Pharmacogenetics of osteoporosis

Influence of the Osteogenomic Profile in Response to Alendronate Therapy in Postmenopausal Women with Osteoporosis: A Retrospective Cohort Study

BACKGROUND

Postmenopausal osteoporosis is a multifactorial disease. Genetic factors play an essential role in contributing to bone mineral density (BMD) variability, which ranges from 60 to 85%. Alendronate is used as the first line of pharmacological treatment for osteoporosis; however, some patients do not respond adequately to therapy with alendronate.

AIM

The aim of this work was to investigate the influence of combinations of potential risk alleles (genetic profiles) associated with response to anti-osteoporotic treatment in postmenopausal women with primary osteoporosis.

METHODS

A total of 82 postmenopausal women with primary osteoporosis receiving alendronate (70 mg administered orally per week) for one year were observed. The bone mineral density (BMD; g/cm2) of the femoral neck and lumbar spine was measured. According to BMD change, patients were divided into two groups: responders and non-responders to alendronate therapy. Polymorphic variants in CYP19, ESR1, IL-6, PTHR1, TGFβ, OPG and RANKL genes were determined and profiles were generated from the combination of risk alleles.

RESULTS

A total of 56 subjects were responders to alendronate and 26 subjects were non-responders. Carriers of the G-C-G-C profile (constructed from rs700518, rs1800795, rs2073618 and rs3102735) were predisposed to response to alendronate treatment (p = 0.001).

CONCLUSIONS

Our findings highlight the importance of the identified profiles for the pharmacogenetics of alendronate therapy in osteoporosis.

Beyond aspirin-cancer prevention with statins, metformin and bisphosphonates

Cancer risk reduction using pharmacological means is an attractive modern preventive approach that supplements the classical behavioural prevention recommendations. Medications that are commonly used by large populations to treat a variety of common, non-cancer-related, medical situations are an attractive candidate pool. This Review discusses three pharmacological agents with the most evidence for their potential as cancer chemopreventive agents: anti-hypercholesterolaemia medications (statins), an antidiabetic agent (metformin) and antiosteoporosis drugs (bisphosphonates). Data are accumulating to support a significant negative association of certain statins with cancer occurrence or survival in several major tumour sites (mostly gastrointestinal tumours and breast cancer), with an augmented combined effect with aspirin or other non-steroidal anti-inflammatory drugs. Metformin, but not other hypoglycaemic drugs, also seems to have some antitumour growth activity, but the amount of evidence in human studies, mainly in breast cancer, is still limited. Experimental and observational data have identified bisphosphonates as a pharmacological group that could have significant impact on incidence and mortality of more than one subsite of malignancy. At the current level of evidence these potential chemopreventive drugs should be considered in high-risk situations or using the personalized approach of maximizing individual benefits and minimizing the potential for adverse effects with the aid of pharmacogenetic indicators.

The influence of the genetic and non-genetic factors on bone mineral density and osteoporotic fractures in Chinese women

To investigate the effects of genetic and non-genetic factors on bone mineral densities (BMDs) and osteoporotic fractures. This was a cross-sectional study to investigate the relationships between 18 SNPs and non-genetic factors with BMDs and osteoporotic fractures in 1012 Chinese Han women. Five SNPs in genes GPR177, CTNNB1, MEF2C, SOX6, and TNFRSF11B were associated with L1-4 or total hip BMDs. rs11898505 in SPTBN1 gene was associated with osteoporotic fractures. Subjects carrying the largest number of risk alleles (highest 10 %) not only had lower BMD values as compared to those carrying the least number of risk alleles (lowest 10 %), they also had a higher risk of fracture [P = 0.002, OR = 2.252, 95 %CI (1.136, 4.463)]. Results from multivariate stepwise regression analysis revealed that age [P < 0.001, OR = 1.038, 95 % CI (1.018, 1.058)], number of falls in a year [P < 0.001, OR = 2.347, 95 % CI (1.459, 3.774)], the G risk allele in rs11898505 [P = 0.023, OR = 1.559, 95 % CI (1.062, 2.290)], and the L1-4 BMD [P = 0.017, OR = 0.286, 95 % CI (0.102, 0.798)] were associated with the occurrence of osteoporotic fractures. Genetic (rs11898505) and non-genetic factors (age, number of falls in a year and L1-4 BMD) could work in concert to contribute to the risk of osteoporotic fractures.

A Bayesian path analysis to estimate causal effects of bazedoxifene acetate on incidence of vertebral fractures, either directly or through non-linear changes in bone mass density

BACKGROUND/AIMS

Bone mass density values have been related with risk of vertebral fractures in post-menopausal women. However, bone mass density is not perfectly accurate in predicting risk of fracture, which decreases its usefulness as a surrogate in clinical trials. We propose a modeling framework with three interconnected parts to improve the evaluation of bone mass density accuracy in forecasting fractures after treatment.

METHODS

The modeling framework includes: (1) a piecewise regression to describe non-linear temporal BMD changes more accurately than crude percent changes, (2) a structural equation model to analyze interdependencies among vertebral fractures and their potential risk factors in preference to regression techniques that consider only directional associations, and (3) a counterfactual causal interpretation of the direct and indirect relationships between treatment and occurrence of vertebral fractures. We apply the methods to BMD repeated measurements from a study of the effect of bazedoxifene acetate on incident vertebral fractures in three different geographical regions.

RESULTS

We made four observations: (1) bone mass density changes varied largely across participants, (2) baseline age and body mass index influenced baseline bone mass density that, in turn, had an effect on prevalent fractures, (3) direct and/or indirect effects of bazedoxifene acetate on incident fractures were different across regions, and (4) estimates of indirect effects were sensible to the presence of post-treatment unmeasured confounders. In one region, around 40% of the bazedoxifene acetate effect on the occurrence of fracture is explained by its effect on bone mass density. Under the counterfactual approach, these 40% represent the average difference in the occurrence of fracture observed for untreated individuals when their bone mass density values are set at the value under bazedoxifene acetate versus under placebo.

CONCLUSIONS

Computational methods are available to evaluate and interpret the surrogacytic capability of a biomarker of a primary outcome.