PXD070630

PXD070630 is an original dataset announced via ProteomeXchange.

Title	Multiomics approach to identify novel fecal biomarkers of Alzheimer’s disease in a mouse model.
Description	Background: Currently, a specific diagnostic test for Alzheimer’s disease (AD) is not available. AD diagnosis is a long process that requires the execution of various clinical and instrumental tests. To date, the possibility of prevention, early diagnosis with prompt management of patients is almost impossible. Although CSF is considered the ideal sample for the evaluation of biomarkers of AD its collection is invasive, poorly tolerated by patients and expensive. Consequently, research is currently committed to identifying new biomarkers in easier-to-obtain biological samples such as blood and saliva. Recent knowledge highlights the role of the intestinal microbiota in neurodegenerative diseases (microbiota-gut-brain axis). Our hypothesis based on interplay between gut and brain is that microbiota alteration could influence stool composition, so our interest is focused on the fecal sample to identify biomarkers of AD. Objectives: The aim of the project is to identify diagnostic and prognostic biomarkers for AD using a multiomics approach (proteome and miRnome) on fecal samples Methods: The study was conducted on a transgenic mouse model of AD (3×Tg-AD) with three mutations associated with familial AD (APP-Swedish, MAPT-P301L, and PSEN1-M146V). miRNome and Proteomic analysis were performed by Next Generation Sequencing (NGS) and high definition mass spectrometry techniques, respectively. Results and conclusion: By Omics analyses we identified 31 microRNAs and 81 proteins differentially modulated in fecal samples from mutant mice with AD compared to wt controls, these molecules are potential biomarkers for AD. Their validation by Real-Time PCR, ELISA or immunoblotting is in progress. By this study, we demonstrated that the fecal sample is suitable to identify new biomarkes, also in neurodegenerative diseases. Furthermore, the use of the fecal sample implies multiple advantages, their collection is non-invasive and repeatable over time.
HostingRepository	PRIDE
AnnounceDate	2026-09-09
AnnouncementXML	Submission_2026-09-09_03:40:25.953.xml
DigitalObjectIdentifier	https://doi.org/10.6019/PXD070630
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Luisa Pieroni
SpeciesList	scientific name: Mus musculus (Mouse); NCBI TaxID: NEWT:10090;
ModificationList	monohydroxylated residue; iodoacetamide derivatized residue
Instrument	Synapt MS

Revision	Datetime	Status	ChangeLog Entry
0	2025-11-12 00:53:10	ID requested
⏵ 1	2026-09-09 03:40:26	announced

Vitali R, Tanno B, Casciati A, Palone F, Pieroni L, Morotti M, Santoro M, Fratini E, Pazzaglia S, Podda MV, Mancuso M, Tg-AD Mice. Cell Mol Neurobiol, 46(1):(2026) [pubmed]

10.6019/PXD070630;

10.1007/s10571-026-01735-5;

submitter keyword: proteomics,ALzheimer Disease (AD), biomarkers

Luisa Pieroni
contact affiliation	Departmental Faculty of Medicine, UniCamillus-Saint Camillus International University of Health and Medical Sciences, 00131 Rome, Italy
contact email	luisa.pieroni@unicamillus.org
lab head
Luisa Pieroni
contact affiliation	Unicamillus, International Medical University of Rome, Departmental Faculty of Medicine and Surgery,Via di Sant’Alessandro, 8, 00131 Rome – IT
contact email	luisa.pieroni@unicamillus.org
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD070630
     1. Label: PRIDE project
     2. Name: Multiomics approach to identify novel fecal biomarkers of Alzheimer’s disease in a mouse model.