Hippocampal formation alterations differently contribute to autobiographic memory deficits in mild cognitive impairment and Alzheimer's disease

Autobiographical memory (AM) is part of declarative memory and includes both semantic and episodic aspects. AM deficits are among the major complaints of patients with Alzheimer's disease (AD) even in early or preclinical stages. Previous MRI studies in AD patients have showed that deficits in semantic and episodic AM are associated with hippocampal alterations. However, the question which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits of AM in individuals with mild cognitive impairment (MCI) and AD patients has not been investigated so far. Hundred and seven participants (38 AD patients, 38 MCI individuals and 31 healthy controls [HC]) underwent MRI at 3 Tesla. AM was assessed with a semi‐structured interview (E‐AGI). FreeSurfer 5.3 was used for hippocampal parcellation. Semantic and episodic AM scores were related to the volume of 5 hippocampal subfields and cortical thickness in the parahippocampal and entorhinal cortex. Both semantic and episodic AM deficits were associated with bilateral hippocampal alterations. These associations referred mainly to CA1, CA2‐3, presubiculum, and subiculum atrophy. Episodic, but not semantic AM loss was associated with cortical thickness reduction of the bilateral parahippocampal and enthorinal cortex. In MCI individuals, episodic, but not semantic AM deficits were associated with alterations of the CA1, presubiculum and subiculum. Our findings support the crucial role of CA1, presubiculum, and subiculum in episodic memory. The present results implicate that in MCI individuals, semantic and episodic AM deficits are subserved by distinct neuronal systems.     

Longitudinal trajectory of Amyloid‐related hippocampal subfield atrophy in nondemented elderly

Hippocampal atrophy and abnormal β‐Amyloid (Aβ) deposition are established markers of Alzheimer's disease (AD). Nonetheless, longitudinal trajectory of Aβ‐associated hippocampal subfield atrophy prior to dementia remains unclear. We hypothesized that elevated Aβ correlated with longitudinal subfield atrophy selectively in no cognitive impairment (NCI), spreading to other subfields in mild cognitive impairment (MCI). We analyzed data from two independent longitudinal cohorts of nondemented elderly, including global PET‐Aβ in AD‐vulnerable cortical regions and longitudinal subfield volumes quantified with a novel auto‐segmentation method (FreeSurfer v.6.0). Moreover, we investigated associations of Aβ‐related progressive subfield atrophy with memory decline. Across both datasets, we found a converging pattern that higher Aβ correlated with faster CA1 volume decline in NCI. This pattern spread to other hippocampal subfields in MCI group, correlating with memory decline. Our results for the first time suggest a longitudinal focal‐to‐widespread trajectory of Aβ‐associated hippocampal subfield atrophy over disease progression in nondemented elderly.     

White matter hyperintensities are associated with disproportionate progressive hippocampal atrophy

This study investigates relationships between white matter hyperintensity (WMH) volume, cerebrospinal fluid (CSF) Alzheimer's disease (AD) pathology markers, and brain and hippocampal volume loss. Subjects included 198 controls, 345 mild cognitive impairment (MCI), and 154 AD subjects with serial volumetric 1.5‐T MRI. CSF Aβ₄₂ and total tau were measured (n = 353). Brain and hippocampal loss were quantified from serial MRI using the boundary shift integral (BSI). Multiple linear regression models assessed the relationships between WMHs and hippocampal and brain atrophy rates. Models were refitted adjusting for (a) concurrent brain/hippocampal atrophy rates and (b) CSF Aβ₄₂ and tau in subjects with CSF data. WMH burden was positively associated with hippocampal atrophy rate in controls (P = 0.002) and MCI subjects (P = 0.03), and with brain atrophy rate in controls (P = 0.03). The associations with hippocampal atrophy rate remained following adjustment for concurrent brain atrophy rate in controls and MCIs, and for CSF biomarkers in controls (P = 0.007). These novel results suggest that vascular damage alongside AD pathology is associated with disproportionately greater hippocampal atrophy in nondemented older adults. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.     

