A Population-Based Human In Vitro Approach to Quantify Inter-Individual Variability in Responses to Chemical Mixtures

Abstract

Human cell-based population-wide in vitro models have been proposed as a strategy to derive chemical-specific estimates of inter-individual variability; however, the utility of this approach has not yet been tested for cumulative exposures in mixtures. This study aimed to test defined mixtures and their individual components and determine whether adverse effects of the mixtures were likely to be more variable in a population than those of the individual chemicals. The in vitro model comprised 146 human lymphoblastoid cell lines from four diverse subpopulations of European and African descent. Cells were exposed, in concentration–response, to 42 chemicals from diverse classes of environmental pollutants; in addition, eight defined mixtures were prepared from these chemicals using several exposure- or hazard-based scenarios. Points of departure for cytotoxicity were derived using Bayesian concentration–response modeling and population variability was quantified in the form of a toxicodynamic variability factor (TDVF). We found that 28 chemicals and all mixtures exhibited concentration–response cytotoxicity, enabling calculation of the TDVF. The median TDVF across test substances, for both individual chemicals or defined mixtures, ranged from a default assumption (101/2) of toxicodynamic variability in human population to >10. The data also provide a proof of principle for single-variant genome-wide association mapping for toxicity of the chemicals and mixtures, although replication would be necessary due to statistical power limitations with the current sample size. This study demonstrates the feasibility of using a set of human lymphoblastoid cell lines as an in vitro model to quantify the extent of inter-individual variability in hazardous properties of both individual chemicals and mixtures. The data show that population variability of the mixtures is unlikely to exceed that of the most variable component, and that similarity in genome-wide associations among components may be used to accrue additional evidence for grouping of constituents in a mixture for cumulative assessments.

Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model

“…The primary innovation of this study is the use of a human population-based in vitro model for both individual chemicals and mixtures to better understand population inter-individual variability in mixture effects, as there has been limited research on evaluating population variability in the additivity of responses to mixtures. We exposed 146 human lymphoblastoid cell lines from 4 subpopulations to 42 ATSDR priority chemicals and 8 defined mixtures to investigate population variability [ 47 ]. Lymphoblastoid cells are useful because they are relatively easy to culture and demonstrate comparable results to iPSC-derived models, which are known as reliable human cell types for in silico studies; further, they can be used to study population variability as an alternative to iPSC-derived models.…”

“…Figure 1 shows the overall workflow of the experiment, data analysis, Bayesian modeling, and CA methods. The detailed methods for the in vitro experiments, including LCL identification, chemical and mixture information, and cytotoxicity data, were previously described [ 47 ]. In brief, 146 LCLs were obtained from The Coriell Institute for Medical Research (Camden, NJ) and comprised cells from four subpopulations, three of European descent (Utah residents with European ancestry (CEU), Tuscans in Italy (TSI), British from England and Scotland (GBR)) and one of African descent (Yoruban from Ibadan, Nigeria).…”

“… Overall workflow to evaluate population variability in mixture additivity. First, lymphoblastoid cell lines from 146 individuals were exposed in vitro to 42 chemicals and 8 defined mixtures in concentration–response [ 47 ]. Cytotoxicity was measured as the endpoint of interest, from which point of departure (POD) and TDVF values were derived using Bayesian concentration–response modeling.…”

“… Comparison of Loewe Additivity Index (LAI) across cell types for cytotoxicity phenotypes. iCell and HUVEC results are from [ 30 ]; LCL results are those for CA Indiv from the present analysis of data reported in [ 47 ]. LAI < 1 indicates greater-than-additive effects (“synergy”) and LAI > 1 indicates less-than-additive effects (“antagonism”).…”

“…These studies suggest that a population-based in vitro NAM may be useful in investigating the intersection of cumulative risk and population variability of mixtures. Therefore, utilizing data from a panel of 146 LCLs from genetically diverse individuals [ 47 ], we apply Bayesian methods to investigate the accuracy of applying CA at either the individual or population level. Specifically, using the same set of 42 ATSDR priority chemicals in 8 defined mixtures as previously investigated [ 30 ], we evaluated the accuracy of CA for predicting points of departure (PODs) for each individual separately and for the “typical” (median) and “sensitive” (first percentile) members of the population.…”