AIMC Topic: Genome-Wide Association Study
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Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies.
PloS one
May 1, 2023
The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of...
The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.
Mammalian genome : official journal of the International Mammalian Genome Society
Apr 19, 2023
Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for ...
Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.
Nature genetics
Apr 17, 2023
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a quantitative liability score has more power...
Deep learning-enabled analysis of medical images identifies cardiac sphericity as an early marker of cardiomyopathy and related outcomes.
Med (New York, N.Y.)
Mar 29, 2023
BACKGROUND: Quantification of chamber size and systolic function is a fundamental component of cardiac imaging. However, the human heart is a complex structure with significant uncharacterized phenotypic variation beyond traditional metrics of size a...
Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass.
Nature communications
Mar 21, 2023
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use...
Plant and microbial sciences as key drivers in the development of metabolomics research.
Proceedings of the National Academy of Sciences of the United States of America
Mar 17, 2023
This year marks the 25th anniversary of the coinage of the term metabolome [S. G. Oliver ., , 373-378 (1998)]. As the field rapidly advances, it is important to take stock of the progress which has been made to best inform the disciplines future. Wh...
Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease.
Genes
Mar 1, 2023
The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genet...
Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.
Scientific reports
Dec 31, 2022
Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown grea...
Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.
Proceedings of the National Academy of Sciences of the United States of America
Aug 15, 2022
There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challengin...
Nested epistasis enhancer networks for robust genome regulation.
Science (New York, N.Y.)
Aug 11, 2022
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...
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