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Wellcome Trust Centre for Human Genetics

Translating gene identification into biological and clinical advances

 The identification of genes involved in susceptibility to diabetes is purely a means to an end. As accidents of nature, causal and susceptibility genes provide tools that we can use to unravel the pathogenesis of diabetes, as well as opportunities for translation of the findings into improved clinical care (through for example identification of novel therapeutic and/or preventative opportunities OR improved diagnostics for risk stratification and therapeutic targeting). The genes identified through our own or others’ research efforts (once confirmed as real through extensive replication studies) require detailed further studies using a range of complementary approaches. We are well-placed to undertake studies in a variety of areas including:

  • Epidemiological: studies of variants in the population context (in birth cohorts and other less-selected samples), including robust measures of population effect, evidence for gene-gene interaction and gene-environment interaction (the latter as part of the INTERACT consortium), and understanding of clinical consequences
  • Physiological: studies of the physiological consequences of genetic variants to aid understanding of the aetiological pathways through: analysis of intermediate trait data in families and cohorts; targeted integrative physiology in groups recruited-by-genotype; genomic analyses in urine, blood, fat.
  • Functional: studies of the molecular and cellular consequences of gene dysfunction in in vitro and in vivo systems, with particular local expertise in studies of fat, liver and beta-cell function, and access to suitable vertebrate and invertebrate animal models.
  • Therapeutics: studies of the consequences of gene variants for therapeutic response using clinical trial data and health-service prescription data, and experimental studies in man;
  • Clinical: evaluation of the value of molecular diagnostics for diabetes based on combinations of clinical and genetic data, their validation, and, if appropriate, implementation.

 

 

 

 

 

 

 
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