FRS, FMedSci, FRCP (Hon), PhD
Professor of Precision Medicine
JDRF/Wellcome Diabetes and Inflammation Laboratory (DIL)
John Todd is Professor of Precision Medicine at the University of Oxford, Director of the JDRF/Wellcome Diabetes and Inflammation Laboratory (DIL) at the Wellcome Centre for Human Genetics and an Emeritus Senior Investigator of the National Institute for Health Research. Until 2016 he was Professor of Medical Genetics at the University of Cambridge and prior to this, Professor of Human Genetics and a Wellcome Trust Principal Research Fellow at the University of Oxford. He helped pioneer genome-wide genetic studies in common diseases and then went on to study the associations between mapped genomic disease-associated regions and phenotypes by founding and deploying the Cambridge BioResource. His research in genetics and diabetes has been recognised by several awards and prizes.
In the latest phase of research, to translate basic genetic and immunological knowledge to treatment and prevention, the DIL has now completed its first two mechanistic, statistically adaptive, drug dose-finding studies in T1D patients. The lab is now ready to test the possibility of using subcutaneous administration of ultra-low doses of IL-2 to preserve pancreatic islet beta-cell function to treat and prevent T1D. They are also investigating which T1D risk regions affect beta-cell function and fragility and are part of an international trial to prevent the autoimmunity that causes T1D in newborn children using daily oral insulin (“POInT”). They are applying the latest single-cell, mass spectrometry methods, bioinformatics and statistical methods to their basic and translational research.
Further details about the DIL: The DIL is led by John Todd (Director) and Linda Wicker (Co-Director). We are researching the causes of the autoimmune disease type 1 diabetes (T1D) in order to treat and prevent the disease by modulating the causative pathways. We achieve this by linking genetic determinants of disease with phenotypes and pathways in cells and in patients, using a wide range of molecular, metabolic, immunological, computational and statistical approaches.
Genetics: identification of T1D genes and their pathways is essential for understanding the biology underpinning disease susceptibility. We are integrating the latest and emerging genomics data - genetic variation, RNA and protein gene expression, methylation, transcription factor binding sites and chromatin phenotypes – to better define the T1D causal genes.
Phenotypes and mechanisms: identify aberrant cellular interactions and pathways caused by susceptibility genes that mediate a loss of immune tolerance to insulin-producing beta cells culminating in their destruction. These will provide potential targets for therapeutic intervention, as demonstrated by our work in the IL-2 pathway. This knowledge will contribute to understanding cell interactions altered by disease genes, an essential step for prioritizing potential immune-modulating agents to be investigated in experimental studies in T1D patients.
Experimental medicine: our hypothesis is that determination of the optimal dosing regimen of a potential therapeutic in terms of its molecular and cellular responses in vivo will greatly improve the likelihood of a beneficial outcome in future clinical trials. We are testing the utility of this approach in the ongoing investigation of the effects of ultra-low doses of IL-2 in patients with T1D, and will consider and evaluate other potential therapeutics. Secondly, we are part of an randomised control trial for primary prevention T1D in children in the population by feeding newborn children oral insulin every day for three years to promote immune tolerance to insulin, the primary autoantigen in T1D. Thirdly, we are planning investigation of the enhancing the healthy state, including improving tolerance to insulin through cross reactivity with a commensal antigen that we have discovered, of the intestinal microbiome using combinations of bacterial probiotics and prebiotics, in the context of deep microbiome genome sequencing and interactions with the HLA class II genotypes that increase and decrease risk of autoimmune responses to insulin and to T1D.
A blood atlas of COVID-19 defines hallmarks of disease severity and specificity
Ahern DJ. et al, (2021)
SARS-CoV-2 within-host diversity and transmission
Lythgoe KA. et al, (2021), Science, 372, eabg0821 - eabg0821
Analysis of overlapping genetic association in type 1 and type 2 diabetes.
Inshaw JRJ. et al, (2021), Diabetologia
In vivo negative regulation of SARS-CoV-2 receptor, ACE2, by interferons and its genetic control
Ansari MA. et al, (2021), Wellcome Open Research, 6, 47 - 47
Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics.
Ghoussaini M. et al, (2021), Nucleic acids research, 49, D1311 - D1320