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June 16, 2020; 94 (24) Article

Patterns of longitudinal cortical atrophy over 3 years in empirically derived MCI subtypes

Emily C. Edmonds, View ORCID ProfileAlexandra J. Weigand, Sean N. Hatton, Anisa J. Marshall, Kelsey R. Thomas, Daniela A. Ayala, Mark W. Bondi, Carrie R. McDonald, for the Alzheimer's Disease Neuroimaging Initiative
First published May 11, 2020, DOI: https://doi.org/10.1212/WNL.0000000000009462
Emily C. Edmonds
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Alexandra J. Weigand
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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  • ORCID record for Alexandra J. Weigand
Sean N. Hatton
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Anisa J. Marshall
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Kelsey R. Thomas
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Daniela A. Ayala
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Mark W. Bondi
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Carrie R. McDonald
From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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From the Veterans Affairs San Diego Healthcare System (E.C.E., K.R.T., M.W.B.); Department of Psychiatry (E.C.E., S.N.H., K.R.T., M.W.B., C.R.M.), Center for Multimodal Imaging and Genetics (S.N.H., A.M., C.R.M.), Department of Neurosciences (S.N.H.), and Center for Behavior Genetics of Aging (S.N.H.), University of California San Diego, La Jolla; Joint Doctoral Program in Clinical Psychology (A.J.W., J.E.), San Diego State University/University of California San Diego; Department of Psychology (A.J.M.), University of Southern California, Los Angeles; and Department of Biology (D.A.A.), San Diego State University, CA.
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Patterns of longitudinal cortical atrophy over 3 years in empirically derived MCI subtypes
Emily C. Edmonds, Alexandra J. Weigand, Sean N. Hatton, Anisa J. Marshall, Kelsey R. Thomas, Daniela A. Ayala, Mark W. Bondi, Carrie R. McDonald, for the Alzheimer's Disease Neuroimaging Initiative
Neurology Jun 2020, 94 (24) e2532-e2544; DOI: 10.1212/WNL.0000000000009462

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Abstract

Objective We previously identified 4 empirically derived mild cognitive impairment (MCI) subtypes via cluster analysis within the Alzheimer's Disease Neuroimaging Initiative (ADNI) and demonstrated high correspondence between patterns of cortical thinning at baseline and each cognitive subtype. We aimed to determine whether our MCI subtypes demonstrate unique longitudinal atrophy patterns.

Methods ADNI participants (295 with MCI and 134 cognitively normal [CN]) underwent annual structural MRI and neuropsychological assessments. General linear modeling compared vertex-wise differences in cortical atrophy rates between each MCI subtype and the CN group. Linear mixed models examined trajectories of cortical atrophy over 3 years within lobar regions of interest.

Results Compared to the CN group, those with amnestic MCI (memory deficit) initially demonstrated greater atrophy rates within medial temporal lobe regions that became more widespread over time. Those with dysnomic/amnestic MCI (naming/memory deficits) showed greater atrophy rates largely localized to temporal lobe regions. The mixed MCI (impairment in all cognitive domains) group showed greater atrophy rates in widespread regions at all time points. The cluster-derived normal group, who had intact neuropsychological performance and normal cortical thickness at baseline despite their MCI diagnosis via conventional diagnostic criteria, continued to show normal cognition and minimal cortical atrophy over 3 years.

Conclusions ADNI's purported amnestic MCI sample produced more refined cognitive subtypes with unique longitudinal cortical atrophy rates. These novel MCI subtypes reliably reflect underlying atrophy, reduce false-positive diagnostic errors, and improve prediction of clinical course. Such improvements have implications for the selection of participants for clinical trials and for providing more precise risk assessment for individuals diagnosed with MCI.

Glossary

AD=
Alzheimer disease;
ADNI=
Alzheimer's Disease Neuroimaging Initiative;
AVLT=
Auditory Verbal Learning Test;
CDN=
cluster-derived normal;
CN=
cognitively normal;
MCI=
mild cognitive impairment;
NFT=
neurofibrillary tangle;
ROI=
region of interest

Footnotes

  • Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

  • Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of the ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at in the coinvestigators list at links.lww.com/WNL/B86.

  • Received May 20, 2019.
  • Accepted in final form December 4, 2019.
  • © 2020 American Academy of Neurology
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  • All Neuropsychology/Behavior
  • Alzheimer's disease
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  • Assessment of cognitive disorders/dementia
  • MCI (mild cognitive impairment)

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