The Oswestry Metabolic BONE Cohort

The overarching aim of this study is to look at the longitudinal musculoskeletal and extra-skeletal health outcomes for patients at risk for fracture who are attending the RJAH metabolic bone service as standard of care. This work is designed to use data collected as standard of care as well as research specific data. Standard of care data, which is anonymised before analysis is covered by existing ethics (22/PR/0076). However, the researchers will seek to consent patients for access to their medical records held by their GP. This is due to the importance of having accurate and reliable data on a patient's medical history for both clinical decisions and research studies pertaining to bone health. Data obtained from standard of care, relevant medical history, biological samples, and diagnostic imaging will be analysed to provide a holistic approach to understanding why patients fracture and how best to predict future fracture risk and identify parameters of treatment response. This research will assess the well-established traditional risk factors for fracture and explore novel risk factors related to chronic conditions such as diabetes, obesity, sarcopenia, and frailty as well as novel biomarkers including 'omics' (metabolomics, proteomics) and the microbiome, to understand how the gut microbiome influences bone health and to reveal new pathological and mechanistic metabolic pathways. It is widely known that different lifestyle factors can have a huge impact on health. Smoking, excessive alcohol intake, poor diet and lack of exercise increase the chances of developing a range of diseases, osteoporosis being one of them. The increased body weight in obesity has been consistently shown to be associated with a higher BMD measured by dual energy X-ray absorptiometry (DXA)20 but despite the improved BMD, obese patients may have higher incidence of fracture, a phenomenon known as "obesity paradox". In routine practice, the fracture frisk is calculated using the FRAX® tool which considers high body mass index (BMI) as a protective factor for fracture. As a result, many obese patients with fracture are denied anti-osteoporosis treatment because they do not have a BMD low enough to qualify for treatment with FRAX score falling below the treatment threshold according to the UK National Osteoporosis Guideline Group (NOGG 2021). Chronic conditions such as obesity and diabetes have been linked with an increased fracture risk, but it is unknown whether the combination of these two conditions, termed 'diabesity', carries a higher fracture risk compared to having obesity or diabetes alone. Further research to improve our understanding of these risk factors and optimise the management of osteoporosis is urgently needed and will form part of this body of research work. Metabolomics offers great potential to unlock complex pathways involved in metabolic processes, which could identify biomarkers associated with osteoporosis. This could help in the early detection, diagnosis, and monitoring of disease progression. Building a biobank of blood, plasma and serum samples from consenting patients will allow us to conduct a number of 'omics' and other high content studies, which will ultimately help us to understand disease mechanisms by looking at the interaction of proteins, genes and metabolites. Microbiome studies also offer a huge beneficial research potential. The gut microbiome (GM) is the community of trillions of microorganisms (bacteria, viruses, fungi, and other microbes) that live in the gastrointestinal tract. These microorganisms perform essential functions, including aiding digestion and metabolism, synthesising vitamins, regulating immune responses and inflammation, and protecting against pathogens. An increasingly emerging concept of the gut-bone axis refers to the complex communication pathways between the GM and bone metabolism. When the GM is imbalanced (dysbiosis), it can lead to increased inflammation and oxidative stress, both of which are detrimental to bone health. Dysbiosis can cause: * Increased Bone Resorption: Inflammatory cytokines can activate osteoclasts: bone cells that break down bone tissue. * Reduced Bone Formation: Dysbiosis reduces the production of anti-inflammatory Short Chain Fatty Acids (SCFA's), leading to a decreased ability to form new bone. * Altered Gut Barrier Function: A weakened gut barrier (sometimes called "leaky gut") can allow harmful substances, such as lipopolysaccharides (LPS), to enter the bloodstream and trigger systemic inflammation, further harming bone tissue. Though research is still emerging, animal studies and some human trials show promising results linking gut health and bone health. There are indications that probiotic supplementation could reduce bone