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Using Evolutionary Biology in the Medical Sciences

  1. Michael F Antolin

Published Online: 15 JAN 2010

DOI: 10.1002/9780470015902.a0005846.pub2

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How to Cite

Antolin, M. F. 2010. Using Evolutionary Biology in the Medical Sciences. eLS. .

Author Information

  1. Colorado State University, Fort Collins, Colorado, USA

Publication History

  1. Published Online: 15 JAN 2010

Introduction

  1. Top of page
  2. Introduction
  3. Natural Selection and Human Genetic Legacies
  4. Homology and Common Descent
  5. References
  6. Further Reading

Human diseases are a reflection of the evolutionary history that shaped our genetic proclivities and physiological responses to our current environment, including the pathogenic microbes that plague us. The application of evolutionary thinking in the medical sciences has clear implications for research on proximate and evolutionary causes of disease, and may improve public health practice and care for the sick (Stearns and Koella, 2007; Wolfe et al., 2007; Nesse and Stearns, 2008). The purpose is to help medical practitioners look to the adaptations and maladaptations of both humans and pathogens. Evolutionary thinking provides a dynamic view of both infectious and genetic diseases where numerous evolutionary histories converge within individual patients, including populations of microbes on the one hand and human ancestry on the other. See also Darwinian Medicine

Variability is a hallmark of the evolutionary process: adaptations evolve by natural selection of inherited differences linked to survival and reproduction within populations, altering the characteristics of the populations over time. Genetic disease varies between human populations because both long-term population sizes and histories of natural selection determine how many disease-causing mutations they carry. Further, individual patients may present different symptoms because mutations interact with the patients’ environmental and genetic background. But pathogens also evolve, and thus infectious diseases can locally vary in prevalence and severity between populations. Understanding pathogen variability leads to public health interventions that may reduce exposure and limit chains of transmission (Galvani, 2003). For microbes, we must consider that relatively rapid generation times, high rates of mutation, genetic reassortment and horizontal gene transfer inexorably lead to emergence of new infectious diseases. Evolutionary changes will shape medical practice because of rapid evolution of resistance to antimicrobial drugs or avoidance of immune defences and vaccination strategies (Bergstrom and Feldgarden, 2007; Nesse and Stearns, 2008). This has been called our ‘arms race against an adaptable opponent’ (Lederberg, 2000). This dynamic view of disease accounts for the variability in human-adapted pathogens like influenza viruses and malaria, where evolutionary escape hinders development of vaccines with long-lasting protection. One of the greatest challenges in managing disease lies in the potential for emergence of pathogens. For example, we are well aware of the new viral influenza strains that evolve via genetic reassortment between strains in humans and reservoirs like aquatic birds in the wild and agricultural species like swine. Additional risks arise from emergence of new pathogens like the human immunodeficiency virus (HIV) and Sever acute respiratory syndrome (SARS) viruses that transfer directly from wild animals to humans. See also Avian Influenza Viruses, and Severe Acute Respiratory Syndrome (SARS)

A clear application of evolutionary thinking is in providing social support to the sick by ameliorating stigma associated with disease. The understanding by doctors that many contemporary genetic diseases and human conditions represent adaptations to previous environments – and thus mismatches with current diet and living conditions – can help explain the persistence of modern maladies like obesity, heart disease (Swynghedauw, 2004), type-2 diabetes (Diamond, 2003), breast and prostate cancer (Greaves, 2002), goiter, iodine deficiency, birth defects (Gluckman et al., 2008) and ageing (Williams and Nesse, 1991). Seeing diseases as unfortunate genetic legacies inherited from the past may alleviate grief for some patients. See also The Evolution of Fatness and Susceptibility to Obesity

Ultimately, evolutionary thinking must lead to improved diagnosis or therapies if it is to influence how medicine is practiced, especially when many within the medical field do not recognize the process of evolution (Antonovics et al., 2007; Nesse and Stearns, 2008). The link between evolutionary thinking and medicine continues to grow, an increase generally attributed to the recent influence of Williams and Nesse 1991. This kind of training in medicine was at one time provided under the subject of geographic medicine, but much of it was swept aside after the discovery of antimicrobial drugs in the 1930s and 1940s (Burnet and White, 1972; Anderson, 2004). Currently fewer than half of the medical schools consider using the limited time in their curricula on topics beyond drug resistance, pathogen virulence and natural selection (Nesse and Schiffman, 2003). Doctors will benefit from understanding the evolutionary complexities that underlie failures of drug therapies due to rapid evolution of microbes, resurgence of infectious diseases once thought conquered (e.g. polio and tuberculosis), and increasing frequency of nosocomial infections (Lederberg, 2000; Bergstrom and Feldgarden, 2007). See also Antimicrobial Resistance: Epidemiology, and Antimicrobials Against Streptococci, Pneumococci and Enterococci

