Genetic network properties of the human cortex based on regional thickness and surface area measures.
We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques-biometrical genetic modeling, cluster analysis, and graph theory-to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Anna R
AR
Docherty
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Chelsea K
CK
Sawyers
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Matthew S
MS
Panizzon
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Michael C
MC
Neale
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System San Diego, CA, USA.
Lisa T
LT
Eyler
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Department of Radiology, University of California, San Diego San Diego, CA, USA.
Christine
C
Fennema-Notestine
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Carol E
CE
Franz
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Chi-Hua
CH
Chen
Department of Radiology, University of California, San Diego San Diego, CA, USA.
Linda K
LK
McEvoy
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Brad
B
Verhulst
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA ; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System San Diego, CA, USA ; Department of Neurosciences, University of California, San Diego San Diego, CA, USA.
Ming T
MT
Tsuang
Department of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA ; Department of Neurosciences, University of California, San Diego San Diego, CA, USA.
William S
WS
Kremen
cortical thickness; genetic; imaging; network; small world; structural; surface area; twin