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Jul 11, 2012 - Osteoarthritis (OA) is a highly prevalent joint disease. Its slow progressive nature and the correlation between pathological changes a...
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H NMR Spectroscopy of Serum Reveals Unique Metabolic Fingerprints Associated with Subtypes of Surgically Induced Osteoarthritis in Sheep

Anthony D. Maher,*,† Chantal Coles,†,‡ Jason White,‡,⊥ John F. Bateman,‡ Emily S. Fuller,§ Dan Burkhardt,§ Christopher B. Little,§ Martin Cake,∥ Richard Read,∥ Matthew B. McDonagh,† and Simone Jane Rochfort† †

Discovery Technologies, Biosciences Research Division, Department of Primary Industries, Bundoora 3086, Victoria, Australia Murdoch Childrens Research Institute, Royal Children’s Hospital, Flemington Road, Parkville 3052, Victoria, Australia § Kolling Institute of Medical Research, E25 Royal North Shore Hospital, University of Sydney 2006, NSW, Australia ∥ School of Veterinary and Biomedical Sciences, Murdoch University, Murdoch 6150, Western Australia, Australia ⊥ School of Veterinary Science, University of Melbourne, Flemington Road, Parkville 3010, Victoria, Australia ‡

S Supporting Information *

ABSTRACT: Osteoarthritis (OA) is a highly prevalent joint disease. Its slow progressive nature and the correlation between pathological changes and clinical symptoms mean that OA is often well advanced by the time of diagnosis. In the absence of any specific pharmacological treatments, there is a pressing need to develop robust biomarkers for OA. We have adopted a nuclear magnetic resonance (NMR)-based metabolomic strategy to identify molecular responses to surgically induced OA in an animal model. Sheep underwent one of three types of surgical procedure (sham (control), meniscal destabilization, MD or anterior cruciate ligament transaction, ACLT), and for every animal a serum sample was collected both pre- and postoperatively, thus, affording two types of “control” data for comparison. 1D 1H NMR spectra were acquired from each sample at 800 MHz and the digitized spectral data were analyzed using principal components analysis and partial least-squares regression discriminant analysis. Our approach, combined with the study design, allowed us to separate the metabolic responses to surgical intervention from those associated with OA. We were able to identify dimethyl sulfone (DMSO2) as being increased in MD after 4 weeks, while ACLT-induced OA exhibited increased 3-methylhistidine and decreased branched chain amino acids (BCAAs). The findings are discussed in the context of interpretation of metabolomic results in studies of human disease, and the selection of appropriate “control” data sets. KEYWORDS: metabolomics, metabonomics, nuclear magnetic resonance (NMR), principal components analysis, osteoarthritis, sheep



Metabolomics, and the closely related field of metabonomics, refers to the comprehensive measurement of the metabolic response to a physiological stimulus, and has shown promise as a new logical framework for understanding disease etiology and biomarker identification.4 Several recent studies have adopted a metabolomic approach to investigate metabolic responses to arthritis using readily available biofluids such as urine and plasma.5−8 However, to date, there have been no metabolomics studies using animal models of OA where predisease samples

INTRODUCTION

Osteoarthritis (OA) is the most common joint disease, affecting nearly 10% of the entire population and over 25% of those over the age of 65 in Australia.1 It is characterized by a progressive degeneration of articular cartilage, but there is pathology in all joint tissues in OA, and the pathyophysiology of the disease remains poorly understood.2,3 The clinical disease is characterized by joint pain, but the poor correlation of symptoms with joint pathology means that by the time of diagnosis the disease is often relatively advanced. Because of this “silent onset”, the identification of markers indicative for early disease onset is highly desired.2 © 2012 American Chemical Society

