Nasopharyngeal SARS-CoV-2 load and perinatal outcomes after maternal infection diagnosed close to delivery.

BACKGROUND: The occurrence of COVID-19 during the pregnancy can cause several negative maternal and neonatal outcomes. Nasopharyngeal viral load is associated with inflammatory markers and might influence the disease severity in non-pregnant patients, but there are no data about the relationship between viral load and perinatal outcomes in pregnant patients. OBJECTIVE: To investigate the hypothesis that nasopharyngeal SARS-CoV-2 load (estimated with real-time polymerase chain reaction delta cycle (ΔCt), measured in hospital clinical laboratories) is associated with perinatal outcomes, when COVID-19 is diagnosed in the third trimester of pregnancy. STUDY DESIGN: International, retrospective, observational, multi-center, cohort study enrolling 390 women (393 neonates, three pairs of twins), analyzed with multivariate generalized linear models with skewed distributions (gamma) and identity link. The analyses were conducted for the whole population and then followed by a subgroup analysis according to the clinical severity of maternal COVID-19. RESULTS: The estimated viral load in maternal nasopharynx is not significantly associated with gestational age at birth (adjusted B: -0.008 (95%CI: -0.04; 0.02); p = 0.889), birth weight (adjusted B: 4.29 (95%CI: -25; 35); p = 0.889), weight Z-score (adjusted B: -0.01 (95%CI: -0.03; 1); p = 0.336), 5' Apgar scores (adjusted B: -0. -9.8e-4 (95%CI: -0.01; 0.01); p = 0.889), prematurity (adjusted OR: -0.97 (95%CI: 0.93; 1.03); p = 0.766) and the small for gestational age status (adjusted OR: 1.03 (95%CI: 0.99; 1.07); p = 0.351). Similar results were obtained in subgroup analyses according to COVID-19 clinical severity. CONCLUSIONS: The estimated maternal nasopharyngeal viral load in pregnant women affected by COVID-19 during the third trimester is not associated with main perinatal outcomes.

Circulating tissue inhibitor of metalloproteinases 1 (TIMP-1) at COVID-19 onset predicts severity status.

Background: Systemic biomarkers for severity of SARS-CoV-2 infection are of great interest. In this study, we evaluated a set of collagen metabolites and extracellular matrix remodeling biomarkers including procollagen type III amino terminal propeptide (PIIINP), tissue inhibitor of metalloproteinases 1 (TIMP-1) and hyaluronic acid (HA) as prognostic indicators in COVID-19 patients. Methods: Ninety COVID-19 patients with the absence of chronic liver diseases were enrolled. Serum PIIINP, TIMP-1, and HA were measured and correlated with inflammatory indices and clinical variables. Patients were stratified for disease severity according to WHO criteria in two groups, based on the requirement of oxygen support. Results: Serum TIMP-1, but not PIIINP and HA was significantly higher in patients with WHO score ≥5 compared to patients with WHO score <5 [PIIINP: 7.2 (5.4-9.5) vs. 7.1 (4.5-9.9), p = 0.782; TIMP-1: 298.1 (20.5-460) vs. 222.2 (28.5-452.8), p = 0.01; HA: 117.1 (55.4-193.7) vs. 75.1 (36.9-141.8), p = 0.258]. TIMP-1 showed moderate correlation with CRP (r = 0.312, p = 0.003) and with LDH (r = 0.263, p = 0.009). CRP and serum LDH levels were significantly higher in COVID-19 patients with WHO score ≥5 compared to the group of patients with WHO score < 5 [15.8 (9-44.5) vs. 9.3 (3.4-33.8), p = 0.039 and 373 (282-465) vs. 289 (218-383), p = 0.013, respectively]. Conclusion: In patients with COVID-19, circulating TIMP-1 was associated with disease severity and with systemic inflammatory index, suggesting that TIMP-1 could represent a promising non-invasive prognostic biomarker in COVID-19 patients. Interestingly, our results prompted that serum TIMP-1 level may potentially be used to select the patients for therapeutic approaches targeting matrix metalloproteases pathway.

New strategy for the identification of prostate cancer: The combination of Proclarix and the prostate health index.

OBJECTIVES: Prostate health index (PHI) and, more recently, Proclarix have been proposed as serum biomarkers for prostate cancer (PCa). In this study, we aimed to evaluate Proclarix and PHI for predicting clinically significant prostate cancer (csPCa). PATIENTS AND METHODS: Proclarix and PHI were measured using samples of 344 men from two different centers. All patients underwent prostate biopsy, and among those, 188 men with PCa on biopsy had an additional radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/ml. Evaluation of area under the curve (AUC) and performance at predefined cut-offs of Proclarix and PHI risk scores as well as the linear combination thereof was performed to predict csPCa. PSA density was used as an independent comparator. RESULTS: The cohort median age and PSA were 65 (interquartile range [IQR]: 60-71) and 5.6 (IQR: 4.3-7.2) ng/ml, respectively. CsPCa was diagnosed in 161 (47%) men based on the RP specimen. ROC analysis showed that Proclarix and PHI accurately predicted csPCa with no significant difference (AUC of 0.79 and 0.76, p = 0.378) but significantly better when compared to PSA density (AUC of 0.66, p < 0.001). When using specific cut-offs, Proclarix (cut-off 10) revealed higher specificity and positive predictive value than PHI (cut-off 27) at similar sensitivities. The combination of Proclarix and PHI provided a significant increase in the AUC (p ≤ 0.007) compared to the individual tests alone and the highest clinical benefit was achieved. CONCLUSION: Results of this study show that both Proclarix and PHI accurately detect the presence of csPCa. The model combining Proclarix and PHI revealed the synergistic effect and improved the diagnostic performance of the individual tests.

