Within-Individual Variability: An Index for Subtle Change in Neurocognition in Mild Cognitive Impairment

Article type: Research Article

Authors: Roalf, David R.^{a; *} | Quarmley, Megan^a | Mechanic-Hamilton, Dawn^a | Wolk, David A.^{b; c} | Arnold, Steven E.^{a; b; c; d} | Moberg, Paul J.^{a; b; c} | for the Alzheimer’s Disease Neuroimaging Initiative

Affiliations: [a] Department of Psychiatry, Philadelphia, PA, USA | [b] Department of Neurology, Philadelphia, PA, USA | [c] Alzheimer’s Disease Center of the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA | [d] Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

Correspondence: [*] Correspondence to: David R. Roalf, PhD, Department of Psychiatry, Neuropsychiatry Section, Brain Behavior Laboratory, 10th Floor, Gates Building, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA; Tel.: +1 215 615 3609; Fax: +1 215 662 7903; E-mail: roalf@upenn.edu.

Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.us.edu). As such, the investigators within the ADNI contributed to the design and implementation and 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: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Abstract: Background: The transition from mild cognitive impairment (MCI) to Alzheimer’s disease is characterized by a decline in cognitive performance in many domains. Cognitive performance profiles in MCI are heterogeneous, however, and additional insights into markers of incipient dementia are needed. Typically, studies focus on average or mean performance, but ignore consistency of performance across domains. WIV (within-individual variability) provides an index of this consistency and is a potential marker of cognitive decline. Objective: To use neurocognitive data from the Alzheimer’s Disease Neuroimaging Initiative cohort to measure neurocognitive variability. Methods: The utility of WIV was measured, in addition to global neurocognitive performance (GNP), for identifying AD and MCI. In addition, the association between changes in neurocognitive variability and diagnostic transition over 12 months was measured. Results: As expected, variability was higher in AD and MCI as compared to healthy controls; GNP was lower in both groups as compared to healthy subjects. Global neurocognitive performance alone best distinguished those with dementia from healthy older adults. Yet, for individuals with MCI, including variability along with GNP improved diagnostic classification. Variability was higher at baseline in individuals transitioning from MCI to AD over a 12-month period. Conclusion: We conclude that variability offers complementary information about neurocognitive performance in dementia, particularly in individuals with MCI, and may provide beneficial information about disease transition.

Keywords: ADNI, Alzheimer’s disease, intra-individual variability, mild cognitive impairment, neurocognitive function

DOI: 10.3233/JAD-160259

Journal: Journal of Alzheimer's Disease, vol. 54, no. 1, pp. 325-335, 2016