Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility

Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak

Effect of cross-flow velocity, oil concentration and salinity on the critical flux of an oil-in-water emulsion in microfiltration

Microfiltration is an attractive means for treating oily wastewater, especially when the size of the oil droplets are micrometer-sized since the conventional techniques become deficient. A systematic study on the critical flux of oil-in-water emulsion, which behaves differently from other colloidal foulants with regards to deformation, coalescence and splitting, has not been carried out to date. This was the goal of the current study, which employed the Direct Observation Through the Membrane (DOTM) technique to characterize the critical flux of oil-in-water emulsions of various concentrations, and at various cross-flow velocities (CFV) and salt concentrations. Five observations can be highlighted here. Firstly, the oil droplets with a mean droplet diameter of approximately 5 µm exhibited critical fluxes equal to or greater than latex particles of 10 µm. This is likely due to the twin effects of membrane oleophobicity promoting back-transport of the oil foulant from the membrane and the presence of a droplet size distribution with larger drops that can enhance the shear-induced diffusion of the average drops. Secondly, the critical flux values did not agree with the model that is valid for the size range the mean droplet diameter falls in, but instead agreed with the model adapted for smaller particulate foulants. Thirdly, the increase in the critical flux with CFV was more significant for the lower oil concentration. Fourthly, a striping phenomenon was observed at higher oil concentrations and lower CFV values. Striping was not observed for latex particles. Fifthly, the critical flux decreased with salt concentration. These findings highlight the unique fouling behavior of oil-in-water emulsions in microfiltration.EDB (Economic Devt. Board, S’pore)MOE (Min. of Education, S’pore

Membrane fouling by emulsified oil: a review

Separation of liquid–liquid emulsions is a challenging problem that has gained importance with the development of unconventional oil resources. Large volumes of water contaminated by emulsified oil need to be treated for safe disposal or efficient reuse. Among technologies capable of removing oil dispersed into smaller size droplets (<15 µm), membrane processes occupy a unique niche where the required separation performance and throughput can be achieved at a relatively modest cost. As with most membrane-based processes, separation of emulsified oil entails membrane fouling that requires regular maintenance and imposes additional operational costs. Emulsions present unique challenges as their fouling behavior is affected by droplets’ deformability, coalescence both in the bulk and on the membrane surface, membrane wetting by droplets and films, pore blockage and intrusion by oil. The purpose of this paper is to overview the literature on the separation of oil–water emulsions by pressure-driven membrane processes with an emphasis on how properties of emulsions and membranes affect separation performance. A particular focus is on membrane fouling by oil including physicochemical bases, detection, diagnosis, and visualization. The review spans studies with both industrial oily wastewater and synthetic model emulsions of various types of oil. The discussion of membrane materials is limited to surface modifications that render more fouling-resistant membranes.Economic Development Board (EDB)Ministry of Education (MOE)Nanyang Technological UniversityThis material is based upon work supported in part by the U.S. National Science Foundation Partnerships for International Research and Education program under Grant IIA-1243433 and the U.S. National Science Foundation Graduate Research Fellowship for Emily N. Tummons under Grant No. DGE-0802267. We also acknowledge funding from NTU iFood Research Grant (M4081465.120) and Singapore Ministry of Education Academic Research Fund Tier 2 (MOE2014-T2-2-074). The Singapore Membrane Technology Centre acknowledges support from Singapore’s Economic Development Board

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease