September 01 2016 Thursday 12:26 PM
Modified Date 01-Sep-2016

Molecular epidemiology is one of the most exciting and important areas of research leading into the 21st century. It represents a critical link between the Human Genome Project http://www.ornl.gov/TechResources/Human_Genome/home.html  and medicine/public health. Without well-designed population-based molecular epidemiology studies, it will be impossible to interpret the risk of disease associated with the presence of newly identified susceptibility genes. As a result, molecular epidemiology is essential for the development of medical diagnostics, public health prevention strategies and discussions of the ethical, legal and social issues related to the evolution of the Human Genome Project.

 

Note: human genome project was recently completed, and for the first time the human genome was identified

Author: Jan Dorman, PhD University of Pittsburgh Associate Dean for Research, Nursing School (she also is my wife) http://www.pitt.edu/~super1/lecture/lec0131/005.htm

Many of us in epidemiology that the future of epidemiology was to integrate the genetic markers into epidemiology, to truly understand the etiology of disease, leading to “precision prevention”. When the human genome was sequenced we expected to see relative risk for genetic markers over 10 for chronic diseases like CHD, Cancer or Diabetes.  Disappointingly this has not happened.  Instead huge sample sized studies have found relative risks only in the 1.1 range, with the attributable risk very small. 

It is still our dream to find markers with high levels of sensitivity and specificity, as with these would could then identify those people who are best helped by physical activity smoking, or cholesteral management.

It is ironic that a very crude measure of genetics for chronic diseases, that of asking people if they have a family history of chd, or diabetes, has a relative risk of 6, in contrast with almost all genetic markers having relative risks well below 1.3.  This is one of the most perplexing questions to which epidemiologists are addressing.

In the past for one chronic disease, Type 1 diabetes, Dr. Trucco and Dorman found that the relative risk of a specific marker was over 100. Amazingly there was a very high correlation of the prevalence of this marker to the incidence of disease world wide.  This was one of the first efforts to link a specific genetic marker to registry incidence data.

Why is it that for this chronic disease the RR is huge, and the relationship to prevalence of genetic markers is so high, but this is not seen for other chronic diseases.  This is perhaps the major enigma for chronic disease epidemiology today.

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