Thinner temporal and parietal cortex is related to incident clinical progression to dementia in patients with subjective cognitive decline

Accurate identification of individuals with subjective cognitive decline using 3D regional fractal dimensions on structural magnetic resonance imaging

BACKGROUND AND OBJECTIVE

Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD.

METHODS

This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions.

RESULTS

The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations.

CONCLUSION

Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.

Impact of repetitive negative thinking on subjective cognitive decline: insights into cognition and brain structure

Introduction

Individuals with subjective cognitive decline (SCD) express concern about self-perceived cognitive decline despite no objective impairment and are at higher risk of developing Alzheimer's disease. Despite documented links between SCD and repetitive negative thinking (RNT), the specific impact of RNT on brain integrity and cognition in exacerbating the SCD condition remains unclear. We aimed to investigate the influence of RNT on global cognition and brain integrity, and their interrelationships among healthy middle-aged and older adults experiencing SCD.

Methods

Out of 616 individuals with neuroimaging and neuropsychological data available, 89 (mean age = 56.18 years; 68.54% females) met SCD criteria. Eighty-nine non-SCD individuals matched by age, sex, and education were also selected and represented the control group (mean age = 56.09 years; 68.54% females). Global cognition was measured using the preclinical Alzheimer's cognitive composite (PACC5), which includes dementia screening, episodic memory, processing speed, and category fluency tests. RNT was calculated through three questionnaires assessing intrusive thoughts, persistent worry, and rumination. We generated cortical thickness (CTh) maps and quantified the volume of white matter lesions (WML) in the whole brain, as grey and white matter integrity measures, respectively.

Results

SCD individuals exhibited higher RNT scores, and thinner right temporal cortex compared to controls. No differences were observed in PACC5 and WML burden between groups. Only the SCD group demonstrated positive associations in the CTh-PACC5, CTh-RNT, and WML-RNT relationships.

Discussion

In this cross-sectional study, RNT was exclusively associated with brain integrity in SCD. Even though our findings align with the broader importance of investigating treatable psychological factors in SCD, further research may reveal a modulatory effect of RNT on the relationship between cognition and brain integrity in SCD.

Differences between Alzheimer's disease and mild cognitive impairment using brain networks from magnetic resonance texture analysis

Several studies have aimed at identifying biomarkers in the initial phases of Alzheimer's disease (AD). Conversely, texture features, such as those from gray-level co-occurrence matrices (GLCMs), have highlighted important information from several types of medical images. More recently, texture-based brain networks have been shown to provide useful information in characterizing healthy individuals. However, no studies have yet explored the use of this type of network in the context of AD. This work aimed to employ texture brain networks to investigate the distinction between groups of patients with amnestic mild cognitive impairment (aMCI) and mild dementia due to AD, and a group of healthy subjects. Magnetic resonance (MR) images from the three groups acquired at two instances were used. Images were segmented and GLCM texture parameters were calculated for each region. Structural brain networks were generated using regions as nodes and the similarity among texture parameters as links, and graph theory was used to compute five network measures. An ANCOVA was performed for each network measure to assess statistical differences between groups. The thalamus showed significant differences between aMCI and AD patients for four network measures for the right hemisphere and one network measure for the left hemisphere. There were also significant differences between controls and AD patients for the left hippocampus, right superior parietal lobule, and right thalamus-one network measure each. These findings represent changes in the texture of these regions which can be associated with the cortical volume and thickness atrophies reported in the literature for AD. The texture networks showed potential to differentiate between aMCI and AD patients, as well as between controls and AD patients, offering a new tool to help understand these conditions and eventually aid early intervention and personalized treatment, thereby improving patient outcomes and advancing AD research.

Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment

Objectives

Accurately predicting when patients with mild cognitive impairment (MCI) will progress to dementia is a formidable challenge. This work aims to develop a predictive deep learning model to accurately predict future cognitive decline and magnetic resonance imaging (MRI) marker changes over time at the individual level for patients with MCI.

Methods

We recruited 657 amnestic patients with MCI from the Samsung Medical Center who underwent cognitive tests, brain MRI scans, and amyloid-β (Aβ) positron emission tomography (PET) scans. We devised a novel deep learning architecture by leveraging an attention mechanism in a recurrent neural network. We trained a predictive model by inputting age, gender, education, apolipoprotein E genotype, neuropsychological test scores, and brain MRI and amyloid PET features. Cognitive outcomes and MRI features of an MCI subject were predicted using the proposed network.

Results

The proposed predictive model demonstrated good prediction performance (AUC = 0.814 ± 0.035) in five-fold cross-validation, along with reliable prediction in cognitive decline and MRI markers over time. Faster cognitive decline and brain atrophy in larger regions were forecasted in patients with Aβ (+) than with Aβ (-).

Conclusion

The proposed method provides effective and accurate means for predicting the progression of individuals within a specific period. This model could assist clinicians in identifying subjects at a higher risk of rapid cognitive decline by predicting future cognitive decline and MRI marker changes over time for patients with MCI. Future studies should validate and refine the proposed predictive model further to improve clinical decision-making.

Neuropathological and sociodemographic factors associated with the cortical amyloid load in aging and Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia and is characterized by a progressive decline in cognitive abilities. A pathological hallmark of AD is a region-specific accumulation of the amyloid-beta protein (Aβ). Here, we explored the association between regional Aβ deposition, sociodemographic, and local biochemical factors. We quantified the Aβ burden in postmortem cortical samples from parietal (PCx) and temporal (TCx) regions of 27 cognitively unimpaired (CU) and 15 AD donors, aged 78-100 + years. Histological images of Aβ immunohistochemistry and local concentrations of pathological and inflammatory proteins were obtained at the "Aging, Dementia and TBI Study" open database. We used the area fraction fractionator stereological methodology to quantify the Aβ burden in the gray and white matter within each cortical region. We found higher Aβ burdens in the TCx of AD octogenarians compared to CU ones. We also found higher Aβ loads in the PCx of AD nonagenarians than in AD octogenarians. Moreover, AD women exhibited increased Aβ deposition compared to CU women. Interestingly, we observed a negative correlation between education years and Aβ burden in the white matter of both cortices in CU samples. In AD brains, the Aβ40, Aβ42, and pTau181 isoforms of Aβ and Tau proteins were positively correlated with the Aβ burden. Additionally, in the TCx of AD donors, the proinflammatory cytokine TNFα showed a positive correlation with the Aβ load. These novel findings contribute to understanding the interplay between sociodemographic characteristics, local inflammatory signaling, and the development of AD-related pathology in the cerebral cortex.

