ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2020
An automated clinical mass spectrometric method for identification and quantification of variant and wild-type amyloid-β 1-40 and 1-42 peptides in CSF.
Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05002699 (Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia), which is not on this map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia (IMPACT-AD BC)
Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- A Multiplexed Quantitative Proteomics Approach to the Human Plasma Protein Signature.Biomedicines · 2024Article
- Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics.Molecular & cellular proteomics : MCP · 2024Review
- Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers.Clinical proteomics · 2024Review
- Mass spectrometry-based proteomics as an emerging tool in clinical laboratories.Clinical proteomics · 2023Review
- New Pathways Identify Novel Drug Targets for the Prevention and Treatment of Alzheimer's Disease.International journal of molecular sciences · 2023Review
- Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.Mass spectrometry reviews · 2023Review
- Proteoforms and their expanding role in laboratory medicine.Practical laboratory medicine · 2022Review
- The Diagnostic Potential of Amyloidogenic Proteins.International journal of molecular sciences · 2021Review
- An automated clinical mass spectrometric method for identification and quantification of variant and wild-type amyloid-β 1-40 and 1-42 peptides in CSF.Alzheimer's & dementia (Amsterdam, Netherlands) · 2020Article
- Clinical value of Alzheimer's disease biomarker testing.Alzheimer's & dementia (New York, N. Y.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionWe developed an automated liquid chromatography-tandem mass spectrometry high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method for multiplex quantification of wild-type (wt) amyloid β (Aβ) peptides 1-40 (Aβ40) and 1-42 (Aβ42) and detection of variant Aβ peptides in cerebrospinal fluid.
methodsThe multiplex Aβ HPLC-MS/MS assay was validated in a clinically accredited laboratory following regulatory guidelines, with Aβ42 calibration assigned to the ERM/IFCC certified reference material; sequence variants were additionally multiplexed into the method.
resultsSample preparation was fully automated on a liquid handler. The assay quantified wt-Aβ42 and wt-Aβ40 and detected sequence variants, when present, within the Aβ42 sequence. DISCUSSION: Extension of the HPLC-MS/MS approach for quantification of wt-Aβ42 and wt-Aβ40 to include known sequence variants increases analytical accuracy of the mass spectrometric approach and enables identification of cases of autosomal dominant Alzheimer's disease. Development of an automated workflow and selection of appropriate instrumentation enabled deployment of this method in routine clinical testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.