Preclinical Stage Of Alzheimer's Disease Research Articles

CSF biomarkers of neuroinflammation and cerebrovascular dysfunction in early Alzheimer disease.

ObjectiveTo measure CSF levels of biomarkers reflecting microglia and astrocytes activation, neuroinflammation, and cerebrovascular changes and study their associations with the core biomarkers of Alzheimer disease (AD) pathology (β-amyloid [Aβ] and tau), structural imaging correlates, and clinical disease progression over time.MethodsThe study included cognitively unimpaired elderly (n = 508), patients with mild cognitive impairment (MCI, n = 256), and patients with AD dementia (n = 57) from the longitudinal Swedish BioFINDER cohort. CSF samples were analyzed for YKL-40, interleukin (IL)–6, IL-7, IL-8, IL-15, IP-10, monocyte chemoattractant protein 1, intercellular adhesion molecule 1 (ICAM-1), vascular adhesion molecule 1 (VCAM-1), placental growth factor, and fms-related tyrosine kinase 1 (Flt-1). MRI data were available from 677 study participants. Longitudinal clinical assessments were conducted in control individuals and patients with MCI (mean follow-up 3 years, range 1–6 years).ResultsCSF levels of YKL-40, ICAM-1, VCAM-1, IL-15, and Flt-1 were increased during the preclinical, prodromal, and dementia stages of AD. High levels of these biomarkers were associated with increased CSF levels of total tau, with the associations, especially for YKL-40, being stronger in Aβ-positive individuals. The results were similar for associations between phosphorylated tau and YKL-40, ICAM-1, and VCAM-1. High levels of the biomarkers were also associated with cortical thinning (primarily in the precuneus and superior parietal regions) and with subsequent cognitive deterioration in patients without dementia as measured with Mini-Mental State Examination (YKL-40) and Clinical Dementia Rating Sum of Boxes (YKL-40, ICAM-1, VCAM-1 and IL-15). Finally, higher levels of CSF YKL-40, ICAM-1, and Flt-1 increased risk of development of AD dementia in patients without dementia.ConclusionsNeuroinflammation and cerebrovascular dysfunction are early events occurring already at presymptomatic stages of AD and contribute to disease progression.

SEQUENCE OF COGNITIVE DECLINE IN ADULTS WITH DOWN SYNDROME DURING PROGRESSION FROM PRECLINICAL TO PRODROMAL ALZHEIMER'S DISEASE

Down syndrome (DS, trisomy 21) is associated with a high risk of Alzheimer's disease (AD) due to triplication of the APP gene on chromosome 21. DS is therefore an important population in which to test the efficacy of drugs aimed at preventing or delaying onset of disease, before neurodegeneration occurs. However, there is lack of data on the early progression of AD in DS. We aimed to define the progression of aging-related decline associated with AD in DS using detailed cognitive phenotyping in a large cohort of older individuals with DS to identify tests that could be used as outcome measures, and to understand the sequence of cognitive decline, as well as effect of the APOE gene. Using cognitive test data and informant-rated questionnaires from 316 adults with DS aged 16 and older, we firstly compared individuals in the preclinical, prodromal and dementia stage of AD to identify cognitive domains most affected in each group and to estimate effect sizes of potential cognitive outcome measures for trials. We also used a data-driven approach, the Event-Based Model (EBM), to estimate the sequence of AD-related cognitive decline and assign participants to a disease stage. We demonstrated that individuals with DS experience significant cognitive decline before the onset of clinical dementia, with large effect sizes on several cognitive measures for the transition from preclinical to prodromal, and from prodromal to dementia stages. Decline in visuospatial memory and sustained attention are implicated as early events in AD in DS; informant measures defined later events. A staging model was identified, with older adults with an AD diagnosis and those with APOE e4 status being more likely to be staged later. We estimated sample sizes required for clinical trials to prevent or delay decline. Significant cognitive change occurs during the prodromal stages of AD in DS, highlighting the necessity for early assessment. Sample size calculations suggest that trials of treatment to prevent or delay dementia are feasible in DS individuals.