Received: April 18, 2012 Published: July 11, 2012 4261

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Figure 1. (A) Design of the present study. Thirty-six animals were assigned to one of three groups: sham, meniscal destabilization, or anterior cruciate ligament transaction surgery. Serum samples were collected both pre- and postoperatively. Half the animals in each group (n = 6) were harvested at 4 weeks, and half were harvested at 12 weeks. (B) Typical 1D NMR spectrum from a sheep serum sample. Many of the major metabolites have been assigned based on known chemical shift and coupling patterns from the studies on human blood plasma.



can be obtained and compared with those at different stages of OA onset and progression. One of the major challenges to developing biomarkers for OA is the heterogeneity of the disease with regards to onset and symptoms, hence the usefulness of animal models with welldefined disease progression. Many different types of animal models of OA have been explored,9,10 reflecting the different inciting causes and subtypes of disease. The most commonly studied models are those induced by surgical techniques that alter joint biomechanics, for example meniscectomy, meniscal destabilization (MD), and anterior cruciate ligament transaction (ACLT), all mimicking naturally occurring pathologies in humans that significantly increase the risk of developing OA. There are species-specific differences in the response to these injuries, however, and while meniscal injury induces all the hallmark pathology of progressive OA in sheep, ACLT causes minimal cartilage damage in this species despite inducing joint instability. In the present study, we have taken advantage of these differences and compared the serum metabolomics in these two models and sham-operated sheep, to investigate if any changes could be specifically associated with cartilage degradation. In addition, we have collected serum samples both pre- and postoperatively, giving a unique opportunity to identify within-subject variation in response to OA.

METHODS

Materials

All materials were of analytical reagent grade and purchased from Sigma (St. Louis, MO). Sheep Models of Joint Injury

A total of 36 sheep (4−6 year old female purebred merino, 50− 55 kg) were randomly assigned to one of 3 different surgical procedures: (i) arthrotomy alone (sham surgery control)); (ii) medial menisco-tibial ligament transection to induce meniscal destabilization (MD); or (iii) anterior cruciate ligament transaction (ACLT). All animal procedures and management were conducted at Murdoch University under approval of the local animal ethics committee (approval number R2042/07). Briefly, sheep were anesthetized using intravenous ketamine and diazepam followed by intubation and 1−2% isoflurane in oxygen. Using standard sterile surgical techniques, an arthrotomy adjacent to the medial collateral ligament was performed and the anterior tibial attachment of the medial meniscus and anterior cruciate ligament were identified in all sheep, including the sham group. In the MD group, the anterior media menisco-tibial ligament was isolated using forceps and sharply transected, with resultant free translation of the meniscus confirmed manually. In the ACLT group, forceps were passed behind the ACL to isolate this structure that was 4262

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Figure 2. Results from PLS-DA analysis of pairwise comparisons of NMR data from postoperative serum samples. The PLS loadings have been plotted as a function of chemical shift and the square of the correlation of the NMR data with the response variable back-projected as a color onto the covariance of the same data. (A) Sham vs MD surgery after 4 weeks, (B), sham vs MD surgery after 12 weeks, (C) sham vs ACLT surgery after 4 week, (D) sham vs ACLT surgery after 12 weeks.

and lateral femoral and tibial compartments were scored by two observers blinded to treatment group and harvest time, using previously published methods.11

then transected with a scalpel blade and increased anterior drawer of the tibia was confirmed manually. In all joints including sham operated, hemostasis was ensured using electrocautery where necessary; the joints were lavaged with sterile saline and the incisions closed in 2 layers. All animals received cephalosporin antibiotics preoperatively, and analgesics (morphine and carprofen) for 24 h postoperatively. Following surgical recovery in closed covered pens, the animals were housed in groups in irrigated pasture with partial cover and they were free to exercise. The sheep were fed lucerne hay/ chaff and commercial animal feed pellets twice daily and water ad libitum throughout the duration of these studies. Within each treatment group, half the animals (n = 6) were euthanized with an overdose of pentobarbital/phenytoin at 4 weeks and half at 12 weeks after surgery (see Figure 1A). A blood sample (10 mL) was collected into red-top vacutainers via jugular venepuncture from all animals pre-operatively (preop) and immediately prior to sacrifice (necr). Blood was allowed to clot for 30 min at room temperature and stored at 4 °C for up to 2 h prior to centrifugation (1500g for 5 min). Aliquots of serum were harvested from all samples and stored at −20 °C until further analysis (see below). Both knee joints (mid femur to mid tibia) from all animals were collected within 30 min of death, stored on ice, and shipped at 4 °C overnight to the laboratory for analysis. All joints were opened, photographed, and tissues (synovium, cartilage, meniscus, subchondral bone) harvested for various other studies on molecular pathology. The digital images of the joints were coded, and the cartilage erosion and osteophyte development in the medial

