From John Snow to omics: the long journey of environmental epidemiology

A major difference between infectious and non-communicable diseases is that infectious diseases typically have unique necessary causes whereas noncommunicable diseases have multiple causes which by themselves are usually neither necessary nor sufficient. Epidemiology seems to have reached a limit in disentangling the role of single components in causal complexes, particularly at low doses. To overcome limitations the discipline can take advantage of technical developments including the science of the exposome. By referring to the interpretation of the exposome as put forward in the work of Wild and Rappaport, I show examples of how the science of multi-causality can build upon the developments of omic technologies. Finally, I broaden the picture by advocating a more holistic approach to causality that also encompasses social sciences and the concept of embodiment. To tackle NCDs effectively on one side we can invest in various omic approaches, to identify new external causes of non-communicable diseases (that we can use to develop preventive strategies), and the corresponding mechanistic pathways. On the other side, we need to focus on the social and societal determinants which are suggested to be the root causes of many non-communicable diseases

Diet, genetic susceptibility and carcinogenesis

AbstractAt least six types of gene–environment interactions (GEI) have been proposed (Kouhry and Wagener, 1993) In the first type, neither the environmental exposure (EE) nor the genetic risk factor (GRF) have any effect by themselves, but interaction between them causes disease. This is the case of phenylalanine exposure and the phenylketonuria genotype. Type 2 is a situation in which the GRF has no effect on disease in the absence of exposure, but exacerbates the effects of the latter. This is the most important type of GEI in relation to metabolic susceptibility genes and human carcinogenesis. The third type is the converse of the second (EE is ineffective per se, but enhances the effect of GRF). Type 4 occurs when both EE and GRF increase the risk for disease, but the combination is interactive or synergistic: an example is the interaction between Xeroderma Pigmentosum and UV radiation. Types 5 and 6, according to the classification proposed by Kouhry, refer to cases in which the GRF is protective.The model of GEI that is emerging as the most important in chemical carcinogenesis refers to metabolic susceptibility genes. The general population can be divided into subgroups depending on their susceptibility to the action of carcinogens, based on their ability to metabolize such compounds to electrophilic, reactive metabolites (which form adducts with DNA), or, respectively, electrophobic metabolites that are excreted. The present contribution is a short review of the relevant literature, with particular emphasis on some polymorphisms involved in dietary exposures. In addition, the practical implications of genetic testing in this field are discussed

A darwinian perspective: right premises, questionable conclusion. A commentary on Niall Shanks and Rebecca Pyles' "Evolution and medicine: the long reach of "Dr. Darwin""

As Dobzhansky wrote, nothing in biology makes sense outside the context of the evolutionary theory, and this truth has not been sufficiently explored yet by medicine. We comment on Shanks and Pyles' recently published paper, Evolution and medicine: the long reach of "Dr. Darwin", and discuss some recent advancements in the application of evolutionary theory to carcinogenesis. However, we disagree with Shanks and Pyles about the usefulness of animal experiments in predicting human hazards. Based on the darwinian observation of inter-species and inter-individual variation in all biological functions, Shanks and Pyles suggest that animal experiments cannot be used to identify hazards to human health. We claim that while the activity of enzymes may vary among individuals and among species, this does not indicate that critical events in disease processes occurring after exposure to hazardous agents differ qualitatively between animal models and humans. In addition, the goal is to avoid human disease whenever possible and with the means that are available at a given point in time. Epidemics of cancer could have been prevented if experimental data had been used to reduce human exposures or ban carcinogenic chemicals. We discuss examples

March 2005, Autex Research Journal Vol. 5, No. 1, p. 55-60

Abstract Two kni:ed wool fabrics with the same cover factor, yarn count and twist were used our experiment. The only variable introduced was the mean diameter of the wools, 19.2 μm and 25.6 μm. The aim of the work was to evaluate the effect of proteolyHc enzyme treatment on the pilling behaviour of fabrics, and in parHcular on the yarn structure with different concentraHons of proteolyHc enzyme, and then the pilling behaviour was measured by using the pilling box test. The results obteined show that the proteolyHc enzyme, within given levels of concentraHon, improves the pilling behaviour of the fabrics

Causal models in epidemiology: past inheritance and genetic future

The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification) and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional uncertainty in quantifying interaction and assigning etiologic fractions to different necessary causes because of ignorance about the components of the sufficient cause

Drinking Water Salinity and Maternal Health in Coastal Bangladesh: Implications of Climate Change.

Background: Drinking water from natural sources in coastal Bangladesh has become contaminated by varying degrees of salinity due to saltwater intrusion from rising sea levels, cyclone and storm surges and upstream withdrawal of freshwater. Objective: Our objective was to estimate salt intake from drinking water sources and examine environmental factors that may explain a seasonal excess of hypertension in pregnancy. Methods: Water salinity data (1998-2000) for Dacope, in rural coastal Bangladesh, were obtained from the Centre for Environment and Geographic Information System. Information on drinking water sources, 24-hour urine samples and blood pressure were obtained from 343 pregnant Dacope women during the dry season (October 2009 - March 2010). The hospital-based prevalence of hypertension in pregnancy was determined for 969 pregnant women (July 2008 - March 2010). Results: Average estimated sodium intakes from drinking water ranged from 5 to 16 g/day in the dry season, compared to 0.6 - 1.2 g/day in the rainy season. Average daily sodium excretion in urine was 3.4 g/day (range 0.4 - 7.7 g/d). Women who drank shallow tubewell water were more likely to have urine sodium > 100 mmol/d than women who drank rainwater (OR=2.05, 95% CI: 1.11 - 3.80). The annual hospital prevalence of hypertension in pregnancy was higher in the dry season (12.2%, 95% CI: 9.5 - 14.8) than the rainy season (5.1%, 95% CI: 2.91 - 7.26). Conclusions: The estimated salt intake from drinking water in this population exceeded recommended limits. The problem of saline intrusion into drinking water has multiple causes and is likely to be exacerbated by climate change induced sea-level rise