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Meta-Analysis
. 2013;9(2):e1003247.
doi: 10.1371/journal.pgen.1003247. Epub 2013 Feb 21.

Genetic determinants of trabecular and cortical volumetric bone mineral densities and bone microstructure

Lavinia Paternoster  1 , Mattias Lorentzon, Terho Lehtimäki, Joel Eriksson, Mika Kähönen, Olli Raitakari, Marika Laaksonen, Harri Sievänen, Jorma Viikari, Leo-Pekka Lyytikäinen, Dan Mellström, Magnus Karlsson, Osten Ljunggren, Elin Grundberg, John P Kemp, Adrian Sayers, Maria Nethander, David M Evans, Liesbeth Vandenput, Jon H Tobias, Claes Ohlsson
Affiliations
Meta-Analysis

Genetic determinants of trabecular and cortical volumetric bone mineral densities and bone microstructure

Lavinia Paternoster et al. PLoS Genet. 2013.

Abstract

Most previous genetic epidemiology studies within the field of osteoporosis have focused on the genetics of the complex trait areal bone mineral density (aBMD), not being able to differentiate genetic determinants of cortical volumetric BMD (vBMD), trabecular vBMD, and bone microstructural traits. The objective of this study was to separately identify genetic determinants of these bone traits as analysed by peripheral quantitative computed tomography (pQCT). Separate GWA meta-analyses for cortical and trabecular vBMDs were performed. The cortical vBMD GWA meta-analysis (n = 5,878) followed by replication (n = 1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, p = 3.6×10⁻¹⁴; LOC285735, rs271170, p = 2.7×10⁻¹²; OPG, rs7839059, p = 1.2×10⁻¹⁰; and ESR1/C6orf97, rs6909279, p = 1.1×10⁻⁹). The trabecular vBMD GWA meta-analysis (n = 2,500) followed by replication (n = 1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, p = 1.9×10⁻⁹). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (n = 729). rs1021188 was significantly associated with cortical porosity while rs9287237 was significantly associated with trabecular bone fraction. The genetic variant in the FMN2/GREM2 locus was associated with fracture risk in the MrOS Sweden cohort (HR per extra T allele 0.75, 95% confidence interval 0.60-0.93) and GREM2 expression in human osteoblasts. In conclusion, five genetic loci associated with trabecular or cortical vBMD were identified. Two of these (FMN2/GREM2 and LOC285735) are novel bone-related loci, while the other three have previously been reported to be associated with aBMD. The genetic variants associated with cortical and trabecular bone parameters differed, underscoring the complexity of the genetics of bone parameters. We propose that a genetic variant in the RANKL locus influences cortical vBMD, at least partly, via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences GREM2 expression in osteoblasts and thereby trabecular number and thickness as well as fracture risk.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Genome-wide meta-analysis of cortical vBMD.
(A) QQ plots of the genome-wide meta-analysis of cortical vBMD without (filled circles) or with (open diamonds) removal of the genome-wide significant loci (All SNPs excluded ±1 Mb around the hits). (B) Manhattan plot of the genome-wide meta-analysis of cortical vBMD.
Figure 2
Figure 2. Regional association plots for the 5 independent signals from the discovery genome-wide meta-analysis of cortical vBMD.
(A) rs1021188, (B) rs271170, (C) rs7839059, (D) rs6909279, (E) rs17638544. Circles show the GWA meta-analysis p-values, with different colors indicating varying linkage disequilibrium with the indicated SNP (diamond). SNPs in the same region identified in a recent large-scale GWA meta-analysis of aBMD are indicated by a red outer circle . LocusZoom: http://csg.sph.umich.edu/locuszoom/.
Figure 3
Figure 3. Genome-wide meta-analysis of trabecular vBMD.
(A) QQ plot of the genome-wide meta-analysis of trabecular vBMD. (B) Manhattan plot of the genome-wide meta-analysis of trabecular vBMD.
Figure 4
Figure 4. Regional association plot for rs9287237 of the discovery genome-wide meta-analysis of trabecular vBMD.
Circles show the GWA meta-analysis p-values, with different colors indicating varying linkage disequilibrium with rs9287237 (diamond). LocusZoom: http://csg.sph.umich.edu/locuszoom/.
Figure 5
Figure 5. The genome-wide meta-analyses according to sex.
(A) Cortical vBMD (rs1021188 effect allele = C, rs271170 effect allele = T, rs7839059 effect allele = A, rs6909279 effect allele = G, rs17638544 effect allele = T). (B) Trabecular vBMD for rs9287237 (effect allele = T). Mean and standard error vBMD z-scores are shown for each cohort, stratified by sex. Diamonds show the combined z-scores estimates per genotype (the width of the diamond represents the combined standard error). Disc = discovery cohort, repl = replication cohort.
Figure 6
Figure 6. The associations of the SNPs explaining most of the cortical vBMD (rs1021188) and trabecular vBMD variations (rs9287237), respectively, with bone parameters in the GOOD cohort at the follow-up visit (n = 729).
Mean and standard error z-scores are shown for trabecular and cortical vBMDs as analyzed by pQCT, and for trabecular bone volume per total volume (BV/TV), trabecular number (TbN), trabecular thickness (TbTh), trabecular separation (TbSp) and cortical porosity as analyzed by HRpQCT.
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