Plasma ceramides are altered in mild cognitive impairment and predict cognitive decline and hippocampal volume loss

BackgroundA blood-based biomarker of Alzheimer's disease (AD) would be superior to cerebrospinal fluid (CSF) and neuroimaging measures in terms of cost, invasiveness, and feasibility for repeated measures. We previously reported that blood ceramides varied in relation to timing of memory impairment in a population-based study. The present objective was to examine whether plasma ceramides varied by AD severity in a well-characterized clinic sample and were associated with cognitive decline and hippocampal volume loss over 1 year.MethodsParticipants included 25 normal controls (NC), 17 amnestic Mild Cognitive Impairment (MCI), and 21 early probable AD. A thorough neuropsychological battery and neuroimaging with hippocampal volume determination were conducted at baseline and 1 year later. Plasma ceramides were assayed at baseline using high performance liquid chromatography coupled electrospray ionization tandem mass spectrometry.ResultsAlthough all saturated ceramides were lower in MCI compared with AD at baseline, ceramides C22:0 and C24:0 were significantly lower in the MCI group compared with both NC and AD groups (P < .01). Ceramide levels did not differ (P > .05) in AD versus NC. There were no cross-sectional associations between ceramides C22:0 and C24:0 and either cognitive performance or hippocampal volume among any group. However, among the MCI group, higher baseline ceramide C22:0 and C24:0 levels were predictive of cognitive decline and hippocampal volume loss 1 year later.ConclusionResults suggest that very long-chain plasma ceramides C22:0 and C24:0 are altered in MCI and predict memory loss and right hippocampal volume loss among subjects with MCI. These plasma ceramides may be early indicators of AD progression.     

Extension and refinement of the predictive value of different classes of markers in ADNI: Four-year follow-up data

BackgroundThis study examined the predictive value of different classes of markers in the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) over an extended 4-year follow-up in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.MethodsMCI patients were assessed for clinical, cognitive, magnetic resonance imaging (MRI), positron emission tomography–fluorodeoxyglucose (PET-FDG), and cerebrospinal fluid (CSF) markers at baseline and were followed on a yearly basis for 4 years to ascertain progression to AD. Logistic regression models were fitted in clusters, including demographics, APOE genotype, cognitive markers, and biomarkers (morphometric, PET-FDG, CSF, amyloid-β, and tau).ResultsThe predictive model at 4 years revealed that two cognitive measures, an episodic memory measure and a Clock Drawing screening test, were the best predictors of conversion (area under the curve = 0.78).ConclusionsThis model of prediction is consistent with the previous model at 2 years, thus highlighting the importance of cognitive measures in progression from MCI to AD. Cognitive markers were more robust predictors than biomarkers.     

Cerebrospinal fluid Aβ42 is the best predictor of clinical progression in patients with subjective complaints

BackgroundThe need to recognize Alzheimer’s disease (AD) as early as possible led us to evaluate the predictive value of amyloid β(1-42) (Aβ42), total tau (tau), and phosphorylated tau (ptau) in cerebrospinal fluid (CSF) for clinical progression in patients with subjective complaints.MethodsWe recruited nondemented patients with subjective complaints (i.e., criteria for mild cognitive impairment [MCI] not fulfilled) from our memory clinic. We assessed the predictive value of CSF Aβ42, tau, and ptau for clinical progression using Cox proportional hazards models adjusted for age, gender, and baseline findings on the Mini-Mental State Examination (MMSE). Clinical progression was defined as progression to MCI or AD.ResultsWe included 127 patients with subjective complaints (age 60 ± 10 years, 61 [48%] females, MMSE 29 ± 1). At baseline, Aβ42 and tau were abnormal in 20 patients (both 16%), and ptau in 32 patients (25%). Thirteen patients (10%) progressed to MCI (n = 11) or AD (n = 2). Aβ42 was the strongest predictor of progression to MCI or AD with an adjusted hazard ratio (HR) of 16.0 (3.8–66.4). The adjusted HR associated with tau was 2.8 (0.9–9.2) and with ptau 2.6 (0.8–8.2). Combinations of biomarkers had a lower predictive value than Aβ42 alone.ConclusionLow Aβ42 was the strongest predictor of clinical progression in patients with subjective complaints. These results are in line with the hypothesis that the cascade of pathologic events starts with deposition of Aβ42, whereas neuronal degeneration and hyperphosphorylation of tau are more downstream events, closer to clinical manifestation of AD.     

