Presynaptic dopaminergic imaging as a neurodegeneration staging biomarker in the alpha-synucleinopathy continuum
Year: 2026
Type: article
Study design: Observational Study
Abstract: PURPOSE: To define how dopamine transporter (DaT) SPECT can be used to stage neurodegeneration in neuronal alpha-synucleinopathy patients at the individual level. METHODS: This is an international multicenter study involving 1067 subjects (mean age 69.8 ± 8.7 years; 63.2% males) who underwent DaT-SPECT as a neurodegeneration biomarker. We enrolled 277 controls, 400 patients with idiopathic/isolated REM sleep behavior disorder (iRBD), representing the prodromal alpha-synucleinopathy stage, and 390 patients with an overt stage, including 175 with overt Parkinson’s disease (oPD) and 215 with overt dementia with Lewy bodies (oDLB). iRBD patients were followed over time and were stratified as non-converters (ncRBD, n = 232) or converters (cRBD, n = 168). The ability of DaT-SPECT to stage the neuronal alpha-synucleinopathy continuum was evaluated using forward stepwise logistic regression models, assuming that this stratification reflects progressive neurodegeneration stages (controls, ncRBD, cRBD, and overt PD/DLB). RESULTS: The combination of the most affected putamen and the least affected caudate best staged patients across the continuum (p < 0.001). Our data suggest that the most affected putamen z-scores can be used to define three levels of neurodegeneration, such as undetected (above − 1), moderate (between − 1 and − 2), and severe (below − 2). Cox regression analysis in iRBD patients showed that these cutoffs predicted phenoconversion (hazard ratios 3.10–5.03), outperforming clinical risk metrics (MDS-UPDRS-III, MMSE, and hyposmia) for overall and motor-predominant phenoconversion. CONCLUSION: DaT-SPECT z-score thresholds provide a ready-to-use three-tier staging system for alpha-synucleinopathies, enabling objective assessment of neurodegeneration severity and phenoconversion risk at the individual level.
Authors: Dario Arnaldi, Pietro Mattioli, Beatrice Orso, Stefano Raffa, Francesco Lanfranchi, Federico Massa, Alex Iranzo, Andres Perissinotti, Aida Niñerola-Baizán, Carles Gaig, Monica Serradell, Angelica Montini, Gerard Mayà, Amaia Muñoz-Lopetegi, Claudio Liguori, Mariana Fernandes, Fabio Placidi, Agostino Chiaravalloti, Karel Šonka, Petr Dušek, David Zogala, Jiri Trnka, Bradley F. Boeve, Toji Miyagawa, Val J. Lowe, Tomoyuki Miyamoto, Masayuki Miyamoto, Monica Puligheddu, Michela Figorilli, Alessandra Serra, Michele T. Hu, Johannes C. Klein, Frederik Bes, Dieter Kunz, Valérie Cochen De Cock, Delphine De Verbizier, Giuseppe Plazzi, Elena Antelmi, Fabio Pizza, Michele Terzaghi, Irene Bossert, Kristína Kulcsárová, Valentina Garibotto, Nicolas Nicastro, Aurelien Lathuilière, Laura Bonanni, Silvia Morbelli, Monica Roascio, Gabriele Arnulfo, Matteo Pardini
Institutions: Ospedale Policlinico San Martino, University of Genoa, Biomedical Research Networking Center on Neurodegenerative Diseases, Hospital Clínic de Barcelona, Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Universitat de Barcelona, University of Rome Tor Vergata, Policlinico Tor Vergata, Istituto Neurologico Mediterraneo, Charles University, General University Hospital in Prague, Mayo Clinic, Dokkyo Medical University Saitama Medical Center, Dokkyo Medical University Hospital, University of Cagliari, University of Oxford, St. Hedwig-Krankenhaus, Charité - Universitätsmedizin Berlin, IMT Mines Alès, EuroMov Digital Health in Motion, Centre Hospitalier Universitaire de Montpellier, University of Modena and Reggio Emilia, Istituto delle Scienze Neurologiche di Bologna, University of Verona, University of Bologna, University of Pavia, Istituti Clinici Scientifici Maugeri, University of Pavol Jozef Šafárik, Univerzitná Nemocnica Louisa Pasteura, University Hospital of Geneva, University of Chieti-Pescara, Azienda Ospedaliera Citta' della Salute e della Scienza di Torino, University of Turin, Istituto Giannina Gaslini
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W7147417939