Printer Friendly

Bone health nutraceuticals alter microarray mRNA gene expression: A randomized, parallel, open-label clinical study.

ABSTRACT

Background and objective: Dietary intake of fruits and vegetables has been suggested to have a role in promoting bone health. More specifically, the polyphenols they contain have been linked to physiological effects related to bone mineral density and bone metabolism. In this research, we use standard microarray analyses of peripheral whole blood from post-menopausal women treated with two fixed combinations of plant extracts standardized to polyphenol content to identify differentially expressed genes relevant to bone health. Methods: In this 28-day open-label study, healthy post-menopausal women were randomized into three groups, each receiving one of three investigational fixed combinations of plant extracts: an anti-resorptive (AR) combination of pomegranate fruit (Punica granatum l.) and grape seed (Vitis vinifera L.) extracts; a bone formation (BF) combination of quercetin (Dimorphandra mollis Benthj and iicorice (Glycyrrhiza glabra L.) extracts; and a fixed combination of all four plant extracts (AR plus BF). Standard microarray analysis was performed on peripheral whole blood samples taken before and after each treatment. Annotated genes were analyzed for their association to bone health by comparison to a gene library.

Results: The AR combination down-regulated a number of genes involved in reduction of bone resorption including cathepsin G (CTSG) and tachykinin receptor 1 (TACR1). The AR combination also up-regulated genes associated with formation of extracellular matrix including heparan sulfate proteoglycan 2 (HSPG2) and hyaluronoglucosaminidase 1 (FIYAL1). In contrast, treatment with the BF combination resulted in upregulation of bone morphogenetic protein 2 (BMP-2) and COL1A1 (collagen type I [alpha] 1) genes which are linked to bone and collagen formation while down-regulating genes linked to osteoclastogenesis. Treatment with a combination of all four plant extracts had a distinctly different effect on gene expression than the results of the AR and BF combinations individually. These results could be due to multiple feedback systems balancing activities of osteoblasts and osteoclasts.

Conclusion: In summary, this ex-vivo microarray study indicated that the pomegranate, grape seed, quercetin and licorice combinations of plant extracts modulated gene expression for both osteoclastic and osteogenic processes.

Keywords:

Botanical extracts

Microarray analysis

Receptor activator of nuclear factor kappa-B

ligand

Bone morphogenetic protein 2

Introduction

Bone is a dynamic tissue constantly in a cycle of resorption and formation. Established bone is degraded by osteoclasts through adherence, acidification, and proteolytic digestion; then, osteoblasts build bone in the excavated sites by excreting osteoid which mineralizes to become new bone. Bone remodeling renews approximately 10% of bone each year, resulting in an entirely new skeleton roughly every 7 to 10 years (Post et al. 2010). Bone mass changes with age, peaking in adults aged 20 to 30 years and declining after age 50. The loss of bone mass associated with aging can result in an increased risk of fracture and osteoporosis (Habauzit and Horcajada 2008).

According to the National Health and Nutrition Examination Surveys. the predominate treatment for osteoporosis in the 1988-1994 survey was estrogen, while in the 2005-2006 survey it was almost exclusively bisphosphonates (Looker et al. 2010). In addition to medications, nutritional research on bone health indicates the importance of an adequate intake of dietary calcium, vitamin D, and protein. Research into the correlation between fruit and vegetable intake and bone mineral density has suggested a role for the polyphenolic compounds found in fruits and vegetables in promoting bone health (Habauzit and Horcajada 2008).

Using a targeted series of in vitro and in vivo assays, we have recently identified two botanical extract combinations which affect bone resorption or formation (Lin et al. 2014). One is an anti-resorptive combination of pomegranate fruit and grape seed extracts that was shown to maintain bone mass by preventing calcium loss through its ability to inhibit the expression of receptor activator of nuclear factor kappa-B ligand (RANKL), a cytokine of the tumor necrosis factor family involved in osteoclast differentiation. The other, a combination of quercetin and licorice extracts, was shown to maintain maximum bone mass by stimulating bone formation and enhancing calcium deposition through activation of bone morphogenetic protein 2 (BMP-2), a member of the transforming growth factor beta family known to stimulate bone production (Lin et al. 2014).

Ideally, the next step would be to evaluate the efficacy of these botanical extract combinations on bone health in a human clinical study. The most direct end-point in such clinical trials is a measurement of bone mineral density using dual-energy x-ray absorptiometry (DEXA). However, due to the slow rate of bone turnover in humans, this type of study requires a long intervention period and a large sample size. To reduce these factors, an alternate analysis would be to quantitate the effects of the botanical extract combinations on bone turnover biomarkers such as specific alkaline phosphatase, serum osteocalcin, serum C-terminal cross-linked telopeptides of type 1 collagen, and urinary osteocalcin. Quantifying these markers is safe and easy to perform compared to DEXA or other imaging techniques, however, the use of these biomarkers is not without controversy due to individual variability and the complexity of bone metabolism (Vasikaran 2008).

An alternative to both of these approaches is to use microarray technology to directly evaluate the effect of botanical extracts on molecular mechanisms affecting bone metabolism. Microarray analysis is a potentially valuable tool due to its sensitivity and the increasing ability to correlate changes in gene expression with biomarkers and functional activity. Microarray analyses of circulating monocytes (Dvornyk et al. 2007; Lei et al. 2009; Liu et al. 2005) and B cells (Xiao et al. 2008) extracted from peripheral whole blood in humans with low and high bone mass has been used to identify differentially expressed genes involved in bone metabolism. In this research, we use standard microarray analyses of peripheral whole blood, which includes monocytes and B cells, from post-menopausal women treated with our anti-resorptive and bone building botanical extract combinations, to identify differentially expressed genes relevant to bone health through comparison to a gene library.

Materials and methods

Botanical extracts and test combinations

The composition of the three investigational combinations, an anti-resorptive combination (AR), a bone formation combination (BF), and a combination of all four plant extracts (C), is described in Table 1, and the sources and specifications for the botanical extracts are provided in Table 2. All the extracts are acceptable for use in nutritional supplements in the USA where the study was completed. Botanical authentication was provided by the manufacturers for the purchased extracts, and for the licorice was verified by chain of custody from seed at the Access Business Group Farm. Dosages were determined from analysis of the previous in vitro and in vivo data (Lin et al. 2014) and was converted from rat to human body size and blood volumes using the FDA Human Equivalent Dose conversion formula. The quality and standardization of the extracts were previously described in detail in Fast et al. (2013). Briefly, all extracts except for licorice were obtained from commercial suppliers and each guaranteed for phytochemical standardization by Certificate of Analysis from the supplier. In addition, all the extracts used were analyzed quantitatively and qualitatively and verified using the appropriate analytical methods. Method details and resulting chromatograms are excerpted from Fast et al. (2013) and included in the supplemental materials (e-component).

Subjects and study design

This was a 28-day, open-label study in which 46 healthy postmenopausal women were randomized into three groups, each receiving one of three investigational combinations. All test combinations were in tablet form with microcrystalline cellulose as a carrier. The tablets were manufactured in a Good Manufacturing Practices certified facility.

The study subjects were obtained through the Southbay Pharma Research (Buena Park, CA) population pool which is approximately 40% Caucasian, 20% Hispanic, 30% Asian/Pacific Islander and 10% other ethnicities. The selected subjects were non-smoking postmenopausal (6 months to 5 years after the beginning of menopause) women aged 45 to 62 years old. All participants were required to be in good general health as assessed via interview and abbreviated physical examination. Subjects with stable medical conditions and who followed a consistent medication regimen with proper medical supervision were eligible. For the duration of the trial, participants were instructed to maintain their exercise habits and current diet, with the exception of not consuming pomegranates, foods high in quercetin (e.g., apples and onions), licorice, or supplements containing grape seed extract.

Subjects were excluded from study participation for any of the following conditions: cigarette smoker or history of tobacco use within the past year; use of dietary supplements (vitamins, minerals, and herbal formulas, including herbal drinks) within one week of the beginning of the study; the presence of osteoporosis, cancer, or other unstable health conditions: participation in another clinical trial within 30 days of enrollment into the study; history of or current drug or alcohol abuse; known allergy to the botanical test combinations; a change in hormone therapy (including oral contraceptives) within 4 weeks prior to the beginning of the study or expected change during the study; or any condition that the Principal Investigator thought would put the subject at undue risk.

This study was conducted at Southbay Pharma Research in accordance with the guidelines for current Good Clinical Practice, the Declaration of Helsinki (1996), and US Code of Federal Regulations (Title 21, Part 50 Protection of Human Subjects). All subjects provided full informed consent and the study protocol was approved by the Alpha IRB (San Clemente, CA).

On study Day 1, subjects were enrolled, interviewed as to compliance with the inclusion and exclusion criteria, and written informed consent obtained. A medical history was taken, a medical exam performed, and fasting samples (overnight or a minimum of 8 hours) of urine and blood were obtained. The subjects were randomized to the study groups, given a 2-week supply of test combinations, and instructed to take the tablets according to directions printed on the bottle. It was recommended that all tablets be taken at the same time each day, in the morning, with breakfast.

On Day 2, participants were interviewed by phone and any participants found to have abnormal serum chemistry, hematology, or urinalysis were dismissed from the study. On Day 14, study compliance was assessed at the clinic through interviews and collection of any unused tablets. Subjects were questioned about adverse events or any unusual signs or symptoms. An additional 2-week supply of tablets was dispensed. On Day 28, participants returned to the clinic for assessment of compliance, questioned regarding adverse events, and fasting samples of blood and urine were obtained. Compliance with study tablet administration was recorded as a percentage of the actual intake to total scheduled intake. Non-compliance was defined as consumption of less than 80% of scheduled intake.

Subjects were requested to report any adverse events that occurred during the course of the study. Safety and tolerability were also monitored via serum chemistry, hematology, urinalysis, and vital signs taken on study Day 1 and 28.

Microarray analysis

The effects of each fixed combination of plant extracts were determined by comparing gene expression profiling data between Day 1 (baseline) and end of treatment on Day 28. Fasting blood samples (approximately 2.5 ml) were collected in PAXgene blood RNA tubes and stored at 4[degrees]C for no longer than five days before being shipped to Ocimum Biosolutions, LLC (Houston, TX), for microarray analysis.

The blood samples were analyzed for distribution of peripheral blood mononuclear cells and samples with similar distribution curves were selected for analysis. Ten samples from each treatment group underwent microarray analysis.

