Inflammaging is minimal among forager-horticulturalists in the Bolivian Amazon
Data files
Jul 02, 2025 version files 121.41 KB
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inflammaging_procb_ifnyplotdat.csv
539 B
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inflammaging_procb_il10plotdat.csv
539 B
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inflammaging_procb_il12plotdat.csv
570 B
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inflammaging_procb_il15plotdat.csv
537 B
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inflammaging_procb_il1bplotdat.csv
552 B
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inflammaging_procb_il2plotdat.csv
571 B
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inflammaging_procb_il6plotdat.csv
546 B
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inflammaging_procb_table1.csv
361 B
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inflammaging_procb_table2.csv
891 B
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inflammaging_procb_table3.csv
1.08 KB
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inflammaging_procb_table4.csv
1.08 KB
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inflammaging_procb_table5.csv
922 B
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inflammaging_procb_tnfaplotdat.csv
534 B
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inflammagingvariables.csv
285 B
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README.md
16.18 KB
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Tsimane_inflammaging_code.R
96.23 KB
Abstract
An increase in chronic systemic inflammation in later life, termed inflammaging, is implicated in health risk. However, it is unclear whether inflammaging develops in all human populations, or if it is the product of modern environmental mismatch. We assessed inflammaging in Tsimane forager-horticulturalists of the Bolivian Amazon, using serum cytokines in a primarily cross-sectional sample (1,134 samples from n = 714, ages 39-94, 51.3% female). IL-6 was positively associated with age (β = 0.013, p < 0.01). However, other pro-inflammatory markers, including IL-1β and TNF-α, did not increase with age (β = -0.005 and β = -0.001, respectively). We then compared the Moseten, a neighboring population that has experienced greater market integration (423 samples from n = 380, ages 39-85, 48.2% female). The Moseten also showed a positive age association for IL-6 that attenuated at later ages (age β = 0.025, p < 0.01; age2 β = -0.001, p < 0.05). Further, IL-1β and TNF-α were both positively associated with age (β = 0.021, p < 0.05, and β = 0.011, p < 0.01, respectively). Our results demonstrate minimal inflammaging in the Tsimane, highlighting variation across populations in this age-related process. They also suggest inflammaging is exacerbated by lifestyle shifts.
Dataset DOI: 10.5061/dryad.2v6wwq00q
Description of the data and file structure
The purpose of this study is to assess whether the Tsimane, forager-horticulturalists residing in the Bolivian Amazon, develop chronic inflammation in later life (termed inflammaging). The data collected to answer this question included a panel of cytokines measured from serum samples. Cytokines were measured in pg/mL using the Quansys 15-plex assay. Tsimane data were compared to a neighboring and closely related population, the Moseten, which has experienced greater market integration and lifestyle shifts.
The files include (1) the code used to produce the results, (2) a heading file showing the variable names used in the analysis, (3) data from each table in the manuscript in .csv format, and (4) data from regression models used to produce each figure.
Files and variables
File: inflammagingvariables.csv
Description: A header file showing the variable names in the dataset
Variables
- pid: person id
- Collection.Date: date the serum sample was collected
- hsIL1a.pgmL: High sensitivity interleukin 1 alpha measured in pg/mL
- hsIL1b.pgmL: High sensitivity interleukin 1 beta measured in pg/mL
- hsIL2.pgmL: High sensitivity interleukin 2 measured in pg/mL
- hsIL4.pgmL: High sensitivity interleukin 4 measured in pg/mL
- hsIL5.pgmL: High sensitivity interleukin 5 measured in pg/mL
- hsIL6.pgmL: High sensitivity interleukin 6 measured in pg/mL
- hsIL10.pgmL: High sensitivity interleukin 10 measured in pg/mL
- hsIL12.pgmL: High sensitivity interleukin 12 measured in pg/mL
- hsIL13.pgmL: High sensitivity interleukin 13 measured in pg/mL
- hsIL15.pgmL: High sensitivity interleukin 15 measured in pg/mL
- hsIL17.pgmL: High sensitivity interleukin 17 measured in pg/mL
- hsIL23.pgmL: High sensitivity interleukin 23 measured in pg/mL
- hsIFNy.pgmL: High sensitivity interferon gamma measured in pg/mL
- hsTNFa.pgmL: High sensitivity tumor necrosis factor alpha measured in pg/mL
- hsTNFb.pgmL.1: High sensitivity tumor necrosis factor beta measured in pg/mL
- male: coded 1 = male, 0 = female
- age: age in years
- moseten: coded 1 = Moseten, 0 = Tsimane
- female: coded 1 = female, 0 = male
- age60: age in years centered at 60 years (60 subtracted from age)
- Population: factor variable for plotting ("Tsimane" and "Moseten")
- Sex: factor variable for plotting ("Male" and "Female")
- PC1: The first principal component from all of the cytokines
- distance_town_log: The distance a person was living in from the nearest town of San Borja at the time of study participation (natural log transformed).
