Evidence map›Paper›PMID 26347632›Full record

ArticleFrontiers in human neuroscience2015

Genetic network properties of the human cortex based on regional thickness and surface area measures.

Anna R Docherty, Chelsea K Sawyers, Matthew S Panizzon, Michael C Neale, Lisa T Eyler, Christine Fennema-Notestine, Carol E Franz, Chi-Hua Chen, Linda K McEvoy, Brad Verhulst and 2 more

Abstract read
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Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Anna R DochertyVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Chelsea K SawyersVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Matthew S PanizzonDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Michael C NealeVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Lisa T EylerDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System San Diego, CA, USA.
Christine Fennema-NotestineDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Department of Radiology, University of California, San Diego San Diego, CA, USA.
Carol E FranzDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Chi-Hua ChenDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA.
Linda K McEvoyDepartment of Radiology, University of California, San Diego San Diego, CA, USA.
Brad VerhulstVirginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University Richmond, VA, USA.
Ming T TsuangDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA ; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System San Diego, CA, USA ; Department of Neurosciences, University of California, San Diego San Diego, CA, USA.
William S KremenDepartment of Psychiatry, University of California, San Diego San Diego, CA, USA ; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego San Diego, CA, USA ; Department of Neurosciences, University of California, San Diego San Diego, CA, USA.

Funding

MORPHOMETRY BIOMEDICAL INFORMATICS RESEARCH NETWORKU24RR021382 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2004 to 2008
$24.1M
The VETSA Longitudinal MRI Twin Study of AgingR01AG022381 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2003 to 2019
$22.3M
ULTRAHIGH FIELD TECHNOLOGY FOR FUNCTIONAL IMAGINGP41RR014075 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 1999 to 2011
$16.4M
The VETSA Longitudinal Twin Study of Cognition and AgingR01AG018384 · NIA · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI LYONS, MICHAEL J. · 2002 to 2012
$9.8M
The VETSA longitudinal twin study of cognition and agingR01AG018386 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2002 to 2012
$9.7M
Creating a Pediatric Imaging-Genomics Data ResourceRC2DA029475 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHANG, LINDA, DALE, ANDERS M · 2009 to 2011
$9.1M
Imaging Studies in Neurotoxicity and NeurodevelopmentU54NS056883 · NINDS · UNIVERSITY OF HAWAII AT MANOA · PI CHANG, LINDA · 2007 to 2011
$8.4M
Research Training: Psychiatric &Statistical GeneticsT32MH020030 · NIMH · VIRGINIA COMMONWEALTH UNIVERSITY · PI HERMINE H MAES, MICHAEL CHURTON NEALE · 1999 to 2026
$6.7M
Language, Communication and the BrainT32DC000041 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KUTAS, MARTA · 1993 to 2012
$3.9M
Research Education in Statistical Genetics of Substance AbuseR25DA026119 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI NEALE, MICHAEL CHURTON · 2008 to 2018
$3.2M
The VETSA Longitudinal Twin Study of Cortisol and AgingR01AG022982 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2004 to 2007
$2.6M
Tools for Analyzing Cortical Structure and ConnectivityR01NS052585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2006 to 2010
$2.5M
NCCIH NIH HHS RC1 AT005728NCRR NIH HHS P41 RR014075NCRR NIH HHS U24 RR021382NIA NIH HHS R01 AG018384NIA NIH HHS R01 AG018386NIA NIH HHS R01 AG022381NIA NIH HHS R01 AG022982NIA NIH HHS R01 AG031224NIBIB NIH HHS R01 EB006758NIDA NIH HHS R25 DA026119NIDA NIH HHS RC2 DA029475NIDCD NIH HHS T32 DC000041NIMH NIH HHS T32 MH020030NINDS NIH HHS R01 NS052585NINDS NIH HHS R01 NS070963NINDS NIH HHS R21 NS072652NINDS NIH HHS U54 NS056883
6 · The paper itself

Abstract

We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques-biometrical genetic modeling, cluster analysis, and graph theory-to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.

Indexed as

cortical thicknessgeneticimagingnetworksmall worldstructuralsurface areatwin

Identifiers

PMID26347632
PMCPMC4542323

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.