Prediction Models of Cognitive Trajectories in Patients with Nonamnestic Mild Cognitive Impairment

Lee, Jin San; Cho, Seong Kyung; Kim, Hee Jin; Kim, Yeo Jin; Park, Key Chung; Lockhart, Samuel N.; Na, Duk L.; Kim, Chang-Soo; Seo, Sang Won

doi:10.1038/s41598-018-28881-1

Cited by 20 publications

(22 citation statements)

References 44 publications

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“…This is consistent with our other finding showing that, compared with the stable group, the slow decliners and the fast decliners showed lower scores in language, memory, and frontal/executive function domains. The present finding is also consistent with our previous study based on non-amnestic MCI showing that decliners had decreased cortical thickness compared with the stable group [15]. These regions are known to be predominantly affected in AD [28].…”

Section: Discussionsupporting

confidence: 93%

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Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

et al. 2019

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BackgroundAlthough amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer’s disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory.MethodsWe retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB.ResultsTrajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group.ConclusionsOur data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis.Electronic supplementary materialThe online version of this article (10.1186/s13195-018-0462-z) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 93%

“…It would further provide distinct longitudinal trajectories by complex prognostic profiles as disease progresses over time. Indeed, a recent study from our group suggested that trajectory analysis is useful to identify prognostic profiles in patients with non-amnestic MCI [15].…”

Section: Introductionmentioning

confidence: 99%

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

et al. 2019

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“…Neuroimaging studies have demonstrated that aMCI, characterized by memory decline, has a high probability of developing into Alzheimer’s disease (AD) dementia (Rossetto et al, 2018; Chen et al, 2019a). Moreover, several previous studies have indicated that naMCI might be an intermediate stage between health and aMCI/AD (Lee et al, 2018; Oltra-Cucarella et al, 2018). Furthermore, subjective cognitive decline (SCD), as an earlier stage of MCI, refers to the elderly with a normal cognitive performance level and no objective signs of cognitive impairment who subjectively think they are cognitively impaired (Funaki et al, 2019; Hu et al, 2019).…”

Section: Introductionmentioning

confidence: 97%

Distinct Disruptive Patterns of Default Mode Subnetwork Connectivity Across the Spectrum of Preclinical Alzheimer’s Disease

Xue

Yuan

Yue

et al. 2019

Front. Aging Neurosci.

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Background: The early progression continuum of Alzheimer’s disease (AD) has been considered to advance through subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI). Altered functional connectivity (FC) in the default mode network (DMN) is regarded as a hallmark of AD. Furthermore, the DMN can be divided into two subnetworks, the anterior and posterior subnetworks. However, little is known about distinct disruptive patterns in the subsystems of the DMN across the preclinical AD spectrum. This study investigated the connectivity patterns of anterior DMN (aDMN) and posterior DMN (pDMN) across the preclinical AD spectrum.Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in the DMN subnetworks in 20 healthy controls (HC), eight SCD, 11 naMCI, and 28 aMCI patients. Moreover, a correlation analysis was used to examine associations between the altered connectivity of the DMN subnetworks and the neurocognitive performance.Results: Compared to the HC, SCD patients showed increased FC in the bilateral superior frontal gyrus (SFG), naMCI patients showed increased FC in the left inferior parietal lobule (IPL), and aMCI patients showed increased FC in the bilateral IPL in the aDMN; while SCD patients showed decreased FC in the precuneus, naMCI patients showed increased FC in the left middle temporal gyrus (MTG), and aMCI patients also showed increased FC in the right middle frontal gyrus (MFG) in the pDMN. Notably, the FC between the ventromedial prefrontal cortex (vmPFC) and the left MFG and the IPL in the aDMN was associated with episodic memory in the SCD and aMCI groups. Interestingly, the FC between the posterior cingulated cortex (PCC) and several regions in the pDMN was associated with other cognitive functions in the SCD and naMCI groups.Conclusions: This study demonstrates that the three preclinical stages of AD exhibit distinct FC alternations in the DMN subnetworks. Furthermore, the patient group data showed that the altered FC involves cognitive function. These findings can provide novel insights for tailored clinical intervention across the preclinical AD spectrum.

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“…While a mixedeffect regression-the standard analysis of this type of data-would identify one single trajectory per test that represents the "average" pattern of decline (Salthouse 2019), model-based clustering discovers multiple patterns of decline that are statistically different. The use of this approach to discover patterns of cognitive decline is growing, and it is proving to be useful for stratification of risk of cognitive impairment and Alzheimer's (Blanken et al 2020;Lee et al 2018). To assess the clinical and biological value of the patterns of change discovered with this analysis, we annotated the patterns by their correlation with patients' medical history, medications, circulating biomarkers, genetic markers, and changes of other aging traits and clinical status over time.…”

Section: Introductionmentioning

confidence: 99%

Patterns of multi-domain cognitive aging in participants of the Long Life Family Study

et al. 2020

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Maintaining good cognitive function at older age is important, but our knowledge of patterns and predictors of cognitive aging is still limited. We used Bayesian model-based clustering to group 5064 participants of the Long Life Family Study (ages 49-110 years) into clusters characterized by distinct trajectories of cognitive change in the domains of episodic memory, attention, processing speed, and verbal

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Prediction Models of Cognitive Trajectories in Patients with Nonamnestic Mild Cognitive Impairment

Cited by 20 publications

References 44 publications

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

Distinct Disruptive Patterns of Default Mode Subnetwork Connectivity Across the Spectrum of Preclinical Alzheimer’s Disease

Patterns of multi-domain cognitive aging in participants of the Long Life Family Study

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