Improved SARS-CoV-2 sequencing surveillance allows the identification of new variants and signatures in infected patients.

BACKGROUND: Genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only approach to rapidly monitor and tackle emerging variants of concern (VOC) of the COVID-19 pandemic. Such scrutiny is crucial to limit the spread of VOC that might escape the immune protection conferred by vaccination strategies or previous virus exposure. It is also becoming clear now that efficient genomic surveillance would require monitoring of the host gene expression to identify prognostic biomarkers of treatment efficacy and disease progression. Here we propose an integrative workflow to both generate thousands of SARS-CoV-2 genome sequences per week and analyze host gene expression upon infection. METHODS: In this study we applied an integrated workflow for RNA extracted from nasal swabs to obtain in parallel the full genome of SARS-CoV-2 and transcriptome of host respiratory epithelium. The RNA extracted from each sample was reverse transcribed and the viral genome was specifically enriched through an amplicon-based approach. The very same RNA was then used for patient transcriptome analysis. Samples were collected in the Campania region, Italy, for viral genome sequencing. Patient transcriptome analysis was performed on about 700 samples divided into two cohorts of patients, depending on the viral variant detected (B.1 or delta). RESULTS: We sequenced over 20,000 viral genomes since the beginning of the pandemic, producing the highest number of sequences in Italy. We thus reconstructed the pandemic dynamics in the regional territory from March 2020 to December 2021. In addition, we have matured and applied novel proof-of-principle approaches to prioritize possible gain-of-function mutations by leveraging patients' metadata and isolated patient-specific signatures of SARS-CoV-2 infection. This allowed us to (i) identify three new viral variants that specifically originated in the Campania region, (ii) map SARS-CoV-2 intrahost variability during long-term infections and in one case identify an increase in the number of mutations in the viral genome, and (iii) identify host gene expression signatures correlated with viral load in upper respiratory ways. CONCLUSION: In conclusion, we have successfully generated an optimized and cost-effective strategy to monitor SARS-CoV-2 genetic variability, without the need of automation. Thus, our approach is suitable for any lab with a benchtop sequencer and a limited budget, allowing an integrated genomic surveillance on premises. Finally, we have also identified a gene expression signature defining SARS-CoV-2 infection in real-world patients' upper respiratory ways.

SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system.

BACKGROUND: Since the first complete genome sequencing of SARS-CoV-2 in December 2019, more than 550,000 genomes have been submitted into the GISAID database. Sequencing of the SARS-CoV-2 genome might allow identification of variants with increased contagiousness, different clinical patterns and/or different response to vaccines. A highly automated next generation sequencing (NGS)-based method might facilitate an active genomic surveillance of the virus. METHODS: RNA was extracted from 27 nasopharyngeal swabs obtained from citizens of the Italian Campania region in March-April 2020 who tested positive for SARS-CoV-2. Following viral RNA quantification, sequencing was performed using the Ion AmpliSeq SARS-CoV-2 Research Panel on the Genexus Integrated Sequencer, an automated technology for library preparation and sequencing. The SARS-CoV-2 complete genomes were built using the pipeline SARS-CoV-2 RECoVERY (REconstruction of COronaVirus gEnomes & Rapid analYsis) and analysed by IQ-TREE software. RESULTS: The complete genome (100%) of SARS-CoV-2 was successfully obtained for 21/27 samples. In particular, the complete genome was fully sequenced for all 15 samples with high viral titer (> 200 copies/µl), for the two samples with a viral genome copy number < 200 but greater than 20, and for 4/10 samples with a viral load < 20 viral copies. The complete genome sequences classified into the B.1 and B.1.1 SARS-CoV-2 lineages. In comparison to the reference strain Wuhan-Hu-1, 48 total nucleotide variants were observed with 26 non-synonymous substitutions, 18 synonymous and 4 reported in untranslated regions (UTRs). Ten of the 26 non-synonymous variants were observed in ORF1ab, 7 in S, 1 in ORF3a, 2 in M and 6 in N genes. CONCLUSIONS: The Genexus system resulted successful for SARS-CoV-2 complete genome sequencing, also in cases with low viral copies. The use of this highly automated system might facilitate the standardization of SARS-CoV-2 sequencing protocols and make faster the identification of novel variants during the pandemic.