In bone, sclerostin is mainly osteocyte-derived and plays an important local role in adaptive responses to mechanical loading. Whether circulating levels of sclerostin also play a functional role is currently unclear, which we aimed to examine by two-sample Mendelian randomization (MR). A genetic instrument for circulating sclerostin, derived from a genomewide association study (GWAS) meta-analysis of serum sclerostin in 10,584 European-descent individuals, was examined in relation to femoral neck bone mineral density (BMD; n = 32,744) in GEFOS and estimated bone mineral density (eBMD) by heel ultrasound (n = 426,824) and fracture risk (n = 426,795) in UK Biobank. ◼This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Our GWAS identified two novel serum sclerostin loci, B4GALNT3 (standard deviation [SD]) change in sclerostin per A allele (β = 0.20, p = 4.6 × 10 −49 ) and GALNT1 (β = 0.11 per G allele, p = 4.4 × 10 −11 ). B4GALNT3 is an N-acetyl-galactosaminyltransferase, adding a terminal LacdiNAc disaccharide to target glycocoproteins, found to be predominantly expressed in kidney, whereas GALNT1 is an enzyme causing mucin-type O-linked glycosylation. Using these two single-nucleotide polymorphisms (SNPs) as genetic instruments, MR revealed an inverse causal relationship between serum sclerostin and femoral neck BMD (β = -0.12, 95% confidence interval [CI] -0.20 to -0.05) and eBMD (β = -0.12, 95% CI -0.14 to -0.10), and a positive relationship with fracture risk (β = 0.11, 95% CI 0.01 to 0.21). Colocalization analysis demonstrated common genetic signals within the B4GALNT3 locus for higher sclerostin, lower eBMD, and greater B4GALNT3 expression in arterial tissue (probability >99%). Our findings suggest that higher sclerostin levels are causally related to lower BMD and greater fracture risk. Hence, strategies for reducing circulating sclerostin, for example by targeting glycosylation enzymes as suggested by our GWAS results, may prove valuable in treating osteoporosis. Fig. 2. Forest plot of putative causal relationship between serum sclerostin and bone phenotypes using Mendelian randomization. The x axis represents the causal estimates and 95% confidence intervals of SD change in BMD/eBMD and OR for fracture, per SD increase in sclerostin, as calculated by inverse variance-weighted method. The y axis lists the four bone phenotypes used in the MR analysis. Journal of Bone and Mineral Research ■ 1830 ZHENG ET AL.In murine gene expression studies, B4galnt3 mRNA was expressed at highest levels in kidney, with relatively high levels of expression ◼ 8 ZHENG ET AL.

Guidelines for prevention of cardiovascular diseases use risk scores to guide the intensity of treatment. A comparison of these scores in a German population has not been performed. We have evaluated the correlation, discrimination and calibration of ten commonly used risk equations in primary care in 4044 participants of the DETECT (Diabetes and Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study. The risk equations correlate well with each other. All risk equations have a similar discriminatory power. Absolute risks differ widely, in part due to the components of clinical endpoints predicted: The risk equations produced median risks between 8.4% and 2.0%. With three out of 10 risk scores calculated and observed risks well coincided. At a risk threshold of 10 percent in 10 years, the ACC/AHA atherosclerotic cardiovascular disease (ASCVD) equation has a sensitivity to identify future CVD events of approximately 80%, with the highest specificity (69%) and positive predictive value (17%) among all the equations. Due to the most precise calibration over a wide range of risks, the large age range covered and the combined endpoint including non-fatal and fatal events, the ASCVD equation provides valid risk prediction for primary prevention in Germany.