Six‐month decline in language, but not other cognitive domains, identifies increased risk of conversion from MCI to AD in ADNI: Biomarkers (non‐neuroimaging) / Longitudinal change over time. (7th December 2020)

• Record Type: Journal Article
• Authors: Tommet, Douglas; Choi, Seo‐Eun; Rabin, Laura; Sikkes, Sietske A.M.; Jutten, Roos J.; Grandoit, Evan; Foldi, Nancy; Jones, Richard N.; Lamar, Melissa; Gibbons, Laura E.; Mukherjee, Shubhabrata; Lee, Michael L.; Sanders, R. Elizabeth; Saykin, Andrew J.; Trittschuh, Emily H.; Mez, Jesse; Risacher, Shannon L.; Crane, Paul K.
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.045357
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Identifying people with MCI at greatest risk of AD conversion is an important research goal. Our objective was to determine whether changes in domain‐specific cognitive functioning over 6 months could identify people at greatest risk of AD conversion. Method: We used modern psychometric methods applied to the ADNI cognitive battery to develop composite scores for memory, executive functioning, language, and visuospatial functioning. We considered scores at baseline and 6‐month visits for the 809 participants who had prevalent MCI in ADNI1, ADNIGO, and ADNI2, and characterized people based on quartiles of 6‐month changes in each domain. We used Cox models to determine whether 6‐month changes for each domain associated with risk for conversion to AD. We compared 6‐month changes to APOE genotype and the AD CSF biomarker signature, controlling for age, sex, and years of education. Result: 305 participants (38%) had zero bottom quartile change scores (most decline); 296 (37%) had one; 138 (17%) had two; 60 (7%) had three; and 10 (1.2%) had all four. Cox model results for 6‐month changes in all four domains without and with APOE genotype are shown in Table 1. There were 173 people with CSF results to characterize the AD biomarker signature. Cox results are shown in Table 2. Compared to people in the top quartile for 6‐month language change (most learning), people in the bottom quartile (most decline) were at increased risk of AD conversion, independent of APOE genotype and the AD biomarker signature. For 6‐month memory change, the hazard ratio for the bottom quartile (most decline) was attenuated when APOE genotype was included in the model, and it was null when the CSF biomarker signature was included. 6‐month changes in executive functioning and visuospatial functioning were not associated with risk of AD conversion. Conclusion: 6‐month changes in language identify people with MCI at highest risk of AD conversion. This effect is not explained by APOE genotype or CSF biomarkers. 6‐month language scores may identify people to target in AD prevention trials.