Publications by authors named "Eoin McKinney"

The goal of the TEDDY (The Environmental Determinants of Diabetes in the Young) study is to elucidate factors leading to the initiation of islet autoimmunity (first primary outcome) and those related to progression to type 1 diabetes mellitus (T1DM; second primary outcome). This Review outlines the key findings so far, particularly related to the first primary outcome. The background, history and organization of the study are discussed.

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Article Synopsis
  • - Selective IgA deficiency (SIgAD) is the most common type of inherited immune disorder, but previous studies have struggled to find specific genetic variants due to small sample sizes.
  • - Researchers conducted a meta-analysis of existing Genome-Wide Association Studies (GWAS), discovering four new common genetic variants linked to SIgAD and confirming connections to genes associated with other inherited immune disorders.
  • - By analyzing the genetic links between SIgAD, serum IgA levels, asthma, and rheumatoid arthritis, the study identified an additional 18 genetic variants, raising the total to 27 and supporting the idea that SIgAD has a complex genetic basis.
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Background: Management strategies and clinical outcomes vary substantially in patients newly diagnosed with Crohn's disease. We evaluated the use of a putative prognostic biomarker to guide therapy by assessing outcomes in patients randomised to either top-down (ie, early combined immunosuppression with infliximab and immunomodulator) or accelerated step-up (conventional) treatment strategies.

Methods: PROFILE (PRedicting Outcomes For Crohn's disease using a moLecular biomarker) was a multicentre, open-label, biomarker-stratified, randomised controlled trial that enrolled adults with newly diagnosed active Crohn's disease (Harvey-Bradshaw Index ≥7, either elevated C-reactive protein or faecal calprotectin or both, and endoscopic evidence of active inflammation).

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The use of data from randomized clinical trials to justify treatment decisions for real-world patients is the current state of the art. It relies on the assumption that average treatment effects from the trial can be extrapolated to patients with personal and/or disease characteristics different from those treated in the trial. Yet, because of heterogeneity of treatment effects between patients and between the trial population and real-world patients, this assumption may not be correct for many patients.

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Diagnostic and prognostic models are increasingly important in medicine and inform many clinical decisions. Recently, machine learning approaches have shown improvement over conventional modeling techniques by better capturing complex interactions between patient covariates in a data-driven manner. However, the use of machine learning introduces technical and practical challenges that have thus far restricted widespread adoption of such techniques in clinical settings.

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Clonal expansions driven by somatic mutations become pervasive across human tissues with age, including in the haematopoietic system, where the phenomenon is termed clonal haematopoiesis. The understanding of how and when clonal haematopoiesis develops, the factors that govern its behaviour, how it interacts with ageing and how these variables relate to malignant progression remains limited. Here we track 697 clonal haematopoiesis clones from 385 individuals 55 years of age or older over a median of 13 years.

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MicroRNAs are critical regulators of gene expression controlling cellular processes including inflammation. We explored their role in the pathogenesis of inflammatory bowel disease (IBD) and identified reduced expression of miR-374a-5p in IBD monocytes that correlated with a module of up-regulated genes related to the inflammatory response. Key proinflammatory module genes, including for example TNFα, IL1A, IL6, and OSM, were inversely correlated with miR-374a-5p and were validated in vitro.

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Autoimmunity is believed to play a role in idiopathic pulmonary arterial hypertension (IPAH). It is not clear whether this is causative or a bystander of disease and if it carries any prognostic or treatment significance. To study autoimmunity in IPAH using a large cross-sectional cohort.

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Type 1 diabetes (T1D) is an autoimmune disease characterised by T cell-mediated destruction of the insulin-producing β cells in the pancreas. Similar to other autoimmune diseases, the incidence of T1D is increasing globally. The discovery of insulin 100 years ago dramatically changed the outlook for people with T1D, preventing this from being a fatal condition.

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B cells are important in immunity to both severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and vaccination, but B cell receptor (BCR) repertoire development in these contexts has not been compared. We analyze serial samples from 171 SARS-CoV-2-infected individuals and 63 vaccine recipients and find the global BCR repertoire differs between them. Following infection, immunoglobulin (Ig)G1/3 and IgA1 BCRs increase, somatic hypermutation (SHM) decreases, and, in severe disease, IgM and IgA clones are expanded.

