Problems & Chances in Autoimmunity Biomarker Discovery
The Immunity Fingerprint
The immune system is far from a static, pre-determined range of responses. As we go through our lives, the environment sculpts immunity, driving the body to produce billions of antigen-specific antibodies. What is more, a baseline of autoantibodies exists in all humans – and the stability and reactivity of this fingerprint determine a wide range of diseases, from autoimmune conditions to cancer and diabetes.
A Growing Concern or an Opportunity?
Autoimmunity is on the rise. Not only are we seeing an increase in autoimmune disease occurrence, but we’re understanding the inflammatory aspect of high-morbidity and mortality conditions like heart disease and malignancies. The relevance of antibody research spans way beyond autoimmune disease. Thus, the steady increase of autoimmunity patients that walks through clinic doors is both a concern and an opportunity:
- From a physician´s perspective, we need better tools for diagnosis (especially early identification) and efficient, targeted treatment options.
- On the research side, we have an improved understanding of autoimmunity as an underlying mechanism for a variety of conditions. This means we can focus our efforts on studying autoantibodies as a way to create these better diagnostic and treatment options.
The bottom line? We need accurate biomarkers – sooner rather than later. But how can we find them? Here is what you need to know:
The Search for Biomarkers
The traditional approach to biomarker discovery goes something like this:
- Patients walk in with a set of symptoms, identified as a certain disorder.
- You look at the cause of disease and search for a condition-specific biological process.
- Then form a hypothesis about the suitable biomarkers and test it using standard methods such as ELISA and Western Blot.
While this method provides very clear data, it is a bottom-up approach that may not work for autoimmune diseases. In conditions like SLE, where the cause is unclear, testing separate markers through classic methods is deadly expensive. But the cost isn´t even the most challenging aspect. Hypothesis-based models are highly biased because they rely on a previous understanding of the disease. Since our understanding of autoimmunity is only just developing, can you really trust that you´ll “stumble” on the biomarker with this approach? Fortunately, there is a better way:
Are Protein Arrays Your Supertool?
On the opposite end of antibody-based biomarker discovery are large-scale methods such as protein arrays. This is a top-down method where you can start with symptomatology alone, identify individual autoantibody profiles, and enjoy a high chance of discovery in a single experiment. Our protein arrays use a membrane with spotted E.coli clones, expressing a wide range of human antigens. From full-length protein to fragments and neoantigens, you can look at over 10,000 interactions with a single run.
Why is this so exciting for autoimmunity research?
- Autoantibodies exist against a large portion of the human proteome.
- Systemic diseases like SLE (and most other autoimmune conditions) affect virtually all systems.
- The cause-to-disease pathway of these conditions is poorly understood, making biased methods a less efficient way of biomarker discovery.
In short, since autoimmunity involves such a wide range of targets, it makes sense to look into as many potential biomarkers as possible. Protein arrays allow you to streamline discovery in a cost and labour-effective way. What is more, you can use subarrays to narrow down your biomarker study even further. The process looks like this:
- Run your experiment using our hEXselect or UniPEx array, which test for thousands of antigens.
- Use the results to select potential antigens.
- We will create subarrays, based on your selection.
- Use the subarrays to run even more samples, enjoying the even lower time and money costs of your experiment.
Our Case Study for Systemic Lupus Erythematosus (SLE
Systemic Lupus Erythematosus (SLE) is a chronic inflammatory condition, the most common and serious type of lupus. Immune dysregulation results in autoantibody and immune complex formation, leading to tissue damage across systems. We know the autoimmune attack causes inflammation and contributes to SLE death causes. However, the cause of SLE remains unknown.
With a disease like this, where autoimmunity affects everything, how do we find something to latch on for biomarker discovery?
In a recent experiment our scientists ran, we analysed SLE patient sera, along with self-declared healthy donors. Using a protein array workflow, we got fast results with high data output. With our protein arrays, you can enjoy this high discovery power even with fewer sample sera (<50 µl), too.
What did we find out?
We presented the results at the 12th Autoimmunity Congress. If you missed out, you can still watch the presentation and download the poster: But, there is a larger conclusion than can be drawn from the setup.
Autoimmunity is a complex, often poorly understood topic that can offer new perspectives toward rheumatoid diseases and other conditions. With multisystem disorders, biomarker discovery can be a challenge, because of the sheer range of proteome-targeted antibodies to be tested.
Our protein arrays allow you to check over 10,000 antigens in a single run – and with a smaller sample size. If you have SLE sera laying around, this is a great opportunity to identify potential biomarkers through a bias-free method.
Following this unbiased start to discovery, you can then design a detailed study to find the biomarker you are looking for. Follow-up experiments comparing antibody subclasses as well as disease variants and treatment pathways lead to a paper-ready result with the potential to change patients’ lives.
Ready to evaluate the potential for your project? Get a free brainstorming session!
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- Rees F, Doherty M, Grainge MJ, Lanyon P, Zhang W. The worldwide incidence and prevalence of systemic lupus erythematosus: a systematic review of epidemiological studies. Rheumatology (Oxford). 2017 Nov 1;56(11):1945–1961. DOI: 10.1093/rheumatology/kex260
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