SARS-CoV-2 spike D614G change enhances replication and transmission.

During the evolution of SARS-CoV-2 in humans, a D614G substitution in the spike glycoprotein (S) has emerged; virus containing this substitution has become the predominant circulating variant in the COVID-19 pandemic1. However, whether the increasing prevalence of this variant reflects a fitness advantage that improves replication and/or transmission in humans or is merely due to founder effects remains unknown. Here we use isogenic SARS-CoV-2 variants to demonstrate that the variant that contains S(D614G) has enhanced binding to the human cell-surface receptor angiotensin-converting enzyme 2 (ACE2), increased replication in primary human bronchial and nasal airway epithelial cultures as well as in a human ACE2 knock-in mouse model, and markedly increased replication and transmissibility in hamster and ferret models of SARS-CoV-2 infection. Our data show that the D614G substitution in S results in subtle increases in binding and replication in vitro, and provides a real competitive advantage in vivo-particularly during the transmission bottleneck. Our data therefore provide an explanation for the global predominance of the variant that contains S(D614G) among the SARS-CoV-2 viruses that are currently circulating.

Declining autozygosity over time: An exploration in over 1 million individuals from three diverse cohorts.

Previous studies have hypothesized that autozygosity is decreasing over generational time. However, these studies were limited to relatively small samples (n < 11,000) lacking in diversity, which may limit the generalizability of their findings. We present data that partially support this hypothesis from three large cohorts of diverse ancestries, two from the US (All of Us, n = 82,474; the Million Veteran Program, n = 622,497) and one from the UK (UK Biobank, n = 380,899). Our results from a mixed-effect meta-analysis demonstrate an overall trend of decreasing autozygosity over generational time (meta-analyzed slope = -0.029, SE = 0.009, p = 6.03e-4). On the basis of our estimates, we would predict FROH to decline 0.29% for every 20-year increase in birth year. We determined that a model including an ancestry-by-country interaction term fit the data best, indicating that ancestry differences in this trend differ by country. We found further evidence to suggest a difference between the US and UK cohorts by meta-analyzing within country, observing a significant negative estimate in the US cohorts (meta-analyzed slope = -0.058, SE = 0.015, p = 1.50e-4) but a non-significant estimate in the UK (meta-analyzed slope = -0.001, SE = 0.008, p = 0.945). The association between autozygosity and birth year was substantially attenuated when accounting for educational attainment and income (meta-analyzed slope = -0.011, SE = 0.008, p = 0.167), suggesting they may partially account for decreasing autozygosity over time. Overall, we demonstrate decreasing autozygosity over time in a large, modern sample and speculate that this trend can be attributed to increases in urbanization and panmixia and differences in sociodemographic processes lead to country-specific differences in the rate of decline.

Decoy exosomes provide protection against bacterial toxins.

The production of pore-forming toxins that disrupt the plasma membrane of host cells is a common virulence strategy for bacterial pathogens such as methicillin-resistant Staphylococcus aureus (MRSA)1-3. It is unclear, however, whether host species possess innate immune mechanisms that can neutralize pore-forming toxins during infection. We previously showed that the autophagy protein ATG16L1 is necessary for protection against MRSA strains encoding α-toxin4-a pore-forming toxin that binds the metalloprotease ADAM10 on the surface of a broad range of target cells and tissues2,5,6. Autophagy typically involves the targeting of cytosolic material to the lysosome for degradation. Here we demonstrate that ATG16L1 and other ATG proteins mediate protection against α-toxin through the release of ADAM10 on exosomes-extracellular vesicles of endosomal origin. Bacterial DNA and CpG DNA induce the secretion of ADAM10-bearing exosomes from human cells as well as in mice. Transferred exosomes protect host cells in vitro by serving as scavengers that can bind multiple toxins, and improve the survival of mice infected with MRSA in vivo. These findings indicate that ATG proteins mediate a previously unknown form of defence in response to infection, facilitating the release of exosomes that serve as decoys for bacterially produced toxins.

Genomic partitioning of inbreeding depression in humans.

