Composition, taxonomy and functional diversity of the oropharynx microbiome in individuals with schizophrenia and controls.

The role of the human microbiome in schizophrenia remains largely unexplored. The microbiome has been shown to alter brain development and modulate behavior and cognition in animals through gut-brain connections, and research in humans suggests that it may be a modulating factor in many disorders. This study reports findings from a shotgun metagenomic analysis of the oropharyngeal microbiome in 16 individuals with schizophrenia and 16 controls. High-level differences were evident at both the phylum and genus levels, with Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria dominating both schizophrenia patients and controls, and Ascomycota being more abundant in schizophrenia patients than controls. Controls were richer in species but less even in their distributions, i.e., dominated by fewer species, as opposed to schizophrenia patients. Lactic acid bacteria were relatively more abundant in schizophrenia, including species of Lactobacilli and Bifidobacterium, which have been shown to modulate chronic inflammation. We also found Eubacterium halii, a lactate-utilizing species. Functionally, the microbiome of schizophrenia patients was characterized by an increased number of metabolic pathways related to metabolite transport systems including siderophores, glutamate, and vitamin B12. In contrast, carbohydrate and lipid pathways and energy metabolism were abundant in controls. These findings suggest that the oropharyngeal microbiome in individuals with schizophrenia is significantly different compared to controls, and that particular microbial species and metabolic pathways differentiate both groups. Confirmation of these findings in larger and more diverse samples, e.g., gut microbiome, will contribute to elucidating potential links between schizophrenia and the human microbiota

Benchmark Evaluation of True Single Molecular Sequencing to Determine Cystic Fibrosis Airway Microbiome Diversity

Cystic fibrosis (CF) is an autosomal recessive disease associated with recurrent lung infections that can lead to morbidity and mortality. The impact of antibiotics for treatment of acute pulmonary exacerbations on the CF airway microbiome remains unclear with prior studies giving conflicting results and being limited by their use of 16S ribosomal RNA sequencing. Our primary objective was to validate the use of true single molecular sequencing (tSMS) and PathoScope in the analysis of the CF airway microbiome. Three control samples were created with differing amounts of Burkholderia cepacia, Pseudomonas aeruginosa, and Prevotella melaninogenica, three common bacteria found in cystic fibrosis lungs. Paired sputa were also obtained from three study participants with CF before and \u3e6 days after initiation of antibiotics. Antibiotic resistant B. cepacia and P. aeruginosa were identified in concurrently obtained respiratory cultures. Direct sequencing was performed using tSMS, and filtered reads were aligned to reference genomes from NCBI using PathoScope and Kraken and unique clade-specific marker genes using MetaPhlAn. A total of 180-518K of 6-12 million filtered reads were aligned for each sample. Detection of known pathogens in control samples was most successful using PathoScope. In the CF sputa, alpha diversity measures varied based on the alignment method used, but similar trends were found between pre- and post-antibiotic samples. PathoScope outperformed Kraken and MetaPhlAn in our validation study of artificial bacterial community controls and also has advantages over Kraken and MetaPhlAn of being able to determine bacterial strains and the presence of fungal organisms. PathoScope can be confidently used when evaluating metagenomic data to determine CF airway microbiome diversity

BMP2 commitment to the osteogenic lineage involves activation of Runx2 by DLX3 and a homeodomain transcriptional network

Several homeodomain (HD) proteins are critical for skeletal patterning and respond directly to BMP2 as an early step in bone formation. RUNX2, the earliest transcription factor proven essential for commitment to osteoblastogenesis, is also expressed in response to BMP2. However, there is a gap in our knowledge of the regulatory cascade from BMP2 signaling to the onset of osteogenesis. Here we show that BMP2 induces DLX3, a homeodomain protein that activates Runx2 gene transcription. Small interfering RNA knockdown studies in osteoblasts validate that DLX3 is a potent regulator of Runx2. Furthermore in Runx2 null cells, DLX3 forced expression suffices to induce transcription of Runx2, osteocalcin, and alkaline phosphatase genes, thus defining DLX3 as an osteogenic regulator independent of RUNX2. Our studies further show regulation of the Runx2 gene by several homeodomain proteins: MSX2 and CDP/cut repress whereas DLX3 and DLX5 activate endogenous Runx2 expression and promoter activity in non-osseous cells and osteoblasts. These HD proteins exhibit distinct temporal expression profiles during osteoblast differentiation as well as selective association with Runx2 chromatin that is related to Runx2 transcriptional activity and recruitment of RNA polymerase II. Runx2 promoter mutagenesis shows that multiple HD elements control expression of Runx2 in relation to the stages of osteoblast maturation. Our studies establish mechanisms for commitment to the osteogenic lineage directly through BMP2 induction of HD proteins DLX3 and DLX5 that activate Runx2, thus delineating a transcriptional regulatory pathway mediating osteoblast differentiation. We propose that the three homeodomain proteins MSX2, DLX3, and DLX5 provide a key series of molecular switches that regulate expression of Runx2 throughout bone formation. <br/

