Affiliations: [a]
Banner Alzheimer’s Institute, Phoenix, AZ, USA
| [b] Williams College, Williamstown, MA, USA
| [c] Arizona State University, Tempe, AZ, USA
| [d] Department of Neurobiology and Neurology, Barrow Neurological Institute, Phoenix, AZ, USA
Correspondence:
[*]
Correspondence to: Elliott Mufson, PhD, Director, Alzheimer’s Disease Research Laboratory, Professor, Department of Neurobiology, Barrow Neurological Institute, 350 W. Thomas Rd., Phoenix, AZ 85013, USA. Tel.: +1 602 406 8525; Fax: +1 602 406 8520; E-mail: [email protected].
Abstract: Within neuropsychology, the term dispersion refers to the degree of variation in performance between different cognitive domains for an individual. Previous studies have demonstrated that cognitively normal individuals with higher dispersion are at an increased risk for progressing to mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Therefore, we determined 1) whether increased dispersion in older adults was associated with amyloid plaques and neurofibrillary tangles (NFTs) and 2) whether increased cognitive dispersion accurately differentiated MCI and AD from non-cognitively impaired (NCI) individuals. The intra-subject standard deviation (ISD) was used to quantify cognitive dispersion, and receiver operator characteristic (ROC) analysis determined whether ISD differentiated MCI and AD from NCI. Neuropathological scores for diffuse plaques (DPs), neuritic plaques (NPs), and NFTs were used as outcome measures in a series of negative binomial regression models. Regression analyses found that increased ISD was associated with increased NFT pathology (β= 10.93, SE = 3.82, p = 0.004), but not with DPs (β= 1.33, SE = 8.85, p = 0.88) or NPs (β= 14.64, SE = 8.45, p = 0.08) after adjusting for age at death, gender, education, APOE ɛ4 status, and clinical diagnosis. An interaction term of ISD with age at death also showed a significant negative association (β= –0.13, SE = 0.04, p = 0.004), revealing an age-dependent association between ISD with NFTs. The ISD failed to show an acceptable level of diagnostic accuracy for MCI (AUC = 0.60). These findings suggest that increased cognitive dispersion is related to NFT pathology where age significantly affects this association.
