MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers

Sharing data in the global alzheimer's association interactive network

The Global Alzheimer's Association Interactive Network (GAAIN) aims to be a shared network of research data, analysis tools, and computational resources for studying the causes of Alzheimer's disease. Central to its design are policies that honor data ownership, prevent unauthorized data distribution, and respect the boundaries of contributing institutions. The results of data queries are displayed in graphs and summary tables, which protects data ownership while providing sufficient information to view trends in aggregated data and discover new data sets. In this article we report on our progress in sharing data through the integration of geographically-separated and independently-operated Alzheimer's disease research studies around the world.

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

White matter signal abnormality quality differentiates mild cognitive impairment that converts to Alzheimer's disease from nonconverters

The objective of this study was to assess how longitudinal change in the quantity and quality of white matter signal abnormalities (WMSAs) contributes to the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The Mahalanobis distance of WMSA from normal-appearing white matter using T1-, T2-, and proton density-weighted MRI was defined as a quality measure for WMSA. Cross-sectional analysis of WMSA volume in 104 cognitively healthy older adults, 116 individuals with MCI who converted to AD within 3 years (mild cognitive impairment converter [MCI-C]), 115 individuals with MCI that did not convert in that time (mild cognitive impairment nonconverter [MCI-NC]), and 124 individuals with AD from the Alzheimer's Disease Neuroimaging Initiative revealed that WMSA volume was substantially greater in AD relative to the other groups but did not differ between MCI-NC and MCI-C. Longitudinally, MCI-C exhibited faster WMSA quality progression but not volume compared with matched MCI-NC beginning 18 months before MCI-C conversion to AD. The strongest difference in rate of change was seen in the time period starting 6 months before MCI-C conversion to AD and ending 6 months after conversion (p < 0.001). The relatively strong effect in this time period relative to AD conversion in the MCI-C was similar to the relative rate of change in hippocampal volume, a traditional imaging marker of AD pathology. These data demonstrate changes in white matter tissue properties that occur within WMSA in individuals with MCI that will subsequently obtain a clinical diagnosis of AD within 18 months. Individuals with AD have substantially greater WMSA volume than all MCI suggesting that there is a progressive accumulation of WMSA with progressive disease severity, and that quality change predates changes in this total volume. Given the timing of the changes in WMSA tissue quality relative to the clinical diagnosis of AD, these findings suggest that WMSAs are a critical component for this conversion and are a critical component of this clinical syndrome.

How can neuroimaging facilitate the diagnosis and stratification of patients with psychosis?

Early diagnosis and treatment of patients with psychosis are associated with improved outcome in terms of future functioning, symptoms and treatment response. Identifying neuroimaging biomarkers for illness onset and treatment response would lead to immediate clinical benefits. In this review we discuss if neuroimaging may be utilised to diagnose patients with psychosis, predict those who will develop the illness in those at high risk, and stratify patients. State-of-the-art developments in the field are critically examined including multicentre studies, longitudinal designs, multimodal imaging and machine learning as well as some of the challenges in utilising future neuroimaging biomarkers in clinical trials. As many of these developments are already being applied in neuroimaging studies of Alzheimer's disease, we discuss what lessons have been learned from this field and how they may be applied to research in psychosis.

Imaging biomarkers associated with cognitive decline: a review

In evaluating disease changes, it is critical to have measurements that are sensitive, specific, and reliable. Cognitive decline, particularly in the context of Alzheimer's disease, is an area that has attracted numerous recent studies, and the proposed biomarkers used in these investigations need to be validated. In this review, we highlight studies with important implications about the role of imaging biomarkers in cognitive decline and dementia as well as in distinguishing preclinical dementia before evidence of cognitive decline. Structural changes determined on cross-sectional and longitudinal magnetic resonance imaging provide early prediction of dementia, particularly when combined with other measures. Molecular imaging using positron emission tomography and single photon emission computed tomography tracers quantify the presence or activity of receptors, transporters, enzymes, metabolic pathways, and proteins. The newest developments in molecular imaging are described, and methods are compared. Distinguishing features of imaging biomarkers among dementias and the spectrum of preclinical Alzheimer's disease, mild cognitive impairment, and Alzheimer's disease are described. Appropriate use criteria for positron emission tomography with amyloid tracers are delineated. Although these efforts are still in the early phase of development, there is great promise for further development in structural magnetic resonance imaging and positron emission tomography technologies.

