Hierarchical Genetic Organization of Human Cortical Surface Area

• Published in: Science (American Association for the Advancement of Science) Vol. 335; no. 6076; pp. 1634 - 1636
• Main Authors: Chen, Chi-Hua, Gutierrez, E. D., Thompson, Wes, Panizzon, Matthew S., Jernigan, Terry L., Eyler, Lisa T., Fennema-Notestine, Christine, Jak, Amy J., Neale, Michael C., Franz, Carol E., Lyons, Michael J., Grant, Michael D., Fischi, Bruce, Seidman, Larry J., Tsuang, Ming T., Kremen, William S., Dale, Anders M.
• Format: Journal Article
• Language: English
• Published: Washington, DC American Association for the Advancement of Science 30.03.2012; The American Association for the Advancement of Science
• Subjects: Animal genetics; Biological and medical sciences; Brain; Brain Mapping; cerebral cortex; Cerebral Cortex - anatomy & histology; Cerebral Cortex - metabolism; Cerebral hemispheres; Fundamental and applied biological sciences. Psychology; Gene Expression; Genes; Genetic correlation; Genetic Variation; Genetics; Human genetics; Human subjects; Humans; Image Processing, Computer-Assisted; Individualized Instruction; Inferior temporal cortex; Magnetic Resonance Imaging; Male; Medical genetics; Medical imaging; Middle Aged; Monkeys & apes; Motor cortex; Neurobiology; Phenotype; Prefrontal cortex; Scientific Concepts; Statistical analysis; Surface area; Surface areas; twins; Twins, Dizygotic - genetics; Twins, Monozygotic - genetics; Vertebrates: nervous system and sense organs; Human; Cerebral cortex; Central nervous system; Differentiation; Nuclear magnetic resonance imaging; Encephalon; Twin
• ISSN: 0036-8075; 1095-9203; 1095-9203
• DOI: 10.1126/science.1215330

Surface area of the cerebral cortex is a highly heritable trait, yet little is known about genetic influences on regional cortical differentiation in humans. Using a data-driven, fuzzy clustering technique with magnetic resonance imaging data from 406 twins, we parceled cortical surface area into genetic subdivisions, creating a human brain atlas based solely on genetically informative data. Boundaries of the genetic divisions corresponded largely to meaningful structural and functional regions; however, the divisions represented previously undescribed phenotypes different from conventional (non-genetically based) parcellation systems. The genetic organization of cortical area was hierarchical, modular, and predominantly bilaterally symmetric across hemispheres. We also found that the results were consistent with human-specific regions being subdivisions of previously described, genetically based lobar regionalization patterns.