Regionally specific changes in the hippocampal circuitry accompany progression of cerebrospinal fluid biomarkers in preclinical Alzheimer's disease

Neuropathological and in vivo brain imaging studies agree that the cornu ammonis 1 and subiculum subfields of the hippocampus are most vulnerable to atrophy in the prodromal phases of Alzheimer's disease (AD). However, there has been limited investigation of the structural integrity of the components of the hippocampal circuit, including subfields and extra‐hippocampal white matter structure, in relation to the progression of well‐accepted cerebrospinal fluid (CSF) biomarkers of AD, amyloid‐β 1‐42 (Aβ) and total‐tau (tau). We investigated these relationships in 88 aging asymptomatic individuals with a parental or multiple‐sibling familial history of AD. Apolipoprotein (APOE) ?4 risk allele carriers were identified, and all participants underwent cognitive testing, structural magnetic resonance imaging, and lumbar puncture for CSF assays of tau, phosphorylated‐tau (p‐tau) and Aβ. Individuals with a reduction in CSF Aβ levels (an indicator of amyloid accretion into neuritic plaques) as well as evident tau pathology (believed to be linked to neurodegeneration) exhibited lower subiculum volume, lower fornix microstructural integrity, and a trend towards lower cognitive score than individuals who showed only reduction in CSF Aβ. In contrast, persons with normal levels of tau showed an increase in structural MR markers in relation to declining levels of CSF Aβ. These results suggest that hippocampal subfield volume and extra‐hippocampal white matter microstructure demonstrate a complex pattern where an initial volume increase is followed by decline among asymptomatic individuals who, in some instances, may be a decade or more away from onset of cognitive or functional impairment.     

Causal structural covariance network revealing atrophy progression in Alzheimer's disease continuum

The structural covariance network (SCN) has provided a perspective on the large‐scale brain organization impairment in the Alzheimer''s Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer''s Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1‐weighted structural magnetic resonance images of the subjects. Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.     

Accelerated hippocampal atrophy rates in stable and progressive amnestic mild cognitive impairment

Studies suggest that smaller hippocampal volume predicts Alzheimer's disease (AD) in mild cognitive impairment (MCI). However, few studies have demonstrated decline rates in cognition and hippocampal volume in MCI subjects with stable clinical presentation. Furthermore, the effects of apolipoprotein E (ApoE) on the change rates of medial temporal structures and cognition in MCI are rarely investigated. Fifty-eight subjects with amnestic MCI and 20 normal aging elderly controls received annual neuropsychological and magnetic resonance imaging (MRI) assessments. Annual decline rates in neuropsychological test scores, hippocampal and amygdalar volumes were calculated. ApoE genotypes were examined. Nineteen (32.7%) MCI subjects converted to AD during an average 22.5-month follow-up period. The annual hippocampal atrophy rate was correlated with a decline in memory test scores. The presence of the ApoE ?4 allele did not affect the change rates in neuropsychological test scores and medial temporal structures volume. Compared to subjects with stable MCI (MCI-S) and normal aging, progressive MCI (MCI-P) had the highest annual decline rates in cognition and hippocampal volume. Logistic regression analysis showed that higher annual decline rates in hippocampal volume and global cognitive test scores were associated with conversion to AD. Furthermore, although MCI-S subjects had little cognitive decline, their hippocampal atrophy rates were higher than those of normal aging controls. Therefore, accelerated hippocampal atrophy rates may be an early and important presentation in MCI subjects.     

Value of CSF beta-amyloid1-42 and tau as predictors of Alzheimer's disease in patients with mild cognitive impairment

