APOE4 is associated with elevated blood lipids and lower levels of innate immune biomarkers in a tropical Amerindian subsistence population

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    Evaluation Summary:

    The authors ask why the APOE4 allele has persisted, often at high frequencies, in human populations despite its associations to heart disease and Alzheimer's disease. They consider the hypothesis that APOE4 may be advantageous in a high pathogen and high physical environment settings (as opposed to a low pathogen industrial lifestyle) through an in-depth characterization of the Tsimane in Bolivia. The study is of broad interest with an insightful dataset; the conclusions are somewhat limited by the nature and current description and treatment of the data.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

In post-industrial settings, apolipoprotein E4 ( APOE4 ) is associated with increased cardiovascular and neurological disease risk. However, the majority of human evolutionary history occurred in environments with higher pathogenic diversity and low cardiovascular risk. We hypothesize that in high-pathogen and energy-limited contexts, the APOE4 allele confers benefits by reducing innate inflammation when uninfected, while maintaining higher lipid levels that buffer costs of immune activation during infection. Among Tsimane forager-farmers of Bolivia ( N = 1266, 50% female), APOE4 is associated with 30% lower C-reactive protein, and higher total cholesterol and oxidized LDL. Blood lipids were either not associated, or negatively associated with inflammatory biomarkers, except for associations of oxidized LDL and inflammation which were limited to obese adults. Further, APOE4 carriers maintain higher levels of total and LDL cholesterol at low body mass indices (BMIs). These results suggest that the relationship between APOE4 and lipids may be beneficial for pathogen-driven immune responses and unlikely to increase cardiovascular risk in an active subsistence population.

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  1. Author Response:

    A very sincere thanks to the Editors and Reviewers for their insightful and helpful feedback which undoubtedly strengthened the manuscript. We appreciate the opportunity to respond to these critiques and recommended revisions.

    Evaluation Summary:

    The authors ask why the APOE4 allele has persisted, often at high frequencies, in human populations despite its associations to heart disease and Alzheimer's disease. They consider the hypothesis that APOE4 may be advantageous in a high pathogen and high physical environment settings (as opposed to a low pathogen industrial lifestyle) through an in-depth characterization of the Tsimane in Bolivia. The study is of broad interest with an insightful dataset; the conclusions are somewhat limited by the nature and current description and treatment of the data.

    From Editor and Reviewer comments, we realized that the paper required some clarification regarding our position on APOE allele frequencies in the Tsimane population. As discussed more depth in the reviewer comments, it was not our intent to make a purely adaptationist argument for E4, or to suggest that there are no costs to E4 in other aspects of life, or at different ages, but rather to suggest that the relative costs and benefits of E4 may be environmentally-dependent, such that having an E4 allele is more neutral, and/or may provide some benefits (and limited costs), in pathogenically-diverse and energy-limited environments.

    Reviewer #1 (Public Review):

    Garcia, AR et al. seek to test out the hypothesis that APOE4 is environmentally mediated and may be protective in a high-pathogen environment. The authors test the presence of at least a single APOE4 allele copy with baseline innate immune function in a Tsimane population in Bolivia by measuring various biomarkers. They showed that being an APOE4 allele carrier is associated with higher circulating levels of lipids combined with lower levels of CRP and eosinophils. This finding among the APOE4+ individuals of the Tsimane population demonstrates further support for the hypothesis that higher loads of lipids are protective in higher loads of infection. This work highlights not only connections to immune response but how we can interpret heart disease/Alzheimer's in an evolutionary context dependent on the environment. Furthermore, a strength is that this work was carried out ethically where work with human subjects was not only approved in US-based institutions, but also by the governing body of the Tsimane. Overall, this is a clear study using fieldwork methods to demonstrate connections difficult to replicate in a controlled laboratory setting.