A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data

IntroductionIt is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia.MethodsA deep learning method is developed and validated based on magnetic resonance imaging scans of 2146 subjects (803 for training and 1343 for validation) to predict MCI subjects' progression to AD dementia in a time-to-event analysis setting.ResultsThe deep-learning time-to-event model predicted individual subjects' progression to AD dementia with a concordance index of 0.762 on 439 Alzheimer's Disease Neuroimaging Initiative testing MCI subjects with follow-up duration from 6 to 78 months (quartiles: [24, 42, 54]) and a concordance index of 0.781 on 40 Australian Imaging Biomarkers and Lifestyle Study of Aging testing MCI subjects with follow-up duration from 18 to 54 months (quartiles: [18, 36, 54]). The predicted progression risk also clustered individual subjects into subgroups with significant differences in their progression time to AD dementia (P < .0002). Improved performance for predicting progression to AD dementia (concordance index = 0.864) was obtained when the deep learning–based progression risk was combined with baseline clinical measures.DiscussionOur method provides a cost effective and accurate means for prognosis and potentially to facilitate enrollment in clinical trials with individuals likely to progress within a specific temporal period.     

Inflammatory biomarkers in Alzheimer's disease plasma

IntroductionPlasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a “Holy Grail” of AD research and intensively sought; however, there are no well-established plasma markers.MethodsA hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.ResultsTen analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).DiscussionPlasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.     

Predicting the progression of mild cognitive impairment to Alzheimer’s disease by longitudinal magnetic resonance imaging-based dictionary learning

ObjectiveEfficient prediction of the progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is important for the early intervention and management of AD. The aim of our study was to develop a longitudinal structural magnetic resonance imaging-based prediction system for MCI progression.MethodsA total of 164 MCI patients with longitudinal data were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). After preprocessing, a discriminative dictionary learning framework was applied to differentiate MCI patches, avoiding the segmentation of regions of interest. Then, the proportion of patches classified as more severe atrophy patches in a patient was calculated as his or her feature to be input into a simple support vector machine. Finally, a new subject was predicted with fourfold cross-validation (CV), and the area under the receiver operating characteristic curve (AUC) was determined.ResultsThe average accuracy and AUC values after fourfold CV were 0.973 and 0.984, respectively. The effects of the data from one or two time points were also investigated.ConclusionThe proposed prediction system achieves desirable and reliable performance in predicting progression for MCI patients. Additionally, the prediction of MCI progression with longitudinal data was more effective and accurate.SignificanceThe developed scheme is expected to advance the clinical research and treatment of MCI patients.     

The role of event-related potentials in cognitive decline in Alzheimer’s disease

ObjectivesEarly diagnosis and monitoring of disease progression have become vital in clinical practice as disease modifying treatments for Alzheimer’s disease (AD) become available. This one-year prospective study aimed to clarify the usefulness of event-related potentials (ERPs) in cognitive decline and elucidate their cognitive significance in AD.MethodsUsing the Cognitive Abilities Screening Instrument (CASI) and ERPs, probable AD patients, mild cognitive impairment (MCI) patients, and normal controls were recruited.ResultsThe AD and MCI patients had significantly decreased cognitive function and manifested a delay of P300 latency. The P300 latencies demonstrated significantly more prolongation than their baseline values in probable AD and MCI patients, although their CASI scores showed no statistically significant decline. Whereas N100, P200, and N200 components did not reach statistical differences between groups either in the baseline or follow-up assessments and did not show significant change on follow-up.ConclusionThe combination of neuropsychological tests and P300 measurements proved useful in improving reliability and increasing sensitivity to early cognitive decline or disease progression in AD patients.SignificanceThe P300 latency may reflect cognitive decline more sensitively than neuropsychological tests in the longitudinal follow-up of AD patients.     