A Longitudinal Study on Memory Enhancement in Subjective Cognitive Decline Patients: Clinical and Neuroimaging Perspectives

BACKGROUND

Subjective cognitive decline (SCD) refers to the self-reported persistent cognitive decline despite normal objective testing, increasing the risk of dementia compared to cognitively normal individuals.

OBJECTIVE

This study aims to investigate the attributes of SCD patients who demonstrated memory function improvement.

METHODS

In this prospective study of SCD, a total of 120 subjects were enrolled as part of a multicenter cohort study aimed at identifying predictors for the clinical progression to mild cognitive impairment or dementia (CoSCo study). All subjects underwent 18F-florbetaben PET and brain MRI scans at baseline and annual neuropsychological tests. At the 24-month follow-up, we classified SCD patients based on changes in memory function, the z-score of the Seoul verbal learning test delayed recall.

RESULTS

Of the 120 enrolled patients, 107 successfully completed the 24-month follow-up assessment. Among these, 80 patients (74.8%) with SCD exhibited memory function improvements. SCD patients with improved memory function had a lower prevalence of coronary artery disease at baseline and performed better in the trail-making test part B compared to those without improvement. Anatomical and biomarker analysis showed a lower frequency of amyloid PET positivity and larger volumes in the left and right superior parietal lobes in subjects with improved memory function.

CONCLUSIONS

Our prospective study indicates that SCD patients experiencing memory improvement over a 24-month period had a lower amyloid burden, fewer cardiovascular risk factors, and superior executive cognitive function. Identifying these key factors associated with cognitive improvement may assist clinicians in predicting future memory function improvements in SCD patients.

Volumetric MRI Findings in Mild Traumatic Brain Injury (mTBI) and Neuropsychological Outcome

Region of interest (ROI) volumetric assessment has become a standard technique in quantitative neuroimaging. ROI volume is thought to represent a coarse proxy for making inferences about the structural integrity of a brain region when compared to normative values representative of a healthy sample, adjusted for age and various demographic factors. This review focuses on structural volumetric analyses that have been performed in the study of neuropathological effects from mild traumatic brain injury (mTBI) in relation to neuropsychological outcome. From a ROI perspective, the probable candidate structures that are most likely affected in mTBI represent the target regions covered in this review. These include the corpus callosum, cingulate, thalamus, pituitary-hypothalamic area, basal ganglia, amygdala, and hippocampus and associated structures including the fornix and mammillary bodies, as well as whole brain and cerebral cortex along with the cerebellum. Ventricular volumetrics are also reviewed as an indirect assessment of parenchymal change in response to injury. This review demonstrates the potential role and limitations of examining structural changes in the ROIs mentioned above in relation to neuropsychological outcome. There is also discussion and review of the role that post-traumatic stress disorder (PTSD) may play in structural outcome in mTBI. As emphasized in the conclusions, structural volumetric findings in mTBI are likely just a single facet of what should be a multimodality approach to image analysis in mTBI, with an emphasis on how the injury damages or disrupts neural network integrity. The review provides an historical context to quantitative neuroimaging in neuropsychology along with commentary about future directions for volumetric neuroimaging research in mTBI.

Neuroanatomical and neurocognitive changes associated with subjective cognitive decline

Introduction

Subjective Cognitive Decline (SCD) can progress to mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and thus may represent a preclinical stage of the AD continuum. However, evidence about structural changes observed in the brain during SCD remains inconsistent.

Materials and methods

This cross-sectional study aimed to evaluate, in subjects recruited from the CompAS project, neurocognitive and neurostructural differences between a group of forty-nine control subjects and forty-nine individuals who met the diagnostic criteria for SCD and exhibited high levels of subjective cognitive complaints (SCCs). Structural magnetic resonance imaging was used to compare neuroanatomical differences in brain volume and cortical thickness between both groups.

Results

Relative to the control group, the SCD group displayed structural changes involving frontal, parietal, and medial temporal lobe regions of critical importance in AD etiology and functionally related to several cognitive domains, including executive control, attention, memory, and language.

Conclusion

Despite the absence of clinical deficits, SCD may constitute a preclinical entity with a similar (although subtle) pattern of neuroanatomical changes to that observed in individuals with amnestic MCI or AD dementia.

Graph Analysis of Functional Brain Topology Using Minimum Spanning Tree in Subjective Cognitive Decline

BACKGROUND

Subjects with subjective cognitive decline (SCD) are proposed as a potential population to screen for Alzheimer's disease (AD).

OBJECTIVE

Investigating brain topologies would help to mine the neuromechanisms of SCD and provide new insights into the pathogenesis of AD.

METHODS

Objectively cognitively unimpaired subjects from communities who underwent resting-state BOLD-fMRI and clinical assessments were included. The subjects were categorized into SCD and normal control (NC) groups according to whether they exhibited self-perceived cognitive decline and were worried about it. The minimum spanning tree (MST) of the functional brain network was calculated for each subject, based on which the efficiency and centrality of the brain network organization were explored. Hippocampal/parahippocampal volumes were also detected to reveal whether the early neurodegeneration of AD could be seen in SCD.

RESULTS

A total of 49 subjects in NC and 95 subjects in SCD group were included in this study. We found the efficiency and centrality of brain network organization, as well as the hippocampal/parahippocampal volume were preserved in SCD. Besides, SCD exhibited normal cognitions, including memory, language, and execution, but increased depressive and anxious levels. Interestingly, language and execution, instead of memory, showed a significant positive correlation with the maximum betweenness centrality of the functional brain organization and hippocampal/parahippocampal volume. Neither depressive nor anxious scales exhibited correlations with the brain functional topologies or hippocampal/parahippocampal volume.

CONCLUSION

SCD exhibited preserved efficiency and centrality of brain organization. In clinical practice, language and execution as well as depression and anxiety should be paid attention in SCD.

Static and dynamic functional connectivity variability of the anterior-posterior hippocampus with subjective cognitive decline

Background

Subjective cognitive decline (SCD) is a putative Alzheimer’s disease (AD) precursor without objective neuropsychological deficits. The hippocampus plays an important role in cognitive function and emotional responses and is generally aberrant in SCD. However, previous studies have mainly focused on static functional connectivity (sFC) by resting-state functional magnetic resonance imaging (fMRI) in SCD individuals, and it remains unclear whether hippocampal dynamic functional connectivity (dFC) changes exist in SCD and whether those changes are associated with subtle changes in cognitive function or affect.

