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What is Envirogenomics?

 
 
Envirogenomics involves understanding the relationship between environmental exposures, genomic variation and human disease.

  • Environmental exposures include agents such as toxins, microbes, medicines and dietary nutrients.
  • Genomic variation encompasses DNA sequence differences as well as related gene (and protein) expression changes and interactions.

The general principle of envirogenomics according to the above definition is that people react differently to environmental exposures because of their underlying biological make-up, and as such have varying degrees of susceptibility to disease. 

The Main Goals of Envirogenomics are to:

  • Understand the pathological consequences of environmental exposures.
  • Identify biomarkers of disease susceptibility.
  • Determine the complex interactions between environmental and genomic factors that significantly influence risk of disease.
  • Develop individualized susceptibility profiles based on a combination of genetic and environmental risk factors.

The Technologies Required for Envirogenomics Research:
 

Genomics – DNA sequence analysis (sequencing and genotyping)

Transcriptomics –Gene expression analysis (microarray and quantitative PCR)

Proteomics – Protein identification analysis (2D Gels)

Metabolomics – Functional analysis of metabolic proteins (enzyme activity assays)

Bioinformatics – computational and statistical analysis of molecular data 

Envirogenomics Projects at ESR:

  • Tobacco exposure of neuronal cells
  • Developing bioassays of tobacco smoke addiction
  • Pharmacogenomics of nicotine metabolism
  • Proteomics of Meningococcal disease
  • Pesticide exposure and male infertility
  • Homocysteine metabolism, and alcoholism
  • Genes, migraine and folate supplementation
 
Māori participation in genetic research 

 

 

 

 
Research Team:

Dr Rod Lea
Dr Phil Carter
Dr Paul Fitzmaurice
Dr Ellen Podivinsky
Dr David Slaney
Dr Penny Truman

Technology Platform:

Analytical chemistry
Chemical genetics
Genomics
Proteomics
Cellular models
Bioinformatics

Māori Health

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