T1rho MRI and CSF biomarkers in diagnosis of Alzheimer's disease

In the current study, we have evaluated the performance of magnetic resonance (MR) T1rho (T_1ρ) imaging and CSF biomarkers (T-tau, P-tau and Aβ-42) in characterization of Alzheimer's disease (AD) patients from mild cognitive impairment (MCI) and control subjects. With informed consent, AD (n = 27), MCI (n = 17) and control (n = 17) subjects underwent a standardized clinical assessment and brain MRI on a 1.5-T clinical-scanner. T_1ρ images were obtained at four different spin-lock pulse duration (10, 20, 30 and 40 ms). T_1ρ maps were generated by pixel-wise fitting of signal intensity as a function of the spin-lock pulse duration. T_1ρ values from gray matter (GM) and white matter (WM) of medial temporal lobe were calculated. The binary logistic regression using T_1ρ and CSF biomarkers as variables was performed to classify each group. T_1ρ was able to predict 77.3% controls and 40.0% MCI while CSF biomarkers predicted 81.8% controls and 46.7% MCI. T_1ρ and CSF biomarkers in combination predicted 86.4% controls and 66.7% MCI. When comparing controls with AD, T_1ρ predicted 68.2% controls and 73.9% AD, while CSF biomarkers predicted 77.3% controls and 78.3% for AD. Combination of T_1ρ and CSF biomarkers improved the prediction rate to 81.8% for controls and 82.6% for AD. Similarly, on comparing MCI with AD, T_1ρ predicted 35.3% MCI and 81.9% AD, whereas CSF biomarkers predicted 53.3% MCI and 83.0% AD. Collectively CSF biomarkers and T_1ρ were able to predict 59.3% MCI and 84.6% AD. On receiver operating characteristic analysis T_1ρ showed higher sensitivity while CSF biomarkers showed greater specificity in delineating MCI and AD from controls. No significant correlation between T_1ρ and CSF biomarkers, between T_1ρ and age, and between CSF biomarkers and age was observed. The combined use of T_1ρ and CSF biomarkers have promise to improve the early and specific diagnosis of AD. Furthermore, disease progression form MCI to AD might be easily tracked using these two parameters in combination.

•

Increased T1rho was observed in MCI and AD compared to controls.

•

Increased T-tau and P-tau and decreased Aβ1-42 were observed in MCI and AD.

•

Combined biomarkers have promise to improve early and specific diagnosis of AD.

•

MCI to AD progression might be tracked using these two biomarkers in combination.

Robustness of automated hippocampal volumetry across magnetic resonance field strengths and repeat images

BACKGROUND

Low HCV has recently been qualified by the European Medicines Agency as a biomarker for enrichment of clinical trials in predementia stages of Alzheimer's disease. For automated methods to meet the necessary regulatory requirements, it is essential they be standardized and their performance be well characterized.

METHODS

The within-image and between-field strength reproducibility of automated hippocampal volumetry using the Learning Embeddings for Atlas Propagation (or LEAP) algorithm was assessed on 153 Alzheimer's Disease Neuroimaging Initiative subjects.

RESULTS

Tests/retests at 1.5 T and 3 T, and a comparison between 1.5 T and 3 T, yielded average unsigned variabilities in HCVs of 1.51%, 1.52%, and 2.68%. A small bias between field strengths (mean signed difference, 1.17%; standard deviation, 3.07%) was observed.

CONCLUSIONS

The measured reproducibility characteristics confirm the suitability of using automated magnetic resonance imaging analyses to assess HCVs quantitatively and to represent a fundamental characterization that is critical to meet the regulatory requirements for using hippocampal volumetry in clinical trials and health care.

The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and Alzheimer's disease

We proposed a diffeomorphometry-based statistical pipeline to study the regional shape change rates of the bilateral hippocampus, amygdala, and ventricle in mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared with healthy controls (HC), using sequential magnetic resonance imaging (MRI) scans of 713 subjects (3,123 scans in total). The subgroup shape atrophy rates of the bilateral hippocampus and amygdala, as well as the expansion rates of the bilateral ventricles, for a majority of vertices were found to follow the order of AD>MCI>HC. The bilateral hippocampus and the left amygdala were subsegmented into multiple functionally meaningful subregions with the help of high-field MRI scans. The largest group differences in localized shape atrophy rates on the hippocampus were found to occur in CA1, followed by subiculum, CA2, and finally CA3/dentate gyrus, which is consistent with the neurofibrillary tangle accumulation trajectory. Highly nonuniform group differences were detected on the amygdala; vertices on the core amygdala (basolateral and lateral nucleus) revealed much larger atrophy rates, whereas those on the noncore amygdala (mainly centromedial) displayed similar or even smaller atrophy rates in AD relative to HC. The temporal horns of the ventricles were observed to have the largest localized ventricular expansion rate differences; with the AD group showing larger localized expansion rates on the anterior horn and the body part of the ventricles as well. Significant correlations were observed between the localized shape change rates of each of these six structures and the cognitive deterioration rates as quantified by the Alzheimer's Disease Assessment Scale-Cognitive Behavior Section increase rate and the Mini Mental State Examination decrease rate.

