Abstract
This study was to investigate how OA patients with metabolic syndrome (MetS) are different metabolically from OA patients without MetS components and healthy individuals. A two-stage case–control study design was utilized. Synovial fluid (SF) and plasma samples were collected from patients undergoing total knee joint replacement due to primary OA and healthy controls (only plasma) and metabolically profiled using UPLC-MS coupled with assay kit which measures 186 metabolites. Orthogonal projection to latent structure-discriminant analysis and linear regression were used to identify metabolic markers for discriminating OA patients with MetS components from those without and healthy individuals. 54 paired SF and plasma samples from knee OA patients and 30 plasma samples from healthy controls were included in the discovery stage, and 143 plasma samples (72 from knee OA patients and 71 from the age, sex, and BMI matched controls) were included in the validation stage. OA patients with MetS can be clearly discriminated from OA patients without MetS based on the metabolite profiles of both SF and plasma and the separation appeared to be driven by type 2 diabetes but not obesity, hypertension, or dyslipidemia. When compared with OA patients with diabetes, OA without diabetes, and healthy controls, phosphatidylcholine acyl-alkyl C34:3 (PC ae C34:3) and phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) were identified and confirmed to be associated with the concurrence of OA and diabetes (all p < 0.003). The study demonstrated that altered phosphatidylcholine metabolism was associated with both OA and diabetes mellitus.
Similar content being viewed by others
References
Al-Arfaj, A. S. (2003). Radiographic osteoarthritis and serum cholesterol. Saudi Medical Journal, 24, 745–747.
Alberti, K. G., & Zimmet, P. Z. (1998). Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabetic Medicine, 15, 539–553.
Altman, R., Alarcon, G., Appelrouth, D., et al. (1991). The American College of Rheumatology criteria for the classification and reporting of osteoarthritis of the hip. Arthritis and Rheumatism, 34, 505–514.
Berenbaum, F. (2011). Diabetes-induced osteoarthritis: From a new paradigm to a new phenotype. Annals of the Rheumatic Diseases, 70, 1354–1356.
Berenbaum, F., & Sellam, J. (2008). Obesity and osteoarthritis: What are the links? Joint Bone Spine, 75, 667–668.
Berridge, M. J., & Irvine, R. F. (1989). Inositol phosphates and cell signalling. Nature, 341, 197–205.
Bijlsma, S., Bobeldijk, I., Verheij, E. R., et al. (2006). Large-scale human metabolomics studies: A strategy for data (pre-) processing and validation. Analytical Chemistry, 78, 567–574.
Birtwhistle, R., Morkem, R., Peat, G., et al. (2015). Prevalence and management of osteoarthritis in primary care: An epidemiologic cohort study from the Canadian Primary Care Sentinel Surveillance Network. CMAJ Open., 3, E270–E275.
Blagojevic, M., Jinks, C., Jeffery, A., & Jordan, K. P. (2010). Risk factors for onset of osteoarthritis of the knee in older adults: A systematic review and meta-analysis. Osteoarthritis Cartilage, 18, 24–33.
Chen, Y., Crawford, R. W., & Oloyede, A. (2007). Unsaturated phosphatidylcholines lining on the surface of cartilage and its possible physiological roles. Journal of Orthopaedic Surgery and Research, 2, 14.
Chen, Y., Hills, B. A., & Hills, Y. C. (2005). Unsaturated phosphatidylcholine and its application in surgical adhesion. ANZ Journal of Surgery, 75, 1111–1114.
Cross, M., Smith, E., Hoy, D., et al. (2014). The global burden of hip and knee osteoarthritis: Estimates from the global burden of disease 2010 study. Annals of the Rheumatic Diseases, 73, 1323–1330.
Damyanovich, A. Z., Staples, J. R., Chan, A. D., & Marshall, K. W. (1999). Comparative study of normal and osteoarthritic canine synovial fluid using 500 MHz 1H magnetic resonance spectroscopy. Journal of Orthopaedic Research, 17, 223–231.
Engstrom, G., Gerhardsson de Verdier, M., Rollof, J., Nilsson, P. M., & Lohmander, L. S. (2009). C-reactive protein, metabolic syndrome and incidence of severe hip and knee osteoarthritis. A population-based cohort study. Osteoarthritis Cartilage, 17, 168–173.
Eymard, F., Parsons, C., Edwards, M. H., et al. (2015). Diabetes is a risk factor for knee osteoarthritis progression. Osteoarthritis Cartilage, 23, 851–859.
Farooqui, A. A., Horrocks, L. A., & Farooqui, T. (2000). Glycerophospholipids in brain: Their metabolism, incorporation into membranes, functions, and involvement in neurological disorders. Chemistry and Physics of Lipids, 106, 1–29.
Floegel, A., Stefan, N., Yu, Z., et al. (2013). Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes, 62, 639–648.
Fontaine-Bisson, B., Thorburn, J., Gregory, A., Zhang, H., & Sun, G. (2014). Melanin-concentrating hormone receptor 1 polymorphisms are associated with components of energy balance in the Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study. American Journal of Clinical Nutrition, 99, 384–391.