Subjects with mild cognitive impairment (MCI) are at a high risk of developing clinical Alzheimer's disease (AD). We asked to what extent the core biomarker candidates cerebro-spinal fluid (CSF) beta-amyloid(1-42) (Abeta(1-42)) and CSF tau protein concentrations predict conversion from MCI to AD. We studied 52 patients with MCI, 93 AD patients, and 10 healthy controls (HC). The MCI group was composed of 29 patients who had converted to AD during follow-up, and of 23 patients who showed no cognitive decline. CSF Abeta(1-42) and tau protein levels were assessed at baseline in all subjects, using enzyme-linked immunosorbent assays. For assessment of sensitivity and specificity, we used independently established reference values for CSF Abeta(1-42) and CSF tau. The levels of CSF tau were increased, whereas levels of Abeta(1-42) were decreased in MCI subjects. Abeta(1-42) predicted AD in converted MCI with a sensitivity of 59% and a specificity of 100% compared to HC. Tau yielded a greater sensitivity of 83% and a specificity of 90%. In a multiple Cox regression analysis within the MCI group, low baseline levels of Abeta(1-42), but not other predictor variables (tau protein, gender, age, apolipoprotein E epsilon4 carrier status, Mini Mental Status Examination score, observation time, antidementia therapy), correlated with conversion status (P<0.05). Our findings support the notion that CSF tau and Abeta(1-42) may be useful biomarkers in the early identification of AD in MCI subjects.     

Cerebrospinal fluid markers including trefoil factor 3 are associated with neurodegeneration in amyloid-positive individuals

We aimed to identify cerebrospinal fluid (CSF) biomarkers associated with neurodegeneration in individuals with and without CSF evidence of Alzheimer pathology. We investigated 287 Alzheimer''s Disease Neuroimaging Initiative (ADNI) subjects (age=74.9±6.9; 22/48/30% with Alzheimer''s disease/mild cognitive impairment/controls) with CSF multiplex analyte data and serial volumetric MRI. We calculated brain and hippocampal atrophy rates, ventricular expansion and Mini Mental State Examination decline. We used false discovery rate corrected regression analyses to assess associations between CSF variables and atrophy rates in individuals with and without amyloid pathology, adjusting in stages for tau, baseline volume, p-tau, age, sex, ApoE4 status and diagnosis. Analytes showing statistically significant independent relationships were entered into reverse stepwise analyses. Adjusting for tau, baseline volume, p-tau, age, sex and ApoE4, 4/83 analytes were significantly independently associated with brain atrophy rate, 1/83 with ventricular expansion and 2/83 with hippocampal atrophy. The strongest CSF predictor for the three atrophy measures was low trefoil factor 3 (TFF3). High cystatin C (CysC) was associated with higher whole brain atrophy and hippocampal atrophy rates. Lower levels of vascular endothelial growth factor and chromogranin A (CrA) were associated with higher whole brain atrophy. In exploratory reverse stepwise analyses, lower TFF3 was associated with higher rates of whole brain, hippocampal atrophy and ventricular expansion. Lower levels of CrA were associated with higher whole brain atrophy rate. The relationship between low TFF3 and increased hippocampal atrophy rate remained after adjustment for diagnosis. We identified a series of CSF markers that are independently associated with rate of neurodegeneration in amyloid-positive individuals. TFF3, a substrate for NOTCH processing may be an important biomarker of neurodegeneration across the Alzheimer spectrum.     

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.     

Classification of Alzheimer's disease based on hippocampal multivariate morphometry statistics

Background

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline, and mild cognitive impairment (MCI) is associated with a high risk of developing AD. Hippocampal morphometry analysis is believed to be the most robust magnetic resonance imaging (MRI) markers for AD and MCI. Multivariate morphometry statistics (MMS), a quantitative method of surface deformations analysis, is confirmed to have strong statistical power for evaluating hippocampus.

Aims

We aimed to test whether surface deformation features in hippocampus can be employed for early classification of AD, MCI, and healthy controls (HC).

Methods

We first explored the differences in hippocampus surface deformation among these three groups by using MMS analysis. Additionally, the hippocampal MMS features of selective patches and support vector machine (SVM) were used for the binary classification and triple classification.

Results

By the results, we identified significant hippocampal deformation among the three groups, especially in hippocampal CA1. In addition, the binary classification of AD/HC, MCI/HC, AD/MCI showed good performances, and area under curve (AUC) of triple-classification model achieved 0.85. Finally, positive correlations were found between the hippocampus MMS features and cognitive performances.

Conclusions

The study revealed significant hippocampal deformation among AD, MCI, and HC. Additionally, we confirmed that hippocampal MMS can be used as a sensitive imaging biomarker for the early diagnosis of AD at the individual level.     