Association of Alzheimer's disease GWAS loci with MRI markers of brain aging

Whether novel risk variants of Alzheimer's disease (AD) identified through genome-wide association studies also influence magnetic resonance imaging-based intermediate phenotypes of AD in the general population is unclear. We studied association of 24 AD risk loci with intracranial volume, total brain volume, hippocampal volume (HV), white matter hyperintensity burden, and brain infarcts in a meta-analysis of genetic association studies from large population-based samples (N = 8175-11,550). In single-SNP based tests, AD risk allele of APOE (rs2075650) was associated with smaller HV (p = 0.0054) and CD33 (rs3865444) with smaller intracranial volume (p = 0.0058). In gene-based tests, there was associations of HLA-DRB1 with total brain volume (p = 0.0006) and BIN1 with HV (p = 0.00089). A weighted AD genetic risk score was associated with smaller HV (beta ± SE = -0.047 ± 0.013, p = 0.00041), even after excluding the APOE locus (p = 0.029). However, only association of AD genetic risk score with HV, including APOE, was significant after multiple testing correction (including number of independent phenotypes tested). These results suggest that novel AD genetic risk variants may contribute to structural brain aging in nondemented older community persons.

Computerized touch-panel screening tests for detecting mild cognitive impairment and Alzheimer's disease

OBJECTIVE

The increasing population of elderly people in Japan has accelerated the demand for a simple screening test to detect cognitive and affective declines in mild cognitive impairment (MCI) and the early stage of dementia. Methods We compared the cognitive and affective functions, activities of daily living (ADLs) and the results of four computerized touch-panel screening tests in 41 MCI subjects, 124 patients with Alzheimer's disease (AD) and 75 age- and gender-matched normal controls.

RESULTS

All computerized touch-panel games were successfully used to discriminate the AD patients from the normal controls (** p<0.01). Although there were no differences in the findings of the conventional cognitive assessments, the results of the flipping cards game were significantly different (** p<0.01) between the normal controls (19.3 ± 9.5 sec) and MCI subjects (30.9 ± 18.4 sec). Three conventional affective assessments, the ADL score, Abe's behavioral and psychological symptoms of dementia (ABS) (** p<0.01) and the apathy scale (AS) (* p<0.05), could be used to discriminate the MCI subjects (ABS, 0.9 ± 1.5; AS, 12.8 ± 5.9) from the normal controls (ABS, 0.1 ± 0.4; AS, 8.9 ± 5.3).

CONCLUSION

In the present study, all four touch-panel screening tests could be employed to discriminate AD patients from normal controls, whereas only the flipping cards game was effective for distinguishing MCI subjects from normal controls. Therefore, this novel touch-panel screening test may be a more sensitive tool for detecting MCI subjects among elderly patients.

The association between cardiovascular risk factors and progressive hippocampus volume loss in persons with Alzheimer's disease

BACKGROUND

We performed the current study to test the hypothesis that the aggregation of cardiovascular risk factors in patients with Alzheimer's disease (AD) was associated with a higher rate of volume loss in the hippocampus and progression of cognitive deficits.

METHODS

A total of 103 persons with AD were included (65 men and 38 women, average age of 74.5 ± 0.8 years). All participants underwent 1.5 T structural magnetic resonance imaging (MRI), at specified intervals (6 or 12 months) for 2-3 years. We determined the rates of hippocampus, whole brain, ventricle, middle temporal lobe, fusiform, and entorhinal volume loss (in cubic millimeter/year) for all patients with AD, separately for 0-6 months, 6-12 months and 0-12, 12-18 and 18-24 months scan intervals.

RESULTS

There were significant differences in Mini-Mental State Examination (MMSE) (p = 0.001) and Alzheimer's disease Assessment Scale (ADAS) (p = 0.01) scale scores between persons with and without hypertension and in MMSE (p = 0.04) and Clinical Dementia Rating (CDR) (p = 0.008) scale scores between persons with and without hyperlipidemia. There were no significant differences in MMSE, ADAS, and CDR scales scores between persons with and without diabetes mellitus and cigarette smoking. There were no significant differences in regional brain volume loss in those with or without cardiovascular risk factors.

