Profiling metabolites and lipoproteins in COMETA,an Italian cohort of COVID-19 patients

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, ¹H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2–6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the “healthy” state faster than the lipoproteome.     

Increased sTREM-1 plasma concentrations are associated with poor clinical outcomes in patients with COVID-19

Patients with sepsis display increased concentrations of sTREM-1 (soluble Triggering Receptor Expressed on Myeloid cells 1), and a phase II clinical trial focusing on TREM-1 modulation is ongoing. We investigated whether sTREM-1 circulating concentrations are associated with the outcome of patients with coronavirus disease 2019 (COVID-19) to assess the role of this pathway in COVID-19. This observational study was performed in two independent cohorts of patients with COVID-19. Plasma concentrations of sTREM-1 were assessed after ICU admission (pilot cohort) or after COVID-19 diagnosis (validation cohort). Routine laboratory and clinical parameters were collected from electronic patient files. Results showed sTREM-1 plasma concentrations were significantly elevated in patients with COVID-19 (161 [129–196] pg/ml) compared to healthy controls (104 [75–124] pg/ml; P<0.001). Patients with severe COVID-19 needing ICU admission displayed even higher sTREM-1 concentrations compared to less severely ill COVID-19 patients receiving clinical ward-based care (235 [176–319] pg/ml and 195 [139–283] pg/ml, respectively, P = 0.017). In addition, higher sTREM-1 plasma concentrations were observed in patients who did not survive the infection (326 [207–445] pg/ml) compared to survivors (199 [142–278] pg/ml, P<0.001). Survival analyses indicated that patients with higher sTREM-1 concentrations are at higher risk for death (hazard ratio = 3.3, 95%CI: 1.4–7.8). In conclusion, plasma sTREM-1 concentrations are elevated in patients with COVID-19, relate to disease severity, and discriminate between survivors and non-survivors. This suggests that the TREM-1 pathway is involved in the inflammatory reaction and the disease course of COVID-19, and therefore may be considered as a therapeutic target in severely ill patients with COVID-19.     

Interplay of LncRNAs NEAT1 and TUG1 in Incidence of Cytokine Storm in Appraisal of COVID-19 Infection

Background: In 2019, the coronavirus pandemic emerged, resulting in the highest mortality and morbidity rate globally. It has a prevailing transmission rate and continues to be a global burden. There is a paucity of data regarding the role of long non-coding RNAs (lncRNAs) in COVID-19. Therefore, the current study aimed to investigate lncRNAs, particularly NEAT1 and TUG1, and their association with IL-6, CCL2, and TNF-α in COVID-19 patients with moderate and severe disease.Methods: The study was conducted on 80 COVID-19 patients (35 with severe and 45 with moderate infection) and 40 control subjects. Complete blood count (CBC), D-dimer assay, serum ferritin, and CRP were assayed. qRT-PCR was used to measure RNAs and lncRNAs.Results: NEAT1 and TUG1 expression levels were higher in COVID-19 patients compared with controls (P<0.001). Furthermore, CCL2, IL-6, and TNF-α expressions were higher in COVID-19 patients compared to controls (P<0.001). CCL2 and IL-6 expression levels were significantly higher in patients with severe compared to those with moderate COVID-19 infection (P<0.001). IL-6 had the highest accuracy in distinguishing COVID-19 patients (AUC=1, P<0.001 at a cutoff of 0.359), followed by TUG1 (AUC=0.999, P<0.001 at a cutoff of 2.28). NEAT1 and TUG1 had significant correlations with the measured cytokines, and based on the multivariate regression analysis, NEAT1 is the independent predictor for survival in COVID-19 patients (P=0.02).Conclusion: In COVID-19 patients, significant overexpression of NEAT1 and TUG1 was observed, consistent with cytokine storm. TUG1 could be an efficient diagnostic biomarker, whereas NEAT1 was an independent predictor for overall survival.     

