Genetic Influences on Functional Brain Network Variability

Genetic contributions to the variance in functional brain networks have emerged as a critical factor in understanding individual differences in cognition, emotion and vulnerability to neurological disorders. Large-scale twin and population studies have applied methodologies such as resting-state functional magnetic resonance imaging to characterise variability across canonical brain networks. Heritability estimates for key resting-state connections often range from modest to moderate, revealing that both common and non-additive genetic factors shape the strength and configuration of functional connectivity. Genome-wide association studies have begun to identify specific loci and genes implicated in network global efficiency and network strength, while multivariate modelling highlights the interplay between genetic predisposition and unique environmental influences. This body of work sheds light on the biological underpinnings of network variability, offering potential targets for personalised intervention and advancing our grasp of how gene–environment interactions sculpt brain function over development and into later life.

Research from Nature Portfolio

Recent analyses of young twin cohorts have demonstrated that genetic and environmental contributions to large-scale resting-state networks differ across brain regions and spatial scales. Studies employing classical ACE twin models in juvenile samples revealed selective genetic influence on fronto-temporal connections and shared environmental effects in occipital circuits, while unique environmental factors predominantly govern multi-scale connectivity features. Parallel work in middle-aged populations has used graph theory measures from population biobank data to map genome-wide associations with metrics such as global efficiency and network strength. These investigations uncovered intergenic variants near developmental genes and pointed to links between network integrity and sleep phenotypes, suggesting that genetic variation in functional network topology may relate to behavioural and neurodegenerative outcomes.

Genetic Influences on Functional Brain Network Variability publication trend

The graph below shows the total number of articles in genetic influences on functional brain network variability across all publications each year (not limited to Nature Index journals).

Technical terms

Resting-state functional magnetic resonance imaging (rs-fMRI): A neuroimaging technique that measures spontaneous brain activity patterns in the absence of an explicit task.

Heritability: The proportion of observed variance in a trait attributable to genetic variation within a population.

Functional connectivity: Statistical dependencies between time-series of distinct brain regions, reflecting coordinated neural activity.

Genome-wide association study (GWAS): A method to scan the genome for common genetic variants associated with traits by testing single-nucleotide polymorphisms across many individuals.

ACE model: A statistical twin design decomposing phenotypic variance into additive genetic (A), common environmental (C) and unique environmental (E) components.

References

1. Environmental effects on brain functional networks in a juvenile twin population. Scientific Reports (2023).
2. Novel genetic variants associated with brain functional networks in 18,445 adults from the UK Biobank. Scientific Reports (2021).
3. Heritability of cognitive and emotion processing during functional MRI in a twin sample. Human Brain Mapping (2024).
4. Genome-wide association study of brain functional and structural networks. Network Neuroscience (2024).
5. Heritability of human “directed” functional connectome. Brain and Behavior (2023).