Epigenetic liquid biopsies reveal elevated vascular endothelial cell turnover and erythropoiesis in asymptomatic COVID-19 patients (preprint)

The full spectrum of tissues affected by SARS-CoV-2 infection is crucial for deciphering the heterogenous clinical course of COVID-19. Here, we analyzed DNA methylation and histone modification patterns in circulating chromatin to assess cell type-specific turnover in severe and asymptomatic COVID-19 patients, in relation to clinical outcome. Patients with severe COVID-19 had a massive elevation of circulating cell-free DNA (cfDNA) levels, which originated in lung epithelial cells, cardiomyocytes, vascular endothelial cells and erythroblasts, suggesting increased cell death or turnover in these tissues. The immune response to infection was reflected by elevated B cell and monocyte/macrophage cfDNA levels, and by evidence of an interferon response in cells prior to cfDNA release. Strikingly, monocyte/macrophage cfDNA levels (but not monocyte counts), as well as lung epithelium cfDNA and vascular endothelial cfDNA, predicted clinical deterioration and duration of hospitalization. Asymptomatic patients had elevated levels of immune-derived cfDNA but did not show evidence of pulmonary or cardiac damage. Surprisingly, these patients showed elevated levels of vascular endothelial cell and erythroblast cfDNA, suggesting that sub-clinical vascular and erythrocyte turnover are universal features of COVID-19, independent of disease severity. Epigenetic liquid biopsies provide non-invasive means of monitoring COVID-19 patients, and reveal sub-clinical vascular damage and red blood cell turnover.

Lessons from applied large-scale pooling of 133,816 SARS-CoV-2 RT-PCR tests (preprint)

Pooling multiple swab samples prior to RNA extraction and RT-PCR analysis was proposed as a strategy to reduce costs and increase throughput of SARS-CoV-2 tests. However, reports on practical large-scale group testing for SARS-CoV-2 have been scant. Key open questions concern reduced sensitivity due to sample dilution; the rate of false positives; the actual efficiency (number of tests saved by pooling) and the impact of infection rate in the population on assay performance. Here we report analysis of 133,816 samples collected at April-September 2020, tested by pooling for the presence of SARS-CoV-2. We spared 76% of RNA extraction and RT-PCR tests, despite the reality of frequently changing prevalence rate (0.5%-6%). Surprisingly, we observed pooling efficiency and sensitivity that exceed theoretical predictions, which resulted from non-random distribution of positive samples in pools. Overall, the findings strongly support the use of pooling for efficient large high throughput SARS-CoV-2 testing.

ApharSeq: An Extraction-free Early-Pooling Protocol for Massively Multiplexed SARS-CoV-2 Detection (preprint)

The global SARS-CoV-2 pandemic led to a steep increase in the need for viral detection tests worldwide. Most current tests for SARS-CoV-2 are based on RNA extraction followed by quantitative reverse-transcription PCR assays that involve a separate RNA extraction and qPCR reaction for each sample with a fixed cost and reaction time. While automation and improved logistics can increase the capacity of these tests, they cannot exceed this lower bound dictated by one extraction and reaction per sample. Multiplexed next generation sequencing (NGS) assays provide a dramatic increase in throughput, and hold the promise of richer information on viral strains and host immune response. Here, we establish a significant improvement of existing RNA-seq detection protocols. Our workflow, ApharSeq, includes a fast and cheap RNA capture step, that is coupled to barcoding of individual samples, followed by sample-pooling prior to the reverse transcription, PCR and massively parallel sequencing. Thus, only one step is performed before pooling hundreds of barcoded samples for subsequent steps and further analysis. We characterize the quantitative aspects of the assay, and test ApharSeq on dozens of clinical samples in a robotic workflow. Our proposed workflow is estimated to reduce costs by 10-50 fold, labor by 5-100 fold, automated liquid handling by 5-10 fold, and reagent requirements by 100-1000 fold compared to existing testing methods.