Network interdigitations of Tau and amyloid‐beta deposits define cognitive levels in aging

Amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer''s disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aβ and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory‐based positron emission tomography (PET) analytical approaches, within and between tau and Aβ PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aβ and tau deposits, along with cognitive test scores in CN at both baseline and 2‐year follow‐up (FU). We found highly significant Aβ‐tau network integrations in AD vulnerable areas, as well as significant associations between those Aβ‐tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aβ and tau deposits in heteromodal areas of the human brain. They support a network‐based interaction between Aβ and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.     

CSF Abeta42, tau and phosphorylated tau correlate with medial temporal lobe atrophy

Cerebrospinal fluid (CSF) biomarkers and medial temporal lobe (MTL) atrophy predict the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD). We investigated the association between the CSF biomarkers and MTL atrophy and the ability of these measures to predict AD in MCI patients in the same study population. The study included 21 MCI patients of whom eight progressed to AD during the study. CSF biomarkers were measured by using ELISA method and volumes of MTL structures were assessed by magnetic resonance imaging (MRI). Abeta42 levels were lower and tau and phospho-tau levels were higher in progressive subjects. The progressive subjects had lower volumes in all MRI measures. Tau and phospho-tau correlated inversely with hippocampal volumes and left entorhinal cortex volume in the whole study group. In the stable group, tau correlated with hippocampal volumes. Abeta42 had a negative correlation whereas phospho-tau exhibited a positive correlation with left hippocampal volume in the progressive group. These results indicate that both measures may reflect the ongoing neurodegenerative process in the progressive MCI patients. However, the order of the changes in the CSF biomarkers and MTL atrophy remain unclear due to a small number of studied subjects and study design.     

Diagnostic accuracy of markers for prodromal Alzheimer's disease in independent clinical series

ObjectiveTo capitalize on data from different clinical series to compare sensitivity and specificity of individual biomarkers for predicting mild cognitive impairment (MCI) progression to Alzheimer's disease (AD).MethodsMedial temporal atrophy, cortical hypometabolism, and cerebrospinal fluid biomarkers were assessed in 18 patients with mild cognitive impairment (MCI) with prodromal AD (pAD; conversion time, 26 ± 12 months) and 18 stable MCI (sMCI) patients from the Translational Outpatient Memory Clinic cohort, as well as in 24 pAD patients (conversion time, 36 ± 12 months) and 33 sMCI patients from the Alzheimer's Disease Neuroimaging Initiative cohort. Medial temporal atrophy was measured by manual, semi-automated, and automated hippocampal volumetry; cortical hypometabolism was measured using several indices of AD-related hypometabolism pattern; and cerebrospinal fluid markers were amyloid β (Aβ)42 and total tau protein concentrations. For each biomarker, sensitivity for pAD, specificity for sMCI, and diagnostic accuracy were computed.ResultsSensitivity to predict MCI conversion to AD in the Alzheimer's Disease Neuroimaging Initiative and Translational Outpatient Memory Clinic cohorts was 79% and 94% based on Aβ42, 46% and 28% based on hippocampal volumes, 33% to 66% and 56% to 78% based on different hypometabolism indices, and 46% and 61% based on total tau levels, respectively. Specificity to exclude sMCI was 27% and 50% based on Aβ42, 76% and 94% based on hippocampal volumes, 58% to 67% and 55% to 83% based on different hypometabolism indices, and 61% and 83% based on total tau levels, respectively.ConclusionsCurrent findings suggest that Aβ42 concentrations and hippocampal volumes may be used in combination to best identify pAD.     

The Alzheimer's Disease Neuroimaging Initiative: Progress report and future plans

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.     

Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: Detecting,quantifying, and predicting

This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects. Hum Brain Mapp 35:3701–3725, 2014. © 2014 Wiley Periodicals, Inc.     