CONCLUSIONS

Cardiovascular risk factors have a significant influence on the progression of cognitive deficits in patients with AD. The progression of cognitive deficits in patients with AD is not mediated by progressive hippocampal volume loss.

Integration of multiscale dendritic spine structure and function data into systems biology models

Comprising 10¹¹ neurons with 10¹⁴ synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement.

Genetic modification of the relationship between phosphorylated tau and neurodegeneration

BACKGROUND

A subset of individuals present at autopsy with the pathologic features of Alzheimer's disease having never manifest the clinical symptoms. We sought to identify genetic factors that modify the relationship between phosphorylated tau (PTau) and dilation of the lateral inferior ventricles.

METHODS

We used data from 700 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). A genome-wide association study approach was used to identify PTau × single nucleotide polymorphism (SNP) interactions. Variance explained by these interactions was quantified using hierarchical linear regression.

RESULTS

Five SNP × PTau interactions passed a Bonferroni correction, one of which (rs4728029, POT1, 2.6% of variance) was consistent across ADNI-1 and ADNI-2/GO subjects. This interaction also showed a trend-level association with memory performance and levels of interleukin-6 receptor.

CONCLUSIONS

Our results suggest that rs4728029 modifies the relationship between PTau and both ventricular dilation and cognition, perhaps through an altered neuroinflammatory response.

Genetics pathway-based imaging approaches in Chinese Han population with Alzheimer's disease risk

The tau hypothesis has been raised with regard to the pathophysiology of Alzheimer's disease (AD). Mild cognitive impairment (MCI) is associated with a high risk for developing AD. However, no study has directly examined the brain topological alterations based on combined effects of tau protein pathway genes in MCI population. Forty-three patients with MCI and 30 healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) in Chinese Han, and a tau protein pathway-based imaging approaches (7 candidate genes: 17 SNPs) were used to investigate changes in the topological organisation of brain activation associated with MCI. Impaired regional activation is related to tau protein pathway genes (5/7 candidate genes) in patients with MCI and likely in topologically convergent and divergent functional alterations patterns associated with genes, and combined effects of tau protein pathway genes disrupt the topological architecture of cortico-cerebellar loops. The associations between the loops and behaviours further suggest that tau protein pathway genes do play a significant role in non-episodic memory impairment. Tau pathway-based imaging approaches might strengthen the credibility in imaging genetic associations and generate pathway frameworks that might provide powerful new insights into the neural mechanisms that underlie MCI.

Association between cell-bound blood amyloid-β(1-40) levels and hippocampus volume

INTRODUCTION

The identification of early, preferably presymptomatic, biomarkers and true etiologic factors for Alzheimer's disease (AD) is the first step toward establishing effective primary and secondary prevention programs. Consequently, the search for a relatively inexpensive and harmless biomarker for AD continues. Despite intensive research worldwide, to date there is no definitive plasma or blood biomarker indicating high or low risk of conversion to AD.

METHODS

Magnetic resonance imaging and β-amyloid (Aβ) levels in three blood compartments (diluted in plasma, undiluted in plasma and cell-bound) were measured in 96 subjects (33 with mild cognitive impairment, 14 with AD and 49 healthy controls). Pearson correlations were completed between 113 regions of interest (ROIs) (45 subcortical and 68 cortical) and Aβ levels. Pearson correlation analyses adjusted for the covariates age, sex, apolipoprotein E (ApoE), education and creatinine levels showed neuroimaging ROIs were associated with Aβ levels. Two statistical methods were applied to study the major relationships identified: (1) Pearson correlation with phenotype added as a covariate and (2) a meta-analysis stratified by phenotype. Neuroimaging data and plasma Aβ measurements were taken from 630 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects to be compared with our results.

RESULTS

The left hippocampus was the brain region most correlated with Aβ(1-40) bound to blood cell pellets (partial correlation (pcor) = -0.37, P = 0.0007) after adjustment for the covariates age, gender and education, ApoE and creatinine levels. The correlation remained almost the same (pcor = -0.35, P = 0.002) if phenotype is also added as a covariate. The association between both measurements was independent of cognitive status. The left hemisphere entorhinal cortex also correlated with Aβ(1-40) cell-bound fraction. AB128 and ADNI plasma Aβ measurements were not related to any brain morphometric measurement.

