Back to Search
Start Over
Longitudinal Genotype–Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model
- Source :
- Journal of Computational Biology. 25:809-824
- Publication Year :
- 2018
- Publisher :
- Mary Ann Liebert Inc, 2018.
-
Abstract
- With the rapid development of high-throughput genotyping and neuroimaging techniques, imaging genetics has drawn significant attention in the study of complex brain diseases such as Alzheimer's disease (AD). Research on the associations between genotype and phenotype improves the understanding of the genetic basis and biological mechanisms of brain structure and function. AD is a progressive neurodegenerative disease; therefore, the study on the relationship between single nucleotide polymorphism (SNP) and longitudinal variations of neuroimaging phenotype is crucial. Although some machine learning models have recently been proposed to capture longitudinal patterns in genotype-phenotype association studies, most machine-learning models base the learning on fixed structure among longitudinal prediction tasks rather than automatically learning the interrelationships. In response to this challenge, we propose a new automated time structure learning model to automatically reveal the longitudinal genotype-phenotype interactions and exploits such learned structure to enhance the phenotypic predictions. We proposed an efficient optimization algorithm for our model and provided rigorous theoretical convergence proof. We performed experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort for longitudinal phenotype prediction, including 3123 SNPs and 2 biomarkers (Voxel-Based Morphometry and FreeSurfer). The empirical results validate that our proposed model is superior to the counterparts. In addition, the best SNPs identified by our model have been replicated in the literature, which justifies our prediction.
- Subjects :
- 0301 basic medicine
Longitudinal study
Genotype
Computer science
Imaging genetics
Brain Structure and Function
Neuroimaging
Single-nucleotide polymorphism
Computational biology
Polymorphism, Single Nucleotide
Machine Learning
03 medical and health sciences
0302 clinical medicine
Alzheimer Disease
Genetics
Humans
Association (psychology)
Molecular Biology
Research Articles
Genetic Association Studies
Mechanism (biology)
Brain
Neurodegenerative Diseases
Regression
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
Modeling and Simulation
Algorithms
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 15578666
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- Journal of Computational Biology
- Accession number :
- edsair.doi.dedup.....93bfb988d1237b36a37c60b26469e11d