Summary: By combining genetic profiling, intelligence testing, and neuroimaging, researchers identified a small set of brain regions—mainly within the frontal, parietal, and visual cortices—where genetic variation shapes brain properties that in turn relate to cognitive performance.
Source: RUB (Ruhr University Bochum)
Intelligence is partly heritable. Large genetic studies have shown that many genetic variants are associated with differences in cognitive performance, while neuroscience research has linked multiple brain features—such as cortical surface area and network efficiency—to intelligence.
For the first time, researchers examined all three elements—genetic predisposition, multiple brain characteristics derived from MRI, and measured cognitive ability—within the same sample to determine how genes, brain structure and function, and behavior are connected.
Using polygenic scoring from saliva DNA, magnetic resonance imaging (MRI), and standardized intelligence tests, the team identified which brain features act as intermediaries between genetic variation and cognitive performance.
The findings come from a collaboration led by Dorothea Metzen at the Department of Biopsychology, Ruhr University Bochum, together with Erhan Genç (formerly at Ruhr University, currently at the Leibniz Research Centre for Working Environment and Human Factors—IfADo). The work is published in the journal Human Brain Mapping.
This multidisciplinary project involved researchers from IfADo, several Ruhr University Bochum departments (including biopsychology, human genetics and genetic psychology), Humboldt-Universität zu Berlin, the Central Institute of Mental Health in Mannheim, the Medical School Hamburg and the University of Luxembourg.
Genes, brain, behavior — a uniquely integrated dataset
The study included 557 adults between 18 and 75 years of age. Researchers calculated polygenic scores for each participant based on saliva-derived genetic data; these scores summarize the combined influence of many genetic variants associated with higher educational attainment and intelligence.
All participants completed comprehensive MRI scans. The imaging analyses measured cortical surface area and thickness and quantified properties of structural and functional brain networks, including network efficiency derived from graph-theoretical approaches. Each person also completed standardized intelligence testing to assess cognitive performance.
“Thousands of genetic loci contribute to intelligence,” explains Dorothea Metzen. “Polygenic scores allow us to collapse that distributed genetic signal into a single index of genetic predisposition for higher cognitive ability.”
Erhan Genç emphasizes the novelty of the approach: “This study is, to our knowledge, unprecedented in jointly analyzing genetic predisposition, multiple brain phenotypes, and behavior within the same sample.” The research team specifically examined which genetic differences are linked to which brain measures, and which of those brain measures are linked to cognitive outcomes.
A concentrated neurogenetic pathway in specific brain regions
When the researchers examined links between polygenic scores and brain characteristics alone, many associations appeared across the cortex. However, far fewer brain features showed reliable relationships with measured intelligence scores.
Critically, when all three elements—polygenic scores, brain measures, and cognitive performance—were considered together, only a small number of cortical regions showed evidence that genetic variation affects brain properties that in turn relate to intelligence. These convergent regions were primarily located in frontal, parietal and visual cortical areas.
Among the brain characteristics examined, cortical surface area and the efficiency of structural (fiber) connectivity emerged as the most important mediators linking polygenic propensity to cognitive performance. In contrast, cortical thickness and measures of functional network efficiency showed far fewer conclusive triadic associations with genes and intelligence in this sample.
In other words, the study suggests that genetic influences on intelligence are funneled through specific regional brain architectures—mainly surface area and structural connectivity efficiency—rather than through uniform effects across all brain measures.
A method applicable beyond intelligence research
Beyond the specific findings, the investigators propose their analytic approach as a general method to study how polygenic predispositions relate to brain properties and behavior. This framework can be applied to other complex traits and psychiatric or cognitive phenotypes to identify regionally specific neurogenetic pathways.
The authors note that applying this method to much larger samples—thousands or tens of thousands of participants—would increase statistical power and refine the mapping between genes, brain, and behavior. Examining developmental or aging effects is another promising direction for future research.
About this intelligence and genetics research news
Author: Press Office
Source: RUB (Ruhr University Bochum)
Contact: Press Office – RUB
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Original Research: Open access. “Structural architecture and brain network efficiency link polygenic scores to intelligence” by Dorothea Metzen et al., Human Brain Mapping.
Abstract
Structural architecture and brain network efficiency link polygenic scores to intelligence
Intelligence is highly heritable. Genome-wide association studies have identified thousands of genetic variants that each contribute a small effect to individual differences in cognitive ability. Polygenic scores (PGS), which aggregate these effects into a single metric, are increasingly used to probe genetic contributions in independent samples.
Although PGS can explain a notable portion of variance in intelligence, the neurobiological pathways mediating this relationship remain incompletely understood. In this study, individuals with higher PGS for educational attainment and intelligence tended to achieve higher scores on cognitive tests, exhibit larger cortical surface area, and show greater structural fiber-network efficiency as assessed by graph-theoretical measures.
Fiber network efficiency and surface area of brain regions—partly overlapping with parieto-frontal circuits—were found to mediate the relationship between polygenic predisposition and cognitive performance. These results mark an important step toward decoding the neurogenetic architecture of intelligence by identifying specific regional networks that connect polygenic risk to cognitive outcomes.