Total RNA was extracted using a Qiagen RNeasy Mini Kit per manufacturer's instructions and its quality determined with an Agilent 2100 Bioanalyzer RNA 6000 Nano LabChip Kit. Microarray assessments were performed according to the Agilent One-Color Human 4 x 44 K Gene Expression Microarray protocol. Briefly, total RNA (500 ng) was amplified and labeled using the One-color Quick Amp labeling kit (Agilent Technologies, Santa Clara, CA, USA). Labeled cRNA was purified using Qiagen RNeasy spin columns and the quantity and quality of the cRNA was determined using a Nanodrop ND-1000 UV-VIS spectrophotometer. Using the Agilent Gene Expression Hybridization Kit, 1.65 [micro]g of cRNA were hybridized onto a Human 4 x 44 K Gene Expression Microarray slide, sealed in a hybridization chamber, and hybridized for 17 h, at 65[degrees]C in a rotating oven. The slides were then washed with wash buffer, scanned on an Agilent Microarray Scanner, and data extraction and analysis performed using Feature Extraction software, version 9.5.3. Functionally annotated genes (those linked to any metabolic processes) were further analyzed for their relationship to bone health by comparison with the Gene Logic BioExpress[R] gene expression database (Markowitz and Topaloglou 2001; Markowitz, et al. 2002; Scherf et al. 2000).

Statistical analysis

Quality control and statistical procedures were performed using JMP Genomics software (SAS Institute Inc., Cary, NC). The Mahalanobis distance quality control (MDQC) procedure was applied to identify outlier arrays. Following the quality assessment, the data was processed with normalization and summarization to obtain final expression values for each gene on the log2 scale. Loess normalization procedure was used to perform all these steps on probe-level data.

Statistics were calculated using one-way ANOVA followed by two-sided t-test to determine treatment effect on gene expression. Summary statistics were performed using t-tests in conjunction with log-fold change to determine differentially expressed genes. The differentially expressed genes were identified as a level of significance [alpha] = 0.5 and fold change [greater than or equal to] 1.5. Significance analysis of microarrays (SAM) was used to ensure that the false discovery rate was within 5%. Gene expression diagrams were prepared with Metacore Bioinformatics software from Thomson Reuters (https://portal.genego.com/).

Results

Study participants

Eighty-four post-menopausal women were screened, and 46 were enrolled and randomized into the three treatment groups. Of these 46 subjects, there were 7 Asians (15%), 10 African Americans (22%), 14 Caucasians (30%), and 15 Hispanics (33%). There were no significant differences between treatment groups in age, basal metabolic rate (BM1, kg/[m.sup.2]), or duration from onset of menopause (Table 3). Subjects with type 2 diabetes, hypercholesterolemia, hypertension, osteoarthritis, and rheumatoid arthritis were included in the study if they were cancer-free, in stable condition and followed a consistent medication regimen with medical supervision, distribution of these participants are listed in Table 3. Of the enrolled participants, 43 completed the study. No participants were discontinued from the study due to study treatment. The process of enrollment, intervention and sample analysis is summarized in Fig. 1.

Microarray results

Microarray analysis indicated that 267, 880, and 219 genes were up-regulated in the AR, BF, and C treatment groups, respectively. The number of down-regulated genes were 564,2049, and 1340 in treatment groups AR, BF and C, respectively. Functionally annotated genes were further analyzed for their relationship to bone metabolism.

Anti-resorptive (AR) treatment group

The effect of the AR combination on expression of select annotated genes related to bone metabolism is shown in Table 4; the fold-change from baseline for these differentially expressed genes was significant at the level of significance [alpha] = 0.05. Up-regulated genes included heparan sulfate proteoglycan 2 (HSPG2), hyaluronoglucosaminidase 1 (HYAL1) and interleukin 7 (IL-7), and down-regulated genes included interleukin 6 (1L-6), and C-reactive protein (CRP), as well as cathepsin G (CTSG), tachykinin receptor 1 (TACR1), chemokine (C-X3-C motif) ligand 1(CX3CL1), frizzled homolog 1 (FZD1), and insulin-like growth factor 2 (IGF2). The down-regulation of CTSG and TACR1 is associated with down-regulation of RANKL activity, which is implicated in bone resorption (Lin et al. 2014). A schematic summarizing the effect of the AR combination on the expression of select annotated genes following 28 days of treatment is shown in Fig. 2.

Bone formation (BF) treatment group

The effect of the bone formation combination on expression of select annotated genes associated with osteogenesis is listed in Table 5. BMP-2, the biomarker used in our previous in vitro screening assay (4), was significantly up-regulated by this combination as were collagen type I [alpha]l (COL1 Al), artemin (ARTN), neuromedin B (NMB), syndecan 1 (SDC1), and cystatin SA (CST2). Similar to the effects seen with the AR combination, IL-6 was also down-regulated. Other genes important for enhancing osteoclastogenesis, CD200 receptor 1 (CD200), activin A receptor type 1IB (ACVR2B), toll-like receptor 4 (TLR4), and cathepsin O (CTSO) were also down-regulated following 28 day supplementation with the BF combination. Fig. 3 is a schematic representation of the change in expression of select annotated genes following administration of the BF combination for 28 days.

