Modeling the Mechanism of Action of a DGAT1 Inhibitor Using a Causal Reasoning Platform

Triglyceride accumulation is associated with obesity and type 2 diabetes. Genetic disruption of diacylglycerol acyltransferase 1 (DGAT1), which catalyzes the final reaction of triglyceride synthesis, confers dramatic resistance to high-fat diet induced obesity. Hence, DGAT1 is considered a potential therapeutic target for treating obesity and related metabolic disorders. However, the molecular events shaping the mechanism of action of DGAT1 pharmacological inhibition have not been fully explored yet. Here, we investigate the metabolic molecular mechanisms induced in response to pharmacological inhibition of DGAT1 using a recently developed computational systems biology approach, the Causal Reasoning Engine (CRE). The CRE algorithm utilizes microarray transcriptomic data and causal statements derived from the biomedical literature to infer upstream molecular events driving these transcriptional changes. The inferred upstream events (also called hypotheses) are aggregated into biological models using a set of analytical tools that allow for evaluation and integration of the hypotheses in context of their supporting evidence. In comparison to gene ontology enrichment analysis which pointed to high-level changes in metabolic processes, the CRE results provide detailed molecular hypotheses to explain the measured transcriptional changes. CRE analysis of gene expression changes in high fat habituated rats treated with a potent and selective DGAT1 inhibitor demonstrate that the majority of transcriptomic changes support a metabolic network indicative of reversal of high fat diet effects that includes a number of molecular hypotheses such as PPARG, HNF4A and SREBPs. Finally, the CRE-generated molecular hypotheses from DGAT1 inhibitor treated rats were found to capture the major molecular characteristics of DGAT1 deficient mice, supporting a phenotype of decreased lipid and increased insulin sensitivity

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway

Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron (B.1.1.529), the fifth VOC to be described, harbours multiple amino acid mutations in spike, half of which lie within the receptor-binding domain. Here we demonstrate substantial evasion of neutralization by Omicron BA.1 and BA.2 variants in vitro using sera from individuals vaccinated with ChAdOx1, BNT162b2 and mRNA-1273. These data were mirrored by a substantial reduction in real-world vaccine effectiveness that was partially restored by booster vaccination. The Omicron variants BA.1 and BA.2 did not induce cell syncytia in vitro and favoured a TMPRSS2-independent endosomal entry pathway, these phenotypes mapping to distinct regions of the spike protein. Impaired cell fusion was determined by the receptor-binding domain, while endosomal entry mapped to the S2 domain. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant

OMERACT Core outcome measurement set for shared decision making in rheumatic and musculoskeletal conditions:a scoping review to identify candidate instruments

OBJECTIVES: Shared decision making (SDM) is a central tenet in rheumatic and musculoskeletal care. The lack of standardization regarding SDM instruments and outcomes in clinical trials threatens the comparative effectiveness of interventions. The Outcome Measures in Rheumatology (OMERACT) SDM Working Group is developing a Core Outcome Set for trials of SDM interventions in rheumatology and musculoskeletal health. The working group reached consensus on a Core Outcome Domain Set in 2020. The next step is to develop a Core Outcome Measurement Set through the OMERACT Filter 2.2.METHODS: We conducted a scoping review (PRISMA-ScR) to identify candidate instruments for the OMERACT Filter 2.2 We systematically reviewed five databases (Ovid MEDLINE®, Embase, Cochrane Library, CINAHL and Web of Science). An information specialist designed search strategies to identify all measurement instruments used in SDM studies in adults or children living with rheumatic or musculoskeletal diseases or their important others. Paired reviewers independently screened titles, abstracts, and full text articles. We extracted characteristics of all candidate instruments (e.g., measured construct, measurement properties). We classified candidate instruments and summarized evidence gaps with an adapted version of the Summary of Measurement Properties (SOMP) table.RESULTS: We found 14,464 citations, read 239 full text articles, and included 99 eligible studies. We identified 220 potential candidate instruments. The five most used measurement instruments were the Decisional Conflict Scale (traditional and low literacy versions) (n=38), the Hip/Knee-Decision Quality Instrument (n=20), the Decision Regret Scale (n=9), the Preparation for Decision Making Scale (n=8), and the CollaboRATE (n=8). Only 44 candidate instruments (20%) had any measurement properties reported by the included studies. Of these instruments, only 57% matched with at least one of the 7-criteria adapted SOMP table.CONCLUSION: We identified 220 candidate instruments used in the SDM literature amongst people with rheumatic and musculoskeletal diseases. Our classification of instruments showed evidence gaps and inconsistent reporting of measurement properties. The next steps for the OMERACT SDM Working Group are to match candidate instruments with Core Domains, assess feasibility and review validation studies of measurement instruments in rheumatic diseases or other conditions. Development and validation of new instruments may be required for some Core Domains.</p

Core outcome measurement set for shared decision making in rheumatic and musculoskeletal conditions: A scoping review to identify candidate instruments

OBJECTIVES Shared decision making (SDM) is a central tenet in rheumatic and musculoskeletal care. The lack of standardization regarding SDM instruments and outcomes in clinical trials threatens the comparative effectiveness of interventions. The Outcome Measures in Rheumatology (OMERACT) SDM Working Group is developing a Core Outcome Set for trials of SDM interventions in rheumatology and musculoskeletal health. The working group reached consensus on a Core Outcome Domain Set in 2020. The next step is to develop a Core Outcome Measurement Set through the OMERACT Filter 2.2. METHODS We conducted a scoping review (PRISMA-ScR) to identify candidate instruments for Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation the OMERACT Filter 2.2 We systematically reviewed five databases (Ovid MEDLINE®, Embase, Cochrane Library, CINAHL and Web of Science). An information specialist designed search strategies to identify all measurement instruments used in SDM studies in adults or children living with rheumatic or musculoskeletal diseases or their important others. Paired reviewers independently screened titles, abstracts, and full text articles. We extracted characteristics of all candidate instruments (e.g., measured construct, measurement properties). We classified candidate instruments and summarized evidence gaps with an adapted version of the Summary of Measurement Properties (SOMP) table. RESULTS We found 14,464 citations, read 239 full text articles, and included 99 eligible studies. We identified 220 potential candidate instruments. The five most used measurement instruments were the Decisional Conflict Scale (traditional and low literacy versions) (n=38), the Hip/Knee-Decision Quality Instrument (n=20), the Decision Regret Scale (n=9), the Preparation for Decision Making Scale (n=8), and the CollaboRATE (n=8). Only 44 candidate instruments (20%) had any measurement properties reported by the included studies. Of these instruments, only 57% matched with at least one of the 7-criteria adapted SOMP table. CONCLUSION We identified 220 candidate instruments used in the SDM literature among people with rheumatic and musculoskeletal diseases. Our classification of instruments showed evidence gaps and inconsistent reporting of measurement properties. The next steps for the OMERACT SDM Working Group are to match candidate instruments with Core Domains, assess feasibility and review validation studies of measurement instruments in rheumatic diseases or other conditions. Development and validation of new instruments may be required for some Core Domains