Across species, offspring of related individuals often exhibit significant reduction in fitness-related traits, known as inbreeding depression (ID), yet the genetic and molecular basis for ID remains elusive. Here, we develop a method to quantify enrichment of ID within specific genomic annotations and apply it to human data. We analyzed the phenomes and genomes of ∼350,000 unrelated participants of the UK Biobank and found, on average of over 11 traits, significant enrichment of ID within genomic regions with high recombination rates (>21-fold; p < 10-5), with conserved function across species (>19-fold; p < 10-4), and within regulatory elements such as DNase I hypersensitive sites (∼5-fold; p = 8.9 × 10-7). We also quantified enrichment of ID within trait-associated regions and found suggestive evidence that genomic regions contributing to additive genetic variance in the population are enriched for ID signal. We find strong correlations between functional enrichment of SNP-based heritability and that of ID (r = 0.8, standard error: 0.1). These findings provide empirical evidence that ID is most likely due to many partially recessive deleterious alleles in low linkage disequilibrium regions of the genome. Our study suggests that functional characterization of ID may further elucidate the genetic architectures and biological mechanisms underlying complex traits and diseases.

Characterization of the In Vivo Deuteration of Native Phospholipids by Mass Spectrometry Yields Guidelines for Their Regiospecific Customization.

Customization of deuterated biomolecules is vital for many advanced biological experiments including neutron scattering. However, because it is challenging to control the proportion and regiospecificity of deuterium incorporation in live systems, often only two or three synthetic lipids are mixed together to form simplistic model membranes. This limits the applicability and biological accuracy of the results generated with these synthetic membranes. Despite some limited prior examination of deuterating Escherichia coli lipids in vivo, this approach has not been widely implemented. Here, an extensive mass spectrometry-based profiling of E. coli phospholipid deuteration states with several different growth media was performed, and a computational method to describe deuterium distributions with a one-number summary is introduced. The deuteration states of 36 lipid species were quantitatively profiled in 15 different growth conditions, and tandem mass spectrometry was used to reveal deuterium localization. Regressions were employed to enable the prediction of lipid deuteration for untested conditions. Small-angle neutron scattering was performed on select deuterated lipid samples, which validated the deuteration states calculated from the mass spectral data. Based on these experiments, guidelines for the design of specifically deuterated phospholipids are described. This unlocks even greater capabilities from neutron-based techniques, enabling experiments that were formerly impossible.

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients.

Capabilities in continuous monitoring of key physiological parameters of disease have never been more important than in the context of the global COVID-19 pandemic. Soft, skin-mounted electronics that incorporate high-bandwidth, miniaturized motion sensors enable digital, wireless measurements of mechanoacoustic (MA) signatures of both core vital signs (heart rate, respiratory rate, and temperature) and underexplored biomarkers (coughing count) with high fidelity and immunity to ambient noises. This paper summarizes an effort that integrates such MA sensors with a cloud data infrastructure and a set of analytics approaches based on digital filtering and convolutional neural networks for monitoring of COVID-19 infections in sick and healthy individuals in the hospital and the home. Unique features are in quantitative measurements of coughing and other vocal events, as indicators of both disease and infectiousness. Systematic imaging studies demonstrate correlations between the time and intensity of coughing, speaking, and laughing and the total droplet production, as an approximate indicator of the probability for disease spread. The sensors, deployed on COVID-19 patients along with healthy controls in both inpatient and home settings, record coughing frequency and intensity continuously, along with a collection of other biometrics. The results indicate a decaying trend of coughing frequency and intensity through the course of disease recovery, but with wide variations across patient populations. The methodology creates opportunities to study patterns in biometrics across individuals and among different demographic groups.

Manipulating Fermentation Pathways in the Hyperthermophilic Archaeon Pyrococcus furiosus for Ethanol Production up to 95°C Driven by Carbon Monoxide Oxidation.

