Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in...

Area of Science:

• Biomedical Informatics
• Systems Biology
• Trauma Research

Background:

• Trauma is a leading cause of death in young adults, with limited understanding of post-injury biological mechanisms leading to multiple organ failure (MOF).
• Cytokine levels are crucial in trauma outcomes, but analyzing their role in intracellular signaling pathways is complex due to data heterogeneity.
• Understanding temporal changes in molecular pathways is vital for developing targeted therapies for trauma-induced MOF.

Purpose of the Study:

• To present the Pathway Semantics Algorithm (PSA) for analyzing temporal biological pathway data.
• To discover novel biomedical hypotheses regarding molecular mechanisms in trauma and MOF.
• To investigate the role of cytokines in MOF development using a prospective clinical study.

Main Methods:

• Developed the Pathway Semantics Algorithm (PSA), employing matrix algebra for node and edge analyses of biological pathways over time.
• Utilized data from a prospective clinical study of cytokines in MOF at a major US trauma center.
• Introduced XTALK, a measure of cross-pathway interference, within the PSA edge analysis.

Main Results:

• PSA identified seven computationally evoked molecules differentiating MOF from non-MOF (NMOF) outcomes within 24 hours post-trauma; three were novel associations.
• Molecular interaction patterns, including activation, expression, inhibition, and transcription, showed dynamic changes over time and with outcome.
• PSA edge analysis indicated that timing and specific functional relationships are critical for effective molecularly-based diagnosis, prognosis, or therapy.

Conclusions:

• The PSA provides a novel computational approach for in silico discovery of biomedical hypotheses from complex biological data.
• Identifying specific molecules and their temporal interaction patterns offers potential for improved diagnostics and therapeutics in trauma care.
• Understanding dynamic molecular crosstalk is key to predicting and managing MOF following severe injury.