Musculoskeletal disorders are the second most common cause of disability worldwide. Osteoarthritis (OA), is the most common form of arthritis, resulting in an estimated 8.75 million of the UK population over 45 years of age seeking treatment annually; and a global prevalence of over 500 million 1. Indeed, the World Health Organization reported that OA is the single most common cause of disability in the older population 2. The health burden of osteoarthritis will continue to rise with increasing obesity, sedentary lifestyle and an increasing growing population of 60 years or older, which is expected to double by 2050 2. OA is a late-onset, complex disease of the joint that is typically characterised by degeneration and thinning of the articular cartilage, changes in synovium and subchondral bone causing loss in lubrication in a joint 3.
OA affects the whole joint; however, the main changes occur in articular cartilage leading to the complete loss of articular cartilage in severe cases. Articular cartilage is a connective tissue around 2 to 4 mm deep, present in joints of knees, hips, spine and fingers which serves as a shock absorber facilitating transmission of loads and smooth painless movements of joints. Articular cartilage is avascular, aneural and a lymphatic supply is nourished by the synovial fluids. Articular cartilage is made up of a dense extracellular matrix that predominantly comprises water and electrolytes (60–85% by weight) as well as collagen, non-collagenous proteins, proteoglycans, lipids, phospholipids and a sparse distribution of highly specialized cells (chondrocytes, 10% by weight) that produce the cartilage matrix 4–7. The dry weight of articular cartilage is primarily collagen (60%), however, the protein composition of cartilage is complex and varies depending on the depth of the tissue and distance from the chondrocytes 8–10.
Morphologically, cartilage can be divided into 3 layers: superficial, middle and deep (part of which is calcified, separated from the bone with a tidemark) zones and the key characteristics of each of these layers are summarized in Table 1 10–14. While chondrocytes are found in all three layers, their shape, orientation and expression of collagen type as well as other matrix proteins vary depending on the layer of cartilage in which they are present 10,15,16. Articular cartilage comprised of predominantly type II collagen (up to 90%) but it also contains types IX, XI and VI 16–18. Type I and II collagens are fibrillar and have high activity in second harmonic generation 19.
Table 1
Collagen phenotype across cartilage layers
Cartilage Layer | % of the cartilage volume | Morphology of chondrocytes | Main collagen constituents |
Superficial | 10–20% | Elongated/flattened | Mainly Type II (also, IX and XI) condensed collagen fibers running parallel to the joint |
Middle | 40–60% | Round | Mainly Type II collagen fibers that are randomly arranged and slightly tilted. Transitioning from a more parallel (near the superficial zone) to a more perpendicular orientation (towards the deep layer). |
Deep | ~ 30% | Round, arranged in columns | Type II collagen fibers running perpendicular to the joint and across the tidemark. |
Collagen type VI is found almost exclusively in the pericellular matrix (PCM), the area surrounding the chondron within which the chondrocytes are located providing structural integrity and facilitating communication with the extracellular matrix 17,20. The PCM contains biglycan and decorin proteins which connect type VI collagen fibers with type II collagen fibers, providing stable matrix in the immediate proximity of chondrocytes 20.
At the onset of OA, two important changes are known to occur within the cartilage: (i) chondrocytes undergo proliferation, cell death, autophagy and form clusters 15,16,21 and, (ii) the fluid in the cavity of the joints, the synovial fluid, becomes rich in inflammatory cytokines, complement components and plasma proteins 22,23. The primary inflammatory mediators have been identified as lipid molecules, prostaglandins and leukotriene 24,25 and other molecules released by white adipose tissue 26. Cartilage matrix degradation starts from the superficial layer and progresses to the deeper cartilage layers 12,27,28. However, the aetiology and molecular mechanisms responsible for the onset and progression of osteoarthritis remain poorly understood and their potential for diagnostic prediction has not been fully explored 29,30. The current gold-standard techniques for diagnosis of osteoarthritis focus on observation of the changes in morphology and bulk structure of the tissue. Techniques employed include advanced radiography, four-dimensional CT scan, CT arthrography, nuclear medicine techniques such as SPECT/CT, PET/CT, PET/MRI, three-dimensional quantitative cartilage morphometry as well as MRI and x-rays 3,29,31. These imaging techniques detect morphological changes such as narrowing of the space margin between the two bones in the joint as a consequence of cartilage loss or accumulation of synovial fluids and hence are typically limited to advanced stages of osteoarthritis, following disease progression 27.
