Escott-Price, Valentina - Cardiff University

个人简介

MSc in Mathematics (1991) Department of Mathematics and Mechanics, St.Petersburg University, Russia. PhD in Statistics (2001), School of Mathematics, Cardiff University, UK. Research Assistant, School of Mathematics, Cardiff University (1998-2002). Research Assistant, Department of Psychological Medicine, School of Medicine, Cardiff University (2002-2003). Lecturer in Biostatistics and Genetic Epidemiology, Bioinformatics and Biostatistics Unit, School of Medicine, Cardiff University (2003-2005). RCUK Research Fellow, Bioinformatics and Biostatistics Unit, School of Medicine, Cardiff University (2005-2010). Senior Lecturer, MRC Centre for Neuro-Psychiatric Genetics and Genomics, School of Medicine, Cardiff University (2010-2014). Reader, MRC Centre for Neuro-Psychiatric Genetics and Genomics, School of Medicine, Cardiff University (2014-2016). Since 2016: Professor, MRC Centre for Neuro-Psychiatric Genetics and Genomics, School of Medicine, Cardiff University.

研究领域

My main research interest is to deploy the new opportunities afforded by technological advances and large sample sizes in order to contribute to identification of new risk genes and biological pathways for psychiatric and other disorders, and to undertake integrative analyses to provide additional biological meaning to the basic genetic data. As a member of several international consortia, we analyse terabytes of genome/exome/sequencing data for cohorts of tens of thousands of individuals from different populations. Being a member International Genomics of Alzheimer's Project (IGAP) consortium, we processed and analysed genome-wide data which resulted in the discovery of 11 new susceptibility loci for Alzheimer's disease. Further analysis of this data, with the approximate gene-based analysis, which we developed in 2011 in Cardiff, lead to the discovery of two additional Alzheimer's disease susceptibility genes. My most recent research is focused around evaluation of genetic risk associated with different aspects of psychiatric and neurological diseases. In our recent work we have investigated the polygenic architecture of Alzheimer's and Parkinson’s diseases and have also explored the potential relationship between an individual’s polygenic risk score and the risk of the disease.

近期论文

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Lo, M.et al. 2017. Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders. Nature Genetics 49(1), pp. 152-156. (10.1038/ng.3736) pdf Sims, R.et al. 2017. Rare coding variants in PLCG2, ABI3 and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nature Genetics pdf Lubbe, S.et al. 2016. Additional rare variant analysis in Parkinson?s disease cases with and without known pathogenic mutations: evidence for oligogenic inheritance. Human Molecular Genetics 25(24), pp. 5483-5489. (10.1093/hmg/ddw348) pdf Lubbe, S.et al. 2016. Rare variants analysis of cutaneous malignant melanoma genes in Parkinson's disease. Neurobiology of Aging 48, pp. 222.e1-222.e7. (10.1016/j.neurobiolaging.2016.07.013) pdf Morgan, A.et al. 2016. The correlation between inflammatory biomarkers and polygenic risk score in Alzheimer's Disease. Journal of Alzheimer's Disease (10.3233/JAD-160889) pdf Summers, M.et al. 2016. BRAF and NRAS locus specific variants have different outcomes on survival to colorectal cancer. Clinical Cancer Research (10.1158/1078-0432.CCR-16-1541) pdf Kun-Rodrigues, C.et al. 2016. Analysis of C9orf72 repeat expansions in a large international cohort of dementia with Lewy bodies. Neurobiology of Aging (10.1016/j.neurobiolaging.2016.08.023) pdf Rees, E.et al. 2016. Analysis of intellectual disability copy number variants for association with schizophrenia. JAMA Psychiatry 73(9), pp. 963-969. (10.1001/jamapsychiatry.2016.1831) Pardinas, A.et al. 2016. Common schizophrenia alleles are enriched in mutation-intolerant genes and maintained by background selection. bioRxiv (10.1101/068593) pdf Escott-Price, V.et al. 2016. Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease. Neurobiology of Aging (10.1016/j.neurobiolaging.2016.07.018) pdf Smith, D.et al. 2016. Genome-wide analysis of over 106,000 individuals identifies 9 neuroticism-associated loci. Molecular Psychiatry 21(6), pp. 749-757. (10.1038/mp.2016.49) pdf