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Multilevel Survival Modeling with Structured Penalties for Disease Prediction from Imaging Genetics data

Pascal Lu 1 Olivier Colliot 1 
1 ARAMIS - Algorithms, models and methods for images and signals of the human brain
SU - Sorbonne Université, Inria de Paris, ICM - Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute
Abstract : This paper introduces a framework for disease prediction from multimodal genetic and imaging data. We propose a multilevel survival model which allows predicting the time of occurrence of a future disease state in patients initially exhibitingmild symptoms. This new multilevel setting allows modeling the interactions between genetic and imaging variables. This is incontrast with classical additive models which treat all modalities in the same manner and can result in undesirable elimination of specific modalities when their contributions are unbalanced. Moreover, the use of a survival model allows overcoming the limitations of previous approaches based on classification which consider a fixed time frame. Furthermore, we introduce specific penalties taking into account the structure of the different types of data, such as a group lasso penalty over the genetic modality a a ℓ2-penalty over the imaging modality. Finally, we propose a fast optimization algorithm, based on a proximal gradient method. The approach was applied to the prediction of Alzheimer’s disease (AD) among patients with mild cognitive impairment(MCI) based on genetic (single nucleotide polymorphisms - SNP) and imaging (anatomical MRI measures) data from the ADNI database. The experiments demonstrate the effectiveness of the method for predicting the time of conversion to AD. It revealed how genetic variants and brain imaging alterations interact in theprediction of future disease status. The approach is generic and could potentially be useful for the prediction of other diseases
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Submitted on : Saturday, August 14, 2021 - 9:32:54 AM
Last modification on : Thursday, August 4, 2022 - 5:22:33 PM

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Pascal Lu, Olivier Colliot. Multilevel Survival Modeling with Structured Penalties for Disease Prediction from Imaging Genetics data. IEEE Journal of Biomedical and Health Informatics, Institute of Electrical and Electronics Engineers, 2022, 26 (2), pp.798-808. ⟨10.1109/JBHI.2021.3100918⟩. ⟨hal-03311509v2⟩

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