NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. METHODS: A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. RESULTS: Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. CONCLUSIONS: Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database

KG-Hub-building and exchanging biological knowledge graphs.

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification. AVAILABILITY AND IMPLEMENTATION: https://kghub.org

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app

Characterizing Long COVID: Deep Phenotype of a Complex Condition.

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

Is detection of enteropathogens and human or animal faecal markers in the environment associated with subsequent child enteric infections and growth: an individual participant data meta-analysis.

BACKGROUND: Quantifying contributions of environmental faecal contamination to child diarrhoea and growth faltering can illuminate causal mechanisms behind modest health benefits in recent water, sanitation, and hygiene (WASH) trials. We aimed to assess associations between environmental detection of enteropathogens and human or animal microbial source tracking markers (MSTM) and subsequent child health outcomes. METHODS: In this individual participant data meta-analysis we searched we searched PubMed, Embase, CAB Direct Global Health, Agricultural and Environmental Science Database, Web of Science, and Scopus for WASH intervention studies with a prospective design and concurrent control that measured enteropathogens or MSTM in environmental samples, or both, and subsequently measured enteric infections, diarrhoea, or height-for-age Z-scores (HAZ) in children younger than 5 years. We excluded studies that only measured faecal indicator bacteria. The initial search was done on Jan 19, 2021, and updated on March 22, 2023. One reviewer (AM) screened abstracts, and two independent reviewers (AM and RT) examined the full texts of short-listed articles. All included studies include at least one author that also contributed as an author to the present Article. Our primary outcomes were the 7-day prevalence of caregiver-reported diarrhoea and HAZ in children. For specific enteropathogens in the environment, primary outcomes also included subsequent child infection with the same pathogen ascertained by stool testing. We estimated associations using covariate-adjusted regressions and pooled estimates across studies. FINDINGS: Data from nine published reports from five interventions studies, which included 8603 children (4302 girls and 4301 boys), were included in the meta-analysis. Environmental pathogen detection was associated with increased infection prevalence with the same pathogen and lower HAZ (ΔHAZ -0·09 [95% CI -0·17 to -0·01]) but not diarrhoea (prevalence ratio 1·22 [95% CI 0·95 to 1·58]), except during wet seasons. Detection of MSTM was not associated with diarrhoea (no pooled estimate) or HAZ (ΔHAZ -0·01 [-0·13 to 0·11] for human markers and ΔHAZ -0·02 [-0·24 to 0·21] for animal markers). Soil, children's hands, and stored drinking water were major transmission pathways. INTERPRETATION: Our findings support a causal chain from pathogens in the environment to infection to growth faltering, indicating that the lack of WASH intervention effects on child growth might stem from insufficient reductions in environmental pathogen prevalence. Studies measuring enteropathogens in the environment should subsequently measure the same pathogens in stool to further examine theories of change between WASH, faecal contamination, and health. Given that environmental pathogen detection was predictive of infection, programmes targeting specific pathogens (eg, vaccinations and elimination efforts) can environmentally monitor the pathogens of interest for population-level surveillance instead of collecting individual biospecimens. FUNDING: The Bill & Melinda Gates Foundation and the UK Foreign and Commonwealth Development Office

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Protein Kinase A Governs Oxidative Phosphorylation Kinetics and Oxidant Emitting Potential at Complex I

he mitochondrial electron transport system (ETS) is responsible for setting andmaintaining both the energy and redox charges throughout the cell. Reversiblephosphorylation of mitochondrial proteins, particularly via the soluble adenylyl cyclase(sAC)/cyclic AMP (cAMP)/Protein kinase A (PKA) axis, has recently been revealed asa potential mechanism regulating the ETS. However, the governance of cAMP/PKAsignaling and its implications on ETS function are incompletely understood. In contrastto prior reports using exogenous bicarbonate, we provide evidence that endogenousCO2 produced by increased tricarboxylic acid (TCA) cycle flux is insufficient to increasemitochondrial cAMP levels, and that exogenous addition of membrane permeant8Br-cAMP does not enhance mitochondrial respiratory capacity. We also reportimportant non-specific effects of commonly used inhibitors of sAC which preclude theiruse in studies of mitochondrial function. In isolated liver mitochondria, inhibition of PKAreduced complex I-, but not complex II-supported respiratory capacity. In permeabilizedmyofibers, inhibition of PKA lowered both the Km and Vmax for complex I-supportedrespiration as well as succinate-supported H2O2 emitting potential. In summary, thedata provided here improve our understanding of how mitochondrial cAMP productionis regulated, illustrate a need for better tools to examine the impact of sAC activityon mitochondrial biology, and suggest that cAMP/PKA signaling contributes to thegovernance of electron flow through complex I of the ETS

Multiple major morbidities and increased mortality during long-term follow-up after recovery from thrombotic thrombocytopenic purpura

Recovery from acute episodes of thrombotic thrombocytopenic purpura (TTP) appears complete except for minor cognitive abnormalities and risk for relapse. The Oklahoma TTP-HUS (hemolytic uremic syndrome) Registry enrolled 70 consecutive patients from 1995 to 2011 with ADAMTS13 activity <10% at their initial episode; 57 survived, with follow-up through 2012. The prevalence of body mass index (BMI), glomerular filtration rate (GFR), urine albumin/creatinine ratio (ACR), hypertension, major depression, systemic lupus erythematosus (SLE), and risk of death were compared with expected values based on the US reference population. At initial diagnosis, 57 survivors had a median age of 39 years; 45 (79%) were women; 21 (37%) were black; BMI and prevalence of SLE (7%) were greater (P < .001) than expected; prevalence of hypertension (19%; P = .463) was not different. GFR (P = .397) and ACR (P = .793) were not different from expected values. In 2011-2012, prevalence of hypertension (40% vs 23%; P = .013) and major depression (19% vs 6%; P = .005) was greater than expected values. Eleven patients (19%) have died, a proportion greater than expected compared with US and Oklahoma reference populations (P < .05). TTP survivors may have greater risk for poor health and premature death