Diseases of bone associated with ageing, including osteoporosis (OP) and osteoarthritis (OA), reduce bone mass, bone strength and joint integrity. Current non-surgical approaches are limited to pharmaceutical agents that are not disease modifying and have poor patient tolerability due to side effect profiles. Developing a fundamental understanding of cellular bone homeostasis, including how key cell types affect tissue health, and offering novel therapeutic targets for prevention of bone disease is therefore essential. This is the focus of OSTEOMICS.

A number of factors have been linked to increased risk of bone disease, including genetic predisposition, diet, smoking, ageing, autoimmune disorders and endocrine disorders. In our study, we will recruit patients undergoing elective and non-elective orthopaedic surgery and obtain surgical bone waste for analysis. This will capture a cohort of patients with bone disorders like OP and OA, in addition to patients without overt clinical bone disease. We will study the relationship between the molecular biology of bone cells, bone structure, genetics (DNA) and environmental factors with the aim of identifying and validating novel therapeutic targets.

We will leverage modern single cell technologies to understand the diversity of cell types found in bone. These technologies have now led to the characterisation of virtually every tissue in the body, however bone and bone-adjacent tissues are massively underrepresented due to the anatomical location and underlying technical challenges. Early protocols to demineralise bone and perform single cell profiling have now been developed. We will systematically scale up these efforts to observe how genetic variation at the population level leads to alterations in bone structure and quality.

Over the next 10 years, we will generate data to comprehensively characterise bone across health and disease, use machine learning to drive analysis, and experimentally validate hypotheses - which will ultimately contribute to developing the next generation of therapeutic agents.

Inclusion Criteria:

1. Patients with osteoarthritis undergoing total joint arthroplasty, osteotomy or arthrodesis of any joint (including hip, knee, shoulder, wrist, elbow, ankle).
2. Patient with fractured neck of femurs undergoing hemiarthroplasty or total hip arthroplasty, or other internal fixation procedure.
3. Patients undergoing acute low-velocity or fragility fracture fixation surgery.
4. Patients aged between 18-110 years old with capacity to consent.

Since deteriorating bone health including diseases like osteoporosis are primarily conditions of older age there is no practical upper age-limit. However, study involvement is limited by suitability for surgery which encompasses multiple factors considered on an individual case basis including age, frailty, comorbidities, baseline mobility, renal function and ability to consent (for instance due to dementia or delirium).

We note that our inclusion criteria is purposefully broad as we aim to deduce trends across a wide range of conditions and backgrounds.

Exclusion Criteria:

1. Patients unable to provide informed consent.
2. Patients with suspected/established underlying malignancy.
3. Patients with suspected/established osteomyelitis.
4. Patients with suspected/established bloodborne disease
5. Patients who are currently a subject of a clinical trial involving an investigational medicinal product.

Participants undergoing range of orthopaedic surgeries.

It is intended that the results of the study will be reported and disseminated at international conferences and in peer-reviewed scientific journals.

When the data is no longer required by Relation Therapeutics, we may grant access to raw data (without linked identifiable patient data) and the right to publish freely. There will be no reference in the study results / reports / publications to any information that would identify participants. The final dataset, which may include a small number of select fields from the EDC database, will not contain any identifiable personal data.

Data will not be released until the study is complete. Raw data files in the original format (e.g. fastq) and the accompanying anonymised phenotypic data will be uploaded to a public repository e.g. the NCBI database of Genotypes and Phenotypes (dbGaP) at https://www.ncbi.nlm.nih.gov/gap/.

Any database selected to host genetic data must require legally-binding data access agreements with participating researchers.