Dynamic network connectivity predicts subjective cognitive decline: the Sino-Longitudinal Cognitive impairment and dementia study.
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SUBMITTER: Dong G
PROVIDER: S-EPMC7606422 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionUnderstanding the biological mechanism of subjective cognitive decline (SCD) in preclinical Alzheimer's disease (AD) and identifying those who will soon convert to mild cognitive impairment (MCI) are critical for developing appropriate strategies for early diagnosis and intervention of AD. We present the study protocol of the Sino Longitudinal Study on Cognitive Decline (SILCODE), a longitudinal observational study focusing on SCD in the context of AD.Methods and analysisWithin SILCODE, approximately 800 subjects with SCD who are between 50 and 79 years old will be recruited through standardised public advertisements or memory clinics. They will undergo extensive assessment, including clinical and neuropsychological assessments, blood sample collection for plasma beta-amyloid and ApoE genotype, urine samples collection for AD7c-NTP, and multimodal MRI scans (structural MRI, diffusion tensor imaging, resting-state functional MRI and optional task-based functional MRI) as well as optional glucose metabolism and amyloid positron emission tomography. Subjects will be contacted by telephone every 3 months and interviewed, on average, every 15 months for 5 years. The study endpoint is the development of mild cognitive impairment or dementia. Jak & Bondi's actuarial neuropsychological method will be used for diagnosis of MCI. The least absolute shrinkage and selection operator logistic regression model followed by the sub-distribution hazard function model with death as a competing risk will be constructed to establish risk prediction models.Ethics and disseminationThe ethics committee of the Xuanwu Hospital of Capital Medical University has approved this study protocol (ID: [2017]046). The results will be published in peer-reviewed journals and presented at national and international scientific conferences.Trial registration numberNCT03370744; Pre-results.
| S-EPMC6661672 | biostudies-literature
Project description:AimsWe evaluated whether Subjective Cognitive Decline (SCD) subtypes could be empirically derived within the Sino Longitudinal Study on Cognitive Decline (SILCODE) SCD cohort and examined associated neuroimaging markers, biomarkers, and clinical outcomes.MethodsA cluster analysis was performed on eight neuropsychological test scores from 124 SCD SILCODE participants and 57 normal control (NC) subjects. Structural and functional neuroimaging indices were used to evaluate the SCD subgroups.ResultsFour subtypes emerged: (1) dysexecutive/mixed SCD (n = 23), (2) neuropsychiatric SCD (n = 24), (3) amnestic SCD (n = 22), and (4) cluster-derived normal (n = 55) who exhibited normal performance in neuropsychological tests. Compared with the NC group, each subgroup showed distinct patterns in gray matter (GM) volume and the amplitude of low-frequency fluctuations (ALFF). Lower fractional anisotropy (FA) values were only found in the neuropsychiatric SCD group relative to NC.ConclusionThe identification of empirically derived SCD subtypes demonstrates the presence of heterogeneity in SCD neuropsychological profiles. The cluster-derived normal group may represent the majority of SCD individuals who do not show progressive cognitive decline; the dysexecutive/mixed SCD and amnestic SCD might represent high-risk groups with progressing cognitive decline; and finally, the neuropsychiatric SCD may represent a new topic in SCD research.
| S-EPMC10651943 | biostudies-literature
Project description:Purpose: To investigate the dynamic functional connectivity (DFC) and static parameters of graph theory in individuals with subjective cognitive decline (SCD) and the associations of DFC and topological properties with cognitive performance. Methods: Thirty-three control subjects and 32 SCD individuals were enrolled in this study, and neuropsychological evaluations and resting-state functional magnetic resonance imaging scanning were performed. Thirty-three components were selected by group independent component analysis to construct 7 functional networks. Based on the sliding window approach and k-means clustering, distinct DFC states were identified. We calculated the temporal properties of fractional windows in each state, the mean dwell time in each state, and the number of transitions between each pair of DFC states. The global and local static parameters were assessed by graph theory analysis. The differences in DFC and topological metrics, and the associations of the altered neuroimaging measures with cognitive performance were assessed. Results: The whole cohort demonstrated 4 distinct connectivity states. Compared to the control group, the SCD group showed increased fractional windows and an increased mean dwell time in state 4, characterized by hypoconnectivity both within and between networks. The SCD group also showed decreased fractional windows and a decreased mean dwell time in state 2, dominated by hyperconnectivity within and between the auditory, visual and somatomotor networks. The number of transitions between state 1 and state 2, between state 2 and state 3, and between state 2 and state 4 was significantly reduced in the SCD group compared to the control group. No significant differences in global or local topological metrics were observed. The altered DFC properties showed significant correlations with cognitive performance. Conclusion: Our findings indicated DFC network reconfiguration in the SCD stage, which may underlie the early cognitive decline in SCD subjects and serve as sensitive neuroimaging biomarkers for the preclinical detection of individuals with incipient Alzheimer's disease.
| S-EPMC7886811 | biostudies-literature
Project description:Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders. Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI. Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI. Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.
