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Proceedings Paper

Genomic connectivity networks based on the BrainSpan atlas of the developing human brain
Author(s): Ahmed Mahfouz; Mark N. Ziats; Owen M. Rennert; Boudewijn P. F. Lelieveldt; Marcel J. T. Reinders
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Paper Abstract

The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

Paper Details

Date Published: 21 March 2014
PDF: 7 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90344G (21 March 2014); doi: 10.1117/12.2044384
Show Author Affiliations
Ahmed Mahfouz, Delft Univ. of Technology (Netherlands)
Leids Univ. Medical Ctr. (Netherlands)
Mark N. Ziats, National Institutes of Health (United States)
Univ. of Cambridge (United Kingdom)
Baylor College of Medicine (United States)
Owen M. Rennert, National Institutes of Health (United States)
Boudewijn P. F. Lelieveldt, Leiden Univ. Medical Ctr. (Netherlands)
Delft Univ. of Technology (Netherlands)
Marcel J. T. Reinders, Delft Univ. of Technology (Netherlands)


Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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