Table 1.

Strategies for overcoming key challenges in plasma proteomics

Correlated biomarkers often do not improve disease predictionSearch for uncorrelated (orthogonal) biomarkers either through: unbiased discovery experiments or targeted examination of novel pathways (including those identified by recent genetic association studies)
Complexity of the proteome in clinical samplesAssemble data from multiple large patient populations for comparison; incorporate emerging bioinformatics approaches
High abundance proteins in clinical samplesEvaluate emerging depletion techniques for high abundance plasma constituents; make use of improved mass spectrometry techniques with greater dynamic range
Validation of multiplex assaysCompare assays across each source of reagents in each specimen matrix; collaborate with laboratory standardization groups and agencies (e.g., National Institute of Standards, Clinical Laboratory Standards Institute); apply mass spectrometry approaches to multiplex protein quantification
False positive associations with high-throughput proteomic data analysisApply pathway/functional trend analysis
Heterogeneity in approach to clinical specimen acquisitionUse standardized specimen collection and storage protocols; expand studies of factors affecting analyses of clinical samples (e.g., freeze-thaw cycles, processing details)
Insufficient knowledge of the effect of growth and development on the normal proteomePopulation-based studies of the normal proteome in children