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Abstract: PO1924

Comparison of Proteomic Methods in Evaluating Biomarker-AKI Associations in Cardiac Surgery Patients

Session Information

Category: Pathology and Lab Medicine

  • 1600 Pathology and Lab Medicine

Authors

  • Liu, Richard Xiuri, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
  • Thiessen Philbrook, Heather, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
  • Ramachandran, Vasan S., Boston University School of Medicine, Boston, Massachusetts, United States
  • Coresh, Josef, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, United States
  • Ganz, Peter, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, California, United States
  • Bonventre, Joseph V., Brigham and Women's Hospital, Boston, Massachusetts, United States
  • Kimmel, Paul L., National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States
  • Parikh, Chirag R., Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
Background

Although immunoassays are the most widely used protein measurement method, aptamer-based methods such as the SomaScan platform can quantify up to 7,000 proteins per sample, creating new opportunities for unbiased discovery.

Methods

In a substudy of the TRIBE-AKI cohort, preop and postop plasma samples from 294 patients with previous immunoassay measurements were analyzed using the SomaScan platform. Inter-platform Spearman correlations (rs) and AKI associations were compared across 30 preop and 34 postop immunoassay-aptamer pairs. Possible factors contributing to inter-platform differences were tested for association with inter-platform correlation, including target protein, experimental, immunoassay, and aptamer characteristics.

Results

The median rs was 0.54 (IQR 0.34-0.83) in postop samples and 0.41 (IQR 0.21-0.69) in preop samples. We observed a strong association between rs and biomarker molarity, with Spearman correlation 0.64 preop and 0.53 postop. No strong associations with other factors were found, including %CVs of both platforms and storage time.
We observed significant immunoassay-AKI associations for 13 proteins preop and 24 postop, and SomaScan-AKI associations for 8 proteins preop and 12 postop. All significant AKI associations as measured by SomaScan were also significant as measured by immunoassay. AKI odds ratios were significantly different (P <0.05) between platforms in 4 (14%) pairs, none of which had rs >0.50.

Conclusion

Although similar AKI associations were observed overall, biomarkers with high physiological concentrations tended to have the best inter-platform operability. Aptamer assays provide unprecedented coverage, excellent precision, and promise for disease associations, but interpretation of results should keep in mind a broad range of correlations with immunoassays.

Funding

  • NIDDK Support