SARS-CoV-2 infection is associated with a pro-thrombotic platelet phenotype

Novel coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state, characterized by abnormal coagulation parameters and by increased incidence of cardiovascular complications. With this study, we aimed to investigate the activation state and the expression of transmembrane proteins in platelets of hospitalized COVID-19 patients. We investigated transmembrane proteins expression with a customized mass cytometry panel of 21 antibodies. Platelets of 8 hospitalized COVID-19 patients not requiring intensive care support and without pre-existing conditions were compared to platelets of healthy controls (11 donors) with and without in vitro stimulation with thrombin receptor-activating peptide (TRAP). Mass cytometry of non-stimulated platelets detected an increased surface expression of activation markers P-Selectin (0.67 vs. 1.87 median signal intensity for controls vs. patients, p = 0.0015) and LAMP-3 (CD63, 0.37 vs. 0.81, p = 0.0004), the GPIIb/IIIa complex (4.58 vs. 5.03, p < 0.0001) and other adhesion molecules involved in platelet activation and platelet–leukocyte interactions. Upon TRAP stimulation, mass cytometry detected a higher expression of P-selectin in COVID-19 samples compared to controls (p < 0.0001). However, we observed a significantly reduced capacity of COVID-19 platelets to increase the expression of activation markers LAMP-3 and P-Selectin upon stimulation with TRAP. We detected a hyperactivated phenotype in platelets during SARS-CoV-2 infection, consisting of highly expressed platelet activation markers, which might contribute to the hypercoagulopathy observed in COVID-19. In addition, several transmembrane proteins were more highly expressed compared to healthy controls. These findings support research projects investigating antithrombotic and antiplatelet treatment regimes in COVID-19 patients, and provide new insights on the phenotypical platelet expression during SARS-CoV-2 infection.Subject terms: Mechanisms of disease, Viral infection     

Overall and cause-specific hospitalisation and death after COVID-19 hospitalisation in England: A cohort study using linked primary care,secondary care,and death registration data in the OpenSAFELY platform

BackgroundThere is concern about medium to long-term adverse outcomes following acute Coronavirus Disease 2019 (COVID-19), but little relevant evidence exists. We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation.Methods and findingsWith the approval of NHS-England, we conducted a cohort study, using linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February to December 2020) and surviving at least 1 week, and (i) demographically matched controls from the 2019 general population; and (ii) people discharged from influenza hospitalisation in 2017 to 2019. We used Cox regression adjusted for age, sex, ethnicity, obesity, smoking status, deprivation, and comorbidities considered potential risk factors for severe COVID-19 outcomes.We included 24,673 postdischarge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls, followed for ≤315 days. COVID-19 patients had median age of 66 years, 13,733 (56%) were male, and 19,061 (77%) were of white ethnicity. Overall risk of hospitalisation or death (30,968 events) was higher in the COVID-19 group than general population controls (fully adjusted hazard ratio [aHR] 2.22, 2.14 to 2.30, p < 0.001) but slightly lower than the influenza group (aHR 0.95, 0.91 to 0.98, p = 0.004). All-cause mortality (7,439 events) was highest in the COVID-19 group (aHR 4.82, 4.48 to 5.19 versus general population controls [p < 0.001] and 1.74, 1.61 to 1.88 versus influenza controls [p < 0.001]). Risks for cause-specific outcomes were higher in COVID-19 survivors than in general population controls and largely similar or lower in COVID-19 compared with influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted or die due to their initial infection or other lower respiratory tract infection (aHR 1.37, 1.22 to 1.54, p < 0.001) and to experience mental health or cognitive-related admission or death (aHR 1.37, 1.02 to 1.84, p = 0.039); in particular, COVID-19 survivors with preexisting dementia had higher risk of dementia hospitalisation or death (age- and sex-adjusted HR 2.47, 1.37 to 4.44, p = 0.002). Limitations of our study were that reasons for hospitalisation or death may have been misclassified in some cases due to inconsistent use of codes, and we did not have data to distinguish COVID-19 variants.ConclusionsIn this study, we observed that people discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations, but COVID-19 patients had higher risks of all-cause mortality, readmission or death due to the initial infection, and dementia death, highlighting the importance of postdischarge monitoring.

Krishnan Bhaskaran and co-workers study health outcomes after admission with COVID-19 and subsequent discharge.     

