Characterization of patients with idiopathic normal pressure hydrocephalus using natural language processing within an electronic healthcare record system

OBJECTIVE: Idiopathic normal pressure hydrocephalus (iNPH) is an underdiagnosed, progressive, and disabling condition. Early treatment is associated with better outcomes and improved quality of life. In this paper, the authors aimed to identify features associated with patients with iNPH using natural language processing (NLP) to characterize this cohort, with the intention to later target the development of artificial intelligence–driven tools for early detection. / METHODS: The electronic health records of patients with shunt-responsive iNPH were retrospectively reviewed using an NLP algorithm. Participants were selected from a prospectively maintained single-center database of patients undergoing CSF diversion for probable iNPH (March 2008–July 2020). Analysis was conducted on preoperative health records including clinic letters, referrals, and radiology reports accessed through CogStack. Clinical features were extracted from these records as SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) concepts using a named entity recognition machine learning model. In the first phase, a base model was generated using unsupervised training on 1 million electronic health records and supervised training with 500 double-annotated documents. The model was fine-tuned to improve accuracy using 300 records from patients with iNPH double annotated by two blinded assessors. Thematic analysis of the concepts identified by the machine learning algorithm was performed, and the frequency and timing of terms were analyzed to describe this patient group. / RESULTS: In total, 293 eligible patients responsive to CSF diversion were identified. The median age at CSF diversion was 75 years, with a male predominance (69% male). The algorithm performed with a high degree of precision and recall (F1 score 0.92). Thematic analysis revealed the most frequently documented symptoms related to mobility, cognitive impairment, and falls or balance. The most frequent comorbidities were related to cardiovascular and hematological problems. / CONCLUSIONS: This model demonstrates accurate, automated recognition of iNPH features from medical records. Opportunities for translation include detecting patients with undiagnosed iNPH from primary care records, with the aim to ultimately improve outcomes for these patients through artificial intelligence–driven early detection of iNPH and prompt treatment

Rich pictures for stakeholder dialogue:A polyphonic picture book

We describe the design and use of a ‘polyphonic picture book’ for engaging stakeholders and research participants with findings from an interdisciplinary project investigating how UK citizens create and manage online identities at three significant life transitions. The project delivered socio-cultural and technical findings to inform policy-making and service innovation for enhancing digital literacy in online self-representation. The picture book presented findings through multi-perspectival, fictional scenarios about experiences of life transition. We describe our use of the book with our stakeholders in five workshop settings and our evaluation of the visual format for fostering stakeholder dialogue around the findings and their transferability. This paper contributes methodological insights about using visual storytelling to scaffold interpretative, dialogical contexts of research engagement

Monoallelic Expression of Multiple Genes in the CNS

The inheritance pattern of a number of major genetic disorders suggests the possible involvement of genes that are expressed from one allele and silent on the other, but such genes are difficult to detect. Since DNA methylation in regulatory regions is often a mark of gene silencing, we modified existing microarray-based assays to detect both methylated and unmethylated DNA sequences in the same sample, a variation we term the MAUD assay. We probed a 65 Mb region of mouse Chr 7 for gene-associated sequences that show two distinct DNA methylation patterns in the mouse CNS. Selected genes were then tested for allele-specific expression in clonal neural stem cell lines derived from reciprocal F1 (C57BL/6×JF1) hybrid mice. In addition, using a separate approach, we directly analyzed allele-specific expression of a group of genes interspersed within clusters of OlfR genes, since the latter are subject to allelic exclusion. Altogether, of the 500 known genes in the chromosomal region surveyed, five show monoallelic expression, four identified by the MAUD assay (Agc1, p (pink-eyed dilution), P4ha3 and Thrsp), and one by its proximity to OlfR genes (Trim12). Thrsp (thyroid hormone responsive SPOT14 homolog) is expressed in hippocampus, but the human protein homolog, S14, has also been implicated in aggressive breast cancer. Monoallelic expression of the five genes is not coordinated at a chromosome-wide level, but rather regulated at individual loci. Taken together, our results suggest that at least 1% of previously untested genes are subject to allelic exclusion, and demonstrate a dual approach to expedite their identification

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Increased Cycling Cell Numbers and Stem Cell Associated Proteins as Potential Biomarkers for High Grade Human Papillomavirus+ve Pre-Neoplastic Cervical Disease

High risk (oncogenic) human papillomavirus (HPV) infection causes cervical cancer. Infections are common but most clear naturally. Persistent infection can progress to cancer. Pre-neoplastic disease (cervical intraepithelial neoplasia/CIN) is classified by histology (CIN1-3) according to severity. Cervical abnormalities are screened for by cytology and/or detection of high risk HPV but both methods are imperfect for prediction of which women need treatment. There is a need to understand the host virus interactions that lead to different disease outcomes and to develop biomarker tests for accurate triage of infected women. As cancer is increasingly presumed to develop from proliferative, tumour initiating, cancer stem cells (CSCs), and as other oncogenic viruses induce stem cell associated gene expression, we evaluated whether presence of mRNA (detected by qRT-PCR) or proteins (detected by flow cytometry and antibody based proteomic microarray) from stem cell associated genes and/or increased cell proliferation (detected by flow cytometry) could be detected in well-characterised, routinely collected cervical samples from high risk HPV+ve women. Both cytology and histology results were available for most samples with moderate to high grade abnormality. We found that stem cell associated proteins including human chorionic gonadotropin, the oncogene TP63 and the transcription factor SOX2 were upregulated in samples from women with CIN3 and that the stem cell related, cell surface, protein podocalyxin was detectable on cells in samples from a subset of women with CIN3. SOX2, TP63 and human gonadotrophin mRNAs were upregulated in high grade disease. Immunohistochemistry showed that SOX2 and TP63 proteins clearly delineated tumour cells in invasive squamous cervical cancer. Samples from women with CIN3 showed increased proliferating cells. We believe that these markers may be of use to develop triage tests for women with high grade cervical abnormality to distinguish those who may progress to cancer from those who may be treated more conservatively

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Gendered Frontlines: British Press Coverage of Servicewomen Killed in Iraq

The press plays a crucial role in image formation and information provision about female soldiers who die on battlefields. This article demonstrates how the UK press coverage of the death of four British service women stripped them of their identity as soldiers and minimised their accomplishments and level of military participation. It analyses how media discourse of war and military practices converged to reinforce cultural assumptions of war. The article argues that the nuanced coverage of the four women who died in Iraq within one year was a result of gendered mediation, which accentuated the femininity and masculinity dichotomy associated with the military; and underscored the gendered nature of war. The study shows that the gendering of the death of the women reinforced the entrenched marginalisation of women in war narratives