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

Autor: Jason da Silva Castanheira, Alex I. Wiesman, Justine Y. Hansen, Bratislav Misic, Sylvain Baillet, John Breitner, Judes Poirier, Pierre Bellec, Véronique Bohbot, Mallar Chakravarty, Louis Collins, Pierre Etienne, Alan Evans, Serge Gauthier, Rick Hoge, Yasser Ituria-Medina, Gerhard Multhaup, Lisa-Marie Münter, Natasha Rajah, Pedro Rosa-Neto, Jean-Paul Soucy, Etienne Vachon-Presseau, Sylvia Villeneuve, Philippe Amouyel, Melissa Appleby, Nicholas Ashton, Daniel Auld, Gülebru Ayranci, Christophe Bedetti, Marie-Lise Beland, Kaj Blennow, Ann Brinkmalm Westman, Claudio Cuello, Mahsa Dadar, Leslie-Ann Daoust, Samir Das, Marina Dauar-Tedeschi, Louis De Beaumont, Doris Dea, Maxime Descoteaux, Marianne Dufour, Sarah Farzin, Fabiola Ferdinand, Vladimir Fonov, Julie Gonneaud, Justin Kat, Christina Kazazian, Anne Labonté, Marie-Elyse Lafaille-Magnan, Marc Lalancette, Jean-Charles Lambert, Jeannie-Marie Leoutsakos, Laura Mahar, Axel Mathieu, Melissa McSweeney, Pierre-François Meyer, Justin Miron, Jamie Near, Holly NewboldFox, Nathalie Nilsson, Pierre Orban, Cynthia Picard, Alexa Pichet Binette, Jean-Baptiste Poline, Sheida Rabipour, Alyssa Salaciak, Matthew Settimi, Sivaniya Subramaniapillai, Angela Tam, Christine Tardif, Louise Théroux, Jennifer Tremblay-Mercier, Stephanie Tullo, Irem Ulku, Isabelle Vallée, Henrik Zetterberg, Vasavan Nair, Jens Pruessner, Paul Aisen, Elena Anthal, Alan Barkun, Thomas Beaudry, Fatiha Benbouhoud, Jason Brandt, Leopoldina Carmo, Charles Edouard Carrier, Laksanun Cheewakriengkrai, Blandine Courcot, Doris Couture, Suzanne Craft, Christian Dansereau, Clément Debacker, René Desautels, Sylvie Dubuc, Guerda Duclair, Mark Eisenberg, Rana El-Khoury, Anne-Marie Faubert, David Fontaine, Josée Frappier, Joanne Frenette, Guylaine Gagné, Valérie Gervais, Renuka Giles, Renee Gordon, Clifford Jack, Benoit Jutras, Zaven Khachaturian, David Knopman, Penelope Kostopoulos, Félix Lapalme, Tanya Lee, Claude Lepage, Illana Leppert, Cécile Madjar, David Maillet, Jean-Robert Maltais, Sulantha Mathotaarachchi, Ginette Mayrand, Diane Michaud, Thomas Montine, John Morris, Véronique Pagé, Tharick Pascoal, Sandra Peillieux, Mirela Petkova, Galina Pogossova, Pierre Rioux, Mark Sager, Eunice Farah Saint-Fort, Mélissa Savard, Reisa Sperling, Shirin Tabrizi, Pierre Tariot, Eduard Teigner, Ronald Thomas, Paule-Joanne Toussaint, Miranda Tuwaig, Vinod Venugopalan, Sander Verfaillie, Jacob Vogel, Karen Wan, Seqian Wang, Elsa Yu, Isabelle Beaulieu-Boire, Pierre Blanchet, Sarah Bogard, Manon Bouchard, Sylvain Chouinard, Francesca Cicchetti, Martin Cloutier, Alain Dagher, Clotilde Degroot, Alex Desautels, Marie Hélène Dion, Janelle Drouin-Ouellet, Anne-Marie Dufresne, Nicolas Dupré, Antoine Duquette, Thomas Durcan, Lesley K. Fellows, Edward Fon, Jean-François Gagnon, Ziv Gan-Or, Angela Genge, Nicolas Jodoin, Jason Karamchandani, Anne-Louise Lafontaine, Mélanie Langlois, Etienne Leveille, Martin Lévesque, Calvin Melmed, Oury Monchi, Jacques Montplaisir, Michel Panisset, Martin Parent, Minh-Thy Pham-An, Ronald Postuma, Emmanuelle Pourcher, Trisha Rao, Jean Rivest, Guy Rouleau, Madeleine Sharp, Valérie Soland, Michael Sidel, Sonia Lai Wing Sun, Alexander Thiel, Paolo Vitali
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: EBioMedicine, Vol 105, Iss , Pp 105201- (2024)
Druh dokumentu: article
ISSN: 2352-3964
46662561
DOI: 10.1016/j.ebiom.2024.105201
Popis: 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).
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