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1. Mixture modeling for identifying subtypes in disease course mapping

Author

Stanley Durrleman, Pierre-Emmanuel Poulet, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), This research has received funding from the program 'Investissements d’avenir' ANR-10-IAIHU-06. This work was also funded in part by the French government under management of Agence Nationale de la Recherche as part of the 'Investissements d’avenir' program, reference ANR-19-P3IA-0001 (PRAIRIE 3IA Institute)., Aasa Feragen, Stefan Sommer, Julia Schnabel, Mads Nielsen, ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), This paper is funded in part by grant number 678304 (ERC), 826421 (TVB-Cloud) from H2020 programme, and ANR-10-IAIHU-06 (IHU ICM), ANR-19-P3IA-0001 (PRAIRIE) and ANR-19-JPW2-000 (E-DADS) from ANR., Poulet, Pierre-Emmanuel, PaRis Artificial Intelligence Research InstitutE - - PRAIRIE2019 - ANR-19-P3IA-0001 - P3IA - VALID, Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, Population, Stochastic approximation, Machine learning, computer.software_genre, 01 natural sciences, Synthetic data, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Alzheimer's disease subtypes, mixed-effect models, 0101 mathematics, Cognitive decline, mixture models, education, Cluster analysis, Non-linear mixed-effect model, ComputingMilieux_MISCELLANEOUS, Mixture model, Ground truth, education.field_of_study, MCMC-SAEM, business.industry, Contrast (statistics), Disease course mapping, Disease progression modelling, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Artificial intelligence, business, computer, [STAT.ME]Statistics [stat]/Methodology [stat.ME], 030217 neurology & neurosurgery
Abstract

International audience; Disease modeling techniques summarize the possible trajectories of progression from multimodal and longitudinal data. These techniques often assume that individuals form a homogeneous cluster, thus ignoring possible disease subtypes within the population. We extend a non-linear mixed-effect model used for disease course mapping with a mixture framework. We jointly estimate model parameters and subtypes with a tempered version of a stochastic approximation of the Expectation Maximisation algorithm. We show that our model recovers the ground truth parameters from synthetic data, in contrast to the naive solution consisting in post hoc clustering of individual parameters from a one-class model. Applications to Alzheimer's disease data allows the unsupervised identification of disease subtypes associated with distinct relationship between cognitive decline and progression of imaging and biological biomarkers.

Published
2021
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2. Influence of multiple APOE genetic variants on cognitive function in a cohort of older men – results from the Normative Aging Study

Author

David G. Cox, Jia Zhong, Marc G. Weisskopf, Elena Colicino, Marco Sanchez-Guerra, Joel Schwartz, Diddier Prada, Andrea A. Baccarelli, Lifang Hou, Melinda C. Power, Avron Spiro, Luis A. Herrera, Pantel S. Vokonas, Department of Environmental Health, Harvard School of Public Health, Unidad de Investigación Biomédica en Cáncer, Universidad Nacional Autónoma de México (UNAM)-Instituto Nacional de Cancerología – Instituto de Investigaciones Biomédicas, Department of Biomedical Informatics, Universidad Nacional Autónoma de México (UNAM), Department of Epidemiology, Department of Epidemiology [Baltimore], Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU)-Johns Hopkins University (JHU), Centre de Recherche en Cancérologie de Lyon (UNICANCER/CRCL), Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Department of Veterans Affairs, VA Boston Healthcare System, DP is financially supported by Consejo Nacional de Ciencia y Tecnología(CONACYT) and the Fundación México en Harvard from the program'Postdoctoral Fellowships in the Sciences at Harvard University: Mexico'.Thepresent work has been supported by a grant from the National Institute ofEnvironmental Health Sciences (NIEHS) (R01ES021733).MP is supported by a grant from the National Institute of Aging (NIA) (T32AG027668). AS was supported by a Senior Research Career Scientist award fromthe Clinical Science Research and Development Service for the US Departmentof Veterans Affairs. The US Department of Veterans Affairs (VA) Normative AgingStudy (NAS) is supported by the Cooperative Studies Program/ERIC, USDepartment of Veterans Affairs, and is a research component of theMassachusetts Veterans Epidemiology Research and Information Center(MAVERIC). Additional support to the VA Normative Aging Study was providedby the US Department of Agriculture, Agricultural Research Service (contract53-K06-510). The views expressed in this paper are those of the authors and donot necessarily represent the views of the US Department of Veterans Affairs., Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM)-Instituto Nacional de Cancerología – Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Taibi, Nadia

Subjects
Oncology, Apolipoprotein E, Gerontology, Adult, Male, medicine.medical_specialty, Aging, Genetic variants, Genotype, Cognitive decline, Neuropsychological Tests, Odds, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Apolipoproteins E, Cognition, Polymorphism (computer science), Internal medicine, medicine, Humans, MESH: APOE, Epsilon, Alleles, Haplotypes, Genotyping, 030304 developmental biology, Aged, Aged, 80 and over, 0303 health sciences, Polymorphism, Genetic, Haplotype, Middle Aged, Psychiatry and Mental health, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Cohort, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Psychology, Cognition Disorders, 030217 neurology & neurosurgery, APOE, Research Article
Abstract

Background APOE is the biomarker with the greatest known influence on cognitive function; however, the effect of complex haplotypes involving polymorphisms rs449647, rs405509, rs440446, rs429358 and rs7412 has never been studied in older populations. Methods We evaluated APOE polymorphisms using multiplex PCR for genotyping and Mini-Mental State Examination (MMSE) to evaluate cognitive function in 819 individuals from VA Normative Aging Study. Results Combinatorial analysis of all polymorphisms and individual analysis of polymorphisms rs449647, rs405509, rs440446 and rs7412 did not show any association with cognitive performance. Polymorphism rs429358 was associated with better cognitive performance (odds of MMSE ≤ 25 = 0.63, 95% CI 0.42-0.95; p = 0.03) in the oldest subsample (5th quintile of age) (odds of MMSE ≤ 25 = 0.34; 95% CI 0.13-0.86; p = 0.02). APOE allele ε4 was also associated with better cognitive performance (odds of MMSE ≤ 25 = 0.61, 95% CI 0.40-0.94; p = 0.02), also in the oldest subsample (odds of MMSE ≤ 25 = 0.35, 95% CI 0.14-0.90; p = 0.03). Conclusions These results suggest a beneficial effect of polymorphism rs429358 in the oldest men. Electronic supplementary material The online version of this article (doi:10.1186/s12888-014-0223-x) contains supplementary material, which is available to authorized users.

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