Superfund Research Program
Using a New Model to Identify Health-Impacting Metal Mixtures
Release Date: 03/12/2025
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Highlights:
- Researchers developed a statistical model to estimate the neurobehavioral effects of metals found in drinking water.
- The new model identified six metals, alone and in mixtures, that consistently affected zebrafish behavior.
- More broadly, this approach can help estimate potential neurobehavioral health risks from multiple contaminants in water.
Research Summary
Researchers funded by the NIEHS Superfund Research Program (SRP) developed the linear mixed-effects model (LMM), a framework for statistical analysis, to quickly and effectively estimate the effects of individual metals and metal mixtures on zebrafish larvae behaviors.
Zebrafish are often used as model organisms to study human neurodevelopment because their nervous system is structured similarly to a human’s. Scientists can test effects on zebrafish neurodevelopment by exposing the larvae to certain metals and then measuring their swimming distance.
“We wanted to learn which metals in a mixture where the most responsible for behavioral changes in zebrafish, but current data analysis methods lacked the accuracy needed to do so, especially with a complex fish behavior dataset,” said Nishad Jayasundara, Ph.D., a project leader from the Duke University SRP Center. “So, we set out to develop a new model to overcome those limitations.”
The LMM predicted that six metals can affect larval behavior on their own, as well as three mixtures of metals from the total set of six metals identified.
Developing the New Model
Jayasundara, with support from graduate students Kanchana Dilrukshi and Ilaria Merutka, accounted for the following in the LMM:
- Zebrafish-specific variables, such as the distance each zebrafish traveled.
- Water-specific variables, like the type and concentration of metals in the sample.
- Swimming distance measurements taken from the same larvae over time, accounting for individual differences among larvae.
They tested the LMM using a dataset from a 2021 study, also led by Jayasundara, that used traditional statistical methods to analyze zebrafish larvae swimming distance after the larvae were exposed to metal-contaminated well water from Maine and New Hampshire.
The LMM identified six possible “bad-actor” metals that consistently affected larval motor activity: lead, cadmium, nickel, copper, uranium, and barium. Lead, cadmium, nickel, copper, and barium were linked to decreased larvae swimming distance, while uranium was linked to increased swimming distance. According to the researchers, these findings indicate that exposure to these metals may be linked to developmental delays or hyperactivity, which may be extrapolated to similar disorders in humans.
Additionally, the LMM identified three metal mixtures – barium, copper, and uranium; nickel, lead, and uranium; and barium, lead, and uranium – that affected zebrafish behavior, even at levels where the individual metals are considered safe.
To validate their model’s findings from the drinking water samples, the scientists then exposed zebrafish larvae to the metals individually – excluding uranium, which was too dangerous to test with – and conducted swimming distance tests. They found that exposure to four of the five metals matched the effects the LMM predicted, indicating that the model is relatively accurate. Cadmium was the only metal that did not match the model, which the authors hypothesize may be because not enough cadmium was present in the samples for an accurate prediction.
The Need for a “Bad-Actor” Approach
According to the researchers, while the previous statistical approaches like the one used in the 2021 study are insightful, the new LMM approach allows scientists to consider fish behavioral changes over time and enables identification of any significant metal mixtures to determine the most hazardous compounds in a complex mixture. Defining “bad-actors” in a mixture is becoming increasingly important because of multiple sources of aquatic contamination, the authors say.
Impact Statement
“The LMM we developed provides a more sensitive way to understand how individual metals and metal mixtures in drinking water contribute to zebrafish behavior changes,” said Jayasundara. “More broadly, the study shows that the methods we developed here can be an accurate method of analyzing complex data and revealing the potential neurobehavioral health impacts of exposures to pollutant mixtures.”
For More Information Contact:
Nishad Jayasundara
Duke University
Nicholas School of the Environment
Box 90328
Durham, North Carolina 27708
Email: nj58@duke.edu
To learn more about this research, please refer to the following sources:
- Dilrukshi KR, Merutka IR, Chernick M, Rohrbach S, Babich R, Withanage N, Fernando PW, Jayasundara N. 2024. Determining bad actors: A linear mixed effects model approach to elucidate behavioral toxicity of metal mixtures in drinking water. Ecotoxicol Environ Saf 15:287:117296. doi:10.1016/j.ecoenv.2024.117296 PMID:39536556 PMCID:PMC11629772
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