The effect of a national lockdown in response to COVID-19 pandemic on the prevalence of clinical symptoms in the population (preprint)

The vast and rapid spread of COVID-19 calls for immediate action from policy-makers, and indeed, many countries have implemented lockdown measures to varying degrees. Here, we utilized nationwide surveys that assess COVID-19 associated symptoms to analyse the effect of the lockdown policy in Israel on the prevalence of clinical symptoms in the population. Daily symptom surveys were distributed online and included questions regarding fever, respiratory symptoms, gastrointestinal symptoms, anosmia and ageusia. A total of 2,071,349 survey responses were analysed. We defined a single measure of symptoms, Symptoms Average (SA), as the mean number of symptoms reported by responders. Data were collected between March 15th to June 3rd, 2020. Notably, on the population level, following severe lockdown measures between March 15th and April 20th, SA sharply declined by 83.8% (p < 0.05), as did every single symptom, including the most common symptoms reported by our responders, cough and rhinorrhea and\or nasal congestion, which decreased by 74.1% (p < 0.05) and 69.6% (p < 0.05), respectively. Similarly, on the individual level, analysis of repeated responses from the same individuals (N = 208,637) over time also showed a decrease in symptoms during this time period. Moreover, the reduction in symptoms was observed in all cities in Israel, and in several stratifications of demographic characteristics. Different symptoms exhibit different reduction dynamics, suggesting differences in the nature of the symptoms or in the underlying medical conditions. Between May 13th and June 3rd, following several subsequent lockdown relief measures, we observed an increase in individual symptoms and in SA, which increased by 31.42%. Overall, these results demonstrate a profound decrease in a variety of clinical symptoms following the implementation of a lockdown in Israel, and an increase in the prevalence of symptoms following the loosening of lockdown restrictions. As our survey symptoms are not specific to COVID-19 infection, this effect likely represents an overall nationwide reduction in the prevalence of infectious diseases, including COVID-19. This quantification may be of major interest for COVID-19 pandemic, as many countries consider implementation of lockdown strategies.

Pooled RNA extraction and PCR assay for efficient SARS-CoV-2 detection (preprint)

Testing for active SARS-CoV-2 infection is a fundamental tool in the public health measures taken to control the COVID-19 pandemic. Due to the overwhelming use of SARS-CoV-2 RT-PCR tests worldwide, availability of test kits has become a major bottleneck. Here we demonstrate pooling strategies to perform RNA extraction and RT-PCR in pools, significantly increasing throughput while maintaining clinical sensitivity. We implemented the method in a routine clinical diagnosis setting of asymptomatic populations, and already tested 5,464 individuals for SARS-CoV-2 using 731 RNA extraction and RT-PCR kits. We identified six SARS-CoV-2 positive patients corresponding to 0.11% of the tested population.

Building an International Consortium for Tracking Coronavirus Health Status (preprint)

Information is the most potent protective weapon we have to combat a pandemic, at both the individual and global level. For individuals, information can help us make personal decisions and provide a sense of security. For the global community, information can inform policy decisions and offer critical insights into the epidemic of COVID-19 disease. Fully leveraging the power of information, however, requires large amounts of data and access to it. To achieve this, we are making steps to form an international consortium, Coronavirus Census Collective (CCC, coronaviruscensuscollective.org), that will serve as a hub for integrating information from multiple data sources that can be utilized to understand, monitor, predict, and combat global pandemics. These sources may include self-reported health status through surveys (including mobile apps), results of diagnostic laboratory tests, and other static and real-time geospatial data. This collective effort to track and share information will be invaluable in predicting hotspots of disease outbreak, identifying which factors control the rate of spreading, informing immediate policy decisions, evaluating the effectiveness of measures taken by health organizations on pandemic control, and providing critical insight on the etiology of COVID-19. It will also help individuals stay informed on this rapidly evolving situation and contribute to other global efforts to slow the spread of disease. In the past few weeks, several initiatives across the globe have surfaced to use daily self-reported symptoms as a means to track disease spread, predict outbreak locations, guide population measures and help in the allocation of healthcare resources. The aim of this paper is to put out a call to standardize these efforts and spark a collaborative effort to maximize the global gain while protecting participant privacy.

A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys (preprint)

Coronavirus infection spreads in clusters and therefore early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers. We show preliminary results from a survey of over 38,000 Israelis and call for an international consortium to extend this concept in order to develop predictive models. We expect such data to allow: Faster detection of spreading zones and patients; Obtaining a current snapshot of the number of people in each area who have developed symptoms; Predicting future spreading zones several days before an outbreak occurs; Evaluating the effectiveness of the various social distancing measures taken, and their contribution to reduce the number of symptomatic people. Such information can provide a valuable tool for decision makers to decide which areas need strengthening of social distancing measures and which areas can be relieved. Researchers from the U.S, Spain, and Italy have adopted our approach and we are collaborating to further improve it. We call with urgency for other countries to join this international consortium, and to share methods and data collected from these daily, simple, one-minute surveys.