Mental health is shaped by the complex interplay of genetic and environmental factors, each contributing to individual differences in risk and resilience. While genetic influences are increasingly well-characterized, understanding the role of environment is critical for several reasons. First, environmental exposures are potentially modifiable, and if proven causal, they offer actionable targets for interventions aimed at preventing or mitigating mental illness. Second, quantifying the environment in aggregate within biomedical research has long been challenging, largely because it requires accounting for multiple environmental components at once. As a result, previous studies have often struggled to fully assess environmental exposures and to connect overall environmental burden to health outcomes. Although this remains a complex challenge, recent advances in measurement and analytic methods provide new opportunities to more thoroughly quantify the environment and evaluate its impact on health and disease. Finally, environment is key to understanding mental health disparities, which is crucial for promoting health equity and guiding public health strategies. Focusing on environmental factors can therefore advance mental health understanding and promote more equitable prevention and care across the lifespan.

The exposome as a framework to capture poly-environmental exposures

The exposome framework aims to capture the totality of non-genetic exposures and individual encounters throughout life (Fig. 1), encompassing both the complexity and diversity of environmental influences on health [1]. The exposome can be divided into internal and external domains [2]. The internal exposome includes endogenous factors such as metabolic processes, inflammation, and the microbiome, reflecting the body’s internal response to environmental challenges, while the external exposome consists of exposures outside the body, integrating (i) individual-level exposures related to environmental and lifestyle factors (such as adverse experiences, diet, substance use, physical activity, etc.) and (ii) structural-level exposures which can be captured broadly on country or state level (such as country’s GDP, state-specific legislations) but also more granularly based on geocoded address (such as neighborhood deprivation indices, air pollution, access to green spaces, etc.). This multidimensional approach enables the simultaneous consideration of multiple exposures at multiple levels and aligns with the ecological systems model of human development [3], which recognizes that individuals are shaped by, and embedded within, a web of interacting environmental contexts.

Fig. 1: The exposome and its contributions to health across the lifespan.
Fig. 1: The exposome and its contributions to health across the lifespan.
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Throughout the lifespan, external exposome factors—including individual-level and structural exposures—are integrated within the body as the internal exposome. These dynamic exposures interact across critical life stages, influencing biological processes and shaping downstream health outcomes.

A critical strength of the exposome framework is its intention to link environmental exposures to biological processes, providing mechanistic insight into the biological embedding of environment through molecular, cellular, and physiological pathways that ultimately shape health outcomes [4]. By anchoring exposures to biological alterations, such as epigenetic changes, chronic inflammation, oxidative stress, or metabolic disruptions, the exposome bridges the gap between external factors and the onset or progression of disease, including the process of accelerated aging which is critical to morbidity and mortality [5].

Social determinants of health (SDOH) in the context of the exposome

Social determinants of health refer to the social and environmental conditions, such as socioeconomic status, education, neighborhood, employment, and social support, as well as the broader systems and forces that influence these conditions. These determinants significantly impact health outcomes, particularly mental health [6, 7], and contribute to health inequities both within and between populations [8]. SDOH and the exposome are closely related, both emphasizing that non-genetic environmental factors play a critical role in health and in its inequalities. Despite these similarities, the two concepts differ partly in some ways. SDOH research has focused on both individual-level (e.g., early-life adversities, social connections, food insecurity) and community-level (e.g., racism and other forms of discrimination, neighborhood social and built environment, immigration policies) factors, and has informed both individual (clinical) and policy (socioeconomic) strategies aimed at improving mental and physical health [9, 10]. The exposome aims to capture the totality of non-genetic exposures throughout an individual’s life, including physical and chemical exposures along with social and structural factors. Methodologically, the exposome integrates social exposures with downstream biological data, providing a perspective on how the environment “gets under the skin” to influence health. By linking the external exposome (including SDOH) with the internal exposome, the exposome framework inherently captures the pathway from environmental exposures to biological effects. In this way, the exposome adds biological depth to the SDOH concept by enabling a bio-psycho-social and mechanistic understanding of how diverse environmental factors jointly interact to shape health. In contrast, the study of SDOH allows for the examination of the contribution of specific social factors (e.g., childhood abuse, interpersonal violence, housing stability) to a person’s overall health.

