Exogenous bFGF promotes articular cartilage repair via up-regulation of multiple growth factors

OBJECTIVE

To investigate the roles of exogenous basic fibroblast growth factor (bFGF) on the repair of full-thickness articular cartilage defects in rabbits.

DESIGN

In the present study, a double-layered collagen membrane sandwiched with bFGF-loaded-nanoparticles between a dense layer and a loose layer was implanted into full-thickness articular cartilage defects in rabbits. By grafting the membrane in a different direction, the dense layer or the loose layer facing the surface of the subchondral bone, the effects of the released bFGF on the defects and the profiles of nine growth factors (GFs) in synovial fluid (SF) were investigated using histological methods and antibody arrays, respectively.

RESULTS

In the group with the loose layer facing the surface of the subchondral bone, fast release of bFGF was observed, and early high levels of endogenous transforming growth factor-β2 (TGF-β2), vascular endothelial growth factor (VEGF), bFGF, bone morphogenetic protein 2 (BMP-2), BMP-3, and BMP-4 in SF were detected by antibody arrays, especially on day 3. Chondrocyte-like cells were also observed in this group at an early stage. As a result, this group showed better levels of repair, as compared to the other groups in which low GF levels were detected at an early stage, and chondrocyte-like cells appeared much later.

CONCLUSIONS

Our study suggests that exogenous bFGF promotes articular cartilage repair by up-regulating the levels of multiple GFs, but administration at an early stage is required.

Antitumour effect of sesquiterpene (+)-chabranol on four human cancer cell lines by inducing apoptosis and autophagy

OBJECTIVE

To investigate the effects and mechanisms of sesquiterpene (+)-chabranol on proliferation of a panel of four human tumour cell lines (BGC-823, SGC-7901, SSMC-7721 and HepG2).

METHODS

Cell viability was assessed using a standard methyltetrazolium assay; cell-cycle analysis of BGC-823 cells was performed by flow cytometry. Transmission electron microscopy (TEM) was used to examine the ultrastructure of BGC-823 cells exposed to (+)-chabranol. Apoptosis was investigated by evaluating DNA laddering, using gel electrophoresis.

RESULTS

(+)-Chabranol had a marked time- and concentration-dependent inhibitory effect on BGC-823 cell proliferation. The effect was less marked in SGC-7901, SSMC-7721 and HepG2 cells. Exposure of BGC-823 cells to (+)-chabranol arrested the cell cycle at G(1). Evidence of apoptosis and autophagy was observed by TEM; DNA laddering in BGC-823 cells supported the presence of apoptosis.

CONCLUSIONS

This study suggested that (+)-chabranol has antitumour activity against BGC-823 cells, and may exert its action by inhibition of proliferation and induction of apoptosis and autophagy. With further development, (+)-chabranol may represent a potential novel treatment for poorly differentiated gastric cancer.

Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle

This study investigated the imputation accuracy of different methods, considering both the minor allele frequency and relatedness between individuals in the reference and test data sets. Two data sets from the combined population of Swedish and Finnish Red Cattle were used to test the influence of these factors on the accuracy of imputation. Data set 1 consisted of 2,931 reference bulls and 971 test bulls, and was used for validation of imputation from 3,000 markers (3K) to 54,000 markers (54K). Data set 2 contained 341 bulls in the reference set and 117 in the test set, and was used for validation of imputation from 54K to high density [777,000 markers (777K)]. Both test sets were divided into 4 groups according to their relationship to the reference population. Five imputation methods (Beagle, IMPUTE2, findhap, AlphaImpute, and FImpute) were used in this study. Imputation accuracy was measured as the allele correct rate and correlation between imputed and true genotypes. Results demonstrated that the accuracy was lower when imputing from 3K to 54K than from 54K to 777K. Using various imputation methods, the allele correct rates varied from 93.5 to 97.1% when imputing from 3K to 54K, and from 97.1 to 99.3% when imputing from 54K to 777K; IMPUTE2 and Beagle resulted in higher accuracies and were more robust under various conditions than the other 3 methods when imputing from 3K to 54K. The accuracy of imputation using FImpute was similar to those results from Beagle and IMPUTE2 when imputing from 54K to high density, and higher than the remaining 2 methods. The results also showed that a closer relationship between test set and reference set led to a higher accuracy for all the methods. In addition, the correct rate was higher when the minor allele frequency was lower, whereas the correlation coefficient was lower when the minor allele frequency was lower. The results indicate that Beagle and IMPUTE2 provide the most robust and accurate imputation accuracies, but considering computing time and memory usage, FImpute is another alternative method.