loss in postmenopausal women and improve bone density in osteoporosis patients. However, large-scale human studies are needed to establish definitive therapeutic guidelines. Maintaining a healthy GM through diet, probiotics, and prebiotics may offer a supportive strategy to enhance bone health and reduce the risk of osteoporosis, especially in at-risk populations. It is also widely recognised that an unhealthy microbiome plays a significant role in the development and progression of obesity and type 2 diabetes, which can have an indirect negative impact on bone health. As one of the UK's largest metabolic services, we are in a strong position to build a scientifically and clinically impactful biobank of patient samples that will allow us to collaborate with world leading experts. Researchers will aim to identify novel biomarkers that will directly influence treatment strategies, specifically by predicting how different patients will respond to particular treatments. In a world where personalised, precision medicine is increasingly recognised as essential, this research will be especially beneficial for patients with multiple co-morbidities and complex needs, where a one-size-fits-all approach is unlikely to be effective. Cohort 1: Bone health clinical cohort Suitable patients attending the service for a DXA scan in 2025 onwards will be asked to consent to allowing access to their GP medical records. GP records will be accessed in consenting patients to gain complete and up-to-date medical history, especially information on diagnoses including fracture, diabetes, height, weight, smoking, alcohol intake as well as previous and current medications. As all of this information impacts on the treatment plan for a patient, it is vital that it is accurately obtained. A group of patients will also be asked about their willingness to be involved in PPIE activities and taking part in future clinical trials. This data will be used to discover new trends and relationships pertaining to bone health which will allow us to further extend our studies, improve our knowledge and ultimately benefit patients. Cohort 2: Exploratory cohort of 'omics', microbiome, bone structure, and body composition Patients will be asked to consent to take part in this cohort study. The main objectives are to assess the following: * Omics biomarkers and their predictive values on bone health outcomes, sarcopenia, frailty, ageing, and response to osteoporosis treatments. * Body composition (lean mass and fat mass) measured by whole body DXA. * Quantitative fat assessment measured by MRI of muscle and bone marrow with a focus on visceral fat/intramuscular fat/ sub cutaneous fat. * Bone microstructure measured by QCT at tibia, wrist, hip, and/or spine. * Microbiome studies from stool, urine, blood and or saliva samples. These studies will be conducted with the aim of understanding the impact of muscle mass, body composition and bone quality on fracture risk. This approach would suit patients whose fracture history cannot be explained by bone mineral density and traditional risk factors. Obesity and diabetes type 2 will be a target study as we aim to compare four groups: patients with obesity and type 2 diabetes, patients with obesity without diabetes, patients with healthy weight and type 2 diabetes, and patients with healthy weight without diabetes, to gain new insights into the biological pathways of metabolic bone disease associated with diabetes and obesity. Generation of predictive model A predictive model will be generated to test the impact of obesity, categorised by BMI and WHtR, along other risk factors including FRAX elements, medication, comorbidities, muscle strength, BMD and body composition measured by DXA, QCT results, MRI of muscle and bone marrow results, and biomarkers on the risk of incident fracture. Furthermore, data will be collected on fracture healing time and costs of health care use via a health economics assessment. This research will address an important care gap and inform the rationale for a future study investigating whether obese patients with a fracture who fall below national interventional threshold for anti-osteoporosis therapy could benefit from such treatment. 3\. RESEARCH INTERESTS \& QUESTIONS Cohort 1: Standard of care clinical risk factors for fracture Primary research questions: In postmenopausal women and men \>50 years attending the metabolic service for a bone density scan due to fracture risk factors: 1\. What is the risk of subsequent fractures at 2 and 5 years in those with a recent fragility fracture (within 24 months) who are not recommended anti-osteoporosis therapy based on BMD T-score and FRAX threshold Secondary research questions: 1. Does central obesity (WHtR ≥ 0.6) increase the two-year risk of incident fracture (regardless of prior fracture) compared to those without central obesity (WHtR \< 0.6), with or without type 2 diabetes? 