Lower probability and shorter duration of infections after Covid-19 vaccine correlate with anti-SARS-CoV-2 circulating IgGs (preprint)

The correlation between immune responses and protection from SARS-CoV-2 infections and its duration remains unclear. We performed a sanitary surveillance at the European Institute of Oncology (IEO) in Milan over a 17 months period. Pre-vaccination, in 1,493 participants, we scored 266 infections (17.8%) and 8 possible reinfections (3%). Post-vaccination, we identified 30 infections in 2,029 vaccinated individuals (1.5%). We report that the probability of infection post-vaccination is i) significantly lower compared to natural infection, ii) associated with a significantly shorter median duration of infection than that of first infection and reinfection, iii) anticorrelated with circulating antibody levels.

Inhibiting LSD1 suppresses coronavirus-induced inflammation but spares innate antiviral activity (preprint)

Tissue-resident macrophages exert critical but conflicting effects on the progression of coronavirus infections by secreting both anti-viral type I Interferons and tissue-damaging inflammatory cytokines. Steroids, the only class of host-targeting drugs approved for Covid19, indiscriminately suppress both responses, possibly impairing viral clearance, and provide limited clinical benefit. Here we set up a mouse in vitro co-culture system that reproduces the macrophage response to SARS-CoV2 seen in patients and allows quantitation of inflammatory and antiviral activities. We show that the NFKB-dependent inflammatory response can be selectively inhibited by ablating the lysine-demethylase LSD1, which additionally unleashed interferon-independent ISG activation and blocked viral egress through the lysosomal pathway. These results provide a rationale for repurposing LSD1 inhibitors, a class of drugs extensively studied in oncology, for Covid-19 treatment.

Semantic and geographical analysis of Covid-19 trials reveals a fragmented clinical research landscape likely to impair informativeness. (preprint)

Background. The unprecedented impact of the Covid-19 pandemics on modern society has ignited a "gold rush" for effective treatment and diagnostic strategies, with a significant diversion of economical, scientific and human resources towards dedicated clinical research. We aimed to describe trends in this rapidly changing landscape to inform adequate resource allocation. Methods. We developed informatic tools (Covid Trial Monitor) to analyze in real time growth rate, geographical distribution and characteristics of Covid-19 related trials. We defined structured semantic ontologies with controlled vocabularies to categorize trial interventions, study endpoints and study designs. Data and analyses are publicly available at https://bioinfo.ieo.it/shiny/app/CovidCT Results. We observe a clear prevalence of monocentric trials with highly heterogeneous endpoints and a significant disconnect between geographic distribution and disease prevalence, implying that most countries would need to recruit unrealistic percentages of their total prevalent cases to fulfill enrolment. Conclusions. This geographically and methodologically incoherent growth sheds doubts on the actual feasibility of locally reaching target sample sizes and the probability of most of these trials providing reliable and transferable result. We call for the harmonization of clinical trial design criteria for Covid19 and the increased use of larger master protocols incorporating elements of adaptive designs. Covid Trial Monitor identifies critical issues in current Covid19-related clinical research and represents a useful resource for researchers and policymakers to improve the quality and efficiency of related trials

Meta-analysis of diagnostic performance of serological tests for SARS-CoV-2 antibodies and public health implications (preprint)

Serology-based tests have become a key public health element in the COVID-19 pandemic to assess the degree of herd immunity that has been achieved in the population. These tests differ between one another in several ways. Here, we conducted a systematic review and meta-analysis of the diagnostic accuracy of currently available SARS-CoV-2 serological tests, and assessed their real-world performance under scenarios of varying proportion of infected individuals. We included independent studies that specified the antigen used for antibody detection and used quantitative methods. We identified nine independent studies, of which six were based on commercial ELISA or CMIA/CLIA assays, and three on in-house tests. Test sensitivity ranged from 68% to 93% for IgM, from 65% to 100% for IgG, and from 83% to 98% for total antibodies. Random-effects models yielded a summary sensitivity of 82% (95%CI 75-88%) for IgM, and 85% for both IgG (95%CI 73-93%) and total antibodies (95%CI 74-94%). Specificity was very high for most tests, and its pooled estimate was 98% (95%CI 92-100%) for IgM and 99% (95%CI 98-100%) for both IgG and total antibodies. The heterogeneity of sensitivity and specificity across tests was generally high (I2[≤]50%). In populations with a low prevalence ([≤]5%) of seroconverted individuals, the positive predictive value would be [≤]88% for most assays, except those reporting perfect specificity. Our data suggest that the use of serological tests for large-scale prevalence surveys (or to grant "immunity passports") are currently only justified in hard-hit regions, while they should be used with caution elsewhere.