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45/100

✓ Peer-reviewed alzhub usefulness score 45 out of 100. Biomarkers

Topic: Amyloid, tau and blood-test diagnosis

Alzheimer disease (AD) is a leading cause of dementia that has gained prominence in our aging society. Yet, the complexity of diagnosing AD and measuring its invasiveness poses an obstacle. To this end, blood-based biomarkers could mitigate the inconveniences that impede an accurate diagnosis. We developed models to diagnose AD and measure the severity of neurocognitive impairment using blood protein biomarkers. Multiple reaction monitoring-mass spectrometry, a highly selective and sensitive approach for quantifying targeted proteins in samples, was used to analyze blood samples from 4 AD groups: cognitive normal control, asymptomatic AD, prodromal AD), and AD dementia. Multimarker models were developed using 10 protein biomarkers and apolipoprotein E genotypes for amyloid beta and 10 biomarkers with Korean Mini-Mental Status Examination (K-MMSE) score for predicting Alzheimer disease progression. The accuracies for the AD classification model and AD progression monitoring model were 84.9% (95% CI 82.8 to 87.0) and 79.1% (95% CI 77.8 to 80.5), respectively. The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score. Our study demonstrates the possibility of predicting AD with high accuracy by blood biomarker analysis as an alternative method of screening for AD.

Key findings

The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score.

Why it matters

Blood protein models using mass spectrometry classified Alzheimer disease with about 85% accuracy and monitored progression with about 79% accuracy, doing better than APOE genotype alone or a cognitive score. This is a screening approach and does not treat, cure or prevent the disease.

New to this subject? Start with our plain-English guide: Blood tests & biomarkers →

Study details

Effect size84.9%; 79.1%
Evidence strengthLow

How this study scored 45/100

Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (Scientific reports)
Journal's citation record	3 / 4	Scientific Reports: journal h-index 463 (OpenAlex, 2026-10-29)
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	3 / 5	2022 — within 6 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	2 / 3	Effect reported as a number, without an interval or test
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	3 / 7	Cited 29 times (OpenAlex, 2026-10-10)
Citations per year	2 / 5	4.8 citations a year over 6 year(s) since 2022
Impact for its field and year	3 / 6	Cited 3.8× the average for papers of its field and year (OpenAlex FWCI)
Cited by studies here	0 / 6	No other study in this library cites it
Still being cited	2 / 4	Cited 21 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record	2 / 4	Last-listed author Youngsoo Kim: h-index 43 (OpenAlex, whole career)
Institution's track record	1 / 3	Seoul National University: institution h-index 1,053 (OpenAlex)
Multi-centre collaboration	2 / 3	OpenAlex lists 5 institution(s) in 1 country
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 35075217)
Free to read	2 / 2	Free to read
Total	45 / 100	—

What each of these 20 components measures, and what this score is not →

Read the original

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.

APA 7th

Kim, Y., Kim, J., Son, M., Lee, J., Yeo, I., Choi, K. Y., et al. (2022). Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry. Scientific reports. https://doi.org/10.1038/s41598-022-05384-8

Vancouver

Kim Y, Kim J, Son M, Lee J, Yeo I, Choi KY, et al. Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry. Scientific reports. 2022. doi:10.1038/s41598-022-05384-8. PMID: 35075217.

BibTeX

@article{kim2022-35075217,
  author  = {Kim, Y. and Kim, J. and Son, M. and Lee, J. and Yeo, I. and Choi, K. Y. and Kim, H. and Kim, B. C. and others},
  title   = {{Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry}},
  journal = {Scientific reports},
  year    = {2022},
  doi     = {10.1038/s41598-022-05384-8},
  pmid    = {35075217},
  url     = {https://doi.org/10.1038/s41598-022-05384-8}
}

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