ORCID Profile
0000-0001-9258-3140
Current Organisations
NHS Tayside
,
The University of Edinburgh
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Publisher: Springer Science and Business Media LLC
Date: 16-10-2020
Publisher: Cold Spring Harbor Laboratory
Date: 11-04-2020
DOI: 10.1101/2020.04.06.20055517
Abstract: Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here, we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer’s disease (AD)-free participants. Associations between dementia risk measures (family history, genetic risk score (GRS), and dementia risk scores (combining lifestyle, demographic and genetic factors) and whole-blood DNA methylation were assessed in discovery and replication s les (n=∼400 – ∼5,000) from Generation Scotland. AD genetic risk and two risk scores were associated with differential methylation. The GRS predominantly associated with methylation differences in cis but also identified a genomic region implicated in Parkinson’s disease. Loci associated with the risk scores were enriched for those previously associated with body mass index and alcohol consumption. Dementia risk measures show widespread association with blood-based methylation, which indicates differences in the processes affected by genetic and demographic/lifestyle risk factors.
Publisher: Cold Spring Harbor Laboratory
Date: 23-10-2019
DOI: 10.1101/815035
Abstract: The Apolipoprotein E ( APOE ) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, while the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE ε4 (n=2469) and ε2 (n=1118) carriers from the two largest single-cohort DNA methylation s les profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. We obtained replicated evidence for DNA methylation differences in a ~ 169kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 x 10 −100 ≤ P ≤2.44 x 10 −8 ) and DMRs were identified in SREBF2 and LDLR (1.63 x 10 −4 ≤ P ≤3.01 x 10 −2 ). Pathway and meQTL analyses implicated lipid-related processes and high density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24 . APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.
Publisher: Cold Spring Harbor Laboratory
Date: 06-04-2020
DOI: 10.1101/2020.04.03.023804
Abstract: Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. By mapping and replicating protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 in iduals, we identified 467 pQTLs for 85 proteins. The pQTLs were used in combination with other sources of information to evaluate known drug targets, and suggest new target candidates or repositioning opportunities, underpinned by a) causality assessment using Mendelian randomization, b) pathway mapping using trans -pQTL gene assignments, and c) protein-centric polygenic risk scores enabling matching of plausible target mechanisms to sub-groups of in iduals enabling precision medicine.
Publisher: eLife Sciences Publications, Ltd
Date: 15-01-2019
DOI: 10.7554/ELIFE.39856
Abstract: We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. In idual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed ( xref ref-type="decision-letter" rid="SA1" see decision letter /xref ).
Publisher: Springer Science and Business Media LLC
Date: 11-12-2021
DOI: 10.1038/S41586-020-03065-Y
Abstract: Host-mediated lung inflammation is present
Publisher: Springer Science and Business Media LLC
Date: 07-03-2022
DOI: 10.1038/S41586-022-04576-6
Abstract: Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care 1 or hospitalization 2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from in iduals 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 in iduals 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.
Publisher: Springer Science and Business Media LLC
Date: 17-05-2023
DOI: 10.1038/S41586-023-06034-3
Abstract: Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown 1 to be highly efficient for discovery of genetic associations 2 . Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group 3 . Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling ( JAK1 ), monocyte–macrophage activation and endothelial permeability ( PDE4A ), immunometabolism ( SLC2A5 and AK5 ), and host factors required for viral entry and replication ( TMPRSS2 and RAB2A ).
