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The William Harvey Research Institute - Faculty of Medicine and Dentistry

Dr James Timmons

James

Reader, Translational Bioinformatics

Centre: Clinical Pharmacology and Precision Medicine

Email: j.timmons@qmul.ac.uk

Profile

ORCID iD: 0000-0002-2255-1220

James graduated from the Universities of Glasgow and Nottingham (Physiology and Pharmacology) and then spent 7yrs as a team-leader in the pharmaceutical industry (responsible for in vivo and in vitro models). He ran a team working on lead identification and leading optimisation for metabolic disease, thrombosis and atherosclerosis. He set up one of the first human clinical studies (1998) to use global transcriptomics to stratify human responses to exercise therapy and led the pharmacology for an anti-thrombotic drug nomination (2002). 

He moved to the Karolinska Institute in 2003 to re-train in RNA biology, particularly noncoding RNA. During this time his group discovered, with the Cannon lab, the developmental link between ‘brown’ adipocytes and muscle. He was appointed to Chair in Exercise Physiology (2006), first at Heriot-Watt and later at Loughborough University (2013) and a 5yr visiting Professorship at University of Stockholm (2007). In Edinburgh, his group discovered that very brief (<5min) intermittent high intensity exercise (‘HIT’) was sufficient to improve insulin action, challenging 50 years of exercise advice (work that featured in a BBC Horizon documentary). In 2011, he led a FP7 consortium that validated the principal of HIT in randomised clinical trials, and in 2019 WHO exercise guidelines were altered to reflect the work from several independent groups. As Director of Research, he led the School of Biological Sciences RAE2008 return.  

James has also held Professor posts (Research) at the Royal Veterinary College and King’s College London – running molecular physiology studies - funded by the MRC, BBSRC, NIH and Industry – while managing his EU FP7 multi-centred HIT trial. His group have used machine learning to build the first molecular classifier for cardiorespiratory adaptability in humans (2010), and the first transcriptomic multi-tissue classifier of human age (2015). In 2017, after two decades of ‘wet-lab’ activities, he decided to focus full time on bioinformatics - joining WHRI in 2021, as a Senior Fellow (Reader in Data Science). From 1998 to 2022 James has trained >20 graduate and post-doctoral scientists in industry and academia. He has an H-index of 49 (from 90, mostly first or senior authored, articles). He is a visiting Professor at the University of Miami, and a member of the Royal Society of Medicine and the Biochemical Society.

Research

I am interested in RNA biology and study the role of RNA in human aging, common chronic diseases (cardiovascular, metabolic and dementia) and exercise (as a treatment paradigm). The efficacy of exercise therapy in humans is variable, so much so that <20% of individuals demonstrate all the main health benefits. I am part of an international team, that has developed a large human exercise intervention biobank – incorporating global molecular profiling and deep physiological phenotyping. We use this to identify molecular transducers of the physiological responses to exercise. I also work on NIH funded biomarker projects, developing diagnostics and prognostics of cardio-metabolic disease and dementia. We are particularly interested in the following methodologies: 

  • The use of network strategies to study the biology of long noncoding RNAs  
  • Development of RNA pre-processing and gene-splicing methodologies 
  • Application of spatial transcriptomics to study single cell-type treatment responses 
  • Development of transcriptomic models as drug-repurposing tools 
  • Machine learning strategies to stratify human responses to exercise therapy

