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Identifying age-specific gene signatures of the human cerebral cortex with joint analysis of transcriptomes and functional connectomes.
Zhao, Xingzhong; Chen, Jingqi; Xiao, Peipei; Feng, Jianfeng; Nie, Qing; Zhao, Xing-Ming.
Afiliação
  • Zhao X; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China.
  • Chen J; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China.
  • Xiao P; Department of Electronic and Information Engineering, Tongji University, China.
  • Feng J; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, China.
  • Nie Q; Department of Biomedical Engineering, University of California, Irvine, USA.
  • Zhao XM; ISTBI, RIICS, Fudan University, and MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and Frontiers Center for Brain Science, China.
Brief Bioinform ; 22(4)2021 07 20.
Article em En | MEDLINE | ID: mdl-33367491
ABSTRACT
The human cerebral cortex undergoes profound structural and functional dynamic variations across the lifespan, whereas the underlying molecular mechanisms remain unclear. Here, with a novel method transcriptome-connectome correlation analysis (TCA), which integrates the brain functional magnetic resonance images and region-specific transcriptomes, we identify age-specific cortex (ASC) gene signatures for adolescence, early adulthood and late adulthood. The ASC gene signatures are significantly correlated with the cortical thickness (P-value <2.00e-3) and myelination (P-value <1.00e-3), two key brain structural features that vary in accordance with brain development. In addition to the molecular underpinning of age-related brain functions, the ASC gene signatures allow delineation of the molecular mechanisms of neuropsychiatric disorders, such as the regulation between ARNT2 and its target gene ETF1 involved in Schizophrenia. We further validate the ASC gene signatures with published gene sets associated with the adult cortex, and confirm the robustness of TCA on other brain image datasets.

Availability:

All scripts are written in R. Scripts for the TCA method and related statistics result can be freely accessed at https//github.com/Soulnature/TCA. Additional data related to this paper may be requested from the authors.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Envelhecimento / Córtex Cerebral / Fatores de Terminação de Peptídeos / Translocador Nuclear Receptor Aril Hidrocarboneto / Fatores de Transcrição Hélice-Alça-Hélice Básicos / Transcriptoma Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Child / Female / Humans / Male / Middle aged Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Envelhecimento / Córtex Cerebral / Fatores de Terminação de Peptídeos / Translocador Nuclear Receptor Aril Hidrocarboneto / Fatores de Transcrição Hélice-Alça-Hélice Básicos / Transcriptoma Tipo de estudo: Prognostic_studies Limite: Adolescent / Adult / Aged / Aged80 / Child / Female / Humans / Male / Middle aged Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China