Novel urinary biomarkers for diagnosing bipolar disorder

Bipolar disorder (BD) is a debilitating mental disorder. However, there are no biomarkers available to support objective laboratory testing for this disorder. Here, a nuclear magnetic resonance spectroscopy-based metabonomic method was used to characterize the urinary metabolic profiling of BD subjects and healthy controls in order to identify and validate urinary metabolite biomarkers for BD. Four metabolites, α-hydroxybutyrate, choline, isobutyrate, and N-methylnicotinamide, were defined as biomarkers. A combined panel of these four urinary metabolites could effectively discriminate between BD subjects and healthy controls, achieving an area under the receiver operating characteristic curve (AUC) of 0.89 in a training set (n = 60 BD patients and n = 62 controls). Moreover, this urinary biomarker panel was capable of discriminating blinded test samples (n = 26 BD patients and n = 34 controls) with an AUC of 0.86. These findings suggest that a urine-based laboratory test using these biomarkers may be useful in the diagnosis of BD.     

Krebs Von den Lungen-6 as a predictive indicator for the risk of secondary pulmonary fibrosis and its reversibility in COVID-19 patients

Dysregulated immune response and abnormal repairment could cause secondary pulmonary fibrosis of varying severity in COVID-19, especially for the elders. The Krebs Von den Lungen-6 (KL-6) as a sensitive marker reflects the degree of fibrosis and this study will focus on analyzing the evaluative efficacy and predictive role of KL-6 in COVID-19 secondary pulmonary fibrosis. The study lasted more than three months and included total 289 COVID-19 patients who were divided into moderate (n=226) and severe groups (n=63) according to the severity of illness. Clinical information such as inflammation indicators, radiological results and lung function tests were collected. The time points of nucleic acid test were also recorded. Furthermore, based on Chest radiology detection, it was identified that 80 (27.7%) patients developed reversible pulmonary fibrosis and 34 (11.8%) patients developed irreversible pulmonary fibrosis. Receiver operating characteristic (ROC) curve analysis shows that KL-6 could diagnose the severity of COVID-19 (AUC=0.862) and predict the occurrence of pulmonary fibrosis (AUC = 0.741) and irreversible pulmonary fibrosis (AUC=0.872). Importantly, the cross-correlation analysis demonstrates that KL-6 rises earlier than the development of lung radiology fibrosis, thus also illuminating the predictive function of KL-6. We set specific values (505U/mL and 674U/mL) for KL-6 in order to assess the risk of pulmonary fibrosis after SARS-CoV-2 infection. The survival curves for days in hospital show that the higher the KL-6 levels, the longer the hospital stay (P<0.0001). In conclusion, KL-6 could be used as an important predictor to evaluate the secondary pulmonary fibrosis degree for COVID-19.     

Secretome-based identification of ULBP2 as a novel serum marker for pancreatic cancer detection

Background

To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues.

Methods

ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9).

Results

Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls.

Conclusions

Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening.     

Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

BackgroundEpidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.Methods and findingsWe selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10⁻⁸ from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m²; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10⁻⁵; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m², p = 2.1 × 10⁻⁵). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.ConclusionsIn this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

Aaron Leong and co-workers investigate causal risk factors for COVID-10 illness and severity.     

Quantitative hepatic phosphorus-31 magnetic resonance spectroscopy in compensated and decompensated cirrhosis

Few studies have examined the physiological/biochemical status of hepatocytes in patients with compensated and decompensated cirrhosis in situ. Phosphorus-31 magnetic resonance spectroscopy ((31)P MRS) is a noninvasive technique that permits direct assessments of tissue bioenergetics and phospholipid metabolism. Quantitative (31)P MRS was employed to document differences in the hepatic metabolite concentrations among patients with compensated and decompensated cirrhosis as well as healthy controls. All MRS examinations were performed on a 1.5-T General Electric Signa whole body scanner. The concentration of hepatic phosphorylated metabolites among patients with compensated cirrhosis (n = 7) was similar to that among healthy controls (n = 8). However, patients with decompensated cirrhosis (n = 6) had significantly lower levels of hepatic ATP compared with patients with compensated cirrhosis and healthy controls (P < 0.02 and P < 0.009, respectively) and a higher phosphomonoester/phosphodiester ratio than controls (P < 0.003). The results of this study indicate that metabolic disturbances in hepatic energy and phospholipid metabolism exist in patients with decompensated cirrhosis that are not present in patients with compensated cirrhosis or healthy controls. These findings provide new insights into the pathophysiology of hepatic decompensation.     