Methods

Seventy SCD patients and 65 healthy controls were recruited. Demographic data, comprehensive neuropsychology assessments, and resting-state fMRI data were collected. The bilateral anterior and posterior hippocampi were selected as seeds to investigate the static and dynamic functional connectivity alterations in SCD.

Results

Compared to healthy controls, subjects with SCD exhibited: (1) decreased sFC between the left caudal hippocampus and left precuneus; (2) decreased dFC variability between the bilateral caudal hippocampus and precuneus; (3) increased dFC variability between the bilateral rostral hippocampus and caudate nucleus; and (4) increased dFC variability between the left rostral hippocampus and left olfactory cortex. Additionally, the attention scores were positively correlated with dFC variability between the left posterior hippocampus and left precuneus, and the dFC variability between the bilateral anterior hippocampus and caudate nucleus was positively correlated with depression scores and negatively correlated with global cognition scores.

Conclusion

SCD individuals exhibited abnormal sFC and dFC in the anterior-posterior hippocampus, and abnormal dFC was more widespread than abnormal sFC. A combination of sFC and dFC provides a new perspective for exploring the brain pathophysiological mechanisms in SCD and offers potential neuroimaging biomarkers for the early diagnosis and intervention of AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01066-9.

Altered pattern analysis and identification of subjective cognitive decline based on morphological brain network

Subjective cognitive decline (SCD) is considered the first stage of Alzheimer's disease (AD). Accurate diagnosis and the exploration of the pathological mechanism of SCD are extremely valuable for targeted AD prevention. However, there is little knowledge of the specific altered morphological network patterns in SCD individuals. In this present study, 36 SCD cases and 34 paired-matched normal controls (NCs) were recruited. The Jensen-Shannon distance-based similarity (JSS) method was implemented to construct and derive the attributes of multiple brain connectomes (i.e., morphological brain connections and global and nodal graph metrics) of individual morphological brain networks. A t-test was used to discriminate between the selected nodal graph metrics, while the leave-one-out cross-validation (LOOCV) was used to obtain consensus connections. Comparisons were performed to explore the altered patterns of connectome features. Further, the multiple kernel support vector machine (MK-SVM) was used for combining brain connectomes and differentiating SCD from NCs. We showed that the consensus connections and nodal graph metrics with the most discriminative ability were mostly found in the frontal, limbic, and parietal lobes, corresponding to the default mode network (DMN) and frontoparietal task control (FTC) network. Altered pattern analysis demonstrated that SCD cases had a tendency for modularity and local efficiency enhancement. Additionally, using the MK-SVM to combine the features of multiple brain connectomes was associated with optimal classification performance [area under the curve (AUC): 0.9510, sensitivity: 97.22%, specificity: 85.29%, and accuracy: 91.43%]. Therefore, our study highlighted the combination of multiple connectome attributes based on morphological brain networks and offered a valuable method for distinguishing SCD individuals from NCs. Moreover, the altered patterns of multidimensional connectome attributes provided a promising insight into the neuroimaging mechanism and early intervention in SCD subjects.

Brain Photobiomodulation Improves Sleep Quality in Subjective Cognitive Decline: A Randomized, Sham-Controlled Study

Background: Sleep appears to be a sensitive biomarker that facilitates early detection and effective intervention for Alzheimer’s disease, while subjective cognitive decline (SCD) is a risk factor for Alzheimer’s disease. Prefrontal cortex atrophy is associated with both sleep disruption and cognitive decline. Transcranial brain photobiomodulation (PBM) therapy can enhance frontal cortex oxygen consumption, increasing frontal cortex mediated memory function. Objective: This study aimed to test whether PBM therapy targeting the frontal cortex could improve sleep and cognitive function in SCD. Methods: Fifty-eight SCDs were divided into the PBM group (N = 32) in which real light therapy was administered and a sham light therapy group (N = 26). All the participants received either real light or sham light therapy for 6 days consecutively, while the sleep data were recorded. The n-back task was employed to measure each participant’s working memory. Results: We found no differences in sleep efficiency change (F = 211, p = 0.279), REM stage percent change (F = 420, p = 0.91), and wake-up time (F = 212, p = 0.277) between the two groups. The sleep efficiency and REM were improved within the true light group on the fifth day. The true light group perform better than the control group in the n-back test, the accuracy was higher in the 2-back test (88.6% versus 79.6%, p = 0.001), and the reaction time in 1-back was shorter (544.80±202.00 versus 592.87±222.05, p = 0.003). Conclusion: After five days of PBM therapy targeting the prefrontal cortex, sleep efficiency and N-back cognitive performance were improved on the fifth day.

The interplay between gray matter and white matter neurodegeneration in subjective cognitive decline

Aims: To investigate the interplay between gray matter (GM) and white matter (WM) neurodegeneration in subjective cognitive decline (SCD), including thickness across the whole cortical mantle, hippocampal volume, and integrity across the whole WM.

Methods: We included 225 cognitively unimpaired individuals from a community-based cohort. Subjective cognitive complaints were assessed through 9 questions covering amnestic and non-amnestic cognitive domains. In our cohort, 123 individuals endorsed from one to six subjective cognitive complaints (i.e. they fulfilled the diagnostic criteria for SCD), while 102 individuals reported zero complaints. GM neurodegeneration was assessed through measures of cortical thickness across the whole mantle and hippocampal volume. WM neurodegeneration was assessed through measures of mean diffusivity (MD) across the whole WM skeleton. Mediation analysis and multiple linear regression were conducted to investigate the interplay between the measures of GM and WM neurodegeneration.

Results: A higher number of complaints was associated with reduced hippocampal volume, cortical thinning in several frontal and temporal areas and the insula, and higher MD across the WM skeleton, with a tendency to spare the occipital lobe. SCD-related cortical thinning and increased MD were associated with each other and jointly contributed to complaints, but the contribution of cortical thinning to the number of complaints was stronger.

Conclusions: Neurodegeneration processes affecting the GM and WM seem to be associated with each other in SCD and include brain areas other than those typically targeted by Alzheimer’s disease. Our findings suggest that SCD may be a sensitive behavioral marker of heterogeneous brain pathologies in individuals recruited from the community.