2. Is the response to anti-osteoporosis treatment different among patients with healthy weight, obesity, and obesity with type 2 diabetes? 3. Is there a difference in mortality rates at 2 and 5 years between obese and non-obese patients attending the metabolic service for bone density scans? 4. Is there a difference in healthcare resource utilisation following a fracture between obese and non-obese patients? Analysis of the data from this patient cohort will include some or all the following research themes and objectives: * Compare the frequency, skeletal site affected, and time of subsequent fractures (time to event) between baseline obese (BMI ≥ 30 kg/cm2, WHtR ≥ 0.6) and non-obese (BMI \< 30 kg/cm2, WHtR \< 0.6) at two years and five years follow up in patents with a recent fracture within 24 months. * Determine patient and fracture characteristics that predict subsequent fracture risk in patients with obesity according to BMI and WHtR categories. * Compare the percentage (%) of patients who require anti-osteoporosis treatment at two years and 5 years between the obese and non-obese groups at baseline * Compare the frequency, skeletal site affected, and time to subsequent fracture at two and five years between men and women in the obesity group * Understand potential barriers that prevent obese patients with a fragility fracture from taking part in research studies and explore their acceptability of a future drug trial * Compare BMD change from baseline at femoral neck, total hip, and lumbar spine between baseline obese and non-obese patients at 2 years and 5 years follow up Other objectives include: * Establish the overall frequency of obesity defined by BMI \> 30 kg/cm2 and WHtR \> 0.6 in patients attending a UK West Midlands bone densitometry service * Report the frequency of obesity defined by BMI \> 30 kg/cm2 and WHtR \> 0.6 separately in men \>50 years and postmenopausal women with a recent low trauma fracture and not recommend anti-osteoporosis therapy * Assess risk of subsequent fracture in patients with type 2 diabetes mellitus (T2DM) and examine if T2DM plus central adiposity (diabesity) increases the risk of subsequent fracture beyond the risk associated with obesity and diabetes individually Cohort 2: Exploratory study of 'omics', microbiome, bone structure, and body composition Research questions: 1. Is the diversity and composition of the gut microbiota different among patients with a healthy weight, obesity, and obesity with type 2 diabetes? 2. What is the relationship between the composition and diversity of the gut microbiota, its metabolites, and the following determinants of bone strength: areal BMD measured by DXA, volumetric BMD and parameters of bone microstructure at the hip and spine measured by QCT, and bone turnover markers? 3. What is the association between gut microbiota composition, its metabolites, and fat content in bone marrow and thigh muscle quantified by MRI? 4. Does fat quantification in the bone marrow (spine) and thigh muscle mediate the relationship between gut microbiota and bone health parameters? 5. Does the gut microbiome mediate the relationship between central obesity, type 2 diabetes, and the risk of incident fractures? 6. Can novel biomarkers such as metabolomics and proteomics reveal new biological pathways in metabolic bone disease associated with diabetes and central obesity? 4\. Inclusion \& exclusion criteria Inclusion * Postmenopausal women and men \> 50 years old * A fragility fracture sustained during two years prior to the baseline DXA including spine, hip, wrist, humerus, pelvis, elbow, rib, sternum, clavicle, scapula, distal femur, tibia, fibula, and foot * A DXA measurement at the lumbar spine and hip between 2025-2035 * Non-osteoporotic BMD (T-score \>-2.5) and * Anti-osteoporosis therapy not recommended following the DXA scan Exclusion * Traumatic fracture * Patients who lack capacity. Assessment Items 1-11 are standard of care in our metabolic bone service. 1. Lifestyle factors: smoking, alcohol intake, vaping, dietary intake, mobility, and physical activity 2. Demographics: age, sex, ethnicity 3. Drug history 4. Family history of hip fracture 5. Measurements of height, weight, waist circumference, BMI, WHtR, grip power, clinical frailty scale, FRAX 6. Fracture history 7. Comorbidities including diabetes, chronic kidney disease, sarcopenia and falls 8. Response to osteoporosis treatment (real world data) 9. BMD measured by DXA for all patients: Baseline, 2, and 5 years 10. Trabecular bone score (TBS) measured from DXA images 11. Standard of care tests and biomarkers related to bone strength, muscle function, sarcopenia, and aging including CRP, vitamin D, calcium, parathyroid hormone, HbA1C, fasting glucose, and bone turnover markers including PINP, CTX, bone alkaline phosphatase, osteocalcin, FGF23 12. For the exploratory Cohort 2 study in consented patients: * Novel biomarkers related to bone metabolism including leptin and adiponectin, metabolomics and proteomics measured by Mass Spectrometry (MS). * Body composition measured by DXA: lean tissue mass, fat tissue mass, percentage (%) fat. * MRI of muscle and bone marrow: muscle volume, fat quantification. * QCT: volumetric BMD of the spine and hip, and body composition. * Building a biobank of samples for microbiome studies. 