Can Ancient Urbanisation Predict Disease Resistance?

Prehistoric and modern disease rates have been difficult to compare. By finding significant correlation between urban development and an allele associated with Tuberculosis resistance, it is shown that disease rates increase significantly post-urbanisation.

Over the past ten thousand years, humans have urbanised their surroundings. A link between urbanisation and increased disease occurrence can be seen using recent and historical records, however prehistorically it is difficult to assess whether this association remains.

Getting sick is nothing new. Humans (and our evolutionary ancestors) have succumbed to viral and bacterial infections for millions of years, immunological defences within the human body fighting back against these pathogens with varying degrees of effectiveness. This variation in effectiveness is attributable to genetic differences between individuals, exposed to the same conditions.

Even though proof of disease in prehistoric humans exists¹, there are significant problems with inferring disease occurrence information from prehistoric remains. Most infections do not cause skeletal lesions or remodelling¹, compounded by the fact that there are vastly fewer human fossils from prehistoric time available² as compared to more modern remains.

Due to evolution, both pathogens and the human immune system are caught in an “arms race” of development – each side adapting in successive generations of individuals, to more effectively infect hosts or destroy invading pathogens. Writing in Evolution, Barnes et al.³ postulates that if a positive correlation between urbanisation and disease occurrence exists, this genetic “arms race” would be expected to greater select for disease resistance in urbanised areas, as compared to areas not urbanised or urbanised for less time.

In order to measure disease resistance, a polymorphic gene known to be associated with susceptibility to Tuberculosis in humans (SLC11A1)⁴, was selected for analysis. One allele of this gene (1729 + 55del4) is protective against the disease.

Seventeen populations, with a range of urbanisation histories were selected and their polymorphic state for the Tuberculosis susceptibility gene (SLC11A1) measured. In order to determine the length of urbanisation for each of the selected populations, comprehensive archaeological and historical literature was searched to locate the first description of the region as a major town or city, or for evidence of high density living.

Using numerous statistical techniques⁵, it was determined that the length of time an environment had been urbanised for significantly impacted the polymorphic state for the Tuberculosis susceptibility gene (SLC11A1), as compared to the expected frequency of polymorphism in a non-urbanised environment. This difference in allelic diversity trended towards protecting against the disease in individuals who resided in areas of longest urbanisation (see Fig. 1).

Figure 1: Percentage of protective allele & total time urbanized



A number of possibly confounding issues were taken into account by the researchers³; shared demographic histories between populations, a number of issues relating to the method of determining urbanisation length in each population, the possibility that not urbanisation length, but domestication of cattle was the correlative factor and that only “Old World” populations were sampled. Each of these issues were either shown via statistical tests to have little to no effect on correlation, or it was determined that the bias they may have, if any, would serve to weaken, rather than strengthen, correlation.

Previous to this study by Barnes et al.³, the effects of urbanisation on disease occurrence were not well understood. Understanding this relationship not only sheds light on a previously unrecognised example of selection, but helps future researchers by creating a framework that utilises historical data to explain allele frequencies and selective pressures.

The results of this study are compelling; even after numerous statistical corrections for possible biases in the datasets, significant correlation between urbanisation and disease occurrence were shown.  However, there are a number of issues with the design of the study itself. That the urbanisation length was calculated for each population by means of a best estimate, found in archaeological and historical documents is of concern; as every statistical test used this data, it is possible these estimates “seeded” the entire study with inaccuracy. Also, Barnes et al.³ mentions that the Tuberculosis susceptibility gene (SLC11A1) has been proposed to associate with autoimmune diseases, creating the possibility of balancing selection affecting the polymorphism of the gene, yet this assertion is not statistically investigated.

One of the broader comments made in the abstract of this study is that a difficulty assessing the correlation between urban living and disease occurrence in prehistoric times exists, which is not directly answered. Indirectly however, the study does well in showing a correlation between the start of urbanisation and disease occurrence, hinting at the fact that prehistoric populations, due to their lack of urbanisation, had less disease occurrence. This is not directly proven (or even mentioned) and other studies have spoken to the difficulties that research faces when attempting to answer this question^{1, 2}, but the contrast drawn in this study acts as fantastic starting point for further prehistoric research.

Further study could also be conducted to determine if modern day urban and rural populations, within the same region, differ in allele frequency for the protective allele of the Tuberculosis susceptibility gene (SLC11A1) as the resolution of individuals in the seventeen regions sampled was not granular enough to determine this.

Although the topic of disease occurrence can be unclear, especially in prehistoric time, this study has built a foundation for the novel utilisation of historical data towards scientific endeavours, allowed a glimpse into prehistoric time by contrast with the modern-day and acts as a starting point for further research.

References:

1. Wood, J.W. et al. The Osteological Paradox (Current Anthropology, 1992)
2. Roberts, C.A & Cox, M. Health and disease in Britain : from prehistory to the present day. (Sutton Publishing, 2003)
3. Barnes, I. et al. Ancient Urbanisation Predicts Genetic (Evolution, 2010)
4. Bellamy, R.C. et al. Variations in the Nramp1 gene and susceptibility to tuberculosis in West Africans (New England Journal of Medicine, 1998)
5. Cook, R.D. Detection of influential observations in linear regression. (Technometrics, 1977)