Accuracy of genomic prediction using different models and response variables in the Nordic Red cattle population

Breeding animals can be accurately evaluated using appropriate genomic prediction models, based on marker data and phenotype information. In this study, direct genomic values (DGV) were estimated for 16 traits of Nordic Total Merit (NTM) Index in Nordic Red cattle population using three models and two different response variables. The three models were as follows: a linear mixed model (GBLUP), a Bayesian variable selection model similar to BayesA (BayesA*) and a Bayesian least absolute shrinkage and selection operator model (Bayesian Lasso). The response variables were deregressed proofs (DRP) and conventional estimated breeding values (EBV). The reliability of genomic predictions was measured on bulls in the validation data set as the squared correlation between DGV and DRP divided by the reliability of DRP. Using DRP as response variable, the reliabilities of DGV among the 16 traits ranged from 0.151 to 0.569 (average 0.317) for GBLUP, from 0.152 to 0.576 (average 0.318) for BayesA* and from 0.150 to 0.570 (average 0.320) for Bayesian Lasso. Using EBV as response variable, the reliabilities ranged from 0.159 to 0.580 (average 0.322) for GBLUP, from 0.157 to 0.578 (average 0.319) for BayesA* and from 0.159 to 0.582 (average 0.325) for Bayesian Lasso. In summary, Bayesian Lasso performed slightly better than the other two models, and EBV performed slightly better than DRP as response variable, with regard to prediction reliability of DGV. However, these differences were not statistically significant. Moreover, using EBV as response variable would result in problems with the scale of the resulting DGV and potential problem due to double counting.

Selection for increased number of piglets at d 5 after farrowing has increased litter size and reduced piglet mortality

Selection for litter size at d 5 after farrowing (LS5) was introduced in 2004 to increase the number of piglets weaned and to reduce piglet mortality in Danish Landrace and Yorkshire. The objective of this study was to investigate selection responses for LS5, total number born (TNB), and mortality [MORT, defined as (TNB - LS5)/TNB] when selection for increasing LS5 was a part of the breeding goal. Data were collected from nucleus herds recorded from 2004 to 2010, including first litters of 42,807 Landrace sows and 33,225 Yorkshire sows. The data were analyzed using a 3-trait animal model of TNB, MORT, and LS5. Significant (co) variances were estimated between the 3 traits in both populations. The heritabilities of TNB, MORT, and LS5 were 0.10, 0.09, and 0.09 in Landrace and 0.12, 0.10, and 0.10 in Yorkshire. The genetic correlations were 0.28 and 0.22 between TNB and MORT, 0.74 and 0.68 between TNB and LS5, and -0.43 and -0.57 between MORT and LS5 in Landrace and Yorkshire, respectively. The results show that the genetic improvement of LS5 was a combination of increased TNB and reduced MORT. During the observation period, the genetic improvement was 1.7 piglets per litter for LS5, 1.3 piglets per litter for TNB, and 4.7% for MORT in Landrace and 2.2 piglets per litter, 1.9 piglets per litter, and 5.9% in Yorkshire. Phenotypic improvement was 1.4 piglets per litter for LS5, 0.3 piglets per litter for TNB, and 7.9% for MORT in Landrace and 2.1 piglets per litter, 1.3 piglets per litter, and 7.6% in Yorkshire. In addition, genetic gain was evaluated in 3 phenotypic groups of TNB, representing the 25% smallest litters, the 50% medium litters, and the 25% largest litters. In all 3 groups, the genetic and phenotypic gains of TNB and LS5 increased, whereas MORT reduced in both populations.

