Evidence map›Paper›PMID 34151801›Full record

ArticleJournal of Alzheimer's disease : JAD2021

Salivaomics as a Potential Tool for Predicting Alzheimer's Disease During the Early Stages of Neurodegeneration.

Maxime François, Avinash Karpe, Jian-Wei Liu, David Beale, Maryam Hor, Jane Hecker, Jeff Faunt, John Maddison, Sally Johns, James Doecke and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

  1. Pooled it
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  9. An Update of Salivary Biomarkers for the Diagnosis of Alzheimer's Disease.International journal of molecular sciences · 2025
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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.

Maxime FrançoisCSIRO Health & Biosecurity, Nutrition and Health Program, Molecular Diagnostic Solutions Group, Adelaide, South Australia, Australia.
Avinash KarpeCSIRO Land & Water, Metabolomics Unit, Ecosciences Precinct, Dutton Park, QLD, Australia.
Jian-Wei LiuCSIRO Land & Water, Agricultural and Environmental Sciences Precinct, Acton, Canberra, ACT, Australia.
David BealeCSIRO Land & Water, Metabolomics Unit, Ecosciences Precinct, Dutton Park, QLD, Australia.
Maryam HorCSIRO Health & Biosecurity, Nutrition and Health Program, Molecular Diagnostic Solutions Group, Adelaide, South Australia, Australia.
Jane HeckerDepartment of Internal Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Jeff FauntDepartment of General Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia.
John MaddisonAged Care Rehabilitation & Palliative Care, SA Health, Modbury Hospital, South Australia, Australia.
Sally JohnsAged Care Rehabilitation & Palliative Care, SA Health, Modbury Hospital, South Australia, Australia.
James DoeckeCSIRO Health and Biosecurity/Australian e-Health Research Centre Level 5, University of Queensland Health Sciences Building, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Stephen RoseCSIRO Health and Biosecurity/Australian e-Health Research Centre Level 5, University of Queensland Health Sciences Building, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
Wayne R LeifertCSIRO Health & Biosecurity, Nutrition and Health Program, Molecular Diagnostic Solutions Group, Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is poorly understood and the relationships between systemic abnormalities in metabolism and AD/AMCI pathogenesis are unclear.

objectiveThe aim of the study was to compare the metabolomic and proteomic signature of saliva from cognitively normal and patients diagnosed with MCI or AD, to identify specific cellular pathways altered with the progression of the disease.

methodsWe analyzed 80 saliva samples from individuals with MCI or AD as well as age- and gender-matched healthy controls. Saliva proteomic and metabolomic analyses were conducted utilizing mass spectrometry methods and data combined using pathway analysis.

resultsWe found significant alterations in multiple cellular pathways, demonstrating that at the omics level, disease progression impacts numerous cellular processes. Multivariate statistics using SIMCA showed that partial least squares-data analysis could be used to provide separation of the three groups.

conclusionThis study found significant changes in metabolites and proteins from multiple cellular pathways in saliva. These changes were associated with AD, demonstrating that this approach might prove useful to identify new biomarkers based upon integration of multi-omics parameters.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseBiomarkersCognitive DysfunctionEarly DiagnosisFemaleHumansMaleMetabolomicsNeurodegenerative DiseasesPredictive Value of TestsProteomicsSalivaBiomarkersAlzheimer’s diseasemetabolomicsmulti-omics integrationproteomicssalivasystems biology

Identifiers

PMID34151801
PMCPMC8461673

What OpenQuestion holds

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LicenceCC BY-NC
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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.