Genes contain the instructions needed for a cell to make molecules called proteins, which perform various roles in the body. Different variants of a gene can affect how the protein works, and in some cases, can increase a person’s risk to develop certain diseases.

For example, people who carry a version of the apolipoprotein E gene called APOE4 have a greater risk of developing Alzheimer’s disease or heart disease. Individuals with two copies of this genetic variant have a 45% higher risk of heart disease and 12 times higher risk of Alzheimer’s disease. Studies in industrialized countries suggest this increased risk may be the result of higher cholesterol and inflammation in people with APOE4. But if APOE4 is harmful, why does it continue to be so common worldwide?

One potential explanation is that APOE4, which has been around since before modern humans, may be beneficial in some contexts. Cholesterol is essential for many vital tasks in the body. In physically demanding environments where parasitic infections are common – conditions similar to those experienced by early humans – APOE4 might be beneficial. Under those circumstances, having more cholesterol might help fuel metabolic activities, fight infections, or reduce inflammation caused by infections.

Garcia et al. investigated the link between the APOE4 genetic variant, cholesterol and inflammation in 1,266 Indigenous Tsimane people from 80 villages in Bolivia. Tsimane people live an active lifestyle foraging and farming for food. Parasite infections are a common problem in their communities, but obesity rates are very low. Garcia et al. found that Tsimane people with at least one copy of the APOE4 have lower levels of inflammation and higher levels of cholesterol than those who have two copies of the APOE3 version of the gene. Very lean people with APOE4 had especially high levels of the so called “bad” low density lipoprotein (LDL) cholesterol compared to people with APOE3 only. However, in this situation, storing a little extra cholesterol may not be so bad.

The findings contradict other studies that have linked obesity to higher LDL levels and APOE4 to higher levels of inflammation. For the majority of human history, humans lived in more physically strenuous and calorically restrictive environments, with less access to clean water. Garcia et al. suggest that the harmful effects of APOE4 seen in studies in more industrialized societies – where people tend to be more sedentary and have less exposure to pathogens – may reflect a mismatch between a person’s environment and their genes. More studies that capture the diversity of environmental conditions under which people live will help clarify the role of APOE4 health and disease.

The apolipoprotein E4 (APOE4) allele is considered a major shared risk factor for both cardiovascular disease (CVD) (Hansson and Libby, 2006) and Alzheimer’s disease (AD) (Belloy et al., 2019; Smith et al., 2019), in part due to its role in lipid metabolism and related inflammation (Huebbe and Rimbach, 2017). APOE4+ carriers consistently show higher levels of total cholesterol, low-density lipoprotein (LDL), and oxidized LDL (Safieh et al., 2019; Yassine and Finch, 2020). While some studies suggest APOE4+ carriers have higher inflammatory responses (Gale et al., 2014; Olgiati et al., 2010), the APOE4 allele is also associated with downregulation of aspects of innate immune function, including acute phase proteins (Lumsden et al., 2020; Martiskainen et al., 2018; Vasunilashorn et al., 2011), and toll-like receptor (TLR) signaling molecules (Dose et al., 2018).

APOE, lipids, and immune function may interact differently in contemporary obesogenic post-industrial contexts compared to environments where infections are prevalent. For instance, a prospective U.S.-based cohort study (Framingham Heart Study) found that individuals with APOE4 and low-grade chronic obesity-related inflammation had higher risk of developing AD, with earlier onset than APOE3/3 and APOE4+ carriers without inflammation (Tao et al., 2018). By contrast, APOE4 may protect against cognitive loss among those infected with parasites (Oriá et al., 2005; Trumble et al., 2017) and accelerate recovery from viral infection (Mueller et al., 2016).

These findings suggest that interactive influences of APOE4, lipids, and immune function on disease risks may be environmentally moderated. However, this is difficult to test because most biomedical research is conducted in controlled laboratory settings using animal models, or in post-industrial populations with low-pathogen burden and high obesity prevalence (Gurven and Lieberman, 2020). Here, we begin to fill this gap by evaluating both immune and lipid profiles of individuals with APOE3/3 and APOE4+ genotypes living in a pathogenically diverse, energy-limited environment.

