A team led by Adam Socrates of King’s College London and the Icahn School of Medicine at Mount Sinai, together with Jessie Baldwin of University College London, veteran psychosis researcher Robin Murray, Paul O’Reilly of Mount Sinai, and Jean-Baptiste Pingault of King’s College London, set out to test a deceptively simple question: if you measure someone’s inherited liability to psychopathology, does it predict their exposure to environmental risk? The answer, drawn from one of the largest and most systematic screenings ever attempted in this field, is a qualified but striking yes.

The researchers harnessed data from the UK Biobank, a vast biomedical database containing genetic and health information from roughly half a million British adults. Crucially, they restricted their sample to 307,493 participants who had no recorded diagnosis of schizophrenia, bipolar disorder, or major depressive disorder, and who were not taking antipsychotic medication. This design choice matters: by excluding people already diagnosed with serious mental illness, the team could ask whether genetic risk predicts environmental exposure before any disorder emerges, rather than simply detecting the downstream consequences of being ill.

On the genetic side, the investigators computed nine polygenic scores — numerical summaries of the small genetic variants scattered across a person’s genome that collectively contribute to a trait or condition. These scores covered attention deficit hyperactivity disorder, schizophrenia, bipolar disorder, major depression, neuroticism, educational attainment, and other genetically influenced characteristics. The scores were generated using PRS-CS, a sophisticated statistical method that leverages large-scale genome-wide association data to sharpen the predictive power of polygenic scores, improving on older approaches that count risk variants more crudely.

On the environmental side, the team assembled an extraordinary catalogue of 49 distinct risk factors, spanning five broad categories: victimisation and adverse life events, socioeconomic circumstances, behavioural and lifestyle factors, cognitive and educational measures, and perception-based or subjective factors such as how people appraise their own lives. Each polygenic score was then tested against each environmental factor in a grid of 441 standardised linear regression models, using HC1 robust standard errors — a statistical safeguard that protects against distortions caused by uneven variability in the data, a common problem in large biobank samples.

Because so many tests were run, the risk of false positives was substantial. To guard against this, the researchers applied false discovery rate correction within each polygenic score, a procedure that adjusts the statistical threshold so that the expected proportion of spurious findings stays controlled. Even under this conservative standard, 212 associations survived. That is a remarkable yield, and it suggests that the overlap between genetic liability and environmental exposure is not a statistical artefact but a pervasive feature of the data.

The breadth of the associations varied by genetic score. Polygenic scores for ADHD, educational attainment, major depression, schizophrenia, and bipolar disorder showed the widest-reaching profiles, correlating with environmental factors across multiple domains. Yet the pattern was not uniform: each score carried its own signature of environmental associations, hinting that different forms of inherited liability travel along different social and behavioural routes. A genetic predisposition toward ADHD, for example, may nudge individuals toward different life circumstances than a predisposition toward depression, even when both ultimately relate to elevated psychiatric risk.

One of the study’s most provocative findings emerged from a secondary analysis. When the team separated environmental factors into those involving perception or subjectivity — how people interpret and report their experiences — and those that are more objective, they found that seven perception-related factors showed stronger pooled associations with polygenic scores for schizophrenia, major depression, ADHD, bipolar disorder, and neuroticism than the 25 objective factors did. In other words, the genetic signal seemed to flow more strongly through the lens of subjective experience than through externally verifiable circumstances. Four conceptually tighter matched comparisons — pairing subjective and objective measures of the same underlying construct — produced a similar pattern, although it was not entirely consistent across all comparisons.

The authors are careful about interpretation, and the caveats deserve emphasis. The effects observed were small, and the study is observational: it establishes correlation, not causation. A polygenic score predicting environmental exposure does not mean genes directly cause adversity. Instead, the findings point to what behavioural geneticists call gene–environment correlation, the process by which inherited tendencies influence the situations people encounter. A person genetically inclined toward impulsivity may, for instance, drift into riskier social settings; a person with inherited cognitive tendencies may attain different levels of education and income; and inherited differences in temperament may colour how people perceive and report the events of their lives.