Genetic engineering of hyperthermophilic organisms for the production of fuels and other useful chemicals is an emerging biotechnological opportunity. In particular, for volatile organic compounds such as ethanol, fermentation at high temperatures could allow for straightforward separation by direct distillation. Currently, the upper growth temperature limit for native ethanol producers is 72°C in the bacterium Thermoanaerobacter ethanolicus JW200, and the highest temperature for heterologously-engineered bioethanol production was recently demonstrated at 85°C in the archaeon Pyrococcus furiosus. Here, we describe an engineered strain of P. furiosus that synthesizes ethanol at 95°C, utilizing a homologously-expressed native alcohol dehydrogenase, termed AdhF. Ethanol biosynthesis was compared at 75°C and 95°C with various engineered strains. At lower temperatures, the acetaldehyde substrate for AdhF is most likely produced from acetate by aldehyde ferredoxin oxidoreductase (AOR). At higher temperatures, the effect of AOR on ethanol production is negligible, suggesting that acetaldehyde is produced by pyruvate ferredoxin oxidoreductase (POR) via oxidative decarboxylation of pyruvate, a reaction known to occur only at higher temperatures. Heterologous expression of a carbon monoxide dehydrogenase complex in the AdhF overexpression strain enabled it to use CO as a source of energy, leading to increased ethanol production. A genome reconstruction model for P. furiosus was developed to guide metabolic engineering strategies and understand outcomes. This work opens the door to the potential for 'bioreactive distillation' since fermentation can be performed well above the normal boiling point of ethanol. IMPORTANCE Previously, the highest temperature for biological ethanol production was 85°C. Here, we have engineered ethanol production at 95°C by the hyperthermophilic archaeon Pyrococcus furiosus. Using mutant strains, we showed that ethanol production occurs by different pathways at 75°C and 95°C. In addition, by heterologous expression of a carbon monoxide dehydrogenase complex, ethanol production by this organism was driven by the oxidation of carbon monoxide. A genome reconstruction model for P. furiosus was developed to guide metabolic engineering strategies and understand outcomes.

Predicting causal genes from psychiatric genome-wide association studies using high-level etiological knowledge.

Genome-wide association studies have discovered hundreds of genomic loci associated with psychiatric traits, but the causal genes underlying these associations are often unclear, a research gap that has hindered clinical translation. Here, we present a Psychiatric Omnilocus Prioritization Score (PsyOPS) derived from just three binary features encapsulating high-level assumptions about psychiatric disease etiology - namely, that causal psychiatric disease genes are likely to be mutationally constrained, be specifically expressed in the brain, and overlap with known neurodevelopmental disease genes. To our knowledge, PsyOPS is the first method specifically tailored to prioritizing causal genes at psychiatric GWAS loci. We show that, despite its extreme simplicity, PsyOPS achieves state-of-the-art performance at this task, comparable to a prior domain-agnostic approach relying on tens of thousands of features. Genes prioritized by PsyOPS are substantially more likely than other genes at the same loci to have convergent evidence of direct regulation by the GWAS variant according to both DNA looping assays and expression or splicing quantitative trait locus (QTL) maps. We provide examples of genes hundreds of kilobases away from the lead variant, like GABBR1 for schizophrenia, that are prioritized by all three of PsyOPS, DNA looping and QTLs. Our results underscore the power of incorporating high-level knowledge of trait etiology into causal gene prediction at GWAS loci, and comprise a resource for researchers interested in experimentally characterizing psychiatric gene candidates.

Disentangling the influences of parental genetics on offspring's cognition, education, and psychopathology via genetic and phenotypic pathways.

BACKGROUND: Specific pathways of intergenerational transmission of behavioral traits remain unclear. Here, we aim to investigate how parental genetics influence offspring cognition, educational attainment, and psychopathology in youth. METHODS: Participants for the discovery sample were 2,189 offspring (aged 6-14 years), 1898 mothers and 1,017 fathers who underwent genotyping, psychiatric, and cognitive assessments. We calculated polygenic scores (PGS) for cognition, educational attainment, attention-deficit hyperactivity disorder (ADHD), and schizophrenia for the trios. Phenotypes studied included educational and cognitive measures, ADHD and psychotic symptoms. We used a stepwise approach and multiple mediation models to analyze the effect of parental PGS on offspring traits via offspring PGS and parental phenotype. Significant results were replicated in a sample of 1,029 adolescents, 363 mothers, and 307 fathers. RESULTS: Maternal and paternal PGS for cognition influenced offspring general intelligence and executive function via offspring PGS (genetic pathway) and parental education (phenotypic pathway). Similar results were found for parental PGS for educational attainment and offspring reading and writing skills. These pathways fully explained associations between parental PGS and offspring phenotypes, without residual direct association. Associations with maternal, but not paternal, PGS were replicated. No associations were found between parental PGS for psychopathology and offspring specific symptoms. CONCLUSIONS: Our findings indicate that parental genetics influences offspring cognition and educational attainment by genetic and phenotypic pathways, suggesting the expression of parental phenotypes partially explain the association between parental genetic risk and offspring outcomes. Multiple mediations might represent an effective approach to disentangle distinct pathways for intergenerational transmission of behavioral traits.

