Evidence map›Paper›PMID 38436501›Full record

ArticleAging cell2024

Multi-proteomic analyses of 5xFAD mice reveal new molecular signatures of early-stage Alzheimer's disease.

Seulah Lee, Kuk-In Jang, Hagyeong Lee, Yeon Suk Jo, Dayoung Kwon, Geuna Park, Sungwon Bae, Yang Woo Kwon, Jin-Hyeok Jang, Yong-Seok Oh and 2 more

Open access · goldAbstract read
In one paragraph

Article in Aging cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Seulah LeeNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Kuk-In JangCognitive Science Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Hagyeong LeeNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Yeon Suk JoNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Dayoung KwonNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Geuna ParkNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Sungwon BaeNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Yang Woo KwonNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Jin-Hyeok JangDepartment of Brain-Cognitive Science, Daegu-Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
Yong-Seok OhDepartment of Brain-Cognitive Science, Daegu-Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
Chany LeeCognitive Science Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.
Jong Hyuk YoonNeurodegenerative Diseases Research Group, Korea Brain Research Institute, Daegu, Republic of Korea.ORCID 0000-0002-4090-3832
Korea Brain Research Institute · KRDaegu Gyeongbuk Institute of Science and Technology · KR

Funding

Ministry of Science and ICT 22-CoE-BT-02Ministry of Science and ICT 23-BR-02-03Ministry of Science and ICT 23-BR-02-13Ministry of Science and ICT 23-BR-04-02Ministry of Science and ICT 23-BR-05-01Ministry of Science and ICT A0801043001
6 · The paper itself

Abstract

An early diagnosis of Alzheimer's disease is crucial as treatment efficacy is limited to the early stages. However, the current diagnostic methods are limited to mid or later stages of disease development owing to the limitations of clinical examinations and amyloid plaque imaging. Therefore, this study aimed to identify molecular signatures including blood plasma extracellular vesicle biomarker proteins associated with Alzheimer's disease to aid early-stage diagnosis. The hippocampus, cortex, and blood plasma extracellular vesicles of 3- and 6-month-old 5xFAD mice were analyzed using quantitative proteomics. Subsequent bioinformatics and biochemical analyses were performed to compare the molecular signatures between wild type and 5xFAD mice across different brain regions and age groups to elucidate disease pathology. There was a unique signature of significantly altered proteins in the hippocampal and cortical proteomes of 3- and 6-month-old mice. The plasma extracellular vesicle proteomes exhibited distinct informatic features compared with the other proteomes. Furthermore, the regulation of several canonical pathways (including phosphatidylinositol 3-kinase/protein kinase B signaling) differed between the hippocampus and cortex. Twelve potential biomarkers for the detection of early-stage Alzheimer's disease were identified and validated using plasma extracellular vesicles from stage-divided patients. Finally, integrin α-IIb, creatine kinase M-type, filamin C, glutamine γ-glutamyltransferase 2, and lysosomal α-mannosidase were selected as distinguishing biomarkers for healthy individuals and early-stage Alzheimer's disease patients using machine learning modeling with approximately 79% accuracy. Our study identified novel early-stage molecular signatures associated with the progression of Alzheimer's disease, thereby providing novel insights into its pathogenesis.

Indexed as

Alzheimer DiseaseMice, TransgenicProteomicsAnimalsBiomarkersDisease Models, AnimalHumansMaleMiceProteomeBiomarkersProteomeAlzheimer's diseasebiomarkerearly‐stage Alzheimer's diseaseextracellular vesiclemachine learningproteomics

Identifiers

PMID38436501
PMCPMC11166370
OpenAlexW4392379331

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.