Analysis of Plasma Proteins for Biomarker Discovery
Author Information
Author(s): Yadav Amit Kumar, Bhardwaj Gourav, Basak Trayambak, Kumar Dhirendra, Ahmad Shadab, Priyadarshini Ruby, Singh Ashish Kumar, Dash Debasis, Sengupta Shantanu
Primary Institution: Institute of Genomics and Integrative Biology (Council of Scientific and Industrial Research), Delhi, India
Hypothesis
The study aims to identify non-targeted proteins removed during the immunoaffinity depletion of high-abundance proteins from plasma.
Conclusion
The study found that non-targeted proteins are significantly present in the bound fractions of plasma, which are often overlooked in biomarker discovery.
Supporting Evidence
- Plasma is a complex mixture of proteins, making biomarker discovery challenging.
- Immunoaffinity depletion can improve the detection of low-abundance proteins.
- The study identified 101 proteins with high confidence from the bound fractions.
- Non-targeted proteins may be lost during the depletion process, affecting biomarker discovery.
- Using multiple algorithms for peptide identification increases statistical confidence.
- Many identified proteins have been previously associated with disease states.
- High concordance was found between identified proteins and existing protein databases.
- An integrative analysis approach is recommended for better biomarker discovery.
Takeaway
Scientists looked at blood samples to find important proteins that could help diagnose diseases, and they discovered that some proteins are lost when trying to remove the more common ones.
Methodology
Three plasma samples were depleted using three different MARS cartridges, and the eluted fractions were analyzed using gelC-MS and bioinformatics.
Potential Biases
Potential bias may arise from the reliance on multiple algorithms for peptide identification, which could affect the accuracy of protein inference.
Limitations
The study did not explore the specific interactions between non-targeted proteins and targeted proteins in detail.
Participant Demographics
Three healthy individuals provided blood samples for the study.
Statistical Information
P-Value
<1%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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