Evidence map›Paper›PMID 36333348›Full record

Articlenpj aging2022

Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through immune landscape analysis.

Daichi Shigemizu, Shintaro Akiyama, Risa Mitsumori, Shumpei Niida, Kouichi Ozaki

Abstract read
In one paragraph

Article in npj aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

5 authors.

Daichi ShigemizuMedical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan. daichi@ncgg.go.jp.ORCID http://orcid.org/0000-0002-4412-0552
Shintaro AkiyamaMedical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan.
Risa MitsumoriMedical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan.
Shumpei NiidaCore Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan.
Kouichi OzakiMedical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Aichi, 474-8511, Japan. ozakikk@ncgg.go.jp.ORCID http://orcid.org/0000-0003-0028-1570

Funding

Japan Agency for Medical Research and Development (AMED) JP18kk0205009Japan Agency for Medical Research and Development (AMED) JP18kk0205012Japan Agency for Medical Research and Development (AMED) JP21de0107002Japan Agency for Medical Research and Development (AMED) JP21dk0207045Japan Agency for Medical Research and Development (AMED) JP21dk0207052Japan Agency for Medical Research and Development (AMED) JP21km0405501Japan Agency for Medical Research and Development (AMED) JP22dk0207060MEXT | Japan Society for the Promotion of Science (JSPS) JP21H02470
6 · The paper itself

Abstract

Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer's disease (AD). Recent genetic studies have reported on associations between AD risk genes and immunity. Here, we obtained samples and data from 317 AD, 432 MCI, and 107 cognitively normal (CN) subjects and investigated immune-cell type composition and immune clonal diversity of T-cell receptor (TRA, TRB, TRG, and TRD) and B-cell receptor (IGH, IGK, and IGL) repertoires through bulk RNA sequencing. We found the proportions of plasma cells, γδ T cells, neutrophils, and B cells were significantly different and the diversities of IGH, IGK, and TRA were significantly small with AD progression. We then identified a differentially expressed gene, WDR37, in terms of risk of MCI-to-AD conversion. Our prognosis prediction model using the potential blood-based biomarkers for early AD diagnosis, which combined two immune repertoires (IGK and TRA), WDR37, and clinical information, successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank test P = 2.57e-3). It achieved a concordance index of 0.694 in a discovery cohort and of 0.643 in an independent validation cohort. We believe that further investigation, using larger sample sizes, will lead to practical clinical use in the near future.

Identifiers

PMID36333348
PMCPMC9636153

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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.