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Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework
Devanarayan P, Devanarayan V, Llano DA, the Alzheimer’s Disease Neuroimaging Initiative (ADNI).. Journal of Alzheimer's disease : JAD, 2018-10-15
Topic: Amyloid, tau and blood-test diagnosis
The 2018 NIA-AA research framework proposes a classification system with beta- A myloid deposition, pathologic T au, and n eurodegeneration (ATN) for the diagnosis and staging of Alzheimer’s Disease (AD). Data from the ADNI (AD neuroimaging initiative) database can be utilized to identify diagnostic signatures for predicting AD progression, and to determine the utility of this NIA-AA research framework. Profiles of 320 peptides from baseline cerebrospinal fluid (CSF) samples of 287 normal, mild cognitive impairment (MCI) and AD subjects followed over a 3-10 year period were measured via multiple reaction monitoring (MRM) mass spectrometry.
Key findings
- Data from the ADNI (AD neuroimaging initiative) database can be utilized to identify diagnostic signatures for predicting AD progression, and to determine the utility of this NIA-AA research framework.
- Profiles of 320 peptides from baseline cerebrospinal fluid (CSF) samples of 287 normal, mild cognitive impairment (MCI) and AD subjects followed over a 3-10 year period were measured via multiple reaction monitoring (MRM) mass spectrometry.
- CSF Aβ 42 , total-Tau (tTau), phosphorylated-Tau (pTau-181) and hippocampal volume were also measured.
- From these candidate markers, optimal diagnostic signatures with decision thresholds to separate AD and normal subjects were first identified via unbiased regression and tree-based algorithms.
Why it matters
Using baseline cerebrospinal fluid peptides and MRI data from 287 people followed for 3 to 10 years, this study identified a cut-point based signature for predicting Alzheimer's disease progression that supports the 2018 NIA-AA research framework. It is a prediction and staging tool, not a treatment, cure, or prevention.
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Study details
- Evidence strengthLow
How this study scored 34/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 22 of the 64 points we could judge it on, which is 34 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of Alzheimer's disease : JAD) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2018 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 30775985) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 22 / 64 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 22 of the 64 points we could judge it on is 34 out of 100. |
| Total | 34 / 100 | — |
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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APA 7th
Devanarayan, P., Devanarayan, V., & Llano, D. A. (2018). Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework. Journal of Alzheimer's disease : JAD. https://doi.org/10.1101/443325
Vancouver
Devanarayan P, Devanarayan V, Llano DA. Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework. Journal of Alzheimer's disease : JAD. 2018. doi:10.1101/443325.
BibTeX
@article{devanarayan2018-1622868e,
author = {Devanarayan, P. and Devanarayan, V. and Llano, D. A.},
title = {{Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer’s disease progression that reinforces the 2018 NIA-AA research framework}},
journal = {Journal of Alzheimer's disease : JAD},
year = {2018},
doi = {10.1101/443325},
url = {https://doi.org/10.1101/443325}
}
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