Hypothesis and aims

In pathogenically diverse environments, innate immune defenses are likely to be activated owing to more frequent encounters with novel pathogens. This more diverse pathogenic setting may increase selective pressure to favor stronger immune regulation. We hypothesize that in such a context, an APOE4 variant is less harmful because it (a) minimizes damage caused by chronic innate inflammation and (b) maintains higher circulating cholesterol levels, which buffer energetic costs of pathogen-driven innate immune activation. In post-industrial contexts, where there is a relative absence of diverse pathogens and thus reduced pathogen-mediated lipid regulation, coupled with an overabundance of calories, the effect of APOE4 on circulating lipids may instead incur a cost. Lifestyle factors that promote obesity and excessive circulating lipids may lead to sterile endogenous inflammation (Trumble and Finch, 2019) that overshadows any potentially positive effects of APOE4 on immune function. Thus, the APOE4 variant has greater potential to lead to hyperlipidemia and coincide with related inflammatory diseases in high-calorie, low-pathogen, environments (Figure 1).

Figure 1

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This study describes the immunophenotypes and lipid profiles of individuals with APOE3/3 and APOE4+ genotypes living in a pathogenically diverse, energy-limited environment. For the purpose of hypothesis testing, we focus on testing genotype-related differences in components of innate immunity (CRP, neutrophils, eosinophils, and erythrocyte sedimentation rate [ESR]) and blood lipids linked to inflammation (total cholesterol, LDL, and oxidized LDL [ox-LDL]). We evaluate the extent to which body mass index (BMI) moderates the association between lipids and innate inflammation (CRP, neutrophils, ESR). Finally, we test whether the APOE4 allele has a moderating effect on the relationship between BMI and lipids to evaluate the role of APOE4 in the maintenance of stable lipid levels under energetic restriction.

This research focused on the Tsimane, an Amerindian population in the Bolivian tropics that faces high exposure to a diverse suite of pathogens, and endemic helminthic infections. Tsimane have high rates of infection across all ages, with 70% helminth prevalence and >50% of adults with co-infections from multiple species of parasite or protozoan (Blackwell et al., 2015; Garcia et al., 2020). Compared to U.S. and European reference populations, the Tsimane have also been found to have upregulated immune function across the life course (Blackwell et al., 2016). In most villages, there is little or no access to running water or infrastructure for sanitation (Dinkel et al., 2020). The Tsimane are primarily reliant on foods acquired through slash-and-burn horticulture, fishing, hunting, gathering, and small animal domestication, supplemented with market goods (e.g. salt, sugar, cooking oil) (Kraft et al., 2018). Tsimane are rarely sedentary, instead engaging in sustained low and moderate physical activity over much of their life course (Gurven et al., 2013), and have minimal atherosclerosis (Kaplan et al., 2017). However, with greater globalization and improvements in technology, the Tsimane are experiencing ongoing lifestyle changes; there is variation in participation in the market economy, and related variation in diet (e.g. access and uptake of processed foods) and activity level. Despite increasing access to markets and towns, infections remain the largest source of morbidity (Gurven et al., 2020).

Data include APOE genotype and multiple measurements of BMI, lipids, and immune markers in 1266 Tsimane adults. Mixed effects multiple regression models were used to accommodate for multiple measurements per individual for some biomarkers, as well as community-level differences in pathogen exposures. Leveraging multiple observations per individual over time should better capture individuals’ average levels, and minimize the potential of single or few outliers driving results. Models also include covariates which adjust for age, sex, seasonality, and current infection (WBC >12 × 10⁹/L) (see Materials and methods for details). The sample is 50% female and includes individuals from 80 villages. The mean ± SD age of the sample is 54 ± 11 years (range: 21–93). Mean ± SD BMI is 24 ± 3 for both sexes; Tsimane adults are relatively short (women: 150.5 ± 4.8 cm; men: 161.7 ± 5.3 cm) with low body fat (median body fat percentage for men and women is 18% and 26%, respectively). Prevalence of obesity is relatively low (10%). In general, blood immune biomarkers vary significantly across adult ages (Supplementary file 1; Figure 2). Table 1 provides a full description of lipid and immune levels of individuals by APOE genotype.

