Subjective cognitive decline and rates of incident Alzheimer's disease and non–Alzheimer's disease dementia

Slot, Rosalinde E.R.; Sikkes, Sietske A.M.; Berkhof, Johannes; Brodaty, Henry; Buckley, Rachel F.; Cavedo, Enrica; Dardiotis, Efthimios; Guillo-Benarous, Francoise; Hampel, Harald; Kochan, Nicole A.; Lista, Simone; Luck, Tobias; Maruff, Paul; Molinuevo, José Luís; Kornhuber, Johannes; Reisberg, Barry; Riedel‐Heller, Steffi G.; Risacher, Shannon L.; Röhr, Susanne; Sachdev, Perminder S.; Scarmeas, Nikolaos; Scheltens, Philip; Shulman, Melanie; Saykin, Andrew J.; Verfaillie, Sander C.J.; Visser, Pieter Jelle; Vos, Stephanie J.B.; Wagner, Michael; Wolfsgruber, Steffen; Jessen, Frank; Boada, Merçé; Deyn, Peter Paul De; Jones, Roy; Frisoni, Giovanni B.; Spiru, Luiza; Nobili, Flavio; Freund‐Levi, Yvonne; Soininen, Hilkka; Verhey, Frans R.J.; Wallin, Åsa; Touchon, Jacques; Rikkert, Marcel G M Olde; Rigaud, A.-S.; Bullock, Roger; Tsolaki, Magda; Vellas, Bruno; Wilcock, Gordon; Froelich, Lutz; Bakardjian, Hovagim; Benali, Habib; Bertin, Hugo; Bonheur, Joel; Boukadida, Laurie; Boukerrou, Nadia; Chiesa, Patrizia Andrea; Colliot, Olivier; Dubois, Bruno; Dubois, M.; Epelbaum, Stéphane; Gagliardi, Geoffroy; Genthon, Rémy; Habert, Marie Odile; Houot, Marion; Kas, Aurélie; Lamari, Foudil; Lévy, Marcel; Metzinger, Christiane; Mochel, Fanny; Nyasse, Francis; Poisson, Catherine; Potier, Marie Claude; Revillon, Marie; Santos, Antonio; Andrade, Katia Santos; Solé, Marine; Surtee, Mohmed; Schotten, Michel Thiebaud de; Vergallo, Andrea; Younsi, Nadjia; Flier, Wiesje M. van der

doi:10.1016/j.jalz.2018.10.003

Cited by 290 publications

(323 citation statements)

References 56 publications

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“…Indeed, the evolution of preclinical and predementia stages is extremely variable between individuals (see, e.g., 75 ). MCI and SCD stages are heterogeneous conditions that may be caused by different pathologies (see, e.g., [76][77][78][79] ), so it can be expected that the majority of SCD and MCI patients included in our study will never progress to AD. Another explanation for these negative results may thus be that these two groups of participants are on average more alike to healthy subjects, possibly overshadowing a continuous progression of DMN alteration from SCD to AD.…”

Section: Discussionmentioning

confidence: 99%

Alterations in resting-state network dynamics along the Alzheimer’s disease continuum: a combined MEG-PET/MR approach

Puttaert

Coquelet

Wens

et al. 2020

Preprint

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Human brain activity is intrinsically organized into resting-state networks (RSNs) that transiently activate or deactivate at the sub-second timescale. Few neuroimaging studies have addressed how Alzheimer's disease (AD) affects these fast temporal brain dynamics, and how they relate to the cognitive, structural and metabolic abnormalities characterizing AD.We aimed at closing this gap by investigating both brain structure and function using magnetoencephalography (MEG) and hybrid positron emission tomography-magnetic resonance (PET/MR) in 10 healthy elders, 10 patients with Subjective Cognitive Decline (SCD), 10 patients with amnestic Mild Cognitive Impairment (aMCI) and 10 patients with typical Alzheimer's disease with dementia (AD). The fast activation/deactivation state dynamics of RSNs were assessed using hidden Markov modeling (HMM) of power envelope fluctuations at rest measured with MEG. HMM patterns were related to participants' cognitivetest scores, whole hippocampal grey matter volume and regional brain glucose metabolism.The posterior default-mode network (DMN) was less often activated and for shorter durations in AD patients than matched healthy elders. No significant difference was found in patients with SCD or aMCI. The time spent by participants in the activated posterior DMN state did not correlate significantly with cognitive scores. However, it correlated positively with the whole hippocampal volume and regional glucose consumption in the right temporo-parietal junctions and dorsolateral prefrontal cortex, and negatively with glucose consumption in the cerebellum.In AD patients, alterations of posterior DMN power activation dynamics at rest correlate with structural and neurometabolic abnormalities. These findings represent an additional electrophysiological correlate of AD-related synaptic and neural dysfunction.

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Section: Discussionmentioning

confidence: 99%

Alterations in resting-state network dynamics along the Alzheimer’s disease continuum: a combined MEG-PET/MR approach

Puttaert

Coquelet

Wens

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…The latter characteristic appears preferable when studying the interplay between cognitive and physical function. In addition, the presence of subjective cognitive complaint, part of the operationalization of MCI, which is highly predictive of dementia in people referred to a memory clinic or to general practitioners [25], shows less accuracy in population-based studies because of a higher number of false positive and false negative results [26][27][28][29]. Based on example of previous reports [17,23], we operationalized CIND as the presence of objective cognitive impairment, defined as scoring 1.5 standard deviations (SDs) or more below age group-specific means in at least one domain of the neuropsychological assessment, in the absence of dementia [23].…”

Section: Definitions Of Main Variables and Covariatesmentioning

confidence: 99%

Disability trajectories and mortality in older adults with different cognitive and physical profiles

et al. 2019

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Background Cognitive and physical deficits independently raise the risk for negative events in older adults. Less is known about whether their co-occurrence constitutes a distinct risk profile. This study quantifies the association between cognitive impairment, no dementia (CIND), slow walking speed (WS) and their combination and disability and mortality. Methods We examined 2546 dementia-free people aged ≥ 60 years, part of the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) up to 12 years. The following four profiles were created: (1) healthy profile; (2) isolated CIND (scoring 1.5 SD below age-specific means on at least one cognitive domain); (3) isolated slow WS (< 0.8 m/s); (4) CIND+ slow WS. Disability was defined as the sum of impaired activities of daily living and trajectories of disability were derived from mixed-effect linear regression models. Piecewise proportional hazard models were used to estimate mortality rate [hazard ratios (HRs)]. Population attributable risks of death were calculated. Results Participants with both CIND and slow WS had the worst prognosis, especially in the short-term period. They experienced the steepest increase in disability and five times the mortality rate (HR 5.1; 95% CI 3.5-7.4) of participants free from these conditions. Similar but attenuated results were observed for longer follow-ups. Co-occurring CIND and slow WS accounted for 30% of short-term deaths. Conclusions Co-occurring cognitive and physical limitations constitute a distinct risk profile in older people, and account for a large proportion of short-term deaths. Assessing cognitive and physical function could enable early identification of people at high risk for adverse events.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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“…As the preclinical stage of AD, SCD precedes the occurrence of MCI by approximately 15 years (Rabin et al, 2015). Patient with SCD has a significantly higher risk of AD than those without SCD (Slot et al, 2018).…”

mentioning

confidence: 99%

A promising structural magnetic resonance imaging assessment in patients with preclinical cognitive decline and diabetes mellitus

Dong

Wang²,

Yao

et al. 2019

Journal Cellular Physiology

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Subjective cognitive decline (SCD) is frequently reported in diabetic patients. Diabetes mellitus (DM) is associated with changes in the microstructure of the brain arise in diabetic patients, including changes in gray matter volume (GMV). However, the underlying mechanisms of changes in GMV in DM patients with cognitive impairment remain uncertain. Here, we present an overview of amyloid‐β‐dependent cognitive impairment in DM patients with SCD. Moreover, we review the evolving insights from studies on the GMV changes in GMV and cognitive dysfunction to which provide the mechanisms of cognitive impairment in T2DM. Ultimately, the novel structural magnetic resonance imaging (MRI) protocol was used for detecting neuroimaging biomarkers that can predict the clinical outcomes in diabetic patients with SCD. A reliable MRI protocol would be helpful to detect neurobiomarkers, and to understand the pathological mechanisms of preclinical cognitive impairment in diabetic patients.

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Subjective cognitive decline and rates of incident Alzheimer's disease and non–Alzheimer's disease dementia

Cited by 290 publications

References 56 publications

Alterations in resting-state network dynamics along the Alzheimer’s disease continuum: a combined MEG-PET/MR approach

Alterations in resting-state network dynamics along the Alzheimer’s disease continuum: a combined MEG-PET/MR approach

Disability trajectories and mortality in older adults with different cognitive and physical profiles

A promising structural magnetic resonance imaging assessment in patients with preclinical cognitive decline and diabetes mellitus

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