Catastrophic Health Care Expenditure Following Brachial Plexus Injury.

PURPOSE: Brachial plexus injuries (BPIs) are devastating to patients not only functionally but also financially. Like patients experiencing other traumatic injuries and unexpected medical events, patients with BPIs are at risk of catastrophic health expenditure (CHE) in which out-of-pocket health spending exceeds 40% of postsubsistence income (income remaining after food and housing expenses). The individual financial strain after BPIs has not been previously quantified. The purpose of this study was to assess the proportion of patients with BPIs who experience risk of CHE after reconstructive surgery. METHODS: Administrative databases were used from 8 states to identify patients who underwent surgery for BPIs. Demographics including age, sex, race, and insurance payer type were obtained. Inpatient billing records were used to determine the total surgical and inpatient facility costs within 90 days after the initial surgery. Due to data constraints, further analysis was only conducted for privately-insured patients. The proportion of patients with BPIs at risk of CHE was recorded. Predictors of CHE risk were determined from a multivariable regression analysis. RESULTS: Among 681 privately-insured patients undergoing surgery for BPIs, nearly one-third (216 [32%]) were at risk of CHE. Black race and patients aged between 25 and 39 years were significant risk factors associated with CHE. Sex and the number of comorbidities were not associated with risk of CHE. CONCLUSIONS: Nearly one-third of privately-insured patients met the threshold for being at risk of CHE after BPI surgery. CLINICAL RELEVANCE: Identifying those patients at risk of CHE can inform strategies to minimize long-term financial distress after BPIs, including detailed counseling regarding anticipated health care expenditures and efforts to optimize access to appropriate insurance policies for patients with BPIs.

The challenges of sociogenomics make it more, not less, worthy of careful and innovative investigation.

Influences on social traits involve a tangled interplay of genetic, social, and environmental factors. Moreover, there is increasing awareness that gene-environment correlations are real and potentially measurable. Such gene-environment correlations can mislead if they are uncontrolled and genetic associations are interpreted as being purely because of direct genetic effects. This complexity is cause for more and better investigation, not a reason to refrain from researching one of the potentially important factors (genetics) influencing trait variation.

Association of Adverse Events With Antibiotic Treatment for Urinary Tract Infection.

BACKGROUND: Little is known about the relative harms of different antibiotic regimens prescribed to treat uncomplicated urinary tract infection (UTI). We sought to compare the risk of adverse events associated with commonly used oral antibiotic regimens for the outpatient treatment of uncomplicated UTI. METHODS: Using data from the IBM® MarketScan® Commercial Database, we identified 1 169 033 otherwise healthy, nonpregnant women aged 18-44 years with uncomplicated UTI who initiated an oral antibiotic with activity against common uropathogens from 1 July 2006 to 30 September 2015. We used propensity score-weighted Kaplan-Meier methods and Cox proportional hazards regression models to estimate the association between antibiotic agent and adverse events. RESULTS: Of 2 first-line agents, trimethoprim-sulfamethoxazole (vs nitrofurantoin) was associated with higher risk of several adverse drug events including hypersensitivity reaction (hazard ratio, 2.62; 95% confidence interval, 2.30-2.98), acute renal failure (2.56; 1.55-4.25), skin rash (2.42; 2.13-2.75), urticaria (1.37; 1.19-1.57), abdominal pain (1.14; 1.09-1.19), and nausea/vomiting (1.18; 1.10-1.28), but a similar risk of potential microbiome-related adverse events. Compared with nitrofurantoin, non-first-line agents were associated with higher risk of several adverse drug events and potential microbiome-related adverse events including non-Clostridium difficile diarrhea, C. difficile infection, vaginitis/vulvovaginal candidiasis, and pneumonia. Treatment duration modified the risk of potential microbiome-related adverse events. CONCLUSIONS: The risks of adverse drug events and potential microbiome-related events differ widely by antibiotic agent and duration. These findings underscore the utility of using real-world data to fill evidentiary gaps related to antibiotic safety.