Figure 2

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In our sample, 21.2% have at least one APOE4 allele; 245 individuals are heterozygous 3/4, and 23 are homozygous 4/4. The remaining 78.8% (n = 998) are homozygous for APOE3/3. Overall frequency of the APOE4 allele is 11.5%. The APOE2 allele was absent. Throughout the rest of the paper, APOE genotype is defined categorically, binning individuals as homozygous APOE3 (E3/3) or as APOE4+ carriers (if they had at least one copy of the APOE4 allele). Heterozygous and APOE4 homozygotes were binned together due to the small number of homozygotes (1.8% of total sample, and thus too small of a group for adequately powered statistical tests).

Characterization of lipid and immune profiles by APOE genotype

Relative to APOE3/3 homozygotes, APOE4 carriers have higher BMI (β = 0.15 [CI: 0.02–0.28], p = 0.02), total cholesterol (β = 0.15 [CI: 0.04, 0.27], p = 0.009), and oxidized LDL (β = 0.16 [CI: –0.00, 0.32], p = 0.05), yet lower levels of innate immune blood biomarkers: CRP (β = –0.29 [CI: −0.44,–0.14], p < 0.001), eosinophils (β = –0.16 [CI: −0.24,–0.08], p < 0.001) (Table 1, Figure 3). Similarly, in constrained models that excluded all individuals with CRP >10 mg/L and >5 mg/L, APOE4 carriers maintained lower levels of CRP relative to APOE3/3 homozygotes (β = –0.23 [CI: −0.38,–0.09], p < 0.001; β = –0.22 [CI: −0.36,–0.08], p = 0.002, respectively). Adjusting for multiple testing, CRP (FDR adj. p < 0.001) and eosinophils (FDR adj. p < 0.001) remain significantly different between APOE genotypes. APOE4 is also associated with a lower eosinophil to lymphocyte ratio (β = –0.14 [CI: −0.23,–0.05], p = 0.001) and lower total leukocytes (β = –0.08 [CI: −0.15,–0.01], p = 0.02), but not with LDL, high-density lipoprotein (HDL), or triglycerides (Figure 3—figure supplement 1). Full models shown in Supplementary file 1b-e.

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Does BMI moderate the association between lipids and inflammation?

For Tsimane with higher (>28) BMI, total cholesterol and LDL did not associate with CRP; however, for individuals with median (21 ≤ BMI ≤ 28) or low (<21) BMI, higher total cholesterol and LDL associate with lower CRP (Figure 4). When considered as a continuous variable, BMI significantly moderates these associations (total cholesterol: β = 0.15 [CI: 0.08, 0.21], p < 0.001; LDL: β = 0.16 [CI: 0.10, 0.22], p < 0.001). BMI also interacts with ox-LDL (β = 0.14 [CI: 0.08, 0.19], p < 0.001) in predicting CRP; however, this relationship is distinct from the other lipids tested. For Tsimane with high BMI, ox-LDL positively associates with CRP, while for those with low BMI the inverse is true (Figure 3C). For ESR, total cholesterol (β = 0.05 [CI: 0.01, 0.08], p = 0.008) and LDL (β = 0.03 [CI: –0.00, 0.07], p = 0.07) positively associate with ESR only among Tsimane with higher BMIs. After adjusting for multiple testing, relationships between cholesterols and CRP all remain significant (all FDR adj. p < 0.001), as does the relationship between total cholesterol and ESR (FDR adj. p = 0.02).

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Concerning independent relationships, there are no direct relationship between ox-LDL and CRP, whereas higher total cholesterol and LDL are associated with lower CRP (total cholesterol: β = –0.13 [CI: −0.20,–0.05], p < 0.001; LDL: β = –0.11 [CI: −0.18,–0.03], p = 0.006) (Figure 4—figure supplement 1). Total cholesterol is also negatively associated with ESR (β = –0.06 [CI: −0.10,–0.02], p = 0.002). There are no independent or interactive relationships between BMI, cholesterols, and neutrophils. For full models, see Supplementary file 1f-h.

