Completed Bones, Joints & Muscles Infection & Immunity

An Immunological Toolkit for Clinical Application

In plain English

AI plain-English summary

Rheumatoid arthritis patients have immune systems that attack their own joints, but doctors still cannot predict which drug will work for which patient. The problem is that the immune abnormalities driving RA remain poorly understood. Current treatments are prescribed by trial and error—patients may cycle through several drugs before finding one that works, while their joints sustain irreversible damage. This project aims to map those immune abnormalities in detail, comparing white blood cells from RA patients against immune responses in healthy people receiving a vaccine. The goal is to identify simple, reliable lab tests that reveal what each patient’s immune system is actually doing. If successful, these tests could transform how rheumatologists prescribe existing drugs—matching the right treatment to the right patient from the start, rather than guessing. The work could also speed up diagnosis and help predict which patients will develop joint damage. Because the immune mechanisms at play in RA may overlap with those in diabetes, multiple sclerosis, asthma, and organ transplant rejection, the same laboratory toolkit could eventually improve care across multiple conditions. This is applied immunology with a clear clinical target: turning a messy immune system into something measurable and manageable.

View original technical description
Patients with rheumatoid arthritis (RA) suffer with joint pain and stiffness, and joint damage which leads to a reduced ability to carry out everyday tasks. Although these are the most obvious features of the disease, the root cause of the disease lies within the human immune system. At the moment we don?t fully understand the immune abnormalities that lead to RA but, if we did, this should help us to manage the disease better. It would become easier to make a diagnosis, as well as to determine whether a patient?s RA is likely to damage their joints in the future. Perhaps most importantly it would help us to design better drugs to combat the disease, and to better use the drugs that already exist. Something that we would really like to be able to do is to decide the most appropriate drug for each patient and a better understanding of the immune abnormalities would also help here. Therefore our plans are to study, in detail, the immune system of patients with RA. This will involve taking blood from patients and running a panel of advanced laboratory tests on their white blood cells. We will compare the results we obtain with the immune changes in healthy individuals responding to a vaccine ? expecting some to be the same and some to be different. Our work is in three phases and, during the phases, we plan to slowly ?home in? on simple laboratory tests that will allow us to measure what is happening to the immune system in patients with RA. An exciting aspect of the work is that what is relevant to RA may also relate to other diseases (diabetes, multiple sclerosis, asthma) and to patients with an organ transplant. Therefore our results could have wide-ranging influence beyond improving the care of patients with RA

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Researchers

Catharien Hilkens (Co-Investigator)Christopher Buckley (Co-Investigator)Costantino Pitzalis (Co-Investigator)Frederic Geissmann (Co-Investigator)Iain McInnes (Co-Investigator)John Isaacs (Principal Investigator)Michael Ehrenstein (Co-Investigator)Paul Emery (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

Biomarkers for assessing the immune state in rheumatoid arthritis and their application in a cellular therapy clinical trial
Towards a cure for early rheumatoid arthritis
Using core genes and pathways to stratify rheumatoid arthritis and predict outcomes in Rheumatoid Arthritis
Exploiting methodological and technological innovations for targeted treatment and precision medicine
Identification of immune cell types predicting response to treatment with biologics in rheumatoid arthritis

Original classification

Research Grant

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