A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events (preprint)

Background: Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposures to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predict diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-art DNAm risk scores for cardiovascular diseases, the ‘next-generation’ epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2. Results: : Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent datasets from Europe and the US. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant). Conclusions: : We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore , predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures.

Evaluation of the diagnostic accuracy of a new point-of-care rapid test for SARS-CoV-2 virus detection (preprint)

Background: The easy access to a quick diagnosis of coronavirus disease 2019 (COVID-19) is a key point to improve the management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to contain its spread. Up to now, laboratory real-time PCR is the standard of care, but requires a fully equipped laboratory and significant infrastructure. Consequently, new diagnostic tools are required. Methods: In the present work, the diagnostic accuracy of the point-of-care rapid test "bKIT Virus Finder COVID-19" (Hyris Ltd) is evaluated by a retrospective and a prospective analysis on SARS CoV-2 samples previously assessed with an FDA “authorized for the emergency use - EUA” reference method. Descriptive statistics were used for the present study.Results: Results obtained with the Hyris Kit are the same as that of standard laboratory-based real time PCR methods for all the analyzed samples. In addition, the Hyris Kit provides the test results in less than 2 hours, a significantly shorter time compared to the reference methods, without the need of a fully equipped laboratory. Conclusions: To conclude, the Hyris kit represents a promising tool to improve the health surveillance and to increase the capacity of SARS-CoV-2 testing.

Comparing the COVID-19 pandemic in space and over time in Europe, using numbers of deaths, crude rates and adjusted mortality trend ratios (preprint)

Background Since COVID19 was declared a pandemic, attempts have been made to monitor trends over time and to compare countries and regions. Insufficient testing for COVID19 underestimates the incidence and inflates the case/fatality proportion. Given the age and sex distribution of morbidity and mortality from COVID19, the underlying sex and age distribution of a population needs to be accounted for. The aim of this paper is to present a method for monitoring trends of COVID19 using adjusted mortality trend ratios (AMTR). Methods Age and sex mortality distribution of a reference population composed of the first 14,086 fatalities which occurred before the end of March and were reported in Europe by some countries were used to calculate age and sex specific mortality rates per 1,000,000 population. These were applied to each country population to calculate the expected deaths. Adjusted Mortality Trend Ratios (AMTRs) with 95% confidence intervals (C.I.) were calculated for selected European countries from 17/03/2020 to 22/06/2020 by dividing observed cumulative mortality, by expected mortality times the crude mortality of the reference population. These estimated the sex and age adjusted mortality for COVID19 per million population in each country. Results The cumulative mortality from COVID19, the crude mortality rates, and the AMTRs were calculated for each country and compared. United Kingdom, Italy, France and Spain registered the highest mortality in Europe. On 22/06/2020 in Europe the total mortality rate from COVID-19 was 352 per 1,000,000 inhabitants; and it was highest in Belgium (850 per 1,000,000 inhabitants) followed by Spain, UK, Italy, Sweden and France. When accounting for the underlying age and sex structure of each country, Belgium remained the single country experiencing the highest AMTR of 929 per million inhabitants on 22/06/2020; however Ireland (which had a CMR in line with the total European population) emerged as having experienced a much more important impact of COVID19 mortality with an AMTR of 550/million on 22/06/2020, higher than Sweden and Italy. Conclusions In understanding and managing the pandemic of COVID19, comparable international data is a priority. Our methods allow a fair comparison of mortality in space and over time. The authors urge the WHO, given the absence of age and sex-specific mortality data for direct standardisation, to adopt this method to estimate the comparative mortality from COVID19 pandemic worldwide.

Tocilizumab for patients with COVID-19 pneumonia. The TOCIVID-19 phase 2 trial (preprint)

BackgroundTocilizumab blocks pro-inflammatory activity of interleukin-6 (IL-6), involved in pathogenesis of pneumonia the most frequent cause of death in COVID-19 patients. MethodsA multicentre, single-arm, hypothesis-driven phase 2 trial was planned to study the effect of Tocilizumab on lethality rates at 14 and 30 days (co-primary endpoints). A cohort of patients consecutively enrolled after phase 2 was used as a validation dataset. A multivariable logistic regression was performed to generate hypotheses, while controlling for possible confounders. Resultsout of 301 patients in phase 2 intention-to-treat (ITT) analysis, 180 (59.8%) received tocilizumab. With 67 death events, lethality rates were 18.4% (97.5%CI: 13.6-24.0, P=0.52) and 22.4% (97.5%CI: 17.2-28.3, P<0.001) at 14 and 30 days. Lethality rates were lower in the validation dataset, including 920 patients. No signal of specific drug toxicity was reported. The multivariable logistic regression suggests tocilizumab might be more effective in patients not requiring mechanical respiratory support at baseline. Also, it supports a positive effect on lethality rate of the use of corticosteroids. ConclusionsTocilizumab reduced lethality rate at 30 days compared with null hypothesis, without significant toxicity. Such result support the use of tocilizumab while waiting for ongoing phase 3 trials. RegistrationEudraCT (2020-001110-38); clinicaltrials.gov (NCT04317092)