Facilitating World Class Arthritis Research

What We’ve Got

Inspiral Biomedical Ltd has a vast array of musculoskeletal samples, with associated medical data, in order to provide academic and industrial researchers access to this unique resource with the ultimate aim of improving patient care more quickly. In particular we have collected many thousands of biological samples, with linked data such as treatment response, therapy history, autoantibody status, CRP, HLA and whole genome genetic data, on samples collected at baseline before treatment and at 3 and 6 month follow-up, all of which are available for researchers to access.

Cohort: Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate

Baseline (pre-treatment)

Asset Number
DNA 2721
RNA 1488
Serum 1488
Anti-CCP 2721
RF 2721
CRP 2721
HLA type 2721
Whole genome genotype 1150
Patient questionnaire 2721
Response to treatment 2721
Treatment regime 2721

3 months post treatment

Asset Number
DNA 2721
RNA 1488
Serum 1488
Anti-CCP 2721
RF 2721
CRP 2721
HLA type 2721
Whole genome genotype 1150
Patient questionnaire 2721
Response to treatment 2721
Treatment regime 2721

6 months post treatment

Asset Number
DNA 2721
RNA 1488
Serum 1488
Anti-CCP 2721
RF 2721
CRP 2721
HLA type 2721
Whole genome genotype 1150
Patient questionnaire 2721
Response to treatment 2721
Treatment regime 2721

Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGSS)

The biologic treatments (anti-TNF: infliximab, adalimumab, etanercept, golimumab, certolizumab; B-cell depleting therapy: rituximab; anti-IL6: tocilizumab; T cell co-stimulatory therapy: abatacept) have had a huge impact on the way that we treat our patients. However, data from the British Society of Rheumatology Biologics Register (BSRBR) suggests that only about 20% patients receiving these agents achieve a good response whilst 20% have no clinically important response at all.

Given the cost of these drugs, it would be of enormous economic benefit if it were possible to identify factors that would allow clinicians to predict who would and who wouldn't respond to these therapies as it would allow better targeting of scarce resources. Furthermore, it would protect those patients unlikely to respond to these treatments from being exposed to potentially serious side effects including infection. Whilst clinical predictors will certainly be important, we hypothesize that there are also genetic and genomic predictors of treatment response.

More info

Publications

Journal

Investigating CD11c expression as a potential genomic biomarker of response to TNF inhibitor biologics in whole blood rheumatoid arthritis samples

Journal

Differential Methylation as a Biomarker of Response to Etanercept in Patients With Rheumatoid Arthritis

Journal

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

Journal

Genetics of rheumatoid arthritis contributes to biology and drug discovery

Journal

Capture Hi-C reveals novel candidate genes and complex long-range interactions with related autoimmune risk loci