PND5 - The Clinical Value of Early Diagnosis Tests for the Long-Term Management of Dementia

A key challenge in early treatment for Alzheimer’s Disease (AD) is identifying the best population for treatment. Genetic tests and imaging technologies are now available to assess the presence of ApoE4 genes or β-amyloid plaques at preclinical stages of AD. Our objective was to assess the utility of these diagnostics for predicting conversion to AD. We simulated disease progression in cognitively normal patients using the AD Archimedes Condition-Event simulator (AD ACE). The AD ACE is constructed using predictive equations for change in disease biomarkers and clinical scales derived primarily from analyses of AD Neuroimaging Initiative (ADNI) data. We compared simulation results over 10 years for 400 patients in each of four patient subgroups (Aβ+/ApoE4+, Aβ+/ApoE4-, Aβ-/ApoE4+, Aβ-/ApoE4-) to evaluate the predictive power of ApoE4 genetic testing versus β-amyloid imaging. Patients with baseline florbetapir PET level ≥ 1.1 for the mcSUVR were considered as Aβ+. Patients with at least one ApoE4 allele were consider ApoE4+. All four patient groups were similar at baseline in terms of their mean age, baseline biomarkers (except β-amyloid level), and cognition scales. Incidence of MCI and AD in the simulation in each subgroup was: Aβ+/ApoE4+ (58%,45%); Aβ+/ApoE4- (57%,39%); Aβ-/ApoE4+ (39%,15%); Aβ-/ApoE4- (35%,13%). Aβ status had moderate power to predict development of MCI, but showed much greater differences in development of AD. While ApoE4 status had minimal incremental information for predicting development of MCI, within the Aβ+ subgroups it retained modest predictive value for the conversion from MCI to AD; 77% of the Aβ+/ApoE4+ subgroup developing MCI converted to AD vs 67% of the Aβ+/ApoE4- subgroup. Amyloid testing was more effective at identifying candidates for an early treatment than ApoE4 status, but ApoE4 can help refine estimates of long-term rates of developing dementia.

Predicting Imminent Progression to Clinically Significant Memory Decline Using Volumetric MRI and FDG PET.

Brain imaging measurements can provide evidence of possible preclinical Alzheimer's disease (AD). Their ability to predict individual imminent clinical conversion remains unclear. To investigate the ability of pre-specified volumetric magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) measurements to predict which cognitively unimpaired older participants would subsequently progress to amnestic mild cognitive impairment (aMCI) within 2 years. From an apolipoprotein E4 (APOE4) enriched prospective cohort study, 18 participants subsequently progressed to the clinical diagnosis of aMCI or probable AD dementia within 1.8±0.8 years (progressors); 20 participants matched for sex, age, education, and APOE allele dose remained cognitively unimpaired for at least 4 years (nonprogressors). A complementary control group not matched for APOE allele dose included 35 nonprogressors. Groups were compared on baseline FDG-PET and MRI measures known to be preferentially affected in the preclinical and clinical stages of AD and by voxel-wise differences in regional gray matter volume and glucose metabolism. Receiver Operating Characteristic, binary logistic regression, and leave-one-out procedures were used to predict clinical outcome for the a priori measures. Compared to non-progressors and regardless of APOE-matching, progressors had significantly reduced baseline MRI and PET measurements in brain regions preferentially affected by AD and reduced hippocampal volume was the strongest predictor of an individual's imminent progression to clinically significant memory decline (79% sensitivity/78% specificity among APOE-matched cohorts). Regional MRI and FDG-PET measurements may be useful in predicting imminent progression to clinically significant memory decline.

Global cerebrovascular burden and long-term clinical outcomes in Asian elderly across the spectrum of cognitive impairment.