Combination (C) of all four botanical extracts treatment group

The effect on gene expression of all four botanical extracts combined is listed in Table 6. This combinaton was shown to up-regulate fibroblast growth factor 9 (FGF9), a secreted growth factor known to have a critical role in angiogenesis and osteogenesis, and runt-related transcription factor 2 (RUNX2), a transcription factor involved in osteoblast differentiation and maturation. The combination all four plant extracts (AR + BF) down-regulated mediators of osteoclastogenesis such as transforming growth factor alpha (TGF[alpha]) and chemokine (C-X-C motif) ligand 10 (CXCL10) as well as chemokine (C-X-C motif) ligand 1 (CXCL1), a mediator of inflammation. Other select annotated genes down-regulated following 28 day supplementation with the combination of all four extracts (AR + BF) were TNF receptor superfamily member 6, FAS ligand (FASLG), and interleukin 1 receptor accessory protein (IL1RAP). The results for the combination treatment group did not show an increase in BMP-2 gene expression despite an increase following treatment with the BF combination alone, nor a decrease in CTSG and TACR1 gene expression as found in the treatment with AR combination alone. Fig. 4 is a schematic representation of the change in expression of select annotated genes following administration of the C combination of all four plant extracts for 28 days.

Safety and tolerability of the botanical extract combinations

No serious adverse events were reported for subjects in any of the treatment groups. Nine of the 43 participants had biochemical test results outside normal range on day 28 (Table 7). Six of these showed blood glucose levels above normal range; two had previously diagnosed type 2 diabetes, and four were in the BF treatment group. None of the abnormal test results were determined by study physician to be due to study treatment. Overall, all three fixed combinations of botanical extracts were considered safe and well-tolerated throughout the study period.

Discussion

Molecular genetic studies have linked a number of genes to osteogenesis and osteoporosis in human populations, laying a foundation for our understanding of the mechanisms of gene expression underlying bone health. The most widely studied of these genes are the vitamin D receptor, estrogen receptor, and LDL receptor-related protein 5. However, many other genes have also been identified as links to bone health including genes for calciotropic hormones, cytokines, growth factors, and bone matrix proteins (Markowitz et al. 2002). Recent microarray studies involving osteoporosis and related traits have focused on regulation of osteoblast and osteoclast activity; differentiation of mesenchymal stem cells; comparison of healthy and diseased tissues; the effects of therapeutic agents, and endocrine regulation (Xu et al. 2010).

In this study, we examined the effect of two botanical extract combinations, separately and in combination, on gene expression in an ex-vivo microarray analysis of mRNA obtained from whole blood samples of post-menopausal women treated for 28 days. The preparation and analysis include the monocytes and B cells which have been shown to reflect influence on bone tissue. The botanical extract combinations were previously identified through in vitro assays for their effects on RANKL or BMP-2 expression, and further tested by functional studies in calvarial tissues and animal models (Lin et al. 2014), providing a link between gene expression and functionality. In this research, we identify differentially expressed genes linked to functional activities related to bone metabolism.

The interaction between receptor activator of nuclear factor kappa-B (RANK) and RANKL leads to the proliferation and activation of osteoclasts. Therefore, the RANK-RANKL pathway for induction of bone resorption is a recognized target for therapeutic agents in the treatment of osteoporosis (Deschaseaux et al. 2009; Teletchea et al. 2014). The pomegranate and grape seed extracts in the AR combination inhibited RANKL expression in vitro (Lin et al. 2014) but no direct change in RANKL expression was measured in this ex-vivo study. However, the microarray analysis did demonstrate that CTSG and TACR1 were down-regulated in the AR treatment group, a process thought to inhibit osteolysis by reducing RANKL production (Kojima et al. 2006; Matayoshi et al. 2005; Steinhoff et al. 2014; Wang et al. 2009; Wilson et al. 2008).

Genes up-regulated in the AR treatment group included HSPG2 and HYAL1, proteins involved in extracellular matrix generation and remodeling (Xu et al. 2010), and IL-7, a direct inhibitor of osteoclastogenesis (Gendron et al. 2008). Besides CTSG and TACR1, other genes down-regulated in the AR treatment group included CX3CL1, FZD1 and IGF2, associated proteins known to play a role in enhancing osteoclastogenesis (Xu et al. 2010), and IL-6 and CRP, mediators associated with inflammation (McLean 2009). IL-6 induces osteoclastic precursor cell proliferation, and its inhibition is a suggested target for the treatment of osteoporosis (Terpos et al. 2011). Increased levels of CRP, a general inflammation biomarker, are associated with a number of disease conditions, but its role in osteoporosis is not clear. A cohort study with a follow-up period of 6 years reported that low CRP levels were associated with reduced risk of osteoporotic fracture in elderly Asian women (Nakamura et al. 2011). However, a population based study conducted in Iran concluded that subclinical systemic inflammation may not be involved in loss of bone mass in healthy postmenopausal women (Nabipour et al. 2009).

Botanical extracts (quercetin and licorice extract) in the BF combination were previously shown to increase expression of BMP-2 mRNA and protein, and to promote bone growth in cultured mouse calvariae (Lin et al. 2014), BMP-2 gene expression was up-regulated in this ex vivo human study following treatment with the BF combination. BMP-2 and BMP-4, members of the transforming growth factor [beta] family, have been established as crucial for the progression and maturation of osteogenesis (Deschaseaux et al. 2009). Recombinant human BMP-2 has found clinical use in the treatment of fractures that do not heal as expected (Garrison et al. 2010).

Microarray analyses of blood samples from the BF treatment group also show an increase in COL1A1 gene expression. Collagen type 1 is the most abundant protein in connective tissue and is essential for normal bone function (Xu et al. 2010). The up-regulation of COL1A1 indicates that collagen synthesis may be stimulated following treatment with the BF combination. Other genes associated with osteoblastic and chondrocytic activities were also up-regulated including ARTN, NMB, SDC1, and CST2. Similar to treatment with the AR combination, IL-6 was down-regulated in the BF treatment group indicating a reduction in osteoclastic precursor cell proliferation. Other genes important for enhancing osteodastogenesis including CD200, ACVR2B, TLR4, and CTSO were also down-regulated in the BF treatment group.

Treatment with the combination of all four plant extracts, the C treatment, increased expression of RUNX2, considered one of the 'master genes' for bone formation (Deschaseaux et al. 2009). FGF9 was also up-regulated by the combination of all four plant extracts suggesting an increase in osteoblast proliferation and bone formation (Behr et al. 2010). Genes that were down-regulated in the C treatment group included TGF[alpha], a known stimulator of osteoclastic bone resorption working with RANKL in the early stage of osteoclast differentiation (Fox et al. 2008); CXCL10, known to have a pathogenic role in bone destruction and osteodastogenesis possibly by mediating increases in RANKL expression (Lee et al. 2011); and CXCL1, known to initiate migration of osteoclasts (Xu et al. 2010). Interestingly, while both the AR and BF supplemental treatments suppressed inflammatory markers, there were no effects on these markers with the combined treatment.

These results demonstrate that the two botanical extract combinations developed through a targeted series of in vitro and in vivo assays (Lin et al. 2014) caused changes in gene expression indicating that osteoclastic and osteogenic processes were modulated with both. The anti-resorptive combination of pomegranate and grape seed extracts caused differential expression of select annotated genes related to the reduction of bone resorption through the inhibition of proliferation and activation of osteoclasts possibly through the inhibition of the RANK-RANKL pathway. The bone formation combination of quercetin and licorice extracts demonstrated a series of differentially expressed genes known to reduce osteoclast activity and increase osteoblastic activity in part through the stimulation of the BMP-2 pathway. The combination of all four plant extracts demonstrates that modulating both bone resorption and bone formation simultaneously is difficult, possibly due to multiple feedback systems balancing the osteoblast and osteoclast activity. In summary, this ex-vivo microarray study indicates that the two botanical extract combinations modulate gene expression for both osteoclastic and osteogenic processes. Further work is warranted to confirm these results and to investigate the effect of the botanical extracts on the differentially expressed genes and their functional relationship to bone metabolism.

ARTICLE INFO

Article history:

Received 26 February 2015

Revised 11 November 2015

Accepted 12 November 2015

Conflicts of interest

Authors Kevin W. Gellenbeck, David Fast, Valentina Kazlova, Mary A. Murray, and Amit Chandra are employed by Access Business Group, LLC which funded this research. Yumei Lin and Shyam Ramakrishnan were employed by Access Business Group LLC while this work was completed. United States and world patent applications have been filed for this work.

Financial support

This work was funded by Access Business Group, LLC. Employees of Access Business Group LLC had a role in the design of the experiment and the interpretation of the data.

Acknowledgments

The authors would like to thank Stephen Cosio for his technical support with sample preparation.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.phymed.2015.11.011.

References

Behr, B., Leucht, P., Longaker, M.T., Quarto, N., 2010. Fgf-9 is required for angiogenesis and osteogenesis in long bone repair. Proc. Natl. Acad. Sci. USA 107, 11853-11858.

Deschaseaux, F., Sensebe, L., Heymann, D., 2009. Mechanisms of bone repair and regeneration. Trends Mol. Med. 15, 417-429.

Dvornyk, V., Liu, Y., Lu, Y., Shen, H., Lappe, J.M., Lei, S., Recker, R.R., Deng, H., 2007. Effect of menopause on gene expression profiles of circulating monocytes: a pilot in vivo microarray study. J. Genet. Genomics 34, 974-983.

Fast, D., Chandra, A., Lin, Y., Murray, M.A., Gellenbeck, K., 2013. Novel approach for screening natural plant ingredients for development of nutraceutical bone health supplements, in: Carkeet, C., Grann, K., Randolph, R.K., Venzon, D.S., Izzy, S.M. (Eds.), Phytochemicals: Health Promotion and Therapeutic Potential. CRC Press, Boca Raton, FL, pp. 73-93.

Fox, S.W., Evans, K.E., Lovibond, A.C., 2008. Transforming growth factor-beta enables NFATcl expression during osteodastogenesis. Biochem. Biophys. Res. Commun. 366, 123-128.

Garrison K.R., Shemilt I., Donell S., Ryder J.J., Mugford M., Harvey L, Song F., Alt V., 2010. Bone morphogenetic protein (BMP) for fracture healing in adults. Cochrane Database Syst. Rev. CD006950, http://onlinelibrary.wiley.com/doi/10. 1002/14651858.CD006950.pub2/abstract

Gendron, S., Boisvert, M., Chetoui, N., Aoudjit, F., 2008. Alphalbetal integrin and interleukin-7 receptor up-regulate the expression of RANKL in human T cells and enhance their osteoclastogenic function. Immunology 125, 359-369.

Habauzit, V., Horcajada, M.N., 2008. Phenolic phytochemicals and bone. Phytochem. Rev. 7, 313-344.

Kojima, T., Yamaguchi, M., Kasai, K., 2006. Substance P stimulates release of RANKL via COX-2 expression in human dental pulp cells. Inflamm. Res. 55, 78-84.

Lee, E.Y., Seo, M., Juhnn, Y.S., Kim, J.Y., Hong, Y.J., Lee, Y.J., Lee, E.B., Song, Y.W., 2011. Potential role and mechanism of IFN-gamma inducible protein-10 on receptor activator of nuclear factor kappa-B ligand (RANKL) expression in rheumatoid arthritis. Arthritis Res.Ther. 13, R104.

Lei, S.F., Wu, S., Li, L.M., Deng, F.Y., Xiao, S.M., Jiang, C., Chen, Y., Jiang, H., Yang. F., Tan, L.J., Sun, X., Zhu, X.Z., Liu, M.Y., Liu, Y.Z., Chen, X.D., Deng, H.W., 2009. An in vivo genome wide gene expression study of circulating monocytes suggested GBP1, STAT1 and CXCL10 as novel risk genes for the differentiation of peak bone mass. Bone 44, 1010-1014.

Lin, Y., Murray, M.A., Garrett, R.I., Gutierrez, G.E., Nyman, J.S., Mundy, G., Fast, D., Gellenbeck, K.W., Chandra, A., Ramakrishnan, S., 2014. A targeted approach for evaluating preclinical activity of botanical extracts for support of bone health. J. Nutri. Sci. 3 (e13), 1-11.

Liu, Y.Z., Dvornyk, V., Lu, Y, Shen, H., Lappe, J.M., Recker, R.R., Deng, H.W., 2005. A novel pathophysiological mechanism for osteoporosis suggested by an in vivo gene expression study of circulating monocytes. J. Biol. Chem. 280, 29011-29016.

Looker, A.C., Melton, L.J., Harris, T.B., Borrud, L.G., Shepherd, J.A., 2010. Prevalence and trends in low femur bone density among older US adults: NHANES 2005-2006 compared with NHANES III. J. Bone Miner. Res. 25, 64-71.

Markowitz, V.M., Chen, 1-M., Kosky, A., 2002. Gene expression data management: a case study, in: Advances in database technology. EDBT, pp. 722-731.

Markowitz, V.M., Topaloglou, T., 2001. Applying data warehouse concepts to gene expression data management, in: Proceedings of the IEEE 2nd International Symposium on Bioinformatics and Bioengineering Conference, 4-6 Nov 2001.

Matayoshi, T., Goto, T., Fukuhara, E., Takano, H., Kobayashi, S., Takahashi, T., 2005. Neuropeptide substance P stimulates the formation of osteoclasts via synovial fibroblastic cells. Biochem. Biophys. Res. Commun. 327, 756-764.

McLean. R.R., 2009. Proinflammatory cytokines and osteoporosis. Curr. Osteoporos. Rep. 7, 134-139.

Nabipour, I., Larijani, B., Vahdat, K., Assadi, M., Jafari, S.M., Ahmadi, E., Movahed, A., Moradhaseli, F., Sanjdideh, Z., Obeidi, N., Amiri, Z., 2009. Relationships among serum receptor of nuclear factor-kappaB ligand, osteoprotegerin, high-sensitivity C-reactive protein, and bone mineral density in postmenopausal women: osteoimmunity versus osteoinflammatory. Menopause 16, 950-955.

Nakamura. K., Saito, T., Kobayashi, R., Oshiki, R., Oyama, M., Nishiwaki, T., Nashimoto, M., Tsuchiya, Y., 2011. C-reactive protein predicts incident fracture in community-dwelling elderly Japanese women: the Muramatsu study. Osteoporos. Int. 22, 2145-2150.

Post, T.M., Cremers, S.C., Kerbusch, T., Danhof, M., 2010. Bone physiology, disease and treatment: towards disease system analysis in osteoporosis. Clin. Pharmacokinet. 49, 89-118.

Scherf U., Ross D., Waltham M.. Smith L.H., Lee J.K., Tanabe L., Kohn K.W., Reinhold W.C., Myers T.G., Andrews D.T., Scudiero D.A., Eisen M.B., Sausville E.A., Pommier Y., Botstein D., Brown P.O., Weinstein J.N., 2000. A gene expression database for the molecular pharmacology of cancer, Nature Genet. 24, 236-244.

Steinhoff, M.S., von Mentzer, B., Geppetti, P., Pothoulakis, C., Bunnett, N.W., 2014. Tachykinins and their receptors: contributions to physiological control and the mechanisms of disease. Physiol. Rev. 94, 265-301.

Teletchea, S., Stresing, V., Hervouet, S., Baud'huin, M., Heymann, M.F., Bertho, G., Charrier, C., Ando, K., Heymann, D., 2014. Novel RANK antagonists for the treatment of bone-resorptive disease: theoretical predictions and experimental validation. J. Bone Miner. Res. 29, 1466-1477.

Terpos, E., Fragiadaki, K., Konsta, M., Bratengeier, C., Papatheodorou, A., Sfikakis, P.P., 2011. Early effects of IL-6 receptor inhibition on bone homeostasis: a pilot study in women with rheumatoid arthritis. Clin. Exp. Rheumatol. 29, 921-925.

Vasikaran, S.D., 2008. Utility of biochemical markers of bone turnover and bone mineral density in management of osteoporosis. Crit. Rev. Clin. Lab. Sci. 45, 221-258.

Wang, L., Zhao, R., Shi, X., Wei, T., Halloran, B.P., Clark, D.J., Jacobs, C.R., Kingery, W.S., 2009. Substance P stimulates bone marrow stromal cell osteogenic activity, osteoclast differentiation, and resorption activity in vitro. Bone 45, 309-320.