Every patient has a slightly different evolutionary history, and therefore a different genetic makeup, different reactions to drugs and oftentimes different disease symptoms (e.g. Meyer, 1999). In managing health care, such differences can result in life, death or long-term morbidity. Evolutionary thinking provides a framework for connecting what may appear to be a large number of unrelated observations by linking proximate effects of disease to the context of their ultimate origins (Nesse and Stearns, 2008). Here I present a number of examples of how evolutionary thinking can influence, how medicine and public health are practiced (Williams and Nesse, 1991; Purssell, 2005; Nesse and Stearns, 2008; Naugler, 2008). Evolution has many faces that can be seen in genetics and adaptations of both humans and pathogens, and in how common descent informs medical research. Both pathogen and patient should be viewed in terms of evolutionary history, homology and trade-offs on natural selection that may cause disease.

Natural Selection and Human Genetic Legacies

  1. Top of page
  2. Introduction
  3. Natural Selection and Human Genetic Legacies
  4. Homology and Common Descent
  5. References
  6. Further Reading

As previously mentioned, some conditions and diseases may represent current mismatches to traits that evolved by natural selection in ancient environments. Evolutionary biology further suggests that diseases persist in the modern world under the kinds of trade-offs that lie at the core of functional (developmental) and genetic constraints on natural selection. An example of developmental trade-offs leading to disease is increased susceptibility to heart disease in adults in relation to periods of nutritional deficiencies and slowed growth in early childhood. The damage is potentially higher if subsequent weight gain (catch-up growth) is too rapid when better nutrition becomes available. Evolutionary biologists view this kind of phenotypic plasticity – the ability for organisms to display different phenotypes under different conditions – as potentially adaptive when each alternative provides the highest fitness in the environment in which it develops. That flexibility, however, often comes at a fitness cost when phenotype and environment are mismatched, when the correct phenotype in one environment is maladaptive in another. In the case of growth rates and body size, adult heart disease is a cost of rapid growth following nutritional stress, and should be considered during care of low birth weight or premature human babies (Bateson et al., 2004). See also Ecological Genetics

The limits on trait evolution are a particularly pressing problem in the evolution of ageing. In evolutionary biology, fitness accrues via reproductive success summed across all stages of an individual's life history. The evolutionary theory of ageing suggests that early life fitness components such as developmental rate and age of reproductive maturity incur trade-offs later in life with fitness components like fecundity and mortality. If this trade-off results from the same genes acting at both life stages, selection on early life traits will increase their frequency even while they negatively impact fitness-related traits later in life (this genetic effect has been called antagonistic pleiotropy (cf. Williams, 1957)). The role of testosterone in males provides an example. Although increased testosterone has clear benefits for maximizing male reproductive success, this may come at the expense of disease resistance because increased testosterone also reduces immune function (Bribiescas and Ellison, 2007). Higher reproductive success early in life may come at the expense of disease and morbidity later, especially if infections are chromic. Whether the negative correlation between testosterone and immune function also represents a genetic trade-off may be determined using modern genomic analyses and association studies. See also Ageing, and Aging: Genetics

But genetic diseases manifested later in life also may persist in relatively high frequency simply because their deleterious effects come after individuals had the opportunity to reproduce. Thus, these traits have never been under strong selection that would purge them from populations. Huntington chorea, a dominant genetic disease that often shows few symptoms until individuals are in their 30s is a primary example.