This mechanism has profound implications for psychiatric research. Many celebrated studies of environmental risk — childhood adversity, urban upbringing, socioeconomic deprivation — implicitly assume that these exposures are independent of genetic liability. If they are not, some portion of the apparent environmental effect may actually reflect inherited confounding, meaning that genetic risk inflates both the exposure and the outcome. The new findings suggest that measured environmental risk is partly correlated with inherited liability through behavioural, social, socioeconomic, cognitive, and perception-related pathways. Future studies of environmental effects on mental health, the work implies, should routinely adjust for or otherwise account for polygenic liability, or risk overstating purely environmental causes.

There is also a subtler lesson about measurement. The stronger links between genetic scores and subjective, perception-based factors raise the possibility that some of what researchers record as environmental exposure is filtered through the same psychological tendencies that genetics influence. Two people may live through objectively similar events yet encode them very differently, and those differences in appraisal are themselves partly heritable. That does not make subjective reports unreliable — how people perceive their lives is genuinely consequential for mental health — but it complicates the tidy division between what happens to us and what we are.

The study’s scale and rigour lend it unusual weight. Running 441 pre-specified models with robust standard errors, correcting for multiple testing, and probing results with matched comparisons reflects a level of methodological discipline that the field has often lacked. The use of a sample free of major psychiatric diagnoses strengthens the argument that genetic risk shapes environmental exposure in the general population, not merely among the ill. And the open-access publication means the full analysis is available for scrutiny and reuse by other researchers.

Still, the work is a beginning rather than an endpoint. The UK Biobank is a predominantly British, largely European-ancestry sample, and polygenic scores derived from European genome-wide studies lose accuracy in other populations, so the findings will need replication in more diverse cohorts. The environmental measures, though numerous, are self-reported and cross-sectional, limiting what can be said about the direction of effects over time. Longitudinal designs — following genetically characterised individuals from childhood — will be essential to disentangle whether genetic liability truly precedes environmental exposure, and through which specific pathways.

What the study delivers now is a conceptual correction with viral potential: the tidy story in which genes and environment are separate contributors to mental illness is wrong, or at least incomplete. Our inherited makeup quietly helps write the circumstances of our lives — the neighbourhoods, the stresses, the perceptions — that in turn feed back into mental health. Understanding that loop, rather than pretending it does not exist, may be the key to designing interventions that genuinely break the cycle of psychiatric risk.

Subject of Research: Gene–environment correlation between polygenic scores for psychopathology and environmental risk factors

Article Title: Genetic risk of psychopathology predicts environmental risk

Article References: Socrates, A., Baldwin, J. R., Murray, R. M., O’Reilly, P. F., & Pingault, J.-B. (2026). Genetic risk of psychopathology predicts environmental risk. Schizophrenia. https://doi.org/10.1038/s41537-026-00805-3

Image Credits: AI Generated

DOI: 10.1038/s41537-026-00805-3

Keywords: polygenic scores, gene-environment correlation, psychiatry, UK Biobank, schizophrenia, major depression, ADHD, bipolar disorder, neuroticism, environmental risk factors, behavioural genetics, psychosis

The urgency of this shift is grounded in hard epidemiological data. Twin studies and large meta-analyses indicate that genetic factors explain only a modest fraction of chronic disease burden, with heritability estimates for most human traits far below what would be needed to account for the rapid global rise of immune-mediated disorders. Genes simply do not change fast enough to explain why inflammatory bowel disease has surged in industrialized nations and is now emerging in regions that historically had very low incidence. Population-based studies of immigrants tell a striking story: people who move from low-incidence to high-incidence countries acquire elevated disease risk within a single generation, and their children, born in the new environment, often reach incidence rates approaching those of the host population. That pattern points squarely at modifiable environmental exposures acting on genetically susceptible individuals.