Gandhi, R., Kapoor, M., Mahomed, N. N., & Perruccio, A. V. (2015). A comparison of obesity related adipokine concentrations in knee and shoulder osteoarthritis patients. Obesity Research & Clinical Practice, 9, 420–423.
Gandhi, R., Woo, K. M., Zywiel, M. G., & Rampersaud, Y. R. (2014). Metabolic syndrome increases the prevalence of spine osteoarthritis. Orthopaedic Surgery, 6, 23–27.
Hart, D. J., Doyle, D. V., & Spector, T. D. (1995). Association between metabolic factors and knee osteoarthritis in women: The Chingford Study. Journal of Rheumatology, 22, 1118–1123.
Henrotin, Y. E., Bruckner, P., & Pujol, J. P. (2003). The role of reactive oxygen species in homeostasis and degradation of cartilage. Osteoarthritis Cartilage, 11, 747–755.
Hills, B. A. (1990). Oligolamellar nature of the articular surface. Journal of Rheumatology, 17, 349–356.
Hills, B. A. (2000). Role of surfactant in peritoneal dialysis. Peritoneal Dialysis International, 20, 503–515.
Hills, B. A. (2002). Surface-active phospholipid: A Pandora’s box of clinical applications. Part II. Barrier and lubricating properties. Internal Medicine Journal, 32, 242–251.
Hiraiwa, H., Sakai, T., Mitsuyama, H., et al. (2011). Inflammatory effect of advanced glycation end products on human meniscal cells from osteoarthritic knees. Inflammation Research, 60, 1039–1048.
Hochrath, K., Krawczyk, M., Goebel, R., et al. (2012). The hepatic phosphatidylcholine transporter ABCB4 as modulator of glucose homeostasis. FASEB Journal, 26, 5081–5091.
Hurley, M. V. (1999). The role of muscle weakness in the pathogenesis of osteoarthritis. Rheumatic Disease Clinics of North America, 25, 283–298. vi.
Kaur, J. (2014). A comprehensive review on metabolic syndrome. Cardiology Research and Practice, 2014, 943162.
King, K. B., & Rosenthal, A. K. (2015). The adverse effects of diabetes on osteoarthritis: Update on clinical evidence and molecular mechanisms. Osteoarthritis Cartilage, 23, 841–850.
Kroger, J., Zietemann, V., Enzenbach, C., et al. (2011). Erythrocyte membrane phospholipid fatty acids, desaturase activity, and dietary fatty acids in relation to risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. American Journal of Clinical Nutrition, 93, 127–142.
Lamers, R. J., DeGroot, J., Spies-Faber, E. J., et al. (2003). Identification of disease- and nutrient-related metabolic fingerprints in osteoarthritic Guinea pigs. Journal of Nutrition, 133, 1776–1780.
Lamers, R. J., van Nesselrooij, J. H., Kraus, V. B., et al. (2005). Identification of an urinary metabolite profile associated with osteoarthritis. Osteoarthritis Cartilage, 13, 762–768.
Lee, J. M., Lee, Y. K., Mamrosh, J. L., et al. (2011). A nuclear-receptor-dependent phosphatidylcholine pathway with antidiabetic effects. Nature, 474, 506–510.
Llorach-Asuncion, R., Jauregui, O., Urpi-Sarda, M., & Andres-Lacueva, C. (2010). Methodological aspects for metabolome visualization and characterization: A metabolomic evaluation of the 24 h evolution of human urine after cocoa powder consumption. Journal of Pharmaceutical and Biomedical Analysis, 51, 373–381.
Magnusson, K., Hagen, K. B., Osteras, N., Nordsletten, L., Natvig, B., & Haugen, I. K. (2015). Diabetes is associated with increased hand pain in erosive hand osteoarthritis: Data from a population-based study. Arthritis Care & Research, 67, 187–195.
Magnusson, C. D., & Haraldsson, G. G. (2011). Ether lipids. Chemistry and Physics of Lipids, 164, 315–340.
McNulty, A. L., Stabler, T. V., Vail, T. P., McDaniel, G. E., & Kraus, V. B. (2005). Dehydroascorbate transport in human chondrocytes is regulated by hypoxia and is a physiologically relevant source of ascorbic acid in the joint. Arthritis and Rheumatism, 52, 2676–2685.
Monira Hussain, S., Wang, Y., Cicuttini, F. M., et al. (2014). Incidence of total knee and hip replacement for osteoarthritis in relation to the metabolic syndrome and its components: A prospective cohort study. Seminars in Arthritis and Rheumatism, 43, 429–436.
Nah, S. S., Choi, I. Y., Yoo, B., Kim, Y. G., Moon, H. B., & Lee, C. K. (2007). Advanced glycation end products increases matrix metalloproteinase-1, -3, and -13, and TNF-alpha in human osteoarthritic chondrocytes. FEBS Letters, 581, 1928–1932.