Biomarkers of Alzheimer's Disease and Cerebrovascular Lesions and Clinical Progression in Patients with Subjective Cognitive Decline: A Systematic Review

BACKGROUND

Early identification of Alzheimer's disease (AD) may be extremely beneficial for delaying disease progression. Subjective cognitive decline (SCD) may be an early indicator of AD pathology. Not all individuals with SCD will eventually develop AD, making it critical to identify biomarkers during the SCD stage which indicate likely clinical progression.

OBJECTIVE

The present review aims to summarize available data on structural MRI and cerebrospinal fluid (CSF) biomarkers and their association with clinical progression to mild cognitive impairment (MCI) or AD in people with SCD.

METHODS

Database searches were conducted using Embase and PubMed until June 2020. Longitudinal studies assessing biomarkers in individuals with SCD and assessing clinical progression to MCI/AD were included. Two assessors performed data extraction and assessed the risk of bias in the included studies. Data were synthesized narratively.

RESULTS

An initial search identified 1,065 papers; after screening and review 14 studies were included. Sample size of the included studies ranged from 28-674, mean age was 60.0-68.6 years, and 10.2%-52%of participants converted to MCI/AD. Lower levels of CSF Aβ 42 were consistently associated with clinical progression. Combination measures identifying an AD-like profile of Aβ 42 and tau levels were strongly associated with clinical progression. Biomarkers identified with structural MRI were less conclusive, as some studies found significant associations while others did not.

CONCLUSION

Biomarkers may be able to predict clinical progression in those with cognitive complaints. Aβ 42, or combinations of Aβ 42 and tau may be useful biomarkers in identifying individuals with SCD who will progress to MCI/AD.

Progressive Brain Degeneration From Subjective Cognitive Decline to Amnestic Mild Cognitive Impairment: Evidence From Large-Scale Anatomical Connection Classification Analysis

People with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are both at high risk for Alzheimer’s disease (AD). Behaviorally, both SCD and aMCI have subjective reports of cognitive decline, but the latter suffers a more severe objective cognitive impairment than the former. However, it remains unclear how the brain develops from SCD to aMCI. In the current study, we aimed to investigate the topological characteristics of the white matter (WM) network that can successfully identify individuals with SCD or aMCI from healthy control (HC) and to describe the relationship of pathological changes between these two stages. To this end, three groups were recruited, including 22 SCD, 22 aMCI, and 22 healthy control (HC) subjects. We constructed WM network for each subject and compared large-scale topological organization between groups at both network and nodal levels. At the network level, the combined network indexes had the best performance in discriminating aMCI from HC. However, no indexes at the network level can significantly identify SCD from HC. These results suggested that aMCI but not SCD was associated with anatomical impairments at the network level. At the nodal level, we found that the short-path length can best differentiate between aMCI and HC subjects, whereas the global efficiency has the best performance in differentiating between SCD and HC subjects, suggesting that both SCD and aMCI had significant functional integration alteration compared to HC subjects. These results converged on the idea that the neural degeneration from SCD to aMCI follows a gradual process, from abnormalities at the nodal level to those at both nodal and network levels.

Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old

Objective

To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition.

Methods

We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [¹⁸F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas.

Results

Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy.

Interpretation

These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.

Prediction of 7-year's conversion from subjective cognitive decline to mild cognitive impairment

Subjective cognitive decline (SCD) is a high‐risk yet less understood status before developing Alzheimer's disease (AD). This work included 76 SCD individuals with two (baseline and 7 years later) neuropsychological evaluations and a baseline T1‐weighted structural MRI. A machine learning‐based model was trained based on 198 baseline neuroimaging (morphometric) features and a battery of 25 clinical measurements to discriminate 24 progressive SCDs who converted to mild cognitive impairment (MCI) at follow‐up from 52 stable SCDs. The SCD progression was satisfactorily predicted with the combined features. A history of stroke, a low education level, a low baseline MoCA score, a shrunk left amygdala, and enlarged white matter at the banks of the right superior temporal sulcus were found to favor the progression. This is to date the largest retrospective study of SCD‐to‐MCI conversion with the longest follow‐up, suggesting predictable far‐future cognitive decline for the risky populations with baseline measures only. These findings provide valuable knowledge to the future neuropathological studies of AD in its prodromal phase.

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease

Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.

Depression and APOEε4 Status in Individuals with Subjective Cognitive Decline: A Meta-Analysis

OBJECTIVE

To evaluate the associative role of depression and apolipoprotein E epsilon 4 allele (APOEε4) in subjective cognitive decline (SCD) and its progression to objective cognitive decline.

METHODS

After literature search in electronic databases, studies were selected by following precise eligibility criteria. Meta-analyses were performed to examine the role of APOEε4 and depression in SCD or its progression to mild cognitive impairment (MCI) or dementia.

RESULTS

APOEε4 positivity was not different between SCD and normal individuals but was significantly higher in individuals with SCD plus than in normal individuals [odds ratio: 2.39 (95% CI: 1.87, 3.05); p<0.00001] and in SCD converters than in non-converters [odds ratio: 5.19 (95% CI: 2.36, 11.42); p<0.00001]. Depression was significantly higher in individuals with SCD [standardized mean difference: 0.63 (0.45, 0.82); p<0.00001] and SCD plus [standardized mean difference: 0.83 (0.43, 1.22); p<0.0001] than in normal individuals. However, depression was not different between SCD and MCI or between SCD converters and non-converters. Age of SCD converters was higher than non-converters [mean difference: 2.95 years (0.58, 5.31)].

CONCLUSION

Whereas APOEε4 positivity was higher in SCD plus and SCD converters, depression was higher in SCD and SCD plus but was not different between SCD and MCI.

ATN classification and clinical progression in subjective cognitive decline: The SCIENCe project

Objective

To investigate the relationship between the ATN classification system (amyloid, tau, neurodegeneration) and risk of dementia and cognitive decline in individuals with subjective cognitive decline (SCD).

Methods

We classified 693 participants with SCD (60 ± 9 years, 41% women, Mini-Mental State Examination score 28 ± 2) from the Amsterdam Dementia Cohort and Subjective Cognitive Impairment Cohort (SCIENCe) project according to the ATN model, as determined by amyloid PET or CSF β-amyloid (A), CSF p-tau (T), and MRI-based medial temporal lobe atrophy (N). All underwent extensive neuropsychological assessment. For 342 participants, follow-up was available (3 ± 2 years). As a control population, we included 124 participants without SCD.

