Gene networks show associations with seed region connectivity.
Marie ForestYasser Iturria-MedinaJennifer S GoldmanClaudia L KleinmanAmanda LovatoKathleen Oros KleinAlan EvansAntonio CiampiAurélie LabbeCelia M T GreenwoodPublished in: Human brain mapping (2017)
Primary patterns in adult brain connectivity are established during development by coordinated networks of transiently expressed genes; however, neural networks remain malleable throughout life. The present study hypothesizes that structural connectivity from key seed regions may induce effects on their connected targets, which are reflected in gene expression at those targeted regions. To test this hypothesis, analyses were performed on data from two brains from the Allen Human Brain Atlas, for which both gene expression and DW-MRI were available. Structural connectivity was estimated from the DW-MRI data and an approach motivated by network topology, that is, weighted gene coexpression network analysis (WGCNA), was used to cluster genes with similar patterns of expression across the brain. Group exponential lasso models were then used to predict gene cluster expression summaries as a function of seed region structural connectivity patterns. In several gene clusters, brain regions located in the brain stem, diencephalon, and hippocampal formation were identified that have significant predictive power for these expression summaries. These connectivity-associated clusters are enriched in genes associated with synaptic signaling and brain plasticity. Furthermore, using seed region based connectivity provides a novel perspective in understanding relationships between gene expression and connectivity. Hum Brain Mapp 38:3126-3140, 2017. © 2017 Wiley Periodicals, Inc.
Keyphrases
- resting state
- functional connectivity
- white matter
- gene expression
- network analysis
- genome wide
- dna methylation
- poor prognosis
- genome wide identification
- multiple sclerosis
- copy number
- magnetic resonance imaging
- transcription factor
- binding protein
- electronic health record
- cerebral ischemia
- artificial intelligence
- subarachnoid hemorrhage
- big data
- single cell
- drug delivery