Does APOE genotype moderate the association between BMI and lipids?

Finally, we assess whether APOE genotypes differentially moderate associations between cholesterol and BMI for lean and high BMI individuals. To evaluate the effects of the APOE4 allele on lipid levels across the range of BMI, we added an interaction term between BMI and APOE genotype to the mixed effects linear regression models assessing relationships between BMI and lipids (Table 2). These analyses show that APOE4 carriers maintain similar levels of total cholesterol and LDL across BMIs (cholesterol: β = –0.08 [CI: −0.18,–0.02], p = 0.11; LDL: β = –0.09 [CI: –0.19, 0.00], p = 0.06), whereas APOE3/3 homozygotes show higher cholesterol with BMI. Specifically, APOE4 carriers maintain higher levels of total and LDL cholesterol at lower BMIs, but have lower levels of both at higher BMIs, relative to individuals that are homozygous APOE3/3 (Figure 5). However, neither of these associations are significant. Ox-LDL, HDL, and triglycerides do not vary by APOE alleles across BMIs. For full models, see Supplementary file 1.

Table 2

Predictors	Total cholesterol			LDL			Oxidized LDL
	β	CI	p	β	CI	p	β	CI	p
E4 * BMI	−0.08	−0.18–0.02	0.111	−0.09	−0.19–0.00	0.061	0.02	−0.13–0.17	0.786
APOE [E4]	0.14	0.03–0.26	0.013	0.07	−0.04–0.18	0.221	0.13	−0.03–0.29	0.112
BMI	0.18	0.14–0.23	<0.001	0.2	0.15–0.25	<0.001	0.21	0.14–0.28	<0.001
Sex [women]	0.15	0.06–0.24	0.001	0.2	0.11–0.28	<0.001	0.09	−0.03–0.21	0.158
Age [in years]	0.01	0.01–0.01	<0.001	0.01	0.01–0.02	<0.001	0	−0.01–0.01	0.869
Currently ill	0.02	−0.13–0.17	0.773	−0.03	−0.18–0.13	0.744	0.15	−0.09–0.39	0.229
Season [wet]	−0.12	−0.20–−0.04	0.004	−0.29	−0.38–−0.21	<0.001	-0.28	−0.44–−0.13	<0.001
(Intercept)	−0.7	−0.94–−0.46	<0.001	−0.71	−0.95–−0.47	<0.001	0.09	−0.28–0.46	0.626
Observations	2581			2390			1032
Marginal R2	0.049			0.074			0.07

Figure 5

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We hypothesized that the effect of the APOE4 polymorphism on disease risk may be environmentally moderated, and that in an energy-limited and pathogenically diverse context, carrying an APOE4 allele may provide some benefit if it aligns with downregulated innate immune function and higher circulating lipids. In support of this hypothesis, we find that Tsimane with an APOE4 allele have higher levels of lipids, yet lower levels of CRP and eosinophils, compared to individuals that have a homozygous APOE3 genotype. Overall, APOE4 carriers also have an adaptive-biased immune profile (as measured by a lower ratio of eosinophils to lymphocytes). These associations remain when controlling for factors known to contribute to differences in inflammation including age, sex, seasonality, and current infection. The most striking example of immunological differences is for CRP, an acute phase protein that functions as part of the complement system and is a marker of generalized inflammation. Though CRP is higher in the Tsimane relative to U.S. and European populations (Blackwell et al., 2016; Gurven et al., 2008), we find that CRP levels are 30% lower among APOE4 carriers than individuals that are homozygous APOE3/3. This replicates a similar finding of lower CRP among Tsimane APOE4 carriers from samples collected over a decade prior to the current study (Vasunilashorn et al., 2011). A study of ‘healthy’ (nondiabetic) Finnish men also found that APOE4 carriers had higher LDL cholesterol coupled with lower CRP (Martiskainen et al., 2018).

