Identification and temporal characterization of features associated with the conversion from mild cognitive impairment to Alzheimer’s disease

Antonio Martinez-Torteya; Hugo Gomez-Rueda; Victor Trevino; Joshua Farber; Jose Tamez-Peña

doi:10.2174/1567205015666180202095616

Identification and temporal characterization of features associated with the conversion from mild cognitive impairment to Alzheimer’s disease

Antonio Martinez-Torteya, Hugo Gomez-Rueda, Victor Trevino, Joshua Farber, Jose Tamez-Peña

Departamento de Ingeniería

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

Background: Diagnosing Alzheimer’s disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications. Objectives: The goals of this study were to identify features from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion. Methods: We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion. Results: 411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis. Conclusion: Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.

Original language	English
Pages (from-to)	751-763
Number of pages	13
Journal	Current Alzheimer Research
Volume	15
Issue number	8
DOIs	https://doi.org/10.2174/1567205015666180202095616
Publication status	Published - 1 Jan 2018

Bibliographical note

Funding Information:
Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigación Grant.

Funding Information:
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-center initiative sponsored by the National Institutes of Health. Despite its name, the database includes subjects’ information from laboratory assays, medical histories, serial MRI and PET scans, and neuropsychological tests. This longitudinal database is available to the public and includes information on subjects with MCI and AD, as well as on healthy controls. In total, the ADNI database is a repository of more than two thousand features of brain morphology and function which have been measured biannually or annually for up to ten years.

Funding Information:
AMT conceived and was responsible for performing the statistical analysis and was primarily responsible for drafting the first version of the manuscript. HGR drafted the discussion and helped to draft the manuscript. JF contributed to the discussion, conclusions and helped to revise and finalize the manuscript. VT help to draft the statistical analysis plan and helped to draft the manuscript. JGTP coconceived and was responsible for overall planning and design of the study, and helped to revise and finalize the manuscript. All authors read and approved the final manuscript. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigación Grant.

Publisher Copyright:
© 2018 Bentham Science Publishers.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

Neurology
Clinical Neurology

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10.2174/1567205015666180202095616

Cite this

@article{dec8cfe6223c4edeacdfcf081257cd65,

title = "Identification and temporal characterization of features associated with the conversion from mild cognitive impairment to Alzheimer{\textquoteright}s disease",

abstract = "Background: Diagnosing Alzheimer{\textquoteright}s disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications. Objectives: The goals of this study were to identify features from the Alzheimer{\textquoteright}s Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion. Methods: We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion. Results: 411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis. Conclusion: Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.",

author = "Antonio Martinez-Torteya and Hugo Gomez-Rueda and Victor Trevino and Joshua Farber and Jose Tamez-Pe{\~n}a",

note = "Funding Information: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer{\textquoteright}s Association; Alzheimer{\textquoteright}s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer{\textquoteright}s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnolog{\'i}a (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigaci{\'o}n Grant. Funding Information: The Alzheimer{\textquoteright}s Disease Neuroimaging Initiative (ADNI) is a multi-center initiative sponsored by the National Institutes of Health. Despite its name, the database includes subjects{\textquoteright} information from laboratory assays, medical histories, serial MRI and PET scans, and neuropsychological tests. This longitudinal database is available to the public and includes information on subjects with MCI and AD, as well as on healthy controls. In total, the ADNI database is a repository of more than two thousand features of brain morphology and function which have been measured biannually or annually for up to ten years. Funding Information: AMT conceived and was responsible for performing the statistical analysis and was primarily responsible for drafting the first version of the manuscript. HGR drafted the discussion and helped to draft the manuscript. JF contributed to the discussion, conclusions and helped to revise and finalize the manuscript. VT help to draft the statistical analysis plan and helped to draft the manuscript. JGTP coconceived and was responsible for overall planning and design of the study, and helped to revise and finalize the manuscript. All authors read and approved the final manuscript. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer{\textquoteright}s Association; Alzheimer{\textquoteright}s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer{\textquoteright}s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnolog{\'i}a (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigaci{\'o}n Grant. Publisher Copyright: {\textcopyright} 2018 Bentham Science Publishers. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",

year = "2018",

month = jan,

day = "1",

doi = "10.2174/1567205015666180202095616",

language = "English",

volume = "15",

pages = "751--763",

journal = "Current Alzheimer Research",

issn = "1567-2050",

publisher = "Bentham Science Publishers",

number = "8",

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TY - JOUR

T1 - Identification and temporal characterization of features associated with the conversion from mild cognitive impairment to Alzheimer’s disease

AU - Martinez-Torteya, Antonio

AU - Gomez-Rueda, Hugo

AU - Trevino, Victor

AU - Farber, Joshua

AU - Tamez-Peña, Jose

N1 - Funding Information: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigación Grant. Funding Information: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-center initiative sponsored by the National Institutes of Health. Despite its name, the database includes subjects’ information from laboratory assays, medical histories, serial MRI and PET scans, and neuropsychological tests. This longitudinal database is available to the public and includes information on subjects with MCI and AD, as well as on healthy controls. In total, the ADNI database is a repository of more than two thousand features of brain morphology and function which have been measured biannually or annually for up to ten years. Funding Information: AMT conceived and was responsible for performing the statistical analysis and was primarily responsible for drafting the first version of the manuscript. HGR drafted the discussion and helped to draft the manuscript. JF contributed to the discussion, conclusions and helped to revise and finalize the manuscript. VT help to draft the statistical analysis plan and helped to draft the manuscript. JGTP coconceived and was responsible for overall planning and design of the study, and helped to revise and finalize the manuscript. All authors read and approved the final manuscript. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work was partially supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) through the SEP-CONACYT Ciencia Basica Grant 16864 and by Universidad de Monterrey through the Fondo de Fomentos a la Investigación Grant. Publisher Copyright: © 2018 Bentham Science Publishers. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: Diagnosing Alzheimer’s disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications. Objectives: The goals of this study were to identify features from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion. Methods: We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion. Results: 411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis. Conclusion: Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.

AB - Background: Diagnosing Alzheimer’s disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications. Objectives: The goals of this study were to identify features from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion. Methods: We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion. Results: 411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis. Conclusion: Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.

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VL - 15

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JO - Current Alzheimer Research

JF - Current Alzheimer Research

IS - 8

ER -

Identification and temporal characterization of features associated with the conversion from mild cognitive impairment to Alzheimer’s disease

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