NMR

Two 4 week postoperative serum samples from sham-operated sheep were lost prior to shipment, and therefore, only 4 samples were available from this group for NMR analysis. Serum samples were thawed and 450 μL was added to 50 μL of a 2 mM trimethylsilyl propionate (TSP) solution supplemented with 0.2% (w/v) sodium azide in D2O and placed into a 5 mm NMR tube. NMR data were acquired on a Bruker AvanceIII spectrometer operating at 800.13 MHz (Bruker Biospin, Karlsruhe, Germany). Data were acquired with a Carr− Purcell−Meiboom−Gill pulse sequence with presaturation during the recycle delay (2 s) and a total echo time of 51.2 ms. The time domain was 128k and the sweep width was 20 ppm. Data were Fourier transformed with exponential line broadening of 0.5 Hz in the frequency domain. Spectra were phased and baselined in Topspin 3.0 (Bruker Biospin, Karlsruhe, Germany) before being imported into Matlab (Mathworks, Natick, MA) at full resolution. Statistical Analysis

The joint pathology scores from the two independent observers were averaged for each joint. Ordinal group data (n = 6 for each surgery and harvest time) is presented graphically in box plots showing median, upper and lower quartile (box), 10−90th percentile (whiskers), and maximum and minimum values. Differences between groups were assessed using nonparametric 4263

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Figure 3. PLS-DA analysis of pairwise comparisons of within-subject variation between pre- and postoperative data. (A) MD after 4 weeks, (B) MD after 12 weeks, (C) ACLT after 4 weeks, and (D) ACLT after 12 weeks.



analysis (Mann−Whitney U test) with P < 0.05 considered significant. After import into Matlab, NMR data were aligned to the anomeric resonance of α-glucose (δ5.233). Nonquantitative spectral regions were removed (δ4.6−5.05) before normalizing to most probabilistic quotient.12 Principal components analysis (PCA) and projections to latent structures (PLS) models were constructed using in-house software based on the NIPALS algorithm.13 All models were autoscaled. To reduce the risk of overfitting PLS models, the Q2 parameter was calculated using the formula

RESULTS

Joint Pathology Data

Meniscal destabilization (MD) but not ACLT resulted in significant cartilage erosion compared with sham surgery at both 4 and 12 weeks postoperation (Figure 1A). In none of the surgery groups was the increase in median cartilage erosion score at 12 versus 4 weeks postsurgery statistically significant. Osteophytes were present in all surgery groups, and the score in ACLT at 4 weeks was greater than that in sham (Figure 1B). However, there was a significant increase from 4 to 12 weeks in the osteophyte score in shams, such that at this later time there was no difference compared with ACLT or MD. The total OA score showed a similar pattern to the cartilage erosion, and MD but not ACLT is significantly greater than sham at both 4 and 12 weeks (Figure S 1C).