CONCLUSIONS

Association of cell-bound Aβ(1-40) in blood with left hippocampal volume was much stronger than previously observed in Aβ plasma fractions. If confirmed, this observation will require careful interpretation and must be taken into account for blood amyloid-based biomarker development.

Reliability of brain volume measurements: a test-retest dataset

Evaluation of neurodegenerative disease progression may be assisted by quantification of the volume of structures in the human brain using magnetic resonance imaging (MRI). Automated segmentation software has improved the feasibility of this approach, but often the reliability of measurements is uncertain. We have established a unique dataset to assess the repeatability of brain segmentation and analysis methods. We acquired 120 T1-weighted volumes from 3 subjects (40 volumes/subject) in 20 sessions spanning 31 days, using the protocol recommended by the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject was scanned twice within each session, with repositioning between the two scans, allowing determination of test-retest reliability both within a single session (intra-session) and from day to day (inter-session). To demonstrate the application of the dataset, all 3D volumes were processed using FreeSurfer v5.1. The coefficient of variation of volumetric measurements was between 1.6% (caudate) and 6.1% (thalamus). Inter-session variability exceeded intra-session variability for lateral ventricle volume (P<0.0001), indicating that ventricle volume in the subjects varied between days.

Physical activity and cognitive trajectories in cognitively normal adults: the adult children study

Increased physical activity may protect against cognitive decline, the primary symptom of Alzheimer disease. In this study, we examined the relationship between physical activity and trajectories of cognitive functioning over serial assessments. Cognitively normal (Clinical Dementia Rating 0) middle-aged and older adults (N=173; mean age, 60.7 ± 7.8 y) completed a self-report measure of physical activity and a battery of standard neuropsychological tests assessing processing speed, attention, executive functioning, and verbal memory. At baseline, individuals with higher physical activity levels performed better on tests of episodic memory and visuospatial functioning. Over subsequent follow-up visits, higher physical activity was associated with small performance gains on executive functioning and working memory tasks in participants with one or more copies of the apolipoprotein ε4 allele (APOE4). In APOE4 noncarriers, slopes of cognitive performance over time were not related to baseline physical activity. Our results suggest that cognitively normal older adults who report higher levels of physical activity may have slightly better cognitive performance, but the potential cognitive benefits of higher levels of physical activity over time may be most evident in individuals at genetic risk for Alzheimer disease.

Correlation of hippocampal volume and cognitive performances in patients with either mild cognitive impairment or Alzheimer's disease

OBJECTIVE

To evaluate hippocampal volume changes and neuropsychological performances in patients with either amnestic mild cognitive impairment (aMCI) or Alzheimer's disease (AD).

METHODS

Thirty-eight AD dementia, 22 aMCI patients, and 20 healthy controls were enrolled. Bilateral hippocampal volume was measured concurrently with mini-mental state examination (MMSE), auditory verbal learning test (AVLT), Boston naming test (BNT), and activities of daily living (ADL) test. Baseline and two additional follow-up examinations were conducted.

RESULTS

Baseline hippocampal volumes were significantly smaller in AD group than that in aMCI and control groups. MMSE, AVLT, ADL, and BNT scores for the AD group were significantly different from that of both aMCI and control groups. Baseline hippocampal volumes were positively correlated with MMSE and AVLT scores in AD and aMCI patients. At follow-up, left hippocampal volume loss was positively correlated with decreased MMSE and AVLT scores both in AD and aMCI groups, while right hippocampal volume loss was positively associated with decreased AVLT performance only in AD group. Increased ADL and decreased BNT scores were positively associated with left hippocampal volume reduction only in the AD group.

CONCLUSIONS

Current findings provide evidence of a close relationship between hippocampal volume and cognitive performances in patients with AD and aMCI, both at baseline and over follow-up.

An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features

Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accuracy to differentiate patients with Alzheimer's disease (AD) from normal elderly controls. Several forms of anatomical features, such as cortical volume, shape, and thickness, have demonstrated discriminative capability. These approaches rely on accurate non-linear image transformation, which could invite several nuisance factors, such as dependency on transformation parameters and the degree of anatomical abnormality, and an unpredictable influence of residual registration errors. In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical data. The method employed gray-level invariant features, which were extracted from linearly transformed images, to characterize AD-specific anatomical features. The intensity information from a disease-specific spatial masking, which was linearly registered to each patient, was used to capture the anatomical features. We implemented a two-step feature selection for anatomic recognition. First, a statistic-based feature selection was implemented to extract AD-related anatomical features while excluding non-significant features. Then, seven knowledge-based ROIs were used to capture the local discriminative powers of selected voxels within areas that were sensitive to AD or mild cognitive impairment (MCI). The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC) using a support vector machine. The statistic-based feature selection, together with the knowledge-based masks, provided a promising solution for capturing anatomical features of the brain efficiently. For the analysis of clinical populations, which are inherently heterogeneous, this approach could stratify the large amount of data rapidly and could be combined with more detailed subsequent analyses based on non-linear transformation.

