Anosognosia in Alzheimer disease: Prevalence, associated factors, and influence on disease progression

Sanz, A. Castrillo; Calvo, María Andrés; Gento, I. Repiso; Delgado, E. Izquierdo; Ríos, R. Gutiérrez; Herrero, R. Rodríguez; Sanz, F. Rodríguez; Tola-Arribas, Miguel A

doi:10.1016/j.nrleng.2015.03.011

Cited by 15 publications

(11 citation statements)

References 36 publications

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“…However, when the same questions were applied to the patients, the EOMCI groups had significantly higher scores, implying that those patients might have more insight about their condition. Similar results have been described in AD patients, in which anosognosia was associated with advanced age, lower education level and more marked behavioral symptoms [57]. This result suggests that there could be other reasons other than lack of awareness to the opposite higher lag between onset and evaluation, namely fear of the diagnosis, lower decline rate or higher diagnostic disbelief.…”

Section: Discussionsupporting

confidence: 85%

Prognosis of Early-Onset vs. Late-Onset Mild Cognitive Impairment: Comparison of Conversion Rates and Its Predictors

et al. 2016

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Background: Despite having the same histopathological characteristics, early-onset and late-onset Alzheimer’s disease (AD) patients show some distinct clinical and neuropsychological profiles. Early Onset Mild Cognitive Impairment (EOMCI) is a less characterized group. The aim of this study is to characterize MCI probably due to AD in terms of the clinical, genetic, Cerebrospinal fluid (CSF) biomarkers profile and conversion rate of EOMCI, compared to the late-onset form (LOMCI). Methods: 159 MCI patients were divided in two groups: 52 EOMCI (onset < 65 years) and 107 LOMCI (onset ≥ 65 years). We investigated differences in neuropsychological scores, clinical variables, ApoE genotype, CSF biomarkers (Aβ42, t -Tau and p -Tau) in both groups. Conversion was ascertained during follow-up. Results: EOMCI showed a longer duration of symptoms prior to the first evaluation (EOMCI = 4.57 vs. LOMCI = 3.31, p = 0.008) and scored higher on the subjective memory complaints scale (9.91 vs. 7.85, p = 0.008), but performed better in brief cognitive tests (27.81 vs. 26.51, p < 0.001 in Mini-Mental State Examination; 19.84 vs. 18.67, p = 0.005 in Montreal Cognitive Assessment) than LOMCI. ApoE genotype distribution and CSF biomarker profile were similar in both groups, as was the conversion risk. Lower Aβ42 (Hazard ratio (HR): 0.998, 95% Confidence Interval (CI) = [0.996–1.000], p = 0.042), higher t -Tau levels (HR: 1.003, 95%CI = [1.000–1.005], p = 0.039) and higher scores in the Alzheimer Disease Assessment Scale-Cognitive (HR: 1.186, 95%CI = [1.083–1.299], p = 0.002) increased the risk of conversion. Discussion: Despite differences in memory performance and memory complaints, EOMCI and LOMCI seem to represent indistinct biological groups that do not have a higher risk of conversion to AD or differ in risk factors for conversion.

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Section: Discussionsupporting

confidence: 85%

Prognosis of Early-Onset vs. Late-Onset Mild Cognitive Impairment: Comparison of Conversion Rates and Its Predictors

et al. 2016

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“…Although anosognosia is observed in a variety of neurological disorders, it is especially common in AD, where it is often described as lack of insight or awareness of cognitive and functional impairments ( Wilson et al., 2016 ). The frequency of anosognosia is estimated to be between 20% and 80% for people with AD ( Castrillo-Sanz et al., 2016 ; Orfei et al., 2010 ; Starkstein, 2014 ). The variability of diagnosing anosognosia within AD is reflected in the large number of anosognosia screening instruments, leading to a lack of specificity in the diagnosis ( Mondragón et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

What are the neural correlates of meta-cognition and anosognosia in Alzheimer's disease? A systematic review

Hallam

Chan

Costafreda

et al. 2020

Neurobiology of Aging

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Awareness of one's own cognitive processes (metacognition) or of one's own illness or deficits ( anosognosia ) can be impaired in people with Alzheimer's disease (AD). The neural correlates of anosognosia within AD remain inconclusive. Understanding anosognosia is of importance because of its impact on carer burden and increased institutionalization. A systematic review of structural and functional neuroimaging studies was conducted to identify specific brain regions associated with anosognosia within AD. Thirty-two studies were included in the systematic review. Reduced gray matter density, cerebral blood flow, and hypometabolism in 8 key regions were significantly associated with increased anosognosia scores in people with AD. The most frequently associated regions were the inferior frontal gyrus, anterior cingulate cortex, and medial temporal lobe. Other key regions include the superior frontal gyrus, medial frontal gyrus, orbitofrontal cortex, posterior cingulate cortex, and the insula. Identifying brain regions associated with anosognosia can aid understanding and identification of anosognosia in people with AD and potentially facilitate improvements in care.

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“…Castrillo Sanz et al. (2016) conducted a prospective observational study on 97 patients with AD which unveiled the prevalence of anosognosia in approximately 71% of their studied patients. Using a multivariate analysis, they found an association of anosognosia with less education, more behavioral difficulties, and older age.…”

Section: Interrelationship Between Anosognosia Tpj and Dmn In Admentioning

confidence: 99%

The emergent relationship between temporoparietal junction and anosognosia in Alzheimer's disease

Lattanzio

Seames

Holden

et al. 2021

J of Neuroscience Research

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Anosognosia and impairment of insight are characteristic features of Alzheimer's disease (AD), which can lead to delays in appropriate medical care and significant family discord. The default mode network (DMN), a distributed but highly connected network of brain regions more active during rest than during task, is integrally involved in awareness. DMN dysfunction is common in AD, and disrupted communication between memory‐related and self‐related DMN networks is associated with anosognosia in AD patients. In addition, the temporoparietal junction (TPJ) is a key region of the “social brain” and also contributes to representations of the self. The exact classification of the TPJ within the DMN is unclear, though connections between the TPJ and DMN have been highlighted in multiple avenues of research. Here we discuss the relationship between the TPJ, DMN, and AD, as well as the potential involvement of the TPJ in anosognosia in AD. We review past and present findings to raise attention to the TPJ, with a specific emphasis on neuroimaging technologies which suggest a pivotal role of the TPJ within large‐scale brain networks linked to anosognosia in AD.

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Anosognosia in Alzheimer disease: Prevalence, associated factors, and influence on disease progression

Cited by 15 publications

References 36 publications

Prognosis of Early-Onset vs. Late-Onset Mild Cognitive Impairment: Comparison of Conversion Rates and Its Predictors

Prognosis of Early-Onset vs. Late-Onset Mild Cognitive Impairment: Comparison of Conversion Rates and Its Predictors

What are the neural correlates of meta-cognition and anosognosia in Alzheimer's disease? A systematic review

The emergent relationship between temporoparietal junction and anosognosia in Alzheimer's disease

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