ArticleBrain sciences2022
Integrated Analysis of Cortex Single-Cell Transcriptome and Serum Proteome Reveals the Novel Biomarkers in Alzheimer's Disease.
Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 20 citations in OpenAlex.
- Segmental specification of the human female fetal reproductive tract revealed by spatiotemporal dynamics.Nature cell biology · 2026Article
- Omics-driven strategies for identifying biomarkers in Alzheimer's disease.Metabolic brain disease · 2026Review
- Identifying Hub Genes and miRNAs Associated with Alzheimer's Disease: A Bioinformatics Pathway to Novel Therapeutic Strategies.Biomolecules · 2024Article
- MORE: a multi-omics data-driven hypergraph integration network for biomedical data classification and biomarker identification.Briefings in bioinformatics · 2024Article
- Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles.Nature aging · 2024Article
- Multi-omics approach reveals dysregulated genes during hESCs neuronal differentiation exposure to paracetamol.iScience · 2023Article
- Advances in proteomic phenotyping of microglia in neurodegeneration.Proteomics · 2023Review
- Review
- Integrated analysis of plasma proteome and cortex single-cell transcriptome reveals the novel biomarkers during cortical aging.Frontiers in aging neuroscience · 2023Article
- The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease.Frontiers in aging neuroscience · 2022Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Blood-based proteomic analysis is a routine practice for detecting the biomarkers of human disease. The results obtained from blood alone cannot fully reflect the alterations of nerve cells, including neurons and glia cells, in Alzheimer's disease (AD) brains. Therefore, the present study aimed to investigate novel potential AD biomarker candidates, through an integrated multi-omics approach in AD. We propose a comprehensive strategy to identify high-confidence candidate biomarkers by integrating multi-omics data from AD, including single-nuclei RNA sequencing (snRNA-seq) datasets of the prefrontal and entorhinal cortices, as wells as serum proteomic datasets. We first quantified a total of 124,658 nuclei, 8 cell types, and 3701 differentially expressed genes (DEGs) from snRNA-seq dataset of 30 human cortices, as well as 1291 differentially expressed proteins (DEPs) from serum proteomic dataset of 11 individuals. Then, ten DEGs/DEPs (NEBL, CHSY3, STMN2, MARCKS, VIM, FGD4, EPB41L2, PLEKHG1, PTPRZ1, and PPP1R14A) were identified by integration analysis of snRNA-seq and proteomics data. Finally, four novel candidate biomarkers (NEBL, EPB41L2, FGD4, and MARCKS) for AD further stood out, according to bioinformatics analysis, and they were verified by enzyme-linked immunosorbent assay (ELISA) verification. These candidate biomarkers are related to the regulation process of the actin cytoskeleton, which is involved in the regulation of synaptic loss in the AD brain tissue. Collectively, this study identified novel cell type-related biomarkers for AD by integrating multi-omics datasets from brains and serum. Our findings provided new targets for the clinical treatment and prognosis of AD.
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