AIMC Topic: Genetic Predisposition to Disease

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Genetic and Genomic Testing in Cardiovascular Disease: A Policy Statement From the American Heart Association.

Circulation
The rapid advancement of genomic and precision medicine has expanded the role of genetics and genomics in the diagnosis, risk stratification, and management of cardiovascular diseases. With the decreasing cost and increasing accessibility of genetic ...

The Genetic Architecture of the Human Corpus Callosum and its Subregions.

Nature communications
The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses and performing associative or executive functions. Identifying which ge...

ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction.

BMC bioinformatics
Small nucleolar RNAs (snoRNAs), a class of non-coding RNAs broadly distributed in eukaryotes, are emerging as pivotal regulators in the field of epigenomics. In addition to guiding 2'-O-methylation and pseudouridylation modifications at specific rRNA...

Multiple polygenic score approach in colorectal cancer risk prediction.

Scientific reports
Recent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance - known as Multiple Polygenic Score (MPS)...

Denoising self-supervised learning for disease-gene association prediction.

BMC bioinformatics
Understanding the interplay between diseases and genes is crucial for gaining deeper insights into disease mechanisms and optimizing therapeutic strategies. In recent years, various computational methods have been developed to uncover potential disea...

Multimodal integration of plasma biomarkers, MRI, and genetic risk to predict cerebral amyloid burden in Alzheimer's disease.

NeuroImage
Alzheimer's disease (AD), the most prevalent neurodegenerative disorder, is marked by the accumulation of amyloid-β (Aβ) plaques. Although cerebral Aβ positron emission tomography (Aβ-PET) remains the gold standard for assessing cerebral Aβ burden, i...

Multi-class machine learning-based classification of SCID-related genetic variants.

Immunologic research
BACKGROUND: Variants of uncertain significance (VUS) represent a major diagnostic challenge in the interpretation of genetic testing results, particularly in the context of inborn errors of immunity such as severe combined immunodeficiency (SCID). Th...

Machine learning-based penetrance of genetic variants.

Science (New York, N.Y.)
Accurate variant penetrance estimation is crucial for precision medicine. We constructed machine learning (ML) models for 10 diseases using 1,347,298 participants with electronic health records, then applied them to an independent cohort with linked ...

Deep adversarial learning identifies ADHD-specific associations between apoptotic genes and white matter microstructure in frontal-striatum-cerebellum circuit.

Translational psychiatry
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by genetic predisposition and alterations in brain structural connectivity. While existing studies have established associations between genetic variants a...