Abstract
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.
Highlights
We are still far from completely understanding the etiology and causal patterns for many common diseases, such as breast and colon cancer, or neurodegenerative diseases
Levels of e.g. ETS or air pollution is not a "cause" of cancer in itself, but because it occurs on top of pre-existing vulnerability. This could well explain why small changes in environmental exposures can have big effects, if they occur in a population of vulnerable subjects
The concept of acquired "clinical vulnerability" is related to previous insults/pathophysiological changes that predispose to disease
Summary
We are still far from completely understanding the etiology and causal patterns for many common diseases, such as breast and colon cancer, or neurodegenerative diseases. They analysed spectra from two 24-hour urine specimens for each of 4,630 participants from the INTERMAP epidemiological study, involving 17 population samples in China, Japan, UK and USA They showed that urinary metabolite excretion patterns for East Asian and western population samples, with contrasting diets, diet-related major risk factors, and coronary heart disease/ stroke rates, were significantly differentiated (P < 10(16)), as were Chinese/Japanese metabolic phenotypes, and subgroups with differences in dietary vegetable/animal protein and blood pressure. Among discriminatory metabolites, they quantified four and showed associations (P < 0.05 to P < 0.0001) of mean 24-hour urinary formate excretion with blood pressure in multiple regression analyses. Mean 24-hour urinary excretion of alanine (direct) and hippurate (inverse), reflecting diet and gut microbial activities, were associated with blood pressure [51]
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