SARS-CoV-2 Delta-Omicron Recombinant Viruses, United States.

To detect new and changing SARS-CoV-2 variants, we investigated candidate Delta-Omicron recombinant genomes from Centers for Disease Control and Prevention national genomic surveillance. Laboratory and bioinformatic investigations identified and validated 9 genetically related SARS-CoV-2 viruses with a hybrid Delta-Omicron spike protein.

Novel approach for parallelizing pairwise comparison problems as applied to detecting segments identical by decent in whole-genome data.

MOTIVATION: Pairwise comparison problems arise in many areas of science. In genomics, datasets are already large and getting larger, and so operations that require pairwise comparisons-either on pairs of SNPs or pairs of individuals-are extremely computationally challenging. We propose a generic algorithm for addressing pairwise comparison problems that breaks a large problem (of order n2 comparisons) into multiple smaller ones (each of order n comparisons), allowing for massive parallelization. RESULTS: We demonstrated that this approach is very efficient for calling identical by descent (IBD) segments between all pairs of individuals in the UK Biobank dataset, with a 250-fold savings in time and 750-fold savings in memory over the standard approach to detecting such segments across the full dataset. This efficiency should extend to other methods of IBD calling and, more generally, to other pairwise comparison tasks in genomics or other areas of science. AVAILABILITY AND IMPLEMENTATION: A GitHub page is available at https://github.com/emmanuelsapin with the code to generate data needed for the implementation.

Exploring the Relationships Between Autozygosity, Educational Attainment, and Cognitive Ability in a Contemporary, Trans-Ancestral American Sample.

Previous studies have found significant associations between estimated autozygosity - the proportion of an individual's genome contained in homozygous segments due to distant inbreeding - and multiple traits, including educational attainment (EA) and cognitive ability. In one study, estimated autozygosity showed a stronger association with parental EA than the subject's own EA. This was likely driven by parental EA's association with mobility: more educated parents tended to migrate further from their hometown, and because of the strong correlation between ancestry and geography in the Netherlands, these individuals chose partners farther from their ancestry and therefore more different from them genetically. We examined the associations between estimated autozygosity, cognitive ability, and parental EA in a contemporary sub-sample of adolescents from the Adolescent Brain Cognitive Development Study℠ (ABCD Study®) (analytic N = 6,504). We found a negative association between autozygosity and child cognitive ability consistent with previous studies, while the associations between autozygosity and parental EA were in the expected direction of effect (with greater levels of autozygosity being associated with lower EA) but the effect sizes were significantly weaker than those estimated in previous work. We also found a lower mean level of autozygosity in the ABCD sample compared to previous autozygosity studies, which may reflect overall decreasing levels of autozygosity over generations. Variation in spousal similarities in ancestral background in the ABCD study compared to other studies may explain the pattern of associations between estimated autozygosity, EA, and cognitive ability in the current study.

The estimation of environmental and genetic parental influences.

Parents share half of their genes with their children, but they also share background social factors and actively help shape their child's environment - making it difficult to disentangle genetic and environmental causes of parent-offspring similarity. While adoption and extended twin family designs have been extremely useful for distinguishing genetic and nongenetic parental influences, these designs entail stringent assumptions about phenotypic similarity between relatives and require samples that are difficult to collect and therefore are typically small and not publicly shared. Here, we describe these traditional designs, as well as modern approaches that use large, publicly available genome-wide data sets to estimate parental effects. We focus in particular on an approach we recently developed, structural equation modeling (SEM)-polygenic score (PGS), that instantiates the logic of modern PGS-based methods within the flexible SEM framework used in traditional designs. Genetically informative designs such as SEM-PGS rely on different and, in some cases, less rigid assumptions than traditional approaches; thus, they allow researchers to capitalize on new data sources and answer questions that could not previously be investigated. We believe that SEM-PGS and similar approaches can lead to improved insight into how nature and nurture combine to create the incredible diversity underlying human behavior.

Equal incidence of COVID-19 among homeless and non-homeless ED patients when controlling for confounders.