Further, in support of our hypothesis that lifestyle and ecological (e.g. pathogen exposure) factors affect how lipids influence inflammation, we find that BMI significantly moderates relationships between lipids and markers of innate inflammation. Our results are consistent with expectations for a high infection context: Tsimane with high BMI (~1 SD above the mean) show no relationship between total cholesterol or LDL with CRP and ESR, but those with mean or low BMI have higher lipid levels that are associated with lower CRP and ESR. In contemporary post-industrialized contexts (Figure 1a), these findings may seem counterintuitive. But in a high-pathogen context, higher concentrations of circulating lipids may allow individuals, especially those that are energy-compromised, to better tolerate infection (Gurven et al., 2016). Thus, the negative association between cholesterol and inflammatory markers could indicate lower infectious burden. For the Tsimane, higher cholesterol levels are likely an indicator of robust health (e.g. not fighting an infection) rather than chronic disease. Independently, lipids are either neutral or negatively associated with immune markers in this sample. This is consistent with previous research among the Tsimane that found blood lipids varied inversely with IgE, eosinophils, and other markers of infection (Vasunilashorn et al., 2010). Overall, the Tsimane maintain low levels of cholesterol relative to U.S. and European standards – less than 5% of sample had a total cholesterol higher than 200 mg/dL. The lack of hyperlipidemic cholesterol levels likely also explains in part why cholesterol does not associate with higher inflammation in this population.

Notably, the moderation effect of BMI indicates that the relationship between ox-LDL and CRP are inverted at the low and high ends of the BMI range. For individuals with low BMI, higher ox-LDL levels are associated with lower CRP, while for those with high BMI, higher ox-LDL is associated with higher CRP (Figure 3c). One possible explanation for the opposing relationships we find between ox-LDL and CRP is that there may be differences in the underlying causes of oxidization in these groups. Though ox-LDL is often considered a consequence of obesogenic or hyperlipidemic oxidization of LDL (Neuparth et al., 2013), ox-LDL is also produced in response to pathogen-mediated immune activation (Han, 2009), and its relationship with downstream immune functions largely depends on the cause of oxidation. For example, while nonpathogenic oxidization of LDL promotes inflammation (Neuparth et al., 2013; Tall and Yvan-Charvet, 2014), during protozoal or bacterial infections, ox-LDL contributes to lower inflammatory responses (Han, 2009). Thus, those with high BMI may represent the transition to sterile inflammation as lifestyles change with greater participation in a market economy (Trumble and Finch, 2019). Indeed, other studies have documented what may be the start of a nutritional transition among the Tsimane (Kraft et al., 2018; Masterson et al., 2017; Rosinger et al., 2013).

Our finding that innate immune biomarkers are lower among APOE4 carriers is in line with prior reports (Lumsden et al., 2020; Martiskainen et al., 2018; Trumble et al., 2017; Vasunilashorn et al., 2011), however the causes are uncertain. One proximate explanation involves the mevalonate pathway, which plays a key role in multiple cellular processes, including modulating sterol and cholesterol biosynthesis and innate immune function (Buhaescu and Izzedine, 2007). One ultimate explanation that we consider relates to the utility of downregulated baseline inflammation in contexts where there is likely chronic exposure to a wide diversity of novel pathogens. In such a context, the costs of inflammation would be amplified, and elements that are involved in regulating innate inflammation may be under stronger selective pressure. This would be plausible so long as downregulating immune function does not compromise one’s ‘ability to respond’ to immunological threats, as has previously been argued (Man et al., 2016). Regarding the main finding for CRP, it is also possible that this is because APOE4 carriers experience a lower innate immune sensing (Dose et al., 2018) or have faster clearance following the resolution of an acute spike. While there is currently no direct evidence for the latter, some studies have found that higher circulating lipids were associated with more rapid clearance of active infections (Andersen, 2018; Pérez-Guzmán et al., 2005). The current study design did not allow analysis of these potential pathways.

