The ethical aspects of exposome research: a systematic review

Abstract

In recent years, exposome research has been put forward as the next frontier for the study of human health and disease. Exposome research entails the analysis of the totality of environmental exposures and their corresponding biological responses within the human body. Increasingly, this is operationalized by big-data approaches to map the effects of internal as well as external exposures using smart sensors and multi-omics technologies. However, the ethical implications of exposome research are still only rarely discussed in the literature. Therefore, we conducted a systematic review of the academic literature regarding both the exposome and underlying research fields and approaches, to map the ethical aspects that are relevant to exposome research. We identify five ethical themes that are prominent in ethics discussions: the goals of exposome research, its standards, its tools, how it relates to study participants and the consequences of its products. Furthermore, we provide a number of general principles for how future ethics research can best make use of our comprehensive overview of the ethical aspects of exposome research. Lastly, we highlight three aspects of exposome research that are most in need of ethical reflection: the actionability of its findings, the epidemiological or clinical norms applicable to exposome research and the meaning and action-implications of bias.

Enabling the Nonhypothesis-Driven Approach: On Data Minimalization, Bias, and the Integration of Data Science in Medical Research and Practice

“…Furthermore, we have found in the literature that, if a particular formulation of the principle of data minimalization includes the need for a "particular research question" that one attempts to answer via one's research approach, then there is a possibility for conflict between the two (Safarlou et al 2023). This possibility depends on whether the granularity of the word "particular" implies a research question being "informed by a prior hypothesis that determines which data should be gathered."…”

“…If a specific formulation of the principle of data minimalization does not allow for nonhypothesis-driven research, then it needs to be reformulated. Also, researchers doing nonhypothesis-driven research should then look into other measures for guarding against (the harmful effects of) data leaks and for making it easy to share and reuse data, such as those recommended by the FAIR principles (Safarlou et al 2023).…”

“…Also, with respect to cognitive bias, such an approach affords the elimination of confirmation bias (and the identification of confounders) to the extent to which confirmation bias affects variable selection. For an overview of discussions of statistical bias, 'normative' bias, and how these two interact with each other, see (Safarlou et al 2023). 4 Note that we do not exhaustively discuss all positive (or potentially negative) ethical and epistemic aspects of the nonhypothesis-driven approach in this commentary.…”