Admixture mapping identifies novel loci for obstructive sleep apnea in Hispanic/Latino Americans

Human Molecular Genetics, 2019, Vol. 28, No. 4 675–687 doi: 10.1093/hmg/ddy387 Advance Access Publication Date: 7 November 2018 Association Studies Article A S S O C I AT I O N S T U D I E S A R T I C L E Admixture mapping identifies novel loci for Heming Wang1,2,3,4 , Brian E. Cade2,3,4 , Tamar Sofer2,3,5 , Scott A. Sands2,3 , Han Chen6,7 , Sharon R. Browning5 , Adrienne M. Stilp5 , Tin L. Louie5 , Timothy A. Thornton5 , W. Craig Johnson5 , Jennifer E. Below8 , Matthew P. Conomos5 , Daniel S. Evans9 , Sina A. Gharib10 , Xiuqing Guo11 , Alexis C. Wood12 , Hao Mei13 , Kristine Yaffe14,15 , Jose S. Loredo16 , Alberto R. Ramos17 , Elizabeth Barrett-Connor18 , Sonia Ancoli-Israel19,20 , Phyllis C. Zee21 , Raanan Arens22 , Neomi A. Shah23 , Kent D. Taylor11 , Gregory J. Tranah9 , Katie L. Stone9 , Craig L. Hanis6 , James G Wilson24 , Daniel J. Gottlieb2,3,25 , Sanjay R. Patel26 , Ken Rice5 , Wendy S. Post27 , Jerome I. Rotter11 , Shamil R. Sunyaev4,28,29 , Jianwen Cai30 , Xihong Lin31 , Shaun M. Purcell2,4,32 , Cathy C. Laurie5 , Richa Saxena2,3,4,33 , Susan Redline2,3,34,* and Xiaofeng Zhu1,* 1 Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA, 2 Division USA, 3 Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA 02115, of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA, 4 Broad Institute, Cambridge, MA 02142, USA, 5 Department of Biostatistics, University of Washington, Seattle, WA 98195, USA, 6 Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, 7 Center for Precision Health, School of Public Health & School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA, 8 Vanderbilt Genetics Institute, Department of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN 37232, USA, 9 California Pacific Medical Center Research Institute, San Francisco, CA 94158, USA, 10 Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, WA 98195, USA, 11 Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA 90502, USA, 12 USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030, USA, 13 Department of Data Science, University of Mississippi Medical Center, Jackson, MS 39216, USA, 14 Departments of Psychiatry and Neurology, University of California, San Francisco, San Francisco, CA, USA, Received: June 29, 2018. Revised: October 30, 2018. Accepted: November 5, 2018 © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: 675 obstructive sleep apnea in Hispanic/Latino Americans 676 Human Molecular Genetics, 2019, Vol. 28, No. 4 15 Department *To whom correspondence should be addressed at: Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Harvard Medical School, 221 Longwood Avenue, Boston, MA 02115, USA. Tel: +1 6179837420; Fax: +1 6177324015; Email: and Xiaofeng Zhu, Department of Population and Quantitative Health Sciences, Case Western Reserve University, 2103 Cornell Road, Cleveland, OH 44106, USA. Tel: +1 2163680201; Fax: +1 2163684880; Email: Abstract Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Its prevalence and severity vary across ancestral background. Although OSA traits are heritable, few genetic associations have been identified. To identify genetic regions associated with OSA and improve statistical power, we applied admixture mapping on three primary OSA traits [the apnea hypopnea index (AHI), overnight average oxyhemoglobin saturation (SaO2 ) and percentage time SaO2 < 90%] and a secondary trait (respiratory event duration) in a Hispanic/Latino American population study of 11 575 individuals with significant variation in ancestral background. Linear mixed models were performed using previously inferred African, European and Amerindian local genetic ancestry markers. Global African ancestry was associated with a lower AHI, higher SaO2 and shorter event duration. Admixture mapping analysis of the primary OSA traits identified local African ancestry at the chromosomal region 2q37 as genome-wide significantly associated with AHI (P < 5.7 × 10−5 ), and European and Amerindian ancestries at 18q21 suggestively associated with both AHI and percentage time SaO2 < 90% (P < 10−3 ). Follow-up joint ancestry-SNP association analyses identified novel variants in ferrochelatase (FECH), significantly associated with AHI and percentage time SaO2 < 90% after adjusting for multiple tests (P < 8 × 10−6 ). These signals contributed to the admixture mapping associations and were replicated in independent cohorts. In this first admixture mapping study of OSA, novel associations with variants in the iron/heme metabolism pathway suggest a role for iron in inf luencing respiratory traits underlying OSA. Introduction Obstructive sleep apnea (OSA) is characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation (1). OSA affects more than 10% of adults (2) and increases risk of adverse health outcomes, including hypertension and cardiovascular disease as well as increased mortality (3–5). Candidate gene studies have identified associations between the apnea hypopnea index (AHI), the chief disease defining metric, measured continuously or dichotomized, with variants in genes associated with inflammation, serotoninergic pathways and ventilatory control (6–8). We have recently identified the first genome-wide significant associations with objectively measured OSA traits (9,10). However, the findings are limited by the statistical power with the modest sample size of the available datasets. One approach for increasing power while being robust to allelic heterogeneity is admixture mapping (11,12), a powerful analytic tool that can be applied to recently admixed populations whose ancestral populations were from isolated continents. This method assumes that the ancestral populations have different disease prevalence/severity and different allele frequencies of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA, 16 Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, UC San Diego School of Medicine, La Jolla, CA 92093, USA, 17 Department of Neurology, University of Miami Miller School of Medicine, Miami, FL 33136, USA, 18 Department of Family and Preventive Medicine, University of California, San Diego, CA 920 (...truncated)