TY - JOUR
T1 - Anosognosia g pIS an independent py g predictor of conversion y From mild cognitive impairment to Alzheimer’s disease and is associated with reduced brain metabolism
AU - Alzheimer's Disease Neuroimaging Initiative
AU - Gerretsen, Philip
AU - Chung, Jun Ku
AU - Shah, Parita
AU - Plitman, Eric
AU - Iwata, Yusuke
AU - Caravaggio, Fernando
AU - Nakajima, Shinichiro
AU - Pollock, Bruce G.
AU - Graff-Guerrero, Ariel
N1 - Funding Information:
supported by OMHF –Type A Grant (Dr Graff-Therapeutic Research Institute at the University of and the study is coordinated by the Alzheimer’s 2010;81(3):331–336.PubMed doi:10.1136/jnnp.2009.184598 Guerrero); NIH RO1MH084886-01A2 (Dr Graff-Southern California. ADNI data are disseminated Starkstein SE, Jorge R, Mizrahi R, et al. Insight Guerrero); and by CIHR, OMHF, and CAMH by the Laboratory for Neuro Imaging at the and danger in Alzheimer’s disease. Eur J fellowship awards (Dr Gerretsen). University of Southern California. Data used in Neurol. 2007;14(4):455–460.PubMed Role of the sponsor: The listed funding sources preparation of this article were obtained from Turró-Garriga O, Garre-Olmo J, Vilalta-Franch had no role in the design and conduct of the the ADNI database (adni.loni.usc.edu). As such, J, et al. Burden associated with the presence study; collection, management, analysis, and the investigators within the ADNI contributed to of anosognosia in Alzheimer’s disease. Int J interpretation of the data; and or preparation, the design and implementation of ADNI and/or Geriatr Psychiatry. 2013;28(3):291–297.PubMed doi:10.1002/gps.3824 review, or approval of the manuscript. provided data but did not participate in analysis or 7. Spalletta G, Girardi P, Caltagirone C, et al.
Funding Information:
Potential conflicts of interest: Dr Gerretsen Defense award number W81XWH-12-2-0012). U01 AG024904) and DOD ADNI (Department of has received fellowship awards from Canadian ADNI is funded by the National Institute on Mental Health Foundation (OMHF), and Centre for Institutes of Health Research (CIHR), Ontario Aging and the National Institute of Biomedical
Funding Information:
Submitted: November 29, 2016; accepted March Acknowledgments: Data collection and sharing 6, 2017. for this project were funded by the Alzheimer’s Publishedonline:October 10, 2017. Disease Neuroimaging Initiative (ADNI) NIH Grant
Funding Information:
Addiction and Mental Health (CAMH). Dr Nakajima generouscontributionsfromthefollowing:ImagingandBioengineeringandthrough has received fellowship grants from the Canadian AbbVie, Alzheimer’s Association; Alzheimer’s Drug CIHR, Japan Society for the Promotion of Science, Discovery Foundation; Araclon Biotech; BioClinica; AnosognosiainAlzheimer’sdisease:Kashiwa Y, Kitabayashi Y, Narumoto J, et al. and Nakatomi Foundation and has received Biogen; Bristol-Myers Squibb; CereSpir; Cogstate; association with patient characteristics, manuscriptfeesfromDainipponSumitomo Eisai; Elan Pharmaceuticals; Eli Lilly; EuroImmun; psychiatric symptoms and cognitive deficits. Pharma and Kyowa Hakko Kirin. Dr Pollock has F. Hoffmann-La Roche and its affiliated company received research support from the National Genentech; Fujirebio; GE Healthcare; IXICO; Psychiatry Clin Neurosci. 2005;59(6):697–704.PubMed doi:10.1111/j.1440-1819.2005.01439.x Institutes of Health (NIH) and CIHR. Dr Graff- Janssen Alzheimer Immunotherapy Research & Weston A, Barton C, Lesselyong J, et al. Guerrero has received support from Brain Canada, Development; Johnson & Johnson Pharmaceutical Functional deficits among patients with mild Canadian Foundation for Innovation, CIHR, Ontario Research & Development; Lumosity; Lundbeck; cognitive impairment. Alzheimers Dement. Ministry of Health and Long-Term Care, Ontario Merck; Meso Scale Diagnostics; NeuroRx Research; 2011;7(6):611–614.PubMed doi:10.1016/j.jalz.2010.12.011 Ministry of Research and Innovation, the US NIH, Neurotrack Technologies; Novartis; Pfizer; Mak E, Chin R, Ng LT, et al. Clinical OMHF, Consejo Nacional de Ciencia y Tecnologia Piramal Imaging; Servier; Takeda; and Transition associations of anosognosia in mild (CONACyT), Instituto de Ciencia y Tecnología Therapeutics. CIHR is providing funds to support cognitive impairment and Alzheimer’s del DF (ICyTDF), and Brain & Behavior Research ADNI clinical sites in Canada. Private sector disease. Int J Geriatr Psychiatry. Foundation and reports no competing interests. contributions are facilitated by the Foundation 2015;30(12):1207–1214.PubMed doi:10.1002/gps.4275 DrsIwataandCaravaggio, MsShah, MrChung, for the National Institutes of Health (www.fnih. Hurt CS, Banerjee S, Tunnard C, et al; and MrPlitmanreport no conflicts of interest. org). The grantee organization is the Northern AddNeuroMed Consortium. Insight, Funding/support:The research was partially California Institute for Research and Education, disease.J NeurolNeurosurgPsychiatry. cognition and quality oflife in Alzheimer’s
Funding Information:
The research was partially supported by OMHF –Type A Grant (Dr Graff-Guerrero); NIH RO1MH084886-01A2 (Dr Graff-Guerrero); and by CIHR, OMHF, and CAMH fellowship awards (Dr Gerretsen).
