Can Your Genes Predict Your Neighborhood?
Your genetic makeup may determine where you decide to live
A new study published in Nature is the largest attempt yet. An international team pooled genetic and personality data from 46 research cohorts, covering between about 611,000 and 1.14 million people depending on the trait. They focused on the “Big Five” personality traits that psychologists use to describe nearly everyone:
- Extraversion: sociable, assertive, energetic
- Agreeableness: compassionate, respectful, trusting
- Conscientiousness: organized, productive, responsible
- Neuroticism: prone to anxiety, low mood and emotional ups and downs
- Openness to experience: curious, imaginative, drawn to art and ideas
The researchers scanned the genome for markers linked to each trait. They then asked three questions: Do these genetic links hold up across countries, ages and personality questionnaires? Are they real, or just a side effect of how families live? And how do they connect to health, behavior and life outcomes?
What Makes This Study Noteworthy
Your personality genes may track where you end up living. Among roughly 419,000 UK Biobank participants, people whose genes tilted toward high openness were more likely, by age 50 and older, to have moved into cosmopolitan, professional city neighborhoods. People whose genes tilted toward high conscientiousness were more likely to have moved out of those areas and into affluent suburbs. The analysis accounted for where people were born, so it reflects where they moved. These effects are small, though. The authors stress that these genetic scores cannot predict any one person’s future.
Personality is written in thousands of tiny genetic nudges. The study identified 1,260 genetic markers linked to personality, 824 of them never reported before. That’s 3 to 43 times more than earlier studies found, depending on the trait. Yet each marker matters very little on its own: a typical extraversion marker shifts a person from the 50th to about the 50.35th percentile. The researchers estimate that roughly 16,000 independent common variants contribute to each trait, on average.
Genes explain only part of the picture. Common genetic variants accounted for about 5 to 9 percent of the differences in personality between people, or up to about 13 percent when personality was measured with more reliable questionnaires. Twin studies put the total genetic influence closer to 40 to 60 percent. Either way, environment and life experience play a major role.
Family upbringing isn’t distorting the results. For many traits, such as educational attainment, genetic studies are partly inflated by family factors like shared wealth or parenting. To check for this, the researchers compared siblings within the same families. For personality, the within-family results were nearly identical to the population-wide results (about 96 percent as strong). For educational attainment, the comparable figure is closer to 60 percent.
Birds of a feather don’t flock together, at least genetically. Spouses were barely more similar in their personality genetics than two people picked at random. That’s far less than the genetic similarity spouses show for educational attainment.
Personality genetics overlap with mental and physical health. Genes linked to neuroticism overlapped strongly with genetic risk for depression, anxiety and related conditions. Genes linked to conscientiousness overlapped with less substance use, more frequent exercise, lower body weight and fewer hospital stays. Some analyses suggested these links may be causal (for example, conscientiousness lowering BMI and smoking), but the authors describe these as “plausible” and in need of confirmation.
Your genes may even shape whether you take part in research. Genes associated with openness and agreeableness were linked to completing optional research questionnaires. Genes associated with neuroticism were linked to skipping them and answering “I don’t know” more often. That suggests the people who end up in survey-based studies may not be a neutral sample.
Long-held brain-chemistry theories took a hit. Popular theories link extraversion and openness to dopamine, and the other traits to serotonin. The genetic data offered little support for either. Instead, the signals pointed to genes active in neurons broadly, and in the prefrontal cortex for every trait except agreeableness.
Limitations and cautions
Limited diversity. About 95 percent of participants had European ancestry, and all the regions compared were Western. The findings may not hold as strongly for other populations.
- No individual predictions. These are group-level patterns. A genetic score cannot tell you who a specific person is or will become.
- Not pre-registered. The authors state that the analysis plan wasn’t registered in advance, which matters in a study with this many analyses.
- Causal claims are tentative. The “causal” findings rely on Mendelian randomization, a method that uses genes as a natural experiment. It’s informative, but it rests on assumptions that can be hard to verify for behavioral traits.
- Agreeableness is the least consistent trait. Its genetic links varied more across countries and questionnaires than the other four traits.
The Tessa Overall Score
TScore: 83 / 100 🟢 Green
A strong green score. Tessa found well-reported, methodologically rigorous research whose main conclusions are well supported. The limits are the ones typical of large observational studies, and the most ambitious claims, about cause and effect, are appropriately cautious.
The Tessa Graphical Abstract of its analysis of the paper “Robust inference and correlates from genetic associations with personality”
Tessa Analysis Breakdown
Tessa evaluates every paper across three main pillars (Transparency, Explainability and Significance), broken into five weighted sub-scores:
| Category | Score | Weight | What it means |
|---|---|---|---|
| Theoretical vs. Experimental | 70 | 27% | Built on real-world data from over a million people, but observational rather than a controlled experiment. |
| Weak to Rigorous | 74 | 27% | Unusually thorough checks for robustness and confounding; causal claims are more tentative. |
| Known to Novel | 70 | 27% | The question isn’t new, but the scale, family-based checks and 824 new markers advance the field substantially. |
| Journal Score | 100 | 14% | Published in Nature. |
| Media Score | 35 | 5% | Modest online discussion relative to the study’s scope. |
Tessa’s Deep Dive then checked the paper against two established frameworks for observational research:
| Framework | Focus Area | Result |
|---|---|---|
| STROBE | Reporting completeness | 90%. 27 of 30 applicable items addressed at least in part. Strong on rationale, methods and statistics; gaps in missing-data handling and participant flow, much of which sits in the supplementary materials. |
| ROBINS-E | Risk of bias | Some Concerns. Low risk for how genes were measured. Some concerns for confounding, participant selection, personality measurement, missing data and the lack of pre-registration. |
Tessa’s key insight: The study’s own finding that personality genes influence who completes research questionnaires has a second implication. If participation in the cohorts depended on personality, that could subtly skew the genetic results themselves. Tessa flagged this as a potential selection bias that the authors didn’t directly address.
Citation check
- 95 references; 79 citations assessed in context, with an average relevance of 7.3 out of 10.
- 46 citations strongly support the claims they’re attached to, and 24 partially support them.
- 9 were flagged for a closer look. They were looser fits rather than errors.
Strengths
- A very large sample, pooled across 46 cohorts in multiple countries.
- Results replicated closely when the cohorts were split into two halves and analyzed separately.
- Three separate family-based designs (twins, parents and children, and siblings) all point to minimal family confounding.
- Open science: analysis code, procedures and summary data are publicly available.
- The authors are careful to say the findings can’t predict individuals and that causal claims need confirmation.
Weaknesses
- About 95 percent European-ancestry participants; findings in other populations are less certain.
- No pre-registered analysis plan, despite a very large number of analyses.
- Possible selection bias from who chooses to take part in research.
- Personality was measured with different questionnaires across cohorts, which adds noise, especially for agreeableness.
- Key details on participants and missing data are in the supplements rather than the main paper.
Read Tessa’s full summary analysis of this paper, including the author and institution relationship map, citation timeline and a gallery of the paper’s figures that you can check with Google Image Search, at tessapp.ai/report/42686911.
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