The impact of new research technologies on our understanding of environmental causes of disease: the concept of clinical vulnerability.
In spite of decades of epidemiological research, the etiology and causal patterns for many common diseases, such as breast and colon cancer or neurodegenerative diseases, are still largely unknown. Such chronic diseases are likely to have an environmental origin. However, "environmental" risks have been often elusive in epidemiological studies. This is a conundrum for current epidemiological research. On the other side, the relative contribution of genes to chronic diseases, as emerging from GWAS, seems to be modest (15-50% increase in disease risk). What is yet to be explored extensively is a model of disease based on long-term effects of low doses of environmental exposures, incorporating both genetic and acquired susceptibility ("clinical vulnerability"), and the cumulative effects of different exposures. Such a disease model would be compatible with the weak associations found by GWAS and the still elusive role of many (low-level) environmental exposures. We also propose that the introduction of "-omic" high-throughput technologies, such as transcriptomics, proteomics and metabolomics, may provide, in the next years, powerful tools to investigate early effects of environmental exposures and understand the etiology of common diseases better, according to the "clinical vulnerability model". The development of "-omics", in spite of current limitations and lack of sound validation, could greatly contribute to the elucidation of the disease model we propose.
Vineis
Paolo
P
MRC/HPA Centre for Environment and Health, Imperial College, UK. p.vineis@imperial.ac.uk
Khan
Aneire E
AE
Vlaanderen
Jelle
J
Vermeulen
Roel
R
D015415:Biomarkers; D015984:Causality; D004198:Disease Susceptibility; D004781:Environmental Exposure; D016021:Epidemiologic Studies; D044127:Epigenesis, Genetic; D055106:Genome-Wide Association Study; D006801:Humans; D013677:Medical Laboratory Science / Q000639:trends; D055432:Metabolomics; D040901:Proteomics; D012307:Risk Factors
D015415:Biomarkers