Publisher Copyright:
© Copyright 2017 Physicians Postgraduate Press, Inc.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - Objective: Anosognosia, or impaired illness awareness, is a common feature of Alzheimer’s disease (AD) and less so of mild cognitive impairment (MCI). Importantly, anosognosia negatively influences clinical outcomes for patients and their caregivers and may predict the conversion from MCI to AD. This study aimed to examine (1) the relationship between brain glucose metabolism as measured by fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and anosognosia in patients with MCI and AD and (2) the predictive utility of anosognosia in patients with MCI for later conversion to AD, even when controlling for other factors, including gender, education, apolipoprotein E ε4 carrier status, dementia severity, and cognitive dysfunction. Methods: Data for 1,062 participants from the Alzheimer’s Disease Neuroimaging Initiative database (2003 to August 2015) classified as having AD (n = 191) or MCI (n = 499) or as healthy comparison (HC) subjects (n = 372) were analyzed. HC participants had Mini-Mental State Examination (MMSE) scores from 24 to 30 and a Clinical Dementia Rating (CDR) of 0. MCI participants had MMSE scores from 24 to 30, a memory complaint, objective memory loss, a CDR of 0.5, absence of significant levels of impairment in other cognitive domains, and essentially preserved activities of daily living. AD participants had MMSE scores ≤ 26 and a CDR of ≥ 0.5, and met National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria for probable AD. Anosognosia was measured with the composite discrepancy score of the study partner and participants’ scores on the Everyday Cognition scale (ECog). Bivariate correlations and multiple regression analyses were performed to assess the relationship between anosognosia and FDG-PET findings in each group. Lastly, logistic regression and receiver operating characteristic curve analyses were performed in the MCI sample to determine if anosognosia was predictive of conversion from MCI to AD. Results: Hypometabolism was independently associated with anosognosia in AD, particularly in the posterior cingulate cortex and right angular gyrus. Anosognosia was associated with conversion from MCI to AD within 5 years (OR = 2.74 [95% CI, 1.95 to 3.85], χ2 1 = 33.65, P< .001), even after including covariates (OR = 1.64 [95% CI, 1.12 to 2.40], χ2 1 = 6.43, P= .011). ECog-composite scores ≤ −0.75 were 93% sensitive and 15% specific for conversion from MCI to AD. Conclusions: Anosognosia in AD is related to brain glucose hypometabolism. Further, anosognosia independently predicts conversion from MCI to AD. The absence of anosognosia may be clinically useful to identify those patients that are unlikely to convert from MCI to AD.
AB - Objective: Anosognosia, or impaired illness awareness, is a common feature of Alzheimer’s disease (AD) and less so of mild cognitive impairment (MCI). Importantly, anosognosia negatively influences clinical outcomes for patients and their caregivers and may predict the conversion from MCI to AD. This study aimed to examine (1) the relationship between brain glucose metabolism as measured by fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and anosognosia in patients with MCI and AD and (2) the predictive utility of anosognosia in patients with MCI for later conversion to AD, even when controlling for other factors, including gender, education, apolipoprotein E ε4 carrier status, dementia severity, and cognitive dysfunction. Methods: Data for 1,062 participants from the Alzheimer’s Disease Neuroimaging Initiative database (2003 to August 2015) classified as having AD (n = 191) or MCI (n = 499) or as healthy comparison (HC) subjects (n = 372) were analyzed. HC participants had Mini-Mental State Examination (MMSE) scores from 24 to 30 and a Clinical Dementia Rating (CDR) of 0. MCI participants had MMSE scores from 24 to 30, a memory complaint, objective memory loss, a CDR of 0.5, absence of significant levels of impairment in other cognitive domains, and essentially preserved activities of daily living. AD participants had MMSE scores ≤ 26 and a CDR of ≥ 0.5, and met National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria for probable AD. Anosognosia was measured with the composite discrepancy score of the study partner and participants’ scores on the Everyday Cognition scale (ECog). Bivariate correlations and multiple regression analyses were performed to assess the relationship between anosognosia and FDG-PET findings in each group. Lastly, logistic regression and receiver operating characteristic curve analyses were performed in the MCI sample to determine if anosognosia was predictive of conversion from MCI to AD. Results: Hypometabolism was independently associated with anosognosia in AD, particularly in the posterior cingulate cortex and right angular gyrus. Anosognosia was associated with conversion from MCI to AD within 5 years (OR = 2.74 [95% CI, 1.95 to 3.85], χ2 1 = 33.65, P< .001), even after including covariates (OR = 1.64 [95% CI, 1.12 to 2.40], χ2 1 = 6.43, P= .011). ECog-composite scores ≤ −0.75 were 93% sensitive and 15% specific for conversion from MCI to AD. Conclusions: Anosognosia in AD is related to brain glucose hypometabolism. Further, anosognosia independently predicts conversion from MCI to AD. The absence of anosognosia may be clinically useful to identify those patients that are unlikely to convert from MCI to AD.
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UR - http://www.scopus.com/inward/citedby.url?scp=85040071979&partnerID=8YFLogxK
U2 - 10.4088/JCP.16m11367
DO - 10.4088/JCP.16m11367
M3 - Article
C2 - 29022655
AN - SCOPUS:85040071979
SN - 0160-6689
VL - 78
SP - e1187-e1196
JO - Journal of Clinical Psychiatry
JF - Journal of Clinical Psychiatry
IS - 9
ER -