I am an Epidemiologist based at the Stroke Research Group with an interest in cardiovascular disease and related conditions.
At present my work utilises genome-wide association studies (GWAS) alongside bioinformatic approaches to obtain insights in disease aetiology. This includes applying techniques such as Mendelian randomization to prioritise therapeutic targets and inform clinical or public health decision making.
More widely, I have an interest in individual participant data meta-analysis, the use of electronic health records in medical research, the application and integration of various “-omic” technologies (e.g. metabolomics, proteomics, phenomics), machine learning and modelling of longitudinal data.
* denotes joint first author, # joint last author
Junqueira, C.*, Crespo, Â.*, Ranjbar, S.*, [25 co-authors], Bell, S., Goldfeld A.E., Filbin M.R.#, & Lieberman, J.# (2022). FcγR-mediated SARS-CoV-2 infection of monocytes activates inflammation. Nature, DOI: 10.1038/s41586-022-04702-4.
Traylor, M., [8th of 39 authors], & Markus, H.S. (2021). Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies. The Lancet Neurology, 20(5), 351-361.
Sun, L.*, Pennells, L.*, Kaptoge, S.* [5th of 14 authors], Danesh, J.#, Samani, N.J.#, Inouye, M.#, & Di Angelantonio, E.# (2021). Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses. PLOS Medicine, 18(1), e1003498
Emerging Risk Factors Collaboration (6th of 31 authors). (2020). Association between depressive symptoms and incident cardiovascular diseases. JAMA, 324, 2396–2405.
Batty, G.D., Gale, C.R., Kivimaki, M., Deary, I.J., & Bell, S. (2020). Comparison of risk factor associations in UK Biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis. BMJ, 368, m131.
The WHO CVD Risk Chart Collaboration (12th of 102 authors). (2019). World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions. The Lancet Global Health, 7(10), 1332-1345.
Sun, Y-Q.*, Burgess, S.*, [3rd of 13 authors], & Mai, X-M. (2019). Body mass index and all-cause mortality in the HUNT and UK Biobank studies: Linear and non-linear Mendelian randomization analyses. BMJ, 364, I1042.
Emerging Risk Factors Collaboration (7th of 74 authors). (2019). Cardiovascular risk factors associated with venous thromboembolism. JAMA Cardiology, 4(2), 163-173.
Emerging Risk Factors Collaboration/EPIC-CVD/UK Biobank Alcohol Study Group (11th of 120 authors) (2018). Risk thresholds for alcohol consumption: combined analysis of individual-participant data on 599,912 current drinkers in 83 prospective studies. The Lancet, 391(10129), 1513-1523.
Schormair, B.*, Zhao, C.*, Bell, S.*, [45 other authors], Di Angelantonio, E.#, Hinds, D.A.#, Müller-Myhsok, B.#, & Winkelmann, J.# (2017). Identification of novel risk loci for restless legs syndrome: a meta-analysis of genome-wide association studies in individuals of European ancestry. The Lancet Neurology, 16(11), 898–907.
Bell, S., Daskalopoulou, M., Rapsomaniki, E., George, J., Britton, A., Bobak, M., Casas, J.P., Dale, C.E., Denaxas, S., Shah, A.D., & Hemingway, H. (2017). Association of clinically recorded alcohol consumption with the initial presentation of twelve cardiovascular diseases: a population-based cohort study using linked health records. BMJ, 356, j909.
Batty, G.D., Zaninotto, P., Watt, R.G., & Bell, S. (2017). Associations of pet ownership with biomarkers of ageing: population based cohort study. BMJ, 359, j5558.
Britton, A., Ben-Schlomo, Y., Benzeval, M., Kuh, D., & Bell, S. (2015). Life course trajectories of alcohol consumption in the United Kingdom using longitudinal data from nine cohort studies. BMC Medicine, 13, 47.
Bell, S., & Britton, A. (2014). An exploration of the dynamic longitudinal relationship between mental health and alcohol consumption: a prospective cohort study. BMC Medicine, 12, 91.