Identifying Cognitive Subtypes of Mild-to-Moderate Alzheimer’s Disease Using the National Alzheimer’s Coordinating Center Uniform Dataset Neuropsychological Test Battery (P5.180)

Objective: We sought to determine if the NACC Uniform Data Set (UDS) neuropsychological test battery (v. 3) could effectively identify “typical” and “atypical” patterns of cognitive deficits in patients with clinically diagnosed AD. Background: Typical AD is characterized by early, significant episodic memory loss greater than loss in other cognitive domains. A smaller, atypical group of AD patients has early loss greater in non-memory than memory domains. (Dubois et al., 2014) Design/Methods: Principal component (PC) and cluster analyses were applied to cognitive test scores from 962 patients with probable AD and MOCA scores 6 – 20 (mean=13.8, sd=4.1). Mean age was 75.1 (sd=9.9); mean education was 15.3 (sd=3.0). Tests included measures of memory, attention, executive function, language and visuospatial ability. Missing scores were imputed. Derived scores were regressed on clinical and demographic characteristics. Results: Two PCs explained 49% of total variance. Factor loadings for PC1 represented general severity of impairment across all cognitive domains. PC2 had loadings of opposing signs for memory and non-memory domains; patients with relatively greater memory impairment scored lower on PC2. Model-based clustering of patients’ PC scores yielded 2 clusters, one with low scores on PC2 and broad representation on PC1 (“typical” AD), and the other with moderate scores on PC1 and higher scores on PC2 (“atypical” AD). Linear regression models showed that degree of “atypicality” is associated with younger age, fewer APOE e4 alleles, less global impairment and worse depression scores. Conclusions: A principal component analysis from the UDS cognitive test battery yields a continuous score which can classify “typical” and “atypical” AD patients that differ in clinical and demographic characteristics. Future work will investigate diagnostic accuracy (vs. pathology findings) and longitudinal decline as a function of classification, with an eye towards potential impact on clinical trial outcomes. Study Supported by: This research was supported by NIA P50 AG005131 and the Shiley-Marcos Alzheimer’s Disease Research Center at the University of California San Diego Medical Center. The NACC database is funded by NIA/NIH Grant U01 AG016976. NACC data are contributed by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD, MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG005131 (PI James Brewer, MD, PhD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PI Henry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638 (PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PI John Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD). Disclosure: Dr. Qiu has nothing to disclose. Dr. Jacobs has nothing to disclose. Dr. Messer has nothing to disclose. Dr. Salmon has nothing to disclose. Dr. Feldman has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Medscape. Dr. Feldman has received research support from consulting service agreements with UCSD for Tau Rx, Merck, Eisai, Genentech, and Probiodrug (unpaid). Funding to the ADCS for clinical trials with Lilly, Toyama, and Biohaven.