The evolutionary history of genes can also explain the persistence of some genetic diseases in modern populations at frequencies higher than would be predicted from their detrimental effects. They may have mediated resistance to infectious diseases that are now absent from developed countries (Hill and Motulsky, 1999). A classical example is sickle cell anaemia in North Americans of African ancestry because of resistance to malaria that evolved in Africa. It has been suggested that the high frequencies of Tay–Sachs, Gaucher and Niemann–Pick diseases in Ashkenazi populations also may reflect a history of exposure infectious diseases (tuberculosis and influenza). It should be noted, however, that racial identity (even self-identity) is not entirely equivalent with ancestry, and that understanding individual ancestries (family histories) are what actually matter for medical practice (Tishkoff and Kidd, 2004). Further, individual patients may present different symptoms because disease-causing mutations interact with the patients’ genetic (and environmental) background. See also An Evolutionary Genetic Framework for Heritable Disorders, and Balancing Selection in Human Evolution

There has been some discussion of whether symptoms of disease such as fever, cough, diarrhoea and fatigue are adaptive reactions of the human host, and thus treatment of the symptoms would be unwise (Nesse and Stearns, 2008). Reducing fever in some cases is thought to prolong courses of infection and transmission because the fever may be an adaptation to reduce replication by the pathogen. But symptoms could also be adaptations pathogens use to manipulate hosts to their benefit, in which case symptoms should be treated immediately. By analysing how medical treatments affect selection on pathogens we can distinguish two possibilities: benefit to host or benefit to pathogen. In some cases, treatment could backfire when the pathogen responds to the selection implicit in the treatment. For example, worm infections are usually treated with drugs absorbed through the intestine. The treatment selects for a change in the behaviour of the worms, which move away from the intestine and blood vessels, deeper into tissues where they can persist longer and cause greater damage (Skorping and Read, 1998). See also Coevolution: Host–Parasite

Homology and Common Descent

  1. Top of page
  2. Introduction
  3. Natural Selection and Human Genetic Legacies
  4. Homology and Common Descent
  5. References
  6. Further Reading

The concept of homology, that traits in different species have common evolutionary origins, is critical to biomedical research and development of pharmaceuticals, which are first tested on mammals like mice, rats and dogs. Promising candidates may then be tested on primates before clinical trials with human volunteers. Thus biomedical research advances by understanding that species that are phylogenetically closest to humans have the most similar genetics, physiology and immune systems and thus are reliable models for developing treatment and therapy. With deeper probing, however, we now know that homologous genes induce eye and brain development in flies, mice and humans, and limb development in mice and humans (Carroll, 1995), and may mediate effects of ageing in worms, flies and humans (Kirkwood and Austad, 2000). These discoveries further solidify the strategy of using tractable model systems to work out basic mechanisms shared with humans, in which most experiments are impossible. See also Single Nucleotide Polymorphisms in Human Disease and Evolution: Phylogenies and Genealogies

An interesting group of genes are those coding for the hundreds of cytochrome P450 enzymes that now metabolize many drugs, but originated more than 500 million years ago as enzymes used to detoxify food poisons. Homologues of these enzymes exist in worms and flies, where their biochemistry can be studied experimentally to facilitate medical research. Human populations vary in the frequency of slow- and fast-metabolizing versions of these enzymes that influence reaction to therapies. This variation among populations helps inform clinical practice by identifying groups at risk, but individual family histories and P450 enzyme profiles, when they can be obtained, are even better predictors of drug response (Meyer, 1999). See also Drug Metabolism: Evolution

End Notes
  1. Based in part on Stephen C Stearns, “Using Evolutionary Biology in the Medical Sciences”, Encyclopedia of Life Sciences.

References

  1. Top of page
  2. Introduction
  3. Natural Selection and Human Genetic Legacies
  4. Homology and Common Descent
  5. References
  6. Further Reading

Further Reading

  1. Top of page
  2. Introduction
  3. Natural Selection and Human Genetic Legacies
  4. Homology and Common Descent
  5. References
  6. Further Reading
  • Antolin MF (2009) Evolutionary biology of disease and Darwinian medicine. In: Ruse M and Travis J (eds) Evolution: The First Four Billion Years, pp. 281298. Cambridge, MA: Harvard University Press.
  • Ewald P (1994) The Evolution of Infectious Diseases. New York: Oxford University Press.
  • Nesse RM and Williams GC (1995) Why We Get Sick: The New Science of Darwinian Medicine. New York: Times Books.
  • Trevathan W, Smith EO and McKenna JJ (eds) (2008) Evolutionary Medicine and Health: New Perspectives. New York: Oxford University Press.