Evidence map›Paper›PMID 30430703›Full record

ArticleHuman brain mapping2019

Genetic architecture of hippocampal subfields on standard resolution MRI: How the parts relate to the whole.

Jeremy A Elman, Matthew S Panizzon, Nathan A Gillespie, Donald J Hagler, Christine Fennema-Notestine, Lisa T Eyler, Linda K McEvoy, Michael C Neale, Michael J Lyons, Carol E Franz and 2 more

Abstract read
In one paragraph

Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
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  8. Article
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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.

Jeremy A ElmanDepartment of Psychiatry, University of California San Diego, San Diego, California.ORCID 0000-0002-5840-1769
Matthew S PanizzonDepartment of Psychiatry, University of California San Diego, San Diego, California.
Nathan A GillespieVirginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia.ORCID 0000-0001-8655-2823
Donald J HaglerDepartment of Radiology, University of California San Diego, San Diego, California.
Christine Fennema-NotestineDepartment of Psychiatry, University of California San Diego, San Diego, California.
Lisa T EylerDepartment of Psychiatry, University of California San Diego, San Diego, California.
Linda K McEvoyDepartment of Radiology, University of California San Diego, San Diego, California.
Michael C NealeVirginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia.
Michael J LyonsDepartment of Psychological and Brain Sciences, Boston University, Boston, Massachusetts.
Carol E FranzDepartment of Psychiatry, University of California San Diego, San Diego, California.
Anders M DaleDepartment of Radiology, University of California San Diego, San Diego, California.
William S KremenDepartment of Psychiatry, University of California San Diego, San Diego, California.

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
The VETSA Longitudinal Twin Study of Cognition and Aging (VETSA 4)R01AG050595 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELMAN, JEREMY A, FRANZ, CAROL ELAINE · 2015 to 2024
$28.0M
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
The VETSA Longitudinal MRI Twin Study of Aging (VETSA MRI 4)R01AG076838 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE, Jeremy A Elman · 2022 to 2026
$8.7M
Testosterone-Androgen Receptor Genetics: Role in Cognitive and Biological AgingK08AG047903 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PANIZZON, MATTHEW S · 2014 to 2017
$452k
Department of DefenseMcDonnell Center for Systems NeuroscienceNational Academy of SciencesNational Archives and Records AdministrationNational Research CouncilNIA NIH HHS AG018384AG018386AG022381AG047903AG050595NIA NIH HHS K08 AG047903NIA NIH HHS R01 AG018384NIA NIH HHS R01 AG018386NIA NIH HHS R01 AG022381NIA NIH HHS R01 AG050595NIA NIH HHS R01 AG076838NIH Blueprint for Neuroscience Research 1U54MH091657NIH HHSNIMH NIH HHS U54 MH091657Temple UniversityU.S. Department of Veterans Affairs
6 · The paper itself

Abstract

The human hippocampus can be subdivided into subfields with unique functional properties and differential vulnerability to disease or neuropsychiatric conditions. Identifying genes that confer susceptibility to such processes is an important goal in developing treatments. Recent advances in automatic subfield segmentation from magnetic resonance images make it possible to use these measures as phenotypes in large-scale genome-wide association studies. Such analyses are likely to rely largely on standard resolution (~1 mm isotropic) T

Indexed as

AgedAgingAutomationConnectomeFactor Analysis, StatisticalFemaleGenetic VariationGenome-Wide Association StudyHippocampusHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedPhenotypeTwinsautomated segmentationgenetic correlationgenetic varianceheritabilityhippocampal subregionstwins

Identifiers

PMID30430703
PMCPMC6397064

What OpenQuestion holds

Textmetadata
LicenceTDM
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.