AIMC Topic: Genome-Wide Association Study
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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 ...
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...
Generative prediction of causal gene sets responsible for complex traits.
Proceedings of the National Academy of Sciences of the United States of America
Jun 12, 2025
The relationship between genotype and phenotype remains an outstanding question for organism-level traits because these traits are generally . The challenge arises from complex traits being determined by a combination of multiple genes (or loci), whi...
Detecting genetic interactions with visible neural networks.
Communications biology
Jun 5, 2025
Non-linear interactions among single nucleotide polymorphisms (SNPs), genes, and pathways play an important role in human diseases, but identifying these interactions is a challenging task. Neural networks are state-of-the-art predictors in many doma...
Epistasis regulates genetic control of cardiac hypertrophy.
Nature cardiovascular research
Jun 5, 2025
Although genetic variant effects often interact nonadditively, strategies to uncover epistasis remain in their infancy. Here we develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy, u...
Induced Pluripotent Stem Cells
Connectin
Magnetic Resonance Imaging
Receptor, IGF Type 1
Heart Failure
Humans
Deep Learning
Ventricular Remodeling
Phenotype
Genome-Wide Association Study
Myocytes, Cardiac
Female
Gene Regulatory Networks
Hypertrophy, Left Ventricular
Aged
Genetic Predisposition to Disease
Epistasis, Genetic
Male
Middle Aged
Performance of deep-learning-based approaches to improve polygenic scores.
Nature communications
Jun 2, 2025
Polygenic scores, which estimate an individual's genetic propensity for a disease or trait, have the potential to become part of genomic healthcare. Neural-network based deep-learning has emerged as a method of intense interest to model complex, nonl...
Bridging Genomic Research Disparities in Osteoporosis GWAS: Insights for Diverse Populations.
Current osteoporosis reports
May 24, 2025
PURPOSE OF REVIEW: Genome-wide association studies (GWAS) have significantly advanced osteoporosis research by identifying genetic loci associated with bone mineral density (BMD) and fracture risk. However, disparities persist due to the underreprese...
Genomics
Genetic Predisposition to Disease
Core Binding Factor Alpha 1 Subunit
Asian People
White People
Gene-Environment Interaction
Osteoporotic Fractures
Machine Learning
Bone Density
Osteoporosis
Humans
Genome-Wide Association Study
African People
Low Density Lipoprotein Receptor-Related Protein-5
Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions.
BMC genomics
May 1, 2025
Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript's ...
Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.
Plant biotechnology journal
Apr 20, 2025
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...
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