The impact of the COVID-19 lockdown on greenhouse gases: a multi-city analysis of in situ atmospheric observations

We tested the capabilities of urban greenhouse gas (GHG) measurement networks to detect abrupt changes in emissions, such as those caused by the roughly 6-week COVID-19 lockdown in March 2020 using hourly in situ GHG mole fraction measurements from six North American cities. We compared observed changes in CO2, CO, and CH4 for different mole fraction metrics (diurnal amplitude, vertical gradients, enhancements, within-hour variances, and multi-gas enhancement ratios) during 2020 relative to previous years for three periods: pre-lockdown, lockdown, and ongoing recovery. The networks showed decreases in CO2 and CO metrics during the lockdown period in all cities for all metrics, while changes in the CH4 metrics were variable across cities and not statistically significant. Traffic decreases in 2020 were correlated with the changes in GHG metrics, whereas changes in meteorology and biology were not, implying that decreases in the CO2 and CO metrics were related to reduced emissions from traffic and demonstrating the sensitivity of these tower networks to rapid changes in urban emissions. The enhancements showed signatures of the lockdowns more consistently than the three micrometeorological methods, possibly because the urban measurements are collected at relatively high altitudes to be sensitive to whole-city emissions. This suggests that urban observatories might benefit from a mixture of measurement altitudes to improve observational network sensitivity to both city-scale and more local fluxes. &nbsp;</p

Targeted copy number variant identification across the neurodegenerative disease spectrum

Background: Although genetic factors are known to contribute to neurodegenerative disease susceptibility, there remains a large amount of heritability unaccounted for across the diagnoses. Copy number variants (CNVs) contribute to these phenotypes, but their presence and influence on disease state remains relatively understudied. Methods: Here, we applied a depth of coverage approach to detect CNVs in 80 genes previously associated with neurodegenerative disease within participants of the Ontario Neurodegenerative Disease Research Initiative (n = 519). Results: In total, we identified and validated four CNVs in the cohort, including: (1) a heterozygous deletion of exon 5 in OPTN in an Alzheimer\u27s disease participant; (2) a duplication of exons 1–5 in PARK7 in an amyotrophic lateral sclerosis participant; (3) a duplication of \u3e3 Mb, which encompassed ABCC6, in a cerebrovascular disease (CVD) participant; and (4) a duplication of exons 7–11 in SAMHD1 in a mild cognitive impairment participant. We also identified 43 additional CNVs that may be candidates for future replication studies. Conclusion: The identification of the CNVs suggests a portion of the apparent missing heritability of the phenotypes may be due to these structural variants, and their assessment is imperative for a thorough understanding of the genetic spectrum of neurodegeneration

A Novel fry1 Allele Reveals the Existence of a Mutant Phenotype Unrelated to 5′->3′ Exoribonuclease (XRN) Activities in Arabidopsis thaliana Roots

International audienceBackgroundMutations in the FRY1/SAL1 Arabidopsis locus are highly pleiotropic, affecting drought tolerance, leaf shape and root growth. FRY1 encodes a nucleotide phosphatase that in vitro has inositol polyphosphate 1-phosphatase and 3′,(2′),5′-bisphosphate nucleotide phosphatase activities. It is not clear which activity mediates each of the diverse biological functions of FRY1 in planta.Principal FindingsA fry1 mutant was identified in a genetic screen for Arabidopsis mutants deregulated in the expression of Pi High affinity Transporter 1;4 (PHT1;4). Histological analysis revealed that, in roots, FRY1 expression was restricted to the stele and meristems. The fry1 mutant displayed an altered root architecture phenotype and an increased drought tolerance. All of the phenotypes analyzed were complemented with the AHL gene encoding a protein that converts 3′-polyadenosine 5′-phosphate (PAP) into AMP and Pi. PAP is known to inhibit exoribonucleases (XRN) in vitro. Accordingly, an xrn triple mutant with mutations in all three XRNs shared the fry1 drought tolerance and root architecture phenotypes. Interestingly these two traits were also complemented by grafting, revealing that drought tolerance was primarily conferred by the rosette and that the root architecture can be complemented by long-distance regulation derived from leaves. By contrast, PHT1 expression was not altered in xrn mutants or in grafting experiments. Thus, PHT1 up-regulation probably resulted from a local depletion of Pi in the fry1 stele. This hypothesis is supported by the identification of other genes modulated by Pi deficiency in the stele, which are found induced in a fry1 background.Conclusions/SignificanceOur results indicate that the 3′,(2′),5′-bisphosphate nucleotide phosphatase activity of FRY1 is involved in long-distance as well as local regulatory activities in roots. The local up-regulation of PHT1 genes transcription in roots likely results from local depletion of Pi and is independent of the XRNs.

A Randomized Trial Examining the Effects of Parent Engagement on Early Language and Literacy: The Getting Ready Intervention

Language and literacy skills established during early childhood are critical for later school success. Parental engagement with children has been linked to a number of adaptive characteristics in preschoolers including language and literacy development, and family-school collaboration is an important contributor to school readiness. This study reports the results of a randomized trial of a parent engagement intervention designed to facilitate school readiness among disadvantaged preschool children, with a particular focus on language and literacy development. Participants included 217 children, 211 parents, and 29 Head Start teachers in 21 schools. Statistically significant differences in favor of the treatment group were observed between treatment and control participants in the rate of change over 2 academic years on teacher reports of children’s language use (d = 1.11), reading (d = 1.25), and writing skills (d = .93). Significant intervention effects on children’s direct measures of expressive language were identified for a subgroup of cases where there were concerns about a child’s development upon entry into preschool. Additionally, other child and family moderators revealed specific variables that influenced the treatment’s effects

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

cited By 0Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies similar to 7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.Peer reviewe

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 hospitalization2–4 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

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352

Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 × 10−8) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for ∼11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction