Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays.


Journal

PLoS pathogens
ISSN: 1553-7374
Titre abrégé: PLoS Pathog
Pays: United States
ID NLM: 101238921

Informations de publication

Date de publication:
20 Sep 2024
Historique:
received: 09 07 2024
accepted: 30 08 2024
medline: 20 9 2024
pubmed: 20 9 2024
entrez: 20 9 2024
Statut: aheadofprint

Résumé

Disease associated pathological aggregates of alpha-synuclein (αSynD) exhibit prion-like spreading in synucleinopathies such as Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Seed amplification assays (SAAs) such as real-time quaking-induced conversion (RT-QuIC) have shown high diagnostic sensitivity and specificity for detecting proteopathic αSynD seeds in a variety of biospecimens from PD and DLB patients. However, the extent to which relative proteopathic seed concentrations are useful as indices of a patient's disease stage or prognosis remains unresolved. One feature of current SAAs that complicates attempts to correlate SAA results with patients' clinical and other laboratory findings is their quantitative imprecision, which has typically been limited to discriminating large differences (e.g. 5-10 fold) in seed concentration. We used end-point dilution (ED) RT-QuIC assays to determine αSynD seed concentrations in patient biospecimens and tested the influence of various assay variables such as serial dilution factor, replicate number and data processing methods. The use of 2-fold versus 10-fold dilution factors and 12 versus 4 replicate reactions per dilution reduced ED-RT-QuIC assay error by as much as 70%. This enhanced assay format discriminated as little as 2-fold differences in αSynD seed concentration besides detecting ~2-16-fold seed reductions caused by inactivation treatments. In some scenarios, analysis of the data using Poisson and midSIN algorithms provided more consistent and statistically significant discrimination of different seed concentrations. We applied our improved assay strategies to multiple diagnostically relevant PD and DLB antemortem patient biospecimens, including cerebrospinal fluid, skin, and brushings of the olfactory mucosa. Using ED αSyn RT-QuIC as a model SAA, we show how to markedly improve the inter-assay reproducibility and quantitative accuracy. Enhanced quantitative SAA accuracy should facilitate assessments of pathological seeding activities as biomarkers in proteinopathy diagnostics and prognostics, as well as in patient cohort selection and assessments of pharmacodynamics and target engagement in drug trials.

Identifiants

pubmed: 39302978
doi: 10.1371/journal.ppat.1012554
pii: PPATHOGENS-D-24-01429
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1012554

Informations de copyright

Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Déclaration de conflit d'intérêts

I have read the journal’s policy and the authors of this manuscript have the following competing interests: BC and CDO are inventors on some RT-QuIC assay patents.

Auteurs

Ankit Srivastava (A)

Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Hamilton, Montana, United States of America.

Qinlu Wang (Q)

Bioinformatics and Computational Biosciences Branch, National Institute of Allergy, and Infectious Diseases (NIAID), National Institutes of Health (NIH), Bethesda, Maryland, United States of America.

Christina D Orrù (CD)

Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Hamilton, Montana, United States of America.

Manel Fernandez (M)

Parkinson's Disease & Movement Disorders Unit, Neurology Service, Hospital Clínic I Universitari de Barcelona; IDIBAPS, CIBERNED (CB06/05/0018-ISCIII), ERN- RND, Institut Clínic de Neurociències (Maria de Maeztu Excellence Centre), Universitat de Barcelona. Barcelona, Catalonia, Spain.

Yaroslau Compta (Y)

Parkinson's Disease & Movement Disorders Unit, Neurology Service, Hospital Clínic I Universitari de Barcelona; IDIBAPS, CIBERNED (CB06/05/0018-ISCIII), ERN- RND, Institut Clínic de Neurociències (Maria de Maeztu Excellence Centre), Universitat de Barcelona. Barcelona, Catalonia, Spain.

Bernardino Ghetti (B)

Indiana University School of Medicine, Indianapolis, Indiana, United States of America.

Gianluigi Zanusso (G)

Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.

Wen-Quan Zou (WQ)

Departments of Pathology and Neurology, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.
Institute of Neurology, Jiangxi Academy of Clinical Medical Sciences, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, China.

Byron Caughey (B)

Laboratory of Neurological Infections and Immunity, Rocky Mountain Laboratories, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Hamilton, Montana, United States of America.

Catherine A A Beauchemin (CAA)

Department of Physics, Toronto Metropolitan University, Toronto, Canada.
Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) at RIKEN, Wako, Japan.

Classifications MeSH