| S-EPMC8484524 | biostudies-literature
Project description:BACKGROUND:Subjective cognitive decline (SCD) and anxiety symptoms both predict neurocognitive disorders, but the two correlate strongly with each other. It is unclear whether they reflect two independent disease processes in the development of neurocognitive disorders and hence deserve separate attention. This cohort study examined whether SCD and anxiety symptoms demonstrate independent risks of mild cognitive disorder and dementia (MCI/dementia). METHODS:The study included 14,066 participants aged ??50?years and diagnosed with normal cognition at baseline, recruited from Alzheimer's Disease Centers across the USA. The participants were evaluated for SCD and anxiety symptoms at baseline and followed up almost annually for incident MCI/dementia (median follow-up 4.5?years; interquartile range 2.2-7.7?years). SCD and anxiety symptoms were included in Cox regression to investigate their independent risks of MCI/dementia. RESULTS:SCD and anxiety symptoms demonstrated independent risks of MCI/dementia, with HR 1.9 (95% CI 1.7-2.1) and 1.3 (95% CI 1.2-1.5), respectively. Co-occurring SCD and anxiety symptoms demonstrated the highest risk (HR 2.4, 95% CI 1.9-2.9)-participants in this group had a 25% probability of developing MCI/dementia by 3.1?years (95% 2.4-3.7), compared to 8.2?years among those without SCD or anxiety (95% CI 7.9-8.6). The results remained robust even in the sensitivity analyses that took into account symptom severity and consistency of symptoms in the first 2 annual visits. CONCLUSIONS:The findings suggest that clinicians should not dismiss one over the other when patients present with both SCD and anxiety and that both constructs may potentially be useful to identify high-risk populations for preventive interventions and trials. The findings also point to the need for further research to clarify on the neurobiological distinctions between SCD and anxiety symptoms, which may potentially enrich our understanding on the pathogenesis of neurocognitive disorders.
| S-EPMC7488541 | biostudies-literature
Project description:BackgroundIn cognitively normal individuals, subjective cognitive decline (SCD) has been reported to predict MCI and dementia (MCI/dementia). However, prior studies mostly captured SCD at single time-points without considering the longitudinal course of SCD. This study examined whether the trajectories of SCD provide any added information-beyond one-time assessments of SCD-on the risk of MCI/dementia.MethodsThis cohort study included 5661 participants from the Alzheimer's Disease Centers across the USA, who were ≥ 50 years and had normal cognition in the first-four annual visits (year 1 to year 4). The participants were evaluated for SCD in the first-four annual visits (year 1 to year 4), and followed-up almost annually (year 4 up to year 14) for incident MCI/dementia. SCD trajectories (as identified from latent-class-growth-curve-analysis) were included in Cox regression to estimate their risks of MCI/dementia, with analyses further stratified by age (< 75 years versus ≥ 75 years; based on median-split).ResultsCompared to those without SCD (in the first-four annual visits), Intermittent SCD (i.e., reported in 1-2 of the first-four annual visits) predicted a higher risk (HR 1.4) and Persistent SCD (i.e., reported in 3-4 of the first-four annual visits) predicted the highest risk (HR 2.2), with the results remaining significant even after adjusting for baseline SCD. Age-stratified analysis revealed that the risk associated with Intermittent SCD was only present in older individuals, while risk related to Persistent SCD was consistently present across the younger and older age groups. Age compounded the effects of the trajectories, whereby older individuals with Persistent SCD had > 75% probability of developing MCI/dementia by 10 years, in contrast to < 25% probability by 10 years in younger individuals with No SCD.ConclusionsThe findings demonstrate the utility of SCD trajectories-especially when used in combination with age strata-in identifying high-risk populations for preventive interventions and trials. They also suggest a potential modification in the current SCD criteria, with the inclusion of "persistent SCD over several years" as a feature of SCD plus.
| S-EPMC7592368 | biostudies-literature
Project description:BackgroundSubjective cognitive impairment (SCI) is common after acute ischemic stroke and adversely affects the quality of life. SCI is associated with an increased risk of developing mild cognitive impairment and dementia. Identifying biomarkers which could predict long-term cognitive outcomes of post-stroke SCI is of importance for early intervention. This study aims to investigate the association between circulating neurofilament light (NfL) and long-term cognitive function in patients with post-stroke SCI.MethodsThis longitudinal study recruited 304 patients with post-stroke SCI, and serum NfL levels were determined at baseline. These patients were followed up for 12 months for the observation of cognitive change. Cognitive performances were assessed by a Chinese version of the Telephone Interview of Cognitive Status-40 (TICS-40) scale.ResultsThe patients were divided into a progression group (as determined by decreased TICS-40 scores) and a stable group (as determined by increased or unchanged TICS-40 scores). The progression group had significantly higher serum NfL levels than the stable group at baseline. Serum NfL levels were predictive for longitudinal cognitive decline during follow-up.ConclusionThese findings imply that circulating NfL could predict the long-term cognitive change of patients with post-stroke SCI.
| S-EPMC8165181 | biostudies-literature
Project description:Background: The recent COVID-19 pandemic is not only a major healthcare problem in itself, but also poses enormous social challenges. Though nursing homes increasingly receive attention, the majority of people with cognitive decline and dementia live at home. We aimed to explore the psychosocial effects of corona measures in memory clinic (pre-)dementia patients and their caregivers. Methods: Between April 28th and July 13th 2020, n = 389 patients of Alzheimer center Amsterdam [n = 121 symptomatic (age = 69 ± 6, 33%F, MMSE = 23 ± 5), n = 268 cognitively normal (age = 66 ± 8, 40% F, MMSE = 29 ± 1)] completed a survey on psychosocial effects of the corona measures. Questions related to social isolation, worries for faster cognitive decline, behavioral problems and discontinuation of care. In addition, n = 147 caregivers of symptomatic patients completed a similar survey with additional questions on caregiver burden. Results: Social isolation was experienced by n = 42 (35%) symptomatic and n = 67 (25%) cognitively normal patients and two third of patients [n = 129 (66%); n = 58 (75%) symptomatic, n = 71 (61%) cognitively normal] reported that care was discontinued. Worries for faster cognitive decline were existed in symptomatic patients [n = 44 (44%)] and caregivers [n = 73 (53%)], but were also reported by a subgroup of cognitively normal patients [n = 27 (14%)]. Both patients [n = 56 (46%) symptomatic, n = 102 (38%) cognitively normal] and caregivers [n = 72 (48%)] reported an increase in psychological symptoms. More than three quarter of caregivers [n = 111(76%)] reported an increase in patients' behavioral problems. A higher caregiver burden was experienced by n = 69 (56%) of caregivers and n = 43 (29%) of them reported that a need for more support. Discontinuation of care (OR = 3.3 [1.3-7.9]), psychological (OR = 4.0 [1.6-9.9]) and behavioral problems (OR = 3.0 [1.0-9.0]) strongly related to experiencing a higher caregiver burden. Lastly, social isolation (OR = 3.2 [1.2-8.1]) and psychological symptoms (OR = 8.1 [2.8-23.7]) were red flags for worries for faster cognitive decline. Conclusion: Not only symptomatic patients, but also cognitively normal patients express worries for faster cognitive decline and psychological symptoms. Moreover, we identified patients who are at risk of adverse outcomes of the corona measures, i.e., discontinued care, social isolation, psychological and behavioral problems. This underlines the need for health care professionals to provide ways to warrant the continuation of care and support (informal) networks surrounding patients and caregivers to mitigate the higher risk of negative psychosocial effects.
| S-EPMC7649118 | biostudies-literature
Project description:The abnormality occurs at molecular, cellular as well as network levels in patients with Alzheimer's disease (AD) prior to diagnosis. Most previous connectivity studies were conducted at 1 out of 3 (local, meso and global) scales in subjects covering only part of the entire AD spectrum (subjective cognitive decline, SCD; amnestic mild cognitive impairment, aMCI; and then fully manifest AD). Data interpretation within the framework of disease progression is therefore difficult. The current study included 3 age- and sex-matched cohorts: SCD (n = 32), aMCI (n = 37) and fully-established AD (n = 30). A group of healthy elderly subjects (n = 40) were included as a normal control (NC). Network connectivity was examined at the local (degree centrality), meso [subgraph centrality (SC)], and global (eigenvector and page-rank centralities) levels. As compared to NC, SCD subjects had isolated decrease of SC in primary (somatomotor and visual) networks. aMCI subjects had decreased centralities at all three scales in associative (frontoparietal control, dorsal attention, limbic and default) networks. AD subjects had increased centrality at the global scale in all seven networks. There was a positive association between Montreal Cognitive Assessment (MoCA) scores and DC in the frontoparietal control network in SCD, a negative relationship between Mini-Mental State Examination (MMSE) scores and EC in the somatomotor network in AD. These findings suggest that the primary network is impaired as early as in SCD. Impairment in the associative network also starts at the local level at this stage and may contribute to the cognitive decline. As associative network impairment extends from local to meso and global scales in aMCI, compensatory mechanisms in the primary network are activated.
| S-EPMC6491896 | biostudies-literature
Project description:BackgroundSubjective cognitive decline, perceived worsening of cognitive ability without apparent performance issues on clinical assessment, may be an important precursor to dementia. While previous cross-sectional research has demonstrated aberrant brain functional connectivity in subjective cognitive decline, longitudinal evaluation remains limited.MethodsHere, we examined trajectories of functional connectivity over three measurement occasions ~18 months apart, using voxelwise latent growth models in cognitively unimpaired older adults with varying self-report of subjective cognitive decline (N = 69).ResultsWe found that individuals who reported a greater degree of subjective cognitive decline showed a larger subsequent decrease in connectivity between components of the default mode network and increase in connectivity between salience and default mode network components. The change in functional connectivity was observed in the absence of change in cognitive performance.ConclusionThe results indicate that functional brain changes may underly the experience of cognitive decline before deterioration reaches a level detected by formal cognitive assessment.
| S-EPMC8166120 | biostudies-literature