AIMC Topic: Mendelian Randomization Analysis
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Identification of MEG3 and MAPK3 as potential therapeutic targets for osteoarthritis through multiomics integration and machine learning.
Scientific reports
Jul 2, 2025
Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder, yet its underlying molecular mechanisms remain puzzling. This study aimed to uncover the genes with a causal relationship to KOA using Mendelian randomization (MR), transcriptomic ...
Exploration of shared pathogenic factors and causative genes in early-stage endometrial cancer and osteoarthritis.
Scientific reports
Jul 1, 2025
Osteoarthritis (OA) has been implicated in the development and progression of early-stage endometrial cancer (EC), suggesting shared pathogenic factors between the two diseases. This study aimed to investigate the causal relationship between OA and E...
Exploring the relationship between graft dysfunction with serum metabolites and inflammatory proteins: integrating Mendelian randomization, single-cell analysis, machine learning, and SHAP methods for comprehensive analysis.
Renal failure
Jun 25, 2025
BACKGROUND: The exact mechanism of graft dysfunction has not been fully clarified. We aimed to explore the causal effects of serum metabolites on graft dysfunction and the mediating role of inflammatory proteins.
Transcriptome combined with Mendelian randomization to identify key genes related to polyamine metabolism in childhood obesity and elucidate their molecular regulatory mechanisms.
Scientific reports
May 22, 2025
Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the identification of key genes associated with polyamines metabolism in CO could offer fresh insights for cl...
Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors.
The journal of headache and pain
May 6, 2025
BACKGROUND: Migraine ranks as the second-leading cause of global neurological disability, affecting approximately 1.1 billion individuals worldwide with severe quality-of-life impairments. Although adjustable risk factors-including environmental expo...
Exploring new drug treatment targets for immune related bone diseases using a multi omics joint analysis strategy.
Scientific reports
Mar 27, 2025
In the field of treatment and prevention of immune-related bone diseases, significant challenges persist, necessitating the urgent exploration of new and effective treatment methods. However, most existing Mendelian randomization (MR) studies are con...
Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning.
Frontiers in immunology
Mar 21, 2025
BACKGROUND: Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.
Identification and Experimental Validation of NETosis-Mediated Abdominal Aortic Aneurysm Gene Signature Using Multi-omics, Machine Learning, and Mendelian Randomization.
Journal of chemical information and modeling
Mar 19, 2025
Abdominal aortic aneurysm (AAA) is a life-threatening disorder with limited therapeutic options. Neutrophil extracellular traps (NETs) are formed by a process known as "NETosis" that has been implicated in AAA pathogenesis, yet the roles and prognost...
Machine learning approach on plasma proteomics identifies signatures associated with obesity in the KORA FF4 cohort.
Diabetes, obesity & metabolism
Feb 27, 2025
AIMS: This study investigated the role of plasma proteins in obesity to identify predictive biomarkers and explore underlying biological mechanisms.
Unveiling the crucial role of glycosylation modification in lung adenocarcinoma metastasis through artificial neural network-based spatial multi-omics single-cell analysis and Mendelian randomization.
BMC cancer
Feb 13, 2025
BACKGROUND: Investigations into the intricacies of glycosylation modifications, a prevalent post-translational alteration observed in neoplasms, especially remain elusive in the context of lung adenocarcinoma. Through the integration of multiple omic...
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