- analyzewbc: White blood cell count (natural log transformed).
- bmi: Body mass index (kg/m2)
- waist: Waist circumference (centimeters)
File: Tsimane_inflammaging_code.R
Description: Code file used to produce the study results and figures
File: inflammaging_procb_table1.csv
Description: Descriptive statistics presented in Table 1
Variables
- descriptive: specifying the particular descriptive
- Tsimane: descriptives for the Tsimane
- Moseten: descriptives for the Moseten
File: inflammaging_procb_table2.csv
Description: Data from Table 2 showing intra-class correlation estimates for the cytokines. Blank cells indicate that the cytokine (noted in the first column) was not measured in the previously published study (noted in the first row).
Variables
- cytokine: designating the cytokine below
- Tsimane icc: the Tsimane intra-class correlation estimate
- Tsimane icc lower: the Tsimane lower 95% confidence interval estimate
- Tsimane icc upper: the Tsimane upper 95% confidence interval estimate
- Moseten icc: the Moseten intra-class correlation estimate
- Moseten icc lower: the Moseten lower 95% confidence interval estimate
- Moseten icc upper: the Moseten upper 95% confidence interval estimate
- Clendenen icc: the icc estimate from the cited Clendenen et al. study
- Gu icc: the icc estimate from the cited Gu et al. study
- Guo icc: the icc estimate from the cited Guo et al. study
- Hofmann icc: the icc estimate from the cited Hofmann et al. study
File: inflammaging_procb_table3.csv
Description: Regression model results for the Tsimane (part 1) shown in Table 3. Blank cells indicate that the variable (specified in the first column) was not included in that particular regression model (specified in the first row).
Variables
- predictor: specifying the predictor variable in the model
- IL-1b 1: results for the first IL-1b model (linear age term)
- IL-1b 2: results for the second IL-1b model (quadratic age term)
- IL-1b 3: results for the third IL-1b model (linear age term adjusting for leukocytes)
- IL-1b 4: results for the fourth IL-1b model (quadratic age term adjusting for leukocytes)
- IL-6 1: results for the first IL-6 model (linear age term)
- IL-6 2: results for the second IL-6 model (quadratic age term)
- IL-6 3: results for the third IL-6 model (linear age term adjusting for leukocytes)
- IL-6 4: results for the fourth IL-6 model (quadratic age term adjusting for leukocytes)
- IL-10 1: results for the first IL-10 model (linear age term)
- IL-10 2: results for the second IL-10 model (quadratic age term)
- IL-10 3: results for the third IL-10 model (linear age term adjusting for leukocytes)
- IL-10 4: results for the fourth IL-10 model (quadratic age term adjusting for leukocytes)
- TNF-a 1: results for the first TNF-a model (linear age term)
- TNF-a 2: results for the second TNF-a model (quadratic age term)
- TNF-a 3: results for the third TNF-a model (linear age term adjusting leukocytes)
- TNF-a 4: results for the fourth TNF-a model (quadratic age term adjusting for leukocytes)
File: inflammaging_procb_table4.csv
Description: Regression model results for the Tsimane (part 2) shown in Table 4. Blank cells indicate that the variable (specified in the first column) was not included in that particular regression model (specified in the first row).
Variables
- predictor: specifying the predictor variable in the model
- IL-2 1: results for the first IL-2 model (linear age term)
- IL-2 2: results for the second IL-2 model (quadratic age term)
- IL-2 3: results for the third IL-2 model (linear age term adjusting for leukocytes)
- IL-2 4: results for the fourth IL-2 model (quadratic age term adjusting for leukocytes)
- IL-12 1: results for the first IL-12 model (linear age term)
- IL-12 2: results for the second IL-12 model (quadratic age term)
- IL-12 3: results for the third IL-12 model (linear age term adjusting for leukocytes)
- IL-12 4: results for the fourth IL-12 model (quadratic age term adjusting for leukocytes)
- IL-15 1: results for the first IL-15 model (linear age term)
- IL-15 2: results for the second IL-15 model (quadratic age term)
- IL-15 3: results for the third IL-15 model (linear age term adjusting for leukocytes)
- IL-15 4: results for the fourth IL-15 model (quadratic age term adjusting for leukocytes)
- IFN-g 1: results for the first IFN-y model (linear age term)
- IFN-g 2: results for the second IFN-y model (quadratic age term)
- IFN-g 3: results for the third IFN-y model (linear age term adjusting for leukocytes)
- IFN-g 4: results for the fourth IFN-y model (quadratic age term adjusting for leukocytes)
File: inflammaging_procb_table5.csv
Description: Regression model results for the Moseten shown in Table 5. Blank cells indicate that the variable (specified in the first column) was not included in that particular regression model (specified in the first row).
