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Your search keyword '"Boer, Cindy G"' showing total 2 results
Start Over Author "Boer, Cindy G" Journal plos genetics
2 results on '"Boer, Cindy G"'

1. Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Author

Suri, Pradeep, Palmer, Melody R, Tsepilov, Yakov A, Freidin, Maxim B, Boer, Cindy G, Yau, Michelle S, Evans, Daniel S, Gelemanovic, Andrea, Bartz, Traci M, Nethander, Maria, Arbeeva, Liubov, Karssen, Lennart, Neogi, Tuhina, Campbell, Archie, Mellstrom, Dan, Ohlsson, Claes, Marshall, Lynn M, Orwoll, Eric, Uitterlinden, Andre, Rotter, Jerome I, Lauc, Gordan, Psaty, Bruce M, Karlsson, Magnus K, Lane, Nancy E, Jarvik, Gail P, Polasek, Ozren, Hochberg, Marc, Jordan, Joanne M, Van Meurs, Joyce BJ, Jackson, Rebecca, Nielson, Carrie M, Mitchell, Braxton D, Smith, Blair H, Hayward, Caroline, Smith, Nicholas L, Aulchenko, Yurii S, and Williams, Frances MK

Subjects
Humans, Back Pain, Intracellular Signaling Peptides and Proteins, DNA-Binding Proteins, Polymorphism, Single Nucleotide, Introns, European Continental Ancestry Group, Genome-Wide Association Study, SOXD Transcription Factors, Genetic Loci, Chronic Pain, Biomarkers, Tumor, DCC Receptor, Polymorphism, Single Nucleotide, Biomarkers, Tumor, Human Genome, Genetics, Aging, Pain Research, 2.1 Biological and endogenous factors, Developmental Biology
Abstract

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥3-6 months; non-cases were included as comparisons ("controls"). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p

Published
2018

2. Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis.

Author

Castaño-Betancourt, Martha C, Evans, Dan S, Ramos, Yolande FM, Boer, Cindy G, Metrustry, Sarah, Liu, Youfang, den Hollander, Wouter, van Rooij, Jeroen, Kraus, Virginia B, Yau, Michelle S, Mitchell, Braxton D, Muir, Kenneth, Hofman, Albert, Doherty, Michael, Doherty, Sally, Zhang, Weiya, Kraaij, Robert, Rivadeneira, Fernando, Barrett-Connor, Elizabeth, Maciewicz, Rose A, Arden, Nigel, Nelissen, Rob GHH, Kloppenburg, Margreet, Jordan, Joanne M, Nevitt, Michael C, Slagboom, Eline P, Hart, Deborah J, Lafeber, Floris, Styrkarsdottir, Unnur, Zeggini, Eleftheria, Evangelou, Evangelos, Spector, Tim D, Uitterlinden, Andre G, Lane, Nancy E, Meulenbelt, Ingrid, Valdes, Ana M, and van Meurs, Joyce BJ

Subjects
Cartilage, Hip Joint, Humans, Osteoarthritis, Hip, Genetic Predisposition to Disease, Trehalase, Transforming Growth Factor alpha, Regulatory Sequences, Nucleic Acid, Genetic Heterogeneity, Polymorphism, Single Nucleotide, Aged, Aged, 80 and over, Middle Aged, Female, Male, Receptor, Fibroblast Growth Factor, Type 3, Genome-Wide Association Study, Phosphatidylinositol 3-Kinases, Class Ia Phosphatidylinositol 3-Kinase, Osteoarthritis, Hip, Regulatory Sequences, Nucleic Acid, Polymorphism, Single Nucleotide, and over, Receptor, Fibroblast Growth Factor, Type 3, Genetics, Developmental Biology
Abstract

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10-8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies.

Published
2016

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