Cerebrospinal fluid beta-amyloid 1-42 concentration may predict cognitive decline in older women

Background

Low levels of cerebrospinal fluid (CSF) β‐amyloid 1–42 (Aβ42) and high total tau (T‐tau) are diagnostic for manifest Alzheimer''s disease. It is not known, however, whether these biomarkers may be risk indicators for cognitive decline in otherwise healthy older people.

Methods

The longitudinal relationship between CSF markers, Aβ42 and T‐tau, measured in 1992, and change in Mini‐Mental State Examination (ΔMMSE) score between 1992 and 2002 were investigated in 55 women (aged 70–84 years, mean (SD) MMSE score = 28.3 (1.5)), who were participants in the Prospective Population Study of Women in Gothenburg, Sweden. These women did not have dementia when they experienced lumbar puncture in 1992–3.

Results

Over the 8‐year follow‐up period, ΔMMSE (range =  +3 to −21 points) was correlated with Aβ42 (Spearman''s r = 0.40, p = 0.002), such that lower levels of Aβ42 were related to greater decline. This was also observed after excluding 4 women who developed dementia between 1992 and 2002 (Spearman''s r = 0.34, p = 0.019). A multivariate logistic regression model predicting a decline of ⩾5 points on the MMSE (observed in six women), or a risk of developing dementia over the 8‐year follow‐up period (observed in four women), including age, education, Aβ42 and T‐tau as covariates, showed that Aβ42 was the sole predictor of significant cognitive decline or dementia (OR per 100 pg/ml Aβ42 = 2.24, 95% CI 1.19 to 4.22, p = 0.013).

Conclusions

Low levels of CSF Aβ42 may predict cognitive decline among older women without dementia.Alzheimer''s disease (AD) is rapidly increasing with advancing age, with reported prevalence estimates of 30% at age 85 years, and as high as 50% at age 95 years.¹ AD is expected to reach epidemic proportions between 2010 and 2050, when the number of people with the disease is projected to be more than double. Juxtaposed against this harrowing background is the fact that risk indicators for AD in healthy older people are lacking.β‐amyloid 1–42 (Aβ42) and total tau (T‐tau) are two known biomarkers of manifest AD that are detectable in cerebrospinal fluid (CSF). Low levels of CSF Aβ42 and high levels of CSF T‐tau in cases of AD have been described in both clinical and population‐based samples.^2,3,4,5,6 Aβ42 is the 42‐amino acid fragment of amyloid precursor protein. It accumulates in the brain and is the principal component of senile plaques. Aβ42 in CSF has been suggested to reflect the deposition of β‐amyloid in senile plaques, with lower levels excreted to the CSF. T‐tau is a microtubule‐associated protein that, on hyperphosphorylation, is the primary component of neurofibrillary tangles in AD.⁷ T‐tau in CSF has been suggested to reflect neuronal and axonal degeneration in AD and/or the formation of neurofibrillary tangles.⁷ Thus, both these markers potentially reflect central pathogenic processes in a brain with AD. In addition, clinical evidence is accumulating that low levels of CSF Aβ42 and high levels of T‐tau may also be useful for predicting progression of mild cognitive impairment (MCI) to AD.⁸Despite known associations between CSF Aβ42 and T‐tau, and manifest AD, little is known about the utility of these biomarkers as risk indicators of cognitive decline in healthy older people who are representative of the population. Thus, we investigated whether lower CSF Aβ42 and higher CSF T‐tau predict cognitive decline, as measured using change in Mini‐Mental State Examination (ΔMMSE) score over 8 years, in a population‐based sample of older women aged 70–84 years.     

Diagnostic power of resting‐state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review

Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer''s disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs‐fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on “nodes” and “edges” together with structural MRI‐based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML‐based image interpretation of rs‐fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD.     

Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease,mild cognitive impairment,and elderly controls

We used a new method we developed for automated hippocampal segmentation, called the auto context model, to analyze brain MRI scans of 400 subjects from the Alzheimer's disease neuroimaging initiative. After training the classifier on 21 hand‐labeled expert segmentations, we created binary maps of the hippocampus for three age‐ and sex‐matched groups: 100 subjects with Alzheimer's disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface‐based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: P = 0.008; MCI versus AD: P = 0.001), mini‐mental state exam (MMSE) scores, and global and sum‐of‐boxes clinical dementia rating scores (CDR; all P < 0.0001, corrected). Right but not left hippocampal atrophy was associated with geriatric depression scores (P = 0.004, corrected); hippocampal atrophy was not associated with subsequent decline in MMSE and CDR scores, educational level, ApoE genotype, systolic or diastolic blood pressure measures, or homocysteine. We gradually reduced sample sizes and used false discovery rate curves to examine the method's power to detect associations with diagnosis and cognition in smaller samples. Forty subjects were sufficient to discriminate AD from normal and correlate atrophy with CDR scores; 104, 200, and 304 subjects, respectively, were required to correlate MMSE with atrophy, to distinguish MCI from normal, and MCI from AD. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.     

Plasma tau as a window to the brain—negative associations with brain volume and memory function in mild cognitive impairment and early alzheimer's disease

Neurofibrillary tangles are associated with cognitive dysfunction, and hippocampal atrophy with increased CSF tau markers. However, the plasma tau levels of Alzheimer's disease (AD) have not been well studied. We investigated plasma tau by using an immunomagnetic reduction assay in 20 patients with mild cognitive impairment (MCI) due to AD, 10 early AD dementia, and 30 healthy elders (HE). All received a 3D‐brain MRI scan and a set of cognitive function test. We explored their relationships with both brain structure and cognitive functions. Images were analyzed to determine the brain volumes and gray matter densities. Patients with MCI or early AD had significantly increased plasma tau levels compared with HE. Plasma tau levels were negatively associated with the performance of logical memory, visual reproduction, and verbal fluency; also negatively associated with volume of total gray matter, hippocampus, amygdala; and gray matter densities of various regions. Regression analyses indicated that logical memory explained 0.394 and hippocampus volume predicted .608 of the variance of plasma tau levels, both P < 0.001. Education years were negatively associated with the gray matter densities of the supramarginal (r = ?0.407), middle temporal gyrus (r = ?0.40) and precuneus (r = ?0.377; all P < 0.05) in HE; and negatively associated with plasma tau levels in patients (r = ?0.626). We propose that plasma tau may serve as a window to both structure and function of the brain. Higher education is a protective factor against AD and is associated with lower plasma tau levels in patients. Hum Brain Mapp 35:3132–3142, 2014. © 2013 Wiley Periodicals, Inc.     

The new Alzheimer’s criteria in a naturalistic series of patients with mild cognitive impairment

To test the validity of the new diagnostic criteria for Alzheimer’s disease (AD) in a naturalistic series of patients with mild cognitive impairment (MCI). Ninety consecutive MCI patients were enrolled in a longitudinal study on the natural history of cognitive impairment. Medial temporal (MT) atrophy on MRI was defined as hippocampal volume below the fifth percentile of the distribution in healthy elders, abnormal CSF was based on Sjogren’s cutoffs for Abeta42 and tau, and temporoparietal hypometabolism on 18F-FDG PET based on Herholz’s t sum score. Patients were followed clinically to detect conversion to AD (MCI-AD), non-AD dementia (MCI-nAD), or no conversion (MCI-NC). The 24 MCI-AD and 15 MCI-nAD patients had sociodemographic, clinical, and neuropsychological baseline features similar to the 51 MCI-NC patients. All MCI patients with MT atrophy converted to AD, as did all those with abnormal CSF, but only 48 and 35% of those without MT atrophy or abnormal CSF converted (p on logrank test = 0.0007 and 0.001). Prediction of AD conversion was enhanced when positivity to either MT atrophy or abnormal CSF was considered, with only 15% of those MCI patients negative on both converting to AD (p < 0.0005). Markers were not predictive of non-AD dementia conversion. The accuracy of either MT atrophy or abnormal CSF in discriminating MCI-AD from MCI-NC was good (AUC 0.82, 95% CI 0.70–0.95). MT atrophy and abnormal CSF are the single most robust predictors of conversion to AD in MCI patients, and their combination enhances prediction. AD markers are not predictive of conversion to non-AD dementia.