Bisphosphonate induced osteonecrosis of the jaw (BONJ) is a complication in patients taking bisphosphonate (BP) that affects their quality of life and compliance. In this cohort study, patients with multiple myeloma (MM) on intravenous BP therapy were enrolled over 1 year. Demographic and clinical data and genotyping of 10 single nucleotide polymorphisms (SNPs) from seven candidate genes associated with drug or bone metabolism were determined. Of the 78 patients enrolled, 12 had BONJ. The median time to developing BONJ was 28 months. Univariate and multivariate analysis revealed a significant association between BONJ and smoking ( p = 0.048) and type of BP treatment ( p = 0.03). A trend for higher odds for BONJ was found for SNPs in five genes: COL1A1 (rs1800012), RANK (rs12458117), MMP2 (rs243865), OPG (rs2073618) and OPN (rs11730582). Considering all five SNPs together, patients with genotype scores ≥5 had a BONJ event rate of 57%; those with scores <5 had a rate of 10%. The adjusted odds ratio was 11.2 (95% confidence interval of 1.8–69.9; p value 0.0097). Smoking, type of BP and combined genotype score of COL1A1 , RANK , MMP2 , OPG and OPN were significantly associated with BONJ in MM patients undergoing BP therapy.
Osteonecrosis of the jaw in patients treated with bisphosphonates (BP) was first described by M arx in 2003 . Since then, hundreds of cases of BP-induced osteonecrosis of the jaws (BONJ) have been reported, but whether BPs are causal to the development of the osteonecrosis remains to be determined. Most incidences are related to intravenous (IV) BP use in cancer patients, but several cases have also been reported in association with oral BPs .
The case reports indicate that not all BPs users develop BONJ, suggesting that environmental and/or genetic variation between individuals may confer susceptibility or resistance to developing BONJ. Only one genetic association study of BONJ has been published to date. In a genome-wide association study of 22 BONJ patients and 65 matched controls, only the cytochrome P450 2C8 gene ( CYP2C8 ) showed a significantly different distribution between cases and controls . This finding has not been replicated in an independent study. BPs are not metabolized by P450 enzymes so such an association was presumed to be through other metabolic pathways that may be affected by CYP2C8 .
In order to explore possible genetic variability as the predictive risk factor for the development of BONJ, the authors selected several genes that may impact bone turnover and remodelling. The main criteria for selecting the genes and their corresponding single nucleotide polymorphisms (SNPs) were based on the published research papers that showed significant association with osteoporosis, bone mineral density, osteonecrosis, osteoclastogenesis, bone resorption and BONJ.
The authors investigated if clinical factors as well as SNPs in several genes including CYP2C8 , COL1A1 , RANK , OPN , MMP2 , OPG and TNF are associated with the risk of developing BONJ in a group of multiple myeloma (MM) patients treated with monthly IV BP.
Consecutive patients with MM attending the multiple myeloma clinic at the University of Florida, College of Medicine, during 2008–2009 who were taking IV BP (zoledronate or pamidronate) were recruited to participate voluntarily in this Institution Review Board (IRB) approved study. These patients signed informed consent and were followed routinely in the outpatient clinic. In addition to MM treatments, patients received either pamidronate 90 mg or zoledronate 4 mg IV monthly. Demographic (age, gender, race/ethnicity) and clinical information (including the known risk factors for BONJ that were identified in the American Association of Oral and Maxillofacial Surgeons position paper 2009 update: type of BP (potency), route of administration, duration of therapy, total exposure, dental procedures and concomitant disease ) were verified from reviewing the medical records and tabled for analysis. Certain life style factors such as smoking at any time in the past, as well as certain co-morbidities such as diabetes mellitus, and concurrent drugs used were amongst the data collected on all patients.
Patients were considered to have BONJ if all of the following three characteristics were present : current or previous treatment with a BP; exposed bone in the maxillofacial region that has persisted for more than 8 weeks; and no history of radiation therapy to the jaws. During follow up, oral symptoms and complaints were documented and proper referrals were made. All BONJ cases were diagnosed in the Oral Medicine Clinic at the University of Florida. Each patient provided one blood sample for genotyping.
