Can our genes predict where mental illness affects the brain?

Researchers from the NIHR Maudsley BRC and King’s College London have been exploring the relationship between the genetic risk of mental health conditions and the brain structures involved. The hope is that a new approach – GEDAR – can provide insight into why, when and how mental health and illness varies between individuals and over time. In this blog Dr Daniel Martins, Professor Danai Dima and Dr Alessio Giacomel describe the findings of a recent study they published using the GEDAR approach.

Psychiatric disorders such as depression and schizophrenia, and neurodevelopmental conditions such as ADHD are strongly influenced by genetics. At the same time, brain scans consistently show that these conditions affect specific brain regions rather than the brain as a whole.

What has remained unclear is how these two facts connect. In particular, researchers and clinicians are interested to find out if genetic risks actually help explain where in the brain these disorders leave their mark?

Genetic maps and real brain changes

In a recent study, published in Molecular Psychiatry, we explored this question by linking genetic risk data with maps of gene expression across the human brain, using a new approach called Gene Expression–based Disorder-Associated Risk (GEDAR).

The idea behind GEDAR is simple. Instead of asking how genetic risk affects individuals, we asked how it is distributed across the brain. In this study we started with large genetic studies of seven major mental health conditions - Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Obsessive Compulsive Disorder, Anorexia Nervosa, ADHD and Autism Spectrum Disorder. From this we identified the genes whose activity is predicted to change for each disorder We then projected those genes onto detailed maps of where they are normally expressed in the brain, derived from the Allen Human Brain Atlas. This allowed us to create brain-wide maps showing predictions for the location of genetically driven changes in the gene expression.

The crucial question was whether these genetic maps resemble real brain changes observed in patients. To answer this, we compared GEDAR maps with thousands of MRI scans analysed by the ENIGMA Consortium, which has identified reliable patterns of brain structure differences across mental health conditions.

Different genetic risk maps for different conditions

The results were strikingly selective. For major depressive disorder, genetic risk mapped strongly onto both cortical and subcortical brain changes. In other words, the brain regions where genetic data predicted there would be the most altered gene expression are also the regions most affected in depression. Many of these genes are involved in immune and inflammatory processes, adding spatial evidence to the growing link between depression, inflammation, and brain structure.

For ADHD and schizophrenia, the alignment appeared mainly in deeper, subcortical brain regions such as the striatum or the hippocampus. In ADHD, the implicated genes were tied to brain development and connectivity, while in schizophrenia they were largely immune-related. Other conditions, such as autism, anorexia nervosa, and obsessive–compulsive disorder, showed little correspondence between genetic maps and adult brain structure.

Importantly, this doesn’t mean genetics are less important in those conditions. Instead, it is likely that it reflects timing. Some disorders may be shaped by genetic effects early in development, long before adult brain structure can be measured with MRI. Our approach captures where genetic risk is expressed in the adult brain (from donors toughly between 24 and 57 years old), and not when it exerts its strongest influence which is likely to be earlier in life.

Figure 3. Correlation between ENIGMA and GEDAR brain maps (calculated from both up- and down-regulated TWAS genes). Panel A shows regional distributions of Z-scores of Cohen’s d effect sizes capturing changes in cortical thickness and subcortical volumes between patients and healthy-controls as provided by the respective ENIGMA meta-analysis (left panel); we also display our estimated GEDAR maps estimated from both up- and down-regulated TWAS genes by applying three different thresholds (top 10, 5 and 1%) to select the most differentially expressed genes. Panel B depicts spearman correlations between ENIGMA maps of structural differences and GEDAR maps calculated at the three different thresholds separately for cortical and subcortical regions. Significance was calculated by generating 1000 random spin permutations to account for spatial autocorrelation. The * highlights significant correlations at pspin<0.05. Abbreviations: Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Anorexia Nervosa (AN), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Obsessive Compulsive Disorder (OCD), Schizophrenia (SCZ).  

Can these genetic changes be inherited?

When we talk about genetics, one key question that arises is whether gene expression changes can be passed down between generations, a feature known as heritability. Genetic traits with high heritability are more likely to be passed down than low ones. One surprising finding was that conditions with stronger genetic heritability, such as schizophrenia and autism, were not necessarily those that were easier to predict in terms of structural changes in the brain Depression, which is only moderately heritable, showed the clearest gene–brain correspondence, while some highly heritable conditions did not. This suggests that genetic risk does not translate into brain changes in a simple or uniform way.

Overall, this work offers a new perspective on how genes shape the brain in mental illness and neurodivergence. Rather than acting everywhere at once, genetic risk appears to concentrate in specific regions - but only for certain conditions, and likely at specific stages of life.

Mapping where genetic risk meets brain structure may help us better understand why mental health conditions and illnesses differ so profoundly in their biology, symptoms, and responses to treatment. The data indicates the relationship is not straightforward and other factors such as developmental timing and environmental risk may contribute to how changes in the brain are shaped. Not surprisingly the answer to our original question is not a simple ‘yes’ or ‘no’. However, this new study has demonstrated the potential of this approach to better understand which genes might contribute to disease risk and what biological pathways might contribute to the brain pathology.

Transcriptome-informed brain cartography of polygenic risk and association with brain structure in major psychiatric disorders by Giacomel, A. et al. was published in Molecular Psychiatry (2026). https://doi.org/10.1038/s41380-026-03497-4

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