Synthetic plasma pool cohort correction for affinity-based proteomics datasets allows multiple study comparison

Area of Science:

• Proteomics
• Genomics
• Biotechnology

Background:

• Quantitative proteomics links genomics to human diseases by analyzing protein levels.
• OLINK's Target 96 is a prominent affinity-based protein measurement method used in large cohorts like SCALLOP.
• Current methods for comparing OLINK Target 96 data across independent cohorts are logistically challenging and costly.

Purpose of the Study:

• To develop a robust and cost-efficient method for accurate quantitative comparison of OLINK Target 96 protein data across independent studies.
• To address the limitations of the 'biological bridging sample' approach in multi-cohort proteomics collaborations.

Main Methods:

• Development of the Synthetic Plasma Pool Cohort Correction (SPOC) approach.
• Utilizing an OLINK-composed synthetic plasma sample for normalization.
• Implementation in a federated data-sharing context, demonstrated with a sepsis use case.

Main Results:

• The SPOC correction method provides accurate and cost-efficient normalization for OLINK Target 96 data.
• The approach simplifies multi-cohort data comparison, overcoming logistical hurdles.
• Successful illustration of the method's utility in a sepsis research scenario.

Conclusions:

• The SPOC correction offers a practical solution for inter-cohort comparison of proteomics data.
• This method enhances collaboration and data sharing in large-scale proteomics studies.
• SPOC correction facilitates more accessible and efficient proteomic data analysis across diverse research settings.