# Electrophysiological resting-state signatures link polygenic scores to general intelligence

## TL;DR

This study links genetic scores for intelligence to brain connectivity patterns measured by EEG, suggesting how genes might influence cognitive abilities.

## Contribution

The study is the first to connect polygenic scores for intelligence with EEG-derived brain connectivity metrics.

## Key findings

- Polygenic scores predicted variance in intelligence and were linked to frequency-specific brain connectivity metrics.
- These connectivity patterns, especially in parieto-frontal regions, were associated with intelligence levels.
- The findings suggest genetic variation may influence intelligence through specific brain network properties.

## Abstract

Intelligence is associated with important life outcomes. Behavioral, genetic, structural, and functional brain correlates of intelligence have been studied for decades, but questions remain as to how genetics are related to trait expression and what intermediary role brain properties play. This study investigated these mediations in a representative sample of 434 individuals, comprising young and older adults. Polygenic scores (PGS) for intelligence were calculated. Resting-state EEG recordings were analyzed using graph theory quantifying functional connectivity across different frequencies. We tested whether global and local graph metrics like efficiency and clustering mediated the association between PGS and intelligence. PGS significantly predicted variance in intelligence and were related to frequency-specific graph metrics in areas predominantly located in parieto-frontal regions, which in turn were associated with intelligence. These findings, based on the first study linking PGS to intelligence using EEG-derived graph metrics, identify candidate pathways through which genetic variation may shape intelligence, providing a foundation for future hypothesis-driven investigations. Data for this study were collected as part of the Dortmund Vital Study (https://www.researchprotocols.org/2022/3/e32352; ClinicalTrials.gov: NCT05155397).

The online version contains supplementary material available at 10.1038/s41598-025-26778-4.