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The presence of protein aggregates is a hallmark of many neurodegenerative diseases, including Parkinson's disease (PD), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Traditionally, each disease has been associated with the aggregation of specific proteins, which serve as disease-specific biomarkers. For example, aggregates of α-synuclein (α-syn) are found in α-synucleinopathies such as PD, dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). Similarly, AD is characterized by aggregates of amyloid-beta (Aβ) and tau proteins. However, it has been observed that these protein aggregates can also occur in other neurodegenerative diseases, contributing to disease progression. For instance, α-syn aggregates have been detected in AD, Down syndrome, Huntington's disease, prion diseases, and various forms of FTLD. Similarly, Aβ aggregates have been found in conditions like DLB and PD. Tau aggregates, in addition to being present in primary tauopathies, have been identified in prion diseases, α-synucleinopathies, and cognitively healthy aged subjects. Finally, aggregates of TDP-43, typically associated with FTLD and amyotrophic lateral sclerosis (ALS), have been observed in AD, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), MSA, DLB, and other neurodegenerative diseases. These findings highlight the complexity of protein aggregation in neurodegeneration and suggest potential interactions and common mechanisms underlying different diseases. A deeper understating of this complex scenario may eventually lead to the identification of a better elucidation of the pathogenetic mechanisms of these devastating conditions and hopefully new therapeutic stragegies., Competing Interests: The authors declare no conflict of interest. Given their role as Guest Editor member of FBL, Fabio Moda and Giorgio Giaccone had no involvement in the peer-review of this article and has no access to information regarding its peer-review. Full responsibility for the editorial process for this article was delegated to Antoni Camins., (© 2023 The Author(s). Published by IMR Press.)

Background: The current diagnosis of Alzheimer's disease (AD) is based on a series of analyses which involve clinical, instrumental and laboratory findings. However, signs, symptoms and biomarker alterations observed in AD might overlap with other dementias, resulting in misdiagnosis., Methods: Here we describe a new diagnostic approach for AD which takes advantage of the boosted sensitivity in biomolecular detection, as allowed by seed amplification assay (SAA), combined with the unique specificity in biomolecular recognition, as provided by surface-enhanced Raman spectroscopy (SERS)., Results: The SAA-SERS approach supported by machine learning data analysis allowed efficient identification of pathological Aβ oligomers in the cerebrospinal fluid of patients with a clinical diagnosis of AD or mild cognitive impairment due to AD., Conclusions: Such analytical approach can be used to recognize disease features, thus allowing early stratification and selection of patients, which is fundamental in clinical treatments and pharmacological trials., (© 2023. The Author(s).)