5\. Outcome measures Primary outcomes: 1. Time to subsequent fracture following baseline assessment. 2. Cumulative risk of fracture at 2 and 5 years. Secondary outcome measures: 1. Percentage (%) change in BMD from baseline at the lumbar spine and hip at 2, 5 years between obese and non-obese groups, categorised by BMI and WHtR categories. No new scans will be requested, all obtained scans will be part of routine clinical practice at 2 and 5 years. 2. Between-group differences in the proportion of fracture at different skeletal sites: hip, MOF, vertebral, central, and peripheral fractures in obese and non-obese 3. Comparative values of BMI and WHtR in predicting incident fracture 4. Difference in healthcare resource utilisation and associated economic costs between obese and non-obese patients 5. Predictive values of biomarkers in fracture risk including: * baseline hs-CRP, vitamin D3, metabolites, circulating proteins, and genomics parameters * muscle strength and function * trabecular bone score (TBS) * body composition measured by DXA * thigh muscle mass and fat content of the thigh muscle and bone marrow measured by MRI * bone microstructure measured by QCT including trabecular and cortical bone * the gut microbiome. 6. Sample size and statistical analysis: Sample size estimation: This study will be powered to detect significant differences in the risk of subsequent fractures between individuals with normal central adiposity and those with high central adiposity who have sustained a recent fracture (within the past 24 months) and who have had no previous osteoporotic therapy. The rate of subsequent fracture in patients with an incident fracture and who are not on anti-osteoporosis treatment is widely accepted to be 12% at 2 years. Preliminary data from these patients, presented at the International Osteoporosis Foundation conference revealed that the relative risk of fracture in centrally obese patients is 1.5 to 2 compared to those with normal central adiposity. Assuming a background 2-year fracture risk of 12% in patients with a prior fracture but normal central adiposity (WHtR \<0.5), and assuming central adiposity (WHtR \>0.6) is associated with a relative risk of 1.5, in a 1:1 ratio with 80% power and significance level of 0.05, 1752 eligible patients will be needed (assuming 20% drop rate) in the whole cohort to show a significant difference in fracture risk at two years. This calculation is based on an internal feasibility study which showed that 15% of our patients have normal central adiposity; half of them were reported to have previous fracture and 30% of those with fracture are on osteoporotic treatment. Cohort 2: Exploratory study of 'omics', microbiome, bone structure, and body composition This will be an exploratory proof of concept study, and no power calculation was done. Statistical analysis Univariable analyses using Chi-squared tests will be performed in both cohorts to compare fracture risk between the WHtR groups; (healthy; 0.4-0.49), increased central adiposity (0.5-0.59), and high central adiposity (≥0.6), and the BMI groups; healthy weight (18.5-24.9), overweight (25-29.9), and obese (≥30). T test and the Chi-square test will be performed to test the differences in distributions of continuous and categorical variables, respectively. Metabolites and circulating proteins will be compared across the 4 diabetes/central obesity groups. Independent variables that demonstrate significant differences in the univariable analyses and variables that are known to be associated with fracture risk will be considered as potential confounders/predictors and adjusted for in multivariable analyses. To assess whether WHtR and BMI are associated with subsequent fragility fractures, a multivariable logistic regression will be carried out, using the occurrence of fragility fracture vs. no fracture as dependent variable. Kaplan Meier survival analysis and log-rank tests will be used to compare time to fracture between the different BMI and WHtR groups. Cox regression analysis will be used to assess the relationship between fracture risk and potential risk factors including obesity indices.