Reduction in the risk of clinical fractures after a single dose of zoledronic Acid 5 milligrams

CONTEXT

Annual infusions of zoledronic acid 5 mg over 3 years have been shown to reduce fracture incidence. There is now evidence that the effects of a single dose of zoledronic acid on bone mineral density and bone turnover last for much more than a year. Whether this is associated with sustained fracture prevention is not known.

OBJECTIVE

The objective of the study was to assess fracture incidence after only 1 infusion of zoledronic acid.

DESIGN

The design of the study included post hoc analysis of subgroups of subjects from 2 trials, who received only 1 study infusion.

SETTING

The study included multicenter, randomized controlled trials.

PARTICIPANTS

A total of 1367 subjects from HORIZON-PFT and HORIZON-RFT studies who received only 1 of the planned annual infusions participated in the study.

INTERVENTION

The intervention of the study consisted of 1 infusion of zoledronic acid or placebo.

MAIN OUTCOME MEASURE

Clinical fracture was the main outcome measure of the study.

RESULTS

Mean follow-up period was 1.5 years. In patients who received only a single infusion, there was a 32% reduction in clinical fracture comparing zoledronic acid with placebo over 3 years of follow-up (95% confidence interval 2-53%, P = .04), comparable with the fracture reduction seen in those who had 3 or more annual infusions (34%; 95% confidence interval, 23-43%, P < .0001). New morphometric vertebral fractures were reduced by 68% in the single-infusion group (P = .004). The between-group differences in total hip bone mineral density at 3 years were 3.8% in those receiving 1 infusion and 6.2% in those receiving 3 infusions.

CONCLUSIONS

In this post hoc analysis based on postrandomization subgroups, fracture risk appears to be reduced for more than 1 year after a single infusion of zoledronic acid. Prospective studies designed to assess this possibility are now warranted.

55 STUDY ON THE INTERSPECIFIC NUCLEAR TRANSFER OF PRZEWALSKI'S GAZELLES AND BOVINES

Przewalski’s gazelle (Procapra przewalskii), also known as Platts antelope, is an endangered species only found in China. It belongs to the Artiodactyla order, Bovidae family, antelope subfamily, and Gazella genus. In this study, 5 experiments were designed to examine the developmental potential of Przewalski’s gazelle somatic cells transplanted into bovine enucleated oocytes. Enucleation was conducted by Hoechst 33342 staining of the oocytes and guided by a fluorescent microscope to ensure the removal of the nuclei. The gazelle cells were then transferred to the enucleated oocytes and electrically fused to reconstructed embryos. The study resulted in 5 major findings. (1) When gazelle-bovine reconstructed embryos were treated with the deacetylase inhibitor valproic acid (VPA), at different concentrations and for different times, treatment of the cloned embryos with VPA at 0.5 mM for 24 h significantly increased the 8- to 16-cell-stage embryo development [61.9% (96/155) v. 33.8% (46/136) control]. However, the morula [1.3% (2/155) v. 1.5% (2/155); P > 0.05] and blastocyst (0.7% v. 1.5%; P > 0.05) development were similar to that of the control. In the intraspecific (bovine-bovine) control group, the cleavage, morula and blastocyst development of 3 cloned embryos were 72.6% (127/175), 28.0% (49/175), and 23.4% (41/175). (2) Octamer-binding transcription factor 4 (Oct-4), as a developmental potential and expression marker, was transfected to gazelle cells. When Oct-4-eGFP-confected cells were transferred, the cloned embryo development did not improve either with or without VPA treatment. (3) When the gazelle-bovine embryos were treated with the deacetylase inhibitor trichostatin A (TSA) for 24 h at 10 ng mL–1, blastocyst development was significantly higher than in the control group [3.6% (6/168) v. 0.8% (1/125); P < 0.05]. (4) When a reverse NT protocol, in which the oocyte nucleus was removed after the cell nucleus was fused to the oocyte, was used for NT, the cloned embryo development did not improve. (5) The gazelle-bovine and bovine-bovine cloned embryos at 8- to 16-cell stages, gazelle cells, bovine cells, and bovine oocytes transcriptomes were analyzed by Affymetrix microarray (Affymetrix Microarray Inc., Santa Clara, CA, USA) and repeated twice. A total of 643 genes were activated in gazelle-cattle embryos compared with oocytes, whereas 1527 genes were activated in bovine-bovine clones. A total of 1010 genes that were exclusively expressed in gazelle somatic cells were still expressed in the interspecies cloned embryos. In conclusion, TSA treatment of Przewalski’s gazelle somatic cells transferred into enucleated bovine oocytes improved development of cloned embryos to the blastocyst stage, although still with low efficiency. Data from microarray analyses of the gazelle-cattle embryos showed that over 1000 gazelle-specific genes were still expressed in the interspecific cloned embryos. This work was supported by the National Basic Research Program of China (no. 2012CB22306).

