AIMC Topic: Genome-Wide Association Study
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Non-coding genetic elements of lung cancer identified using whole genome sequencing in 13,722 Chinese.
Nature communications
Aug 9, 2025
A substantial portion of lung cancer-associated genetic elements in East Asian populations remains unidentified, underscoring the need for large-scale genome-wide studies, particularly on non-coding regulation. We conducted a whole genome sequencing ...
varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction.
Genome medicine
Aug 4, 2025
BACKGROUND: Machine learning and artificial intelligence are increasingly being applied to identify phenotypically causal genetic variation. These data-driven methods require comprehensive training sets to deliver reliable results. However, large unb...
Machine learning in Alzheimer's disease genetics.
Nature communications
Jul 22, 2025
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key contributors to JIA risk prediction.
RMD open
Jul 9, 2025
BACKGROUND: Previous genome-wide association studies (GWAS) have identified numerous genetic loci associated with juvenile idiopathic arthritis (JIA). However, the functional impact of these variants-particularly on tissue-specific gene expression-an...
Identification of key genes as diagnostic biomarkers for IBD using bioinformatics and machine learning.
Journal of translational medicine
Jul 3, 2025
BACKGROUND: The pathogenesis of inflammatory bowel disease (IBD) involves complex molecular mechanisms, and achieving clinical remission remains challenging. This study aims to identify IBD-potential biomarkers, analyze their correlation with immune ...
Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.
Scientific reports
Jul 3, 2025
Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcinoma (LUAD), with the interaction of immune cells within this microenvironment contributing to a poorer prognosis. We sought to investigate the causal r...
A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.
Clinical epigenetics
Jul 2, 2025
DNA methylation in breast tumours has been extensively studied and has provided valuable insights into the clinical heterogeneity of breast cancer. In this review, we summarise the current literature that has used DNA methylation markers to subtype b...
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 ...
Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.
American journal of human genetics
Jun 20, 2025
Electronic health records, biobanks, and wearable biosensors enable the collection of multiple health modalities from many individuals. Access to multimodal health data provides a unique opportunity for genetic studies of complex traits because diffe...
Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological disorders.
NAR genomics and bioinformatics
Jun 13, 2025
Large-scale quantitative studies have identified significant genetic associations for various neurological disorders. Expression quantitative trait locus (eQTL) studies have shown the effect of single-nucleotide polymorphisms (SNPs) on the differenti...
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