0018 Whole Genomic Associations of Transcription Factor Networks With Sleep Disordered Breathing Traits in Trans-Omics for Precision Medicine (TOPMed). (27th April 2018)

• Record Type: Journal Article
• Authors: Cade, B E; Lee, J; Sofer, T; Wang, H; Chen, H; Gharib, S A; Mei, H; Ochs-Balcom, H M; Patel, S R; Saxena, R; Shah, N A; Zhu, X; Gottlieb, D J; Lin, X; Redline, S
• Is Part Of: Sleep. Volume 41(2018)Supplement 1
• Page Start: A8
• Page End: A8
• Publication Date: 2018-04-27
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsy061.017
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: The genetic architecture of sleep disordered breathing (SDB) traits in humans remains largely unknown. Transcription factors such as HIF1A regulate gene expression, facilitate transcriptional programs, and respond to environmental signals. Identifying how variations in transcription factor binding sites (TFBS) across the genome associate with SDB phenotypes may help identify common mechanisms underlying the pathogenesis of SDB and its cardiometabolic consequences. As part of our ongoing genetic analysis of SDB traits at sequence-level resolution, we examined TFBS network mutations in individuals participating in the NHLBI TOPMed Consortium. Methods: We analyzed 3, 525 individuals from 5 NHLBI research cohort studies (892 African-, 206 Asian-, 2013 European-, and 414 Hispanic/Latino-Americans) with overnight objective recordings of average and minimum oxyhemoglobin saturation (SpO2 ) during sleep, percent sleep with SpO2 <90% (Per90), and the apnea-hypopnea index (AHI) and deep sequencing coverage. Mixed-effect models were used to adjust for age, sex, BMI, cohort, and self-identified ancestry with empirical genetic relatedness matrices to account for population structure and relatedness. For each of up to 581 transcription factors, TFBS variants with predicted functional consequences (fathmm-MKL score > 0.5) across the genome were tested together in set-based analyses using MM-SKAT. Results: The lead transcription factor associations were with CTCF (average SpO2 and Per90 SKAT p = 6.5 × 10 –15 and 2.3 × 10 –8 respectively), ERG (minimum SpO2 p = 7.8 × 10 –22 ), and TAL1 (AHI p = 5.9 × 10 –22 ). CTCF, FOXA1 and MYC were among the top 5 transcription factors in 3 analyses (average SpO2, minimum SpO2 and Per90), while PPARG, RELA, and TAL1 were among the top 5 transcription factors in 2 analyses. Conclusion: Important regulators of cell cycles (FOXA1, MYC), transcriptional insulation (CTCF), inflammation (RELA, PPARG), lipid metabolism (PPARG), and hematopoesis (ERG, TAL1) are associated with SDB traits through altered transcription factor binding sites throughout the genome. These results provide further insight into the genetic regulation of traits associated with SDB. Support (If Any): American Thoracic Society Foundation, K01 HL135405, R35 HL135818, R01 HL113338.