Comparison of genomic predictions using medium-density (∼54,000) and high-density (∼777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle populations

This study investigated genomic prediction using medium-density (∼54,000; 54K) and high-density marker panels (∼777,000; 777K), based on data from Nordic Holstein and Red Dairy Cattle (RDC). The Holstein data comprised 4,539 progeny-tested bulls, and the RDC data 4,403 progeny-tested bulls. The data were divided into reference data and test data using October 1, 2001, as a cut-off date (birth date of the bulls). This resulted in about 25% genotyped bulls in the Holstein test data and 20% in the RDC test data. For each breed, 3 data sets of markers were used to predict breeding values: (1) 54K data set with missing genotypes, (2) 54K data set where missing genotypes were imputed, and (3) imputed high-density (HD) marker data set created by imputing the 54K data to the HD data based on 557 bulls genotyped using a 777K single nucleotide polymorphism chip in Holstein, and 706 bulls in RDC. Based on the 3 marker data sets, direct genomic breeding values (DGV) for protein, fertility, and udder health were predicted using a genomic BLUP model (GBLUP) and a Bayesian mixture model with 2 normal distributions. Reliability of DGV was measured as squared correlations between deregressed proofs (DRP) and DGV corrected for reliability of DRP. Unbiasedness was assessed by regression of DRP on DGV, based on the bulls in the test data sets. Averaged over the 3 traits, reliability of DGV based on the HD markers was 0.5% higher than that based on the 54K data in Holstein, and 1.0% higher than that in RDC. In addition, the HD markers led to an improvement of unbiasedness of DGV. The Bayesian mixture model led to 0.5% higher reliability than the GBLUP model in Holstein, but not in RDC. Imputing missing genotypes in the 54K marker data did not improve genomic predictions for most of the traits.

Different methods to calculate genomic predictions--comparisons of BLUP at the single nucleotide polymorphism level (SNP-BLUP), BLUP at the individual level (G-BLUP), and the one-step approach (H-BLUP)

Several strategies to use genomic data in predictions have been proposed. The aim of this study was to compare different genomic prediction methods. The response variables used in the genomic predictions were deregressed proofs, which were derived from 2 estimated breeding value (EBV) data sets. The full EBV data set from March 2010 included the EBV for production and mastitis traits for all Nordic red bulls. The reduced data set included the same animals as the full data set, but the EBV were predicted from a data set that excluded the last 5 yr of observations. Genomic predictions were obtained using different BLUP models: BLUP at the single nucleotide polymorphism level (SNP-BLUP), BLUP at the individual level (G-BLUP), and the one-step approach (H-BLUP). For the selection candidate bulls, the SNP-BLUP and G-BLUP models gave the same direct genomic breeding values (e.g., correlation of direct genomic breeding values between SNP-BLUP and G-BLUP for protein was 0.99), but slightly different from genomic EBV obtained from H-BLUP (correlations of SNP-BLUP or G-BLUP with H-BLUP were about 0.96). For all traits, SNP-BLUP and G-BLUP gave the same validation reliability, whereas H-BLUP led to slightly higher reliability. Therefore, the results support a slight advantage of using H-BLUP for genomic evaluation.

