Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Solving the Coupled System Improves Computational Efficiency of the Bidomain Equations

The bidomain equations are frequently used to model the propagation of cardiac action potentials across cardiac tissue. At the whole organ level the size of the computational mesh required makes their solution a significant computational challenge. As the accuracy of the numerical solution cannot be compromised, efficiency of the solution technique is important to ensure that the results of the simulation can be obtained in a reasonable time whilst still encapsulating the complexities of the system. In an attempt to increase efficiency of the solver, the bidomain equations are often decoupled into one parabolic equation that is computationally very cheap to solve and an elliptic equation that is much more expensive to solve. In this study the performance of this uncoupled solution method is compared with an alternative strategy in which the bidomain equations are solved as a coupled system. This seems counter-intuitive as the alternative method requires the solution of a much larger linear system at each time step. However, in tests on two 3-D rabbit ventricle benchmarks it is shown that the coupled method is up to 80% faster than the conventional uncoupled method — and that parallel performance is better for the larger coupled problem

Microbial inoculation to improve plant performance in mine‐waste substrates: A test using pigeon pea (Cajanus cajan)

Mining activities alter soil physicochemical and biological properties that are critical for plant establishment. Revitalisation of soil biological properties via microbial inoculations can potentially be adopted to improve vegetation restoration. Here, we evaluate the feasibility of using beneficial microorganisms in the form of commercially available inoculants to enhance plant performance in a non-toxic and infertile mine-waste substrate, using pigeon pea [Cajanus cajan (L) Millsp.] as a test plant. Six treatments were established to investigate the effects of inoculants (Bradyrhizobium spp., microbial mix and uninoculated controls) and water availability (low and moderate) in a factorial design over 6 months. Plant performance was determined by physiological parameters (leaf gas exchange, leaf carbon, nitrogen and stable isotopes) and growth (height and biomass). Plant xylem sap phytohormones were measured to determine the plants' physiological status and effects of inoculation treatments. Results revealed that water had a greater effect on plant growth than inoculation treatments. Inoculation treatments, however, improved some physiological parameters. This study suggests that physical conditions such as soil moisture and nutrient availability may occlude more subtle (direct or interactive) effects of beneficial soil microbes on plant growth and plant condition. Prior knowledge on the biological and physicochemical properties of the soil to be amended, and on plant species-specific responses, would be needed to customise microbial inoculants for maximum benefits to ecological restoration, to support future adoption of this practice

Medication Management Performance in Parkinson's Disease: Examination of Process Errors

OBJECTIVE: Individuals with Parkinson's disease (PD) are at risk for increased medication mismanagement, which can lead to worse clinical outcomes. However, the nature of the errors (i.e., undertaking or overtaking medications) contributing to mismanagement and their relationship to cognition in PD is unknown. Therefore, this study sought to examine errors committed on the Medication Management Ability Assessment (MMAA) between PD participants with normal cognition (PD-NC) or mild cognitive impairment (PD-MCI) relative to healthy adults (HA). METHOD: HA (n = 74), PD-NC (n = 102), and PD-MCI (n = 45) participants were administered the MMAA to assess undertaking, overtaking, and overall errors as well as overall performance (total score). Additionally, participants were administered a comprehensive neuropsychological battery from which cognitive composites of Attention, Learning, Memory, Language, Visuospatial, and Executive Functioning were derived. RESULTS: Separate negative binomial regression analyses indicated the PD-MCI group performed significantly worse overall on the MMAA (total score) and committed more undertaking and overall errors relative to HA and PD-NC. In the PD-MCI group, poorer MMAA performance was associated with worse delayed memory performance, whereas cognitive performance was not related to MMAA in HA or PC-NC. CONCLUSION: Compared to PD and healthy adults with normal cognition, PD-MCI patients exhibited greater difficulty with medication management, particularly with undertaking medications. Poorer medication management in PD-MCI was associated with worse delayed recall. Thus, PD-MCI patients experiencing memory problems may require additional assistance with their medications. Findings have clinical relevance suggesting that objective measures of medication errors may assist clinicians in identifying PD patients needing adherence strategies. Published by Oxford University Press 2021.Public domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]