    1. One of the underlying assumptions for the persistence of APOE4 alleles across human populations is because it is or was previously under selection and in the right environment, the APOE4 allele is advantageous. Presumably, in the Tsimane, where the APOE4 allele may be advantageous due to a higher pathogen load and high activity, then wouldn't we expect the allele frequencies to be higher? This section discussing evolution should be a little more fleshed out. Is there any evidence for genetic selection (positive/ balancing) at that locus or is it based on allele frequencies? Given that you do calculate allele frequencies, how do the allele frequencies in Tsimane populations compare to other populations that live in the same geographic region or environment? Would we expect these allele frequencies to be higher than in a post-industrial environment? Do they support selection?

    We thank you for this input, and also appreciate the opportunity to clarify our position; we do not assume that APOE4 was under positive selection in this population, and do not intend to make a purely 'adaptationist' argument for the persistence of APOE4 in this population. Nor do we make any attempts to assess signals of selection. Our goals for this paper are (1) questioning the assumptions that APOE4 is a universally deleterious allele, rather than its effects on phenotype are environmentally moderated, and (2) assessing the relationships between APOE, lipids, and innate inflammation in a population living in a relatively unique (and underrepresented) environmental context. We contend that the benefits of APOE4 may be most appreciable in energetically-constrained and pathogenically-diverse environments, and that APOE4 may also not have the same harmful effects on health under such conditions. It was not our intent to suggest that there are no costs to APOE4 in other aspects of life, or at different ages, but rather to suggest that the relative costs and benefits of APOE4 may be environmentally-dependent, such that having an APOE4 allele is more neutral, and/or may provide some benefits (and limited costs), in pathogenically-diverse and energy-limited environments.

    The distribution of APOE allelic variants in populations around the world is likely due to a mosaic of factors, and potentially include 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 pathogenicity and energetic limitations is one context where the typical costs of APOE4 may not be expressed, the high frequency of APOE4 allele in populations that are appreciably different in terms of latitude, ecology, and population history (e.g. northern European and central African populations), confirm that more is involved in understanding population differences in APOE4 frequency (Abondio et al., 2019). Nonetheless, the context we describe and show evidence for in our paper contrasts with the contemporary obesogenic environment with low pathogen diversity more typical of the Global North, where benefits like lipid buffering are no longer needed- and may in fact incur costs. Wording throughout the paper has been modified to clarify this stance.

    1. Throughout the paper I was wondering if other models were also considered and tested (APOE3/APOE3, APOE3/APOE4, APOE4/APOE4), but I didn't see the reasoning for why the alleles were binned until the methods section. This information should come earlier in the paper, given the way it is structured. If the 3 genotypes were tested, it should be stated in the paper, even if there was no association or there was insufficient sample size and should be discussed in the discussion.

    Unfortunately, there are very few individuals who are homozygous for APOE4 (E3/3: n=998; E3/4: n=245; E4/4: n=23), making it impossible to conduct statistical tests with sufficient statistical power to make inferences. While we understand the interest in reporting findings from models that use 'unbinned' data, we are cautious against doing so, as statistical tests provide no clear or reliable inferences (whether non- or highly-significant), due to the sample size disparities. This is even more problematic in models that include interaction effects (the majority), which further split and lead to disparate sample sizes between groups. We have moved up the explanation for binning APOE genotypes to the beginning of the Results section, and noted the genotypic breakdown.

    Reviewer #2 (Public Review):

    This work investigates the impact of the APOE4 gene variant on inflammation and lipid profiles among the Tsimane subsistence population of Bolivia, a group facing energy constraints and heavy infectious disease burden. APOE4 is associated with greater inflammation, lipids, and downstream cardiovascular disease and Alzheimer's disease in energy-abundant post-industrial populations. Increasingly, human and other model research suggests that the impact of APOE4 on inflammation and lipids may vary under differing conditions of energy availability and infection. It is important to understand this variation to understand how APOE4 impacts disease risk across populations but also to understand why, from an evolutionary perspective, APOE4 frequency is up to 40% in some populations.