A case-control study was conducted over a 2-year period involving participants with no cognitive impairment, cognitive impairment-no dementia (CIND), and Alzheimer's disease (AD). Annually, cognitive function was assessed with a comprehensive neuropsychological battery and the clinical dementia rating (CDR) scale was used to stage disease severity. Of 314 participants, 102 had none/very mild CeVD, 31 mild CeVD, 94 moderate CeVD, and 87 severe CeVD at baseline. There was a 1.14 and 1.42 units decline per year on global cognitive z-scores in moderate and severe CeVD groups, respectively, compared to none/very mild CeVD. Moderate-severe CeVD predicted significant functional deterioration at year 2 (HR = 2.0, 95% CI = 1.2-3.4), and conversion to AD (HR = 6.3, 95% CI = 1.7-22.5), independent of medial temporal atrophy. The global CeVD burden scale predicts poor long-term clinical outcome independent of neurodegenerative markers. Furthermore, CeVD severity affects the rate of cognitive and functional deterioration. Hence, cerebrovascular burden, which is potentially preventable, is a strong prognostic indicator, both at preclinical and clinical stages of AD, independent of neurodegenerative processes.

Increased expression of TREM2 in peripheral cells from mild cognitive impairment patients who progress into Alzheimer's disease.

Neuroinflammation plays a role in the aetiopathogenesis of Alzheimer's disease (AD). Triggering receptor expressed on myeloid cells 2 (TREM2), a cell surface receptor of the immunoglobulin superfamily, seems to have protective anti-inflammatory activity in AD. Triggering receptor expressed on myeloid cells 2 expression was analysed in peripheral blood mononuclear cells from healthy subjects (CT) and from patients with either AD or mild cognitive impairment (MCI). MCI patients were re-evaluated at a 2-year follow-up to investigate their progression to AD (MCI-AD) or lack thereof (MCI-MCI). Triggering receptor expressed on myeloid cells 2 gene expression was higher in AD than CT patients, but was highest in MCI. At recruitment TREM2 levels were higher in MCI-AD than in MCI-MCI, and in MCI-AD were higher initially than at follow-up. TREM2 displayed a moderate degree of sensitivity and specificity for identifying MCI-AD in all MCI patients. Our data showed higher TREM2 levels in allele ε4 of apolipoprotein E (ApoE ε4) carriers than non-carriers in MCI and particularly in MCI-AD. These data seem to confirm the protective role of TREM2 in the pre-clinical stage of AD. Upregulation of TREM2 in MCI-AD could be a mechanism to counteract the activation of neuroinflammatory processes. It is possible that TREM2 and ApoE ε4 interact synergistically in the pre-clinical stage of AD. Therefore, TREM2 may be useful as an early peripheral biomarker for the development of AD.

Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults

The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer’s disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [18F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering (β = −0.12, p < 0.05), and small world values (β = −0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia.

Age-accelerated cognitive decline in asymptomatic adults with CSF β-amyloid.

Compare cognitive and hippocampal volume trajectories in asymptomatic middle-aged and older adults with positive CSF markers of β-amyloid (Aβ) or tau to adults without an Alzheimer disease (AD)-associated biomarker profile. Three hundred ninety-two adults enrolled in a longitudinal cohort study (Wisconsin Registry for Alzheimer's Prevention or Wisconsin Alzheimer's Disease Research Center) completed a lumbar puncture and at least 2 biennial or annual neuropsychological evaluations. Cutoffs for Aβ42, total tau, and phosphorylated tau were developed via receiver operating characteristic curve analyses on a sample of 78 participants (38 dementia, 40 controls). These cutoffs were applied to a separate sample of 314 cognitively healthy adults (mean age at CSF collection = 61.5 years), and mixed-effects regression analyses tested linear and quadratic interactions of biomarker group × age at each visit on cognitive and hippocampal volume outcomes. Two hundred fifteen participants (69%) were biomarker negative (preclinical AD stage 0), 46 (15%) were Aβ+ only (preclinical AD stage 1), 25 (8%) were Aβ+ and tau+ (preclinical AD stage 2), and 28 (9%) were tau+ only. Both stage 1 and stage 2 groups exhibited greater rates of linear decline on story memory and processing speed measures, and nonlinear decline on list-learning and set-shifting measures compared to stage 0. The tau+ only group did not significantly differ from stage 0 in rates of cognitive decline. In an asymptomatic at-risk cohort, elevated CSF Aβ (with or without elevated tau) was associated with greater rates of cognitive decline, with the specific pattern of decline varying across cognitive measures.

