ArticleJournal of Alzheimer's disease : JAD2015
Predicting Alzheimer's Disease Using Combined Imaging-Whole Genome SNP Data.
Article in Journal of Alzheimer's disease : JAD, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Potential neuroimaging biomarkers of pathologic brain changes in Mild Cognitive Impairment and Alzheimer's disease: a systematic review.BMC geriatrics · 2016Pooled it
- DYNAMIC PREDICTION WITH MULTIVARIATE LONGITUDINAL OUTCOMES AND LONGITUDINAL MAGNETIC RESONANCE IMAGING DATA.The annals of applied statistics · 2025Article
- Article
- Early prediction of Alzheimer's disease using artificial intelligence and cortical features on T1WI sequences.Frontiers in neurology · 2025Article
- Prognostic model for predicting Alzheimer's disease conversion using functional connectome manifolds.Alzheimer's research & therapy · 2024Article
- Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment.Frontiers in aging neuroscience · 2024Article
- Gene-Environment Analyses in a UK Biobank Skin Cancer Cohort Identifies Important SNPs in DNA Repair Genes That May Help Prognosticate Disease Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Predicting Alzheimer's Disease and Quantifying Asymmetric Degeneration of the Hippocampus Using Deep Learning of Magnetic Resonance Imaging Data.Proceedings. IEEE International Symposium on Biomedical Imaging · 2023Article
- Integrative Bayesian tensor regression for imaging genetics applications.Frontiers in neuroscience · 2023Article
- Joint model for survival and multivariate sparse functional data with application to a study of Alzheimer's Disease.Biometrics · 2022Article
- Screening and predicting progression from high-risk mild cognitive impairment to Alzheimer's disease.Scientific reports · 2021Article
- A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2019Article
- EARLY PREDICTION OF ALZHEIMER'S DISEASE DEMENTIA BASED ON BASELINE HIPPOCAMPAL MRI AND 1-YEAR FOLLOW-UP COGNITIVE MEASURES USING DEEP RECURRENT NEURAL NETWORKS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2019Article
- [Progress in the study of the imaging genomics of Alzheimer's disease].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2019Review
- A Robust Reduced Rank Graph Regression Method for Neuroimaging Genetic Analysis.Neuroinformatics · 2018Article
- Classifying Alzheimer's disease with brain imaging and genetic data using a neural network framework.Neurobiology of aging · 2018Article
- A prognostic model of Alzheimer's disease relying on multiple longitudinal measures and time-to-event data.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2018Observational
- Radiomic analysis in prediction of Human Papilloma Virus status.Clinical and translational radiation oncology · 2017Article
- Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017Review
- Potential fluid biomarkers for pathological brain changes in Alzheimer's disease: Implication for the screening of cognitive frailty.Molecular medicine reports · 2016Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The growing public threat of Alzheimer's disease (AD) has raised the urgency to discover and validate prognostic biomarkers in order to predicting time to onset of AD. It is anticipated that both whole genome single nucleotide polymorphism (SNP) data and high dimensional whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. The aim of this paper is to test whether both whole genome SNP data and whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. In 343 subjects with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI-1), we extracted high dimensional MR imaging (volumetric data on 93 brain regions plus a surface fluid registration based hippocampal subregion and surface data), and whole genome data (504,095 SNPs from GWAS), as well as routine neurocognitive and clinical data at baseline. MCI patients were then followed over 48 months, with 150 participants progressing to AD. Combining information from whole brain MR imaging and whole genome data was substantially superior to the standard model for predicting time to onset of AD in a 48-month national study of subjects at risk. Our findings demonstrate the promise of combined imaging-whole genome prognostic markers in people with mild memory impairment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.