The P323L substitution in the SARS-CoV-2 polymerase (NSP12) confers a selective advantage during infection

Background The mutational landscape of SARS-CoV-2 varies at the dominant viral genome sequence and minor genomic variant population. During the COVID-19 pandemic, an early substitution in the genome was the D614G change in the spike protein, associated with an increase in transmissibility. Genomes with D614G are accompanied by a P323L substitution in the viral polymerase (NSP12). However, P323L is not thought to be under strong selective pressure. Results Investigation of P323L/D614G substitutions in the population shows rapid emergence during the containment phase and early surge phase during the first wave. These substitutions emerge from minor genomic variants which become dominant viral genome sequence. This is investigated in vivo and in vitro using SARS-CoV-2 with P323 and D614 in the dominant genome sequence and L323 and G614 in the minor variant population. During infection, there is rapid selection of L323 into the dominant viral genome sequence but not G614. Reverse genetics is used to create two viruses (either P323 or L323) with the same genetic background. L323 shows greater abundance of viral RNA and proteins and a smaller plaque morphology than P323. Conclusions These data suggest that P323L is an important contribution in the emergence of variants with transmission advantages. Sequence analysis of viral populations suggests it may be possible to predict the emergence of a new variant based on tracking the frequency of minor variant genomes. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions

Viral coinfections in hospitalized coronavirus disease 2019 patients recruited to the international severe acute respiratory and emerging infections consortium WHO clinical characterisation protocol UK study

Background We conducted this study to assess the prevalence of viral coinfection in a well characterized cohort of hospitalized coronavirus disease 2019 (COVID-19) patients and to investigate the impact of coinfection on disease severity. Methods Multiplex real-time polymerase chain reaction testing for endemic respiratory viruses was performed on upper respiratory tract samples from 1002 patients with COVID-19, aged <1 year to 102 years old, recruited to the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK study. Comprehensive demographic, clinical, and outcome data were collected prospectively up to 28 days post discharge. Results A coinfecting virus was detected in 20 (2.0%) participants. Multivariable analysis revealed no significant risk factors for coinfection, although this may be due to rarity of coinfection. Likewise, ordinal logistic regression analysis did not demonstrate a significant association between coinfection and increased disease severity. Conclusions Viral coinfection was rare among hospitalized COVID-19 patients in the United Kingdom during the first 18 months of the pandemic. With unbiased prospective sampling, we found no evidence of an association between viral coinfection and disease severity. Public health interventions disrupted normal seasonal transmission of respiratory viruses; relaxation of these measures mean it will be important to monitor the prevalence and impact of respiratory viral coinfections going forward

Stellar velocity dispersions and emission line properties of SDSS-III/BOSS galaxies

AbstractWe perform a spectroscopic analysis of 492,450 galaxy spectra from the first two years of observations of the Sloan Digital Sky Survey-III/Baryonic Oscillation Spectroscopic Survey (BOSS) collaboration. This data set has been released in the ninth SDSS data release, the first public data release of BOSS spectra. We show that the typical signal-to-noise ratio of BOSS spectra is sufficient to measure stellar velocity dispersion and emission line fluxes for individual objects. The typical velocity dispersion of a BOSS galaxy is 240 km/s, with an accuracy of better than 30 per cent for 93 per cent of BOSS galaxies. The distribution in velocity dispersion is redshift independent between redshifts 0.15 and 0.7, which reflects the survey design targeting massive galaxies with an approximately uniform mass distribution in this redshift interval. The majority of BOSS galaxies lack detectable emission lines. We analyse the emission line properties and present diagnostic diagrams using the emission lines [OII], Hβ, [OIII], Halpha, and [NII] (detected in about 4 per cent of the galaxies). We show that the emission line properties are strongly redshift dependent and that there is a clear correlation between observed frame colours and emission line properties. Within in the low-z sample around 0.15 &lt; z &lt; 0.3, half of the emission-line galaxies have LINER-like emission line ratios, followed by Seyfert-AGN dominated spectra, and only a small fraction of a few per cent are purely star forming galaxies. AGN and LINER-like objects, instead, are less prevalent in the high-z sample around 0.4 &lt; z &lt; 0.7, where more than half of the emission line objects are star forming. This is a pure selection effect caused by the non-detection of weak Hβ emission lines in the BOSS spectra. Finally, we show that star forming, AGN and emission line free galaxies are well separated in the g - r vs r - i target selection diagram.</jats:p

Clinical predictors of influenza in young children:the limitations of “influenza-like illness”

Background Influenza-like illness (ILI) definitions have been infrequently studied in young children. Despite this, clinical definitions of ILI play an important role in influenza surveillance. This study aims to identify clinical predictors of influenza infection in children =5 years old from which age-specific ILI definitions are then constructed.Methods Children aged 6–59 months with a history of fever and acute respiratory symptoms were recruited in the Western Australia Influenza Vaccine Effectiveness (WAIVE) Study. Clinical data and per-nasal specimens were obtained from all children. Logistic regression identified significant predictors of influenza infection. Different ILI definitions were compared for diagnostic accuracy.Results Children were recruited from 2 winter influenza seasons (2008–2009; n = 944). Of 919 eligible children, 179 (19.5%) had laboratory-confirmed influenza infection. Predictors of infection included increasing age, lack of influenza vaccination, lower birth weight, fever, cough, and absence of wheeze. An ILI definition comprising fever =38°C, cough, and no wheeze had 58% sensitivity (95% confidence interval [CI], 50–66), 60% specificity (95% CI, 56–64), 26% positive predictive value (95% CI, 21–31), and 86% negative predictive value (95% CI, 82–89). The addition of other symptoms or higher fever thresholds to ILI definition had little impact. The Centers for Disease Control and Prevention definition of ILI (presence of fever [=37.8°C] and cough and/or sore throat) was sensitive (92%; 95% CI, 86–95), yet lacked specificity (10%; 95% CI, 8–13) in this population.Conclusions Influenza-like illness is a poor predictor of laboratory-confirmed influenza infection in young children but can be improved using age-specific data. Incorporating age-specific ILI definitions and/or diagnostic testing into influenza surveillance systems will improve the accuracy of epidemiological data