    Strengths:

    *The evolutionary medicine approach used in this study allows for a powerful analysis to probe both proximate ("how") and ultimate ("why") questions relating to variation in APOE4 frequency and associated disease risk.

    *The sample size is relatively large and is, it appears, the first to combine this set of measures in a subsistence population experiencing a wide range of energy availability. This allows for the testing of variable interactions and moderating effects using mixed models that can accommodate data clustering and missing data.

    *The paper is organized nicely. The findings, as currently described, have important implications for understanding evolved mechanisms of pathogen defense and the rapidly increasing burden of cardiovascular disease in many low-and middle-income countries.

    Weaknesses:

    *The observational design and correlative nature of the analysis limit causal inference. This is exacerbated by near-single measures of some key variables and the use of proxies of energy availability (e.g., BMI) and pathogen exposure (e.g., community) that lack specificity.

    We concur that the data available limit causal inference. We discuss this point in detail in the Limitations section (excerpt below), and offer ideas that we believe would be useful and necessary to extend this research, by designing experimental lab-based models to test some of the main findings.

    Regarding the measures used, while we agree that BMI is not a perfect proxy for energy availability, given that our main goal in the paper -- with regards to energy availability -- was to investigate APOE and lipids at the extreme tails of BMI (overweight vs. lean), we do feel that BMI can adequately capture broad differences in energetic availability between these two groups. For example, a previous paper showed that BMI and body fat were closely associated among adults in this population (Gurven et al. 2012: r=.0.75 in women; r=0.57 in men; Fig. S4). Also, though we use BMI as a continuous measure for models, we plot the upper and lower tertiles from these models to distinguish these overweight vs. lean groups.

    Regarding justification for using community as a proxy for pathogen exposure, we have added the following sentence to Methods: "Because Tsimane villages vary in sanitation infrastructure, including access to soap and other hygienic products, and potentially prevalence by pathogen type (e.g. some living very close to the river versus farther out in the forest), individuals were clustered by community to account for variation in such community-level factors." We would also like to note that we include season and white blood cell count as additional covariates to adjust for individual-level differences in current pathogen exposure.

    Excerpt from Limitations: "Because these findings may be important for furthering evolutionary (i.e. why the APOE4 allele is maintained) and clinical (i.e. the role of APOE in disease pathogenesis) understanding, they require replication, and warrant experimental testing. The central thesis presented here – that persistent exposure to pathogens and obesogenic diets moderate the relationship between blood lipids and inflammation – is amenable to experimental manipulation under lab conditions. Specifically, a mammalian model system could be split into two treatments: those raised under sterile conditions versus regimented exposure to non-lethal pathogens. These treatments may then be crossed with dietary or physical activity conditions that produce differential levels of adiposity. Our hypothesis predicts that both decreased adiposity and increased life course pathogen exposure will reduce or even eliminate positive associations between blood lipids and chronic inflammation. Importantly, inflammatory biomarkers can be measured at more frequent intervals in lab conditions to assess long-term differences in the function of both pro- and anti-inflammatory pathways between experimental treatments."

    *There may be reporting errors in the key marker of inflammation (CRP) and, potentially, the sample sizes. This adds concern for the analysis.

    We had mistakenly reported CRP in mg/dL. We truly appreciate this Reviewer for catching the unit reporting error: CRP units have been updated and now correctly report in mg/L.

    We realized the lack of clarity regarding the sample size for each of the specific models, given that sample sizes differed across models, dependent upon the number of measurements/observations available per biomarker. For clarity, we have added sample sizes for each model (total observations and unique sample IDs) to tables in the main text of the document. To this end, raw data points have also been added to all figures. Full models with covariates are still included in the Supplement.

    *While the argument of the paper is based on "baseline" measures of inflammation and lipids, it is unclear given the nature of the data and analysis if representative measures are actually being used. If not, the interpretation of the data could change considerably.