Results

Fifty-six (n = 385) participants had normal Alzheimer disease (AD) biomarkers (A–T–N–), 27% (n = 186) had non-AD pathologic change (A–T–N+, A–T+N–, A–T+N+), 18% (n = 122) fell within the Alzheimer continuum (A+T–N–, A+T–N+, A+T+N–, A+T+N+). ATN profiles were unevenly distributed, with A–T+N+, A+T–N+, and A+T+N+ containing very few participants. Cox regression showed that compared to A–T–N–, participants in A+ profiles had a higher risk of dementia with a dose–response pattern for number of biomarkers affected. Linear mixed models showed participants in A+ profiles showed a steeper decline on tests addressing memory, attention, language, and executive functions. In the control group, there was no association between ATN and cognition.

Conclusions

Among individuals presenting with SCD at a memory clinic, those with a biomarker profile A–T+N+, A+T–N–, A+T+N–, and A+T+N+ were at increased risk of dementia, and showed steeper cognitive decline compared to A–T–N– individuals. These results suggest a future where biomarker results could be used for individualized risk profiling in cognitively normal individuals presenting at a memory clinic.

Jiao-tai-wan inhibits inflammation of the gut-brain-axis and attenuates cognitive impairment in insomnic rats

ETHNOPHARMACOLOGICAL RELEVANCE

Jiao-tai-wan is a well-known traditional Chinese herbal medicine formula that is used to treat insomnia and systemic inflammation. Studies indicate chronic insomnia might contribute to the prevalence of cognitive impairment. The role of systemic inflammation and intestinal permeability in the progression of neurodegenerative diseases attracts much attention.

AIM OF THE STUDY

This study aimed to investigate if Jiao-tai-wan plays a role in promoting the repair of the intestinal epithelial barrier to suppress systemic inflammation and cognitive impairment in sleep-deprived (SD) rats.

MATERIALS AND METHODS

Male obesity-resistant SD rats were partially sleep-deprived for 16 weeks. During the last 8 weeks, they were treated with Jiao-tai-wan. A Morris water maze was used to analyze their cognitive ability. Aβ42 and proinflammation cytokines in the cerebrospinal fluid, tissue, or serum were determined using enzyme-linked immunosorbent assay or polymerase chain reaction. Intestinal permeability was detected using the fluorescein isothiocyanate-dextran perfusion assay method. Plasma lipopolysaccharide (LPS) levels were detected with Tachypleus Amebocyte Lysate. Western bolt was used in the signaling pathway analysis.

RESULTS

Sleep deprivation deteriorated the performance of rats in the Morris water maze and increased the Aβ42, caspase3, IL-6, and TNF-α levels in their brains. The intestinal TLR4/NF-κB pathway was activated with an increase in the expression of IL-6 and TNF-α. The expression of tight junction proteins was also decreased in the intestinal tissue. This increased the intestinal permeability and circulation of LPS, LPS binding protein, IL-6, and TNF-α. Treatment with Jiao-tai-wan could partly reverse these changes.

CONCLUSION

Jiao-tai-wan has the potential to attenuate systemic inflammation and cognitive impairment in partially sleep-deprived rats. The possible underlying mechanism is by preventing an inflammation trigger being transferred through the gut-brain-axis.

Structural and Functional Hippocampal Changes in Subjective Cognitive Decline From the Community

Background

Recently, subjective cognitive decline (SCD) has been described as the earliest at-risk state of Alzheimer’s disease (AD), and drawn attention of investigators. Studies suggested that SCD-community individuals may constitute a more vulnerable population than SCD-clinic patients, therefore, to investigate the early changes of the brain may provide guidance for treatment of the disease. We sought to investigate the changes of structure and functional connectivity alternation of the hippocampus in individuals with SCD recruited from the community using structural and resting-state functional MRI (fMRI).

Methods

Thirty-five SCD patients and 32 healthy controls were recruited. Resting-state fMRI data and high-resolution T1-weighted images were collected. Whole-brain voxel-based morphometry was used to examine the brain structural changes. We also used the hippocampal tail and the whole hippocampus as seeds to investigate functional connectivity alternation in SCD.

Results

Individuals with SCD showed significant gray matter volume decreases in the bilateral hippocampal tails and enlargement of the bilateral paracentral lobules. We also found that individuals with SCD showed decreased hippocampal tail resting-state functional connectivity (rsFC) with the right medial prefrontal cortex (mPFC) and the left temporoparietal junction (TPJ), and decreased whole hippocampus rsFC with the bilateral mPFC and TPJ. These brain region and FC showing significant differences also showed significantly correlation with Montreal Cognitive Assessment (MoCA) scores.

Conclusion

Individuals with SCD recruited from the community is associated with structural and functional changes of the hippocampus, and these changes may serve as potential biomarkers of SCD.

Clinical Trial Registration

The Declaration of Helsinki, and the study was registered in http://www.chictr.org.cn. The Clinical Trial Registration Number was ChiCTR-IPR-16009144.

Differential Regional Brain Spontaneous Activity in Subgroups of Mild Cognitive Impairment

Background: Amnestic mild cognitive impairment (aMCI) has a high conversion risk to Alzheimer's disease (AD). The aMCI patients may have only a memory deficit (single-domain-aMCI, sd-aMCI) or deficits in multiple cognitive domains (multiple-domain-aMCI, md-aMCI). However, differences in intrinsic brain activity between these two sub-types remain unclear. Method: Neuropsychological and resting-state functional magnetic resonance imaging (fMRI) data were acquired from 24 patients with sd-aMCI, 23 patients with md-aMCI, and 32 healthy controls (HCs). We used the fractional amplitude of low-frequency fluctuation (fALFF) to characterize the intensity of spontaneous brain activity. The analysis of covariance (ANCOVA) and post hoc tests was performed to determine the between-group differences in fALFF. Results: We found higher fALFF in left-sided superior-to-middle frontal gyri and middle-to-inferior temporal gyri in sd-aMCI compared to both the md-aMCI and HCs. Conversely, a lower fALFF was found in the left inferior parietal lobe in both the md-aMCI and sd-aMCI patients. The fALFF values in the left middle and inferior temporal gyri were correlated with cognitive performances. Conclusion: The gradual reduction in the left inferior parietal lobe from single to multiple domain aMCI suggest a functional inefficiency underlying cognitive impairment, while increased activity in the frontal and temporal gyri in sd-aMCI rather than md-aMCI might indicate functional compensation. This study indicates differential functional profiles in the sd-aMCI and md-aMCI, which may be helpful for the prediction of the future conversion of aMCI to AD.