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.

Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study.

BackgroundThe metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression.Methods and findingsQuantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and “asymptomatic Alzheimer’s disease” (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes—sphingolipids and glycerophospholipids—that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer’s Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each metabolite to severity of AD pathology and disease progression (Endophenotype Association Score in Early Alzheimer’s Disease [EASE-AD]). Finally, we mapped the main metabolite classes emerging from our analyses to key biological pathways implicated in AD pathogenesis. We found that distinct sphingolipid species including sphingomyelin (SM) with acyl residue sums C16:0, C18:1, and C16:1 (SM C16:0, SM C18:1, SM C16:1) and hydroxysphingomyelin with acyl residue sum C14:1 (SM (OH) C14:1) were consistently associated with severity of AD pathology at autopsy and AD progression across prodromal and preclinical stages. Higher log-transformed blood concentrations of all four sphingolipids in cognitively normal individuals were significantly associated with increased risk of future conversion to incident AD: SM C16:0 (hazard ratio [HR] = 4.430, 95% confidence interval [CI] = 1.703–11.520, p = 0.002), SM C16:1 (HR = 3.455, 95% CI = 1.516–7.873, p = 0.003), SM (OH) C14:1 (HR = 3.539, 95% CI = 1.373–9.122, p = 0.009), and SM C18:1 (HR = 2.255, 95% CI = 1.047–4.855, p = 0.038). The sphingolipid species identified map to several biologically relevant pathways implicated in AD, including tau phosphorylation, amyloid-β (Aβ) metabolism, calcium homeostasis, acetylcholine biosynthesis, and apoptosis. Our study has limitations: the relatively small number of brain tissue samples may have limited our power to detect significant associations, control for heterogeneity between groups, and replicate our findings in independent, autopsy-derived brain samples.ConclusionsWe present a novel framework to identify biologically relevant brain and blood metabolites associated with disease pathology and progression during the prodromal and preclinical stages of AD. Our results show that perturbations in sphingolipid metabolism are consistently associated with endophenotypes across preclinical and prodromal AD, as well as with AD pathology at autopsy. Sphingolipids may be biologically relevant biomarkers for the early detection of AD, and correcting perturbations in sphingolipid metabolism may be a plausible and novel therapeutic strategy in AD.

Exercise Intervention Associated with Cognitive Improvement in Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease with the syndrome of cognitive and functional decline. Pharmacotherapy has always been in a dominant position for the treatment of AD. However, in most cases, drug therapy is accompanied with clinical delays when older adults have suffered from cognitive decline in episodic memory, working memory, and executive function. On the other hand, accumulating evidence suggests that exercise intervention may ameliorate the progression of cognitive impairment in aging ones while the standard strategy is lacking based on different levels of cognitive decline especially in mild cognitive impairment (MCI) and AD. MCI is the preclinical stage of AD in which neurodegeneration may be reversed via neuroplasticity. Therefore, taking exercise intervention in the early stage of MCI and healthy aging at the risk of AD could slow down the process of cognitive impairment and provide a promising cost-effective nonpharmacological therapy to dementia.

Longitudinal structural cerebral changes related to core CSF biomarkers in preclinical Alzheimer's disease: A study of two independent datasets.

