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GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

ABSTRACT: Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N???28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N?=?13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P?=?2.3?×?10-42, ??=?-0.090) and confers risk of hip fracture (P?=?1.0?×?10-8, OR?=?1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density.

SUBMITTER: Styrkarsdottir U

PROVIDER: S-EPMC6499783 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

Styrkarsdottir Unnur U Stefansson Olafur A OA Gunnarsdottir Kristbjorg K Thorleifsson Gudmar G Lund Sigrun H SH Stefansdottir Lilja L Juliusson Kristinn K Agustsdottir Arna B AB Zink Florian F Halldorsson Gisli H GH Ivarsdottir Erna V EV Benonisdottir Stefania S Jonsson Hakon H Gylfason Arnaldur A Norland Kristjan K Trajanoska Katerina K Boer Cindy G CG Southam Lorraine L Leung Jason C S JCS Tang Nelson L S NLS Kwok Timothy C Y TCY Lee Jenny S W JSW Ho Suzanne C SC Byrjalsen Inger I Center Jacqueline R JR Lee Seung Hun SH Koh Jung-Min JM Lohmander L Stefan LS Ho-Pham Lan T LT Nguyen Tuan V TV Eisman John A JA Woo Jean J Leung Ping-C PC Loughlin John J Zeggini Eleftheria E Christiansen Claus C Rivadeneira Fernando F van Meurs Joyce J Uitterlinden Andre G AG Mogensen Brynjolfur B Jonsson Helgi H Ingvarsson Thorvaldur T Sigurdsson Gunnar G Benediktsson Rafn R Sulem Patrick P Jonsdottir Ingileif I Masson Gisli G Holm Hilma H Norddahl Gudmundur L GL Thorsteinsdottir Unnur U Gudbjartsson Daniel F DF Stefansson Kari K

Nature communications 20190503 1

Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is wit ...[more]

PMID: 31053729

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Project description:Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P?<?0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Project description:Osteoarthritis (OA) risk is widely recognized to be heritable but few loci have been identified. Observational studies have identified higher systemic bone mineral density (BMD) to be associated with an increased risk of radiographic knee osteoarthritis. With this in mind, we sought to evaluate whether well-established genetic loci for variance in BMD are associated with risk for radiographic OA in the Osteoarthritis Initiative (OAI) and the Johnston County Osteoarthritis (JoCo) Project. Cases had at least one knee with definite radiographic OA, defined as the presence of definite osteophytes with or without joint space narrowing (Kellgren-Lawrence [KL] grade ? 2) and controls were absent for definite radiographic OA in both knees (KL grade ? 1 bilaterally). There were 2014 and 658 Caucasian cases, respectively, in the OAI and JoCo Studies, and 953 and 823 controls. Single nucleotide polymorphisms (SNPs) were identified for association analysis from the literature. Genotyping was carried out on Illumina 2.5M and 1M arrays in Genetic Components of Knee OA (GeCKO) and JoCo, respectively and imputation was done. Association analyses were carried out separately in each cohort with adjustments for age, body mass index (BMI), and sex, and then parameter estimates were combined across the two cohorts by meta-analysis. We identified four SNPs significantly associated with prevalent radiographic knee OA. The strongest signal (p?=?0.0009; OR?=?1.22; 95% CI, 1.08-1.37) maps to 12q3, which contains a gene coding for SP7. Additional loci map to 7p14.1 (TXNDC3), 11q13.2 (LRP5), and 11p14.1 (LIN7C). For all four loci the allele associated with higher BMD was associated with higher odds of OA. A BMD risk allele score was not significantly associated with OA risk. This meta-analysis demonstrates that several genomewide association studies (GWAS)-identified BMD SNPs are nominally associated with prevalent radiographic knee OA and further supports the hypothesis that BMD, or its determinants, may be a risk factor contributing to OA development. © 2014 American Society for Bone and Mineral Research.

Dataset Information

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

Publications

GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

Similar Datasets

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