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Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of “lifestyle” diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be “mismatched” and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit “genotype by environment” (GxE) interactions, with different health effects in “ancestral” versus “modern” environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the “matched” to “mismatched” spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures. 

The “mismatch” between evolved human physiology and Western lifestyles is thought to explain the current epidemic of cardiovascular disease (CVD) in industrialized societies. However, this hypothesis has been difficult to test because few populations concurrently span ancestral and modern lifestyles. To address this gap, we collected interview and biomarker data from individuals of Turkana ancestry who practice subsistence-level, nomadic pastoralism (the ancestral way of life for this group), as well as individuals who no longer practice pastoralism and live in urban areas. We found that Turkana who move to cities exhibit poor cardiometabolic health, partially because of a shift toward “Western diets” high in refined carbohydrates. We also show that being born in an urban area independently predicts adult health, such that life-long city dwellers will experience the greatest CVD risk. By focusing on a substantial lifestyle gradient, our work thus informs the timing, magnitude, and evolutionary causes of CVD.