Gene and SNP selection
Seven candidate genes ( CYP2C8 , COL1A1 , RANK , OPN , MMP2 , OPG and TNF ) were selected based on their potential roles in osteoclastogenesis, osteoclast differentiation, and bone resorption and/or previous association with bone mineral density (BMD) or osteoporosis. COL1A1 gene is considered an important functional candidate gene for the pathogenesis of osteoporosis because the type I collagen is an important protein of bone and a mutation in this gene results in osteogenesis imperfecta, characterized by reduced BMD and increased bone fragility . Thus genetic variants of COL1A1 may play an important role in osteoporosis or osteoporotic fractures. A study showed that the G>T polymorphism of COL1A1 gene, was associated with osteoporosis . The gene for matrix metalloproteinase 2 ( MMP2 ) has been suggested as a candidate gene for the development of BONJ because BP treatment is associated with atrial fibrillation and MMP2 is the only gene known to be associated with bone abnormalities and atrial fibrillation . RANK and osteoprotegerin ( OPG ), a receptor and decoy receptor, respectively, for RANK ligand, are members of the tumour necrosis factor receptor super family that plays a central role in osteoclast development. Studies of the mouse counterpart suggest that RANK directly mediates the osteoprotegerin ligand ( OPGL )-induced osteoclastogenesis in osteoclast precursor cells. Koh et al. identified two novel SNPs (+34,863 G>A and +35,928 insertion/deletion C) in RANK that are possibly associated with low BMD in postmenopausal women . Another study by Hsu et al. showed significant positive association between BMD in men and polymorphism in exon 7 (Ala192Val) of RANK . OPG is a known regulator of bone remodelling which, together with RANK , is central to osteoclastogenesis and activation of bone resorption. Osteopontin ( OPN ), which is produced as adhesive glycophosphoprotein in different tissues such as, bone, teeth and kidney, is involved in extracellular matrix organization, bone metabolism, angiogenesis, immune regulation and is essential for osteoclast function. Two OPN promoter SNPs (rs11730582 and rs28357094) that have been shown to affect the transcription level of OPN were selected for this study .
The SNPs selected are either reported in the literature to be associated with risk for osteoporosis or bone remodelling or nonsynonymous SNPs that are considered to be functional with minor allele frequency of >5% or showed more significance than other SNPs in a study (e.g. CYP 2C8) . The 10 SNPs included in this study are: COL1A1 (rs1800012), RANK (rs12458117), CYP2C8 (rs1934980 and rs1934951, the 2 strongest SNPs from previous report), MMP2 (rs243865), OPN (rs11730582 and rs28357094), OPG (rs2073618 and rs3102735) and TNF (rs1800629).
Genomic DNA was extracted from lymphocytes in whole blood using a commercially available kit (Qiagen DNA Blood Isolation Kit, Qiagen, Valencia, CA, USA). Polymorphisms were genotyped by Taqman ® genotyping method or pyrosequencing . The Applied Biosystems 7900 HT SNP genotyping platform was used for the Taqman ® assay. The polymerase chain reaction (PCR) primers and probes for COL1A1 SNP G/T rs1800012 (ID C___7477170_30), RANK SNP A/G rs12458117 (ID C__31393804_10), CYP2C8 SNP C/T rs1934980 (ID C___361427_10), CYP2C8 SNP A/G rs1934951 (ID C___361409_1_) and MMP2 SNP C/T rs243865 (ID C_3225943_10) were purchased from Applied Biosystems (Applied Biosystems, Foster City, USA). Reactions of 5 μl each in 384-well plate were prepared and the assays were performed and analysed according to the manufacturer’s recommendations. Pyrosequencing (Biotage, Uppsala, Sweden) was performed on the rest of the SNPs using a PSQ HS96A SNP reagent kit (Biotage AB, Uppsala, Sweden) (primers available upon request). Genotype accuracy was verified by genotyping 5–10% randomly selected duplicate samples for each SNP.
Baseline characteristics were compared using Student’s t -test or the χ 2 -test as appropriate. Allele frequencies and deviations from Hardy–Weinberg equilibrium were assessed within each race group using the χ 2 -test with one degree of freedom. A dominant mode of inheritance was assumed in single SNP association analyses. The event rates were compared between carriers and non-carriers using χ 2 tests. Logistic regression was used to assess the odds ratios (OR) for BONJ, using wild-type homozygous as the reference group.
