How evolutionary principles improve the understanding of human health and disease

An appreciation of the fundamental principles of evolutionary biology provides new insights into major diseases and enables an integrated understanding of human biology and medicine. However, there is a lack of awareness of their importance amongst physicians, medical researchers, and educators, all of whom tend to focus on the mechanistic (proximate) basis for disease, excluding consideration of evolutionary (ultimate) reasons. The key principles of evolutionary medicine are that selection acts on fitness, not health or longevity; that our evolutionary history does not cause disease, but rather impacts on our risk of disease in particular environments; and that we are now living in novel environments compared to those in which we evolved. We consider these evolutionary principles in conjunction with population genetics and describe several pathways by which evolutionary processes can affect disease risk. These perspectives provide a more cohesive framework for gaining insights into the determinants of health and disease. Coupled with complementary insights offered by advances in genomic, epigenetic, and developmental biology research, evolutionary perspectives offer an important addition to understanding disease. Further, there are a number of aspects of evolutionary medicine that can add considerably to studies in other domains of contemporary evolutionary studies

Evolution And Medicine In Undergraduate Education: A Prescription For All Biology Students

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91331/1/j.1558-5646.2011.01552.x.pd

An experimental search strategy retrieves more precise results than PubMed and Google for questions about medical interventions

Objective. We compared the precision of a search strategy designed specifically to retrieve randomized controlled trials (RCTs) and systematic reviews of RCTs with search strategies designed for broader purposes.Methods. We designed an experimental search strategy that automatically revised searches up to five times by using increasingly restrictive queries as long at least 50 citations were retrieved. We compared the ability of the experimental and alternative strategies to retrieve studies relevant to 312 test questions. The primary outcome, search precision, was defined for each strategy as the proportion of relevant, high quality citations among the first 50 citations retrieved.Results. The experimental strategy had the highest median precision (5.5%; interquartile range [IQR]: 0%–12%) followed by the narrow strategy of the PubMed Clinical Queries (4.0%; IQR: 0%–10%). The experimental strategy found the most high quality citations (median 2; IQR: 0–6) and was the strategy most likely to find at least one high quality citation (73% of searches; 95% confidence interval 68%–78%). All comparisons were statistically significant.Conclusions. The experimental strategy performed the best in all outcomes although all strategies had low precision