Hospital trajectories and early predictors of clinical outcomes differ between SARS-CoV-2 and influenza pneumonia.

BACKGROUND: A comparison of pneumonias due to SARS-CoV-2 and influenza, in terms of clinical course and predictors of outcomes, might inform prognosis and resource management. We aimed to compare clinical course and outcome predictors in SARS-CoV-2 and influenza pneumonia using multi-state modelling and supervised machine learning on clinical data among hospitalised patients. METHODS: This multicenter retrospective cohort study of patients hospitalised with SARS-CoV-2 (March-December 2020) or influenza (Jan 2015-March 2020) pneumonia had the composite of hospital mortality and hospice discharge as the primary outcome. Multi-state models compared differences in oxygenation/ventilatory utilisation between pneumonias longitudinally throughout hospitalisation. Differences in predictors of outcome were modelled using supervised machine learning classifiers. FINDINGS: Among 2,529 hospitalisations with SARS-CoV-2 and 2,256 with influenza pneumonia, the primary outcome occurred in 21% and 9%, respectively. Multi-state models differentiated oxygen requirement progression between viruses, with SARS-CoV-2 manifesting rapidly-escalating early hypoxemia. Highly contributory classifier variables for the primary outcome differed substantially between viruses. INTERPRETATION: SARS-CoV-2 and influenza pneumonia differ in presentation, hospital course, and outcome predictors. These pathogen-specific differential responses in viral pneumonias suggest distinct management approaches should be investigated. FUNDING: This project was supported by NIH/NCATS UL1 TR002345, NIH/NCATS KL2 TR002346 (PGL), the Doris Duke Charitable Foundation grant 2015215 (PGL), NIH/NHLBI R35 HL140026 (CSC), and a Big Ideas Award from the BJC HealthCare and Washington University School of Medicine Healthcare Innovation Lab and NIH/NIGMS R35 GM142992 (PS).

Altered Maternal Plasma Glycogen Phosphorylase Isoenzyme BB as a Biomarker for Preeclampsia and Small for Gestational Age.

OBJECTIVES: To investigate whether maternal plasma glycogen phosphorylase BB (GPBB) levels were altered in early pregnancy and/or at the time of diagnosis of disease in preeclampsia (term and preterm <37 weeks' gestation) or small for gestational age (SGA). METHODS: We conducted 6 nested case-control studies within the Screening of Pregnancy Endpoint (SCOPE) Ireland cohort. Blood samples from women with preeclampsia or SGA were analyzed both from the time of disease presentation and at 15 and 20 weeks' gestation. These were compared with control samples obtained from SCOPE women with healthy uncomplicated pregnancies matched for age, ethnicity, parity, body mass index, and gestational age. Glycogen phosphorylase BB levels were measured using the Diacordon GPBB enzyme-linked immunosorbent assay (Diagenics, Germany). RESULTS: Glycogen phosphorylase BB levels were higher in women with preeclampsia compared with controls at the time of disease (term preeclampsia median [interquartile range (IQR)]: 22.2 [15.1-39.8] ng/mL vs 16.9 [10.4-19.1] ng/mL; P = .04; N = 14 and preterm preeclampsia median [IQR]: 23.1 [11.2-30.9] ng/mL vs 17.2 [9.8-19.1] ng/mL; P = .04; N = 11) and at 20 weeks' gestation (median [IQR]: 23.0 [15.6-31.4] ng/mL vs 17.0 [13.4-23.6] ng/mL; N = 39; P = .04). Glycogen phosphorylase BB levels were also significantly higher in women with SGA compared with normal controls at the time of disease detection (median [IQR]: 22.7 [12.6-25.5] ng/mL vs 17.0 [9.8-18.0] ng/mL; N = 23; P = .03) but significantly less than controls at 15 weeks' gestation prior to disease detection (median [IQR]: 16.0 [12.1-23.2] ng/mL vs 22.2 [17.0-28.9] ng/mL; N = 25; P = .02). CONCLUSION: Glycogen phosphorylase BB alone has modest predictive abilities for the development of preeclampsia or SGA. Further research may examine its use in combination with other markers.

Assessment of glycogen phosphorylase isoenzyme BB as a biomarker for pre-eclampsia and small for gestational age.