Matrix Metalloproteinases -8 and -9 and Tissue Inhibitor of Metalloproteinase-1 in Burn Patients. A Prospective Observational Study

IntroductionMatrix metalloproteinases (MMPs) -8 and -9 are released from neutrophils in acute inflammation and may contribute to permeability changes in burn injury. In retrospective studies on sepsis, levels of MMP-8, MMP-9, and tissue inhibitor of metalloproteinase-1 (TIMP-1) differed from those of healthy controls, and TIMP-1 showed an association with outcome. Our objective was to investigate the relationship between these proteins and disease severity and outcome in burn patients.MethodsIn this prospective, observational, two-center study, we collected plasma samples from admission to day 21 post-burn, and burn blister fluid samples on admission. We compared MMP-8, -9, and TIMP-1 levels between TBSA<20% (N = 19) and TBSA>20% (N = 30) injured patients and healthy controls, and between 90-day survivors and non-survivors. MMP-8, -9, and TIMP-1 levels at 24-48 hours from injury, their maximal levels, and their time-adjusted means were compared between groups. Correlations with clinical parameters and the extent of burn were analyzed. MMP-8, -9, and TIMP-1 levels in burn blister fluids were also studied.ResultsPlasma MMP-8 and -9 were higher in patients than in healthy controls (P<0.001 and P = 0.016), but only MMP-8 differed between the TBSA<20% and TBSA>20% groups. MMP-8 and -9 were not associated with clinical severity or outcome measures. TIMP-1 differed significantly between patients and controls (P<0.001) and between TBSA<20% and TBSA>20% groups (P<0.002). TIMP-1 was associated with 90-day mortality and correlated with the extent of injury and clinical measures of disease severity. TIMP-1 may serve as a new biomarker in outcome prognostication of burn patients.     

Income differences in COVID-19 incidence and severity in Finland among people with foreign and native background: A population-based cohort study of individuals nested within households

BackgroundAlthough intrahousehold transmission is a key source of Coronavirus Disease 2019 (COVID-19) infections, studies to date have not analysed socioeconomic risk factors on the household level or household clustering of severe COVID-19. We quantify household income differences and household clustering of COVID-19 incidence and severity.Methods and findingsWe used register-based cohort data with individual-level linkage across various administrative registers for the total Finnish population living in working-age private households (N = 4,315,342). Incident COVID-19 cases (N = 38,467) were identified from the National Infectious Diseases Register from 1 July 2020 to 22 February 2021. Severe cases (N = 625) were defined as having at least 3 consecutive days of inpatient care with a COVID-19 diagnosis and identified from the Care Register for Health Care between 1 July 2020 and 31 December 2020. We used 2-level logistic regression with individuals nested within households to estimate COVID-19 incidence and case severity among those infected.Adjusted for age, sex, and regional characteristics, the incidence of COVID-19 was higher (odds ratio [OR] 1.67, 95% CI 1.58 to 1.77, p < 0.001, 28.4% of infections) among individuals in the lowest household income quintile than among those in the highest quintile (18.9%). The difference attenuated (OR 1.23, 1.16 to 1.30, p < 0.001) when controlling for foreign background but not when controlling for other household-level risk factors. In fact, we found a clear income gradient in incidence only among people with foreign background but none among those with native background. The odds of severe illness among those infected were also higher in the lowest income quintile (OR 1.97, 1.52 to 2.56, p < 0.001, 28.0% versus 21.6% in the highest quintile), but this difference was fully attenuated (OR 1.08, 0.77 to 1.52, p = 0.64) when controlling for other individual-level risk factors—comorbidities, occupational status, and foreign background. Both incidence and severity were strongly clustered within households: Around 77% of the variation in incidence and 20% in severity were attributable to differences between households. The main limitation of our study was that the test uptake for COVID-19 may have differed between population subgroups.ConclusionsLow household income appears to be a strong risk factor for both COVID-19 incidence and case severity, but the income differences are largely driven by having foreign background. The strong household clustering of incidence and severity highlights the importance of household context in the prevention and mitigation of COVID-19 outcomes.

Sanni Saarinen and colleagues explore the association between income differences and COVID-19 incidence and severity among people with foreign and native background in Finland.     