Aβ and cognitive change: Examining the preclinical and prodromal stages of Alzheimer's disease

BackgroundHigh β-amyloid (Aβ) is associated with faster memory decline in healthy individuals and adults with mild cognitive impairment (MCI). However, longer prospective studies are required to determine if Aβ-related memory decline continues and whether it is associated with increased rate of disease progression.MethodsHealthy controls (HCs; n = 177) and adults with MCI (n = 48) underwent neuroimaging for Aβ and cognitive assessment at baseline. Cognition was reassessed 18 and 36 months later.ResultsCompared with low-Aβ HCs, high-Aβ HC and MCI groups showed moderate decline in episodic and working memory over 36 months. Those with MCI with low Aβ did not show any cognitive decline. Rates of disease progression were increased in the high-Aβ HC and MCI groups.ConclusionsIn healthy individuals, high Aβ likely indicates that Alzheimer's disease (AD)-related neurodegeneration has begun. Once commenced, the rate of decline in cognitive function remains constant across the preclinical and prodromal stages of AD.     

Relevance of functional neuroimaging in the progression of mild cognitive impairment

Abstract

Aim: To assess whether combining neuropsychological tests and cerebral blood flow markers improves progression accuracy from mild cognitive impairment (MCI) to Alzheimer's disease (AD) than each of them on its own.

Methods: Forty-two patients were investigated prospectively, undergoing baseline and 3-year follow-up neuropsychological tests and neuroimaging with Tc-ECD–SPECT. Twenty-one patients had developed AD while 21 retained their initial diagnosis. The relative blood flow and cognitive differences were studied. Validity parameters, multivariant analysis and logistic regression model were calculated.

Results: Patients who deteriorated showed lower scoring than stable subjects in some neuropsychological tests (p = 0.03–0.001) and in relative blood flow in selected regions (8–10%). Low cognitive test scoring and low relative blood flow in some regions showed sensibilities and specificities from 70% to 86% for the diagnosis of early Alzheimer's disease. The relative risk of progression to AD was up to 4.7 times higher for these patients (p = 0.0001). The left frontal relative blood flow, the CAMCOG and orientation scoring were the best data to predict the risk of progression to AD.

Conclusions: The combination of functional imaging and neuropsychological tests can diagnose with high sensitivity and specificity if a patient is suffering cognitive impairment in its early stages, and may aid in predicting the risk of developing dementia.     

A Single Baseline Amyloid Positron Emission Tomography Could Be Sufficient for Predicting Alzheimer’s Disease Conversion in Mild Cognitive Impairment

ObjectiveBaseline amyloid burden in mild cognitive impairment (MCI) has been linked to conversion to Alzheimer’s disease (AD), but the comparison of baseline and longitudinal changes in amyloid burden for predicting AD remains unresolved. The objectives of this study aimed to compare the prognostic ability of baseline and longitudinal changes in amyloid burden in MCI patients. MethodsSeventy-five individuals with MCI were recruited and examined annually by clinical interviews for a mean follow-up of 24 months (range, 11.6–42.0). [18F]Florbetaben positron emission tomography (PET) scans were performed. T1-weighted 3D volumes were acquired for co-registration, and to define regions of interest. We examined whether baseline and longitudinal amyloid burden changes can improve AD conversion by Cox proportional hazard model analysis and receiver operating characteristic (ROC) curve analysis. ResultsCox proportional hazards model analysis showed that baseline amyloid burden was significantly associated with increased risk of conversion to AD (hazard ratio [HR]=10.0; 95% confidence interval [CI], 1.15–85.39; p=0.04), but longitudinal amyloid burden changes was not (HR=0.2; 95% CI, 0.02–1.18; p=0.07). When predicting AD, longitudinal amyloid burden changes had better ROC accuracy of 65.2% (95% CI, 48.4–82.0) than baseline amyloid burden of 59.6% (95% CI, 40.3–79.0), without statistical significance in pairwise comparison. ConclusionA single baseline amyloid PET could be sufficient in the prediction of AD conversion in MCI.     

