Multi-analyte proteomic analysis identifies blood-based neuroinflammation, cerebrovascular and synaptic biomarkers in preclinical Alzheimer's disease.

Autor: Zeng X; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Lafferty TK; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Sehrawat A; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Chen Y; Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, 15213, USA., Ferreira PCL; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Bellaver B; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Povala G; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Kamboh MI; Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA., Klunk WE; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Cohen AD; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Lopez OL; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA., Ikonomovic MD; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.; Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA., Pascoal TA; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Ganguli M; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA.; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA., Villemagne VL; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA., Snitz BE; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA., Karikari TK; Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA. Karikaritk@upmc.edu.
Jazyk: angličtina
Zdroj: Molecular neurodegeneration [Mol Neurodegener] 2024 Oct 10; Vol. 19 (1), pp. 68. Date of Electronic Publication: 2024 Oct 10.
DOI: 10.1186/s13024-024-00753-5
Abstrakt: Background: Blood-based biomarkers are gaining grounds for the detection of Alzheimer's disease (AD) and related disorders (ADRDs). However, two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction. A novel proteomic method for pre-selected analytes, based on proximity extension technology, was recently introduced. Referred to as the NULISAseq CNS disease panel, the assay simultaneously measures ~ 120 analytes related to neurodegenerative diseases, including those linked to both core (i.e., tau and amyloid-beta (Aβ)) and non-core AD processes. This study aimed to evaluate the technical and clinical performance of this novel targeted proteomic panel.
Methods: The NULISAseq CNS disease panel was applied to 176 plasma samples from 113 individuals in the MYHAT-NI cohort of predominantly cognitively normal participants from an economically underserved region in southwestern Pennsylvania, USA. Classical AD biomarkers, including p-tau181, p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were independently measured using Single Molecule Array (Simoa) and correlations and diagnostic performances compared. Aβ pathology, tau pathology, and neurodegeneration (AT(N) statuses) were evaluated with [ 11 C] PiB PET, [ 18 F]AV-1451 PET, and an MRI-based AD-signature composite cortical thickness index, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA and neuroimaging-determined AT(N) biomarkers.
Results: NULISA concurrently measured 116 plasma biomarkers with good technical performance (97.2 ± 13.9% targets gave signals above assay limits of detection), and significant correlation with Simoa assays for the classical biomarkers. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878-0.983). Fourteen markers were significantly decreased in Aβ-PET + participants, including TIMP3, BDNF, MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET + participants. Novel plasma biomarkers with tau PET-dependent longitudinal changes included proteins associated with neuroinflammation, synaptic function, and cerebrovascular integrity, such as CHIT1, CHI3L1, NPTX1, PGF, PDGFRB, and VEGFA; all previously linked to AD but only reliable when measured in cerebrospinal fluid. The autophagosome cargo protein SQSTM1 exhibited significant association with neurodegeneration after adjusting age, sex, and APOE ε4 genotype.
Conclusions: Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes, consistent with the recently revised biological and diagnostic framework. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.
(© 2024. The Author(s).)
Databáze: MEDLINE
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