Decades of research have already identified a substantial catalog of risk factors. Smoking increases the risk of Crohn’s disease while paradoxically appearing protective in ulcerative colitis, yet molecular work shows that smoking alters DNA methylation at inflammatory loci in ways that plausibly mediate gut inflammation. Air pollution has been linked to ulcerative colitis through epigenetic changes in the CXCR2 gene and the MHC class III region. Antibiotic use, particularly early in life and during pregnancy, disturbs the developing gut microbiome and raises offspring risk. Appendectomy, oral contraceptives, gastrointestinal infections with pathogens such as Salmonella, Campylobacter and Helicobacter species, and Epstein-Barr virus timing all leave measurable fingerprints on disease risk. Conversely, protective exposures have emerged too: early-life contact with agriculture, biodiversity and green space, a diverse diet rich in plant-based foods, and physical activity are consistently associated with lower incidence.

The Perspective distinguishes carefully between early-life and later-life exposures, a distinction the authors argue is essential for prevention science. The developmental origins of health and disease paradigm, rooted in David Barker’s work on fetal programming, holds that exposures during critical windows of immune and microbiome development can set long-term trajectories of disease susceptibility. In inflammatory bowel disease, the preclinical phase can last years, with altered gut microbiome composition, elevated fecal calprotectin and subtle immune changes detectable in at-risk first-degree relatives long before symptoms appear. Studies analyzing deciduous teeth have even reconstructed prenatal and postnatal metal exposure histories, linking them to later Crohn’s disease risk. Early exposures such as mode of delivery, breastfeeding, infant diet diversity and childhood antibiotic courses therefore represent unusually potent intervention targets, because they act before the disease process has gained momentum.

At the same time, the authors highlight exposures that traditional epidemiology has largely overlooked, and this is where the exposome concept becomes technically transformative. Food contact contaminants are a case in point. Plastic teabags release billions of microparticles and nanoparticles into hot tea, microwavable plastic containers shed both microplastics and intentionally and non-intentionally added chemical substances, and nonstick cookware can contaminate food with microplastics and PTFE. Perfluoroalkyl and polyfluoroalkyl substances, the so-called forever chemicals, migrate from food packaging into the diet, and elevated serum levels of these compounds have been associated with later occurrence of inflammatory bowel disease and with intestinal barrier defects in experimental systems. Pesticide residues on produce, antibiotic residues in animal products, and synthetic chemicals in processed food collectively form a chronic, low-dose chemical mixture that no single-exposure study can adequately capture.

Among emerging pollutants, microplastics and nanoplastics occupy a special place of concern. These particles have now been detected in human stool, blood, lung tissue, placenta, atherosclerotic plaques and even human brain tissue, with some evidence of bioaccumulation over time. In animal models, chronic exposure to polystyrene nanoplastics induces mechanical and immune barrier dysfunction in the intestine. In humans, one analysis of fecal samples found that microplastic concentrations correlated with inflammatory bowel disease status, although the authors of the new Perspective are careful to note that causality remains unproven and that more rigorous science, standardized definitions and better detection methods are urgently needed. Novel analytical tools, including stimulated Raman scattering microscopy capable of single-particle nanoplastic imaging and surface-enhanced Raman spectroscopy with nanogap arrays, are now making it possible to detect and quantify these particles at environmentally relevant concentrations.

Measurement technology is the second pillar of the exposome revolution. High-resolution mass spectrometry platforms can now screen thousands of chemicals in biological samples without needing to know in advance which ones to look for, an approach known as non-targeted analysis. Coupled with ion mobility separation and computational metabolomics, these platforms are expanding the observable chemical space of human exposure from a few hundred targeted biomarkers to tens of thousands of features. On the statistical side, new methods designed for real-world exposure complexity, including weighted quantile sum regression, quantile-based g-computation and Bayesian kernel machine regression, allow researchers to model the health effects of correlated chemical mixtures rather than isolated agents. Machine learning approaches have begun to identify synergistic interactions among pesticides, phthalates, phenols and trace metals, and longitudinal personal monitoring with wearable sensors has revealed how dynamically an individual’s chemical exposure profile shifts from day to day.