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Although two-dose mRNA vaccination provides excellent protection against SARS-CoV-2, there is little information about vaccine efficacy against variants of concern (VOC) in individuals above eighty years of age. Here we analysed immune responses following vaccination with the BNT162b2 mRNA vaccine in elderly participants and younger healthcare workers. Serum neutralization and levels of binding IgG or IgA after the first vaccine dose were lower in older individuals, with a marked drop in participants over eighty years old.

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Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive.

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Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) with the majority of cases characterised by relapsing/remitting (RRMS) attacks of neurologic dysfunction followed by variable resolution. Improving clinical outcomes in RRMS requires both a better understanding of the immunological mechanisms driving recurrent demyelination and better means of predicting future disease course to facilitate early targeted therapy. Here, we apply hypothesis-generating network transcriptomics to CD8 cells isolated from patients in RRMS, identifying a signature reflecting expansion of a subset of CD8 natural killer cells (NK8) associated with favourable outcome.

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The COVID-19 global pandemic is a threat not only to the health of millions of individuals, but also to the stability of infrastructure and economies around the world. The disease will inevitably place an overwhelming burden on healthcare systems that cannot be effectively dealt with by existing facilities or responses based on conventional approaches. We believe that a rigorous clinical and societal response can only be mounted by using intelligence derived from a variety of data sources to better utilize scarce healthcare resources, provide personalized patient management plans, inform policy, and expedite clinical trials.

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The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways.

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Objective: We have previously described a prognostic transcriptional signature in CD8 T cells that separates patients with IBD into two phenotypically distinct subgroups, termed IBD1 and IBD2. Here we sought to develop a blood-based test that could identify these subgroups without cell separation, and thus be suitable for clinical use in Crohn's disease (CD) and ulcerative colitis (UC).

Design: Patients with active IBD were recruited before treatment.

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For over a decade the term "Big data" has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, "Big data" no longer means what it once did.

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Background: The course of Crohn's disease (CD) varies substantially between individuals, but reliable prognostic markers do not exist. This hinders disease management because patients with aggressive disease are undertreated by conventional 'step-up' therapy (in which treatment is gradually escalated in response to refractory or relapsing disease) while those with more indolent disease would be exposed to unnecessary treatment-related toxicity if a more aggressive 'top-down' approach was indiscriminately used. The Predicting outcomes for Crohn's disease using a molecular biomarker trial will assess whether a prognostic transcriptional biomarker, that we have developed and validated, can improve clinical outcomes by facilitating personalised therapy in CD.

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T cell exhaustion represents a continuous spectrum of cellular dysfunction induced during chronic viral infection, facilitating viral persistence and associating with poor clinical outcome. Modulation of T cell exhaustion can restore function in exhausted CD8 T cells, promoting viral clearance. Exhaustion has also been implicated as playing an important role in anti-tumour responses, whereby exhausted tumour-infiltrating lymphocytes fail to control tumour progression.

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During acute viral infection CD8 T cells rapidly expand before contracting down to a persistent memory population that confers long-lasting immunity. However when the antigen persists, such as during chronic viral infection, a dysfunctional process termed 'exhaustion' limits the antiviral response, facilitating ongoing viraemia and poor clinical outcome. CD8 T-cell exhaustion was originally identified in lymphocytic choriomeningitis virus infection of mice; however, new evidence has shown that exhaustion is associated with the control of a wide range of human chronic inflammatory states, including chronic viral infection, autoimmunity and cancer.

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Objectives: Type 1 interferons (IFN-1) are implicated in the pathogenesis of systemic lupus erythematosus (SLE), but most studies have only reported the effect of IFN-1 on mixed cell populations. We aimed to define modules of IFN-1-associated genes in purified leucocyte populations and use these as a basis for a detailed comparative analysis.

Methods: CD4+ and CD8+ T cells, monocytes and neutrophils were purified from patients with SLE, other immune-mediated diseases and healthy volunteers and gene expression then determined by microarray.

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The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence.

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A small but increasing number of gene expression based biomarkers are becoming available for routine clinical use, principally in oncology and transplantation. These underscore the potential of gene expression arrays and RNA sequencing for biomarker development, but this potential has not yet been fully realized and most candidates do not progress beyond the initial report. The first part of this review examines the process of gene expression- based biomarker development, highlighting how systematic biases and confounding can significantly skew study outcomes.

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