker for disease course.

Circulating mortalin in blood and activation of the alternative complement pathway as risk indicators in COVID-19 infection.

Background: Mortalin/GRP75 is a ubiquitous mitochondrial chaperone related to the cytosolic heat shock protein 70. It protects cells from various types of damages and from senescence. Our goal was to determine whether COVID-19 patients have circulating mortalin in their blood and to assess its prognostic value in anticipating disease severity. Methods: Mortalin was determined by ELISA in the sera of 83 COVID-19 patients enrolled in the study. Patients were categorized into 4 groups: critical patients who died (FATAL) or required intensive care and survived (ICU), patients of mild severity (hospitalized but not critical) who required nasal oxygen support (HOSP+O2), and patients who did not need oxygen therapy (HOSP). Results: The mortalin concentration in the serum of all COVID-19 patients in the cohort was 194-2324 pg/mL. A comparison of the mortalin levels by peak severity among the various patient groups showed a highly significant difference between the HOSP and FATAL groups and a significant difference between the HOSP and the ICU groups. COVID-19 patients who eventually failed to survive had at hospitalization a markedly higher level of mortalin in their sera. Cox regression analysis revealed a high mortality hazard (HR=3.96, p<0.01) in patients with high mortalin circulating levels (above the median, ≥651 pg/mL). This was confirmed in survival curve analysis (Kaplan-Meier; p=0.0032, log-rank test). Mortalin remained an independent predictor of mortality even after adjusting for age and sex or various complement activation products. Complement activation data collected in an earlier study in the same cohort was compared regarding the mortalin levels. Patients with higher circulating mortalin levels also had higher levels of complement C3a but reduced levels of properdin. Discussion: This is the first report on circulating mortalin in COVID-19 patients. Higher mortalin levels were associated with more severe illnesses and a higher risk of death. We claim that quantifying the blood levels of mortalin and activated complement proteins will provide important information on the prognosis of COVID-19 patients and will serve as a useful tool for guiding their clinical management and treatment.

Combination protein biomarkers predict multiple sclerosis diagnosis and outcomes.

Establishing biomarkers to predict multiple sclerosis diagnosis and prognosis has been challenging using a single biomarker approach. We hypothesised that a combination of biomarkers would increase the accuracy of prediction models to differentiate multiple sclerosis from other neurological disorders and enhance prognostication for people with multiple sclerosis. We measured 24 fluid biomarkers in the blood and cerebrospinal fluid of 77 people with multiple sclerosis and 80 people with other neurological disorders, using ELISA or Single Molecule Array assays. Primary outcomes were multiple sclerosis versus any other diagnosis, time to first relapse, and time to disability milestone (Expanded Disability Status Scale 6), adjusted for age and sex. Multivariate prediction models were calculated using the area under the curve value for diagnostic prediction, and concordance statistics (the percentage of each pair of events that are correctly ordered in time for each of the Cox regression models) for prognostic predictions. Predictions using combinations of biomarkers were considerably better than single biomarker predictions. The combination of cerebrospinal fluid [chitinase-3-like-1 + TNF-receptor-1 + CD27] and serum [osteopontin + MCP-1] had an area under the curve of 0.97 for diagnosis of multiple sclerosis, compared to the best discriminative single marker in blood (osteopontin: area under the curve 0.84) and in cerebrospinal fluid (chitinase-3-like-1 area under the curve 0.84). Prediction for time to next relapse was optimal with a combination of cerebrospinal fluid[vitamin D binding protein + Factor I + C1inhibitor] + serum[Factor B + Interleukin-4 + C1inhibitor] (concordance 0.80), and time to Expanded Disability Status Scale 6 with cerebrospinal fluid [C9 + Neurofilament-light] + serum[chitinase-3-like-1 + CCL27 + vitamin D binding protein + C1inhibitor] (concordance 0.98). A combination of fluid biomarkers has a higher accuracy to differentiate multiple sclerosis from other neurological disorders and significantly improved the prediction of the development of sustained disability in multiple sclerosis. Serum models rivalled those of cerebrospinal fluid, holding promise for a non-invasive approach. The utility of our biomarker models can only be established by robust validation in different and varied cohorts.

Storage of Transfusion Platelet Concentrates Is Associated with Complement Activation and Reduced Ability of Platelets to Respond to Protease-Activated Receptor-1 and Thromboxane A2 Receptor.

Platelet activation and the complement system are mutually dependent. Here, we investigated the effects of storage time on complement activation and platelet function in routinely produced platelet concentrates. The platelet concentrates (n = 10) were stored at 22 °C for seven days and assessed daily for complement and platelet activation markers. Additionally, platelet function was analyzed in terms of their responsiveness to protease-activated receptor-1 (PAR-1) and thromboxane A2 receptor (TXA2R) activation and their capacity to adhere to collagen. Complement activation increased over the storage period for all analyzed markers, including the C1rs/C1-INH complex (fold change (FC) = 1.9; p < 0.001), MASP-1/C1-INH complex (FC = 2.0; p < 0.001), C4c (FC = 1.8, p < 0.001), C3bc (FC = 4.0; p < 0.01), and soluble C5b-9 (FC = 1.7, p < 0.001). Furthermore, the levels of soluble platelet activation markers increased in the concentrates over the seven-day period, including neutrophil-activating peptide-2 (FC = 2.5; p < 0.0001), transforming growth factor beta 1 (FC = 1.9; p < 0.001) and platelet factor 4 (FC = 2.1; p < 0.0001). The ability of platelets to respond to activation, as measured by surface expression of CD62P and CD63, decreased by 19% and 24% (p < 0.05) for PAR-1 and 69-72% (p < 0.05) for TXA2R activation, respectively, on Day 7 compared to Day 1. The extent of platelet binding to collagen was not significantly impaired during storage. In conclusion, we demonstrated that complement activation increased during the storage of platelets, and this correlated with increased platelet activation and a reduced ability of the platelets to respond to, primarily, TXA2R activation.