Oloyede, A., Gudimetla, P., Crawford, R., & Hills, B. A. (2004). Consolidation responses of delipidized articular cartilage. Clinical Biomechanics, 19, 534–542.
Pietilainen, K. H., Sysi-Aho, M., Rissanen, A., et al. (2007). Acquired obesity is associated with changes in the serum lipidomic profile independent of genetic effects–a monozygotic twin study. PLoS One, 2, e218.
Puenpatom, R. A., & Victor, T. W. (2009). Increased prevalence of metabolic syndrome in individuals with osteoarthritis: An analysis of NHANES III data. Postgraduate Medicine, 121, 9–20.
Rahman, M. M., Cibere, J., Anis, A. H., Goldsmith, C. H., & Kopec, J. A. (2014). Risk of type 2 diabetes among osteoarthritis patients in a prospective longitudinal study. International Journal of Rheumatology, 2014, 620920.
Raubenheimer, P. J., Nyirenda, M. J., & Walker, B. R. (2006). A choline-deficient diet exacerbates fatty liver but attenuates insulin resistance and glucose intolerance in mice fed a high-fat diet. Diabetes, 55, 2015–2020.
Rhee, E. P., Cheng, S., Larson, M. G., et al. (2011). Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans. The Journal of Clinical Investigation, 121, 1402–1411.
Roberts, L. D., & Gerszten, R. E. (2013). Toward new biomarkers of cardiometabolic diseases. Cell Metabolism, 18, 43–50.
Sas, K. M., Karnovsky, A., Michailidis, G., & Pennathur, S. (2015). Metabolomics and diabetes: Analytical and computational approaches. Diabetes, 64, 718–732.
Schett, G., Kleyer, A., Perricone, C., et al. (2013). Diabetes is an independent predictor for severe osteoarthritis: Results from a longitudinal cohort study. Diabetes Care, 36, 403–409.
Sturmer, T., Sun, Y., Sauerland, S., et al. (1998). Serum cholesterol and osteoarthritis. The baseline examination of the Ulm Osteoarthritis Study. Journal of Rheumatology, 25, 1827–1832.
Tuck, M. K., Chan, D. W., Chia, D., et al. (2009). Standard operating procedures for serum and plasma collection: Early detection research network consensus statement standard operating procedure integration working group. Journal of Proteome Research, 8, 113–117.
Wallner, S., & Schmitz, G. (2011). Plasmalogens the neglected regulatory and scavenging lipid species. Chemistry and Physics of Lipids, 164, 573–589.
Xia, J., Psychogios, N., Young, N., & Wishart, D. S. (2009). MetaboAnalyst: A web server for metabolomic data analysis and interpretation. Nucleic Acids Research, 37, W652–W660.
Yoshimura, N., Muraki, S., Oka, H., et al. (2012). Accumulation of metabolic risk factors such as overweight, hypertension, dyslipidaemia, and impaired glucose tolerance raises the risk of occurrence and progression of knee osteoarthritis: A 3-year follow-up of the ROAD study. Osteoarthritis Cartilage, 20, 1217–1226.
Zhai, G., Aref-Eshghi, E., Rahman, P. et al. (2014). Attempt to replicate the published osteoarthritis-associated genetic variants in the Newfoundland & Labrador Population.
Zhai, G., Wang-Sattler, R., Hart, D. J., et al. (2010). Serum branched-chain amino acid to histidine ratio: A novel metabolomic biomarker of knee osteoarthritis. Annals of the Rheumatic Diseases, 69, 1227–1231.
Zhang, W., Likhodii, S., Aref-Eshghi, E., et al. (2015). Relationship between blood plasma and synovial fluid metabolite concentrations in patients with osteoarthritis. Journal of Rheumatology, 42, 859–865.
Zhang, W., Likhodii, S., Zhang, Y., et al. (2014). Classification of osteoarthritis phenotypes by metabolomics analysis. BMJ Open., 4, e006286-2014-006286.
Zhuo, Q., Yang, W., Chen, J., & Wang, Y. (2012). Metabolic syndrome meets osteoarthritis. Nature Reviews Rheumatology, 8, 729–737.
Acknowledgments
We thank all the study participants who made this study possible, and all the staff who helped us in the collection of samples. The study was funded by Canadian Institutes of Health Research (CIHR), Newfoundland & Labrador RDC, and Memorial University.
Financial support
Canadian Institutes of Health Research (CIHR); Newfoundland & Labrador RDC; Memorial University of Newfoundland
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interests
Ethical statement
The study was approved by the Health Research Ethics Authority (HREA) of Newfoundland and Labrador and written consent was obtained from all the participants.
Additional information
Roger Green—Deceased.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Zhang, W., Sun, G., Likhodii, S. et al. Metabolomic analysis of human synovial fluid and plasma reveals that phosphatidylcholine metabolism is associated with both osteoarthritis and diabetes mellitus. Metabolomics 12, 24 (2016). https://doi.org/10.1007/s11306-015-0937-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-015-0937-x