Emily C Edmonds1, Lisa Delano-Wood2, Lindsay R Clark3, Amy J Jak2, Daniel A Nation4, Carrie R McDonald1, David J Libon5, Rhoda Au6, Douglas Galasko7, David P Salmon8, Mark W Bondi9. 1. Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, CA, USA. 2. Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA. 3. San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA. 4. Department of Psychology, University of Southern California, Los Angeles, CA, USA. 5. Department of Neurology, Drexel University, College of Medicine, Philadelphia, PA, USA. 6. Department of Neurology, Boston University, School of Medicine, Boston, MA, USA; Framingham Heart Study, Boston University, School of Medicine, Boston, MA, USA. 7. Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Neurosciences, University of California San Diego, School of Medicine, La Jolla, CA, USA. 8. Department of Neurosciences, University of California San Diego, School of Medicine, La Jolla, CA, USA. 9. Department of Psychiatry, University of California San Diego, School of Medicine, La Jolla, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA. Electronic address: mbondi@ucsd.edu.
Abstract
BACKGROUND: We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes. METHODS: Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants. RESULTS: Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group. CONCLUSIONS: Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.
BACKGROUND: We assessed whether mild cognitive impairment (MCI) subtypes could be empirically derived within the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI cohort and examined associated biomarkers and clinical outcomes. METHODS: Cluster analysis was performed on neuropsychological data from 825 MCI ADNI participants. RESULTS: Four subtypes emerged: (1) dysnomic (n = 153), (2) dysexecutive (n = 102), (3) amnestic (n = 288), and (4) cluster-derived normal (n = 282) who performed within normal limits on cognitive testing. The cluster-derived normal group had significantly fewer APOE ε4 carriers and fewer who progressed to dementia compared with the other subtypes; they also evidenced cerebrospinal fluid Alzheimer's disease biomarker profiles that did not differ from the normative reference group. CONCLUSIONS: Identification of empirically derived MCI subtypes demonstrates heterogeneity in MCI cognitive profiles that is not captured by conventional criteria. The large cluster-derived normal group suggests that conventional diagnostic criteria are susceptible to false-positive errors, with the result that prior MCI studies may be diluting important biomarker relationships.
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