Comprehensive review of bioanalytical methods and data-processing (including AI) for identifying and characterizing cytoskeletal proteins (e.g., tau and neuronal intermediate filaments) implicated in neurodegenerative disease pathology.

Useful as a methodological resource for detecting cytoskeletal biomarkers and profiling protein alterations that can support biomarker discovery or target validation related to Parkinson’s-associated cytoskeletal dysfunction, but it is a general methods review with limited PD-specific mechanistic…

Neurodegenerative diseases (NDs) are a heterogeneous group of progressive disorders characterized by the selective loss of neuronal structure or function, often leading to cognitive and/or motor dysfunction. Although NDs present clinical diversity, several of these diseases share a common pathological characteristic, which consists of the aggregation of cytoskeletal proteins in specific regions of the central nervous system (CNS). The cytoskeleton is an intricate network of filamentous proteins within the cytoplasm and plays a critical role in maintaining neuronal polarity, axonal transport, synaptic integrity, and overall cellular architecture. Structural and functional abnormalities in the cytoskeleton, especially in neuronal intermediate filament (IF) proteins and microtubule-associated protein tau (MAPT), can compromise neuronal function, inciting inflammation and leading to neuron cell death. So, cytoskeletal protein species can be considered biomarkers and provide guidance for treatments associated with NDs. Considering the complexity of the biological matrix and the molecular mechanisms involved, the identification and characterization of cytoskeletal protein abnormalities require robust and sensitive analytical tools, comprising sample preparation protocol, advanced instrumental techniques and data processing algorithms. So, this chapter provides a comprehensive review of the bioanalytical approaches employed in the investigation of cytoskeletal proteins involved in the pathogenesis of NDs. Also, some tools applied in data processing are discussed here, considering the combination of classical data analysis algorithms with artificial intelligence focused on the discovery of cytoskeletal biomarker proteins. Furthermore, a general discussion of the possible molecular mechanisms related to neuronal degeneration involving the main cytoskeletal proteins is presented.