Environmental and demographic risk factors for egg allergy in a population-based study of infants

Background Although egg allergy is the most common food allergy in infants and young children, risk factors for egg allergy remain largely unknown. This study examined the relationship between environmental and demographic factors and egg allergy in a population-based infant cohort. Methods In a study of 5276 infants (HealthNuts), infants underwent skin prick testing (SPT) to egg white at 12 months of age. Questionnaire data on relevant exposures were obtained. 699/873 (80%) infants eligible for oral food challenge (detectable wheal on SPT) attended for formal assessment of egg allergy status; 453 had confirmed egg allergy (positive challenge and SPT ≥ 2 mm). Associations between environmental and demographic factors and egg allergy were investigated using multivariable logistic regression. Results Children with older siblings and those with a pet dog at home were less likely to develop egg allergy by 1 year of age (adjusted OR [aOR], 0.72; 95% CI, 0.62, 0.83 per sibling; and aOR, 0.72; 95% CI, 0.52, 0.99, respectively). Caesarean section delivery, antibiotic use in infancy, childcare attendance and maternal age were not associated with egg allergy. History of allergic disease in an immediate family member and having parents born in East Asia were strong risk factors for infantile egg allergy (aOR, 1.82; 95% CI, 1.40, 2.36; and aOR, 3.30; 95% CI, 2.45, 4.45, respectively). Conclusions Exposure in the first year of life to siblings and dogs may decrease the risk of subsequent egg allergy. Infants with a family history of allergy and those with parents born in East Asia are at increased risk of egg allergy. © 2012 John Wiley &amp; Sons A/S

Mapping the human genetic architecture of COVID-19

AbstractThe genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.</jats:p

Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study

AbstractCOVID-19 is clinically characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied clustering techniques to a large prospective cohort of hospitalised patients with COVID-19 to identify clinically meaningful sub-phenotypes. We obtained structured clinical data on 59,011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25,477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33,534 cases recruited to ISARIC-4C, and in 4,445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-phenotypes. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were also identified, alongside a sub-phenotype of patients reporting few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom sub-phenotypes were highly consistent in replication analysis within the ISARIC-4C study. Similar patterns were externally verified in patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four sub-phenotypes are usefully distinct from the core symptom group: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms.</jats:p

Variation in the Plasma Membrane Monoamine Transporter (PMAT) (Encoded by <i>SLC29A4</i>) and Organic Cation Transporter 1 (OCT1) (Encoded by <i>SLC22A1</i>) and Gastrointestinal Intolerance to Metformin in Type 2 Diabetes: An IMI DIRECT Study

OBJECTIVE Gastrointestinal adverse effects occur in 20–30% of patients with metformin-treated type 2 diabetes, leading to premature discontinuation in 5–10% of the cases. Gastrointestinal intolerance may reflect localized high concentrations of metformin in the gut. We hypothesized that reduced transport of metformin via the plasma membrane monoamine transporter (PMAT) and organic cation transporter 1 (OCT1) could increase the risk of severe gastrointestinal adverse effects. RESEARCH DESIGN AND METHODS The study included 286 severe metformin-intolerant and 1,128 metformin-tolerant individuals from the IMI DIRECT (Innovative Medicines Initiative: DIabetes REsearCh on patient straTification) consortium. We assessed the association of patient characteristics, concomitant medication, and the burden of mutations in the SLC29A4 and SLC22A1 genes on odds of intolerance. RESULTS Women (P &amp;lt; 0.001) and older people (P &amp;lt; 0.001) were more likely to develop metformin intolerance. Concomitant use of transporter-inhibiting drugs increased the odds of intolerance (odds ratio [OR] 1.72, P &amp;lt; 0.001). In an adjusted logistic regression model, the G allele at rs3889348 (SLC29A4) was associated with gastrointestinal intolerance (OR 1.34, P = 0.005). rs3889348 is the top cis-expression quantitative trait locus for SLC29A4 in gut tissue where carriers of the G allele had reduced expression. Homozygous carriers of the G allele treated with transporter-inhibiting drugs had more than three times higher odds of intolerance compared with carriers of no G allele and not treated with inhibiting drugs (OR 3.23, P &amp;lt; 0.001). Use of a genetic risk score derived from rs3889348 and SLC22A1 variants found that the odds of intolerance were more than twice as high in individuals who carry three or more risk alleles compared with those carrying none (OR 2.15, P = 0.01). CONCLUSIONS These results suggest that intestinal metformin transporters and concomitant medications play an important role in the gastrointestinal adverse effects of metformin. </jats:sec