Phylogenetics Applied to Genotype/Phenotype Association and Selection Analyses with Sequence Data from Angptl4 in Humans

Genotype/phenotype association analyses (Treescan) with plasma lipid levels and functional site prediction methods (TreeSAAP and PolyPhen) were performed using sequence data for ANGPTL4 from 3,551 patients in the Dallas Heart Study. Biological assays of rare variants in phenotypic tails and results from a Treescan analysis were used as “known” variants to assess the site prediction abilities of PolyPhen and TreeSAAP. The E40K variant in European Americans and the R278Q variant in African Americans were significantly associated with multiple lipid phenotypes. Combining TreeSAAP and PolyPhen performed well to predict “known” functional variants while reducing noise from false positives

Critical Assessment of Metagenome Interpretation:A benchmark of metagenomics software

International audienceIn metagenome analysis, computational methods for assembly, taxonomic profilingand binning are key components facilitating downstream biological datainterpretation. However, a lack of consensus about benchmarking datasets andevaluation metrics complicates proper performance assessment. The CriticalAssessment of Metagenome Interpretation (CAMI) challenge has engaged the globaldeveloper community to benchmark their programs on datasets of unprecedentedcomplexity and realism. Benchmark metagenomes were generated from newlysequenced ~700 microorganisms and ~600 novel viruses and plasmids, includinggenomes with varying degrees of relatedness to each other and to publicly availableones and representing common experimental setups. Across all datasets, assemblyand genome binning programs performed well for species represented by individualgenomes, while performance was substantially affected by the presence of relatedstrains. Taxonomic profiling and binning programs were proficient at high taxonomicranks, with a notable performance decrease below the family level. Parametersettings substantially impacted performances, underscoring the importance ofprogram reproducibility. While highlighting current challenges in computationalmetagenomics, the CAMI results provide a roadmap for software selection to answerspecific research questions

The Liverpool alcohol-related liver disease algorithm identifies twice as many emergency admissions compared to standard methods when applied to Hospital Episode Statistics for England

BackgroundEmergency admissions in England for alcohol-related liver disease (ArLD) have increased steadily for decades. Statistics based on administrative data typically focus on the ArLD-specific code as the primary diagnosis and are therefore at risk of excluding ArLD admissions defined by other coding combinations.AimTo deploy the Liverpool ArLD Algorithm (LAA), which accounts for alternative coding patterns (e.g., ArLD secondary diagnosis with alcohol/liver-related primary diagnosis), to national and local datasets in the context of studying trends in ArLD admissions before and during the COVID-19 pandemic.MethodsWe applied the standard approach and LAA to Hospital Episode Statistics for England (2013-21). The algorithm was also deployed at 28 hospitals to discharge coding for emergency admissions during a common 7-day period in 2019 and 2020, in which eligible patient records were reviewed manually to verify the diagnosis and extract data.ResultsNationally, LAA identified approximately 100% more monthly emergency admissions from 2013 to 2021 than the standard method. The annual number of ArLD-specific admissions increased by 30.4%. Of 39,667 admissions in 2020/21, only 19,949 were identified with standard approach, an estimated admission cost of £70 million in under-recorded cases. Within 28 local hospital datasets, 233 admissions were identified using the standard approach and a further 250 locally verified cases using the LAA (107% uplift). There was an 18% absolute increase in ArLD admissions in the seven-day evaluation period in 2020 versus 2019. There were no differences in disease severity or mortality, or in the proportion of admissions with decompensation of cirrhosis or alcoholic hepatitis.ConclusionsThe LAA can be applied successfully to local and national datasets. It consistently identifies approximately 100% more cases than the standard coding approach. The algorithm has revealed the true extent of ArLD admissions. The pandemic has compounded a long-term rise in ArLD admissions and mortality

2019 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

The International Liaison Committee on Resuscitation has initiated a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation science. This is the third annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. It addresses the most recent published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. This summary addresses the role of cardiac arrest centers and dispatcher-assisted cardiopulmonary resuscitation, the role of extracorporeal cardiopulmonary resuscitation in adults and children, vasopressors in adults, advanced airway interventions in adults and children, targeted temperature management in children after cardiac arrest, initial oxygen concentration during resuscitation of newborns, and interventions for presyncope by first aid providers. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the certainty of the evidence on the basis of the Grading of Recommendations, Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence to Decision Framework Highlights sections. The task forces also listed priority knowledge gaps for further research

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication