Publications by authors named "Katie Burnham"

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors.

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Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS.

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Article Synopsis
  • - Sepsis is a severe response to infection that causes life-threatening organ dysfunction, highlighting the need for better understanding and new treatments for this global health issue.
  • - Researchers utilized high-throughput tandem mass spectrometry to analyze the plasma proteins of sepsis patients compared to other groups, collecting extensive data from over 2,600 samples to identify specific protein changes and disease features.
  • - The findings offer insights into the immune response to sepsis, helping to pinpoint subtypes of the condition, potential biomarkers for diagnosis, and paving the way for personalized treatment strategies.
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Rationale: Heterogeneity of the host response within sepsis, acute respiratory distress syndrome (ARDS) and more widely critical illness, limits discovery and targeting of immunomodulatory therapies. Clustering approaches using clinical and circulating biomarkers have defined hyper-inflammatory and hypo-inflammatory subphenotypes in ARDS associated with differential treatment response. It is unknown if similar subphenotypes exist in sepsis populations where leucocyte transcriptomic-defined subphenotypes have been reported.

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Objective: To describe immune pathways and gene networks altered following major abdominal surgery and to identify transcriptomic patterns associated with postoperative pneumonia.

Background: Nosocomial infections are a major healthcare challenge, developing in over 20% of patients aged 45 or over undergoing major abdominal surgery, with postoperative pneumonia associated with an almost 5-fold increase in 30-day mortality.

Methods: From a prospective consecutive cohort (n=150) undergoing major abdominal surgery, whole-blood RNA was collected preoperatively and at 3 time-points postoperatively (2-6, 24, and 48 h).

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Sepsis arises from diverse and incompletely understood dysregulated host response processes following infection that leads to life-threatening organ dysfunction. Here we showed that neutrophils and emergency granulopoiesis drove a maladaptive response during sepsis. We generated a whole-blood single-cell multiomic atlas (272,993 cells, n = 39 individuals) of the sepsis immune response that identified populations of immunosuppressive mature and immature neutrophils.

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Although alterations in myeloid cells have been observed in COVID-19, the specific underlying mechanisms are not completely understood. Here, we examine the function of classical CD14 monocytes in patients with mild and moderate COVID-19 during the acute phase of infection and in healthy individuals. Monocytes from COVID-19 patients display altered expression of cell surface receptors and a dysfunctional metabolic profile that distinguish them from healthy monocytes.

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Advances in our understanding of the nature of the immune response to SARS-CoV-2 infection, and how this varies within and between individuals, is important in efforts to develop targeted therapies and precision medicine approaches. Here we present a database for the COvid-19 Multi-omics Blood ATlas (COMBAT) project, COMBATdb (https://db.combat.

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Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map.

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Article Synopsis
  • Scientists are trying to find a better way to measure inflammation in blood vessels of COVID-19 patients to help figure out who might have serious issues later and who might benefit from treatments.
  • They created a new system using artificial intelligence that looks at images from CT scans to help identify this inflammation, called C19-RS.
  • Their study showed that COVID-19 patients had higher levels of this C19-RS, and those with certain virus variants were even more likely to have serious complications, helping doctors predict who might not survive their hospital stay.
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Background: Gram-positive and Gram-negative bacteria are the most common causative pathogens in community-acquired pneumonia (CAP) on the intensive care unit (ICU). The aim of this study was to determine whether the host immune response differs between Gram-positive and Gram-negative CAP upon ICU admission.

Methods: 16 host response biomarkers providing insight into pathophysiological mechanisms implicated in sepsis and blood leukocyte transcriptomes were analysed in patients with CAP upon ICU admission in two tertiary hospitals in the Netherlands.

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Objective: The purpose of this study was to identify disease relevant genes and explore underlying immunological mechanisms that contribute to early and late onset forms of myasthenia gravis.

Methods: We used a novel genomic methodology to integrate genomewide association study (GWAS) findings in myasthenia gravis with cell-type specific information, such as gene expression patterns and promotor-enhancer interactions, in order to identify disease-relevant genes. Subsequently, we conducted additional genomic investigations, including an expression quantitative analysis of 313 healthy people to provide mechanistic insights.

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Epstein-Barr virus (EBV) reactivation is common in sepsis patients but the extent and nature of this remains unresolved. We sought to determine the incidence and correlates of EBV-positivity in a large sepsis cohort. We also hypothesised that EBV reactivation would be increased in patients in whom relative immunosuppression was the major feature of their sepsis response.

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Article Synopsis
  • - Recent studies on Drosophila simulans have shown the emergence of X-linked segregation distorters, termed the "Paris" system, leading to the selection of Y chromosomes resistant to these distorters, with observable variation in the proportion of female progeny they produce.
  • - Analysis of 386 Y chromosomes indicates a continuum of response to the Paris system, revealing only three polymorphic sites resulting in three distinct haplotypes, with one haplotype associated with resistance found fixed in Sub-Saharan African samples.
  • - The rapid evolution and replacement of susceptible Y chromosomes by the resistant haplotype were documented in populations from Egypt and Morocco within a few years, highlighting the influence of intragenomic conflicts and suggesting the rapid emergence
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Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection. Drug targets with genetic support are more likely to be therapeutically valid, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level.

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Rationale: There remains uncertainty about the role of corticosteroids in sepsis with clear beneficial effects on shock duration, but conflicting survival effects. Two transcriptomic sepsis response signatures (SRSs) have been identified. SRS1 is relatively immunosuppressed, whereas SRS2 is relatively immunocompetent.

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Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients.

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Background: Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis.

Methods: This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort).

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Rationale: Heterogeneity in the septic response has hindered efforts to understand pathophysiology and develop targeted therapies. Source of infection, with different causative organisms and temporal changes, might influence this heterogeneity.

Objectives: To investigate individual and temporal variations in the transcriptomic response to sepsis due to fecal peritonitis, and to compare these with the same parameters in community-acquired pneumonia.

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Background: Biological interpretation of genomic summary data such as those resulting from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is one of the major bottlenecks in medical genomics research, calling for efficient and integrative tools to resolve this problem.

Results: We introduce eXploring Genomic Relations (XGR), an open source tool designed for enhanced interpretation of genomic summary data enabling downstream knowledge discovery. Targeting users of varying computational skills, XGR utilises prior biological knowledge and relationships in a highly integrated but easily accessible way to make user-input genomic summary datasets more interpretable.

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Background: Effective targeted therapy for sepsis requires an understanding of the heterogeneity in the individual host response to infection. We investigated this heterogeneity by defining interindividual variation in the transcriptome of patients with sepsis and related this to outcome and genetic diversity.

Methods: We assayed peripheral blood leucocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with sepsis due to community-acquired pneumonia and evidence of organ dysfunction.

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