Wilson, T.J., Nannuru, K.C., Futakuchi, M., Sadanandam, A., Singh, R.K., 2008. Cathepsin G enhances mammary tumor-induced osteolysis by generating soluble receptor activator of nuclear factor-kappaB ligand. Cancer Res 68, 5803-5811.

Xiao, P., Chen, Y., Jiang, H., Liu, Y.Z., Pan, F., Yang, T.L., Tang, Z.H., Larsen, J.A., Lappe. J.M., Recker, R.R., Deng, H.W., 2008. In vivo genome-wide expression study on human circulating B cells suggests a novel ESR1 and MAPK3 network for postmenopausal osteoporosis. J. Bone Miner. Res. 23, 644-654.

Xu, X.H., Dong, S.S., Guo, Y., Yang, T.L., Lei, S.F., Papasian, C.J., Zhao, M., Deng, H.W., 2010. Molecular genetic studies of gene identification for osteoporosis: the 2009 update. Endocr. Rev. 31, 447-505.

Yumei Lin (a,d), Valentina Kazlova (a), Shyam Ramakrishnan (a,c), Mary A. Murray (a), David Fast (b), Amitabh Chandra (b), Kevin W. Gellenbeck (a), *

(a) Nutrilite Health Institute, Amway R&D, 5600 Beach Boulevard, Buena Park, CA 90622, United States

(b) Access Business Croup, 7575 East Fulton Avenue, Ada, MI 49355, United States

(c) The Himalaya Drug Company, Makali, Tumkur Road, Bangalore 562123, India

(d) Yumei Consulting, Inc, P.O. Box 821, Huntington Beach, CA 92648, United States

E-mail address: kevin.gellenbeck@amway.com (K.W. Gellenbeck).

* Authorship: Yumei Lin. Valentina Kazlova, Shyam Ramakrishnan, Mary A. Murray, David Fast, Kevin W. Gellenbeck, and Amit Chandra were all involved in the study design, research; data analysis, and preparation of the report. Yumei Lin had primary responsibility for the final content. All authors read and approved the final manuscript.

Abbreviations: A, osteoarthritis; AR, anti-resorptive fixed combinations of plant extracts; BF, bone formation fixed combinations of plant extracts; BMI, body mass index; BMP-2, bone morphogenetic protein 2; C, combination of all four plant extracts; DEXA, dual-energy x-ray absorptiometry; DM, diabetes miletus type 2; ETOH, ethanol; HC, hypercholesterolemia; HT, hypertension; RANKL, receptor activator of nuclear factor kappa-B ligand.

* Corresponding author. Tel.: +1 714 562-4875; fax: +1 714 736 7605.

http://dx.doi.org/10.1016/j.phymed.2015.11.011

Table 1
Tablet dose of botanical extract combinations for each treatment
group.

Group                  Total daily dose

Anti-Resorptive (AR)   500 mg ellagic acid (from 1250 mg pomegranate)
                       and 50 mg total polyphenol (from 125 mg
                       grape seed extract) in 3 tablets.

Bone Formation (BF)    215 mg quercetin (from 250 mg quercetin
                       extract) and 0.0625 mg glabridin (from 125
                       mg licorice extract) in 2 tablets.

Combination (C)        500 mg ellagic acid (from 1250 mg pomegranate)
                       and 50 mg total polyphenol (from 125 mg
                       grape seed extract) and 215 mg quercetin
                       (from 250 mg quercetin extract) and 0.0625
                       mg glabridin (from 125 mg licorice extract)
                       in 4 tablets.

Table 2
Botanical extract preparations.

Common name   Manufacturer      Genus/Species           Plant part

Pomegranate   Polinat           Punica granatum L.      Dry fruit
                                (Lythraceae)

Grape         Polyphenolics     Vitis vinifera L.       Dry seed
                                (Vitaceae)

Fava d'anta   PVP Sociedade     Dimorphandra mollis     Dry fruit
              Anonima           Benth. (Leguminosae)

Licorice      Access Business   Glycyrrhiza glabra L.   Dry rhizome
              Group             (Leguminosae)

                                  Drug Extract
Common name   Standardization *   Ratio/Solvent      Excipient

Pomegranate   40% ellagic acid    40:1/70% ethanol   None

Grape         40% total           40:1 /water        50% maltodextrin
              polyphenols

Fava d'anta   86% quercetin       15:l/ethanol       None

Licorice      0.05% glabridin     6:1/70% ethanol    25% maltodextrin

* Minimum specifications.

Table 3

Subject characteristics.

Group   n    Age          Years from   BMI
                          onset of
                          menopause

             Mean   SD    Mean   SD    Mean   SD

AR      15   52.0   3.7   2.2    1.3   27.1   5.6
BF      15   52.8   5.8   3.3    1.3   30.8   7.5
C       16   55.6   6.0   2.8    1.4   31.2   8.0

Group   Number of subjects with specific
        medical conditions

        DM   HC   HT   A

AR      2    1    3    1
BF      2    1    4    1
C       1    3    5    3

BMI, body mass index; DM, diabetes miletus type 2; HC,
hypercholesterolemia; HT, hypertension; A, osteoarthritis; AR,
anti-resorptive combination; BF, bone formation combination; C,
all four fixed combinations of plant extracts (AR + BF).

