Evidence map›Paper›PMID 36611114›Full record

ArticleJournal of neurology2023

A blood mRNA panel that differentiates Alzheimer's disease from other dementia types.

Xiaofeng Fu, Changbiao Chu, Yana Pang, Huimin Cai, Ziye Ren, Longfei Jia

Abstract read
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In one paragraph

Article in Journal of neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 4 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

6 authors at 1 institution in 1 country.

Xiaofeng Fu *Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China.
Changbiao Chu *Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China.
Yana PangInnovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China.
Huimin CaiInnovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China.
Ziye RenInnovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China.
Longfei JiaInnovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, 45 Changchun St., Beijing, China. longfei@mail.ccmu.edu.cn.
Capital Medical University · CN

Funding

Beijing Brain Initiative from Beijing Municipal Science & Technology Commission Z201100005520016Beijing Municipal Natural Science Foundation 7202061Capital's Funds for Health Improvement and Research 2022-2-2017National Natural Science Foundation of China 81870825National Natural Science Foundation of China 82071194
6 · The paper itself

Abstract

backgroundMessenger RNAs (mRNAs) have been reported to be associated with Alzheimer's disease (AD). In this study, we investigated whether plasma-based mRNAs could distinguish AD from cognitively normal controls and other types of dementia, including vascular dementia (VaD), Parkinson's disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and dementia with Lewy body (DLB).

methodsPlasma mRNA expression was measured in three independent datasets. Dataset 1 (n = 40; controls, 20; AD, 20) was used to identify the differentially expressed mRNAs. Dataset 2 (n = 122; controls: 60; AD: 62) was used to develop a diagnostic AD model using an mRNA panel. Furthermore, we applied the model to Dataset 3 (n = 334; control, 57; AD, 58; VaD, 55; PDD, 54; bvFTD, 55; DLB, 55) to verify its ability to identify AD and other types of dementia.

resultsDataset 1 showed 22 upregulated and 21 downregulated mRNAs. A panel of six mRNAs distinguished AD from the control group in Dataset 2. The panel was used to successfully differentiate AD from other types of dementia in Dataset 3.

conclusionsAn AD-specific panel of six mRNAs was created that can be used for AD diagnosis.

Indexed as

Alzheimer DiseaseDementia, VascularFrontotemporal DementiaLewy Body DiseaseParkinson DiseaseHumansAlzheimer’s diseaseBiomarkerDementiaDiagnosismRNA

Identifiers

PMID36611114
OpenAlexW4313681603

What OpenQuestion holds

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Registered trials

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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.