Background: An ideal imaging biomarker for a neurodegenerative disorder should be able to measure abnormalities in the earliest stages of the disease. Objective: We investigated metabolic network changes in two independent cohorts of drug-naïve Parkinson's disease (PD) patients who have not been exposed to dopaminergic medication. Methods: We scanned 85 de novo, drug-naïve PD patients and 85 age-matched healthy control subjects from Italy (n = 96) and the United States (n = 74) with [18F]-fluorodeoxyglucose PET. All patients had clinical follow-ups to verify the diagnosis of idiopathic PD. Spatial covariance analysis was used to identify and validate de novo PD-related metabolic patterns in the Italian and U.S. cohorts. We compared the de novo PD-related metabolic patterns to the original PD-related pattern that was identified in more advanced patients who had been on chronic dopaminergic treatment. Results: De novo PD-related metabolic patterns were identified in each of the two independent cohorts of drug-naïve PD patients, and each differentiated PD patients from healthy control subjects. Expression values for these disease patterns were elevated in drug-naïve PD patients relative to healthy controls in the identification as well as in each of the validation subgroups. The two de novo PD-related metabolic patterns were topographically very similar to each other and to the original PD-related pattern. Conclusions: Reproducible PD-related patterns are expressed in de novo, drug-naïve PD patients. In PD, disease-related metabolic patterns have stereotyped topographies that develop independently of chronic levodopa treatment.

Metabolic network abnormalities in drug-naïve Parkinson's Disease

Morbelli, Silvia;
2020-01-01

Abstract

Background: An ideal imaging biomarker for a neurodegenerative disorder should be able to measure abnormalities in the earliest stages of the disease. Objective: We investigated metabolic network changes in two independent cohorts of drug-naïve Parkinson's disease (PD) patients who have not been exposed to dopaminergic medication. Methods: We scanned 85 de novo, drug-naïve PD patients and 85 age-matched healthy control subjects from Italy (n = 96) and the United States (n = 74) with [18F]-fluorodeoxyglucose PET. All patients had clinical follow-ups to verify the diagnosis of idiopathic PD. Spatial covariance analysis was used to identify and validate de novo PD-related metabolic patterns in the Italian and U.S. cohorts. We compared the de novo PD-related metabolic patterns to the original PD-related pattern that was identified in more advanced patients who had been on chronic dopaminergic treatment. Results: De novo PD-related metabolic patterns were identified in each of the two independent cohorts of drug-naïve PD patients, and each differentiated PD patients from healthy control subjects. Expression values for these disease patterns were elevated in drug-naïve PD patients relative to healthy controls in the identification as well as in each of the validation subgroups. The two de novo PD-related metabolic patterns were topographically very similar to each other and to the original PD-related pattern. Conclusions: Reproducible PD-related patterns are expressed in de novo, drug-naïve PD patients. In PD, disease-related metabolic patterns have stereotyped topographies that develop independently of chronic levodopa treatment.
2020
35
4
587
594
PET; Parkinson's disease; drug naïve; imaging biomarker; network analysis
Schindlbeck, Katharina A; Lucas-Jiménez, Olaia; Tang, Chris C; Morbelli, Silvia; Arnaldi, Dario; Pardini, Matteo; Pagani, Marco; Ibarretxe-Bilbao, Nar...espandi
File in questo prodotto:
File Dimensione Formato  
MovDisord_2020_Eidelberg.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 1 MB
Formato Adobe PDF
1 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1957331
Citazioni
  • ???jsp.display-item.citation.pmc??? 11
  • Scopus 23
  • ???jsp.display-item.citation.isi??? 19
social impact