Antioxidants for the treatment of mild cognitive impairment

Abstract

The isolated deficit in recent memory frequently associated with decline to Alzheimer's disease (AD) is defined as mild cognitive impairment (MCI). The observed progression of MCI to AD suggests a common pathogenesis between these two clinical syndromes, and several neuroimaging, neuropsychological and biological methods are applied with the purpose of identifying subjects at risk of AD. Among these methods, the evaluation of a condition of oxidative stress is gaining increasing attention. Since oxidative stress seems to be involved in the earliest phases of AD, and MCI may be considered as a prodromal phase of dementia, it is an attractive issue to focus therapeutic interventions on the early phase of the disease.     

The relevance of hippocampal subfield integrity and clock drawing test performance for the diagnosis of Alzheimer’s disease and mild cognitive impairment

Objectives: The clock drawing test (CDT) is one of the worldwide most used screening tests for Alzheimer’s disease (AD). MRI studies have identified temporo-parietal regions being involved in CDT impairment. However, the contributions of specific hippocampal subfields and adjacent extrahippocampal structures to CDT performance in AD and mild cognitive impairment (MCI) have not been investigated so far. It is unclear whether morphological alterations or CDT score, or a combination of both, are able to predict AD.

Methods: 38 AD patients, 38?MCI individuals and 31 healthy controls underwent neuropsychological assessment and MRI at 3 Tesla. FreeSurfer 5.3 was used to perform hippocampal parcellation. We used a collection of statistical methods to better understand the relationship between CDT and hippocampal formation. We also tested the clinical feasibility of this relationship when predicting AD.

Results: Impaired CDT performance in AD was associated with widespread atrophy of the cornu ammonis, presubiculum, and subiculum, whereas MCI subjects showed CDT-related alterations of the CA4-dentate gyrus and subiculum. CDT correlates in AD and MCI showed regional and quantitative overlap. Importantly, CDT score was the best predictor of AD.

Conclusions: Our findings lend support for an involvement of different hippocampal subfields in impaired CDT performance in AD and MCI. CDT seems to be more efficient than subfield imaging for predicting AD.     

Decreased Levels of Circulating Adiponectin in Mild Cognitive Impairment and Alzheimer’s Disease

Adiponectin, an adipocytokine released by the adipose tissue and has important roles in the metabolic regulation and inflammatory control, may play an important roles in the physiopathology of psychiatric and neurodegenerative disorders. The aim of the present work was to evaluate adiponectin serum levels in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) as compared to cognitively healthy elders and to correlate these levels with clinical and cognitive parameters. We further evaluated whether circulating adiponectin levels could predict progression from MCI to Alzheimer’s disease upon follow-up. We recruited 157 subjects (41 with AD, 65 with MCI and 51 elderly controls) in the baseline assessment. Follow-up data were available for 54 subjects with MCI and 43 controls in whom we ascertained the conversion to AD and the progression of cognitive impairment. Adiponectin was assayed by sandwich ELISA. Serum levels of adiponectin were significantly lower in MCI and AD as compared to controls (p < 0.001). After controlling for age, educational level and APOE genotype, adiponectin levels remained significantly reduced in these groups (p < 0.001). Circulating adiponectin levels did not predict cognitive decline in the elderly controls (i.e., progression from normal cognition to MCI) or progression to Alzheimer’s disease in subjects with MCI. We conclude that lower levels of adiponectin were associated with cognitive dysfunction, though it did not predict additional cognitive decline and conversion to dementia in this cohort of elderly subjects. Decreased adiponectin may be a surrogate marker of the pathological process in AD, linking clinical comorbidities, inflammation and cognitive dysfunction.     

Cognitive Decline in Mild Cognitive Impairment With Lewy Bodies or Alzheimer Disease: A Prospective Cohort Study