Disclosure of Amyloid Status for Risk of Alzheimer Disease to Cognitively Normal Research Participants With Subjective Cognitive Decline: A Longitudinal Study

This study aimed to investigate the long-term impacts of disclosing amyloid status for a risk of Alzheimer disease (AD) to cognitively normal research participants with subjective cognitive decline (SCD), which represents an initial manifestation of AD. Forty-two participants were classified as the amyloid-positive (n = 10) or amyloid-negative (n = 32) groups. We assessed symptoms of anxiety, depression, and test-related distress at 6, 24, and 52 weeks after results disclosure. No difference was found over time in anxiety, depression, and test-related distress in either group. Although no significant differences were observed between groups in anxiety or depression, the amyloid-negative group had a significantly higher level of test-related distress than the amyloid-positive group at 52 weeks. Disclosing amyloid status to cognitively healthy research participants with SCD did not cause significant long-term psychological risks. However, a theoretical spectrum of subjective concern may exist about cognitive decline in amyloid-negative individuals.

Biomarker-Based Signature of Alzheimer's Disease in Pre-MCI Individuals

Alzheimer’s disease (AD) pathology begins decades before the onset of clinical symptoms. It is recognized as a clinicobiological entity, being detectable in vivo independently of the clinical stage by means of pathophysiological biomarkers. Accordingly, neuropathological studies that were carried out on healthy elderly subjects, with or without subjective experience of cognitive decline, reported evidence of AD pathology in a high proportion of cases. At present, mild cognitive impairment (MCI) represents the only clinically diagnosed pre-dementia stage. Several attempts have been carried out to detect AD as early as possible, when subtle cognitive alterations, still not fulfilling MCI criteria, appear. Importantly, pre-MCI individuals showing the positivity of pathophysiological AD biomarkers show a risk of progression similar to MCI patients. In view of successful treatment with disease modifying agents, in a clinical setting, a timely diagnosis is mandatory. In clinical routine, biomarkers assessment should be taken into consideration whenever a subject with subtle cognitive deficits (pre-MCI), who is aware of his/her decline, requests to know the cause of such disturbances. In this review, we report the available neuropsychological and biomarkers data that characterize the pre-MCI patients, thus proposing pre-MCI as the first clinical manifestation of AD.

Association of TLR4 with Alzheimer's disease risk and presymptomatic biomarkers of inflammation

INTRODUCTION

A coding variant in the TLR4 receptor (rs4986790), previously associated with longevity and Alzheimer's disease (AD) risk reduction, was examined in a population isolate (Québec Founder Population [QFP]) and in presymptomatic individuals with a parental history of AD (Pre-Symptomatic Evaluation of Novel or Experimental Treatment for Alzheimer's Disease [PREVENT-AD]).

METHODS

Genotyping was performed using the Illumina HumanHap 550k (QFP) and the Illumina Omni2.5 beadchips (PREVENT-AD). Cognition was assessed using the Repeatable Battery for Assessment of Neuropsychological Status (RBANS). Whole-brain cortical thickness data were analyzed using CIVET 1.12. Cerebrospinal fluid concentrations of cytokines were obtained by using Milliplex.

RESULTS

The minor allele of the rs4986790 polymorphism (G) is associated with a reduced risk of developing AD in the QFP, as well as higher visuospatial and constructional abilities, higher cortical thickness in visual-related regions, and stable cerebrospinal fluid IL-1β levels in the PREVENT-AD cohort.

DISCUSSION

The rs4986790 G coding variant in the TLR4 gene appears to reduce AD risk through the modulation of IL-1β synthesis and secretion in the presymptomatic phase of the disease.

Personalized risk for clinical progression in cognitively normal subjects-the ABIDE project

Background

Biomarkers such as cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) have predictive value for progression to dementia in patients with mild cognitive impairment (MCI). The pre-dementia stage takes far longer, and the interpretation of biomarker findings is particular relevant for individuals who present at a memory clinic, but are deemed cognitively normal. The objective of the current study is to construct biomarker-based prognostic models for personalized risk of clinical progression in cognitively normal individuals presenting at a memory clinic.

Methods

We included 481 individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort. Prognostic models were developed by Cox regression with patient characteristics, MRI, and/or CSF biomarkers to predict clinical progression to MCI or dementia. We estimated 5- and 3-year individualized risks based on patient-specific values. External validation was performed on Alzheimer’s Disease Neuroimaging Initiative (ADNI) and an European dataset.

Results

Based on demographics only (Harrell’s C = 0.70), 5- and 3-year progression risks varied from 6% [3–11] and 4% [2–8] (age 55, MMSE 30) to 38% [29–49] and 28% [21–37] (age 70, MMSE 27). Normal CSF biomarkers strongly decreased progression probabilities (Harrell’s C = 0.82). By contrast, abnormal CSF markedly increased risk (5 years, 96% [56–100]; 3 years, 89% [44–99]). The CSF model could reclassify 58% of the individuals with an “intermediate” risk (35–65%) based on the demographic model. MRI measures were not retained in the models.

Conclusion

The current study takes the first steps in a personalized approach for cognitively normal individuals by providing biomarker-based prognostic models.

Electronic supplementary material

The online version of this article (10.1186/s13195-019-0487-y) contains supplementary material, which is available to authorized users.

Amyloid-β Load Is Related to Worries, but Not to Severity of Cognitive Complaints in Individuals With Subjective Cognitive Decline: The SCIENCe Project

