Using ice core measurements from Taylor Glacier, Antarctica, to calibrate in situ cosmogenic 14 C production rates by muons

Cosmic rays entering the Earth’s atmosphere produce showers of secondary particles such as protons, neutrons, and muons. The interaction of these particles with oxygen-16 (16O) in minerals such as ice and quartz can produce carbon-14 (14C). In glacial ice, 14C is also incorporated through trapping of 14C-containing atmospheric gases (14CO2, 14CO, and 14CH4). Understanding the production rates of in situ cosmogenic 14C is important to deconvolve the in situ cosmogenic and atmospheric 14C signals in ice, both of which contain valuable paleoenvironmental information. Unfortunately, the in situ 14C production rates by muons (which are the dominant production mechanism at depths of > 6m solid ice equivalent) are uncertain. In this study, we use measurements of in situ 14C in ancient ice (> 50 ka) from the Taylor Glacier, an ablation site in Antarctica, in combination with a 2D ice flow model to better constrain the compound-specific rates of 14C production by muons and the partitioning of in situ 14C between CO2, CO, and CH4. Our measurements show that 33.7% (11.4%; 95% confidence interval) of the produced cosmogenic 14C forms 14CO and 66.1% (11.5%; 95% confidence interval) of the produced cosmogenic 14C forms 14CO2. 14CH4 represents a very small fraction (< 0.3%) of the total. Assuming that the majority of in situ muogenic 14C in ice forms 14CO2, 14CO, and 14CH4, we also calculated muogenic 14C production rates that are lower by factors of 5.7 (3.6–13.9; 95% confidence interval) and 3.7 (2.0–11.9; 95% confidence interval) for negative muon capture and fast muon interactions, respectively, when compared to values determined in quartz from laboratory studies (Heisinger et al., 2002a, b) and in a natural setting (Lupker et al., 2015). This apparent discrepancy in muogenic 14C production rates in ice and quartz currently lacks a good explanation and requires further investigation

Spatial pattern of accumulation at Taylor Dome during Marine Isotope Stage 4: stratigraphic constraints from Taylor Glacier

New ice cores retrieved from the Taylor Glacier (Antarctica) blue ice area contain ice and air spanning the Marine Isotope Stage (MIS) 5–4 transition, a period of global cooling and ice sheet expansion. We determine chronologies for the ice and air bubbles in the new ice cores by visually matching variations in gas- and ice-phase tracers to preexisting ice core records. The chronologies reveal an ice age–gas age difference (Δage) approaching 10 ka during MIS 4, implying very low snow accumulation in the Taylor Glacier accumulation zone. A revised chronology for the analogous section of the Taylor Dome ice core (84 to 55 ka), located to the south of the Taylor Glacier accumulation zone, shows that Δage did not exceed 3 ka. The difference in Δage between the two records during MIS 4 is similar in magnitude but opposite in direction to what is observed at the Last Glacial Maximum. This relationship implies that a spatial gradient in snow accumulation existed across the Taylor Dome region during MIS 4 that was oriented in the opposite direction of the accumulation gradient during the Last Glacial Maximum

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year