Table 4
The effect of the anti-resorptive combination on change of expression
of select annotated genes as measured by microarray.

Gene     Gene names, alternative abbreviations    Fold       Direction
symbol                                            change *

1L-6     Interleukin 6 (interferon, beta 2)       1.66       down

CRP      C-reactive protein, pentraxin-related    1.53       down

IL-7     Interleukin 7                            1.67       up

CX3CL1   Chemokine (C-X3-C motif) ligand 1        2.27       down

1GF2     Insulin-like growth factor 2             2.02       down
         (somatomedin A)

FZD1     Frizzled homolog 1 (Drosophila)          2.12       down

TACR1    Tachykinin receptor 1, substance P       2.37       down
         receptor

CTSG     Cathepsin G                              2.11       down

CD80     CD80 molecule                            1.86       down

CD86     CD86 molecule                            2.27       down

HYAL1    Hyaluronoglucosaminidase 1               1.5        up

HSPG2    Heparan sulfate proteoglycan 2           1.51       up
         (Perlecan)

TNR      Tenascin R (restrictin, janusin)         1.53       up

SPON1    Spondin 1, R-spondinl extracellular      1.88       up
         matrix protein

* Fold-change from baseline was significant at p < 0.05.

Table 5
The effect of the bone forming combination on change of expression of
select genes as measured by microarray.

Gene     Gene names, alternative abbreviations    Fold       Direction
symbol                                            change *

IL1R1    Interleukin 1 receptor, type I           1.75       Down

IL-6     Interleukin 6 (interferon, beta 2)       1.66       Down

1L-8     Interleukin 8                            1.72       Down

CD200    CD200 receptor 1                         2.29       Down

ACVR2B   Activin A receptor, type IIB, ActRIIB    2.67       Down

CTSO     Cathepsin 0                              2.13       Down

TLR4     Toll-like receptor 4                     2.16       Down

CMTM6    CKLF-like MARVEL transmembrane domain    2.07       Down
         containing 6

AMH      Anti-Mullerian hormone                   2.49       Up

SDC1     Syndecan 1                               1.62       Up

AVP      Arginine vasopressin (Neurophysin-II,    2.47       Up
         antidiuretic hormone, diabetes
         insipidus, neurohypophyseal)

CST2     Cystatin SA                              2.06       Up

NMB      Neuromedin B                             1.58       Up

BMP-2    Bone morphogenetic protein 2, BMP2       3.23       Up

COL1A1   Collagen type 1 [alpha] 1                2.24       Up

COL5A1   Collagen type V [alpha] 1                1.76       Up

TNXB     Tenascin XB, tenascin-X                  2          up

THBS4    Thrombospondin 4                         1.97       up

COL4A2   Collagen type IV [alpha] 2               1.84       Up

COL9A1   Collagen type IX [alpha] 1               1.58       Up

ARTN     Artemin                                  3.11       Up

* Fold-change from baseline was significant at p < 0.05.

Table 6
The effect of a combination of all four plant extracts (AR + BF) on
change of expression of select genes as measured by microarray.

Gene     Gene names, alternative abbreviations    Fold       Direction
symbol                                            change *

CXCL1    Chemokine (C-X-C motif) ligand 1         1.65       Down
         (melanoma growth stimulating
         activity, alpha)

TCFo-    Transforming growth factor, alpha.       1.73       Down
         TGF-alpha

CXCL10   Chemokine (C-X-C motif) ligand 10,       1.57       Down
         IP10

FASLG    Fas ligand (TNF superfamily, member      1.61       Down
         6), FasL(TNFSF6)

1L1RAP   Interleukin 1 receptor accessory         1.85       Down
         protein

RUNX2    Runt-related transcription factor 2      1.7        Up

FGF9     Fibroblast growth factor 9               1.69       Up
         (glia-activating factor)

* Fold-change from baseline was significant at p < 0.05.

Table 7
Summary of adverse events.

Adverse event                        Treatment   Known medical
                                     group       condition(s)

Glucose, AST, ATL value above        AR          Depression,
normal range                                     hepatitis C

Glucose value above normal range.    AR          Diabetes type 2
C02 value below normal range

Glucose value above normal range     BF          Hypertension,
                                                 osteoarthritis

Glucose value above normal range     BF          --

Glucose value above normal range     BF          --

WBC and platelet count below         BF          --
normal range

Glucose value above normal range     BF          Diabetes type 2

Albumin value below normal range     C           Osteoarthritis

WBC count above normal range         C           --

Adverse events are those reported on study day 28; AST, aspartate
aminotransferase; ATL, alanine aminotransferase; WBC, white blood
cell; AR, anti-resorptive combination; BF, bone formation
combination; C, combination of all four plant extracts (AR + BF).
COPYRIGHT 2016 Urban & Fischer Verlag
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Lin, Yumei; Kazlova, Valentina; Ramakrishnana, Shyam; Murray, Mary A.; Fast, David; Chandra, Amitabh
Publication:Phytomedicine: International Journal of Phytotherapy & Phytopharmacology
Article Type:Report
Geographic Code:1USA
Date:Jan 15, 2016
Words:6511
Previous Article:Vitexin reduces neutrophil migration to inflammatory focus by down-regulating pro-inflammatory mediators via inhibition of p38, ERK1/2 and JNK...
Next Article:Biological activities of polyphenols-enriched propolis from Argentina arid regions.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |