Evidence map›Paper›PMID 34895338›Full record

ArticleCell & bioscience2021

Soluble amyloid-beta isoforms predict downstream Alzheimer's disease pathology.

Guilherme Povala, Bruna Bellaver, Marco Antônio De Bastiani, Wagner S Brum, Pamela C L Ferreira, Andrei Bieger, Tharick A Pascoal, Andrea L Benedet, Diogo O Souza, Ricardo M Araujo and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cell & bioscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Experimental modeling of Alzheimer's disease: Translational lessons from cross-taxon analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Review
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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

14 authors at 4 institutions in 3 countries.

Guilherme PovalaGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Bruna BellaverGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Marco Antônio De BastianiGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Wagner S BrumGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Pamela C L FerreiraGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Andrei BiegerGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Tharick A PascoalDepartment of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, USA.
Andrea L BenedetTranslational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, 6825 LaSalle Boulevard, Verdun, QC, H4H 1R3, Canada.
Diogo O SouzaGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Ricardo M AraujoGraduate Program in Computing, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Bruno ZattGraduate Program in Computing, Universidade Federal de Pelotas (UFPEL), Pelotas, Brazil.
Pedro Rosa-NetoTranslational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, 6825 LaSalle Boulevard, Verdun, QC, H4H 1R3, Canada. pedro.rosa@mcgill.ca.
Eduardo R ZimmerGraduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. erzimmer@gmail.com.ORCID http://orcid.org/0000-0002-5349-0053
for the Alzheimer’s Disease Neuroimaging Initiative
Universidade Federal do Rio Grande do Sul · BRMontreal Neurological Institute and Hospital · CAUniversidade Federal de Pelotas · BRUniversity of Pittsburgh · US

Funding

Alzheimer's Association NIRG-12-92090Alzheimer's Association NIRP-12-259245CIHR FRN, 152985CIHR MOP-11-51-31Conselho Nacional de Desenvolvimento Científico e Tecnológico 312410/2018-2Conselho Nacional de Desenvolvimento Científico e Tecnológico 435642/2018-9Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88882.345577/2019-01Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.336490/2019-00Fonds de Recherche du Québec - Santé 2020-VICO-279314Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul 30786.434.24734.23112017Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul 54392.632.30451.05032021Instituto Serrapilheira Serra-1912-31365
6 · The paper itself

Abstract

backgroundChanges in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer's disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity.

methodsWe used CSF measurements of three soluble Aβ peptides (Aβ

resultsOur findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML model. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed.

conclusionsOur results demonstrate that, by applying a refined ML analysis, a combination of Aβ isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction.

Indexed as

Alzheimer’s diseaseAmyloid-betaMachine learningNeurodegenerationProteomicsTau pathology

Identifiers

PMID34895338
PMCPMC8665586
OpenAlexW4200174260

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.