Variables
- predictor: the predictor variables in the model
- IL-1b 1: results for the first IL-1b model (linear age term)
- IL-1b 2: results for the second IL-1b model (quadratic age term)
- IL-6 1: results for the first IL-6 model (linear age term)
- IL-6 2: results for the second IL-6 model (quadratic age term)
- IL-10 1: results for the first IL-10 model (linear age term)
- IL-10 2: results for the second IL-10 model (quadratic age term)
- TNF-a 1: results for the first TNF-a model (linear age term)
- TNF-a 2: results for the second TNF-a model (quadratic age term)
- IL-2 1: results for the first IL-2 model (linear age term)
- IL-2 2: results for the second IL-2 model (quadratic age term)
- IL-12 1: results for the first IL-12 model (linear age term)
- IL-12 2: results for the second IL-12 model (quadratic age term)
- IL-15 1: results for the first IL-15 model (linear age term)
- IL-15 2: results for the second IL-15 model (quadratic age term)
- IFN-g 1: results for the first IFN-y model (linear age term)
- IFN-g 2: results for the second IFN-y model (quadratic age term)
File: inflammaging_procb_il6plotdat.csv
Description: Regression model results used to create the IL-6 plot in Figure 1. These metadata produce the age trend line (with 95% confidence intervals) for IL-6 in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_il10plotdat.csv
Description: Model results data used to make the IL-10 plot in Figure 1. These metadata produce the age trend line (with 95% confidence intervals) for IL-10 in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_il1bplotdat.csv
Description: Model results data used to make the IL-1b plot in Figure 1. These metadata produce the age trend line (with 95% confidence intervals) for IL-1b in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_tnfaplotdat.csv
Description: Model results data used to make the TNF-a plot in Figure 1. These metadata produce the age trend line (with 95% confidence intervals) for TNF-a in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_il2plotdat.csv
Description: Model results data used to make the IL-2 plot in Figure 2. These metadata produce the age trend line (with 95% confidence intervals) for IL-2 in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_il12plotdat.csv
Description: Model results data used to make the IL-12 plot in Figure 2. These metadata produce the age trend line (with 95% confidence intervals) for IL-12 in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_il15plotdat.csv
Description: Model results data used to make the IL-15 plot in Figure 2. These metadata produce the age trend line (with 95% confidence intervals) for IL-15 in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
File: inflammaging_procb_ifnyplotdat.csv
Description: Model results data used to make the IFN-y plot in Figure 2. These metadata produce the age trend line (with 95% confidence intervals) for IFN-y in the Tsimane and Moseten.
Variables
- fit: the fitted cytokine value derived from the regression model
- se: the standard error for the fit value
- lower ci: the lower 95% confidence interval for the fit value
- upper ci: the upper 95% confidence interval for the fit value
- age: age in years
- population: designating either Tsimane or Moseten
Code/software
R version 4.4.2 (2024-10-31)
attached base packages:
stats graphics grDevices utils datasets methods base
other attached packages:
ggExtra_0.10.1 effects_4.2-2 performance_0.13.0 AER_1.2-14 survival_3.7-0 car_3.1-3
carData_3.0-5 ggpubr_0.6.0 lmtest_0.9-40 zoo_1.8-13 sandwich_3.1-1 stargazer_5.2.3
lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.4 readr_2.1.5
tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0
Human subjects data
Informed consent was given by the Tsimane Government (Gran Consejo Tsimane), village leaders, and all study participants directly. Methods and procedures were approved by the Institutional Review Boards of the University of New Mexico (HRRC #07-157; #15-133; #17-230), University of California Santa Barbara (HRRC #28-21-0788), and the Universidad San Simon Cochabamba, Bolivia.
Individual-level data are stored in the Tsimane Health and Life History Project (THLHP) Data Repository, and are available through restricted access for ethical reasons. THLHP's highest priority is the safeguarding of human subjects and minimization of risk to study participants. The THLHP adheres to the “CARE Principles for Indigenous Data Governance” (Collective Benefit, Authority to Control, Responsibility, and Ethics), which assure that the Tsimane 1) have sovereignty over how data are shared, 2) are the primary gatekeepers determining ethical use, 3) are actively engaged in the data generation, and 4) derive benefit from data generated and shared for use whenever possible. The THLHP is also committed to the “FAIR Guiding Principles for scientific data management and stewardship” (Findable, Accessible, Interoperable, Reusable). Requests for individual-level data should take the form of an application that details the exact uses of the data and the research questions to be addressed, procedures that will be employed for data security and individual privacy, potential benefits to the study communities, and procedures for assessing and minimizing stigmatizing interpretations of the research results (see the following webpage for links to the data sharing policy and data request forms: https://tsimane.anth.ucsb.edu/data.html). Requests for individual-level data will require institutional IRB approval (even if exempt) and will be reviewed by an Advisory Council composed of Tsimane community leaders, community members, Bolivian scientists, and the THLHP leadership. The study authors and the THLHP leadership are committed to open science and are available to assist interested investigators in preparing data access requests.