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on Evolutionary Economics |
| By: | Amanda J. Lea; Angela Garcia; Jesusa Arevalo; Julien F. Ayroles; Kenneth Buetow; Steve W. Cole; Daniel Eid Rodriguez; Maguin Gutierrez Cayuba; Heather M. Highland; Paul L. Hooper; Anne Justice; Thomas S. Kraft; Kari E. North; Jonathan Stieglitz (IAST - Institute for Advanced Study in Toulouse); Hillard Kaplan; Benjamin C. Trumble; Michael Gurven |
| Abstract: | A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype–phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits. |
| Date: | 2023–01–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03925274&r=evo |
| By: | Büttner, Nicolas (ETH Zurich); Grimm, Michael (University of Passau); Günther, Isabel (ETH Zurich); Harttgen, Kenneth (ETH Zurich); Klasen, Stephan (University of Göttingen) |
| Abstract: | Despite the recent economic growth in many countries on the African continent, the region has seen a slow fertility transition. In this study, we explore whether the lack of structural economic change can explain this slow fertility transition. We create a unique panel data set combining Demographic and Health Surveys, Household Income Surveys, and nighttime light intensity data, as an indicator for industrialization, from 57 countries at the sub-national regional level over three decades to analyze the driving forces of fertility transitions across low- and middle-income countries. Our results confirm that household wealth, reduced child mortality, and female basic education are crucial for fertility reductions. Yet, our analysis also highlights the important role of increased female labor force participation in the formal sector, industrialization, increased female secondary education, and the expansion of health insurance coverage. Urbanization appears to have a limited, if any, effect. Our simulations indicate that if high-fertility countries in sub-Saharan Africa had experienced similar structural economic change as low- and middle-income countries with low fertility, their fertility levels could be up to 50% lower. |
| Keywords: | demographic transition, fertility, structural change, human capital, sub-Saharan Africa |
| JEL: | D13 J11 J13 J22 O12 |
| Date: | 2023–02 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp15966&r=evo |