Evidence map›Paper›PMID 24082094›Full record

Trial reportProceedings of the National Academy of Sciences of the United States of America2013

Genetic topography of brain morphology.

Chi-Hua Chen, Mark Fiecas, E D Gutiérrez, Matthew S Panizzon, Lisa T Eyler, Eero Vuoksimaa, Wesley K Thompson, Christine Fennema-Notestine, Donald J Hagler, Terry L Jernigan and 7 more

Abstract readClinical TrialMulticenter StudyTwin Study
In one paragraph

Trial report in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
135citing papers in PubMed, 3 pooled it
–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

135 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
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  10. Review
  11. Cerebral cortical structures linked to intelligence.bioRxiv : the preprint server for biology · 2025
    Article
  12. Article
  13. Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping the Human Cortical Layout.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  14. Article
  15. Article
  16. Revealing Fine-grained Genetically Informed Cortical Parcellation Maps of Neonates Based on Multi-view Spectral Clustering.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024
    Article
  17. Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  18. Article
  19. Article
  20. Article

75 more citing papers are in PubMed but not listed here.

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

17 authors.

Chi-Hua ChenDepartments of Psychiatry, Cognitive Science, Radiology, and Neurosciences, Center for Behavioral Genomics, and Institute of Genomic Medicine, University of California, San Diego, La Jolla, CA 92093.
Mark Fiecas
E D Gutiérrez
Matthew S Panizzon
Lisa T Eyler
Eero Vuoksimaa
Wesley K Thompson
Christine Fennema-Notestine
Donald J Hagler
Terry L Jernigan
Michael C Neale
Carol E Franz
Michael J Lyons
Bruce Fischl
Ming T Tsuang
Anders M Dale
William S Kremen

Funding

The VETSA Longitudinal MRI Twin Study of AgingR01AG022381 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2003 to 2019
$22.3M
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
The VETSA Longitudinal Twin Study of Cortisol and AgingR01AG022982 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KREMEN, WILLIAM S. · 2004 to 2007
$2.6M
Structural & Metabolic Neuroimaging Biomarkers in Early Alzheimer's DiseaseR01AG031224 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DALE, ANDERS M · 2008 to 2012
$1.9M
NIA NIH HHS AG018384NIA NIH HHS AG018386NIA NIH HHS AG022381NIA NIH HHS AG022982NIA NIH HHS AG031224NIA NIH HHS R01 AG018384NIA NIH HHS R01 AG018386NIA NIH HHS R01 AG022381NIA NIH HHS R01 AG022982NIA NIH HHS R01 AG031224NIDA NIH HHS DA029475NIDA NIH HHS RC2 DA029475NINDS NIH HHS NS056883NINDS NIH HHS U54 NS056883
6 · The paper itself

Abstract

Animal data show that cortical development is initially patterned by genetic gradients largely along three orthogonal axes. We previously reported differences in genetic influences on cortical surface area along an anterior-posterior axis using neuroimaging data of adult human twins. Here, we demonstrate differences in genetic influences on cortical thickness along a dorsal-ventral axis in the same cohort. The phenomenon of orthogonal gradations in cortical organization evident in different structural and functional properties may originate from genetic gradients. Another emerging theme of cortical patterning is that patterns of genetic influences recapitulate the spatial topography of the cortex within hemispheres. The genetic patterning of both cortical thickness and surface area corresponds to cortical functional specializations. Intriguingly, in contrast to broad similarities in genetic patterning, two sets of analyses distinguish cortical thickness and surface area genetically. First, genetic contributions to cortical thickness and surface area are largely distinct; there is very little genetic correlation (i.e., shared genetic influences) between them. Second, organizing principles among genetically defined regions differ between thickness and surface area. Examining the structure of the genetic similarity matrix among clusters revealed that, whereas surface area clusters showed great genetic proximity with clusters from the same lobe, thickness clusters appear to have close genetic relatedness with clusters that have similar maturational timing. The discrepancies are in line with evidence that the two traits follow different mechanisms in neurodevelopment. Our findings highlight the complexity of genetic influences on cortical morphology and provide a glimpse into emerging principles of genetic organization of the cortex.

Indexed as

BrainCerebral CortexCohort StudiesGenetics, MedicalHumansMagnetic Resonance ImagingMaleMiddle AgedRadiographyTwins, DizygoticTwins, MonozygoticgeneticsMRIregionalization

Identifiers

PMID24082094
PMCPMC3801007

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.