COVID-19 infection dynamics revealed by SARS-CoV-2 wastewater sequencing analysis and deconvolution (preprint)

The use of RNA sequencing from wastewater samples is proven to be a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach has the advantage of being independent from patient population testing and symptomatic disease courses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given the sequencing data from the wastewater. Here we provide the first analysis of variant dynamics in Germany using wastewater sequencing and present PiGx SARS-CoV-2, a bit-by-bit reproducible end-to-end pipeline with comprehensive reports. To our knowledge, this is the first pipeline that includes all steps from raw-data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analysis. Using our pipeline on a dataset of wastewater samples, from different locations across Berlin, over the time period from February 2021 to June 2021, we could reconstruct the dynamic of the Variant of Concern (VoC) B.1.1.7 (alpha). Additionally, we detected the unique signature mutation M:T26767C for the VoC B.1.617.2 (delta) and its raise in early June. We also show that SARS-CoV-2 mutation load measured from wastewater sequencing is correlated with actual case numbers and it has potential to be used in a predictive manner. All in all, our study provides additional evidence that systematic wastewater analysis using sequencing and computational methods can be used for modeling the infection dynamics of SARS-CoV-2. In addition, the results show that our tool can be used to tease out new mutations and to detect any emerging new lineages of concern before clinical detection. Our approach can support efforts for establishing continuous monitoring and early-warning projects for COVID-19 or any other infectious disease.

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations (preprint)

Due to the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), deepening the host genetic contribution to severe COVID-19 may further improve our understanding about underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany, as well as hypothesis-driven targeted analysis of the human leukocyte antigen (HLA) region and chromosome Y haplotypes. We include detailed stratified analyses based on age, sex and disease severity. In addition to already established risk loci, our data identify and replicate two genome-wide significant loci at 17q21.31 and 19q13.33 associated with severe COVID-19 with respiratory failure. These associations implicate a highly pleiotropic ~0.9-Mb 17q21.31 inversion polymorphism, which affects lung function and immune and blood cell counts, and the NAPSA gene, involved in lung surfactant protein production, in COVID-19 pathogenesis.

Recovered not restored: Long-term health consequences after mild COVID-19 in non-hospitalized patients (preprint)

BackgroundWhile the leading symptoms during coronavirus disease 2019 (COVID-19) are acute and the majority of patients fully recover, a significant fraction of patients now increasingly experience long-term health consequences. However, most data available focus on health-related events after severe infection and hospitalization. We present a longitudinal, prospective analysis of health consequences in patients who initially presented with no or minor symptoms of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection. Hence we focus on mild COVID-19 in non-hospitalized patients. MethodsWe included 958 patients with confirmed SARS-CoV-2 infection in this study. Patients were observed for seven months from April 6th to December 2nd 2020 for long-term symptoms and SARS-CoV-2 antibodies. We identified anosmia, ageusia, fatigue or shortness of breath as most common, persisting symptoms at month 4 and 7 and summarized presence of such long-term health consequences as post-COVID syndrome (PCS). Predictors of long-term symptoms were assessed using an uni- and multivariable logistic regression model. FindingsWe observed 442 and 353 patients over four and seven months after symptom onset, respectively. Four months post SARS-CoV-2 infection, 8.6% (38/442) of patients presented with shortness of breath, 12.4% (55/442) with anosmia, 11.1% (49/442) with ageusia and 9.7% (43/442) with fatigue. At least one of these characteristic symptoms was present in 27.8% (123/442) and 34.8% (123/353) at month 4 and 7 post-infection, respectively. This corresponds to 12.8% patients with long-lasting symptoms relative to the initial total cohort (123/958). A lower baseline level of SARS-CoV-2 IgG, anosmia and diarrhea during acute COVID-19 were associated with higher risk to develop long-term symptoms. InterpretationThe on-going presence of either shortness of breath, anosmia, ageusia or fatigue as long-lasting symptoms even in non-hospitalized patients was observed at four and seven months post-infection and summarized as post-COVID syndrome (PCS). The continued assessment of patients with PCS will become a major task to define and mitigate the socioeconomic and medical long-term effects of COVID-19. FundingCOVIM:"NaFoUniMedCovid19"(FKZ: 01KX2021) Research in contextO_ST_ABSEvidence before this studyC_ST_ABSData about long-term health consequences after SARS-CoV-2 infection and COVID-19 is scarce and most available data describe health consequences in hospitalized patients during acute COVID-19. However, these studies do not take into account the vast majority of patients with a milder course of infection (WHO score1-3). Added value of this studyOur cohort consists of mostly mild COVID-19 cases that have been prospectively followed for a median time of 6.8 months. At least one trained physician critically reviewed the patients reported symptoms at each visit. We assessed SARS-CoV-2 IgG at each visit to correlate reported symptoms with serological data. At 4 months after SARS-CoV-2 infection, shortness of breath occurred in 8.6% (38/442), anosmia in 12.4% (55/442), ageusia in 11.1% (49/442), and fatigue in 9.7% (43/442) of patients. At least one characteristic symptom was present in 27.8% (123/442) and 34.8% (123/353) at months 4 and 7 post-infection, respectively. Symptoms were summarized as post-COVID syndrome (PCS). Relative to our initial total cohort (123/958), this corresponds to 12.8% patients with long-lasting symptoms. Lower baseline level of SARS-CoV-2 IgG, anosmia and diarrhea during acute COVID-19 were associated with higher risk of developing long-term symptoms. Implications of all available evidenceWe believe that our findings have important implications for the fields of infectious diseases and public health, because we show long-term health consequences may occur even after very mild COVID-19 in the outpatient setting. As up to 81% of all SARS-CoV-2 infected patients present with mild disease, it can be expected that PCS will affect a larger number of individuals than initially assumed, posing major medical, social and economic challenges.