INTRODUCTION: The World Health Organization (WHO) declared severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a pandemic in March 2020. Theoretically, homeless patients could have disproportionately worse outcomes from COVID-19, but little research has corroborated this claim. This study aimed to examine the demographics and incidence of COVID-19 in homeless vs non-homeless emergency department (ED) patients. METHODS: This is a retrospective study of all patients seen in the University of Louisville Hospital Emergency Department (ULH ED) from March 2019 to December 2020, excluding January and February 2020. Data was collected from the Kentucky Homeless Management Information System (HMIS) and ULH electronic health records. RESULTS: A total of 51,532 unique patients had 87,869 visits during the study period. There was a 18.1% decrease in homeless patient visits over the time period, which was similar to the decrease in non-homeless patient visits (19.2%). In the total population, 9471 individuals had known COVID-19 testing results, with a total of 610 positive (6.4% positivity rate). Of the 712 homeless ED patients, 39 tested positive (5.5% positivity rate). After adjusting for age, gender identity, race, and insurance, there was no statistically significant difference in test positivity between homeless and non-homeless patients, OR 1.23 (0.88, 1.73). Homeless patients were less likely to be admitted to either the intensive care unit (ICU) or hospital (OR = 0.55, 95% CI: OR 0.51, 0.60) as they were more likely to be discharged (OR = 1.65, 95% CI: 1.52, 1.79). CONCLUSION: Previous literature has indicated that higher disease burden, lack of access to social distancing, and poor hygiene would increase the risk of homeless individuals contracting COVID-19 and experiencing serious morbidity. However, this study found that homelessness was not an independent risk factor for COVID-19 infection.

Multiplex Real-Time Reverse Transcription PCR for Influenza A Virus, Influenza B Virus, and Severe Acute Respiratory Syndrome Coronavirus 2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019, and the outbreak rapidly evolved into the current coronavirus disease pandemic. SARS-CoV-2 is a respiratory virus that causes symptoms similar to those caused by influenza A and B viruses. On July 2, 2020, the US Food and Drug Administration granted emergency use authorization for in vitro diagnostic use of the Influenza SARS-CoV-2 Multiplex Assay. This assay detects influenza A virus at 102.0, influenza B virus at 102.2, and SARS-CoV-2 at 100.3 50% tissue culture or egg infectious dose, or as few as 5 RNA copies/reaction. The simultaneous detection and differentiation of these 3 major pathogens increases overall testing capacity, conserves resources, identifies co-infections, and enables efficient surveillance of influenza viruses and SARS-CoV-2.

Bias and Precision of Parameter Estimates from Models Using Polygenic Scores to Estimate Environmental and Genetic Parental Influences.

In a companion paper Balbona et al. (Behav Genet, in press), we introduced a series of causal models that use polygenic scores from transmitted and nontransmitted alleles, the offspring trait, and parental traits to estimate the variation due to the environmental influences the parental trait has on the offspring trait (vertical transmission) as well as additive genetic effects. These models also estimate and account for the gene-gene and gene-environment covariation that arises from assortative mating and vertical transmission respectively. In the current study, we simulated polygenic scores and phenotypes of parents and offspring under genetic and vertical transmission scenarios, assuming two types of assortative mating. We instantiated the models from our companion paper in the OpenMx software, and compared the true values of parameters to maximum likelihood estimates from models fitted on the simulated data to quantify the bias and precision of estimates. We show that parameter estimates from these models are unbiased when assumptions are met, but as expected, they are biased to the degree that assumptions are unmet. Standard errors of the estimated variances due to vertical transmission and to genetic effects decrease with increasing sample sizes and with increasing [Formula: see text] values of the polygenic score. Even when the polygenic score explains a modest amount of trait variation ([Formula: see text]), standard errors of these standardized estimates are reasonable ([Formula: see text]) for [Formula: see text] trios, and can even be reasonable for smaller sample sizes (e.g., down to 4K) when the polygenic score is more predictive. These causal models offer a novel approach for understanding how parents influence their offspring, but their use requires polygenic scores on relevant traits that are modestly predictive (e.g., [Formula: see text] as well as datasets with genomic and phenotypic information on parents and offspring. The utility of polygenic scores for elucidating parental influences should thus serve as additional motivation for large genomic biobanks to perform GWAS's on traits that may be relevant to parenting and to oversample close relatives, particularly parents and offspring.