Evidence mapPaperPMID 40595262Full record

SynthesisScientific reports2025

Integrative bioinformatics frameworks for abdominal aortic aneurysm using GWAS meta-analysis, biological network construction, and structural modeling.

Pakorn Sagulkoo, Hathaichanok Chuntakaruk, Apichat Suratanee, Kitiporn Plaimas, Nuttinee Teerakulkittipong

Abstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Pakorn Sagulkoo *Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.
Hathaichanok Chuntakaruk *Center for Artificial Intelligence in Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Bangkok, 10330, Thailand.
Apichat SurataneeDepartment of Mathematics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, 10800, Thailand.
Kitiporn PlaimasDepartment of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, 10330, Thailand. kitiporn.p@chula.ac.th.
Nuttinee TeerakulkittipongDepartment of Pharmacology and Biopharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Burapha University, Chonburi, 20131, Thailand. nuttinee@go.buu.ac.th.

Funding

The National Science, Research and Innovation Fund (NSRF) and King Mongkut's University of Technology North Bangkok KMUTNB-FF-67-B-24The National Science, Research and Innovation Fund (NSRF) via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation B02G650007
6 · The paper itself

Abstract

Abdominal aortic aneurysm (AAA) is a non-communicable disease (NCD) with high morbidity and mortality, commonly observed worldwide. Understanding its molecular mechanisms and identifying potential therapeutic targets are crucial for disease screening, diagnosis, and treatment. In this study, we conducted a meta-analysis of multiple genome-wide association studies (GWASs) to identify genetic variants associated with AAA and explored the functional implications of these variants in disease pathology. We identified differentially expressed genes (DEGs) based on significant single nucleotide polymorphisms (SNPs) from expression quantitative trait loci (eQTL) and transcriptome-wide association study (TWAS) analyses. Using these DEGs, we constructed an AAA-related protein-protein interaction (PPI) network and prioritized key genes for further analysis. Furthermore, we performed drug repurposing by identifying drug-gene and drug-protein interactions in existing databases and validated potential candidates through molecular docking. Our findings reveal 42 novel disease-associated SNPs and 52 previously unreported disease-related genes. Some residual confounding factors cannot be fully ruled out and may represent a limitation of our study. However, it is worth noting that only a minority of SNPs exhibited heterogeneity. Functional pathways analysis highlighted key processes, including lipid and cholesterol metabolism, tissue remodeling, and acetylcholine activation. We identified 74 DEGs through eQTL and TWAS analyses, with PPI network analysis highlighting CD40 and LRP1 as key proteins. Drug repurposing and molecular docking suggested abciximab and paclitaxel as potential therapeutic agents targeting CD40, while ivermectin emerged as a strong candidate for LRP1 binding. In conclusion, our integrative bioinformatics frameworks links genomics and transcriptomics with network biology and structural modeling, providing valuable insights into the molecular mechanisms of AAA and potential therapeutic strategies.

Indexed as

Aortic Aneurysm, AbdominalComputational BiologyGenome-Wide Association StudyGene Regulatory NetworksGenetic Predisposition to DiseaseHumansMolecular Docking SimulationPolymorphism, Single NucleotideProtein Interaction MapsQuantitative Trait LociTranscriptomeAbdominal aortic aneurysmBiological networkDrug repurposingGenome-wide associations studiesMeta-analysisMolecular docking

Identifiers

PMID40595262
PMCPMC12218227

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.