Professor Andrew Wood (he/him)

About me:

I am an associate professor in statistical genetics and health data science. My work focusses on the analysis of population-based studies, such as the UK Biobank, to investigate the genetic architecture of common diseases and related phenotypes. My phenotypic interests include type 2 diabetes, glycemic traits, anthropometric traits, sleep, and gene expression levels. In addition I am also interested in the underlying genetic architecture of complex traits and models underlying specific genetic associations.

My experience as a statistical geneticist with a background in computer science enables me to develop and apply computations methods and technologies to "Big Data" sets to elucidate the role of genetics for complex traits. I am interested in the development of computational and statistical methods used in the analysis of genetic and phenotypic data. This includes machine learning and metaheuristic-based methods.

I was previously a visiting fellow at the Big Data Institute, University of Oxford.

Current affiliations:

Turing Fellow, The Alan Turing Institute

Some recent publications include:

A Saturated Map of Common Genetic Variants Associated with Human Height from 5.4 million Individuals of Diverse Ancestries. Yengo L*, Vedantam, S., Marouli, E. +625 authors, Wood A.R.*, Viscsher P*., Hirschhorn, J. *. Nature 610, 704-712 (2022).

The impact of Mendelian sleep and circadian genetic variants in a population setting. Weedon, M.N., Jones S.E., Lane, J.M., Lee, J, Ollila H.M.,, Dawes, A., Tyrrell, J., Beaumont, R.N., Partonen, T., Merikanto, I., Rich, S.S., Rotter, J.I., Frayling, T.M., Rutter, M.K., Redline, S., Sofer, T., Saxena, R., Wood, A.R. PLoS Genet. 18(9):e1010356 (2022).

Awards:

2021 Academy of Medical Sciences Springboard Award

2017 European Foundation for the Study of Diabetes Rising Star Award

2017 ASHG/Charles J. Epstein Trainee Awards for Excellence in Human Genetics Research Semi-finalist

Interests:

I am statistical geneticist interested in the analysis of population-based studies to investigate the role of genetic variation inolved in aetiology of common diseases and variation on quantiative traits. My phenotypic interests include type 2 diabetes, glycemic traits, anthropometric traits and gene expression levels.

I apply the latest statistical/computational analysis methods and technologies (inc. whole-genome sequencing) to further the understanding. I am also interested in the development of computational and statistical methods used in the analysis of genetic data.

Qualifications:

2009-2013: PhD - Next Generation Genome-wide Association Studies for Complex Human Quantitative Traits, Peninsula College of Medicine and Dentistry

2006-2007: MRes Bioinformatics, University of Exeter

2003-2006: BSc (hons) Computer Science, University of Exeter

Career:

Keynote: Using wearable devices and genetics to estimate and validate mechanisms of sleep, British Sleep Society, 21st November 2019, Birmingham UK

Platform: "Using wearable devices and genetics to estimate and validate mechanisms of sleep", Health Data Science, 12 June 2019, Hinxton Wellcome Genome Campus, UK

Platform: "Gene x “lifestyle” interactions in the UK Biobank: Evidence that physical inactivity and sleep inefficiency accentuate the genetic risk of obesity", American Diabetes Association, 22nd June 2018, Orlanda, USA.

Invited Speaker, "The genetics of accelerometer-derived sleep characteristics", Big Data Institute, 21st May 2018, Oxford, UK.

Platform: European Association for the Study of Diabetes, Rising Star Symposium, 15th September 2017, Lisbon, Portugal.

Platform: "Gene x environment interactions in the UK Biobank: Evidence that physical inactivity and sleep inefficiency accentuate the genetic risk of obesity", American Society of Human Genetics, 20th October 2017, Orlando, USA.

Platform: "Detecting deviation from polygenic modes of inheritance in the extreme
tails of human complex traits", Probabilistic Modeling in Genomics 2016, University of Oxford.

Platform: "Imputation of rare variants from the new Haplotype Reference Consortium identifies associations missed by 1000 Genomes", American Society of Human Genetics, 9th October 2015, Baltimore, USA,

Platform: "Analysis of variants obtained through whole-genome sequencing provides an alternative explanation to apparent epistasis", American Society of Human Genetics, 21st October 2014, San Diego, USA,

Platform: "An alternative explanation to apparent epistasis", The 1000 Genomes Project and Beyond, 25th June 2014, Churchill College, Cambridge, UK,

Platform: "Low-pass whole-genome sequencing in Europeans identifies multiple low frequency-large effect associations", American Society of Human Genetics, 23rd October 2013, Boston, USA

Poster: "Deep whole-genome sequencing in pedigrees to quantify the contribution of private variants to type 2 diabetes and related metabolic traits", Genomics of Common Disease, Keble College, Oxford, 9th September 2013.

Poster: "Low-pass whole-genome sequencing in Europeans identifies multiple low frequency-large effect associations", Genomics of Common Disease, Keble College, Oxford, 8th September 2013.

Poster: "Defining the role of common variation in the genomic and biological architecture of adult human height", Genomics of Common Disease, Keble College, Oxford, 8th September 2013.

Platform: "Deep whole-genome sequencing in pedigrees to quantify the contribution of low frequency, rare and private variants to Type 2 Diabetes and related glycemic traits", EASD-SDDG, 3rd May 2013, Malmo, Sweden.

Poster: "1000 Genomes imputation identifies low frequency-large effect circulating biomarker associations undetected by HapMap based imputation", American Society of Human Genetics, 7th November 2012, San Francisco, USA.

Platform: "Genome-wide association studies (GWAS) for height variations: where are we now?", Symposium, European Society of Paediatric Endocrinology, 22nd September 2012, Leipzig, Germany.

Platform: "1000 Genomes Imputation Identifies Low-Frequency, Large-Effect Biomarker Associations", 1000 Genomes Community Meeting, 13th July 2012, Ann Arbor, Michigan, USA.

Platform: "Deep sequencing to identify variants associated with diabetes and diabetes related traits", European Society of Human Genetics, 23rd June 2012, Nuremberg, Germany.

Platform: "Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association", Lenna Peltonen School of Human Genetics", Tuesday 9th August 2011, Sanger Institute, Hinxton, Cambridge, UK.

Poster: "Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association", Genomics of Common Diseases, August 2011, Sanger Institute, Hinxton, Cambridge, UK.

Platform: "Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association", American Society of Human Genetics, Wednesday 13th October 2011, Montreal, Canada.

Poster: "Common genetic variants associated with fasting glucose in Europeans have similar effects in South Asian individuals from Pakistan", American Society of Human Genetics, Washington D.C., USA.

Platform: "Complete Genomics: the Exeter experience", Complete Genomics Forum, 12th October 2010, San Francisco, USA.