    We see the problem of stating that the reported levels for biomarkers are specifically "baseline", particularly given the observational nature of the data. A main focus of the paper is in applying an evolutionary lens to understanding relationships between APOE variants, lipids, and immune functions-- including the widely-observed phenomenon that in healthy, non-obese, individuals, APOE4 is consistently associated with lower innate inflammation. We aim to apply an evolutionary theoretical framework to understand this relationship, however, with the existing data, we cannot make strong inferences or rule out the alternate explanations (lower baseline vs faster clearance, etc.) posed. We have deleted all uses of the term "baseline" to describe observed levels of immune function. We have also added sentences to the discussion section to illuminate some possible explanations for genotype differences in levels of innate immune function. Further, with regards to one of our main results (that APOE4 carriers have significantly lower CRP): to address the possibility that we are capturing a high number of acute inflammatory events, which may affect findings, we reran models constraining them to include only observations of CRP < 10mg/L. The median level for CRP for this subset is 2.5mg/L. Constraining the models does not alter the results, however, we report the results for both, and include constrained models in the Supplement.

    From Discussion (additions underlined): "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). Regarding the main finding for CRP, it is possible that 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 pathways."

    *The paper does not have the sample size to address the impact of having 1 vs. 2 copies of APOE4 and could better discuss population-level variation in APOE4 frequencies and why Tsimane frequency (12%) is, in fact, much lower than in many other populations (e.g., in Central Africa).

    As noted above, we agree that it would informative to be able to tease apart phenotypic effects from having one or two E4 alleles versus none, and recognize that we are unfortunately not in the position to parse out such differences in this paper due to the relatively small sample size of homozygous E4/E4 individuals (E3/3: n=998; E3/4: n=245; E4/4: n=23). We have moved up the explanation for binning APOE genotypes to the beginning of the Results section, and noted the genotypic breakdown to explain why we needed to bin APOE4 carriers vs non-carriers for the statistical analyses.

    We completely agree that making inferences about APOE4 frequency across populations is interesting and would be a useful extension, but it is unfortunately beyond the scope of this manuscript. Certainly some degree of genetic drift, founder effects, population bottlenecks, antagonistic pleiotropy and other forces should be considered jointly to make inferences about the frequency of E4 in the Tsimane population, and in comparison to other populations worldwide. Unfortunately, that set of analyses is beyond the scope of this paper, which provides data on associations between APOE genotype and lipid and immune phenotypes. Given that E4 is the ancestral allele, it is possible that a combination of lower costs (or even benefits) in pathogenically-diverse environments, and maintenance due to drift/lack of bottlenecks, may in part explain the high frequencies in some parts of Africa. While pathogen risk and energetic limitations is one context where the typical cardiovascular costs of E4 may not be expressed, the high frequency of E4 allele in northern European populations confirms that more is involved in understanding population differences in E4 frequency. Nonetheless, the context we describe and show evidence for in our paper contrasts with the contemporary obesogenic environment with low pathogen diversity more typical of the Global North, where benefits like lipid buffering are no longer needed- and may in fact incur costs. Wording throughout has been modified to clarify this stance.

  2. Evaluation Summary:

    The authors ask why the APOE4 allele has persisted, often at high frequencies, in human populations despite its associations to heart disease and Alzheimer's disease. They consider the hypothesis that APOE4 may be advantageous in a high pathogen and high physical environment settings (as opposed to a low pathogen industrial lifestyle) through an in-depth characterization of the Tsimane in Bolivia. The study is of broad interest with an insightful dataset; the conclusions are somewhat limited by the nature and current description and treatment of the data.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  3. Reviewer #1 (Public Review):