Objective: Subjective cognitive decline (SCD) is associated with an increased risk of Alzheimer's Disease (AD). Early disease processes, such as amyloid-β aggregation measured with quantitative PET, may help to explain the phenotype of SCD. The aim of this study was to investigate whether quantitative amyloid-β load is associated with both self- and informant-reported cognitive complaints and memory deficit awareness in individuals with SCD. Methods: We included 106 SCD patients (mean ± SD age: 64 ± 8, 45%F) with 90 min dynamic [¹⁸F]florbetapir PET scans. We used the following questionnaires to assess SCD severity: cognitive change index (CCI, self and informant reports; 2 × 20 items), subjective cognitive functioning (SCF, four items), and five questions "Do you have complaints?" (yes/no) for memory, attention, organization and language), and "Does this worry you? (yes/no)." The Rivermead Behavioral Memory Test (RBMT)-Stories (immediate and delayed recall) was used to assess objective episodic memory. To investigate the level of self-awareness, we calculated a memory deficit awareness index (Z-transformed (inverted self-reported CCI minus episodic memory); higher index, heightened self-awareness) and a self-proxy index (Z-transformed self- minus informant-reported CCI). Mean cortical [¹⁸F]florbetapir binding potential (BP_ND) was derived from the PET data. Logistic and linear regression analyses, adjusted for age, sex, education, and depressive symptoms, were used to investigate associations between BP_ND and measures of SCD. Results: Higher mean cortical [¹⁸F]florbetapir BP_ND was associated with SCD-related worries (odds ratio = 1.76 [95%CI = 1.07 ± 2.90]), but not with other SCD questionnaires (informant and self-report CCI or SCF, total scores or individual items, all p > 0.05). In addition, higher mean cortical [¹⁸F]florbetapir BP_ND was associated with a higher memory deficit awareness index (Beta = 0.55), with an interaction between BP_ND and education (p = 0.002). There were no associations between [¹⁸F]florbetapir BP_ND and self-proxy index (Beta = 0.11). Conclusion: Amyloid-β deposition was associated with SCD-related worries and heightened memory deficit awareness (i.e., hypernosognosia), but not with severity of cognitive complaints. Our findings indicate that worries about self-perceived decline may reflect an early symptom of amyloid-β related pathology rather than subjective cognitive functioning.

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

BACKGROUND

In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.

MAIN BODY

Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.

CONCLUSION

We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

Computer-assisted prediction of clinical progression in the earliest stages of AD

Introduction

Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression.

Methods

We included 674 patients with SCD (46% female, 64 ± 9 years, Mini-Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts.

Results

After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8).

Discussion

We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

Subjective Cognitive Impairment Cohort (SCIENCe): study design and first results

BACKGROUND

We aimed to describe the Subjective Cognitive Impairment Cohort (SCIENCe) study design, to cross-sectionally describe participant characteristics, and to evaluate the SCD-plus criteria.

METHODS

The SCIENCe is a prospective cohort study of subjective cognitive decline (SCD) patients. Participants undergo extensive assessment, including cerebrospinal fluid collection and optional amyloid positron emission tomography scan, with annual follow-up. The primary outcome measure is clinical progression.

RESULTS

Cross-sectional evaluation of the first 151 participants (age 64 ± 8, 44% female, Mini-Mental State Examination 29 ± 2) showed that 28 (25%) had preclinical Alzheimer's disease (AD) (amyloid status available n = 114 (75%)), 58 (38%) had subthreshold psychiatry, and 65 (43%) had neither. More severe subjective complaints were associated with worse objective performance. The SCD-plus criteria age ≥ 60 (OR 7.7 (95% CI 1.7-38.9)) and apolipoprotein E (genotype) e4 (OR 4.8 (95% CI 1.6-15.0)) were associated with preclinical AD.

CONCLUSIONS

The SCIENCe study confirms that SCD is a heterogeneous group, with preclinical AD and subthreshold psychiatric features. We found a number of SCD-plus criteria to be associated with preclinical AD. Further inclusion and follow-up will address important questions related to SCD.

A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline

OBJECTIVES

Grey matter network disruptions in Alzheimer's disease (AD) are associated with worse cognitive impairment cross-sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD).

EXPERIMENTAL DESIGN

We included 231 individuals with SCD who had annually repeated neuropsychological assessment (3 ± 1 years; n = 646 neuropsychological investigations) available from the Amsterdam Dementia Cohort (54% male, age: 63 ± 9, MMSE: 28 ± 2). Single-subject grey matter networks were extracted from baseline 3D-T1 MRI scans and we computed basic network (size, degree, connectivity density) and higher-order (path length, clustering, betweenness centrality, normalized path length [lambda] and normalized clustering [gamma]) parameters at whole brain and/or regional levels. We tested associations of network parameters with baseline and annual cognition (memory, attention, executive functioning, language composite scores, and global cognition [all domains with MMSE]) using linear mixed models, adjusted for age, sex, education, scanner and total gray matter volume.

PRINCIPAL OBSERVATIONS

Lower network size was associated with steeper decline in language (β ± SE = 0.12 ± 0.05, p < 0.05FDR). Higher-order network parameters showed no cross-sectional associations. Lower gamma and lambda values were associated with steeper decline in global cognition (gamma: β ± SE = 0.06 ± 0.02); lambda: β ± SE = 0.06 ± 0.02), language (gamma: β ± SE = 0.11 ± 0.04; lambda: β ± SE = 0.12 ± 0.05; all p < 0.05FDR). Lower path length values in precuneus and fronto-temporo-occipital cortices were associated with a steeper decline in global cognition.

CONCLUSIONS

A more randomly organized grey matter network was associated with a steeper decline of cognitive functioning, possibly indicating the start of cognitive impairment.

In vivo MR in the drug pipeline

The application of in vivo magnetic resonance (MR) in drug development has several requirements that differ significantly from most applications primarily because the biopharmaceutical industry must develop new safe and effective drugs more quickly and at lower cost in a highly regulated environment. In vivo MR is recognized as a useful method to provide biomarkers for target engagement, treatment response, safety and mechanism of action that can be translated between animal and clinical studies. Thus, it has the potential to help identify drugs that are more likely to be safe and effective earlier in the process of drug development, which may help reduce the time and money required to get new drugs to patients with an unmet medical need. A brief introduction of how novel drugs are discovered and developed, what drives the biopharmaceutical industry's interest in using biomarkers and what it takes to use MR as a biomarker to support drug development, including regulatory concerns, provides context for understanding what makes the application of in vivo MR in drug development different from most others. Exploration of three programs (trebananib, ZD6126 and axitinib) using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in the development of antivascular agents provides insight into how in vivo MR biomarkers impact drug discovery and development and the limitations of biomarkers.