ObjectiveWe explored whether the mild cognitive impairment (MCI) stages of dementia with Lewy bodies (DLB) and Alzheimer disease (AD) differ in their cognitive profiles, and longitudinal progression.DesignA prospective, longitudinal design was utilized with annual follow-up (Max 5 years, Mean 1.9, standard deviation 1.1) after diagnosis. Participants underwent repeated cognitive testing, and review of their clinical diagnosis and symptoms, including evaluation of core features of DLB.SettingThis was an observational study of independently living individuals, recruited from local healthcare trusts in North East England, UK.ParticipantsAn MCI cohort (n = 76) aged ≥60 years was utilized, differentially diagnosed with MCI due to AD (MCI-AD), or possible/probable MCI with Lewy bodies (MCI-LB).MeasurementsA comprehensive clinical and neuropsychological testing battery was administered, including ACE-R, trailmaking tests, FAS verbal fluency, and computerized battery of attention and perception tasks.ResultsProbable MCI-LB presented with less impaired recognition memory than MCI-AD, greater initial impairments in verbal fluency and perception of line orientation, and thereafter demonstrated an expedited decline in visuo-constructional functions in the ACE-R compared to MCI-AD. No clear diagnostic group differences were found in deterioration speeds for global cognition, language, overall memory, attention or other executive functions.ConclusionThese findings provide further evidence for differences in severity and decline of visuospatial dysfunctions in DLB compared with AD; further exploration is required to clarify when and how differences in attention, executive, and memory functions emerge, as well as speed of decline to dementia.     

An investigation of PreMCI: subtypes and longitudinal outcomes

Background/AimsTo investigate the clinical features and rates of progression of conditions that are not considered to be normal, but do not fulfill criteria for mild cognitive impairment (MCI).MethodsWe longitudinally evaluated 269 elderly subjects who did not meet formal criteria for MCI at baseline but had: (1) a clinical history suggesting MCI without neuropsychological deficits (PreMCI-Clinical); or (2) neuropsychological deficits on one or more memory measures in conjunction with a negative clinical examination (amnestic PreMCI-NP) or were normal on both neuropsychological and clinical examination.ResultsThe rate of progression to MCI or dementia over an average of 2- to 3 years was 3.7% for no cognitive impairment subjects, whereas it was significantly greater for all PreMCI subtypes (22.0% for PreMCI-Clinical, 38.9% for amnestic PreMCI-NP subjects with two or more memory impairments). Among PreMCI subjects as a whole, lower baseline scores on object memory and category fluency tests were the best predictors of progression to MCI or dementia. Cardiovascular risk factors, Parkinsonian symptoms, and hippocampal atrophy were not associated with progression.ConclusionDistinct PreMCI subtypes defined on the basis of clinical and neuropsychological evaluations were found to have distinct characteristics, but both subtypes demonstrated elevated risk for progression to MCI or dementia. Despite the lack of evidence of clinical impairment, subjects with neuropsychological deficits in two memory domains were particularly at increased risk for progression of their deficits.     

Effect of brain-derived neurotrophic factor Val66Met polymorphism and serum levels on the progression of mild cognitive impairment

Abstract

Objectives. Abnormalities in neurotrophic systems have been reported in Alzheimer's disease (AD), as shown by decreased serum brain-derived neurotrophic factor (BDNF) levels and association with BDNF genetic polymorphisms. In this study, we investigate whether these findings can be detected in patients with mild cognitive impairment (MCI), which is recognized as a high risk condition for AD. We also address the impact of these variables on the progression of cognitive deficits within the MCI-AD continuum. Methods. One hundred and sixty older adults with varying degrees of cognitive impairment (30 patients with AD, 71 with MCI, and 59 healthy controls) were longitudinally assessed for up to 60 months. Baseline serum BDNF levels were determined by sandwich ELISA, and the presence of polymorphisms of BDNF and apolipoprotein E (Val66Met and APOE*E4, respectively) was determined by allelic discrimination analysis on real time PCR. Modifications of cognitive state were ascertained for non-demented subjects. Results. Mean serum BDNF levels were reduced in patients with MCI and AD, as compared to controls (509.2±210.5; 581.9±379.4; and 777.5±467.8 pg/l respectively; P<0.001). Baseline serum BDNF levels were not associated with the progression of cognitive impairment upon follow-up in patients with MCI (progressive MCI, 750.8±463.0; stable MCI, 724.0±343.4; P=0.8), nor with the conversion to AD. Although Val66Met polymorphisms were not associated with the cross-sectional diagnoses of MCI or AD, the presence of Met-BDNF allele was associated with a higher risk of disease-progression in patients with MCI (OR=3.0 CI_95% [1.2–7.8], P=0.02). We also found a significant interaction between the APOE*E4 and Met-BDNF allele increasing the risk of progression of cognitive impairment in MCI patients (OR=4.4 CI_95% [1.6–12.1], P=0.004). Conclusion. Decreased neurotrophic support, as indicated by a reduced systemic availability of BDNF, may play role in the neurodegenerative processes that underlie the continuum from MCI to AD. The presence of Met-BDNF allele, particularly in association with APOE*E4, may predict a worse cognitive outcome in patients with MCI.     

