Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and...

Area of Science:

• Biochemistry
• Proteomics
• Ophthalmology

Background:

• Human tear fluid is a complex mixture of compounds with dynamic and variable concentrations.
• Understanding tear composition variability is crucial for identifying tear functions and limitations as biomarker sources.

Purpose of the Study:

• To quantitatively analyze variations in tear protein profiles of healthy volunteers.
• To identify personal characteristics within tear fluid proteomes and immunoglobulin composition.
• To explore the potential of tear fluid as a biomarker for personalized medicine.

Main Methods:

• Quantitative proteomic analysis of human tear samples from healthy volunteers.
• Evaluation of normalization and outlier exclusion methods to manage data variance.
• Statistical analysis, including cluster analysis and correlation analysis, to interpret proteomic data.

Main Results:

• High day-to-day and inter-eye variations were observed in tear volume, protein content, and composition.
• Despite variability, tear proteome and immunoglobulin profiles exhibit statistically significant personal characteristics.
• Correlation analysis identified protein clusters linked to their sources, providing insights into tear biochemistry.

Conclusions:

• Human tear fluid proteome exhibits personal characteristics, despite significant intrapersonal variations.
• Statistical evaluation of tear proteome dynamics offers insights into the biochemical background of tears.
• This pilot study supports the use of tear fluid for personalized protein profiling in medicine.