⎛ ∑ (y − y )̂ 2 ⎞ ⎟ Q2 = 1 − ⎜ SSY ⎠ ⎝

where SSY is the sum of the squares of the Y matrix, and ŷ is the predicted y value. Estimates of the significance of the Q2 values were obtained by response permutation. For each PLS model, several hundred parallel models were constructed from the same data but with randomly reordered Y data. The “permuted” Q2 values were then regressed against the correlation of the Y data with the permuted Y data. A strong correlation was considered indicative of a good model. These data appear as insets in each PLS loadings plot, and expanded versions are available in the Supporting Information. To assist biological interpretation, PLS models were visualized by plotting model loadings as a function of chemical shift after multiplying by the standard deviation of the X matrix. The square of the loadings were then projected as a color onto this plot. This facilitates interpretation since the loadings resemble NMR spectra.14,15

NMR Data

Figure 1 B shows a typical 1D NMR spectrum from a sheep serum sample from this study. Most of the major metabolites can be immediately assigned based on known chemical shift and coupling patterns of the same metabolites in human plasma.16 Data matrices were constructed from the digitized spectra where each row was a different sample and each column an intensity, which serves as a proxy for metabolite concentration. These matrices were then subject to multivariate statistical analyses. Postoperative Sham Samples as Control

Metabolic responses to surgery-induced OA were initially evaluated by comparing postoperative samples from diseased animals with postoperative sham surgery to provide controls for 4264

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Figure 2 show loadings from ACLT samples when compared to sham surgery at 4 and 12 weeks, respectively. After 4 weeks, tyrosine and branched chain amino acids (valine, isoleucine, and leucine) were observed to be lower in ACLT sera compared to sham surgery, along with choline, TMA, and acetate, while glycine and 3-methylhistidine were increased (Figure 2C). After 12 weeks, the major differences were increased glutamine (gln), creatine, creatinine, and 3-methylhistidine, and lower TMAO and BCAAs for ACLT compared to sham surgery. Preoperative Samples as Controls

While the above results used the sham surgery samples as controls, the following section shows results generated when the preoperative samples were used as controls. Supporting Information Figure S3 shows the scores plots for three PCA models from each of the surgical interventions color-coded by disease stage with blue circles representing preoperative samples (grouped together since these are functionally equivalent), while red and green circles represent sera from animals harvested at 4 and 12 weeks, respectively. Although there is no clear separation within the MD cohort (Supporting Information Figure S3B), the three stages of disease appear to cluster into distinct groups for the animals that underwent ACLT surgery (Supporting Information Figure S3C). Interestingly, there did appear to be clustering of groups within those animals that underwent sham surgery (Supporting Information Figure S3A), suggesting that the surgical intervention itself has a detectable metabolic response. Although the above results show there were significant metabolic responses to surgically induced OA, a clear understanding of the progressive changes associated with each subtype may be obscured by the natural variation known to exist for most metabolites in mammalian samples.17 One of the advantages of the use of animal models is the availability of samples prior to the onset of disease. These are generally not available in studies of human diseases, and therefore offer potentially unique insights into the molecular mechanisms leading to the disease state within an individual. Furthermore, having access to pre- and postdisease samples allows us to analyze the data using “multivariate paired data analysis”, where the within subject variation is separated from the between subject variation,18,19 greatly enhancing the identification of systematic metabolic changes. Figure 3 shows the PLS-DA models of pairwise comparisons of preoperative to postoperative samples. Panels A and B of Figure 3 show the results from PLS-DA models for the postoperative MD samples at 4 and 12 weeks postsurgery, respectively, compared to the preoperative samples from the same animals. At 4 weeks postsurgery (Figure 3A), there were decreases in lactate and increases in TMAO, glutamine (gln), and a singlet at δ3.15 which has been assigned to DMSO2.20 After 12 weeks, the MD animals had decreased lactate and creatine, with increased acetate (Figure 3B). The PLS-DA models from the ACLT samples at 4 weeks showed decreases in lactate and BCAAs, with increases in acetate, glutamine, TMAO, and 3-methylhistidine (Figure 3C), while at 12 weeks, there were decreases in lactate and BCAAs and increases 3methylhistidine, acetate, and citrate. Finally, two further PLS-DA models were constructed to compare the preoperative with the postoperative samples from the animals subjected to sham surgery to identify the metabolites that were altered in response to surgery alone.