BACKGROUND: Glycogen phosphorylase is a key enzyme in the regulation of glycogen metabolism and consists of three isoenzymes, including glycogen phosphorylase isoenzyme BB (GPBB). Pre-eclampsia, gestational hypertension, and small-for-gestational-age (SGA) infants are complications in about 15% of all nulliparous pregnancies. Biomarkers for these adverse pregnancy outcomes remain elusive. GPBB has been proposed as a potential biomarker for the detection of these adverse outcomes. We aimed to investigate this hypothesis. METHODS: Blood samples from women with pre-eclampsia or SGA were analysed from the time of disease presentation and from samples collected at 15 and 20 weeks' gestation. They were compared with control samples obtained from women recruited to the Screening for Pregnancy Endpoints (SCOPE) study. These control samples were from healthy women with uncomplicated pregnancies matched for age, ethnicity, parity, body-mass index, and gestational age. GPBB concentrations were measured with ELISA (Diacordon, Diagenics, Essen, Germany). FINDINGS: Significant differences in GPBB were observed between all three gestations (p=0·03). GPBB concentrations were higher in women with pre-eclampsia than in controls at the time of disease presentation (term pre-eclampsia n=14, median 22·2 ng/mL [IQR 15·1-39·8] vs 16·9 [10·4-19·1], p=0·04; preterm pre-eclampsia n=11, 23·1 [11·2-30·9] vs 17·2 [9·8-19·1], p=0·04) and at 20 weeks' gestation (n=39, 23·0 [15·6-31·4] vs 17·0 [13·4-23·6]; p=0·04). GPBB concentrations were also significantly higher in women with SGA than in controls at the time of disease detection (n=23, 22·7 [12·6-25·5] vs 17·0 [9·8-18·0]; p=0·03) but significantly less than in controls at 15 weeks' gestation before disease detection (n=25, 16·0 [12·1-23·2] vs 22·2 [17·0-28·9]; p=0·02). INTERPRETATION: We have shown that significant variation of GPBB concentrations occurs in normal pregnancy, pre-eclampsia, and SGA pregnancies. GPBB in healthy pregnancy lowers as pregnancy progresses from the first to the third trimester. GPBB might, therefore, be useful as a biomarker in early pregnancy and at the time of disease in the prediction of both preterm and term pre-eclampsia and SGA. FUNDING: National Institute for Health Research, SCOPE Study was funded by the Health Research Board. This work was performed in the Irish Centre for Fetal and Neonatal Translational Research and partly supported by Science Foundation Ireland.

PP054. Elevated maternal plasma glycogen phosphorylase isoenzyme BB as time of disease biomarker of pre-eclampsia and small-for-gestational-age.

INTRODUCTION: Glycogen phosphorylase isoenzyme BB (GPBB) is a marker of acute coronary syndromes. Pre-eclampsia (PE) and coronary syndrome share several aetiological and pathophysiological features. GPBB levels have previously been found to be elevated in pregnancy and preterm PE. OBJECTIVES: We conducted 6 case-control studies within the SCOPE Ireland cohort to investigate whether plasma GPBB levels are altered at time of disease presentation and to examine if GPBB has any power as a predictive biomarker at earlier gestations. Methods Blood samples were taken at time of presentation with PE (n=25) and SGA (n=23) and also at 15 and 20 weeks gestation for PE with no SGA (n=33), PE and SGA (n=18), SGA no PE with gestational hypertension (GH) (n=25) and no GH (n=25). All were matched to uncomplicated pregnancy controls. GPBB plasma concentration was measured with GPBB-ELISA kits (Diagenics, Germany). RESULTS: The plasma GPBB concentration at disease presentation with PE and SGA was significantly higher than in normal uncomplicated pregnancies. There was no difference in plasma GPBB levels at 15 or 20 weeks' gestation in women who subsequently developed PE or SGA compared with controls. CONCLUSION: Plasma GPBB is increased at time of presentation with PE and SGA suggesting that plasma GPBB is a biomarker of uteroplacental insufficiency. However, we found no evidence to support its use as an early pregnancy biomarker as it was not significantly elevated at 15 or 20 weeks' gestation.

In Arabidopsis thaliana codon volatility scores reflect GC3 composition rather than selective pressure.

BACKGROUND: Synonymous codon usage bias has typically been correlated with, and attributed to translational efficiency. However, there are other pressures on genomic sequence composition that can affect codon usage patterns such as mutational biases. This study provides an analysis of the codon usage patterns in Arabidopsis thaliana in relation to gene expression levels, codon volatility, mutational biases and selective pressures. RESULTS: We have performed synonymous codon usage and codon volatility analyses for all genes in the A. thaliana genome. In contrast to reports for species from other kingdoms, we find that neither codon usage nor volatility are correlated with selection pressure (as measured by dN/dS), nor with gene expression levels on a genome wide level. Our results show that codon volatility and usage are not synonymous, rather that they are correlated with the abundance of G and C at the third codon position (GC3). CONCLUSIONS: Our results indicate that while the A. thaliana genome shows evidence for synonymous codon usage bias, this is not related to the expression levels of its constituent genes. Neither codon volatility nor codon usage are correlated with expression levels or selective pressures but, because they are directly related to the composition of G and C at the third codon position, they are the result of mutational bias. Therefore, in A. thaliana codon volatility and usage do not result from selection for translation efficiency or protein functional shift as measured by positive selection.

Functional annotation of the Arabidopsis genome using controlled vocabularies.

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community.

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.

TAIR: a resource for integrated Arabidopsis data.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) provides an integrated view of genomic data for Arabidopsis thaliana. The information is obtained from a battery of sources, including the Arabidopsis user community, the literature, and the major genome centers. Currently TAIR provides information about genes, markers, polymorphisms, maps, sequences, clones, DNA and seed stocks, gene families and proteins. In addition, users can find Arabidopsis publications and information about Arabidopsis researchers. Our emphasis is now on incorporating functional annotations of genes and gene products, genome-wide expression, and biochemical pathway data. Among the tools developed at TAIR, the most notable is the Sequence Viewer, which displays gene annotation, clones, transcripts, markers and polymorphisms on the Arabidopsis genome, and allows zooming in to the nucleotide level. A tool recently released is AraCyc, which is designed for visualization of biochemical pathways. We are also developing tools to extract information from the literature in a systematic way, and building controlled vocabularies to describe biological concepts in collaboration with other database groups. A significant new feature is the integration of the ABRC database functions and stock ordering system, which allows users to place orders for seed and DNA stocks directly from the TAIR site.