Though numerous other studies have established links between the APOE4 polymorphism and neighboring genes (the APOE gene cluster) (Kulminski et al., 2019), and increased circulating lipids (Yassine and Finch, 2020; de Chaves and Narayanaswami, 2008; Safieh et al., 2019; Saito et al., 2004), to our knowledge, this study is the first to assess whether APOE moderates lipid levels under energetic constraints. Specifically, our results show that the APOE4+ genotype is marginally associated with higher relative lipids in a low-energy, pathogenically diverse system. In one study conducted in an obesogenic environment (mean BMI 28 kg/m²), BMI was independently associated with higher total cholesterol, but this relationship did not differ by APOE genotype (Petkeviciene et al., 2012). While it is difficult to pinpoint the cause for discrepant findings across studies, one possibility is that the Lithuanian study did not capture moderation at low BMI (the mean BMI was 28 for both E4 APOE4+ and APOE3/3 genotypes). Another possibility is that the low-pathogen context of urban Lithuania led to less moderation of cholesterols at high BMIs. As mentioned in Introduction, one proposal for the persistence of the ancestral E4 allele despite its deleterious health effects at later ages relies on the fitness benefits of lipid buffering in early life relative to the more recent E3 mutation (van Exel et al., 2017; Yassine and Finch, 2020). The ability to maintain adequate lipid reserves under energetic and pathogenic pressures would also provide additional benefits over the life course (Finch and Kulminski, 2021).

Finally, nearly one-fourth of individuals in the sample had at least one copy of APOE4. The allelic frequency of APOE4 reported here is similar to what has been previously documented among other South American and Amerindian populations, which ranges from 5% to 30% and varies widely by region and level of genetic admixture (Corbo and Scacchi, 1999; Gayà-Vidal et al., 2012). The distribution of APOE allelic variants in populations around the world is likely due to a mosaic of factors, from genetic drift, to antagonistic pleiotropy, to potential differences related to environmentally dependent costs and benefits of functionally distinct variants. Certainly some degree of genetic drift or founder effects (Gayà-Vidal et al., 2012; Singh et al., 2006), antagonistic pleiotropy (Smith et al., 2019; van Exel et al., 2017) and other forces (e.g. genetic relatedness) play an important role in determining population and global frequencies and should be considered jointly to make inferences about the frequency of E4 in the Tsimane population. While pathogen risk and energetic limitations is one context where the typical costs of E4 may not be expressed, the high frequency of E4 allele in populations that are appreciably different in terms of latitude, ecology, and population history (e.g. northern European and central African populations) confirms that more is involved in understanding population differences in E4 frequency (Abondio et al., 2019; Eisenberg et al., 2010).

The commonly reported associations between APOE4 and disease risk in post-industrialized societies may differ from subsistence populations due to environmental mismatch (Trotter et al., 2010). In an environment where calories are limited, and one’s innate immune system is already primed by multiple pathogens, the benefit of having an APOE4 allele – which facilitates upregulated lipids (sufficient for mounting immune responses) and downregulates innate immune function – may be amplified. Such a phenotype could be beneficial particularly if downregulated immune function did not compromise responses to immunological threats. Further, in such an environment, this phenotype may be energetically conservative, maintaining resources to fuel other systems, such as cognitive functioning (Trumble and Finch, 2019). Indeed, there is some evidence that APOE4 carriers may be better able to buffer the negative effects of infection. An APOE4 polymorphism in Brazilian children with a history of infection (measured by bouts of diarrhea in infancy) predicted better scores on cognitive exams (Oria et al., 2011). Among Tsimane infected with parasites, only APOE4 carriers performed better on cognitive tests (Trumble et al., 2017). However, in hygienic post-industrialized contexts, the risk of helminthic and protozoal infection is low, and most pathogens can be quickly treated with medication. Thus, the potential benefits of the APOE4 allele are muted, and the costs of higher lipids are much more severe in these obesogenic environments.

Working with indigenous populations requires special care and sensitivity, especially in regards to the public sharing of genetic data. A long history of abuse and mistrust between researchers and indigenous populations behooves us to prioritize the wishes of Tsimane. Given current ethical restrictions on sharing Tsimane genetic data, we cannot upload Tsimane genetic data to a public server at this time. Individuals interested in accessing the APOE genetic data should submit a request to the co-senior authors. Access will be granted for health focused research, subject to approval by THLHP co-Directors and Tsimane Gran Consejo (Tsimane governing body). All other de-identified data and code are openly accessible on Dryad through the following link: https://datadryad.org/stash/share/FqfEp93SdnqklFbfbjBbenHsZh_10gulo8cf_9LMR3o While we are strong advocates of open science and believe that inclusion of diverse populations in genomics is critical for advancing the goals of public health and health equality, we also need to ensure that all research participants are protected. Our research team is working toward a long-term solution for data-sharing and a streamlined process for requests. This includes the creation of a locally-based ethics and review board comprised of representatives from Tsimane communities and leadership, research collaborators at the Universidad de San Simon (Cochabamba), and THLHP co-directors. The goal of this board is to ensure genomic (and all) data collected are shared according to both global and culturally-specific ethical standards, and considerations about confidentiality.

