The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans

Mohamad Habes; Raymond Pomponio; Haochang Shou; Jimit Doshi; Elizabeth Mamourian; Guray Erus; Ilya Nasrallah; Lenore J Launer; Tanweer Rashid; Murat Bilgel; Yong Fan; Jon B Toledo; Kristine Yaffe; Aristeidis Sotiras; Dhivya Srinivasan; Mark Espeland; Colin Masters; Paul Maruff; Jurgen Fripp; Henry Völzk; Sterling C Johnson; John C Morris; Marilyn S Albert; Michael I Miller; R Nick Bryan; Hans J Grabe; Susan M Resnick; David A Wolk; Christos Davatzikos; iSTAGING consortium, the Preclinical AD consortium, the ADNI, and the CARDIA studies

doi:10.1002/alz.12178

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans

Alzheimers Dement. 2021 Jan;17(1):89-102. doi: 10.1002/alz.12178. Epub 2020 Sep 13.

Authors

Mohamad Habes^{1

2

3

4}, Raymond Pomponio^{1

4}, Haochang Shou^{1

5}, Jimit Doshi^{1

4}, Elizabeth Mamourian^{1

4}, Guray Erus^{1

4}, Ilya Nasrallah^{1

4}, Lenore J Launer⁶, Tanweer Rashid^{1

4}, Murat Bilgel⁷, Yong Fan^{1

4}, Jon B Toledo^{8

9}, Kristine Yaffe¹⁰, Aristeidis Sotiras^{1

11}, Dhivya Srinivasan^{1

4}, Mark Espeland¹², Colin Masters¹³, Paul Maruff¹³, Jurgen Fripp¹⁴, Henry Völzk¹⁵, Sterling C Johnson¹⁶, John C Morris¹⁷, Marilyn S Albert¹⁸, Michael I Miller¹⁹, R Nick Bryan²⁰, Hans J Grabe^{21

22}, Susan M Resnick⁷, David A Wolk^{1

2}, Christos Davatzikos^{1

4}; iSTAGING consortium, the Preclinical AD consortium, the ADNI, and the CARDIA studies¹

Affiliations

¹ Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
² Department of Neurology and Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
³ Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
⁴ Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁵ Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁶ Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland, USA.
⁷ Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland, USA.
⁸ Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.
⁹ Stanley Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas, USA.
¹⁰ Departments of Neurology, Psychiatry and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
¹¹ Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
¹² Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
¹³ Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
¹⁴ CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Australia.
¹⁵ Institute for Community Medicine, University of Greifswald, Greifswald, Germany.
¹⁶ Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
¹⁷ Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.
¹⁸ Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
¹⁹ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
²⁰ Department of Diagnostic Medicine, University of Texas, Austin, Texas, USA.
²¹ Department of Psychiatry and Psychotherapy, University of Greifswald, Germany.
²² German Center for Neurodegenerative Diseases (DZNE), Rostock, Greifswald, Germany.

Abstract

Introduction: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects).

Methods: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD.

Results: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aβ) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD.

Discussion: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.

Keywords: Alzheimer's disease pathology; Dementia; MRI; Machine Learning; Neuroimaging; PET; beta-amyloid; brain aging; brain signatures; cognitive testing; harmonized neuroimaging cohorts; preclinical Alzheimer's disease; small vessel ischemic disease; tau.

Publication types

Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural

MeSH terms

Adult
Aged
Aged, 80 and over
Aging / physiology*
Amyloid beta-Peptides / metabolism*
Atrophy
Biomarkers
Brain / growth & development*
Cerebral Small Vessel Diseases / metabolism
Cerebral Small Vessel Diseases / psychology
Cognitive Dysfunction
Disease Progression
Female
Humans
Image Processing, Computer-Assisted
Machine Learning*
Magnetic Resonance Imaging / methods*
Male
Middle Aged
Neuropsychological Tests
White Matter / growth & development*
White Matter / pathology
Young Adult

Substances

Amyloid beta-Peptides
Biomarkers

Abstract

Publication types

MeSH terms

Substances

Grants and funding