Figure 4. PLS-DA analysis of pairwise comparisons of within-subject variation between pre- and postoperative data for animals subject to sham surgery only. (A) Sham after 4 weeks, (B) sham after 12 weeks.

the effect of surgery alone. A PCA model was constructed from data from all samples collected 4 weeks postsurgery. The scores plot (Supporting Information Figure S2A) suggested the OA subtypes clustered together as a distinct group compared to controls (black). However, at 12 weeks, the scores from the ACLT samples (yellow squares) separated out from the MD and sham controls, which clustered together (Supporting Information Figure S2B). Although PCA can give a good overview of the data, PLS-DA can be used to build a quantitative relationship between the NMR data and the disease status, the predictivity of which can be estimated by cross validation. The cross-validation parameter, Q2, is an indicator of how well the model predicts new samples, and the robustness of Q2 can be estimated by permutation testing. If Q2 is above 0.5, it suggests the model is statistically robust, and the PLS loadings can be inspected to identify metabolites that discriminate disease status (putative biomarkers). Figure 2 shows the results from a PLS-DA model comparing MD with sham 4 weeks post surgery. The model loadings (expressed as the square of the correlation of the NMR data with the disease status) have been projected as a color onto the covariance of the same data. This facilitates interpretation of the model because the loadings resemble NMR spectra, and so the metabolites that are influencing the model can be identified from their chemical shift and coupling patterns. Figure 2A shows relative decreases in trimethylamine, choline, and acetate for MD compared to sheep subjected to sham surgery. After 12 weeks, the MD samples were metabolically equivalent to sham as judged by the low Q2 value for this model (Figure 2B, inset). Panels C and D in 4265

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Figure 5. (A) Summary of the pairwise analyses in the present study. Ten different PLS-DA models were used to quantify the metabolic response to surgically induced OA. Models on postoperative samples (presented in Figure 2) represent the “traditional” approach to comparing disease with controls, while other models compare preoperative with postoperative samples from the same individuals. (B) Summary of the unique metabolic changes found for both OA subtypes in this study, and changes unique to the surgical intervention.

response to surgery after 4 weeks (seen in all models), but this decrease is sustained in the OA surgery models at 12 weeks but not in the sham controls.

Although the total number of samples is low (only 3 pairs of samples were available), after 4 weeks (Figure 4A), there were increases in TMAO, glutamine, and acetate, and decreases in lactate and glycine. After 12 weeks, TMAO and tyrosine were elevated in response to sham surgery.



Combined Analysis of NMR Results

DISCUSSION

The major biological finding in this work was the identification of the different metabolic responses to the two OA models over time. After 4 weeks, MD animals had increased DMSO2, but by 12 weeks, with the exception of a decrease in creatine, they had recovered to be almost metabolically identical to those animals subject to sham surgery. DMSO2 is a common metabolite in mammalian plasma, and in humans may derive from dietary sources or from metabolism of gut bacterial-derived methanethiol. It is unclear what the source of DMSO2 is in this study, but it is interesting that it has been previously investigated as a therapeutic agent in osteoarthritis,21 and has recently been shown to have anti-inflammatory properties in chondrocyte cell lines.22 Furthermore, in a recent NMR study that identified a urinary metabolic profile for OA in humans, the authors noted an unassigned resonance at δ3.14 as being associated with OA,5 a finding that would be consistent with our observation of elevated DMSO2 in the MD model of OA at 4 weeks. Creatine is a product of muscle breakdown, and may indicate decreased muscle metabolism in these animals after 12 weeks.

