Osteoarthritis (OA) is one of the most common chronic diseases characterised by a disorder in the subchondral bone (SB), cartilage damage, and osteophyte formation. Due to an inadequate understanding of the mechanism of disease pathology, no treatment is currently available to effectively prevent the initiation or progression of OA, and severe treatment modalities, such as hip joint replacement, are currently available. A better understanding of the chemical and mechanical properties of bone will also help improve OA’s diagnosis. This study aims to investigate the chemical properties of SB from the femoral head (FH) of patients with OA through an invasive and label-free approach. Vibrational spectroscopy has shown the potential to provide diagnostic information. A combination of Raman, Fourier-Transform Infrared (FTIR) spectroscopic, and Photoacoustic Fourier Transform Infrared Spectroscopy (FTIR-PAS) methods were used for the chemical analysis of samples. Principal Component Analysis (PCA) was used to identify variations within different tissue of OA bone. Linear Discriminant Analysis (LDA) was used to predict pathogenic markers with high sensitivity (Sn) and specificity (Sp). The combination of Infrared and Raman spectroscopy with chemometrics were very helpful in identifying new spectral markers to differentiate OA bone samples. Initially, preliminary studies were conducted on bovine bones, which are almost comparable to human bones. They were applied on Raman and FTIR to study the chemical composition concerning the different cutting directions to prevent mistakes and enhance the primary study. For Raman, the PCA bovine result showed a perfect clustering, with PC-1 and PC-2 accounting for 92% of the variation, resulting in excellent Sn and Sp of 100%. The results for FTIR also exhibited perfect clustering, with PC-1 and PC-4 accounting for 80% of the variance, resulting in 100% Sn and Sp. Raman, FTIR and FTIR-PAS have identified structural and compositional changes in OA compared to tissue-specific (subregion). Significant statistical differences were detected among the bone types, including organic and inorganic composites. The results of the PCA in all vibrational spectroscopy showed that the PCA had good clustering, accounting for 74, 75, and 86% of the variation for Raman, FTIR and FTIR-PAS, respectively, leading to excellent Sn and Sp of 100%, representing the whole spectrum. Furthermore, as the aetiology and pathogenesis of OA are not fully understood, measuring the mechanical properties of bone by applying nanoindentation to FH to extract the mechanical properties is essential in order to understand the disease profile. The mechanical results show that the reduced modulus (𝐸𝑟) and the hardness (H) averaged out to be (16.07±3.05 GPa) and (0.56±0.107 GPa), respectively. The average elastic modulus (𝐸𝑏) of bone was measured to be (14.84±2.85 GPa), whereas the indentation modulus (E_ind) was (16.31±3.14 GPa). Compared to the other bone types, the osteophyte (Osteo) bone has the lowest value, while the cortical bone (Cort) has the highest value. The parameters in RS and FTIR confirm that increasing mineralisation ratios in bone types were correlated with a decreased 𝐸𝑏 and vice versa. In conclusion, vibrational spectroscopy is a highly effective method for identifying chemical changes associated with different subtypes of bone tissue disease. This study confirms its significance in evaluating both chemical and mechanical changes in cases of severe OA affecting the human FH helping to understand the reasons for the disease process and enable an improved treatment modality. Furthermore, these findings will assist the research community in identifying regions of the skeleton where the local physical and chemical properties of bone, in addition to the mechanical properties, should be characterised during the preclinical optimisation process of treatments for skeletal diseases.