BACKGROUND: Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects. METHODS: 201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE 4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included. RESULTS: AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE 4 was not associated with any trajectory. CONCLUSION: Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.
BACKGROUND: Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates, have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects. METHODS: 201 Caucasian subjects with possible or probable Alzheimer's disease (AD) were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept with initial MMSE score, age, gender, education, and APOE 4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included. RESULTS:AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE 4 was not associated with any trajectory. CONCLUSION: Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in AD.
Authors: Ruth O'Hara; Barbara Sommer; Nate Way; Helena C Kraemer; Joy Taylor; Greer Murphy Journal: J Psychiatr Res Date: 2007-01-23 Impact factor: 4.791
Authors: E H Corder; A M Saunders; W J Strittmatter; D E Schmechel; P C Gaskell; G W Small; A D Roses; J L Haines; M A Pericak-Vance Journal: Science Date: 1993-08-13 Impact factor: 47.728
Authors: Oscar L Lopez; Lewis H Kuller; Annette Fitzpatrick; Diane Ives; James T Becker; Norman Beauchamp Journal: Neuroepidemiology Date: 2003 Jan-Feb Impact factor: 3.282
Authors: Jeannie-Marie S Leoutsakos; Dingfen Han; Michelle M Mielke; Sarah N Forrester; JoAnn T Tschanz; Chris D Corcoran; Robert C Green; Maria C Norton; Kathleen A Welsh-Bohmer; Constantine G Lyketsos Journal: Int Psychogeriatr Date: 2012-06-12 Impact factor: 3.878
Authors: Elise A Weamer; Mary Ann A DeMichele-Sweet; Yona K Cloonan; Oscar L Lopez; Robert A Sweet Journal: J Clin Psychiatry Date: 2016-12 Impact factor: 4.384
Authors: Kumar B Rajan; Elizabeth A McAninch; Robert S Wilson; Jennifer Weuve; Lisa L Barnes; Denis A Evans Journal: J Alzheimers Dis Date: 2019 Impact factor: 4.472
Authors: Lirong Wang; Jian Ying; Peihao Fan; Elise A Weamer; Mary Ann A DeMichele-Sweet; Oscar L Lopez; Julia K Kofler; Robert A Sweet Journal: Am J Geriatr Psychiatry Date: 2019-03-27 Impact factor: 4.105
Authors: Anil Varma V Vatsavayi; Julia Kofler; Mary Ann A Demichele-Sweet; Patrick S Murray; Oscar L Lopez; Robert A Sweet Journal: Int Psychogeriatr Date: 2014-03-04 Impact factor: 3.878
Authors: R Wiest; Y Burren; M Hauf; G Schroth; J Pruessner; M Zbinden; K Cattapan-Ludewig; C Kiefer Journal: AJNR Am J Neuroradiol Date: 2012-10-11 Impact factor: 3.825