Multiple markers contribute to risk of progression from normal to mild cognitive impairment

Jennifer S. Rabin; Taylor E. Neal; Hannah E. Nierle; Sietske A.M. Sikkes; Rachel F. Buckley; Rebecca E. Amariglio; Kathryn V. Papp; Dorene M. Rentz; Aaron P. Schultz; Keith A. Johnson; Reisa A. Sperling; Trey Hedden

NeuroImage: Clinical (Jan 2020)

Multiple markers contribute to risk of progression from normal to mild cognitive impairment

Jennifer S. Rabin,
Taylor E. Neal,
Hannah E. Nierle,
Sietske A.M. Sikkes,
Rachel F. Buckley,
Rebecca E. Amariglio,
Kathryn V. Papp,
Dorene M. Rentz,
Aaron P. Schultz,
Keith A. Johnson,
Reisa A. Sperling,
Trey Hedden

Affiliations

Jennifer S. Rabin: Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Harquail Centre for Neuromodulation and Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Department of Medicine (Neurology), University of Toronto, Toronto, ON M5S 3H2, Canada
Taylor E. Neal: Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
Hannah E. Nierle: Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
Sietske A.M. Sikkes: Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit, The Netherlands; Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA
Rachel F. Buckley: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Florey Institutes of Neuroscience and Mental Health, Melbourne and Melbourne School of Psychological Science, University of Melbourne, Melbourne, Australia; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
Rebecca E. Amariglio: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
Kathryn V. Papp: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
Dorene M. Rentz: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
Aaron P. Schultz: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
Keith A. Johnson: Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, MA 02144, USA
Reisa A. Sperling: Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
Trey Hedden: Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Corresponding author.

Journal volume & issue: Vol. 28
p. 102400

Abstract

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Objective: To identify a parsimonious set of markers that optimally predicts subsequent clinical progression from normal to mild cognitive impairment (MCI). Methods: 250 clinically normal adults (mean age = 73.6 years, SD = 6.0) from the Harvard Aging Brain Study were assessed at baseline on a wide set of markers, including magnetic resonance imaging markers of gray matter thickness and volume, white matter lesions, fractional anisotropy, resting state functional connectivity, positron emission tomography markers of glucose metabolism and β-amyloid (Aβ) burden, and a measure of vascular risk. Participants were also tested annually on a battery of clinical and cognitive tests (median follow-up = 5.0 years, SD = 1.66). We applied least absolute shrinkage and selection operator (LASSO) Cox models to determine the minimum set of non-redundant markers that predicts subsequent clinical progression from normal to MCI, adjusting for age, sex, and education. Results: 23 participants (9.2%) progressed to MCI over the study period (mean years of follow-up to diagnosis = 3.96, SD = 1.89). Progression was predicted by several brain markers, including reduced entorhinal thickness (hazard ratio, HR = 1.73), greater Aβ burden (HR = 1.58), lower default network connectivity (HR = 1.42), and smaller hippocampal volume (HR = 1.30). When cognitive test scores were added to the model, the aforementioned neuroimaging markers remained significant and lower striatum volume as well as lower scores on baseline memory and processing speed tests additionally contributed to progression. Conclusion: Among a large set of brain, vascular and cognitive markers, a subset of markers independently predicted progression from normal to MCI. These markers may enhance risk stratification by identifying clinically normal individuals who are most likely to develop clinical symptoms and would likely benefit most from therapeutic intervention.

Published in NeuroImage: Clinical

ISSN: 2213-1582 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system
Website: http://www.journals.elsevier.com/neuroimage-clinical/

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