Alzheimer's disease (AD) is characterized by an accumulation of β-amyloid (Aβ42) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that Aβ42 accumulation is associated with gray matter (GM) changes prior to the development of cognitive impairment, in the so-called preclinical stage of the AD (pre-AD). It also has been proved that the GM atrophy profile is not linear, both in normal ageing but, especially, on AD. However, several other factors may influence this association and may have an impact on the generalization of results from different samples. In this work, we estimate differences in rates of GM volume change in cognitively healthy elders in association with baseline core cerebrospinal fluid (CSF) AD biomarkers, and assess to what these differences are sample dependent. We report the dependence of atrophy rates, measured in a two-year interval, on Aβ42, computed both over continuous and categorical values of Aβ42, at voxel-level (p < 0.001; k < 100) and corrected for sex, age and education. Analyses were performed jointly and separately, on two samples. The first sample was formed of 31 individuals (22 Ctrl and 9 pre-AD), aged 60–80 and recruited at the Hospital Clinic of Barcelona. The second sample was a replica of the first one with subjects selected from the ADNI dataset. We also investigated the dependence of the GM atrophy rate on the basal levels of continuous p-tau and on the p-tau/Aβ42 ratio. Correlation analyses on the whole sample showed a dependence of GM atrophy rates on Aβ42 in medial and orbital frontal, precuneus, cingulate, medial temporal regions and cerebellum. Correlations with p-tau were located in the left hippocampus, parahippocampus and striatal nuclei whereas correlation with p-tau/Aβ42 was mainly found in ventral and medial temporal areas. Regarding analyses performed separately, we found a substantial discrepancy of results between samples, illustrating the complexities of comparing two independent datasets even when using the same inclusion criteria. Such discrepancies may lead to significant differences in the sample size needed to detect a particular reduction on cerebral atrophy rates in prevention trials. Higher cognitive reserve and more advanced pathological progression in the ADNI sample could partially account for the observed discrepancies. Taken together, our findings in these two samples highlight the importance of comparing and merging independent datasets to draw more robust and generalizable conclusions on the structural changes in the preclinical stages of AD.

The Erlangen Score Algorithm in the diagnosis and prediction of the progression from subjective cognitive decline and mild cognitive impairment to Alzheimer-type dementia.

The evaluation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD) (β-amyloid, t-tau, p-tau) can be used to estimate the risk of developing dementia in patients at the pre-clinical stages of AD, i.e. subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Erlangen Score Algorithm allows interpretation of CSF biomarker concentrations and is cut-off value independent. The aim of this study was to establish if this algorithm can be applied for routine diagnostic testing in clinical and preclinical subjects and has prognostic value. We analysed 217 patients from the memory clinic with the diagnosis of SCD (n = 31), MCI (n = 104), and AD (n = 82) with clinical follow-up amounting to 14.33 months (SD = 6.82). It was found that the highest Erlangen Score dominated in the AD group and was the rarest in the SCD group. In the group of patients with progression of symptoms during our period of observation, the AD pathology was confirmed in 93.75% of cases. Among the non-progressing subjects (n = 119) the algorithm indicated the risk of developing AD as possible in 40.34% and probable in 15.97% of cases. To conclude, the Erlangen Score Algorithm is auseful tool to determinate the risk of developing AD before the onset of dementia or to confirm the AD diagnosis. It is extremely valuable in preclinical stages of AD for planning purposes and early intervention as well as for future clinical trials.

A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis.

Although alternations of brain functional networks (BFNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been considered as promising biomarkers for early Alzheimer's disease (AD) diagnosis, it is still challenging to perform individualized diagnosis, especially at the very early stage of preclinical stage of AD, i.e., early mild cognitive impairment (eMCI). Recently, convolutional neural networks (CNNs) show powerful ability in computer vision and image analysis applications, but there is still a gap for directly applying CNNs to rs-fMRI-based disease diagnosis. In this paper, we propose a novel multiple-BFN-based 3D CNN framework that can automatically and deeply learn complex, high-level, hierarchical diagnostic features from various independent component analysis-derived BFNs. More importantly, the embedded features of different BFNs could comprehensively support each other towards a more accurate eMCI diagnosis in a unified model. The performance of the proposed method is validated by a large-sample, multisite, rigorously controlled publicly accessible dataset. The proposed framework can also be conveniently and straightforwardly applied to individualized diagnosis of various neurological and psychiatric diseases.

