A5023537491- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- Brain Metastases and Treatment
- Lung Cancer Research Studies
- MicroRNA in disease regulation
- Ferroptosis and cancer prognosis
- Hepatitis B Virus Studies
- Lung Cancer Treatments and Mutations
- Hepatitis C virus research
- Epigenetics and DNA Methylation
- Glioma Diagnosis and Treatment
- Melanoma and MAPK Pathways
- Cancer Immunotherapy and Biomarkers
- Computational Drug Discovery Methods
- RNA Research and Splicing
- Gene expression and cancer classification
- Cancer-related molecular mechanisms research
- Genetic Mapping and Diversity in Plants and Animals
- Genetic Associations and Epidemiology
- HIV/AIDS Research and Interventions
- Cancer Mechanisms and Therapy
University of Bristol
2021-2024
Medical Research Council
2024
Chapel Allerton Hospital
2024
University of Leeds
2024
Leeds Teaching Hospitals NHS Trust
2024
MRC Epidemiology Unit
2023
Abstract Cognitive decline is a major health concern and identification of genes that may serve as drug targets to slow important adequately support an aging population. Whilst genetic studies cross-sectional cognition have been carried out, cognitive change less well-understood. Here, using data from the TOMMORROW trial, we investigate associations with in cognitively normal older cohort. We conducted genome-wide association study trajectories repeated measures (using generalised estimating...
Abstract Background/Objectives Glioma represents the largest entity of primary brain tumours in adults, with an overall survival less than 20% over 5 years. Glioblastoma is most frequent and aggressive glioma subtype. At present, there are few well-established pre-clinical predictors for incidence. Due to availability size prognostic studies glioma, we utilised a Mendelian randomization framework identify non-causal protein biomarkers which associated early-onset European population. Methods...
Abstract Background Genetic variants associated with molecular traits that are also liability to glioma can provide causal evidence for the identification and prioritisation of drug targets. Methods We performed comprehensive two-sample Mendelian randomisation (Wald ratio and/or IVW) colocalisation analyses on glioma. Instrumentable (QTLs P < 5 × 10−8) were identified amongst 11 985 gene expression measures, 13 285 splicing isoforms 10 198 protein abundance derived from 15 brain...
Abstract AIMS Genetic variants associated with molecular traits are also liability to glioma. We sought pro- vide causal evidence for the prioritization of these using triangulation several inference approaches. METHOD performed two-sample Mendelian randomization and genetic colocalization on Molecular data were taken from studies expression quantitative trait loci (QTL) [11,803 genes]; protein QTL [7,376 proteins] splicing [13,285 genes]) derived 15 brain tissues. Glioma a genome-wide...
Abstract Background Genetic variants associated with molecular traits that are also liability to glioma can provide causal evidence for the prioritisation of these as candidate drug targets. Methods We performed two-sample Mendelian randomisation and genetic colocalisation a large panel on glioma. Molecular data were taken from studies expression quantitative trait loci (QTL) [11,985 genes]; splicing QTL [13,285 genes] protein [7,376 proteins] derived 15 brain tissues. Glioma summary-level...
Abstract AIMS To use two-sample Mendelian Randomisation to prioritise novel genes for drug targeting in glioma risk using expression, protein and splicing quantitative trait loci (eQTLs, pQTLs sQTLs, respectively). METHOD We used genetic variants from GWAS compare the effects of eQTLs, sQTLs on liability (n=12,496). eQTL data was retrieved MetaBrain study five different brain tissues (n=108 2,970). pQTL BrainQTL dorsolateral prefrontal cortex tissue (n = 330), sQTL Genotype-Tissue Expression...