Browsing by Author "McCarty, Catherine A."

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    Epistatic gene-based interaction analyses for glaucoma in eMERGE and NEIGHBOR Consortium
    (Public Library of Science, 2016) Verma, Shefali Setia; Bailey, Jessica N. Cooke; Lucas, Anastasia; Bradford, Yuki; Linneman, James G.; Hauser, Michael A.; Pasquale, Louis R.; Peissig, Peggy L.; Brilliant, Murray H.; McCarty, Catherine A.; Haines, Jonathan L.; Wiggs, Janey L.; Vrabec, Tamara R.; Tromp, Gerard; Ritchie, Marylyn D.; eMERGE Network; NEIGHBOR Consortium
    Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.
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    A trans-ethnic genome-wide association study of uterine fibroids
    (Frontiers Media, 2019) Edwards, Todd L.; Giri, Ayush; Hellwege, Jacklyn N.; Hartmann, Katherine E.; Stewart, Elizabeth A.; Jeff, Janina M.; Pendergrass, Sarah A.; Torstenson, Eric S.; Keaton, Jacob M.; Jones, Sarah H.; Gogoi, Radhika P.; Kuivaniemi, Helena; Jackson, Kathryn L.; Kho, Abel N.; Kullo, Iftikhar J.; McCarty, Catherine A.; Im, Hae Kyung; Pacheco, Jennifer A.; Pathak, Jyotishman; Williams, Marc S.; Tromp, Gerard; Kenny, Eimear E.; Peissig, Peggy L.; Denny, Joshua C.; Roden, Dan M.; Edwards, Digna R. Velez
    ENGLISH 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.