Raman Spectroscopy Predicts the Link between Claw Keratin and Bone Collagen Structure in a Rodent Model of Oestrogen Deficiency

Osteoporosis is a common disease characterized by reduced bone mass and an increased risk of fragility fractures. Low bone mineral density is known to significantly increase the risk of osteoporotic fractures; however, the majority of non-traumatic fractures occur in individuals with a bone mineral density too high to be classified as osteoporotic. Therefore, there is an urgent need to investigate aspects of bone health, other than bone mass, that can predict the risk of fracture. Here, we successfully predicted association between bone collagen and nail keratin in relation to bone loss due to oestrogen deficiency using Raman spectroscopy. Raman signal signature successfully discriminated between ovariectomised rats and their sham controls with a high degree of accuracy for the bone (sensitivity 89%, specificity 91%) and claw tissue (sensitivity 89%, specificity 82%). When tested in an independent set of claw samples the classifier gave 92% sensitivity and 85% specificity. Comparison of the spectral changes occurring in the bone tissue with the changes occurring in the keratin showed a number of common features that could be attributed to common changes in the structure of bone collagen and claw keratin. This study established that systemic oestrogen deficiency mediates parallel structural changes in both the claw (primarily keratin) and bone proteins (primarily collagen). This strengthens the hypothesis that nail keratin can act as a surrogate marker of bone protein status where systemic processes induce changes

Raman Spectroscopy as a Predictive Tool for Monitoring Osteoporosis Therapy in a Rat Model of Postmenopausal Osteoporosis

Pharmacological therapy of osteoporosis reduces bone loss and risk of fracture in patients. Modulation of bone mineral density cannot explain all effects. Other aspects of bone quality affecting fragility and ways to monitor them need to be better understood. Keratinous tissue acts as surrogate marker for bone protein deterioration caused by oestrogen deficiency in rats. Ovariectomised rats were treated with alendronate (ALN), parathyroid hormone (PTH) or estrogen (E2). MicroCT assessed macro structural changes. Raman spectroscopy assessed biochemical changes. Micro CT confirmed that all treatments prevented ovariectomy-induced macro structural bone loss in rats. PTH induced macro structural changes unrelated to ovariectomy. Raman analysis revealed ALN and PTH partially protect against molecular level changes to bone collagen (80% protection) and mineral (50% protection) phases. E2 failed to prevent biochemical change. The treatments induced alterations unassociated with the ovariectomy; increased beta sheet with E2, globular alpha helices with PTH and fibrous alpha helices with both ALN and PTH. ALN is closest to maintaining physiological status of the animals, while PTH (comparable protective effect) induces side effects. E2 is unable to prevent molecular level changes associated with ovariectomy. Raman spectroscopy can act as predictive tool for monitoring pharmacological therapy of osteoporosis in rodents. Keratinous tissue is a useful surrogate marker for the protein related impact of these therapies. The results demonstrate utility of surrogates where a clear systemic causation connects the surrogate to the target tissue. It demonstrates the need to assess broader biomolecular impact of interventions to examine side effects. [Figure not available: see full text.]

Raman Spectroscopic Analysis of Fingernail Clippings Can Help Differentiate between Postmenopausal Women Who Have and Have Not Suffered a Fracture

Raman spectroscopy was applied to nail clippings from 633 postmenopausal British and Irish women, from six clinical sites, of whom 42% had experienced a fragility fracture. The objective was to build a prediction algorithm for fracture using data from four sites (known as the calibration set) and test its performance using data from the other two sites (known as the validation set). Results from the validation set showed that a novel algorithm, combining spectroscopy data with clinical data, provided area under the curve (AUC) of 74% compared to an AUC of 60% from a reduced QFracture score (a clinically accepted risk calculator) and 61% from the dual-energy X-ray absorptiometry T-score, which is in current use for the diagnosis of osteoporosis. Raman spectroscopy should be investigated further as a noninvasive tool for the early detection of enhanced risk of fragility fracture