Figure 5A gives a summary of the pairwise comparisons made in this study. Each treatment group (MD and ACLT at both time points) effectively has two different types of “control” data: the postoperative samples from the sham surgery; and the preoperative samples from the same animals. By integrating the knowledge gained from pairwise comparisons of each group with both controls, it becomes possible to identify metabolic changes that are unique to each treatment (summarized in Figure 5B), for an enhanced understanding of the identified putative biomarkers. For example, pairwise comparisons of postoperative samples at week 4 appeared to indicate relative decreases in choline and TMA in both MD and ACLT (Figure 2). However, comparing postoperative sham surgery to preoperative samples from the same animals (Figure 4B) suggests that choline and TMA were increased in response to sham surgery; hence, the intervention itself may be the cause of this change. It should be noted that this does not necessarily mean that TMA and choline are “biomarkers” for surgery, rather that we can exclude them as specific markers for either OA subtype. Furthermore, lactate appears to be decreased in 4266

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the results with respect to the applicability of the study to the population in question and the broader population.

Metabolic changes in animals that were subject to ACLT were more extensive. There was a marked decrease in BCAAs, with a corresponding increase in 3-methylhistidine over both time points, with further increases in glutamine, creatine, and creatinine at 12 weeks, the latter metabolites suggesting altered muscle metabolism. Interestingly, methylhistidine metabolism has been previously identified as being altered in metabolomic studies of arthritis,6 with a recent human study suggesting the serum BCAA/histidine ratio as a biomarker for knee OA.7 Our findings for decreased BCAA would appear to contrast with those results; however, direct comparisons are limited given the different model and species used in the present work. Interpretation of our findings are further hampered by confusion in the literature regarding the naming of 1- and 3methylhistidine.23 We have assigned this metabolite to 3methylhistidine based on comparison with pure compound spectra from chemicals bought from a commercial company. However, the nomenclature for 1- and 3-methylhistidine has been used interchangeably over the years, making interpretations at this stage difficult, other than to note that both are involved in muscle and connective tissue metabolism.23 A further finding in our study was the identification of a metabolic response to surgery, independent of OA in sheep. The decrease in lactate and increases in acetate and TMAO were observed in all animals following surgery. A recent study investigating the metabolic responses to surgical trauma in rats identified elevated urinary TMAO, but no significant alterations in lactate. Serum lactate is generally considered a marker for anerobic metabolism, and has been suggested to be of prognostic value in surgery.24 However, our findings suggest in sheep, the opposite may be the case, with acetate and TMAO more consistent indicators of surgical trauma. Finally, it is interesting to compare the data from the joint pathology with the NMR data. For both cartilage erosion and total OA score, MD, and not ACLT, was significantly different from the controls at both 4 and 12 weeks. This is in contrast to the serum metabolomic data, in which ACLT appeared more metabolically distinct from sham. These data suggest that the metabolic responses we have measured are not reflective of the joint pathology we have scored, but from a different aspect of the disease that is greater in magnitude in ACLT. This study presents the first metabolomic approach to measuring the responses to surgically induced OA in sheep. It should be noted that the biological interpretations of the present study are limited in that tissue-specific changes that have not been measured (synovitis, subchondrial bone remodelling, meniscal remodelling, altered limb loading, etc.) may all be contributing to the metabolic changes, but the contribution of each cannot be quantified at this stage. A unique feature of this study, compared to other metabolomic studies of OA, was the availability of preoperative samples, viz., samples from the same subjects prior to having any disease. When combined with efficient statistical analysis such as multivariate paired data analysis, this allowed enhanced interpretation of the results. This is a crucial point in the context of understanding the results of similar studies of disease in humans. The ultimate goal of metabolomic studies of disease is to establish whether the disease status of individuals can be predicted from the overall metabolic content of samples collected from them. This requires the collection of “control” samples from a comparable population. However, the definition of “control” is not trivial, as this will affect the interpretation of



ASSOCIATED CONTENT

S Supporting Information *

This material is available free of charge via the Internet at http://pubs.acs.org.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +61-3-9032 7014. Fax: +61-3-9032-7158. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The surgical studies in sheep were performed as part of the Ph.D. of Emily Fuller funded by a scholarship from The University of Sydney Medical Foundation. C.C., J.W., and J.F.B. were supported by the Victorian Government’s Operational Infrastructure Support Program. C.C. and J.F.W. acknowledge funding from Muscular Dystrophy Australia.



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