title: Prediction of cognitive decline in healthy older adults using fMRI.
abstract: Few studies have examined the extent to which structural and functional MRI, alone and in combination with genetic biomarkers, can predict future cognitive decline in asymptomatic elders. This prospective study evaluated individual and combined contributions of demographic information, genetic risk, hippocampal volume, and fMRI activation for predicting cognitive decline after an 18-month retest interval. Standardized neuropsychological testing, an fMRI semantic memory task (famous name discrimination), and structural MRI (sMRI) were performed on 78 healthy elders (73% female; mean age = 73 years, range = 65 to 88 years). Positive family history of dementia and presence of one or both apolipoprotein E (APOE) ε4 alleles occurred in 51.3% and 33.3% of the sample, respectively. Hippocampal volumes were traced from sMRI scans. At follow-up, all participants underwent a repeat neuropsychological examination. At 18 months, 27 participants (34.6%) declined by at least 1 SD on one of three neuropsychological measures. Using logistic regression, demographic variables (age, years of education, gender) and family history of dementia did not predict future cognitive decline. Greater fMRI activity, absence of an APOE ε4 allele, and larger hippocampal volume were associated with reduced likelihood of cognitive decline. The most effective combination of predictors involved fMRI brain activity and APOE ε4 status. Brain activity measured from task-activated fMRI, in combination with APOE ε4 status, was successful in identifying cognitively intact individuals at greatest risk for developing cognitive decline over a relatively brief time period. These results have implications for enriching prevention clinical trials designed to slow AD progression.
authors.affiliation: Department of Psychology, Wayne State University, Detroit, MI, USA.
authors.forename: John L
authors.initials: JL
authors.lastname: Woodard
authors.forename: Michael
authors.initials: M
authors.lastname: Seidenberg
authors.forename: Kristy A
authors.initials: KA
authors.lastname: Nielson
authors.forename: J Carson
authors.initials: JC
authors.lastname: Smith
authors.forename: Piero
authors.initials: P
authors.lastname: Antuono
authors.forename: Sally
authors.initials: S
authors.lastname: Durgerian
authors.forename: Leslie
authors.initials: L
authors.lastname: Guidotti
authors.forename: Qi
authors.initials: Q
authors.lastname: Zhang
authors.forename: Alissa
authors.initials: A
authors.lastname: Butts
authors.forename: Nathan
authors.initials: N
authors.lastname: Hantke
authors.forename: Melissa
authors.initials: M
authors.lastname: Lancaster
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Rao
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D053327:Apolipoprotein E4 / Q000235:genetics; D003072:Cognition Disorders / Q000175:diagnosis* / Q000235:genetics / Q000503:physiopathology; D005260:Female; D006624:Hippocampus / Q000033:anatomy & histology* / Q000503:physiopathology; D006801:Humans; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009483:Neuropsychological Tests; D009929:Organ Size; D012307:Risk Factors
chemical_list: D053327:Apolipoprotein E4