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Please use this identifier to cite or link to this item:
http://ir.nhri.org.tw/handle/3990099045/11479
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| Title: | Whole genome sequence association analysis of sleep-disordered breathing traits in trans-omics for precision medicine (topmed) |
| Authors: | Cade, B;Wang, H;Chen, H;Ekunwe, L;Gharib, S;Guo, X;Hale, L;Hsiung, A;McGarvey, S;Mei, H;Mitchell, B;Min, N;Ochs-Balcom, H;Patel, S;Purcell, S;Rotter, J;Saxena, R;Shah, N;Sofer, T;Sul, JH;Sunyaev, S;Wilson, J;Zhu, X;Gottlieb, D;Lin, X;Redline, S |
| Contributors: | Institute of Population Health Sciences |
| Abstract: | Introduction: Sleep-disordered breathing (SDB) is associated with increased risk of cardiovascular disease and mortality. There is a limited understanding of the bases for differences in patterns of overnight hypoxemia across individuals. The genetic architecture of SDB in humans is largely unknown, despite significant heritability. Further understanding may help elucidate mechanisms influencing obstructive sleep apnea and oxygenation as well as identify individuals at increased morbidity risk. Materials and methods: We performed a Whole-Genome Sequence Analysis (WGSA) in the TOPMed Consortium using the Apnea Hypopnea Index (AHI) and complementary measures of overnight oxyhemoglobin saturation (SpO2): average and minimum SpO2 and the percentage of the sleep episode with SpO2 < 90% (Per90). WGSA single-variant and gene-based analyses included pooled samples with deep (>30×) sequence coverage of 71.7 million variants from the Cleveland Family Study (507 African-Americans, 486 European-Americans) and the Framingham Heart Study (459 European-Americans). We used mixed effect models adjusting for age, sex, BMI, cohort, and self-identified ancestry with empirical kinship to account for relatedness and population structure. Gene-based test variants were comprised of adverse coding mutations (e.g. stop loss) with strong predicted functional consequences (fathmm-MKL score >0.9). Results: Heritability based on genetic variants at all frequencies was estimated at 0.29 (AHI), 0.44 (average SpO2), 0.20 (minimum SpO2), and 0.24 (Per90). AHI was associated near DIP2C and CLRN1-AS1 (rs75429350 p = 4.13 × 10-8; 3:150545337_T/G p = 4.87 × 10-8). Average SpO2 was associated near SNX3 (6:108585281_A/G p = 1.12 × 10-9) and C2orf73 (rs73931770 p = 4.03 × 10-8). Minimum SpO2 associations included regions near ADAM3A (rs150052514 p = 8.27 × 10-10) and rs148168881 (chr13q33 intergenic, p = 6.62 × 10-9). Per90 was associated with the AK5 region (rs201266006 p = 1.12 × 10-8). Secondary population- and sex-specific single variant analyses included an association between AHI and 12:8091955_T/C in females (SLC2A3 region, p = 7.74 × 10-11). PCSK9 and CHAF1Bwere significantly associated with minimum SpO2 in pooled gene-based analyses (Proprotein convertase subtilisin/kexin type 9, p = 1.19 × 10-6; Chromatin assembly factor I, subunit B, p = 2.92 × 10-6). ESRRG was associated with the AHI (Estrogen related receptor gamma, p = 1.21 x 10-6). Secondary gene analyses included an AHI association with KLHL1(kelch like family member 1; European males p = 1.7 × 10-10). Conclusions: These are the first WGSA analyses performed on sleep traits. Preliminary results suggest that novel loci are associated with SDB traits. Work is ongoing to characterize non-coding functional regions and extend these analyses using four additional studies with objective sleep recordings in TOPMed Phases 2 and 3 (n > 10,000). |
| Date: | 2017-12 |
| Relation: | Sleep Medicine. 2017 Dec;40(Suppl. 1):E44-E45. |
| Link to: | http://dx.doi.org/10.1016/j.sleep.2017.11.124 |
| JIF/Ranking 2023: | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1389-9457&DestApp=IC2JCR |
| Cited Times(WOS): | https://www.webofscience.com/wos/woscc/full-record/WOS:000444558902124 |
| Appears in Collections: | [熊昭] 會議論文/會議摘要
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| ISI000444558902124.pdf | 56Kb | Adobe PDF | 265 | View/Open |
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