A low level of lysophosphatidic acid in human gingival crevicular fluid from patients with periodontitis due to high soluble lysophospholipase activity: Its potential protective role on alveolar bone loss by periodontitis

We previously detected a submicromolar concentration of lysophosphatidic acid (LPA) in human saliva. Here, we compare LPA concentrations in human gingival crevicular fluid (GCF) from patients with periodontitis and healthy controls, and examine how the local LPA levels are regulated enzymatically. The concentrations of LPA and its precursor lysophospholipids in GCF was measured by liquid chromatography-tandem mass spectrometry. The LPA-producing and LPA-degrading enzymatic activities were measured by quantifying the liberated choline and free fatty acid, respectively. The concentration of LPA in GCF of periodontitis patients was lower than that of healthy controls, due to higher soluble lysophospholipase activity toward LPA. LPA was found to prevent survival of Sa3, a human gingival epithelium-derived tumor cell line, activate Sa3 through Ca²⁺ mobilization, and release interleukin 6 from Sa3 in vitro. Furthermore, local injection of LPA into the gingiva attenuated ligature-induced experimental alveolar bone loss induced by oral bacteria inoculation in a rat model of periodontitis in vivo. A high concentration of LPA in human GCF is necessary to maintain normal gingival epithelial integrity and function, protecting the progression of periodontitis.     

COVID-19 induces a hyperactive phenotype in circulating platelets

Coronavirus Disease 2019 (COVID-19), caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has affected over 30 million globally to date. Although high rates of venous thromboembolism and evidence of COVID-19-induced endothelial dysfunction have been reported, the precise aetiology of the increased thrombotic risk associated with COVID-19 infection remains to be fully elucidated. Therefore, we assessed clinical platelet parameters and circulating platelet activity in patients with severe and nonsevere COVID-19. An assessment of clinical blood parameters in patients with severe COVID-19 disease (requiring intensive care), patients with nonsevere disease (not requiring intensive care), general medical in-patients without COVID-19, and healthy donors was undertaken. Platelet function and activity were also assessed by secretion and specific marker analysis. We demonstrated that routine clinical blood parameters including increased mean platelet volume (MPV) and decreased platelet:neutrophil ratio are associated with disease severity in COVID-19 upon hospitalisation and intensive care unit (ICU) admission. Strikingly, agonist-induced ADP release was 30- to 90-fold higher in COVID-19 patients compared with hospitalised controls and circulating levels of platelet factor 4 (PF4), soluble P-selectin (sP-selectin), and thrombopoietin (TPO) were also significantly elevated in COVID-19. This study shows that distinct differences exist in routine full blood count and other clinical laboratory parameters between patients with severe and nonsevere COVID-19. Moreover, we have determined all COVID-19 patients possess hyperactive circulating platelets. These data suggest abnormal platelet reactivity may contribute to hypercoagulability in COVID-19 and confirms the role that platelets/clotting has in determining the severity of the disease and the complexity of the recovery path.

The reason for the increased thrombotic risk associated with SARS-CoV-2 infection remains unclear. This study reveals that disease severity is associated with increased mean platelet volume and decreased platelet:neutrophil ratio; moreover, all COVID-19 patients possess hyperactive circulating platelets, with agonist-induced ADP release 30-to-90 fold higher than controls.     

Obstetrical outcomes and maternal morbidities associated with COVID-19 in pregnant women in France: A national retrospective cohort study

