Literature DB >> 21893661

Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

Jesus J Gomar1, Maria T Bobes-Bascaran, Concepcion Conejero-Goldberg, Peter Davies, Terry E Goldberg.   

Abstract

CONTEXT: Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors.
OBJECTIVE: To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease.
DESIGN: Longitudinal study. PARTICIPANTS: We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses.
SETTING: The Alzheimer's Disease Neuroimaging Initiative public database. OUTCOME MEASURES: Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes.
RESULTS: In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease.
CONCLUSIONS: Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic trajectory of the disease than by a sharp decline in functional ability and, to a lesser extent, by declines in executive function.

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Year:  2011        PMID: 21893661     DOI: 10.1001/archgenpsychiatry.2011.96

Source DB:  PubMed          Journal:  Arch Gen Psychiatry        ISSN: 0003-990X


  126 in total

1.  A composite score for executive functioning, validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment.

Authors:  Laura E Gibbons; Adam C Carle; R Scott Mackin; Danielle Harvey; Shubhabrata Mukherjee; Philip Insel; S McKay Curtis; Dan Mungas; Paul K Crane
Journal:  Brain Imaging Behav       Date:  2012-12       Impact factor: 3.978

2.  Use of Flutemetamol F 18-Labeled Positron Emission Tomography and Other Biomarkers to Assess Risk of Clinical Progression in Patients With Amnestic Mild Cognitive Impairment.

Authors:  David A Wolk; Carl Sadowsky; Beth Safirstein; Juha O Rinne; Ranjan Duara; Richard Perry; Marc Agronin; Jose Gamez; Jiong Shi; Adrian Ivanoiu; Lennart Minthon; Zuzana Walker; Steen Hasselbalch; Clive Holmes; Marwan Sabbagh; Marilyn Albert; Adam Fleisher; Paul Loughlin; Eric Triau; Kirk Frey; Peter Høgh; Andrea Bozoki; Roger Bullock; Eric Salmon; Gillian Farrar; Christopher J Buckley; Michelle Zanette; Paul F Sherwin; Andrea Cherubini; Fraser Inglis
Journal:  JAMA Neurol       Date:  2018-09-01       Impact factor: 18.302

3.  ApoE and pulse pressure interactively influence level and change in the aging of episodic memory: Protective effects among ε2 carriers.

Authors:  G Peggy McFall; Sandra A Wiebe; David Vergote; David Westaway; Jack Jhamandas; Lars Bäckman; Roger A Dixon
Journal:  Neuropsychology       Date:  2014-12-01       Impact factor: 3.295

4.  Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers.

Authors:  Jennifer L Shaffer; Jeffrey R Petrella; Forrest C Sheldon; Kingshuk Roy Choudhury; Vince D Calhoun; R Edward Coleman; P Murali Doraiswamy
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5.  Isomer-specific chromatographic profiling yields highly sensitive and specific potential N-glycan biomarkers for epithelial ovarian cancer.

Authors:  Serenus Hua; Cynthia C Williams; Lauren M Dimapasoc; Grace S Ro; Sureyya Ozcan; Suzanne Miyamoto; Carlito B Lebrilla; Hyun Joo An; Gary S Leiserowitz
Journal:  J Chromatogr A       Date:  2013-01-11       Impact factor: 4.759

6.  Amyloid-β Positivity Predicts Cognitive Decline but Cognition Predicts Progression to Amyloid-β Positivity.

Authors:  Jeremy A Elman; Matthew S Panizzon; Daniel E Gustavson; Carol E Franz; Mark E Sanderson-Cimino; Michael J Lyons; William S Kremen
Journal:  Biol Psychiatry       Date:  2020-01-07       Impact factor: 13.382

7.  Prediction of Conversion to Alzheimer's Disease with Longitudinal Measures and Time-To-Event Data.

Authors:  Kan Li; Wenyaw Chan; Rachelle S Doody; Joseph Quinn; Sheng Luo
Journal:  J Alzheimers Dis       Date:  2017       Impact factor: 4.472

8.  The Relationship Between Cognitive Impairment and Upper Extremity Function in Older Primary Care Patients.

Authors:  Sarah Seligman Rycroft; Lien T Quach; Rachel E Ward; Mette M Pedersen; Laura Grande; Jonathan F Bean
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2019-03-14       Impact factor: 6.053

9.  Class-Specific Incidence of All-Cause Dementia and Alzheimer's Disease: A Latent Class Approach.

Authors:  Andrea R Zammit; Charles B Hall; Mindy J Katz; Graciela Muniz-Terrera; Ali Ezzati; David A Bennett; Richard B Lipton
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

10.  The co-existence of geriatric depression and amnestic mild cognitive impairment detrimentally affect gray matter volumes: voxel-based morphometry study.

Authors:  Chunming Xie; Wenjun Li; Gang Chen; B Douglas Ward; Malgorzata B Franczak; Jennifer L Jones; Piero G Antuono; Shi-Jiang Li; Joseph S Goveas
Journal:  Behav Brain Res       Date:  2012-08-14       Impact factor: 3.332

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