To study the potential combined effect of all five SNPs that showed a trend for statistical significance ( OPG _rs2073618, COL1A1 _rs1800012, RANK _rs12458117, MMP2 _rs243865 and OPN _rs11730582), the authors constructed genotype scores on the basis of the number of unfavourable alleles (those associated with higher risk for BONJ) that were carried by each subject for each of the five SNPs. The genotype score for each patient was calculated as the sum of genotype scores for all five SNPs, each with a possible value of 0 (homozygous for common allele), 1 (heterozygous) or 2 (homozygous for rare allele). Based on the distribution of the genotype scores, the genotype scores were dichotomized into < or ≥5 (at least one rare allele for each of the five SNPs on average). The crude incidence rates of BONJ were calculated according to strata of genotype scores of < or ≥5. The genotype scoring method has been widely used to evaluate multiple gene effects on complex diseases . In the multivariate logistic regression, covariates such as age, gender, race/ethnicity, smoking history, diabetes, type of BP treatment and number of prior treatments were included in a stepwise model selection analysis (with selection criteria of p = 0.1 for entry and p = 0.05 for staying). Only the significant risk factors for BONJ were included in the final multivariate logistic model.
Power analysis revealed that with sample size of 12 cases and 66 controls, assuming additive mode of inheritance, at alpha of 0.05, there is >80% power to detect ORs of >5 with minor allele frequency of 10% and ORs of >4 with minor allele frequency of 20%. Pharmacogenetic effect sizes tend to be much larger than ORs commonly seen in disease association studies . Thus, whilst the ORs used for these power calculations may not be realistic for disease association studies, the preliminary data, and numerous lines of evidence in other pharmacogenetic studies, suggest these are reasonable ORs for the pharmacogenetic questions being addressed. All statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC, USA). A p value of <0.05 was considered statistically significant.
78 patients with MM, including 12 BONJ patients (15%) were enrolled and their characteristics are shown in Table 1 . The age and gender of the BONJ and BP groups were similar, but there was a significant difference in race/ethnicity between BONJ and non-BONJ patients ( p = 0.045). Ten of the 12 BONJ patients (83%) were white. None of the BONJ patients was African American. In non-BONJ patients, 65% and 29% were white and African Americans, respectively. 2 of 3 Hispanic patients in this study were diagnosed with BONJ.
|BONJ § ( n = 12)||No BONJ ( n = 66)|
|Age, median (range)||57 (33–71)||59 (29–77)|
|Male gender||6 (50%)||42 (64%)|
|W||10 (83%)||43 (65%)|
|AA||0 (0%)||19 (29%)|
|H||2 (17%)||1 (2%)|
|Other||0 (0%)||2 (3%)|
|Length of BP treatment, median (range), mo||27.5 (11-93)||28.5 (5–108)|
|Smoking (ever)||9 (75%)||25 (38%)|
|Smoking at time of MM diagnosis||3 (25%)||4 (6%)|
|Smoking (pack/year), median (range)||7.5 (0-730)||0 (0–1095)|
|Chronic periodontitis||8 (67%)||43 (65%)|
|Diabetes||2 (17%)||12 (18%)|
|Thalidomide||6 (50%)||42 (64%)|
|Prednisone||2 (17%)||3 (5%)|
|Type of BP|
|P||1 (8%)||7 (11%)|
|P/Z *||2 (17%)||10 (15%)|
|Z/P *||6 (50%)||5 (8%)|
|Z||3 (25%)||44 (67%)|
The median time to developing BONJ was 28 months, but that was not different from the median length of BP treatment for the whole group. This finding confirms prior published data that BONJ usually develops after more than 2 years of BP therapy.
Of the 12 BONJ patients, the mandible was involved in 7 (58%). Only one patient had a dental procedure (extraction) prior to the onset of BONJ. All the other 11 BONJ were spontaneous. 67% of BONJ patients had adult chronic periodontitis compared with 65% in the non-BONJ group ( Table 1 ). One of the 12 BONJ patients was taking pamidronate (P), three were taking zoledronate (Z), two were taking pamidronate and then switched to zoledronate (P/Z) and six were taking zoledronate then switched to pamidronate (Z/P) ( Table 1 ).
