Identification of Novel α-Synuclein Isoforms in Human Brain Tissue by using an Online NanoLC-ESI-FTICR-MS Method

Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB) are neurodegenerative diseases that are characterized by intra-neuronal inclusions of Lewy bodies in distinct brain regions. These inclusions consist mainly of aggregated α-synuclein (α-syn) protein. The present study used immunoprecipitation combined with nanoflow liquid chromatography (LC) coupled to high resolution electrospray ionization Fourier transform ion cyclotron resonance tandem mass spectrometry (ESI-FTICR-MS/MS) to determine known and novel isoforms of α-syn in brain tissue homogenates. N-terminally acetylated full-length α-syn (Ac-α-syn1–140) and two N-terminally acetylated C-terminally truncated forms of α-syn (Ac-α-syn1–139 and Ac-α-syn1–103) were found. The different forms of α-syn were further studied by Western blotting in brain tissue homogenates from the temporal cortex Brodmann area 36 (BA36) and the dorsolateral prefrontal cortex BA9 derived from controls, patients with DLB and PD with dementia (PDD). Quantification of α-syn in each brain tissue fraction was performed using a novel enzyme-linked immunosorbent assay (ELISA)

Clinical mass spectrometry in neuroscience. Proteomics and peptidomics.

In this review we discuss the merits and drawbacks with the use of proteomic and peptidomic strategies for identification of proteins and peptides in their multidimensional interactions in complex biological processes. The progress in proteomics and peptidomics during the last years offer us new challenges to study changes in the protein and peptide synthesis. These strategies also offer new tools to follow post-translational modifications and other disturbed chemical processes that may be indicative of pathophysiological alteration(s). Furthermore these techniques can contribute to improvements in the diagnosis and therapy of neurodegenerative diseases, such as Alzheimer\u27s disease, and psychiatric diseases, as depression and post traumatic stress disorders. We also consider different practical aspects of the applications of mass spectrometry in clinical neuroscience, illustrated by example from our laboratories. The new proteomic and peptidomic strategies will further enable the progress for clinical neuroscience research

The neurophysiological brain-fingerprint of Parkinson’s diseaseResearch in context

Summary: Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson’s disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson’s disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson’s brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson’s symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson’s brain-fingerprint aligns with that of neurotransmitter systems affected by the disease’s pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson’s disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson’s disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311)