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  1. Brassington L, Arner AM, Watowich MM, Damstedt J, Ng KS, Lim YAL, et al.
    Evol Med Public Health, 2024;12(1):214-226.
    PMID: 39484023 DOI: 10.1093/emph/eoae014
    More than 60 years ago, James Neel proposed the Thrifty Genotype Hypothesis to explain the widespread prevalence of type 2 diabetes in Western, industrial contexts. This hypothesis posits that variants linked to conservative energy usage and increased fat deposition would have been favored throughout human evolution due to the advantages they could provide during periods of resource limitation. However, in industrial environments, these variants instead produce an increased risk of obesity, metabolic syndrome, type 2 diabetes, and related health issues. This hypothesis has been popular and impactful, with thousands of citations, many ongoing debates, and several spin-off theories in biomedicine, evolutionary biology, and anthropology. However, despite great attention, the applicability and utility of the Thrifty Genotype Hypothesis (TGH) to modern human health remains, in our opinion, unresolved. To move research in this area forward, we first discuss the original formulation of the TGH and its critiques. Second, we trace the TGH to updated hypotheses that are currently at the forefront of the evolutionary medicine literature-namely, the Evolutionary Mismatch Hypothesis. Third, we lay out empirical predictions for updated hypotheses and evaluate them against the current literature. Finally, we discuss study designs that could be fruitful for filling current knowledge gaps; here, we focus on partnerships with subsistence-level groups undergoing lifestyle transitions, and we present data from an ongoing study with the Orang Asli of Malaysia to illustrate this point. Overall, we hope this synthesis will guide new empirical research aimed at understanding how the human evolutionary past interacts with our modern environments to influence cardiometabolic health.
  2. Lea AJ, Clark AG, Dahl AW, Devinsky O, Garcia AR, Golden CD, et al.
    PLoS Biol, 2023 Sep;21(9):e3002311.
    PMID: 37695771 DOI: 10.1371/journal.pbio.3002311
    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.
  3. Lea AJ, Clark AG, Dahl AW, Devinsky O, Garcia AR, Golden CD, et al.
    ArXiv, 2023 Feb 13.
    PMID: 36713247
    Globally, we are witnessing the rise of complex, non-communicable diseases (NCDs) related to changes in our daily environments. Obesity, asthma, cardiovascular disease, and type 2 diabetes are part of a long list of "lifestyle" diseases that were rare throughout human history but are now common. A key idea from anthropology and evolutionary biology-the evolutionary mismatch hypothesis-seeks to explain this phenomenon. It posits that humans evolved in environments that radically differ from the ones experienced by most people today, and thus traits that were advantageous in past environments may now be "mismatched" and disease-causing. This hypothesis is, at its core, a genetic one: it predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions and have differential health effects in ancestral versus modern environments. Here, we discuss how this concept could be leveraged to uncover the genetic architecture of NCDs in a principled way. Specifically, we advocate for partnering with small-scale, subsistence-level groups that are currently transitioning from environments that are arguably more "matched" with their recent evolutionary history to those that are more "mismatched". These populations provide diverse genetic backgrounds as well as the needed levels and types of environmental variation necessary for mapping GxE interactions in an explicit mismatch framework. Such work would make important contributions to our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and sociocultural contexts.
  4. Watowich MM, Arner AM, Wang S, John E, Kahumbu JC, Kinyua P, et al.
    medRxiv, 2024 Aug 26.
    PMID: 39252903 DOI: 10.1101/2024.08.26.24312234
    BACKGROUND: Many subsistence-level and Indigenous societies around the world are rapidly experiencing urbanization, nutrition transition, and integration into market-economies, resulting in marked increases in cardiometabolic diseases. Determining the most potent and generalized drivers of changing health is essential for identifying vulnerable communities and creating effective policies to combat increased chronic disease risk across socio-environmental contexts. However, comparative tests of how different lifestyle features affect the health of populations undergoing lifestyle transitions remain rare, and require comparable, integrated anthropological and health data collected in diverse contexts.

    METHODS: We developed nine scales to quantify different facets of lifestyle (e.g., urban infrastructure, market-integration, acculturation) in two Indigenous, transitioning subsistence populations currently undergoing rapid change in very different ecological and sociopolitical contexts: Turkana pastoralists of northwest Kenya (n = 3,692) and Orang Asli mixed subsistence groups of Peninsular Malaysia (n = 688). We tested the extent to which these lifestyle scales predicted 16 measures of cardiometabolic health and compared the generalizability of each scale across the two populations. We used factor analysis to decompose comprehensive lifestyle data into salient axes without supervision, sensitivity analyses to understand which components of the multidimensional scales were most important, and sex-stratified analyses to understand how facets of lifestyle variation differentially impacted cardiometabolic health among males and females.

    FINDINGS: Cardiometabolic health was best predicted by measures that quantified urban infrastructure and market-derived material wealth compared to metrics encompassing diet, mobility, or acculturation, and these results were highly consistent across both populations and sexes. Factor analysis results were also highly consistent between the Turkana and Orang Asli and revealed that lifestyle variation decomposes into two distinct axes-the built environment and diet-which change at different paces and have different relationships with health.

    INTERPRETATION: Our analysis of comparable data from Indigenous peoples in East Africa and Southeast Asia revealed a surprising amount of generalizability: in both contexts, measures of local infrastructure and built environment are consistently more predictive of cardiometabolic health than other facets of lifestyle that are seemingly more proximate to health, such as diet. We hypothesize that this is because the built environment impacts unmeasured proximate drivers like physical activity, increased stress, and broader access to market goods, and serves as a proxy for the duration of time that communities have been market-integrated.

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