Evidence map›Paper›PMID 27006297›Full record

ArticleHuman brain mapping2016

Heritability and genetic correlation between the cerebral cortex and associated white matter connections.

Kai-Kai Shen, Vincent Doré, Stephen Rose, Jurgen Fripp, Katie L McMahon, Greig I de Zubicaray, Nicholas G Martin, Paul M Thompson, Margaret J Wright, Olivier Salvado

Abstract readTwin Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Human brain mapping, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
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  5. Article
  6. Brain Imaging Genomics: Integrated Analysis and Machine Learning.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2020
    Article
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  8. Article
  9. Review
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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

10 authors.

Kai-Kai ShenCSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia.
Vincent DoréCSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia.
Stephen RoseCSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia.
Jurgen FrippCSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia.
Katie L McMahonCentre for Advanced Imaging, University of Queensland, Brisbane, Australia.
Greig I de ZubicarayFaculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia.
Nicholas G MartinQueensland Institute of Medical Research, Brisbane, Australia.
Paul M ThompsonImaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, California.
Margaret J WrightCentre for Advanced Imaging, University of Queensland, Brisbane, Australia.
Olivier SalvadoCSIRO Health and Biosecurity, The Australian eHealth Research Centre, Herston, Queensland, Australia.

Funding

Training U54EB020403 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2018
$10.1M
Genetic influences on the brain: A twin imaging studyR01HD050735 · NICHD · QUEENSLAND INSTITUTE OF MEDICAL RESEARCH · PI WRIGHT, MARGARET JANE · 2007 to 2011
$2.6M
Alzheimer's disease risk analyzed using population imaging genomicsR01AG040060 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2011 to 2016
$2.5M
NIA NIH HHS R01 AG040060NIBIB NIH HHS U54 EB020403NICHD NIH HHS R01 HD050735
6 · The paper itself

Abstract

The aim of this study is to investigate the genetic influence on the cerebral cortex, based on the analyses of heritability and genetic correlation between grey matter (GM) thickness, derived from structural MR images (sMRI), and associated white matter (WM) connections obtained from diffusion MRI (dMRI). We measured on sMRI the cortical thickness (CT) from a large twin imaging cohort using a surface-based approach (N = 308, average age 22.8 ± 2.3 SD). An ACE model was employed to compute the heritability of CT. WM connections were estimated based on probabilistic tractography using fiber orientation distributions (FOD) from dMRI. We then fitted the ACE model to estimate the heritability of CT and FOD peak measures along WM fiber tracts. The WM fiber tracts where genetic influence was detected were mapped onto the cortical surface. Bivariate genetic modeling was performed to estimate the cross-trait genetic correlation between the CT and the FOD-based connectivity of the tracts associated with the cortical regions. We found some cortical regions displaying heritable and genetically correlated GM thickness and WM connectivity, forming networks under stronger genetic influence. Significant heritability and genetic correlations between the CT and WM connectivity were found in regions including the right postcentral gyrus, left posterior cingulate gyrus, right middle temporal gyri, suggesting common genetic factors influencing both GM and WM. Hum Brain Mapp 37:2331-2347, 2016. © 2016 Wiley Periodicals, Inc.

Indexed as

Quantitative Trait, HeritableAdultCerebral CortexCohort StudiesDiffusion Magnetic Resonance ImagingFemaleHumansImage Processing, Computer-AssistedMaleModels, GeneticNeural PathwaysOrgan SizePhenotypeReproducibility of ResultsTwins, DizygoticTwins, Monozygoticcerebral cortexdiffusion MRIgenetic correlationgrey matterheritabilitystructural MRIwhite matter

Identifiers

PMID27006297
PMCPMC4883001

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.