Change in retinal structural anatomy during the preclinical stage of Alzheimer's disease

IntroductionWe conducted a 27-month longitudinal study of mid-life adults with preclinical Alzheimer's disease (AD), using spectral domain optical coherence tomography to compare changes in volume and thickness in all retinal neuronal layers to those of age-matched healthy control subjects. MethodsFifty-six older adults (mean age = 65.36 years) with multiple risk factors for AD completed spectral domain optical coherence tomography retinal imaging and cognitive testing at baseline. Twenty-seven months later, they completed the same examinations and an 18F-florbetapir positron emission tomography imaging study. ResultsCompared to healthy control subjects, those in the preclinical stage of AD showed a significant decrease in macular retinal nerve fiber layer (mRNFL) volume, over a 27-month follow-up interval period, as well as a decrease in outer nuclear layer and inner plexiform layer volumes and thickness in the inferior quadrant. However, only the mRNFL volume was linearly related to neocortical positron emission tomography amyloid standardized uptake value ratio after controlling for any main effects of age (R2 = 0.103; ρ = 0.017). Furthermore, the magnitude of mRNFL volume reduction was significantly correlated with performance on a task of participants' abilities to efficiently integrate visual and auditory speech information (McGurk effect). DiscussionWe observed a decrease in mRNFL, outer nuclear layer, and inner plexiform layer volumes, in preclinical AD relative to controls. Moreover, the largely myelinated axonal loss in the RNFL is related to increased neocortical amyloid-β accumulation after controlling for age. Volume loss in the RNFL, during the preclinical stage, is not related to performance on measures of episodic memory or problem solving. However, this retinal change does appear to be modestly related to relative decrements in performance on a measure of audiovisual integration efficiency that has been recently advanced as a possible early cognitive marker of mild cognitive impairment.

Rich club disturbances of the human connectome from subjective cognitive decline to Alzheimer's disease.

Alzheimer's disease (AD) has a preclinical phase that can last for decades prior to clinical dementia onset. Subjective cognitive decline (SCD) is regarded as the last preclinical AD stage prior to the development of amnestic mild cognitive decline (aMCI) and AD dementia (d-AD). The analysis of brain structural networks based on diffusion tensor imaging (DTI) has identified the so-called 'rich club', a set of cortical regions highly connected to each other, with other regions referred to as peripheral. It has been reported that rich club architecture is affected by regional atrophy and connectivity, which are reduced in patients with aMCI and d-AD.Methods: We recruited 62 normal controls, 47 SCD patients, 60 aMCI patients and 55 d-AD patients and collected DTI data to analyze rich-club organization.Results: We demonstrated that rich club organization was disrupted, with reduced structural connectivity among rich club nodes, in aMCI and d-AD patients but remained stable in SCD patients. In addition, SCD, aMCI and d-AD patients showed similar patterns of disrupted peripheral regions and reduced connectivity involving these regions, suggesting that peripheral regions might contribute to cognitive decline and that disruptions here could be regarded as an early marker of SCD. This organization could provide the fundamental structural architecture for complex cognitive functions and explain the low prevalence of cognitive problems in SCD patients.Conclusions: These findings reveal a disrupted pattern of the AD connectome that starts in peripheral regions and then hierarchically propagates to rich club regions, when patients show clinical symptoms. This pattern provides evidence that disruptions in rich club organization are a key factor in the progression of AD that can dynamically reflect the progression of AD, thus representing a potential biomarker for early diagnosis.

Altered structural network organization in cognitively normal individuals with amyloid pathology

Recent findings show that structural network topology is disrupted in Alzheimer's disease (AD), with changes occurring already at the prodromal disease stages. Amyloid accumulation, a hallmark of AD, begins several decades before symptom onset, and its effects on brain connectivity at the earliest disease stages are not fully known. We studied global and local network changes in a large cohort of cognitively healthy individuals (N = 299, Swedish BioFINDER study) with and without amyloid-β (Aβ) pathology (based on cerebrospinal fluid Aβ42/Aβ40 levels). Structural correlation matrices were constructed based on magnetic resonance imaging cortical thickness data. Despite the fact that no significant regional cortical atrophy was found in the Aβ-positive group, this group exhibited an altered global network organization, including decreased global efficiency and modularity. At the local level, Aβ-positive individuals displayed fewer and more disorganized modules as well as a loss of hubs. Our findings suggest that changes in network topology occur already at the presymptomatic (preclinical) stage of AD and may precede detectable cortical thinning.