The framework’s most consequential contribution, however, may be its prevention architecture, which differentiates between primary and primordial prevention. Primary prevention, borrowed from cardiovascular medicine, means identifying individuals at elevated risk, such as first-degree relatives of patients with inflammatory bowel disease, stratifying them by genetic, microbiome and exposome risk scores, and intervening before disease onset. Recent trials in adjacent fields show this is feasible: teplizumab has delayed type 1 diabetes in at-risk relatives and abatacept has shown promise in preventing rheumatoid arthritis in high-risk individuals, providing templates for immunoprophylaxis in inflammatory bowel disease. Primordial prevention operates one level deeper, aiming to lower the population-wide baseline of risk before susceptibility even arises, through community and policy interventions. Crucially, the authors emphasize the actionable exposome: those exposures that individuals, clinicians or policymakers can realistically modify today, as opposed to the vast conceptual exposome that remains beyond immediate control.

Individual-level mitigation strategies already have an evidentiary basis. Lifestyle studies suggest that a substantial fraction of inflammatory bowel disease cases could be prevented through modifiable behaviors, including a prudent plant-rich diet, regular physical activity, smoking cessation and avoidance of e-cigarettes. Randomized trials have shown that a low-plastic diet reduces urinary levels of plastic-associated phthalates and bisphenols, while simple dietary choices, such as avoiding heating food in plastic containers, reduce microplastic intake. For persistent pollutants like PFAS, interventions including plasma donation and anion exchange resin treatment have demonstrated measurable reductions in body burden. Dietary components rich in anthocyanins and other antioxidants may counteract some pollutant effects. At the community level, the levers are broader: air quality regulation, pesticide policy, green urban planning, washing machine filtration to reduce microfiber emissions, point-of-use drinking water filters, and international treaties to end plastic pollution all shape the exposures that entire populations experience from conception onward.

The authors also confront the global inequities embedded in this agenda. Inflammatory bowel disease is progressing through four epidemiological stages worldwide, from nascent emergence to high prevalence, and the environmental drivers differ profoundly between a newly industrializing city in Asia and a saturated North American market. Industrialized nations that created the modern exposome bear responsibility for generating evidence and technology that low- and middle-income regions can adapt as they urbanize, ideally avoiding the worst exposures from the start. Whether the exposome framework can also illuminate other overlapping immune-mediated diseases, from multiple sclerosis to rheumatoid arthritis, remains an open and tantalizing question. What is clear from this Perspective is that the era of treating environmental risk as an afterthought to genetics is ending, and that a coordinated science of exposure measurement, risk prediction and two-tiered prevention offers the first realistic pathway toward a future in which inflammatory bowel disease is not merely treated but prevented.

Subject of Research: The role of lifespan environmental exposures, the exposome, in inflammatory bowel disease risk and prevention

Article Title: The exposome and inflammatory bowel disease: a framework for primary and primordial prevention

Article References: Agrawal, M., Midya, V., Vianello, A., Valvi, D., Kaplan, G. G., & Colombel, J.-F. (2026). The exposome and inflammatory bowel disease: a framework for primary and primordial prevention. Nature Reviews Gastroenterology & Hepatology. https://doi.org/10.1038/s41575-026-01260-2

Image Credits: AI Generated

DOI: 10.1038/s41575-026-01260-2

Keywords: exposome, inflammatory bowel disease, Crohn's disease, ulcerative colitis, microplastics, PFAS, prevention, environmental risk factors, gut microbiome, air pollution, early-life exposures, epigenetics