BackgroundTo the best of our knowledge, no study has exhaustively evaluated the association between maternal morbidities and Coronavirus Disease 2019 (COVID-19) during the first wave of the pandemic in pregnant women. We investigated, in natural conceptions and assisted reproductive technique (ART) pregnancies, whether maternal morbidities were more frequent in pregnant women with COVID-19 diagnosis compared to pregnant women without COVID-19 diagnosis during the first wave of the COVID-19 pandemic.Methods and findingsWe conducted a retrospective analysis of prospectively collected data in a national cohort of all hospitalizations for births ≥22 weeks of gestation in France from January to June 2020 using the French national hospitalization database (PMSI). Pregnant women with COVID-19 were identified if they had been recorded in the database using the ICD-10 (International Classification of Disease) code for presence of a hospitalization for COVID-19. A total of 244,645 births were included, of which 874 (0.36%) in the COVID-19 group. Maternal morbidities and adverse obstetrical outcomes among those with or without COVID-19 were analyzed with a multivariable logistic regression model adjusted on patient characteristics. Among pregnant women, older age (31.1 (±5.9) years old versus 30.5 (±5.4) years old, respectively, p < 0.001), obesity (0.7% versus 0.3%, respectively, p < 0.001), multiple pregnancy (0.7% versus 0.4%, respectively, p < 0.001), and history of hypertension (0.9% versus 0.3%, respectively, p < 0.001) were more frequent with COVID-19 diagnosis. Active smoking (0.2% versus 0.4%, respectively, p < 0.001) and primiparity (0.3% versus 0.4%, respectively, p < 0.03) were less frequent with COVID-19 diagnosis. Frequency of ART conception was not different between those with and without COVID-19 diagnosis (p = 0.28).When compared to the non-COVID-19 group, women in the COVID-19 group had a higher frequency of admission to ICU (5.9% versus 0.1%, p < 0.001), mortality (0.2% versus 0.005%, p < 0.001), preeclampsia/eclampsia (4.8% versus 2.2%, p < 0.001), gestational hypertension (2.3% versus 1.3%, p < 0.03), postpartum hemorrhage (10.0% versus 5.7%, p < 0.001), preterm birth at <37 weeks of gestation (16.7% versus 7.1%, p < 0.001), <32 weeks of gestation (2.2% versus 0.8%, p < 0.001), <28 weeks of gestation (2.4% versus 0.8%, p < 0.001), induced preterm birth (5.4% versus 1.4%, p < 0.001), spontaneous preterm birth (11.3% versus 5.7%, p < 0.001), fetal distress (33.0% versus 26.0%, p < 0.001), and cesarean section (33.0% versus 20.2%, p < 0.001). Rates of pregnancy terminations ≥22 weeks of gestation, stillbirths, gestational diabetes, placenta praevia, and placenta abruption were not significantly different between the COVID-19 and non-COVID-19 groups. The number of venous thromboembolic events was too low to perform statistical analysis. A limitation of this study relies in the possibility that asymptomatic infected women were not systematically detected.ConclusionsWe observed an increased frequency of pregnant women with maternal morbidities and diagnosis of COVID-19 compared to pregnant women without COVID-19. It appears essential to be aware of this, notably in populations at known risk of developing a more severe form of infection or obstetrical morbidities and in order for obstetrical units to better inform pregnant women and provide the best care. Although causality cannot be determined from these associations, these results may be in line with recent recommendations in favor of vaccination for pregnant women.

In a national retrospective study, Sylvie Epelboin and colleagues investigate obstetrical outcomes and maternal morbidities among pregnant women with a COVID-19 diagnosis in France.     

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors’ samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.     

Moesin and Stress-Induced Phosphoprotein-1 Are Possible Sero-Diagnostic Markers of Psoriasis

To identify diagnostic markers for psoriasis vulgaris and psoriatic arthritis, autoantibodies in sera from psoriasis vulgaris and psoriatic arthritis patients were screened by two-dimensional immunoblotting (2D-IB). Based on 2D-IB and MADLI TOF/TOF-MS analyses, eleven proteins each in psoriasis vulgaris and psoriatic arthritis were identified as autoantigens. Furthermore, serum levels of moesin, keratin 17 (K17), annexin A1 (ANXA1), and stress-induced phophoprotein-1 (STIP1), which were detected as autoantigens, were studied by dot blot analysis with psoriasis patients and healthy controls. The levels of moesin and STIP1 were significantly higher in sera from patients with psoriasis vulgaris than in the controls (moesin: P<0.05, STIP1: P<0.005). The area under the curve (AUC) for moesin and STIP1 between patients with psoraisis vulgaris and controls was 0.747 and 0.792, respectively. STIP1 and K17 levels were significantly higher in sera from patients with psoriatic arthritis than in those with psoriasis vulgaris (P<0.05 each). The AUC for STIP1 and K17 between patients with psoriatic arthritis and psoriasis vulgaris was 0.69 and 0.72, respectively. The STIP1 or moesin, CK17 serum level was not correlated with disease activity of psoriasis patients. These data suggest that STIP1 and moesin may be novel and differential sero-diagnostic markers for psoriasis vulgaris and psoriatic arthritis.     