    Garcia, AR et al. seek to test out the hypothesis that APOE4 is environmentally mediated and may be protective in a high-pathogen environment. The authors test the presence of at least a single APOE4 allele copy with baseline innate immune function in a Tsimane population in Bolivia by measuring various biomarkers. They showed that being an APOE4 allele carrier is associated with higher circulating levels of lipids combined with lower levels of CRP and eosinophils. This finding among the APOE4+ individuals of the Tsimane population demonstrates further support for the hypothesis that higher loads of lipids are protective in higher loads of infection. This work highlights not only connections to immune response but how we can interpret heart disease/Alzheimer's in an evolutionary context dependent on the environment. Furthermore, a strength is that this work was carried out ethically where work with human subjects was not only approved in US-based institutions, but also by the governing body of the Tsimane. Overall, this is a clear study using fieldwork methods to demonstrate connections difficult to replicate in a controlled laboratory setting.

    1. One of the underlying assumptions for the persistence of APOE4 alleles across human populations is because it is or was previously under selection and in the right environment, the APOE4 allele is advantageous. Presumably, in the Tsimane, where the APOE4 allele may be advantageous due to a higher pathogen load and high activity, then wouldn't we expect the allele frequencies to be higher? This section discussing evolution should be a little more fleshed out. Is there any evidence for genetic selection (positive/ balancing) at that locus or is it based on allele frequencies? Given that you do calculate allele frequencies, how do the allele frequencies in Tsimane populations compare to other populations that live in the same geographic region or environment? Would we expect these allele frequencies to be higher than in a post-industrial environment? Do they support selection?

    2. Throughout the paper I was wondering if other models were also considered and tested (APOE3/APOE3, APOE3/APOE4, APOE4/APOE4), but I didn't see the reasoning for why the alleles were binned until the methods section. This information should come earlier in the paper, given the way it is structured. If the 3 genotypes were tested, it should be stated in the paper, even if there was no association or there was insufficient sample size and should be discussed in the discussion.

  4. Reviewer #2 (Public Review):

    This work investigates the impact of the APOE4 gene variant on inflammation and lipid profiles among the Tsimane subsistence population of Bolivia, a group facing energy constraints and heavy infectious disease burden. APOE4 is associated with greater inflammation, lipids, and downstream cardiovascular disease and Alzheimer's disease in energy-abundant post-industrial populations. Increasingly, human and other model research suggests that the impact of APOE4 on inflammation and lipids may vary under differing conditions of energy availability and infection. It is important to understand this variation to understand how APOE4 impacts disease risk across populations but also to understand why, from an evolutionary perspective, APOE4 frequency is up to 40% in some populations.

    Strengths:

    *The evolutionary medicine approach used in this study allows for a powerful analysis to probe both proximate ("how") and ultimate ("why") questions relating to variation in APOE4 frequency and associated disease risk.

    *The sample size is relatively large and is, it appears, the first to combine this set of measures in a subsistence population experiencing a wide range of energy availability. This allows for the testing of variable interactions and moderating effects using mixed models that can accommodate data clustering and missing data.

    *The paper is organized nicely. The findings, as currently described, have important implications for understanding evolved mechanisms of pathogen defense and the rapidly increasing burden of cardiovascular disease in many low-and middle-income countries.

    Weaknesses:

    *The observational design and correlative nature of the analysis limit causal inference. This is exacerbated by near-single measures of some key variables and the use of proxies of energy availability (e.g., BMI) and pathogen exposure (e.g., community) that lack specificity.

    *There may be reporting errors in the key marker of inflammation (CRP) and, potentially, the sample sizes. This adds concern for the analysis.

    *While the argument of the paper is based on "baseline" measures of inflammation and lipids, it is unclear given the nature of the data and analysis if representative measures are actually being used. If not, the interpretation of the data could change considerably.

    *The paper does not have the sample size to address the impact of having 1 vs. 2 copies of APOE4 and could better discuss population-level variation in APOE4 frequencies and why Tsimane frequency (12%) is, in fact, much lower than in many other populations (e.g., in Central Africa).