Biomarker-Driven Analysis Using High-Throughput Approaches in Neuroinflammation and Neurodegenerative Diseases.

Abstract

Aging is responsible for homeostatic dysregulation and the primary risk for neurodegenerative diseases. The main signaling pathways may regulateinflammatory-related disorders and neurodegenerationinclude genomic instability, cell senescence, and mitochondria dysfunction. The use of high-throughput technologies has emerged as a powerful approach to the rapid discovery of many candidate biomarkersfor age-related diseases. Varioustypes of molecules, such as nucleic acids, proteins, or metabolites, can serve as soluble factors in clinical practice with deviationsin their normal biological levels being an indicationof an underlying diseasestate. The development of multifactorialbiomarkersbased on models involvingmolecular alterations in complex disorders mayalso provide specific challenges for translating biologicalfindings and targeted diagnostic tools. As diseases are often regulated by a multiset of markers that coordinate and interact each otherin a complex signaling network to maintain holisticprocesses within a cell, potent network-based approaches to data-driven biomarker identification are required. System-based biomarker discovery pipelines can offeran extraordinary adjustmentopportunity for data heterogeneity and limitation, whereas integrated analysis of distinct networks clusterscan provide important information for the early detection of intracellularpathogenic processes as well as for monitoring the response to treatment.