Reanalyzing Olink Proteomics Data with Omics Playground: Uncovering Therapeutic Drug Potential for Sarcoidosis
Published on October 14th, 2024
by Axel Martinelli
⏱ 5 min read
Introduction
Omics Playground supports a wide variety of transcriptomics and proteomics technologies, including Olink Proteomics, and allows for the comparison between proteomics and transcriptomics data.
To test the platform with a dataset that contains both Olink and transcriptomics data, I selected the published research by William Damsky, MD, PhD and colleagues under the supervision of Brett King from the Yale School of Medicine on the therapeutic properties of tofacitinib, a Janus kinase (JAK) inhibitor, for the treatment of sarcoidosis.
What is Sarcoidosis and Insights Into the Study
Sarcoidosis is an inflammatory disease that can affect various organs in the body, including the skin, and in chronic cases can lead to organ damage.
As part of their study, Damsky and colleagues collected blood samples from patients and healthy volunteers and then sequenced protein content using the Olink Explore 1536 panel. They also obtained skin biopsies that were then sequenced by bulk RNAseq.
I injected both data types in the platform and then used it to identify the main features of sarcoidosis and identify drugs with therapeutic potential via the drug connectivity (drug cmap) module.
Note: To analyze Olink proteomics data with Omics Playground, the data must first be transformed into a matrix format. You can read more on how to format your input data for Omics Playground in our guide.
Transcriptomics and Proteomics Comparative Analysis with Omics Playground
The comparison of transcriptomics and proteomics data indicated that in both datasets (X-axis: proteomics, Y-axis: transcriptomics) pro-inflammatory proteins, including several cytokines, were upregulated (Figure 1A).
In particular, both the transcriptomics and Olink dataset analyses revealed chitinase 1 (CHIT1), a protein secreted by activated macrophages, as one of the most upregulated proteins/genes. It has been shown that CHIT1 is a reliable biomarker for active sarcoidosis and is correlated with disease severity.
Querying the drug cmap with the Olink dataset indicated ruxolitinib as the most likely inhibitor of the disease, as shown the by significant negative correlation with the sarcoidosis protein expression profile in the GSEA-like plot (Figure 1B). Ruxolitinib is a JAK-inhibitor that has been shown to reduce several immunologic mechanisms implicated in sarcoidosis and shares the same mechanism of action as tofacitinib.
Conclusion
To conclude, Omics Playground identified a strong correlation between Olink proteomics data and RNAseq data that highlighted the inflammatory nature of sarcoidosis and the prominent role of protein CHIT1 in both skin biopsies and blood samples.
Furthermore, Omics Playground also identified a JAK-inhibitor as a potential therapy for the disease based on the Olink blood data. This correlates well with the efficacy of tofacitinib, another JAK inhibitor, in the treatment of sarcoidosis, as shown in the article by Damsky et al.
The ability to interactively explore analysis results provides researchers with a powerful tool to gain deeper insights into complex biological datasets. With Omics Playground, users can easily visualize the relationships between proteomics and transcriptomics data, facilitating a more comprehensive understanding of disease mechanisms and potential therapeutic targets.
The platform has been designed to support the proteomics community by offering an intuitive interface and advanced analytical capabilities. You can now upload Olink NPX files directly into the platform, no need to split abundance tables and sample metadata. Omics Playground automatically detects the Olink format, builds the necessary structure internally, and gets you straight to analysis. This new functionality streamlines your workflow and helps you go from data to insights faster.
By enabling researchers with interactive data discovery, Omics Playground helps scientists accelerate discoveries, and ultimately drive innovation in proteomics research.
Interactively Explore Your Proteomics Data with Omics Playground!
About the Author
Axel Martinelli’s academic background is in molecular biology and parasitology. He earned a Ph.D. on the genetics of strain-specific immunity against malaria infections and a master’s degree in bioinformatics with specialization in the analysis of omics data. During his postdoctoral career, he worked on genomics and transcriptomics studies and is currently the head of biology at Bigomics Analytics.