Serum metabolite profiling of B-cell non-Hodgkin’s lymphoma using UPLC-QTOFMS and GC-TOFMS

A global metabolic profiling was generated with serum samples of patients with B-cell non-Hodgkin’s lymphoma (NHL) and healthy controls using two different analytical platforms for metabonomics, UPLC-QTOFMS and GC-TOFMS, in conjunction with multivariate data analysis and ROC analysis. Significant difference in metabolic characteristics was observed between B-cell NHL and healthy control by OPLS-DA. A total of 37 differential metabolites for B-cell NHL were identified. Some significant changes in metabolites were detected, indicating that there were disturbances of key metabolic pathways, including bile acids, glycerophospholipids, fatty acids metabolism, steroid biosynthesis, glycolysis, as well as glycine, serine and threonine metabolism associated with B-cell NHL. A panel of metabolite markers composed of choline, arachidonic acid, LysoPC (17:0), PA (16:0/16:0) and coproporphyrin from UPLC-QTOFMS and another panel of markers composed of benzenebutanoic acid, β-hydroxypyruvic acid, D-2-hydroxyoctanoic acid, pyruvic acid and arachidonic acid derived from GC-TOFMS were selected. A ROC curve analysis of these markers resulted in an AUC of 0.968 and 1.00 for the UPLC-QTOFMS and GC-TOFMS analysis, respectively. These biochemical changes provide a novel molecular diagnostic approach which could be helpful to further understand the pathogenesis and identify the therapeutic target of B-cell NHL.     

Serum DSG2 as a potential biomarker for diagnosis of esophageal squamous cell carcinoma and esophagogastric junction adenocarcinoma

Background: Exploration of serum biomarkers for early detection of upper gastrointestinal cancer is required. Here, we aimed to evaluate the diagnostic potential of serum desmoglein-2 (DSG2) in patients with esophageal squamous cell carcinoma (ESCC) and esophagogastric junction adenocarcinoma (EJA).Methods: Serum DSG2 levels were measured by enzyme-linked immunosorbent assay (ELISA) in 459 participants including 151 patients with ESCC, 96 with EJA, and 212 healthy controls. Receiver operating characteristic (ROC) curves were used to evaluate diagnostic accuracy.Results: Levels of serum DSG2 were significantly higher in patients with ESCC and EJA than those in healthy controls (P<0.001). Detection of serum DSG2 demonstrated an area under the ROC curve (AUC) value of 0.724, sensitivity of 38.1%, and specificity of 84.8% for the diagnosis of ESCC in the training cohort, and AUC 0.736, sensitivity 58.2%, and specificity 84.7% in the validation cohort. For diagnosis of EJA, measurement of DSG2 provided a sensitivity of 29.2%, a specificity of 90.2%, and AUC of 0.698. Similar results were observed for the diagnosis of early-stage ESCC (AUC 0.715 and 0.722, sensitivity 36.3 and 50%, and specificity 84.8 and 84.7%, for training and validation cohorts, respectively) and early-stage EJA (AUC 0.704, sensitivity 44.4%, and specificity 86.9%). Analysis of clinical data indicated that DSG2 levels were significantly associated with patient age and histological grade in ESCC (P<0.05).Conclusion: Serum DSG2 may be a diagnostic biomarker for ESCC and EJA.     

Determining clinically relevant features in cytometry data using persistent homology

Cytometry experiments yield high-dimensional point cloud data that is difficult to interpret manually. Boolean gating techniques coupled with comparisons of relative abundances of cellular subsets is the current standard for cytometry data analysis. However, this approach is unable to capture more subtle topological features hidden in data, especially if those features are further masked by data transforms or significant batch effects or donor-to-donor variations in clinical data. We present that persistent homology, a mathematical structure that summarizes the topological features, can distinguish different sources of data, such as from groups of healthy donors or patients, effectively. Analysis of publicly available cytometry data describing non-naïve CD8+ T cells in COVID-19 patients and healthy controls shows that systematic structural differences exist between single cell protein expressions in COVID-19 patients and healthy controls. We identify proteins of interest by a decision-tree based classifier, sample points randomly and compute persistence diagrams from these sampled points. The resulting persistence diagrams identify regions in cytometry datasets of varying density and identify protruded structures such as ‘elbows’. We compute Wasserstein distances between these persistence diagrams for random pairs of healthy controls and COVID-19 patients and find that systematic structural differences exist between COVID-19 patients and healthy controls in the expression data for T-bet, Eomes, and Ki-67. Further analysis shows that expression of T-bet and Eomes are significantly downregulated in COVID-19 patient non-naïve CD8+ T cells compared to healthy controls. This counter-intuitive finding may indicate that canonical effector CD8+ T cells are less prevalent in COVID-19 patients than healthy controls. This method is applicable to any cytometry dataset for discovering novel insights through topological data analysis which may be difficult to ascertain otherwise with a standard gating strategy or existing bioinformatic tools.