Univariate analysis revealed a significant association between BONJ and the history of ever smoking ( p = 0.012) ( Table 2 ) and smoking at the time of MM diagnosis ( p = 0.05). Smoking of pack/year was not significantly different between BONJ and non-BONJ patients ( p = 0.21). Since the history of ever smoking was the strongest predictor amongst these three measurements of smoking status, this variable was used in the multivariate analysis. This significant association has persisted in multivariate logistic regression analysis. Patients with a smoking history had 4 times higher odds of developing BONJ than those who did not have a smoking history, adjusted OR: 4.39 and 95% confidence interval (CI) of 1.02–18.97 ( p = 0.048).
|Variables||Odds ratio||95% confidence intervals||p -Value|
|Length BP therapy||1.01||0.98–1.03||0.7|
|Race: non-white vs. white||0.37||0.08–1.85||0.23|
|Gender: F vs. M||1.75||0.51–6.03||0.38|
|Bisphosphonates: (P + Z/P) vs. (Z + P/Z)||6.3||1.71–23.28||0.0058|
|Number of prior therapies||2.29||0.97–5.41||0.06|
The authors also found that the type of BP treatment was associated with BONJ both in the univariate analysis ( p = 0.0058) ( Table 2 ) and multivariate analysis ( p = 0.03). Patients on P or Z/P (pamidronate group) had 4 times higher odds of developing BONJ compared with those on Z or P/Z (zoledronate group), with OR of 4.55 (95% CI of 1.16–17.80).
Higher percentage of BONJ patients were on prednisone than non-BONJ patients (17% vs. 5%), with a marginal p value of 0.14. There was a trend towards a significant association between the number of prior MM therapies and the occurrence of BONJ ( p = 0.06). There was no evidence that age, gender, race/ethnicity, length of BP therapy, chronic periodontitis, diabetes or use of thalidomide were associated with BONJ in the univariate analysis ( Table 2 ).
The authors genotyped 10 SNPs from 7 genes in this study. The minor allele frequencies in white and African Americans and univariate and multivariate odds ratios (after adjusting for smoking history and BP use) for BONJ are shown in Table 3 . All SNPs had frequencies of >10% in both white and African Americans. Three SNPs had significantly different allele frequencies between these two racial groups: CYP2C8 _rs1934951 ( p = 0.002), OPG _rs2073618 ( p < 0.0001) and OPN _rs11730582 ( p < 0.0001) ( Table 3 ).
|Gene symbol||Gene name||SNP||Minor allele||MAF *||Odds ratio (95% CI)||p -Value|
|CYP2C8||Cytochrome P450, family 2, subfamily C, polypeptide 8||rs1934980||G||0.16/0.24||0.73 (0.18–3.04)||0.70 (0.15–3.36)||0.66|
|CYP2C8||Cytochrome P450, family 2, subfamily C, polypeptide 8||rs1934951||T||0.16/0.39 **||0.61 (0.15–2.52)||0.68 (0.14–3.22)||0.63|
|COL1A1||Collagen, type I, alpha 1||rs1800012||C||0.11/0.06||1.91(0.43–8.49)||1.69 (0.30–9.70)||0.55|
|TNFRSF11A (RANK)||Tumour necrosis factor receptor superfamily, member 11a, NFKB activator||rs12458117||A||0.12/0.05||1.84 (0.42–8.06)||2.14 (0.39–11.71)||0.38|
|MMP2||Matrix metallopeptidase 2||rs243865||T||0.21/0.05||2.35 (0.64–8.72)||3.49 (0.75–16.18)||0.11|
|TNFRSF11B (OPG)||Tumour necrosis factor receptor superfamily, member 11b||rs2073618||C||0.48/0.13 **||2.93 (0.59–14.49)||2.16 (0.38–12.23)||0.38|
|TNFRSF11B (OPG)||Tumour necrosis factor receptor superfamily, member 11b||rs3102735||C||0.19/0.32||1.12 (0.31–4.08)||0.79 (0.19–3.34)||0.75|
|SPP1 (OPN)||Secreted phosphoprotein 1||rs11730582||G||0.49/0.03 **||3.64 (0.73–18.10)||2.97 (0.53–16.55)||0.21|
|SPP1 (OPN)||Secreted phosphoprotein 1||rs28357094||G||0.23/0.13||0.64 (0.16–2.65)||0.51 (0.10–2.59)||0.41|
|TNF||Tumour necrosis factor||rs1800629||A||0.22/0.24||0.38 (0.08–1.91)||0.68 (0.12–3.95)||0.67|