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. Author manuscript; available in PMC: 2014 Jul 1.
Published in final edited form as: J Med Genet. 2013 Apr 9;50(7):473–478. doi: 10.1136/jmedgenet-2012-101287

Meta-Analysis of Genome-Wide Studies Identifies MEF2C SNPs Associated with Bone Mineral Density at Forearm

Hou-Feng Zheng 1,#, Emma Duncan 2,3, Laura M Yerges-Armstrong 4, Joel Eriksson 5, Ulrica Bergström 6, Paul J Leo 2, William D Leslie 7, David Goltzman 8, John Blangero 9, David A Hanley 10, Melanie A Carless 9, Elizabeth A Streeten 4,11, Mattias Lorentzon 5, Matthew A Brown 2, Tim D Spector 12, Ulrika Pettersson-Kymmer 13,14, Claes Ohlsson 5, Braxton D Mitchell 4, J Brent Richards 1,12,#
PMCID: PMC3769185  NIHMSID: NIHMS504675  PMID: 23572186

Abstract

Background

Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown.

Aim

To identify genetic variants associated with forearm BMD and forearm fractures.

Methods

BMD at distal radius measured by dual-energy X-ray absorptiometry was tested for association with common genetic variants. We conducted a meta-analysis of genome-wide association studies for BMD in 5,866 subjects of European descent and then selected variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-SNP test. We then tested the BMD-associated SNPs for association with forearm fracture in 2,023 cases and 3,740 controls.

Results

We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (P<5×10−8) in meta-analysis (lead SNP, rs11951031[T] −0.20 standard deviations per allele, P=9.01×10−9). The gene-based association test suggested an association between MEF2C and forearm BMD (P=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: odds ratio = 1.14 [95% CI: 0.92–1.35], P = 0.14). Meta analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2.

Conclusion

These findings demonstrate that variants at MEF2C were associated with forearm BMD thereby implicating this gene in the determination of bone mineral density at forearm.

Keywords: Genome-wide association study, Osteoporosis, Bone mineral density, Forearm, Fracture, Meta-analysis, Gene-base, Conditional analysis

INTRODUCTION

Osteoporosis is a common disease characterized by low bone mineral density (BMD), resulting in an increased risk of fragility fracture [1]. BMD, the best clinical indicator of fracture risk, is a highly heritable trait, with heritability estimates of 60%–85% [2]. Forearm fractures are among the most common fractures, affecting 1.7 million individuals per year [3], and have heritability of 54% [4].

Genome-wide association studies (GWAS) have identified more than 10 genes associated with BMD from the Wnt signaling pathway, which is crucial to bone biology [5, 6]. We recently conducted two separate GWAS meta-analyses for cortical bone thickness and forearm BMD, and reported WNT16, which encodes an important Wnt factor, to be associated with BMD, cortical bone thickness, bone strength and osteoporotic fracture risk [7]. In the current study, we extended our study on forearm BMD by adding an additional GWAS cohort with BMD data, increasing our meta-analysis sample size for six GWAS cohorts to 5,866 European-descended samples. In this new analysis we detected an additional locus associated with forearm BMD and then replicated the association in an independent cohort comprising 715 Mexican American samples. We additionally conducted a gene-based association test to more fully characterize association signals from the meta-analysis. Finally, we selected the most compelling SNPs from these analyses and genotyped them in three cohorts comprising 2,023 forearm fracture cases and 3,740 controls to test their effects on the risk of forearm fracture.

MATERIALS AND METHODS

The GWAS and fracture samples have been described previously [7]. Briefly, the six GWAS cohorts include the Amish Family Osteoporosis Study (AFOS), the Gothenburg Osteoporosis and Obesity Determinants (GOOD) study, the Anglo-Australasian Osteoporosis Genetics Consortium (AOGC) study, TwinsUK1, TwinsUK23 and TwinsUK4, comprising a total of 5,866 European-descended samples. The TwinsUK4 cohort, which includes 194 subjects phenotyped for forearm BMD, was not included in our previous GWAS [7], nor was the Mexican American replication sample (see below). Genotyping of the TwinUK4 was done on the Illumina HumanHap650K platform. The quality control criteria are similar to TwinsUK23 described in Zheng et al [7]. Imputation was performed using the IMPUTE2 [8] based on HapMap2, release 22. BMD at distal radius was measured in all cohorts by dual-energy X-ray absorptiometry following standard manufacturer protocols. The fracture cohorts include AOGC, the Umea Fracture and Osteoporosis (UFO) study, the Canadian Multi-Centre Osteoporosis study (CaMos) and the Manitoba-McGill (ManMc) fracture study, comprising 2,023 forearm fracture cases and 3,740 controls. Forearm fracture was defined as fractures resulting from low trauma (such as a fall from standing height) occurring at the wrist, ulna, radius, and forearm, as well as Colles’ fractures. There are no overlapping samples between BMD and fracture. De-novo genotyping of SNP rs12521522 in fracture cases and controls was undertaken at Kbiosciences (England). All study participants provided informed written consent. Approval by local institutional review boards was obtained in all studies.

The replication cohort is from the San Antonio Family Osteoporosis Study (SAFOS), which was designed as a study of cardiovascular and bone health in a representative sample of multigenerational Mexican American families [9]. Probands aged 40–60 years of age were recruited from low-income neighborhoods in San Antonio, Texas regardless of health status. The SAFOS samples were genotyped using the Illumina 550 HumanHap Beadchip by the Texas Biomedical Research Institute as part of the San Antonio Family Heart Study. Association analysis was conducted using the SOLAR software program [10] to account for family structure. To minimize the risk of false associations due to stratification in this admixed sample, we performed a principal component analysis using ~ one million genotypes to capture the total genetic variation in the sample as previously described [11]. We then included as covariates into the association analysis the first four principal components. A total of 715 samples with forearm BMD data were analyzed in the current study; the mean age, height and weight of these study subjects was 42 ± 14.7 (year), 161.9 ± 9.2 (centimeter) and 81.6 ± 21.5 (kilogram), respectively.

Statistical methods for the meta-analysis were similar to those used in the previous analysis [7]. Briefly, all cohorts independently conducted the association analysis of SNP allele dosage with standardized BMD residuals, while adjusting for age, age2, gender, height, weight and population substructure where applicable, for center of recruitment (AOGC), and for family structure in cohorts with family members. A meta-analysis of the GWAS results was conducted using the GWAMA software (Genome-Wide Association Meta Analysis) (http://www.well.ox.ac.uk/gwama/) [12] with fixed-effects inverse variance meta-analysis [13].

We next performed a gene-based association test following the procedure proposed by Liu et al as implemented in the software VEGAS [14], a computationally feasible method for analyzing meta-analytic results. We included all SNPs within genes (including ±50 kb from the 5’ and 3’ UTR) with a maximum of 1×106 simulations to account for the linkage disequilibrium (LD) structure among SNPs within a gene. Conditional analysis was conducted using GCTA 0.93.9 [15], an approximate conditional analysis method using summary-level statistics from the meta-analysis and LD corrections between SNPs estimated from a reference sample [16]. We used TwinsUK23 as the reference sample to calculate the LD information of SNPs, due to its size.

SNPs that were associated with BMD were assessed for association with fracture risk using logistic regression models adjusted for age, gender, height and weight. We used CatS [17] for power calculation.

RESULTS

GWAS analyses were performed in the six cohorts for forearm BMD applying cohort-specific genomic controls. The cohort-specific results were meta-analyzed using fixed effects meta-analysis, again applying the overall meta-analytic genomic control (Overall λ = 1.012, and 1.051 for AFOS; 0.990 for AOGC; 1.014 for GOOD; 1.0089 for TwinsUK1; 1.0037 for TwinsUK23; 1.170 for TwinsUK4). A quantile-quantile plot of the observed P values showed a clear deviation at the tail of the distribution from the null distribution (the distribution expected if there were no association) even after 648 SNPs were removed from the WNT16 region, which was reported previously [7]. This suggests that the observed P values, particularly the ones within the tail of the distribution, are smaller than those expected by chance and probably reflect true genetic association (Figure 1).

Figure 1.

Figure 1

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Quantile-quantile plots of the observed P values versus the expected P values for association. The dots in blue were plotted on the entire set of SNPs, whereas the dots in red were obtained after removing 648 SNPs in WNT16 region (+/− 400KB either side of rs2908004). The black line was the distribution expected if there were no association.

Genome-wide associations with forearm BMD were observed at two loci, WNT16 (7q31) and MEF2C (5q14.3). At WNT16, significant associations were observed with 30 SNPs (3.26×10−8>P>1.87×10−13), replicating an association we have previously observed [7] (Figure 2). At MEF2C, five of eight SNPs were significantly associated with forearm BMD, with the other three SNPs showing suggestive levels of association (4.55×10−7 >P>3.15×10−8) on meta-analysis (Figure 2 and 3). The most significantly associated SNP was rs12521522 (−0.20 standard deviations [SD] per A allele, P = 3.15×10−8) (Table 1). These eight SNPs were highly correlated with each other (HapMap CEU LD calculation: 1> R2 >0.85). Using association results from the GWAS meta-analysis we next sought to determine if there were any gene-based signals arising when GWAS summary statistics were collapsed across the genes [14]; The gene-based test results support the single-SNP findings of the meta-analysis, with collapsing P-values of 0.003 for gene MEF2C.

Figure 2.

Figure 2

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Manhattan plot for GWAS meta-analysis of forearm BMD. Genome-wide P values (−log10 P) of the linear regression analysis plotted against position on each chromosome.

Figure 3.

Figure 3

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Scatter plots of the observed association with forearm BMD in the 800kb wide region around rs12521522 in MEF2C locus. The P values of SNPs (shown as −log10 values in y-axis, from the genome-wide single-marker association analysis using the linear regression model) are plotted against their map position (b36) (x-axis). The color of each SNP spot reflects its r2 with rs12521522. SNPs rs11951031 and rs12521522 are in perfect LD, and rs1366594 is ~237kb away from rs11951031.

Table 1.

Association results of forearm BMD meta-analysis and fracture of the top SNPs.

GWAS Meta analysis SAFOS Joint analysis* Fracture analysis#
CHR SNP POSITION EA NEA EAF BETA SE P EAF BETA SE P BETA SE P OR P
5 rs17558256 88119209 C T 0.06 −0.20 0.04 3.15×10−8 0 NA NA NA NA NA NA 1.20 (0.82–1.43) 0.33
5 rs11958689 88142609 G C 0.06 −0.20 0.04 4.16×10−8 0.08 0.04 0.11 0.72 −0.18 0.03 3.35×10−7 1.21 (0.83–1.45) 0.31
5 rs12521522 88148517 A T 0.06 −0.20 0.04 3.15×10−8 0 NA NA NA NA NA NA 1.14 (0.92–1.35) 0.14
5 rs11955542 88148984 T C 0.06 −0.20 0.04 3.15×10−8 0 NA NA NA NA NA NA 1.20 (0.82–1.43) 0.33
5 rs11951031 88174487 T C 0.06 −0.20 0.04 4.16×10−8 0.04 −0.23 0.14 0.10 −0.20 0.04 9.01×10−9 1.20 (0.81–1.45) 0.33
5 rs12515983 88189831 A T 0.06 −0.20 0.04 6.12×10−8 0 NA NA NA NA NA NA 1.19 (0.81–1.44) 0.34
5 rs12522630 88224123 A G 0.07 −0.18 0.04 3.35×10−7 0.04 −0.29 0.14 0.04 −0.19 0.03 5.19×10−8 1.25 (0.83–1.49) 0.22
5 rs17494872 88228915 A G 0.07 −0.18 0.04 4.55×10−7 0.04 −0.29 0.14 0.04 −0.19 0.03 6.82×10−8 1.25 (0.83–1.49) 0.23
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EA: effect allele; NEA: non-effect allele; EAF: effect allele frequency;

NA: not applicable; these SNPs were not polymorphic in Mexican Americans (rs17558256, rs12521522, rs11955542 and rs12515983).

*

Combined results of GWAS meta-analysis and SAFOS replication study.

#

SNP rs12521522 was tested in 2,023 cases and 3,740 controls; the other 7 SNPs were tested in 155 cases and 1672 controls.

Boldface indicated the genome wide significant SNPs.

Meta analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2, including 34 genome-wide suggestive SNPs in the region of CTNNA2 (1.73×10−6<P<5×10−6) and 10 genome-wide suggestive SNPs at 6q23.2 (5.52×10−7<P<3.76×10−6) (Figure 2).

We attempted an in silico replication on the eight SNPs associated with forearm BMD at MEF2C in the Mexican American population. Four of the eight SNPs were monomorphic in the replication population. Of the remaining four polymorphic SNPs, three had effect sizes in the same direction as, and even slightly larger than, those observed in the meta-analysis, including two SNPs for which the associations in Mexican Americans achieved statistical significance at the 0.05 threshold (rs12522630 and rs17494872) (Table 1). In the joint analysis of discovery and replication populations, evidence of association improved for the three SNPs, with the most significant association at rs11951031 (−0.20 SD per T allele, P = 9.01×10−9) (Table 1 and Figure 4).

Figure 4.

Figure 4

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Forest plot of association of rs11951031 (effect allele T) with forearm BMD.

In order to investigate whether the variants showing association with forearm BMD also have an effect on the risk of forearm fracture, we tested SNP rs12521522 for de novo genotyping in samples with forearm fracture and their controls. In the meta-analysis for fracture, comprising 2,023 forearm fracture cases and 3,740 controls, from 3 cohorts. The association between rs12521522 and risk of fracture did not achieve statistical significance (Odds Ratio [OR] = 1.14 [95% CI: 0.92–1.35], P = 0.14) (Table 1). The fracture associations for the other 7 SNPs at the MEF2C locus were tested in silico in the much smaller AOGC fracture GWAS cohort in 155 cases and 1672 controls and the results showed no evidence of association (Table 1).

Because SNP rs1366594, which locates upstream of MEF2C gene (Figure 3), has been previously reported to be associated with femoral neck (FN) BMD [18], we evaluated whether this SNP or signals from this region could explain the observed association with forearm BMD. First, the minor allele frequency (MAF) of forearm BMD-associated SNP in our study (rs11951031, MAF=0.06) was considerably lower than that of FN BMD-associated SNP (rs1366594, MAF=0.45), and the effect size of rs11951031 (−0.20 SD per T allele) was much larger than rs1366594 (−0.085 SD per C allele). Second, these two SNPs are only very weakly correlated with each other (HapMap CEU LD calculation: R-square =0.087). Third, after conditioning on the effect of rs1366594, the effect size for rs11951031 on forearm BMD decreased from −0.20 SD per T allele (4.16×10−8) to −0.18 SD per T allele (1.35×10−6). Therefore, the SNPs we have found to be associated with forearm BMD are distinct from those found previously [18].

DISCUSSION

We identified gene MEF2C, a member of the Wnt signaling pathway, to be associated with forearm BMD in meta-analysis in a collection of 6,584 individuals. In addition, we observed a non-significant trend towards risk of fracture at this locus.

The Wnt/β-catenin signaling pathway is known to play an important role in the regulation of bone mass and bone turnover [19]. MEF2C is an important member of this pathway [5, 6], and, in fact, in the large GEFOS Consortium, a SNP (rs1366594) located upstream from this gene, was associated with FN BMD, although not with lumbar spine BMD [18], We report in this study that intronic variants in MEF2C are associated with forearm BMD, a clinically distinct phenotype from that at femoral neck.

Our finding adds three novel pieces to the genetics of BMD puzzle. First, bone at the forearm is structurally different than bone at the femoral neck insofar as forearm bone contains a much higher proportion of cortical bone. BMD at both sites predicts fracture at their respective anatomical sites better than at other sites. Second, the associated variants for forearm BMD appear to be quite distinct from the variants associated with FN BMD. Not only are they located over ~237kb from each other (Figure 3), but they have very different allele frequencies (0.06 vs 0.45) and very different effect sizes (−0.20 SD vs −0.06 SD), and they are not correlated. Moreover, conditional analyses reveal that the effect of rs11951031 on forearm BMD are largely independent of any effect of rs1366594. We postulate that these common variants are likely independent signals that have different independent effects on the two BMD phenotypes. It is also possible that both associations arise from several rare causal variants on the same haplotype background [20], however, this hypothesis will likely be tested as more sequencing studies emerge for BMD. These observations also suggest that the same variants have differential effects on different types of bone.

We did not observe a statistically significant association of MEF2C SNP (rs12521522) with osteoporotic fracture in the current study. Our sample size (2,023 cases and 3,740 controls) provided 44% power to detect an odds ratio of 1.14 for a risk allele having a frequency of 0.06. However, the direction of effect of the alleles that decreased BMD was associated with in increase in fracture risk across the study cohorts. Given the sample size for fracture in this study, these results should be interpreted cautiously and require further replication. Additionally, rs1366594, which was reported in Rivadeneira et al [18] showed no evidence of association with forearm fracture neither in the AOGC in silico analysis (155 cases and 1672 controls, P=0.27).

In summary, our data provides first evidence that intronic variants at the MEF2C locus, a member of the Wnt pathway, are associated with forearm BMD. These findings expand our understanding of the genetic determinants of forearm BMD, a clinically relevant skeletal site.

Acknowledgements

We are extremely grateful to all the individuals who took part in this study. We thank the Wellcome Trust Sanger Institute for generating the TwinsUK GWA data. This publication is the work of all authors and they will serve as guarantors for the contents of this paper.

Funding

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. AFOS: NIH research grants R01 AG18728, R01HL088119, R01AR046838, U01 HL084756, P30DK072488 and F32AR059469; AOGC: The Anglo-Australasian Osteoporosis Genetics Consortium was funded by a project grant from the National Health and Medical Research Council (NHMRC) (Australia) (grant reference 511132), and a NHMRC-European Union Collaborative grant. MAB was funded by an NHMRC Senior Principal Research Fellowship (grant reference APP1024879). CaMos/ManMc: This work was supported by grants from the Canadian Foundation for Innovation, the Canadian Institutes of Health Research (CIHR), Fonds de la recherche en sante du Quebec and the Jewish General Hospital, Ministere Développement Économique, Innovation et Exportation du Québec, Fonds de la Recherche en Santé du Québec, Lady Davis Institute of Medical Research and the Dairy Farmers of Canada; GOOD: Financial support was received from the Swedish Research Council, the Swedish Foundation for Strategic Research, the ALF/LUA research grant in Gothenburg, the Lundberg Foundation, the Torsten and Ragnar Söderberg's Foundation, the Västra Götaland Foundation, the Göteborg Medical Society, the Novo Nordisk foundation, and the European Commission grant HEALTH-F2-2008-201865-GEFOS. SAFOS: NIH research grant R01 AR43351. TwinsUK: NIHR Biomedical Research Centre (grant to Guys’ and St. Thomas’ Hospitals and King’s College London); the Chronic Disease Research Foundation, Wellcome Trust; National Institutes of Health Research, National Health and Medical Research Council (Australia). UFO: The Umeå Fracture and Osteoporosis Study (UFO) is supported by BBMRI.se, the Swedish Research Council (K20006-72X-20155013), the Swedish Sports Research Council (87/06), the Swedish Society of Medicine, the Kempe-Foundation (JCK-1021), and by grants from the Medical Faculty of Umeå Unviersity (ALFVLL:968:22-2005, ALFVLL-937-2006, ALFVLL 223:11-2007, ALFVLL-78151-2009) and from the county council of Västerbotten (Spjutspetsanslag VLL:159:33-2007)

Footnotes

Contributors

Conceived and designed the study: H-F Zheng, JB Richards. Analyzed the data: H-F Zheng, E Duncan, LM Yerges-Armstrong, Joel Eriksson, PJ Leo, U Bergström, EA Streeten, BD Mitchell, JB Richards. Contribute reagents/materials/phenotype: WD Leslie, D Goltzman, T Spector, John Blangero, M Lorentzon, C Ohlsson, U Pettersson-Kymmer, Melanie Carless, DA Hanley, Matthew Brown, JB Richards. Wrote the paper: H-F Zheng, BD Mitchell, JB Richards. Revised the manuscript: all authors.

Competing interests None

Patient Consent Written informed consent was obtained from all study participants.

Ethics approval Approval by local institutional review boards was obtained in all studies.

Provenance and peer review Not commissioned; externally peer reviewed.

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