Publisher: Springer Science and Business Media LLC
Date: 09-2021
Publisher: Springer Science and Business Media LLC
Date: 06-09-2023
Publisher: Springer Science and Business Media LLC
Date: 11-07-2023
Publisher: Cold Spring Harbor Laboratory
Date: 02-09-2021
DOI: 10.1101/2021.09.02.21262965
Abstract: Critical illness in COVID-19 is caused by inflammatory lung injury, mediated by the host immune system. We and others have shown that host genetic variation influences the development of illness requiring critical care 1 or hospitalisation 2 4 following SARS-Co-V2 infection. The GenOMICC (Genetics of Mortality in Critical Care) study recruits critically-ill cases and compares their genomes with population controls in order to find underlying disease mechanisms. Here, we use whole genome sequencing and statistical fine mapping in 7,491 critically-ill cases compared with 48,400 population controls to discover and replicate 22 independent variants that significantly predispose to life-threatening COVID-19. We identify 15 new independent associations with critical COVID-19, including variants within genes involved in interferon signalling ( IL10RB, PLSCR1 ), leucocyte differentiation ( BCL11A ), and blood type antigen secretor status ( FUT2 ). Using transcriptome-wide association and colocalisation to infer the effect of gene expression on disease severity, we find evidence implicating expression of multiple genes, including reduced expression of a membrane flippase ( ATP11A ), and increased mucin expression ( MUC1 ), in critical disease. We show that comparison between critically-ill cases and population controls is highly efficient for genetic association analysis and enables detection of therapeutically-relevant mechanisms of disease. Therapeutic predictions arising from these findings require testing in clinical trials.
Publisher: Cold Spring Harbor Laboratory
Date: 27-09-2022
DOI: 10.1101/2022.09.25.22280081
Abstract: Optimising statistical power in early-stage trials and observational studies accelerates discovery and improves the reliability of results. Ideally, intermediate outcomes should be continuously distributed and lie on the causal pathway between an intervention and a definitive outcome such as mortality. In order to optimise power for an intermediate outcome in the RECOVERY trial, we devised and evaluated a modification to a simple, pragmatic measure of oxygenation function - the S a O 2 / F I O 2 (S/F) ratio. We demonstrate that, because of the ceiling effect in oxyhaemoglobin saturation, S/F ceases to reflect pulmonary oxygenation function at high values of S a O 2 . Using synthetic and real data, we found that the correlation of S/F with a gold standard ( P a O 2 / F I O 2 , P/F ratio) improved substantially when measurements with S a O 2 ≥ 0.94 are excluded (Spearman r , synthetic data: S/F : 0.31 S/F 94 : 0.85). We refer to this measure as S/F 94 . In order to test the underlying assumptions and validity of S/F 94 as a predictor of a definitive outcome (mortality), we collected an observational dataset including over 39,000 hospitalised patients with COVID-19 in the ISARIC4C study. We first demonstrated that S/F 94 is predictive of mortality in COVID-19. We then compared the s le sizes required for trials using different outcome measures ( S/F 94 , the WHO ordinal scale, sustained improvement at day 28 and mortality at day 28) ensuring comparable effect sizes. The smallest s le size was needed when S/F 94 on day 5 was used as an outcome measure. To facilitate future study design, we provide an online user interface to quantify real-world power for a range of outcomes and inclusion criteria, using a synthetic dataset retaining the population-level clinical associations in real data accrued in ISARIC4C ndpoints . We demonstrated that S/F 94 is superior to S/F as a measure of pulmonary oxygenation function and is an effective intermediate outcome measure in COVID-19. It is a simple and non-invasive measurement, representative of disease severity and provides greater statistical power to detect treatment differences than other intermediate endpoints.
Publisher: Public Library of Science (PLoS)
Date: 03-2018
Publisher: Springer Science and Business Media LLC
Date: 08-07-2021
DOI: 10.1038/S41586-021-03767-X
Abstract: The genetic make-up of an in idual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-19 1,2 , host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases 3–7 . They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Publisher: Cold Spring Harbor Laboratory
Date: 25-09-2020
DOI: 10.1101/2020.09.24.20200048
Abstract: The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs 1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases. 2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19. 3 GenOMICC (Genetics Of Mortality In Critical Care, genomicc.org ) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing % of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland. We identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 × 10 −12 ), within the gene encoding dipeptidyl peptidase 9 ( DPP9 ), at chr12q24.13 (rs10735079, p =1.65 × 10 −8 ) in a gene cluster encoding antiviral restriction enzyme activators ( OAS1, OAS2, OAS3 ), and at chr21q22.1 (rs2236757, p = 4.99 × 10 −8 ) in the interferon receptor gene IFNAR2 . Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 × 10 −30 ). We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2 , and high expression of TYK2 , to life-threatening disease. 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. Large-scale randomised clinical trials will be essential before any change to clinical practice.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Andrew Bretherick.