The new 2011 recommendations of the National Institute on Aging and the Alzheimer's Association on diagnostic guidelines for Alzheimer's disease: Preclinal stages, mild cognitive impairment, and dementia

BackgroundCriteria for the clinical diagnosis of Alzheimer's disease (AD) were established in 1984, and they needed to be updated and revised, in vue of the scientific knowledge acquired over the last decades.MethodsThe National Institute on Aging (NIA) and the Alzheimer's Association (AA) sponsored a series of advisory round table meetings to establish a revision of diagnostic and research criteria for AD. The workgroups reviewed the biomarker, epidemiological, and neuropsychological evidence, and proposed conceptual frameworks as well as operational research criteria based on the prevailing scientific evidence to date.ResultsThree preclinical stages of AD were proposed: asymptomatic amyloidosis, asymptomatic amyloidosis + neurodegeneration, amyloidosis + neurodegeneration + subtle cognitive decline. The preclinical workgroup developed recommendations to determine the factors, which best predict the risk of progression from normal cognition to mild cognitive impairment (MCI) and AD dementia. It is necessary to refine these models with longitudinal clinical research studies. The workgroups on MCI and AD dementia sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. The symptomatic predementia phase of AD was referred to as MCI due to AD. Core clinical and cognitive criteria of MCI were proposed, the final set of criteria for MCI due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Criteria for all-cause dementia and for AD dementia were presented. Dementia caused by AD were classified in: probable AD dementia, possible AD dementia, and probable or possible AD dementia with evidence of the AD pathophysiological process, for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis.ConclusionsIn the revised criteria, a conceptual distinction is made between AD pathophysiological processes and clinically observable syndromes. The core clinical criteria of the recommendations regarding MCI due to AD and AD dementia are intended to guide diagnosis in the clinical setting whereas the recommendations of the preclinical AD workgroup are intended purely for research purposes and do not have any clinical implications. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings.     

Fluorodeoxyglucose positron emission tomography of mild cognitive impairment with clinical follow-up at 3 years

BackgroundAlzheimer's disease (AD) is the most common dementing illness. Development of effective treatments directed at AD requires an early diagnosis. Mild cognitive impairment (MCI) often heralds AD. Thus, characterizing MCI is fundamental to the early diagnosis of AD.Methods19 MCI patients referred from a memory loss clinic and 27 healthy subjects, all followed up for 3 years. Metabolism scans (MCI minus controls) were compared voxel-wise after anatomic normalization and were examined both visually and with a computerized classifier.ResultsAgreement between raters as to whether the individual scans were normal or abnormal was high. Agreement between raters of the eventual clinical diagnosis and baseline metabolic pattern was poor. A computerized classifier was unsuccessful at classifying MCI from normal; however, its performance improved when using only prototypic AD-like MCI scans, indicating the classifier worked well when shared patterns existed in the data. Outcomes on follow-up were nine of 19 AD, five of 19 remained MCI, and five of 19 developed dementias other than AD. Both MCI cases of early Lewy body dementia (LBD) showed an AD-like metabolic pattern.ConclusionsVisual inspection proved reliable in determining normal from abnormal scans, but it proved unreliable at predicting diagnosis on follow-up. Computerized classification of MCI by using an AD-like metabolic template (such as derived from the averaged MCI images) showed potential to identify patients who will develop AD. However, the metabolic pattern in early LBD did not differ from that in AD.     