Diminution of context association memory structure in subjects with subjective cognitive decline

Alzheimer's disease (AD) progresses insidiously from the preclinical stage to dementia. While people with subjective cognitive decline (SCD) have normal cognitive performance, some may be in the preclinical stage of AD. Neurofibrillary tangles appear first in the transentorhinal cortex, followed by the entorhinal cortex in the clinically silent stage of AD. We expected the earliest changes in subjects with SCD to occur in medial temporal subfields other than the hippocampal proper. These selective structural changes would affect specific memory subcomponents. We used the Family Picture subtest of the Wechsler Memory Scale-III, which was modified to separately compute character, activity, and location subscores for episodic memory subcomponents. We recruited 43 subjects with SCD, 44 subjects with amnesic mild cognitive impairment, and 34 normal controls. MRI was used to assess cortical thickness, subcortical gray matter volume, and fractional anisotropy. The results demonstrated that SCD subjects showed significant cortical atrophy in their bilateral parahippocampus and perirhinal and the left entorhinal cortices but not in their hippocampal regions. SCD subjects also exhibited significantly decreased mean fractional anisotropy in their bilateral uncinate fasciculi. The diminution of cortical thickness over the mesial temporal subfields corresponded to brain areas with early tangle deposition, and early degradation of the uncinate fasciculus was in accordance with the retrogenesis hypothesis. The parahippocampus and perirhinal cortex contribute mainly to context association memory while the entorhinal cortex, along with the uncinate fasciculus, contributes to content-related contextual memory. We proposed that context association and related memory structures are vulnerable in the SCD stage.

A longitudinal study of brain anatomy changes preceding dementia in Down syndrome

Background

We longitudinally assessed Down syndrome individuals at the age of risk of developing dementia to measure changes in brain anatomy and their relationship to cognitive impairment progression.

Methods

Forty-two Down syndrome individuals were initially included, of whom 27 (mean age 46.8 years) were evaluable on the basis of completing the 2-year follow-up and success in obtaining good quality MRI exams. Voxel-based morphometry was used to estimate regional brain volumes at baseline and follow-up on 3D anatomical images. Longitudinal volume changes for the group and their relationship with change in general cognitive status and specific cognitive domains were mapped.

Results

As a group, significant volume reduction was identified in the substantia innominata region of the basal forebrain, hippocampus, lateral temporal cortex and left arcuate fasciculus. Volume reduction in the substantia innominata and hippocampus was more prominent in individuals whose clinical status changed from cognitively stable to mild cognitive impairment or dementia during the follow-up. Relevantly, longitudinal memory score change was specifically associated with volume change in the hippocampus, prospective memory with prefrontal lobe and verbal comprehension with language-related brain areas.

Conclusions

Results are notably concordant with the well-established anatomical changes signaling the progression to dementia in Alzheimer's disease, despite the dense baseline pathology that developmentally accumulates in Down syndrome. This commonality supports the potential value of Down syndrome as a genetic model of Alzheimer's neurodegeneration and may serve to further support the view that Down syndrome patients are best candidates to benefit from treatment research in Alzheimer's disease.

Amsterdam Dementia Cohort: Performing Research to Optimize Care

The Alzheimer center of the VU University Medical Center opened in 2000 and was initiated to combine both patient care and research. Together, to date, all patients forming the Amsterdam Dementia Cohort number almost 6,000 individuals. In this cohort profile, we provide an overview of the results produced based on the Amsterdam Dementia Cohort. We describe the main results over the years in each of these research lines: 1) early diagnosis, 2) heterogeneity, and 3) vascular factors. Among the most important research efforts that have also impacted patients' lives and/or the research field, we count the development of novel, easy to use diagnostic measures such as visual rating scales for MRI and the Amsterdam IADL Questionnaire, insight in different subgroups of AD, and findings on incidence and clinical sequelae of microbleeds. Finally, we describe in the outlook how our research endeavors have improved the lives of our patients.

Subjective Cognitive Decline Is Associated With Altered Default Mode Network Connectivity in Individuals With a Family History of Alzheimer's Disease

BACKGROUND

Both subjective cognitive decline (SCD) and a family history of Alzheimer's disease (AD) portend risk of brain abnormalities and progression to dementia. Posterior default mode network (pDMN) connectivity is altered early in the course of AD. It is unclear whether SCD predicts similar outcomes in cognitively normal individuals with a family history of AD.

METHODS

We studied 124 asymptomatic individuals with a family history of AD (age 64 ± 5 years). Participants were categorized as having SCD if they reported that their memory was becoming worse (SCD⁺). We used extensive neuropsychological assessment to investigate five different cognitive domain performances at baseline (n = 124) and 1 year later (n = 59). We assessed interconnectivity among three a priori defined ROIs: pDMN, anterior ventral DMN, medial temporal memory system (MTMS), and the connectivity of each with the rest of brain.

RESULTS

Sixty-eight (55%) participants reported SCD. Baseline cognitive performance was comparable between groups (all false discovery rate-adjusted p values > .05). At follow-up, immediate and delayed memory improved across groups, but the improvement in immediate memory was reduced in SCD⁺ compared with SCD^- (all false discovery rate-adjusted p values < .05). When compared with SCD^-, SCD⁺ subjects showed increased pDMN-MTMS connectivity (false discovery rate-adjusted p < .05). Higher connectivity between the MTMS and the rest of the brain was associated with better baseline immediate memory, attention, and global cognition, whereas higher MTMS and pDMN-MTMS connectivity were associated with lower immediate memory over time (all false discovery rate-adjusted p values < .05).

CONCLUSIONS

SCD in cognitively normal individuals is associated with diminished immediate memory practice effects and a brain connectivity pattern that mirrors early AD-related connectivity failure.

Thinner cortex in patients with subjective cognitive decline is associated with steeper decline of memory

We aimed to investigate associations between regional cortical thickness and rate of decline over time in 4 cognitive domains in patients with subjective cognitive decline (SCD). We included 233 SCD patients with the total number of 654 neuropsychological assessments (median = 3, range = 2-8) and available baseline magnetic resonance imaging from the Amsterdam Dementia Cohort (125 males, age: 63 ± 9, Mini-Mental State Examination score: 28 ± 2). We assessed longitudinal cognitive functioning at baseline and follow-up in 4 cognitive domains (composite Z-scores): memory, attention, executive function, and language. Thickness (millimeter) was estimated using FreeSurfer for frontal, temporal, parietal, cingulate, and occipital cortices. We used linear mixed models to estimate effects of cortical thickness on cognitive performance (dependent variables). There were no associations between cortical thickness and baseline cognition, but a faster subsequent rate of memory loss was associated with thinner cortex of the frontal [β (SE) = 0.20 (0.07)], temporal [β (SE) = 0.18 (0.07)], and occipital [β (SE) = 0.22 (0.09)] cortices (all p < 0.05_FDR). These findings illustrate that early cortical changes, particularly in the temporal cortex, herald incipient cognitive decline related to neurodegenerative diseases, most prominently Alzheimer's disease.