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