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 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 ε4 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 ε4 was not associated with any trajectory. Conclusion Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in Alzheimer disease.
Objective To compare the trajectories of cognitive decline between groups with, and without, the later development of psychotic symptoms during Alzheimer disease (AD) or Mild Cognitive Impairment (MCI). Design We examined cognitive function in a new analysis of an existing data set, The Cardiovascular Health Study (CHS), an epidemiologic, longitudinal follow-up study. Our analyses examined 9 years of follow-up data. Setting Community. Participants We examined subjects who were without dementia at study entry, received a diagnosis of AD or MCI during follow up and had been rated on the Neuropsychiatric Inventory for the presence of psychosis; 362 for the Modified Mini-Mental State Examination (3MS) analysis and 350 for the Digit Symbol Substitution Test (DSST) analysis had sufficient follow-up data and APOE genotyping. Measurements The 3MS and DSST were administered annually and analyzed using mixed effects models including APOE4 status. Results Mean 3MS and DSST scores did not differ between AD with psychosis and without psychosis groups at baseline. 3MS and DSST scores decreased more rapidly in subjects who ultimately developed psychosis. Conclusions Individuals who ultimately develop psychosis have more rapid cognitive deterioration during the earliest phases of AD than individuals with AD not developing psychosis. The genetic and other neurobiologic factors leading to the expression of AD+P may exert their effects via acceleration of the neurodegenerative process.
Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer Disease, affecting ~ 40% to 60% of individuals with AD (AD with psychosis, AD+P). In comparison to AD subjects without psychosis, AD+P subjects have more rapid cognitive decline and poor outcomes. Prior studies have estimated the heritability of psychosis in AD at 61%, but the underlying genetic sources of this risk are not known. We evaluated a Discovery Cohort of 2876 AD subjects with (N=1761) or without psychosis (N=1115). All subjects were genotyped using a custom genotyping array designed to evaluate SNPs with evidence of genetic association with AD+P and include SNPs affecting or putatively affecting risk for schizophrenia and Alzheimer disease. Results were replicated in an independent cohort of 2194 AD subjects with (N=734) or without psychosis (N=1460). We found that AD+P is associated with polygenic risk for a set of novel loci and inversely associated with polygenic risk for schizophrenia. Among the biologic pathways identified by the associations of schizophrenia SNPs with AD+P are endosomal trafficking, autophagy, and calcium channel signaling. These findings provide the first clear demonstration that AD+P is associated with common genetic variation. In addition, they provide an unbiased link between polygenic risk for schizophrenia and a lower risk of psychosis in AD. This provides an opportunity to leverage progress made in identifying the biologic effects of schizophrenia alleles to identify novel mechanisms protecting against more rapid cognitive decline and psychosis risk in AD.
Objective Patients with late onset Alzheimer disease (AD) vary widely in their trajectory of cognitive decline. Genetic variations in CLU, PICALM, and CR1 are associated with AD, but it is unknown if they exert their effects via altering cognitive trajectory in elderly subjects at risk for AD. Methods We developed a Bayesian model to fit cognitive trajectories in a cohort of elderly subjects and test for genetic effects. We first validated the model’s ability to detect the previously established effects of APOE epsilon 4 alleles on age at cognitive decline and of psychosis on the rate of cognitive decline in 802 subjects from the Cardiovascular Health Study Cognition Study who were without dementia at study entry and developed incident dementia during follow-up. We then evaluated the effects of CLU, PICALM, and CR1 on age and rate of decline in 1831 subjects without dementia at study entry, including those who did, or did not develop incident dementia at study’s end. Results Our model generated robust fits to the observed cognitive trajectory data. Validation analysis supported the utility of the model. CLU and CR1 were associated with more rapid cognitive decline. PICALM was associated with an earlier age at midpoint of cognitive decline. Associations remained after accounting for the effects of APOE and demographic factors. Conclusions Evaluation of cognitive trajectories provides a powerful approach to dissecting genetic effects on the processes leading to cognitive deterioration and AD.
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