Plasma Proteomic Profiles of Cerebrospinal Fluid-Defined Alzheimer's Disease Pathology in Older Adults.

Cerebrospinal fluid (CSF) biomarkers of the beta-amyloid and microtubule associated protein tau metabolism have proven the capacity to improve classification of subjects developing Alzheimer's disease (AD). The blood plasma proteome was characterized to further elaborate upon the mechanisms involved and identify proteins that may improve classification of older adults developing an AD dementia. Identify and describe plasma protein expressions that best classify subjects with CSF-defined presence of AD pathology and cerebral amyloidosis. We performed a cross-sectional analysis of samples collected from community-dwelling elderly with (n = 72) or without (n = 48) cognitive impairment. CSF Aβ1-42, tau, and phosphorylated tau (P-tau181) were measured using ELISA, and mass spectrometry quantified the plasma proteomes. Presence of AD pathology was defined as CSF P-tau181/Aβ1-42 > 0.0779, and presence of amyloidosis was defined as CSF Aβ1-42 < 724 pg/mL. Two hundred and forty-eight plasma proteins were quantified. Plasma proteins did not improve classification of the AD CSF biomarker profile in the whole sample. When the analysis was separately performed in the cognitively impaired individuals, the diagnosis accuracy of AD CSF profile was 88.9% with 19 plasma proteins included. Within the full cohort, there were 16 plasma proteins that improved diagnostic accuracy of cerebral amyloidosis to 92.4%. Plasma proteins improved classification accuracy of AD pathology in cognitively-impaired older adults and appeared representative of amyloid pathology. If confirmed, those candidates could serve as valuable blood biomarkers of the preclinical stages of AD or risk of developing AD.

MRI structural network measures are associated with both general and specific domains of cognitive function

Background: Pre-clinical stages of Alzheimer disease include mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Evidence suggests that cognitive impairment of MCI might arise from disrupted topological organization in the white matter structural networks. However, whether this organization is related to cognitive function and domains remains unclear.

Complexity analysis of cortical surface detects changes in future Alzheimer's disease converters.

Alzheimer's disease (AD) is a neurological disorder that creates neurodegenerative changes at several structural and functional levels in human brain tissue. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of the human brain. In this study, we investigate spherical harmonic-based FD (SHFD), thickness, and local gyrification index (LGI) to assess whether they identify cortical surface abnormalities toward the conversion to AD. We study 33 AD patients, 122 mild cognitive impairment (MCI) patients (50 MCI converters and 29 MCI nonconverters), and 32 healthy controls (HC). SHFD, thickness, and LGI methodology allowed us to perform not only global level but also local level assessments in each cortical surface vertex. First, we found that global SHFD decreased in AD and future MCI converters compared to HC, and in MCI converters compared to MCI nonconverters. Second, we found that local white matter SHFD was reduced in AD compared to HC and MCI mainly in medial temporal lobe. Third, local white-matter SHFD was significantly reduced in MCI converters compared to MCI nonconverters in distributed areas, including the medial frontal lobe. Thickness and LGI metrics presented a reduction in AD compared to HC. Thickness was significantly reduced in MCI converters compared to healthy controls in entorhinal cortex and lateral temporal. In summary, SHFD was the only surface measure showing differences between MCI individuals that will convert or remain stable in the next 4years. We suggest that SHFD may be an optimal complement to thickness loss analysis in monitoring longitudinal changes in preclinical and clinical stages of AD. Hum Brain Mapp 38:5905-5918, 2017. © 2017 Wiley Periodicals, Inc.