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*

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    27 Downloads (CityUHK Scholars)

    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. © 2024 The Authors.
    Original languageEnglish
    Article number120739
    JournalNeuroImage
    Volume297
    Online published14 Jul 2024
    DOIs
    Publication statusPublished - 15 Aug 2024

    Research Keywords

    • Cortical structure
    • Gaussian graphical model
    • Genetic correlation
    • Imaging genetics
    • Spectral clustering

    Publisher's Copyright Statement

    • This full text is made available under CC-BY-NC 4.0. https://creativecommons.org/licenses/by-nc/4.0/

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