Gene networks show associations with seed region connectivity.
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.
Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.|Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.|Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.
Marie
M
Forest
Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.|Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.|Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
Yasser
Y
Iturria-Medina
Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.|Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.|Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
Jennifer S
JS
Goldman
Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.|Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.|Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
Claudia L
CL
Kleinman
Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.
Amanda
A
Lovato
Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.|Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.
Kathleen
K
Oros Klein
Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.|Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.|Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
Alan
A
Evans
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.|Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
Antonio
A
Ciampi
Département De Sciences De La Décision, HEC, Montreal, Quebec, Canada.
Aurélie
A
Labbe
Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, Canada.|Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.|Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Quebec, Canada.|Department of Human Genetics, McGill University, Montreal, Quebec, Canada.|Department of Oncology, McGill University, Montreal, Quebec, Canada.
Celia M T
0000-0002-2427-5696
CMT
Greenwood
D000328:Adult; D001921:Brain / Q000166:cytology / Q000378:metabolism*; D016000:Cluster Analysis; D063132:Connectome; D066264:Datasets as Topic; D038524:Diffusion Magnetic Resonance Imaging; D015870:Gene Expression / Q000502:physiology*; D053263:Gene Regulatory Networks / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D009434:Neural Pathways / Q000378:metabolism*; D055815:Young Adult
DW-MRI; gene-set enrichment analysis; network-based clustering; neuronal plasticity; structural connectivity