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Showing papers by "Lee Murphy published in 2020"


Posted ContentDOI
25 Sep 2020-medRxiv
TL;DR: The results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs) representing >95% of all ICU beds were reported in this article.
Abstract: The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs[PMID: 32526193] and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.[PMID: 32678530] 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.[PMID: 24855243] 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 >95% 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 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p = 1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 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 x 10-30).

90 citations


Journal ArticleDOI
TL;DR: This study describes the experiences of nine new and established mRNA profiling techniques and illustrates that technology selection is a balance between required resolution, sample quality, availability and cost.
Abstract: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated. This study describes our experiences of nine new and established mRNA profiling techniques including Lexogen QuantSeq, Qiagen QiaSeq, BioSpyder TempO-Seq, Ion AmpliSeq, Nanostring, Affymetrix Clariom S or U133A, Illumina BeadChip and RNA-seq of formalin-fixed paraffin embedded (FFPE) and fresh frozen (FF) sequential patient-matched breast tumour samples. The number of genes represented and reliability varied between the platforms, but overall all methods provided data which were largely comparable. Crucially we found that it is possible to integrate data for combined analyses across FFPE/FF and platforms using established batch correction methods as required to increase cohort sizes. However, some platforms appear to be better suited to FFPE samples, particularly archival material. Overall, we illustrate that technology selection is a balance between required resolution, sample quality, availability and cost.

32 citations


Journal ArticleDOI
TL;DR: Induced pluripotent stem cells from 24 people from the Lothian Birth Cohort 1936, whose cognitive ability was tested in childhood and in older age are generated to study molecular mechanisms underlying individual differences in cognitive ageing and resilience to age-related neurodegenerative diseases.

9 citations


Posted ContentDOI
01 Dec 2020-bioRxiv
TL;DR: This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.
Abstract: Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain, and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post-mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (DNA methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent correlations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus ({beta} range=0.83-1.14, p[≤]0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus ({beta}=1.32, p=5x10-4); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions ({beta}=0.40, p=0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.

8 citations


Posted ContentDOI
05 Feb 2020-bioRxiv
TL;DR: Induced pluripotent stem cells from 24 people from the Lothian Birth Cohort 1936, whose cognitive ability was tested in childhood and in older age are generated to study molecular mechanisms underlying individual differences in cognitive ageing and resilience to age-related neurodegenerative diseases.
Abstract: Cognitive decline is among the most feared aspects of ageing. We have generated induced pluripotent stem cells (iPSCs) from 24 people from the Lothian Birth Cohort 1936, whose cognitive ability was tested in childhood and in older age. Peripheral blood mononuclear cells (PBMCs) were reprogrammed using non-integrating oriP/EBNA1 backbone plasmids expressing six iPSC reprogramming factors (OCT3/4 (POU5F1), SOX2, KLF4, L-Myc, shp53, Lin28, SV40LT). All lines demonstrated STR matched karyotype and pluripotency was validated by multiple methods. These iPSC lines are a valuable resource to study molecular mechanisms underlying individual differences in cognitive ageing and resilience to age-related neurodegenerative diseases.

