A trans-ethnic genome-wide association study of uterine fibroids

Todd L. Edwards, Ayush Giri, Jacklyn N. Hellwege, Katherine E. Hartmann, Elizabeth A. Stewart, Janina M. Jeff, Michael J. Bray, Sarah A. Pendergrass, Eric S. Torstenson, Jacob M. Keaton, Sarah H. Jones, Radhika P. Gogoi, Helena Kuivaniemi, Kathryn L. Jackson, Abel N. Kho, Iftikhar J. Kullo, Catherine A. McCarty, Hae Kyung Im, Jennifer A. Pacheco, Jyotishman PathakMarc S. Williams, Gerard Tromp, Eimear E. Kenny, Peggy L. Peissig, Joshua C. Denny, Dan M. Roden, Digna R.Velez Edwards

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Uterine fibroids affect up to 77% of women by menopause and account for up to $34 billion in healthcare costs each year. Although fibroid risk is heritable, genetic risk for fibroids is not well understood. We conducted a two-stage case-control meta-analysis of genetic variants in European and African ancestry women with and without fibroids classified by a previously published algorithm requiring pelvic imaging or confirmed diagnosis. Women from seven electronic Medical Records and Genomics (eMERGE) network sites (3,704 imaging-confirmed cases and 5,591 imaging-confirmed controls) and women of African and European ancestry from UK Biobank (UKB, 5,772 cases and 61,457 controls) were included in the discovery genome-wide association study (GWAS) meta-analysis. Variants showing evidence of association in Stage I GWAS (P < 1 × 10-5) were targeted in an independent replication sample of African and European ancestry individuals from the UKB (Stage II) (12,358 cases and 138,477 controls). Logistic regression models were fit with genetic markers imputed to a 1000 Genomes reference and adjusted for principal components for each race- and site-specific dataset, followed by fixed-effects meta-analysis. Final analysis with 21,804 cases and 205,525 controls identified 326 genome-wide significant variants in 11 loci, with three novel loci at chromosome 1q24 (sentinel-SNP rs14361789; P = 4.7 × 10-8), chromosome 16q12.1 (sentinel-SNP rs4785384; P = 1.5 × 10-9) and chromosome 20q13.1 (sentinel-SNP rs6094982; P = 2.6 × 10-8). Our statistically significant findings further support previously reported loci including SNPs near WT1, TNRC6B, SYNE1, BET1L, and CDC42/WNT4. We report evidence of ancestry-specific findings for sentinel-SNP rs10917151 in the CDC42/WNT4 locus (P = 1.76 × 10-24). Ancestry-specific effect-estimates for rs10917151 were in opposite directions (P-Het-between-groups = 0.04) for predominantly African (OR = 0.84) and predominantly European women (OR = 1.16). Genetically-predicted gene expression of several genes including LUZP1 in vagina (P = 4.6 × 10-8), OBFC1 in esophageal mucosa (P = 8.7 × 10-8), NUDT13 in multiple tissues including subcutaneous adipose tissue (P = 3.3 × 10-6), and HEATR3 in skeletal muscle tissue (P = 5.8 × 10-6) were associated with fibroids. The finding for HEATR3 was supported by SNP-based summary Mendelian randomization analysis. Our study suggests that fibroid risk variants act through regulatory mechanisms affecting gene expression and are comprised of alleles that are both ancestry-specific and shared across continental ancestries.

Original languageEnglish (US)
Article number511
JournalFrontiers in Genetics
Volume10
Issue numberJUN
DOIs
StatePublished - 2019

Bibliographical note

Funding Information:
This work was funded by the Building Interdisciplinary Research Careers in Women’s Health career development program (2K12-HD043483-11; PI: KH) to DE, (2K12HD043483-17; PI: KH) to AG, the National Institutes of Health (NIH) grant 1R01-HD074711-01 to DE, NIH grant 1R03-HD078567-01 to DE, the Vanderbilt Clinical and Translational Research Scholar Award 5KL2-RR024977 to TE from the National Center for Advancing Translational Sciences, the Vanderbilt CTSA award UL1TR000445 from the National Center for Advancing Translational Sciences, and the BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center’s BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Support was also provided by the Vanderbilt Molecular and Genetic Epidemiology of Cancer (MAGEC) training program, funded by R25/T32CA160056 to JH (PI: X.-O. Shu). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. The eMERGE Network was initiated and funded by NHGRI, in conjunction with additional funding from NIGMS through the following grants: U01-HG004610 and U01-HG006375 (Group Health Cooperative/University of Washington); U01-HG004608 (Marshfield Clinic Research Foundation and Vanderbilt University Medical Center); U01-HG-04599 and U01-HG006379 (Mayo Clinic); U01-HG004609 and U01-HG006388 (Northwestern University); U01HG006389 (Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University); U01-HG006382 (Geisinger Clinic); U01-HG006380 (Icahn School of Medicine at Mount Sinai); U01-HG04603 and U01-HG006378 and U01-HG006385 (Vanderbilt University Medical Center, also serving as the Coordinating Center); U01-HG004438 (CIDR) and U01-HG004424 (the Broad Institute) serving as Genotyping Centers.

Funding Information:
This work was funded by the Building Interdisciplinary Research Careers in Women's Health career development program (2K12-HD043483-11; PI: KH) to DE, (2K12HD043483-17; PI: KH) to AG, the National Institutes of Health (NIH) grant 1R01-HD074711-01 to DE, NIH grant 1R03-HD078567-01 to DE, the Vanderbilt Clinical and Translational Research Scholar Award 5KL2-RR024977 to TE from the National Center for Advancing Translational Sciences, the Vanderbilt CTSA award UL1TR000445 from the National Center for Advancing Translational Sciences, and the BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Support was also provided by the Vanderbilt Molecular and Genetic Epidemiology of Cancer (MAGEC) training program, funded by R25/T32CA160056 to JH (PI: X.-O. Shu). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. The eMERGE Network was initiated and funded by NHGRI, in conjunction with additional funding from NIGMS through the following grants: U01-HG004610 and U01-HG006375 (Group Health Cooperative/University of Washington); U01-HG004608 (Marshfield Clinic Research Foundation and Vanderbilt University Medical Center); U01-HG-04599 and U01-HG006379 (Mayo Clinic); U01-HG004609 and U01-HG006388 (Northwestern University); U01HG006389 (Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University); U01-HG006382 (Geisinger Clinic); U01-HG006380 (Icahn School of Medicine at Mount Sinai); U01-HG04603 and U01-HG006378 and U01-HG006385 (Vanderbilt University Medical Center, also serving as the Coordinating Center); U01-HG004438 (CIDR) and U01-HG004424 (the Broad Institute) serving as Genotyping Centers.

Publisher Copyright:
© 2019 Frontiers Media S.A. All Rights Reserved.

Keywords

  • Genetic architecture
  • Genetically predicted gene expression (GPGE)
  • Genome-wide association study (GWAS)
  • Meta-analysis electronic health record (EHR)
  • Trans-ethnic
  • Uterine fibroids

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