Key Publications

Full list of publications 

  1.  Timmons JA, Anighoro A, Brogan RJ, Stahl J, Wahlestedt C, Farquhar DG, Taylor-King JP, Volmar CH, Kraus WE and Philips SM. A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease. eLIFE. 2022. doi.org/10.7554/eLife.68832
  2. Nath M, Romaine SPR, Koekemoer A, Hamby S, Webb TR, Nelson CP, Castellanos-Uribe M, Papakonstantinou M, Anker SD, Lang CC, Metra M, Zannad F, Filippatos G, van Veldhuisen DJ, Cleland JG, Ng LL, May ST, Marelli-Berg F, Voors AA, Timmons JA and Samani NJ. Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure. Eur J Heart Fail. 2022. doi:10.1002/ejhf.2540
  3. Cen H, Hussein B, Botezelli JD, Wang S, Zhang AJ, Noursadeghi N, Jessen N, Rodrigues B, Timmons JA, and Johnson JD. Human and mouse muscle transcriptomic analyses identify insulin receptor mRNA downregulation in hyperinsulinemia-associated insulin resistance. FASEB J. 2021. DOI:10.1096/fj.202100497RR
  4. Stokes T, Timmons JA, Crossland H, Tripp TR, Murphy K, McGlory C, Mitchell CJ, Oikawa SY, Morton RW, Phillips BE, Baker S, Atherton PJ, Wahlestedt C and SM Phillips. Molecular transducers of human skeletal muscle remodeling under different loading states. Cell Reports. 2020. doi.org/10.1016/j.celrep.2020.107980
  5. Timmons JA, Volmar C, Crossland H, Phillips BE, Sood S, Janczura KJ, Törmäkangas T, Kujala UM, Kraus WE, Atherton PJ and Wahlestedt C. Longevity-related molecular pathways are subject to midlife "switch" in humans. Aging Cell. 2019. doi.org/10.1111/acel.12970
  6. Cao H, Salazar-García L, Gao F, Wahlestedt T, Wu CL, Han X, Cai Y, Xu D, Wang F, Tang L, Ricciardi N, Cai D, Wang H, Chin MPS, Timmons JA, Wahlestedt C and Kapranov P. Novel approach reveals genomic landscapes of single-strand DNA breaks with nucleotide resolution in human cells. Nature Communications. 2019. doi. 10.1038/s41467-019-13602-7.
  7. Timmons JA, Gallagher IJ, Sood S, Phillips B, Crossland H, Howard R, Kraus WE and Atherton PJ. A statistical and biological response to an informatics appraisal of healthy aging gene signatures. Genome Biol. 2019. doi: 10.1186/s13059-019-1734-z.
  8. Timmons JA, Atherton PJ, Larsson O, Sood S, Blokhin IO, Brogan RJ, Volmar CH, Josse AR, Slentz C, Wahlestedt C, Phillips SM, Phillips BE, Gallagher IJ and Kraus WE. A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease. Nucleic Acids Res. 2018 doi: 10.1093/nar/gky570.
  9. Phillips BE, Kelly BM, Lilja M, Ponce-González JG, Brogan RJ, Morris DL, Gustafsson T, Kraus WE, Atherton PJ, Vollaard NBJ, Rooyackers O, and Timmons JA. A Practical and Time-Efficient High-Intensity Interval Training Program Modifies Cardio-Metabolic Risk Factors in Adults with Risk Factors for Type II Diabetes. Front Endocrinol. 2017 doi: 10.3389/fendo.2017.00229. *Clinical Trial.
  10. Nakhuda A, Josse AR, Gburcik V, Crossland H, Raymond F, Metairon S, Good L, Atherton PJ, Phillips SM and Timmons JA. Biomarkers of browning of white adipose tissue and their regulation during exercise- and diet-induced weight loss. Am J Clin Nutr. 2016. doi: 10.3945/ajcn.116.132563. *Clinical Trial.
  11. Sood S, Szkop KJ, Nakhuda A, Gallagher IJ, Murie C, Brogan RJ, Kaprio J, Kainulainen H, Atherton PJ, Kujala UM, Gustafsson T, Larsson O, and Timmons JA. iGEMS: an integrated model for identification of alternative exon usage events. Nucleic Acids Res. 2016. doi: 10.1093/nar/gkw263.
  12. Timmons JA, Szkop KJ, Gallagher IJ. Multiple sources of bias confound functional enrichment analysis of global -omics data. Genome Biol. 2015. doi: 10.1186/s13059-015-0761-7.
  13. Sood S, Gallagher IJ, Lunnon K, Rullman E, Keohane A, Crossland H, Phillips BE, Cederholm T, Jensen T, van Loon LJ, Lannfelt L, Kraus WE, Atherton PJ, Howard R, Gustafsson T, Hodges A and Timmons JA. A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status. Genome Biol. 2015. doi: 10.1186/s13059-015-0750-x.
  14. Phillips BE, Williams JP, Gustafsson T, Bouchard C, Rankinen T, Knudsen S, Smith K, Timmons JA and Atherton PJ. Molecular networks of human muscle adaptation to exercise and age. PLoS Genet. 2013. doi: 10.1371/journal.pgen.1003389.
  15. Poulet B, Ulici V, Stone T, Pead M, Gburcik V, Constantinou E, Palmer DB, Beier F, Timmons JA and Pitsillides AA. Time-series transcriptional profiling yields new perspectives on susceptibility to murine osteoarthritis. Arthritis Rheum. 2012. doi: 10.1002/art.34572.
  16. Timmons JA, Baar K, Davidsen PK and Atherton PJ. Is irisin a human exercise gene? Nature. 2012. doi: 10.1038/nature11364.
  17. Keller P, Vollaard NB, Gustafsson T, Gallagher IJ, Sundberg CJ, Rankinen T, Britton SL, Bouchard C, Koch LG and Timmons JA. A transcriptional map of the impact of endurance exercise training on skeletal muscle phenotype. J Appl Physiol. 2011. 110(1):46-59. doi: 10.1152/japplphysiol.00634.2010.
  18. Timmons JA, Wennmalm K, Larsson O, Walden TB, Lassmann T, Petrovic N, Hamilton DL, Gimeno RE, Wahlestedt C, Baar K, Nedergaard J and Cannon B. Myogenic gene expression signature establishes that brown and white adipocytes originate from distinct cell lineages. Proc Natl Acad Sci U S A. 2007 doi: 10.1073/pnas.0610615104.

Sponsors

My research has benefited from the following sources of funding:

Collaborators

Internal: Paul ChappleStavroula Kanoni; Peter McCormickGavin Giovannoni; Alastair Noyce

External: Professor William Kraus (Duke University); Professor Stuart Phillips (McMaster University); Professor Claes Wahlestedt (University of Miami); Professor Nilesh Samani (University of Leicester); Professor Bethan Phillips (University of Nottingham); Professor James Johnson (University of British Columbia); Professor Phillip Atherton (University of Nottingham); Professor Andrew Pitsillides (University of London); Associate Professor Claude Volmar (University of Miami); Associate Professor Iain Gallagher (Napier University Edinburgh); Associate Professor Mintu Nath (University of Aberdeen)

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