The diseases associated with insulin
resistance (type 2 diabetes, hypertension, hyper-lipidaemia,
obesity and coronary heart disease) represent dominant quarters of
premature death and disability.
in conjunction with Queen Mary and Westfield College London, Cambridge University
and Oxford University has been awarded a £5.4
million collaborative program grant funded by the Wellcome
Trust Functional Genomics Development Initiative.
The programme designated a
Biological Atlas of Insulin Resistance, or BAIR, will be implemented by
international investigators with expertise in insulin signalling, rodent
gene targeting, human genetics, emergent -omics (metabonomics, proteomics, transcriptomics)
bioinformatics, and structural biology.
The BAIR programme will evaluate
the major unresolved questions concerning the molecular basis of insulin
action and insulin resistance using existing a novel
functional genomic strategies. Resources and analytical tools
available through the genome project make a systematic molecular
description of normal and disordered insulin action an achievable goal.
Examination of existing and novel
rodent models of insulin resistance with the full range of these tools and
bioinformatics will provide a multidimensional view of the pathogenesis of
insulin resistance, more precise nosological
classification and improved opportunities for targeted prevention and
treatment of associated human diseases.
The consortium's access to extensive clinical cohorts
allows findings from these studies to be related directly to human health.
Background for the project
Defective action of the hormone
insulin, called insulin resistance, lies at the centre of a group of common
human diseases, including late-onset diabetes, obesity, high blood pressure
and coronary heart disease.
These disorders are dominant
causes of ill health and premature death and their frequency is increasing
rapidly in affluent societies. Western lifestyles, principally inactivity
and obesity, contribute to development of insulin resistance, but modifying
these risk factors has proved difficult.
Our understanding of the inherent
biological processes that cause insulin resistance is limited. This lack of
knowledge has restricted strategies for effective prevention and treatment.
In this programme of research, we
shall use the new technologies of the genome project to generate a
comprehensive description of several well-defined states of insulin resistance
in rodent models. We refer to this body of data as a "Biological Atlas
of Insulin Resistance".