Short communication: genotype imputation within and across Nordic cattle breeds

This study investigated the accuracies of imputation from 50K genotypes to high-density genotypes for animals from the Danish, Swedish, or Finnish Red dairy cattle populations, using either a national, combined Red, or combined Red and Holstein reference population. Combining the Red populations increased the imputation accuracy for all 3 populations compared with using single-nationality references. Including Holstein animals in the reference further increased the imputation accuracy for Danish Red.

Effect of marker-data editing on the accuracy of genomic prediction

Genomic selection is a method to predict breeding values using genome-wide single-nucleotide polymorphism (SNP) markers. High-quality marker data are necessary for genomic selection. The aim of this study was to investigate the effect of marker-editing criteria on the accuracy of genomic predictions in the Nordic Holstein and Jersey populations. Data included 4429 Holstein and 1071 Jersey bulls. In total, 48,222 SNP for Holstein and 44,305 SNP for Jersey were polymorphic. The SNP data were edited based on (i) minor allele frequencies (MAF) with thresholds of no limit, 0.001, 0.01, 0.02, 0.05 and 0.10, (ii) deviations from Hardy-Weinberg proportions (HWP) with thresholds of no limit, chi-squared p-values of 0.001, 0.02, 0.05 and 0.10, and (iii) GenCall (GC) scores with thresholds of 0.15, 0.55, 0.60, 0.65 and 0.70. The marker data sets edited with different criteria were used for genomic prediction of protein yield, fertility and mastitis using a Bayesian variable selection and a GBLUP model. De-regressed EBV were used as response variables. The result showed little difference between prediction accuracies based on marker data sets edited with MAF and deviation from HWP. However, accuracy decreased with more stringent thresholds of GC score. According to the results of this study, it would be appropriate to edit data with restriction of MAF being between 0.01 and 0.02, a p-value of deviation from HWP being 0.05, and keeping all individual SNP genotypes having a GC score over 0.15.

IQGAP1 is necessary for pulmonary vascular barrier protection in murine acute lung injury and pneumonia

We recently reported that integrin α(v)β(3) is necessary for vascular barrier protection in mouse models of acute lung injury and peritonitis. Here, we used mass spectrometric sequencing of integrin complexes to isolate the novel β(3)-integrin binding partner IQGAP1. Like integrin β(3), IQGAP1 localized to the endothelial cell-cell junction after sphingosine-1-phosphate (S1P) treatment, and IQGAP1 knockdown prevented cortical actin formation and barrier enhancement in response to S1P. Furthermore, knockdown of IQGAP1 prevented localization of integrin α(v)β(3) to the cell-cell junction. Similar to β(3)-null animals, IQGAP1-null mice had increased pulmonary vascular leak compared with wild-type controls 3 days after intratracheal LPS. In an Escherichia coli pneumonia model, IQGAP1 knockout mice had increased lung weights, lung water, and lung extravascular plasma equivalents of (125)I-labeled albumin compared with wild-type controls. Taken together, these experiments indicate that IQGAP1 is necessary for S1P-mediated vascular barrier protection during acute lung injury and is required for junctional localization of the barrier-protective integrin α(v)β(3).

Post hoc analysis of a single IV infusion of zoledronic acid versus daily oral risedronate on lumbar spine bone mineral density in different subgroups with glucocorticoid-induced osteoporosis

