Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
22108644
TITLE
Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship.
ABSTRACT
Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.
Copyright © 2011 Elsevier Inc. All rights reserved.
DATE PUBLISHED
2012 Feb 15
HISTORY
PUBSTATUS PUBSTATUSDATE
received 2011/06/07
revised 2011/10/20
accepted 2011/10/26
aheadofprint 2011/11/12
entrez 2011/11/24 06:00
pubmed 2011/11/24 06:00
medline 2012/07/04 06:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Duarte-Carvajalino JM Duarte-Carvajalino Julio M JM Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA. duart022@umn.edu
Jahanshad N Jahanshad Neda N
Lenglet C Lenglet Christophe C
McMahon KL McMahon Katie L KL
de Zubicaray GI de Zubicaray Greig I GI
Martin NG Martin Nicholas G NG
Wright MJ Wright Margaret J MJ
Thompson PM Thompson Paul M PM
Sapiro G Sapiro Guillermo G
INVESTIGATORS
JOURNAL
VOLUME: 59
ISSUE: 4
TITLE: NeuroImage
ISOABBREVIATION: Neuroimage
YEAR: 2012
MONTH: Feb
DAY: 15
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Internet
ISSN: 1095-9572
ISSNTYPE: Electronic
MEDLINE JOURNAL
MEDLINETA: Neuroimage
COUNTRY: United States
ISSNLINKING: 1053-8119
NLMUNIQUEID: 9215515
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Comparative Study
Journal Article
COMMENTS AND CORRECTIONS
REFTYPE REFSOURCE REFPMID NOTE
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GRANTS
GRANTID AGENCY COUNTRY
P30 NS057091 NINDS NIH HHS United States
P41 RR008079 NCRR NIH HHS United States
P50 AG016570 NIA NIH HHS United States
R01 AG040060 NIA NIH HHS United States
R01 EB008432 NIBIB NIH HHS United States
R21 EB001561 NIBIB NIH HHS United States
R21 RR019771 NCRR NIH HHS United States
T15 LM007356 NLM NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Adult
Brain Mapping methods
Diffusion Magnetic Resonance Imaging methods
Female methods
Heredity genetics
Humans genetics
Image Processing, Computer-Assisted genetics
Male genetics
Nerve Net anatomy & histology
Neural Pathways anatomy & histology
Sex Characteristics anatomy & histology
Twins genetics
Young Adult genetics
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's
OTHERID SOURCE
NIHMS392948 NLM
PMC3551467 NLM
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