Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease

Mattsson, Niklas; Schott, Jonathan M.; Hardy, John; Turner, Martin R; Zetterberg, Henrik

doi:10.1136/jnnp-2015-311321

Cited by 60 publications

(42 citation statements)

References 64 publications

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“…The difference in tau pathology, functional networks, metabolism may play a major role in selective vulnerability23, but we cannot support any of the previous hypotheses with our data of this present study. In this regard, we at least aim to suggest the “hallmarks” of cortical atrophy for each subtype so that they may serve as a viable start point in future studies.…”

Section: Discussioncontrasting

confidence: 96%

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Park

Kim

et al. 2017

Sci Rep

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Accumulating evidence suggests that Alzheimer’s disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset. Our method categorized very mild AD into three clinically distinct subtypes with high reproducibility (>90%); the parietal-predominant (P), medial temporal-predominant (MT), and diffuse (D) atrophy subtype. The P subtype showed the worst clinical presentation throughout the cognitive domains, while the MT and D subtypes exhibited relatively mild presentation. The MT subtype revealed more impaired language and executive function compared to the D subtype.

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Section: Discussioncontrasting

confidence: 96%

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Park

Kim

et al. 2017

Sci Rep

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“…These behaviors were not correlated with volume changes in the corresponding hubs. This is consistent with previous literature suggesting that damage to hubs causes particularly severe functional impairment due to their critical role in integrative brain processing (Buckner et al, 2009; Brier et al, 2014; Mattson et al, 2016). For example, in Alzheimer’s disease, the aggregation of Aβ seems to be driven by the level of neuronal activity of the cortical hubs, suggesting that the connectivity properties of neuronal subpopulations may play a role in determining their intrinsic sensitivity to stress (Mattson et al, 2016).…”

Section: Discussionsupporting

confidence: 93%

Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA

Mandelli

Welch

Vilaplana³

et al. 2018

Cortex

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“…First, the fact that molecular markers of AD (APOE ε4, CSF amyloid-β 1–42 , total tau) were not associated with NPS symptoms in the present study suggests that NPS in AD may be at least partially independent from AD pathophysiology itself. Similar to cognitive variants of AD, behavioral expression of AD may be linked to genetically and environmentally mediated by selective vulnerability of frontal-subcortical brain circuits [35]. In that regard, previous studies have shown the psychosis in AD is associated with a distinct genetic profile [36–38].…”

Section: Discussionmentioning

confidence: 99%

Risk Factors, Neuroanatomical Correlates, and Outcome of Neuropsychiatric Symptoms in Alzheimer’s Disease

Poulin

Bergeron

Dickerson

2017

JAD

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Background An integrative model of neuropsychiatric symptoms (NPS) in Alzheimer’s disease (AD) is lacking. Objective In this study, we investigated the risk factors, anatomy, biology, and outcomes of NPS in AD. Methods 181 subjects were included from the Alzheimer’s Disease Neuroimaging Study (ADNI). NPS were assessed with the Neuropsychiatric Inventory Questionnaire at baseline and 6 months. NPI >3 was used as a threshold for NPS positivity. Three NPS courses were characterized: 1) minimal/absent (negative at 0 and 6 months, n = 77); 2) fluctuating (positive only at one time point, n = 53); 3) persistent (positive at both time points, n = 51). We examined the association between NPS course and family history of dementia, personal history of psychiatric disorders, cerebrospinal fluid biomarkers, atrophy patterns, as well as longitudinal cognitive and functional measures at 12 and 24 months (MMSE, CDR-SOB, FAQ). Results AD subjects with absent, fluctuating, or persistent NPS had similar CSF amyloid-β and tau levels. AD subjects with minimal/absent NPS had less personal history of psychiatric disorders (35%) than those with fluctuating (57%; p = 0.015) or persistent NPS (47%, not significant). At 24 months, AD subjects with persistent NPS had worse cognitive (MMSE; p = 0.05) and functional (CDR-SOB; p = 0.016) outcomes. Dorsolateral prefrontal atrophy was seen in persistent NPS, but not in fluctuating NPS. Conclusions Our results suggest that individuals with personal history of psychiatric disorders might be more vulnerable to develop NPS throughout the course of AD. The worst cognitive and functional outcomes associated with NPS in AD underscores the importance of monitoring NPS early in the disease course.

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Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease

Cited by 60 publications

References 64 publications

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns

Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA

Risk Factors, Neuroanatomical Correlates, and Outcome of Neuropsychiatric Symptoms in Alzheimer’s Disease

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