AIMC Topic: Genome-Wide Association Study

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Pharmacogenomics and response to lithium in bipolar disorder.

Pharmacogenomics Feb 25, 2025
AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of lithium response in the treatment of bipolar disorder. We focused our research article on reports describing findings from genome-wide association stud...
Bipolar Disorder Lithium Compounds Humans Pharmacogenetics Lithium Precision Medicine Genome-Wide Association Study Antimanic Agents
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Genetic association studies using disease liabilities from deep neural networks.

American journal of human genetics Feb 21, 2025
The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, l...
Neural Networks, Computer Phenotype Female Multifactorial Inheritance Male Humans Genetic Predisposition to Disease Case-Control Studies Polymorphism, Single Nucleotide Genome-Wide Association Study Genetic Association Studies
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.

Translational psychiatry Feb 7, 2025
Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictors of treatment response poses great challenges for personalized treatment. The current study employe...
Male Deep Learning Adolescent Humans Female Membrane Proteins Treatment Outcome Attention Deficit Disorder with Hyperactivity Genome-Wide Association Study Child Polymorphism, Single Nucleotide
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Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jan 24, 2025
Cotton is an important crop for fiber production, but the genetic basis underlying key agronomic traits, such as fiber quality and flowering days, remains complex. While machine learning (ML) has shown great potential in uncovering the genetic archit...
Gossypium Quantitative Trait Loci Polymorphism, Single Nucleotide Machine Learning Flowers Phenotype Cotton Fiber Genome-Wide Association Study
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Modeling gene interactions in polygenic prediction via geometric deep learning.

Genome research Jan 22, 2025
Polygenic risk score (PRS) is a widely used approach for predicting individuals' genetic risk of complex diseases, playing a pivotal role in advancing precision medicine. Traditional PRS methods, predominantly following a linear structure, often fall...
Genome-Wide Association Study Genetic Predisposition to Disease Models, Genetic Humans Neural Networks, Computer Deep Learning Epistasis, Genetic Multifactorial Inheritance
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

The journal of headache and pain Jan 20, 2025
BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associ...
Machine Learning Gene Expression Profiling Genome-Wide Association Study Gene Regulatory Networks Genetic Predisposition to Disease Polymorphism, Single Nucleotide Humans Transcription Factors Migraine Disorders
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Deep self-representation learning with hyper-laplacian regularization for brain imaging genetics association analysis.

Methods (San Diego, Calif.) Jan 19, 2025
Brain imaging genetics aims to explore the association between genetic factors such as single nucleotide polymorphisms (SNPs) and brain imaging quantitative traits (QTs). However, most existing methods do not consider the nonlinear correlations betwe...
Humans Magnetic Resonance Imaging Deep Learning Neuroimaging Genome-Wide Association Study Polymorphism, Single Nucleotide Image Processing, Computer-Assisted Genotype Neural Networks, Computer Genetic Association Studies Algorithms Brain
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Multiple, Single Trait GWAS and Supervised Machine Learning Reveal the Genetic Architecture of Fraxinus excelsior Tolerance to Ash Dieback in Europe.

Plant, cell & environment Jan 17, 2025
Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at epidemic levels throughout Europe. Previous studies have found significant genetic variation among gen...
Fraxinus Plant Diseases Ascomycota Disease Resistance Polymorphism, Single Nucleotide Genotype Europe Machine Learning Phenotype Genome-Wide Association Study
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Genome-wide association study on color-image-based convolutional neural networks.

PeerJ Jan 13, 2025
BACKGROUND: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome...
Image Processing, Computer-Assisted Genotype Color Neural Networks, Computer Humans Convolutional Neural Networks Genome-Wide Association Study
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Genomic determinants of biological age estimated by deep learning applied to retinal images.

GeroScience Jan 8, 2025
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between c...
Polymorphism, Single Nucleotide Mendelian Randomization Analysis Retina Middle Aged Deep Learning Genome-Wide Association Study Humans Female Aged Male Aging
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