This study summarizes the treatment effect of zoledronic acid infusion on lumbar spine bone mineral density in different subgroups with glucocorticoid-induced osteoporosis. Zoledronic acid is significantly more effective than risedronate in increasing lumbar spine (LS) bone mineral density (BMD) in both prevention and treatment of glucocorticoid-induced osteoporosis. Introduction In patients on glucocorticoids, a single zoledronic acid infusion significantly increased BMD versus daily oral risedronate. We assessed treatment effect on LS BMD in different patient subgroups at month 12 that contributed to the risk of osteoporosis in addition to glucocorticoids. Methods Patients randomized to a single IV infusion of zoledronic acid 5 mg or risedronate (5 mg/day) and stratified based on glucocorticoids duration [treatment (>3 months) and prevention (≤ 3 months) subpopulations]were subgrouped by age; gender; menopausal status in women; dose and duration of prednisone during the trial; and baseline serum 25-OH vitamin D, LS BMD T-score, creatinine clearance, and concomitant medication use. Results At month 12, zoledronic acid significantly increased LS BMD versus risedronate in patients ≤ 74 years (P<0.05) in the treatment and 65-74 years (P = 0.0008) in the prevention subpopulation. At month 12, zoledronic acid significantly increased LS BMD versus risedronate in both subpopulations irrespective of gender (all P<0.05), cumulative prednisone dose (all P<0.01), and postmenopausal status (all P<0.05). In premenopausal women, in both subpopulations, zoledronic acid significantly increased total hip BMD (all P<0.05) versus risedronate at month 12 but not LS BMD. Osteoporotic patients in the prevention (P=0.0189) and osteopenic patients in the treatment subpopulation (P=0.0305) showed significant LS BMD increases with zoledronic acid versus risedronate at month 12. Conclusions This post hoc analysis suggests that zoledronic acid is significantly more effective than risedronate in increasing LS BMD in prevention and treatment of glucocorticoid-induced osteoporosis across a wide range of patients.

Genomic prediction for Nordic Red Cattle using one-step and selection index blending

This study investigated the accuracy of direct genomic breeding values (DGV) using a genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step blending approach, and GEBV using a selection index blending approach for 15 traits of Nordic Red Cattle. The data comprised 6,631 bulls of which 4,408 bulls were genotyped using Illumina Bovine SNP50 BeadChip (Illumina, San Diego, CA). To validate reliability of genomic predictions, about 20% of the youngest genotyped bulls were taken as test data set. Deregressed proofs (DRP) were used as response variables for genomic predictions. Reliabilities of genomic predictions in the validation analyses were measured as squared correlations between DRP and genomic predictions corrected for reliability of DRP, based on the bulls in the test data sets. A set of weighting (scaling) factors was used to construct the combined relationship matrix among genotyped and nongenotyped bulls for one-step blending, and to scale DGV and its expected reliability in the selection index blending. Weighting (scaling) factors had a small influence on reliabilities of GEBV, but a large influence on the variation of GEBV. Based on the validation analyses, averaged over the 15 traits, the reliability of DGV for bulls without daughter records was 11.0 percentage points higher than the reliability of conventional pedigree index. Further gain of 0.9 percentage points was achieved by combining information from conventional pedigree index using the selection index blending, and gain of 1.3 percentage points was achieved by combining information of genotyped and nongenotyped bulls simultaneously applying the one-step blending. These results indicate that genomic selection can greatly improve the accuracy of preselection for young bulls in Nordic Red population, and the one-step blending approach is a good alternative to predict GEBV in practical genetic evaluation program.

Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data consisted of genotypes of 15,966 European Holstein bulls from the combined EuroGenomics reference population. Genotypes with the low-density chip were created by erasing markers from 50,000-marker data. The studies were performed in the Nordic countries (Denmark, Finland, and Sweden) using a BLUP model for prediction of DGV and in France using a genomic marker-assisted selection approach for prediction of GEBV. Imputation in both studies was done using a combination of the DAGPHASE 1.1 and Beagle 2.1.3 software. Traits considered were protein yield, fertility, somatic cell count, and udder depth. Imputation of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test data. Mean imputation error rates when using national reference animals was 5.5 and 3.9% in the Nordic countries and France, respectively, whereas imputation based on the EuroGenomics reference data set gave mean error rates of 4.0 and 2.1%, respectively. Prediction of GEBV based on genotypes imputed with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected in the French study, and a loss of 0.06 was observed for the mean reliability of DGV in the Nordic study. Consequently, the reliability of DGV using the imputed SNP data was 0.38 based on national reference data, and 0.48 based on EuroGenomics reference data in the Nordic validation, and the reliability of GEBV using the imputed SNP data was 0.41 based on national reference data, and 0.44 based on EuroGenomics reference data in the French validation.

