66 research outputs found

    The state of the Martian climate

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    60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

    Genotype, Childhood Maltreatment, and Their Interaction in the Etiology of Adult Antisocial Behaviors

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    BACKGROUND: Maltreatment by an adult or caregiver during childhood is a prevalent and important predictor of antisocial behaviors in adulthood. A functional promoter polymorphism in the monoamine oxidase A (MAOA) gene has been implicated as a moderating factor in the relationship between childhood maltreatment and antisocial behaviors. Although there have been numerous attempts at replicating this observation, results remain inconclusive. METHODS: We examined this gene-environment interaction hypothesis in a sample of 3356 white and 960 black men (aged 24-34) participating in the National Longitudinal Study of Adolescent Health. RESULTS: Primary analysis indicated that childhood maltreatment was a significant risk factor for later behaviors that violate rules and the rights of others (p .05). Power analyses indicated that these results were not due to insufficient statistical power. CONCLUSIONS: We could not confirm the hypothesis that MAOA genotype moderates the relationship between childhood maltreatment and adult antisocial behaviors

    Simple Sequence Repeats in the National Longitudinal Study of Adolescent Health: An Ethnically Diverse Resource for Genetic Analysis of Health and Behavior

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    Simple sequence repeats (SSRs) are one of the earliest available forms of genetic variation available for analysis and have been utilized in studies of neurological, behavioral, and health phenotypes. Although findings from these studies have been suggestive, their interpretation has been complicated by a variety of factors including, among others, limited power due to small sample sizes. The current report details the availability, diversity, and allele and genotype frequencies of six commonly examined SSRs in the ethnically diverse, population-based National Longitudinal Study of Adolescent Health (Add Health). A total of 106,743 genotypes were generated across 15,140 participants that included four microsatellites and two di-nucleotide repeats in three dopamine genes (DAT1, DRD4, DRD5), the serotonin transporter (5HTT), and monoamine oxidase A (MAOA). Allele and genotype frequencies showed a complex pattern and differed significantly between populations. For both di-nucleotide repeats we observed a greater allelic diversity than previously reported. The availability of these six SSRs in a large, ethnically diverse sample with extensive environmental measures assessed longitudinally offers a unique resource for researchers interested in health and behavior

    Population Frequencies of the Triallelic 5HTTLPR in Six Ethnicially Diverse Samples from North America, Southeast Asia, and Africa

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    Genetic differences between populations are a potentially an important contributor to health disparities around the globe. As differences in gene frequencies influence study design, it is important to have a thorough understanding of the natural variation of the genetic variant(s) of interest. Along these lines, we characterized the variation of the 5HTTLPR and rs25531 polymorphisms in six samples from North America, Southeast Asia, and Africa (Cameroon) that differ in their racial and ethnic composition. Allele and genotype frequencies were determined for 24,066 participants. Results indicated higher frequencies of the rs25531 G-allele among Black and African populations as compared with White, Hispanic and Asian populations. Further, we observed a greater number of ‘extra-long’ (‘XL’) 5HTTLPR alleles than have previously been reported. Extra-long alleles occurred almost entirely among Asian, Black and Non-White Hispanic populations as compared with White and Native American populations where they were completely absent. Lastly, when considered jointly, we observed between sample differences in the genotype frequencies within racial and ethnic populations. Taken together, these data underscore the importance of characterizing the L-G allele to avoid misclassification of participants by genotype and for further studies of the impact XL alleles may have on the transcriptional efficiency of SLC6A4

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

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    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

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

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    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.

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    Host-mediated lung inflammation is present,1 and drives mortality,2 in critical illness caused by Covid-19. Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development.3 Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study(GWAS) in 2244 critically ill Covid-19 patients from 208 UK intensive care units (ICUs). We identify and replicate novel genome-wide significant associations, on chr12q24.13 (rs10735079, p=1.65 [Formula: see text] 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), on chr19p13.2 (rs2109069, p=2.3 [Formula: see text] 10-12) near the gene encoding tyrosine kinase 2 (TYK2), on chr19p13.3 (rs2109069, p=3.98 [Formula: see text] 10-12) within the gene encoding dipeptidyl peptidase 9 (DPP9), and on chr21q22.1 (rs2236757, p=4.99 [Formula: see text] 10-8) in the interferon receptor gene IFNAR2. We identify potential targets for repurposing of licensed medications: using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease; 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. Large-scale randomised clinical trials will be essential before any change to clinical practice

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

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    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
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