How to Multiplex Analysis of Autoimmune Biomarkers

At Protagen, scientists enlist xMAP® Technology to characterize autoantibodies

Multiplex analysis of autoantibodies is an effective way to understand autoimmune disease, discover important biomarkers, and stratify patients into subgroups, according to Hans-Dieter Zucht, Head of Technology at Protagen. The company uses a biomarker discovery platform for autoimmune disease and immuno-oncology applications.

In a presentation about autoantibody reactivities given at the xMAP Connect conference, Zucht spoke about the use of Luminex multiplexing technology for a workflow where the analytes are autoantibodies that target the host, and recombinant proteins are the bait. By multiplexing these reactions, Zucht and his team generate as many as 10 million data points per year. “This allows us to mine for [up to] 8,000 different targets in the course of different diseases,” he said.

Practical Multiplexing Tips

Zucht’s talk offers viewers practical tips about how to embark on this experimental process, from establishing the multiplex panel to making sense of the data. He advised prospective users to prioritize characterization of their markers before putting them in a panel, and to take care with steps that can sometimes be problematic: defining thresholds, calibrating assays, assessing model stability, and more.

Once autoantibodies have been analyzed, scientists can delve into the resulting patterns to track biomarker signatures, determine marker prevalence, and figure out the most useful ways of stratifying patients. For example, in lupus, markers are effective for grouping patients by disease severity.

Zucht showed how this process is implemented at Protagen, which deploys the information to cluster both antigens and patients. He also recommended the use of Knime or a similar tool for automating data analysis and integrating Luminex data sets with other information generated about markers of interest.

Zucht showed how this process is implemented at Protagen, which deploys the information to cluster both antigens and patients. He also recommended the use of Knime or a similar tool for automating data analysis and integrating Luminex data sets with other information generated about markers of interest.

For more technical detail, check out the 20-minute presentation video.

Resources

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