Evidence map›Paper›PMID 37873875›Full record

ReviewProteomes2023

Unveiling the Molecular Footprint: Proteome-Based Biomarkers for Alzheimer's Disease.

Mukul Jain, Rupal Dhariwal, Nil Patil, Sandhya Ojha, Reshma Tendulkar, Mugdha Tendulkar, Parmdeep Singh Dhanda, Alpa Yadav, Prashant Kaushik

Open access · goldAbstract readReview
In one paragraph

Review in Proteomes, 2023. 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
1.4field-weighted citation impact, top 18% 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, 8 citations in OpenAlex.

  1. Drug Discovery from Gene Expression/Gene Regulation.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
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  3. Article
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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

9 authors at 6 institutions in 2 countries.

Mukul JainCell and Developmental Biology Laboratory, Research and Development Cell, Parul University, Vadodara 391760, India.ORCID 0000-0003-3739-1247
Rupal DhariwalCell and Developmental Biology Laboratory, Research and Development Cell, Parul University, Vadodara 391760, India.ORCID 0000-0002-2056-0959
Nil PatilCell and Developmental Biology Laboratory, Research and Development Cell, Parul University, Vadodara 391760, India.ORCID 0000-0002-9941-3395
Sandhya OjhaDepartment of Life Sciences, Parul Institute of Applied Sciences, Parul University, Vadodara 391760, India.
Reshma TendulkarVivekanand Education Society, College of Pharmacy, Chembur, Mumbai 400071, India.ORCID 0000-0002-6235-8142
Mugdha TendulkarSardar Vallabhbhai Patel College of Science, Mira Rd (East), Thane 400071, India.ORCID 0000-0001-7255-8351
Parmdeep Singh DhandaDepartment of Biochemistry, Punjab Agricultural University, Ludhiana 141027, India.ORCID 0000-0002-3614-3252
Alpa YadavDepartment of Botany, Indira Gandhi University, Meerpur, Rewari 122502, India.
Prashant KaushikInstituto de Conservacióny Mejora de la Agrodiversidad Valenciana, Universitat Politècnica de València, 46022 Valencia, Spain.ORCID 0000-0002-3145-2849
Parul University · INIndira Gandhi Mirpur University · INPunjab Agricultural University · INSardar Patel University · INSwami Vivekanand College of Pharmacy · INUniversitat Politècnica de València · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss. Early and accurate diagnosis of AD is crucial for implementing timely interventions and developing effective therapeutic strategies. Proteome-based biomarkers have emerged as promising tools for AD diagnosis and prognosis due to their ability to reflect disease-specific molecular alterations. There is of great significance for biomarkers in AD diagnosis and management. It emphasizes the limitations of existing diagnostic approaches and the need for reliable and accessible biomarkers. Proteomics, a field that comprehensively analyzes the entire protein complement of cells, tissues, or bio fluids, is presented as a powerful tool for identifying AD biomarkers. There is a diverse range of proteomic approaches employed in AD research, including mass spectrometry, two-dimensional gel electrophoresis, and protein microarrays. The challenges associated with identifying reliable biomarkers, such as sample heterogeneity and the dynamic nature of the disease. There are well-known proteins implicated in AD pathogenesis, such as amyloid-beta peptides, tau protein, Apo lipoprotein E, and clusterin, as well as inflammatory markers and complement proteins. Validation and clinical utility of proteome-based biomarkers are addressing the challenges involved in validation studies and the diagnostic accuracy of these biomarkers. There is great potential in monitoring disease progression and response to treatment, thereby aiding in personalized medicine approaches for AD patients. There is a great role for bioinformatics and data analysis in proteomics for AD biomarker research and the importance of data preprocessing, statistical analysis, pathway analysis, and integration of multi-omics data for a comprehensive understanding of AD pathophysiology. In conclusion, proteome-based biomarkers hold great promise in the field of AD research. They provide valuable insights into disease mechanisms, aid in early diagnosis, and facilitate personalized treatment strategies. However, further research and validation studies are necessary to harness the full potential of proteome-based biomarkers in clinical practice.

Indexed as

Alzheimer’s diseasebioinformaticsbiomarkersmicroarrayproteomics

Identifiers

PMID37873875
PMCPMC10594437
OpenAlexW4387672816

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.