Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data
In this study, we investigated low-frequency and rare variants associated with blood pressure (BP) by focusing on a linkage region on chromosome 16p13. We used whole genome sequencing (WGS) data obtained through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program on 395 Cleveland Family Study (CFS) European Americans (CFS-EA). By analyzing functional coding variants and non-coding rare variants with CADD score > 10 residing within the chromosomal region in families with linkage evidence, we observed 25 genes with nominal statistical evidence (burden or SKAT p < 0.05). One of the genes is RBFOX1, an evolutionarily conserved RNA-binding protein that regulates tissue-specific alternative splicing that we previously reported to be associated with BP using exome array data in CFS. After follow-up analysis of the 25 genes in ten independent TOPMed studies with individuals of European, African, and East Asian ancestry, and Hispanics (N = 29,988), we identified variants in SLX4 (p = 2.19 × 10−4) to be significantly associated with BP traits when accounting for multiple testing. We also replicated the associations previously reported for RBFOX1 (p = 0.007). Follow-up analysis with GTEx eQTL data shows SLX4 variants are associated with gene expression in coronary artery, multiple brain tissues, and right atrial appendage of the heart. Our study demonstrates that linkage analysis of family data can provide an efficient approach for detecting rare variants associated with complex traits in WGS data.
This work was supported by Grants T32 HL007567, HL113338 and HL086694 from the National Heart, Lung, and Blood Institute (NHLBI) and HG003054 from the National Human Genome Research Institute (NHGRI). Whole genome sequencing (WGS) for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). WGS for “NHLBI TOPMed: Atherosclerosis Risk in Communities” (phs001211.v1.p1) was performed at the Baylor College of Medicine Human Genome Sequencing Center (HHSN268201500015C, 3U54HG003273-12S2). WGS for “NHLBI TOPMed: The Framingham Heart Study” (phs000974.v2.p2) was performed at the Broad Institute of MIT and Harvard (HHSN268201500014C). WGS for “NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish” (phs000956.v2.p1) was performed at the Broad Institute of MIT and Harvard (3R01HL121007-01S1). WGS for “NHLBI TOPMed: The Jackson Heart Study” (phs000964.v2.p1) was performed at the University of Washington Northwest Genomics Center (HHSN268201100037C). WGS for “NHLBI TOPMed: The Cleveland Family Study” (phs000954.v1.p1) was performed at the University of Washington Northwest Genomics Center (3R01HL098433-05S1). WGS for “NHLBI TOPMed: Multi-Ethnic Study of Atherosclerosis (MESA)” (phs001416.v1.p1) was performed at the Broad Institute of MIT and Harvard (3U54HG003067-13S1). WGS for “NHLBI TOPMed: Hypertension Genetic Epidemiology Network and Genetic Epidemiology Network of Arteriopathy” (phs001293.v1.p1) was performed at the University of Washington Northwest Genomics Center (3R01HL055673-18S1). WGS for “NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy” (phs001345.v1.p1) was performed at the University of Washington Northwest Genomics Center (3R01HL055673-18S1). WGS for “NHLBI TOPMed: Genetic Studies of Atherosclerosis Risk” (phs001218.v1.p1) was performed at the Macrogen and the Broad Institute of MIT and Harvard (HHSN268201500014C). WGS for “NHLBI TOPMed: Genetic Epidemiology Network of Salt Sensitivity” (phs001217.v1.p1) was performed at the Baylor College of Medicine Human Genome Sequencing Center (HHSN268201500015C). WGS for “NHLBI TOPMed: Women’s Health Initiative” (phs001237.v1.p1) was performed at the Broad Institute of MIT and Harvard (HHSN268201500014C). Centralized read mapping and genotype calling, along with variant quality metrics and filtering, were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1). Phenotype harmonization, data management, sample-identity QC, and general study coordination were provided by the TOPMed Data Coordinating Center (3R01HL-120393-02S1). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I). The authors thank the staff and participants of the ARIC study for their important contributions. The Amish studies upon which these data are based were supported by NIH Grants R01 AG18728, U01 HL072515, R01 HL088119, R01 HL121007, and P30 DK072488. See publication: PMID: 18440328. Support for the Cleveland Family Study was provided by NIH Grants HL 046389, HL113338, and 1R35HL135818. The Framingham Heart Study has been supported by contracts N01-HC-25195 and HHSN268201500001I and Grant R01 HL092577. The Framingham Heart Study thanks the study participants and the multitude of investigators who over its 70-year history continue to contribute so much to further our knowledge of heart, lung, blood, and sleep disorders and associated traits. GeneSTAR was supported by Grants from the National Institutes of Health/National Heart, Lung, and Blood Institute (U01 HL72518, HL087698, HL49762, HL58625, HL071025, HL112064), the National Institutes of Health/National Institute of Nursing Research (NR0224103), and by a Grant from the National Institutes of Health/National Center for Research Resources (M01-RR000052) to the Johns Hopkins General Clinical Research Center. Support for GENOA was provided by the National Heart, Lung and Blood Institute (HL054457, HL054464, HL054481, and HL087660) of the National Institutes of Health. The Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) was supported by research Grants (U01HL072507, R01HL087263, and R01HL090682) from the National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD. The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I/HHSN26800001) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The authors also wish to thank the staffs and participants of the JHS. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. Dr. Bress is supported by K01HL133468 from the National Heart, Lung, and Blood Institute, Bethesda, MD. Dr. Franceschini is supported by DK117445 from the National Institute of Diabetes and Digestive Kidney Diseases (NIDDK) and MD012765 from the National Institute on Minority Health and Health Disparities (NIMHD). The authors would like to acknowledge contributions from the investigators of the NHLBI TOPMed Consortium (https://www.nhlbiwgs.org/topmed-banner-authorship).
Compliance with ethical standards
Conflict of interest
The authors declare no competing interests.
The datasets analyzed during the current study are available in the dbGaP repository. Instructions for accessing TOPMed data can be found on: https://www.nhlbiwgs.org/topmed-data-access-scientific-community.
- Cooper RS et al (2002) Genome scan among nigerians linking blood pressure to chromosomes 2, 3, and 19. Hypertension 40:629–633. https://doi.org/10.1161/01.hyp.0000035708.02789.39 CrossRefGoogle Scholar
- Ensembl Variation - Calculated variant consequences (2018) https://useast.ensembl.org/info/genome/variation/prediction/predicted_data.html. Accessed 11 Dec 2018
- EPACTS: Efficient and Parallelizable Association Container Toolbox (2016) http://genome.sph.umich.edu/wiki/EPACTS. Accessed 1 Dec 2017
- Kupper N, Willemsen G, Riese H, Posthuma D, Boomsma DI, de Geus EJ (2005) Heritability of daytime ambulatory blood pressure in an extended twin design. Hypertension 45:80–85. https://doi.org/10.1161/01.HYP.0000149952.84391.54 CrossRefGoogle Scholar