Evidence map›Paper›PMID 39009250›Full record

ArticleNeuroImage2024

Joint modeling of human cortical structure: Genetic correlation network and composite-trait genetic correlation.

Jiangnan Shen, Yiliang Zhang, Zhaohan Zhu, Youshu Cheng, Biao Cai, Yize Zhao, Hongyu Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Jiangnan ShenDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Yiliang ZhangDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Zhaohan ZhuDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Youshu ChengDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Biao CaiDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Department of Management Sciences, City University of Hong Kong, Hong Kong S.A.R, China.
Yize ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Hongyu ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA; Program of Computational Biology and Biomedical Informatics, Yale University, New Haven, CT, USA. Electronic address: hongyu.zhao@yale.edu.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
An integrative Bayesian approach for linking brain to behavioral phenotypeR01EB034720 · NIBIB · YALE UNIVERSITY · PI R Todd Constable, Yize Zhao · 2023 to 2026
$2.4M
Integrative analysis for patient-centered outcomes and time-to-event data in Alzheimer's diseaseRF1AG081413 · NIA · YALE UNIVERSITY · PI SUN, YIFEI, ZHAO, YIZE · 2023 to 2023
$2.3M
Novel integrative imaging genetics analysis for Alzheimer's disease riskand progressionRF1AG068191 · NIA · YALE UNIVERSITY · PI ZHAO, YIZE · 2021 to 2021
$1.9M
Novel statistical methods and tools to integrate multiple endophenotypes and functional annotation data to study the roles of rare variants in complex human diseases using sequencing dataR01GM134005 · NIGMS · YALE UNIVERSITY · PI WU, BAOLIN, ZHAO, HONGYU · 2020 to 2023
$1.6M
Novel integrative imaging genetics analysis for Alzheimer's disease riskand progressionR01AG068191 · NIA · YALE UNIVERSITY · PI ZHAO, YIZE · 2024 to 2025
$1.2M
NCATS NIH HHS UL1 TR001863NIA NIH HHS R01 AG068191NIA NIH HHS RF1 AG068191NIA NIH HHS RF1 AG081413NIBIB NIH HHS R01 EB034720NIGMS NIH HHS R01 GM134005Wellcome Trust
6 · The paper itself

Abstract

Heritability and genetic covariance/correlation quantify the marginal and shared genetic effects across traits. They offer insights on the genetic architecture of complex traits and diseases. To explore how genetic variations contribute to brain function variations, we estimated heritability and genetic correlation across cortical thickness, surface area, and volume of 33 anatomically predefined regions in left and right hemispheres, using summary statistics of genome-wide association analyses of 31,968 participants in the UK Biobank. To characterize the relationships between these regions of interest, we constructed a genetic network for these regions using recursive two-way cut-offs in similarity matrices defined by genetic correlations. The inferred genetic network matches the brain lobe mapping more closely than the network inferred from phenotypic similarities. We further studied the associations between the genetic network for brain regions and 30 complex traits through a novel composite-linkage disequilibrium score regression method. We identified seven significant pairs, which offer insights on the genetic basis for regions of interest mediated by cortical measures.

Indexed as

Cerebral CortexGenome-Wide Association StudyAgedFemaleGene Regulatory NetworksHumansMagnetic Resonance ImagingMaleMiddle AgedModels, GeneticPolymorphism, Single NucleotideCortical structureGaussian graphical modelGenetic correlationImaging geneticsSpectral clustering

Identifiers

PMID39009250
PMCPMC11367654

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.