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Front Genet. 2019 Jun 12;10:511. doi: 10.3389/fgene.2019.00511. eCollection 2019.

A Trans-Ethnic Genome-Wide Association Study of Uterine Fibroids.

Author information

1
Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
2
Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, United States.
3
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States.
4
Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University School of Medicine, Nashville, TN, United States.
5
Division of Reproductive Endocrinology and Infertility, Departments of Obstetrics and Gynecology and Surgery, Mayo Clinic, Rochester, MN, United States.
6
Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
7
Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA, United States.
8
Sigfried and Janet Weis Center for Research, Geisinger Health System, Danville, PA, United States.
9
SAMRC-SHIP South African Tuberculosis Bioinformatics Initiative, Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa.
10
Center for Health Information Partnerships, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
11
Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
12
Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, United States.
13
Department of Family Medicine and Behavioral Health, University of Minnesota Medical School, Duluth, MN, United States.
14
Department of Medicine, University of Chicago, Chicago, IL, United States.
15
Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
16
Division of Health Informatics, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, United States.
17
Genomic Medicine Institute, Geisinger, Danville, PA, United States.
18
Center for Statistical Genetics, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
19
Biomedical Informatics Research Center, Marshfield Clinic Research Institute, Marshfield, WI, United States.
20
Department of Biomedical Informatics and Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
21
Departments of Medicine, Pharmacology, and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.

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.

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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