Core candidate neurochemical and imaging biomarkers of Alzheimer’s disease

BackgroundIn the earliest clinical stages of Alzheimer’s disease (AD) when symptoms are mild, clinical diagnosis can be difficult. AD pathology most likely precedes symptoms. Biomarkers can serve as early diagnostic indicators or as markers of preclinical pathologic change. Candidate biomarkers derived from structural and functional neuroimaging and those measured in cerebrospinal fluid (CSF) and plasma show the greatest promise. Unbiased exploratory approaches, eg, proteomics or cortical thickness analysis, could yield novel biomarkers. The objective of this article was to review recent progress in selected imaging and neurochemical biomarkers for early diagnosis, classification, progression, and prediction of AD.MethodsWe performed a survey of recent research, focusing on core biomarker candidates in AD.ResultsA number of in vivo neurochemistry and neuroimaging techniques, which can reliably assess aspects of physiology, pathology, chemistry, and neuroanatomy, hold promise as biomarkers. These neurobiologic measures appear to relate closely to pathophysiologic, neuropathologic, and clinical data, such as hyperphosphorylation of tau, amyloid beta (Aβ) metabolism, lipid peroxidation, pattern and rate of atrophy, loss of neuronal integrity, functional and cognitive decline, as well as risk of future decline. Current advances in the neuroimaging of mediotemporal, neocortical, and subcortical areas of the brain of mild cognitive impairment (MCI) and AD subjects are presented. CSF levels of Aβ42, tau, and hyperphosphorylated tau protein (p-tau) can distinguish subjects with MCI who are likely to progress to AD. They also show preclinical alterations that predict later development of early AD symptoms. Studies on plasma Aβ are not entirely consistent, but recent findings suggest that decreased plasma Aβ42 relative to Aβ40 might increase the risk of AD. Increased production of Aβ in aging is suggested by elevation of BACE1 protein and enzyme activity in the brain and CSF of subjects with MCI. CSF tau and p-tau are increased in MCI as well and show predictive value. Other biomarkers might indicate components of a cascade initiated by Aβ, such as oxidative stress or inflammation. These merit further study in MCI and earlier.ConclusionsA number of neuroimaging candidate markers are promising, such as hippocampus and entorhinal cortex volumes, basal forebrain nuclei, cortical thickness, deformation-based and voxel-based morphometry, structural and effective connectivity by using diffusion tensor imaging, tractography, and functional magnetic resonance imaging. CSF Aβ42, BACE1, total tau, and p-tau are substantially altered in MCI and clinical AD. Other interesting novel marker candidates derived from blood are being currently proposed (phase I). Biomarker discovery through proteomic approaches requires further research. Large-scale international controlled multicenter trials (such as the U.S., European, Australian, and Japanese Alzheimer’s Disease Neuroimaging Initiative and the German Dementia Network) are engaged in phase III development of the core feasible imaging and CSF biomarker candidates in AD. Biomarkers are in the process of implementation as primary outcome variables into regulatory guideline documents regarding study design and approval for compounds claiming disease modification.     

Metabolic Syndrome,Mild Cognitive Impairment,and Dementia: A Meta-Analysis of Longitudinal Studies

ObjectiveA systematic review and a meta-analysis of both clinical and population-based studies was undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement to clarify whether Metabolic Syndrome (MetS) is a risk or a protective factor for incident dementia, Alzheimer disease (AD), and vascular dementia (VaD), and whether it's involved in progression to dementia in patients affected by mild cognitive impairment (MCI).MethodsSearch terms included (“metabolic syndrome” OR “syndrome x” OR “plurimetabolic syndrome”) AND (“dementia” OR “Alzheimer disease” OR “vascular dementia” OR “mild cognitive impairment” OR “MCI”). Research was restricted to articles published in English between January 1, 2000 and August 31, 2018. No age limit was set.ResultsAt the end of the selection procedure, nine longitudinal studies were selected for the meta-analysis: six studies enrolled cognitively well-functioning participants and three studies involved MCI patients. A total of 18,313 participants aged older than 40 years with mean MetS prevalence of 22.7% were followed on average for 9.41years. A fixed model was used to estimate pooled hazard ratios and 95% confidence intervals.ConclusionNo statistically significant pooled association emerged between MetS and incident dementia and AD. MetS increased the incidence of pure VaD. MetS increased the risk of progression from MCI to dementia. Follow-up length might be a key factor in investigating these associations further. Because MetS is constituted by a set of potentially modifiable factors, further studies with longer follow-up and repeated assessment of both MetS and cognitive status are desirable to draw definite conclusions.