In one paragraphArticle in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
13 authors.
Ravi R BhattImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0003-2498-8888 Shruti P GadewarImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0003-4790-0092 Ankush ShettyImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0002-7450-8144 Iyad Ba GariImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0003-1443-8786 Elizabeth HaddadImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0002-7622-9085 Shayan JavidImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
Abhinaav RameshImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
Elnaz NourollahimoghadamImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0002-2768-0179 Alyssa H ZhuImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0003-0083-5107 Christiaan de LeeuwDepartment of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands.
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0002-4720-8867 Sarah E MedlandPsychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane 4006, Australia.ORCID 0000-0003-1382-380X Neda JahanshadImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.ORCID 0000-0003-4401-8950 Funding
High resolution mapping of the genetic risk for disease in the aging brainR01AG059874 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JAHANSHAD, NEDA · 2018 to 2022
$3.1MGlobal studies into the Genetic Architecture of the Brain's White Matter Network through Harmonized and Coordinated Analyses in the ENIGMA-ConsortiumR01MH134004 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Neda Jahanshad · 2023 to 2026
$2.6MWorldwide Tractometry Initiative to Investigate Brain Microstructure, Cognitive Impairment & Dementia in Parkinsons DiseaseRF1NS136995 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JAHANSHAD, NEDA, THOMPSON, PAUL M · 2024 to 2024
$2.2MLateral prefrontal organization in emotion: representational and causal mechanismsR01MH134000 · NIMH · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI Regina C Lapate · 2023 to 2026
$2.0MNIA NIH HHS R01 AG059874NIMH NIH HHS R01 MH134000NIMH NIH HHS R01 MH134004NINDS NIH HHS RF1 NS136995
6 · The paper itselfAbstract
The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined
Identifiers
PMID39091796
PMCPMC11291056
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