Genetic influences on resting-state functional networks: A twin study

Yixiao Fu, Zhiwei Ma, Christina Hamilton, Zhifeng Liang, Xiao Hou, Xingshun Ma, Xiaomei Hu, Qian He, Wei Deng, Yingcheng Wang, Liansheng Zhao, Huaqing Meng, Tao Li, Nanyin Zhang

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

Alterations in resting-state networks (RSNs) are often associated with psychiatric and neurologic disorders. Given this critical linkage, it has been hypothesized that RSNs can potentially be used as endophenotypes for brain diseases. To validate this notion, a critical step is to show that RSNs exhibit heritability. However, the investigation of the genetic basis of RSNs has only been attempted in the default-mode network at the region-of-interest level, while the genetic control on other RSNs has not been determined yet. Here, we examined the genetic and environmental influences on eight well-characterized RSNs using a twin design. Resting-state functional magnetic resonance imaging data in 56 pairs of twins were collected. The genetic and environmental effects on each RSN were estimated by fitting the functional connectivity covariance of each voxel in the RSN to the classic ACE twin model. The data showed that although environmental effects accounted for the majority of variance in wide-spread areas, there were specific brain sites that showed significant genetic control for individual RSNs. These results suggest that part of the human brain functional connectome is shaped by genomic constraints. Importantly, this information can be useful for bridging genetic analysis and network-level assessment of brain disorders.

Original languageEnglish (US)
Pages (from-to)3959-3972
Number of pages14
JournalHuman Brain Mapping
Volume36
Issue number10
DOIs
StatePublished - Oct 1 2015

All Science Journal Classification (ASJC) codes

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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