Colloquium papers: Natural selection in a contemporary human population

Abstract

Our aims were to demonstrate that natural selection is operating on contemporary humans, predict future evolutionary change for specific traits with medical significance, and show that for some traits we can make short-term predictions about our future evolution. To do so, we measured the strength of selection, estimated genetic variation and covariation, and predicted the response to selection for women in the Framingham Heart Study, a project of the National Heart, Lung, and Blood Institute and Boston University that began in 1948. We found that natural selection is acting to cause slow, gradual evolutionary change. The descendants of these women are predicted to be on average slightly shorter and stouter, to have lower total cholesterol levels and systolic blood pressure, to have their first child earlier, and to reach menopause later than they would in the absence of evolution. Selection is tending to lengthen the reproductive period at both ends. To better understand and predict such changes, the design of planned large, long-term, multicohort studies should include input from evolutionary biologists.

Fig. 1.

TC between the ages of 20 and 60, 1955–2003. Because the measurement of TC changes with the age of the individual and the year of measurement, we fitted a surface to all measurements, calculated the residuals of all of the measurements for each individual from this surface, and expressed the trait measurement as a single value: the average of the residuals. We only used individuals who had been measured at least three times (n = 2,227 women measured 16,516 times for TC, with one individual’s measures from each cohort added for reference).

Fig. 2.

LRS, by year of birth, for women in the FHS. To deal with secular demographic change, we divided the data into six periods and divided the relative reproductive success of each woman by the mean reproductive success of the women in her group.

Fig. 3.

Plot of average cholesterol values against LRS. Residuals from the surface in Fig. 1 were converted back to the original metric by adding the global mean to each value and then averaged to yield a single average residual estimate for each woman. A cubic spline [using glms40 (25)] was then fitted to these residuals, which have the effects of age and year of measure removed, to give a visual impression of the variation in the data and the strength of selection. The cubic spline is not the linear selection gradient. Dashed lines are ± 1 SE of fitness associations (solid line).