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Author details

1. Angela R Garcia

   1. Center for Evolution and Medicine, Arizona State University, Tempe, United States
   2. Department of Anthropology, Emory University, Atlanta, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing - original draft, Supervision

   For correspondence

   Angela.Garcia.2@asu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6685-5533

2. Caleb Finch

   Leonard Davis School of Gerontology, Dornsife College, University of Southern California, Los Angeles, Los Angeles, United States

   Contribution

   Conceptualization, Resources, Supervision

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7617-3958

3. Margaret Gatz

   Center for Economic and Social Research, University of Southern California, Los Angeles, Los Angeles, United States

   Contribution

   Resources, Supervision

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1071-9970

4. Thomas Kraft

   Department of Anthropology, University of California, Santa Barbara, Santa Barbara, United States

   Contribution

   Data curation, Methodology, Software, Supervision

   Competing interests

   No competing interests declared

5. Daniel Eid Rodriguez

   Department of Medicine, Universidad de San Simón, Cochabamba, Bolivia

   Contribution

   Investigation, Supervision

   Competing interests

   No competing interests declared

6. Daniel Cummings

   Institute for Economics and Society, Chapman University, Orange, United States

   Contribution

   Data curation

   Competing interests

   No competing interests declared

7. Mia Charifson

   Vilcek Institute of Graduate Biomedical Sciences, New York University, New York, United States

   Contribution

   Data curation, Supervision

   Competing interests

   No competing interests declared

8. Kenneth Buetow

   1. Center for Evolution and Medicine, Arizona State University, Tempe, United States
   2. School of Life Sciences, Arizona State University, Tempe, United States

   Contribution

   Resources, Supervision

   Competing interests

   No competing interests declared

9. Bret A Beheim

   Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

   Contribution

   Data curation, Supervision

   Competing interests

   No competing interests declared

10. Hooman Allayee

    1. Department of Preventive Medicine and Biochemistry & Molecular Medicine, Keck School of Medicine, University of Southern California, Irvine, Irvine, United States
    2. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Irvine, Irvine, United States

    Contribution

    Formal analysis, Funding acquisition, Supervision

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2384-5239

11. Gregory S Thomas

    Long Beach Memorial, Long Beach and University of California Irvine, Irvine, United States

    Contribution

    Project administration, Supervision

    Competing interests

    No competing interests declared

12. Jonathan Stieglitz

    Institute for Advanced Study in Toulouse, Universite Toulouse, Toulouse, France

    Contribution

    Project administration, Writing – review and editing, Supervision

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5985-9643

13. Michael D Gurven

    Department of Anthropology, University of California, Santa Barbara, Santa Barbara, United States

    Contribution

    Project administration, Funding acquisition, Resources, Supervision

    Contributed equally with

    Hillard Kaplan and Benjamin C Trumble

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-5661-527X

14. Hillard Kaplan

    Institute for Economics and Society, Chapman University, Orange, United States

    Contribution

    Project administration, Writing – review and editing, Funding acquisition, Resources, Supervision

    Contributed equally with

    Michael D Gurven and Benjamin C Trumble

    Competing interests

    No competing interests declared

15. Benjamin C Trumble

    School of Human Evolution and Social Change, Arizona State University, Tempe, United States

    Contribution

    Conceptualization, Project administration, Investigation, Writing – review and editing, Funding acquisition, Resources, Supervision

    Contributed equally with

    Michael D Gurven and Hillard Kaplan

    For correspondence

    trumble@asu.edu

    Competing interests

    No competing interests declared

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