The complexity of exposome’s effects on mental health throughout the lifespan

Understanding how the environment contributes to health is a complex challenge, given the vast array of exposures, their timing, and the ways they interact with individual biology and social context. Two notable theories showcase this complexity and require consideration when studying environment’s effect across the lifespan. The differential susceptibility theory highlights interindividual differences in sensitivity to environmental influences. These differences, rooted in each person’s unique biological or psychological makeup, can result in greater responsiveness to both positive and negative environmental factors [11]. In this context, using data-driven approaches to study exposomic effects on health is essential, as it enables the identification of not only risk factors but also protective environmental influences that support resilient mental health trajectories. This is especially important because traditional biomedical research often emphasizes risk exposures, potentially overlooking environmental factors that promote resilience. The sensitive period theory emphasizes that the timing of exposure is crucial, with certain developmental windows making individuals especially vulnerable to environmental influences [12]. Below we highlight key considerations for environment’s contributions to mental health in different epochs throughout the lifespan:

Peri-natal and early childhood

Considered sensitive periods owing to the robust brain development early in life, there is strong evidence that peri-natal exposures, such as maternal stress, nutrition, and environmental toxins, can have profound and lasting impacts on neurodevelopment and subsequent mental health outcomes [13]. Additionally, studies indicate that childhood exposure to environmental chemicals, including heavy metals, endocrine disruptors, and pesticides, is associated with an increased risk of mental health problems in children [14].

Adolescence

This is another window of heightened plasticity due to the brain’s maturation processes alongside transition to puberty. During adolescence, peer influences, school environment, and digital exposures become especially prominent aspects of the exposome. Evidence suggests that social stress and substance use during this period may influence long-term emotional regulation and mental health trajectories [15].

Adulthood

Here individual agency grows, and the exposome is increasingly shaped by occupational and lifestyle choices. Chronic exposures, such as persistent work stress, urban pollution, or unhealthy habits, can accumulate, contributing to allostatic load and increased risk for physical and mental health outcomes including mood, anxiety, and psychotic disorders [16].

Older age

In later life, factors like loneliness, social isolation, and the quality of social connections become central to the exposome’s impact on mental health, with robust links to depression, cognitive decline, and dementia risk [17]. With aging, physical morbidity becomes more salient and reciprocates with mental health, further complicating contributions of exposome to mental health through its well-established effects on age-related diseases [18].

Table 1 summarizes recent works that apply data-driven exposomic approaches, such as exposome-wide-association-studies, to model environment’s contribution to mental health outcomes across the lifespan.

Table 1 Exposomic research related to mental health across the lifespan.
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The added value of applying the exposome framework in mental health research

There is a long history of research demonstrating the importance of environmental contributions to mental health, yet the exposome framework offers critical advances that move the field forward. Unlike traditional studies that typically examine environmental factors in isolation, the exposome framework enables integration and assessment of cumulative “poly-environmental” burden, better reflecting the complex and multifactorial nature of real-world exposures. Furthermore, instead of restricting analyses to specific, pre-selected exposures, this approach employs data-driven methodologies to systematically explore all available environmental data, facilitating the discovery of novel associations and interactions. It is important to acknowledge, however, that the entire exposome cannot truly be captured in any single study, comprehensively measuring all exposures throughout the life course is not feasible. As such, methods like exposome-wide association studies (ExWAS) are limited to the exposures collected within a given cohort, and these will inevitably differ across studies. Nevertheless, by conceptualizing the exposome as a holistic, underlying environmental factor that can be reflected through multiple measurements, this framework improves generalizability across different cohorts and study settings. Even when the specific exposures measured vary across studies, findings become less reliant on any single set of exposures and may be more robust overall.

Critical gaps in understanding exposome’s role in mental health

To advance the field, it is essential to chart future directions for exposome research in mental health by embracing comprehensive, agnostic, and longitudinal approaches that can disentangle the complex interplay of environmental exposures and their mechanistic links to psychiatric outcomes. Equally important is the translation of exposome science into clinical mental healthcare, where integrating exposomic data into risk assessment, precision medicine, and personalized interventions promises to enhance prevention, diagnosis, and treatment for diverse patient populations. Below we propose key future directions.

Suggested next steps for integrating exposome and SODH in mental health research

  • Building scalable, longitudinal exposome datasets using different sources: Advancing exposome research in mental health requires a shift toward compiling large, longitudinal datasets that capture a broad array of environmental, lifestyle, and SDOH across the life course. Cohorts should be designed to systematically and repeatedly measure diverse aspects of the exposome, including individual and structural exposures, as well as social, behavioral, chemical, and physical factors, to ensure robust coverage of the many environmental dimensions relevant to mental health. Importantly, researchers should harness scalable data sources, such as electronic health records (EHRs), which, if properly curated and linked with environmental data, can provide rich, real-world information on both exposures and health outcomes across diverse populations. By leveraging both traditional cohorts and EHRs, the field can greatly expand its capacity to understand environmental contributions to mental health, enabling more nuanced and powerful analyses of exposome-health outcome relationships. To maximize impact, fostering a culture of data sharing among researchers is essential. We recognize, however, that sharing EHR data presents greater challenges.

