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    Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

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    Author
    Cade, Brian E
    Lee, Jiwon
    Sofer, Tamar
    Wang, Heming
    Zhang, Man
    Chen, Han
    Gharib, Sina A
    Gottlieb, Daniel J
    Guo, Xiuqing
    Lane, Jacqueline M
    Liang, Jingjing
    Lin, Xihong
    Mei, Hao
    Patel, Sanjay R
    Purcell, Shaun M
    Saxena, Richa
    Shah, Neomi A
    Evans, Daniel S
    Hanis, Craig L
    Hillman, David R
    Mukherjee, Sutapa
    Palmer, Lyle J
    Stone, Katie L
    Tranah, Gregory J
    Abecasis, Gonçalo R
    Boerwinkle, Eric A
    Correa, Adolfo
    Cupples, L Adrienne
    Kaplan, Robert C
    Nickerson, Deborah A
    North, Kari E
    Psaty, Bruce M
    Rotter, Jerome I
    Rich, Stephen S
    Tracy, Russell P
    Vasan, Ramachandran S
    Wilson, James G
    Zhu, Xiaofeng
    Redline, Susan
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    Date
    2021-08-26
    Journal
    Genome Medicine
    Publisher
    Springer Nature
    Type
    Article
    
    Metadata
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    See at
    https://doi.org/10.1186/s13073-021-00917-8
    Abstract
    Background: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. Methods: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap. Results: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10−8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways. Conclusions: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.
    Rights/Terms
    © 2021. The Author(s).
    Keyword
    GWAS
    Genome-wide association study
    Sleep apnea
    Sleep-disordered breathing
    WGS
    Whole-genome sequencing
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/16517
    ae974a485f413a2113503eed53cd6c53
    10.1186/s13073-021-00917-8
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