4 citations


Journal ArticleDOI
30 Jun 2020
TL;DR: This feasibility study demonstrates that self-collected DNA samples from mothers and babies were sufficient for genetic analysis but yields were variable, highlighting the need for alternative strategies for investigating genetic links with PTB.
Abstract: Background: Preterm birth (PTB) represents the leading cause of neonatal death. Large-scale genetic studies are necessary to determine genetic influences on PTB risk, but prospective cohort studies are expensive and time-consuming. We investigated the feasibility of retrospective recruitment of post-partum women for efficient collection of genetic samples, with self-collected saliva for DNA extraction from themselves and their babies, alongside self-recollection of pregnancy and birth details to phenotype PTB. Methods: 708 women who had participated in the OPPTIMUM trial (a randomised trial of progesterone pessaries to prevent PTB [ISRCTN14568373]) and consented to further contact were invited to provide self-collected saliva from themselves and their babies. DNA was extracted from Oragene OG-500 (adults) and OG-575 (babies) saliva kits and the yield measured by Qubit. Samples were analysed using a panel of Taqman single nucleotide polymorphism (SNP) assays. A questionnaire designed to meet the minimum data set required for phenotyping PTB was included. Questionnaire responses were transcribed and analysed for concordance with prospective trial data using Cohen's kappa ( k). Results: Recruitment rate was 162/708 (23%) for self-collected saliva samples and 157/708 (22%) for questionnaire responses. 161 samples from the mother provided DNA with median yield 59.0µg (0.4-148.9µg). 156 samples were successfully genotyped (96.9%). 136 baby samples had a median yield 11.5µg (0.1-102.7µg); two samples failed DNA extraction. 131 baby samples (96.3%) were successfully genotyped. Concordance between self-recalled birth details and prospective birth details was excellent ( k>0.75) in 4 out of 10 key fields for phenotyping PTB (mode of delivery, labour onset, ethnicity and maternal age at birth). Conclusion: This feasibility study demonstrates that self-collected DNA samples from mothers and babies were sufficient for genetic analysis but yields were variable. Self-recollection of pregnancy and birth details was inadequate for accurately phenotyping PTB, highlighting the need for alternative strategies for investigating genetic links with PTB.

3 citations


Posted ContentDOI
30 Nov 2020-medRxiv
TL;DR: It is found that correlations between blood and brain DNAm scores for smoking, high density lipoprotein (HDL) cholesterol, alcohol and body mass index (BMI) were highly variable across brain regions and suggests that lifestyle-related DNAm is likely to be both brain region dependent and in many cases poorly proxied for by blood.
Abstract: Modifiable lifestyle factors influence the risk of developing many neurological diseases. These factors have been extensively linked with blood-based genome-wide DNA methylation (DNAm), but it is unclear if the signatures from blood translate to the target tissue of interest - the brain. To investigate this, we apply blood-derived epigenetic predictors of four lifestyle traits to genome-wide DNAm from five post-mortem brain regions and the last blood sample prior to death in 14 individuals in the Lothian Birth Cohort 1936 (LBC1936). Using these matched samples, we found that correlations between blood and brain DNAm scores for smoking, high density lipoprotein (HDL) cholesterol, alcohol and body mass index (BMI) were highly variable across brain regions. Smoking scores in the dorsolateral prefrontal cortex had the strongest correlations with smoking scores in blood (r=0.5, n=14) and smoking behaviour (r=0.56, n=9). This was also the brain region which exhibited the strongest correlations for DNAm at site cg05575921 - the single strongest correlate of smoking in blood - in relation to blood (r=0.61, n=14) and smoking behaviour (r=-0.65, n=9). This suggested a particular vulnerability to smoking-related differential methylation in this region. Our work contributes to understanding how lifestyle factors affect the brain and suggests that lifestyle-related DNAm is likely to be both brain region dependent and in many cases poorly proxied for by blood. Though these pilot data provide a rarely-available opportunity for the comparison of methylation patterns across multiple brain regions and the blood, due to the limited sample size available our results must be considered as preliminary and should therefore be used as a basis for further investigation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/20239764v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@832fadorg.highwire.dtl.DTLVardef@af188eorg.highwire.dtl.DTLVardef@1753d0aorg.highwire.dtl.DTLVardef@1fa8f8f_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstract 203mm x 127mm (DPI 300) Abbreviated summary [50 words]: We apply blood-derived epigenetic signatures of lifestyle traits to matched blood and brain samples, uncovering variability in how well blood translates across brain regions and a relationship between smoking and the prefrontal cortex. Our preliminary results contribute to understanding how lifestyle-related DNA methylation affects the brain in health and disease.

1 citations