  • Integration with multi-omic approaches: Integrating exposomic and SDOH data with other omics, such as genomics, epigenomics, and metabolomics, within disease models provides a more complete picture of disease causes and progression. This approach uncovers how genes, environment, and social context interact to shape health. For example, exposomic scores that aggregate multiple environmental exposures into a single measure of environmental risk can allow researchers to quantify and integrate the cumulative impact of the exposome on health outcomes alongside other biological risk scores such as polygenic scores, facilitating research on gene-environment mechanisms that are not bound to limitations of multiple testing of isolated environmental or genetic factors.

  • Integrating exposome research with genetically informed study designs: Effective progress in understanding mental health etiology demands analytic methods that explicitly account for the interplay between genes and environment. Genetically informed study designs, such as twin and family studies or Mendelian randomization, along with advanced statistical approaches for modeling gene–environment correlation and longitudinal tracking of exposures and outcomes, can help disentangle the overlapping and interactive contributions of genetic and environmental factors.

  • Generalization and standardization in exposome research: To ensure reproducibility and  external validity, exposome research should prioritize both the generalization of findings and the standardization of measurement methods. One practical approach is to develop aggregate exposomic models that can be applied across cohorts, even when individual exposure features differ within each individual cohort, so long as they capture comparable environmental domains. While perfect harmonization may not always be possible, models that reflect similar environmental constructs can still enhance cross-cohort comparability. At the same time, the field should work toward standardized, validated tools and protocols for exposome quantification and exposure assessment. Standardization will enable better data sharing, replication, and meta-analyses, driving scientific progress and improving study comparability. Achieving this ambitious goal will likely require coordinated global initiatives, much like those that have advanced genomics and neuroimaging research. The recent Exposome Moonshot Forum initiative exemplifies a promising step toward meeting these challenges [19].

  • Advancing causal inference: Robust causal inference methods are essential to clarify how environmental factors drive health outcomes. Leveraging large-scale longitudinal data and novel analytic approaches (e.g., modern matching methods) will disentangle causation from correlation, informing targeted interventions [20]. For example, when evaluating the potential causal effect of a specific exposure, researchers can use aggregate exposome scores to match participants on their overall environmental burden. By doing so, it becomes possible to better isolate the effect of the specific exposure from other correlated environmental factors, thereby strengthening causal inference regarding its association with the outcome of interest.

  • Understanding the stability versus dynamic nature of the exposome across the lifespan: Some exposures are persistent, while others are transient, highlighting the need for longitudinal studies that track changes in exposomic profiles and their mental health consequences over time.

  • Developing methods to quantify and understand the digital exposome: As smartphone use becomes ubiquitous across the lifespan, understanding the “digital exposome”, encompassing digital interactions, online stressors, social media engagement, and use of AI, is critical for mental health research. These exposures disproportionately affect digital-native generations, shaping emotional well-being and risk for disorders. Future work should quantify how digital and traditional offline exposures jointly influence mental health.

Suggested next steps for integrating the exposome and SODH in clinical care

  • Enhancing risk classification and precision medicine: Incorporating exposome and SDOH data into clinical models allows for more nuanced risk classification, advancing the goals of precision medicine. Rather than relying solely on traditional clinical risk factors or genetic data, clinicians can use detailed environmental and social exposure profiles to identify patients at higher risk for specific diseases or adverse outcomes. This approach recognizes that environmental and social factors are major drivers of disease variability and progression, and that their inclusion can improve the accuracy of diagnosis, prognosis, and treatment selection.

  • Targeting individual-level causal exposures: A key clinical implication is the prioritization of interventions that address individual-level causal exposures. By identifying actionable environmental or behavioral risk factors (e.g., exposure to specific pollutants or psychosocial stressors), clinicians can recommend feasible targeted interventions that are impactful for patients. This may include personalized lifestyle modifications, environmental risk mitigation, or referrals to community resources that address specific social needs.

  • Psychoeducation and empowerment: Psychoeducation is essential for helping clinicians, patients, and families understand the role of exposome and SDOH in health and disease. Educating all stakeholders about how environmental and social factors contribute to illness and health disparities can foster greater engagement, collaboration in shared decision making, adherence to interventions, and advocacy for healthier environments. This includes discussing the modifiable nature of many exposures and the interplay between environment and biology.

Conclusions

The exposome framework holds transformative potential for both research and clinical mental health aspects. From a research perspective, advancing exposome science enables a shift from descriptive associations to actionable insights, uncovering root causes of health disparities and informing policies that promote equity. Clinically, integrating exposome and SDOH data empowers providers to identify at-risk individuals, tailor interventions to modifiable environmental and social factors, and educate patients and families about external drivers of health and disease. Together, these advances bridge the gap between environmental understanding and real-world application, fostering precision prevention, personalized care, and a more equitable future for mental health across the lifespan.