Zoledronic acid results in better health-related quality of life following hip fracture: the HORIZON-Recurrent Fracture Trial

This study evaluated the benefits of ZOL versus placebo on health-related quality of life (HRQoL) among patients from HORIZON-RFT. At month 24 and end of the study visit, ZOL significantly improved patients' overall health state compared to placebo as assessed by the EQ-5D VAS.

INTRODUCTION

To evaluate the benefits of zoledronic acid (ZOL) versus placebo on health-related quality of life (HRQoL) among patients from The Health Outcomes and Reduced Incidence With Zoledronic Acid Once Yearly Recurrent Fracture Trial (HORIZON-RFT).

METHODS

In this randomized, double-blind, placebo-controlled trial, 2,127 patients were randomized to receive annual infusion of ZOL 5 mg (n = 1,065) or placebo (n = 1,062) within 90 days after surgical repair of low-trauma hip fracture. HRQoL was measured using EQ-5D Visual Analogue Scale (VAS) and utility scores (EuroQol instrument) at months 6, 12, 24, 36, and end of the study visit. Analysis of covariance model included baseline EQ-5D value, region, and treatment as explanatory variables.

RESULTS

At baseline, patients (mean age 75 years; 24% men and 76% women) were well matched between treatment groups with mean EQ-5D VAS of 65.82 in ZOL and 65.70 in placebo group. At the end of the study, mean change from baseline in EQ-5D VAS was greater for ZOL vs. placebo in all patients (7.67 ± 0.56 vs. 5.42 ± 0.56), and in subgroups of patients experiencing clinical vertebral fractures (8.86 ± 4.91 vs. -1.69 ± 3.42), non-vertebral fractures (5.03 ± 2.48 vs. -1.07 ± 2.16), and clinical fractures (5.19 ± 2.25 vs. -0.72 ± 1.82) with treatment difference significantly in favor of ZOL. EQ-5D utility scores were comparable for ZOL and placebo groups, but more patients on placebo consistently had extreme difficulty in mobility (1.74% for ZOL vs. 2.13% for placebo; p = 0.6238), self-care (4.92% vs. 6.69%; p = 0.1013), and usual activities (10.28% vs. 12.91%; p = 0.0775).

CONCLUSION

ZOL significantly improves HRQoL in patients with low-trauma hip fracture.

Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables

This study compared genomic predictions using conventional estimated breeding values (EBV) and daughter yield deviations (DYD) as response variables based on simulated data. Eight scenarios were simulated in regard to heritability (0.05 and 0.30), number of daughters per sire (30, 100, and unequal numbers with an average of 100 per sire) and numbers of genotyped sires (all or half of sires were genotyped). The simulated genome had a length of 1200 cM with 15,000 equally spaced Single-nucleotide polymorphism (SNP) markers and 500 randomly distributed Quantitative trait locus (QTL). In the simulated scenarios, the EBV approach was as effective as or slightly better than the DYD approach at predicting breeding value, dependent on simulated scenarios and statistical models. Applying a Bayesian common prior model (the same prior distribution of marker effect variance) and a linear mixed model (GBLUP), the EBV and DYD approaches provided similar genomic estimated breeding value (GEBV) reliabilities, except for scenarios with unequal numbers of daughters and half of sires without genotype, for which the EBV approach was superior to the DYD approach (by 1.2 and 2.4%). Using a Bayesian mixture prior model (mixture prior distribution of marker effect variance), the EBV approach resulted in slightly higher reliabilities of GEBV than the DYD approach (by 0.3-3.6% with an average of 1.9%), and more obvious in scenarios with low heritability, small or unequal numbers of daughters, and half of sires without genotype. Moreover, the results showed that the correlation between GEBV and conventional parent average (PA) was lower (corresponding to a relatively larger gain by including PA) when using the DYD approach than when using the EBV approach. Consequently, the two approaches led to similar reliability of an index combining GEBV and PA in most scenarios. These results indicate that EBV can be used as an alternative response variable for genomic prediction.