Early diagnosis of OA is highly desirable to enable timely implementation of lifestyle changes and medical interventions to reduce pain, improve mobility and patient quality of life. There is currently no cure for osteoarthritis and treatment regimens are targeted at alleviating inflammatory symptoms or arthroplasty such as a prosthetic joint replacement. Efficacious application of non-invasive and non-destructive techniques such as Raman spectroscopy that can directly (and potentially in vivo) detect subtle biochemical changes that occur within the cartilage at onset and during osteoarthritis and, critically will provide markers for diagnosis of osteoarthritis before symptoms appear and thus aid the discovery of new pharmacological interventions to halt OA progression, remains a key research goal. Raman spectroscopy is highly applicable for in vivo diagnosis as well as for evaluation of ex vivo articular cartilage samples due to its insensitivity to water and hence, can provide information on constituent molecules as well as their interactions with surrounding molecules despite its high water content. Several characteristic Raman bands have been assigned to vibrational modes of constituent molecules in cartilage tissue. These include modes assigned to C-O stretching; amide I, random coil (1668 cm− 1), Amide I, collagen secondary str (1640 cm− 1), C = C stretching; phenylalanine, tryptophan (1606 cm− 1), Amide II (1557 cm− 1), CH2/CH3 scissoring; collagen and other proteins (1450 cm− 1), COO−; GAGs (1424 cm− 1), CH3; GAGs (1380 (proteoglycan) cm− 1), (NH2) bending; amide III, α-helix (1270 cm− 1), Amide III, α-helix (1260 cm− 1), (NH2) bending; amide III, random coil (1245 cm− 1), Amide III, random coil (1235 cm− 1), Pyranose ring (1163 cm− 1, 1042 cm− 1), C-C, C-OH, C-N stretching, C-O-C glycosidic linkage (1125 cm− 1), SO3− stretching; GAGs (chondroitin sulfate) (1063 cm− 1), Phenylalanine ring breathing (1003 cm− 1), C-C stretching; collagen, α-helix (941 cm− 1), C-C stretching; hydroxyproline (875 cm− 1), C-C stretching; proline (858 cm− 1) and C-C stretching; protein backbone (816 cm− 1) 32–43.
For the diagnosis of osteoarthritis, it is important to identify the spectral changes in cartilage, that is, the changes in the peak patterns instead of intensity of individual peaks. This is carried out through multivariate analysis such as principal component and linear discriminant analysis (PCA and LDA) wherein the spectral loadings link the variance of the peaks across classes to the original spectra. Changes in the ratio of the intensity of certain vibrational modes also provide valuable insight and can potentially provide diagnostic information. The current study has applied PCA and LDA to understand the spectral differences between the different layers in healthy and OA cartilage for their unsupervised and supervised classification.
Raman Spectroscopy has been used by a number of groups to study human osteoarthritic cartilage 34,36,38–41,44. Takahashi et al completed a preliminary study on 5 arthritic human tibial cartilage samples retrieved from knee arthroplasty and found an increase in the relative intensity ratio between the Raman bands of collagen located at 1241 and 1269 cm− 1 (amide III doublet) with increasing degradation grades indicating diagnostic potential 39. A recent feasibility study on 47 patient samples extended the aforementioned work and observed a decrease in sulfated glycosaminoglycans and proteoglycans and increase in collagen disorganization with severity of hip osteoarthritis 40. Similarly the diagnostic potential of Raman spectroscopy to study alterations in collagen structure in disease diagnosis was explored by multiple groups and reviewed by Martinez et al. 36 but the different layers of cartilage were not taken into account. These studies confirm the diagnostic potential of Raman spectroscopy, however, to date, there has been no published evidence of the changes in the different layers of cartilage characterised by Raman spectroscopy or, the use of the differential signatures between the cartilage layers for osteoarthritis diagnosis in patients.
The current study has harnessed Raman Spectroscopy to characterize osteoarthritic and non-osteoarthritic patient samples of cartilage derived from femoral heads post hip arthroplasty. We investigated changes in the different layers of cartilage to identify discrete differences in their molecular composition. PCA and PC loadings were applied to understand the contribution of different vibrational modes to unsupervised classification. PCA-LDA was used for supervised classification. The dependence of the Raman spectral signatures from the different layers of cartilage with gender as well as age was examined. We further used the multimodal imaging techniques of coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG) and two-photon autofluorescence (TPF) microscopy on representative samples to correlate any changes in the structure and organization of different components in the superficial and deep layers with changes observed by Raman spectral analysis. The current work aims explored the potential of OA diagnosis using the Raman signatures of different cartilage layers offering significant diagnostic implications for an increasing aging demographic.