A data-driven model of biomarker changes in sporadic Alzheimer's disease

We demonstrate the use of a probabilistic generative model to explore the biomarker changes occurring as Alzheimer's disease develops and progresses. We enhanced the recently introduced event-based model for use with a multi-modal sporadic disease data set. This allows us to determine the sequence in which Alzheimer's disease biomarkers become abnormal without reliance on a priori clinical diagnostic information or explicit biomarker cut points. The model also characterizes the uncertainty in the ordering and provides a natural patient staging system. Two hundred and eighty-five subjects (92 cognitively normal, 129 mild cognitive impairment, 64 Alzheimer's disease) were selected from the Alzheimer's Disease Neuroimaging Initiative with measurements of 14 Alzheimer's disease-related biomarkers including cerebrospinal fluid proteins, regional magnetic resonance imaging brain volume and rates of atrophy measures, and cognitive test scores. We used the event-based model to determine the sequence of biomarker abnormality and its uncertainty in various population subgroups. We used patient stages assigned by the event-based model to discriminate cognitively normal subjects from those with Alzheimer's disease, and predict conversion from mild cognitive impairment to Alzheimer's disease and cognitively normal to mild cognitive impairment. The model predicts that cerebrospinal fluid levels become abnormal first, followed by rates of atrophy, then cognitive test scores, and finally regional brain volumes. In amyloid-positive (cerebrospinal fluid amyloid-β1-42 < 192 pg/ml) or APOE-positive (one or more APOE4 alleles) subjects, the model predicts with high confidence that the cerebrospinal fluid biomarkers become abnormal in a distinct sequence: amyloid-β1-42, phosphorylated tau, total tau. However, in the broader population total tau and phosphorylated tau are found to be earlier cerebrospinal fluid markers than amyloid-β1-42, albeit with more uncertainty. The model's staging system strongly separates cognitively normal and Alzheimer's disease subjects (maximum classification accuracy of 99%), and predicts conversion from mild cognitive impairment to Alzheimer's disease (maximum balanced accuracy of 77% over 3 years), and from cognitively normal to mild cognitive impairment (maximum balanced accuracy of 76% over 5 years). By fitting Cox proportional hazards models, we find that baseline model stage is a significant risk factor for conversion from both mild cognitive impairment to Alzheimer's disease (P = 2.06 × 10(-7)) and cognitively normal to mild cognitive impairment (P = 0.033). The data-driven model we describe supports hypothetical models of biomarker ordering in amyloid-positive and APOE-positive subjects, but suggests that biomarker ordering in the wider population may diverge from this sequence. The model provides useful disease staging information across the full spectrum of disease progression, from cognitively normal to mild cognitive impairment to Alzheimer's disease. This approach has broad application across neurodegenerative disease, providing insights into disease biology, as well as staging and prognostication.

Learning in Alzheimer's disease is facilitated by social interaction

Seminal work in Gary Van Hoesen's laboratory at Iowa in the early 1980s established that the hallmark neuropathology of Alzheimer's disease (AD; neurofibrillary tangles) had its first foothold in specific parts of the hippocampal formation and entorhinal cortex, effectively isolating the hippocampus from much of its input and output and causing the distinctive impairment of new learning that is the leading early characteristic of the disease (Hyman et al., 1984). The boundaries and conditions of the anterograde memory defect in patients with AD have been a topic of intense research interest ever since (e.g., Graham and Hodges, 1977; Nestor et al., 2006). For example, it has been shown that patients with AD may acquire some new semantic information through methods such as errorless learning, but learning under these conditions is typically slow and inefficient. Drawing on a learning paradigm (a collaborative referencing task) that was previously shown to induce robust and enduring learning in patients with hippocampal amnesia, we investigated whether this task would be effective in promoting new learning in patients with AD. We studied five women with early-stage AD and 10 demographically matched healthy comparison participants, each interacting with a familiar communication partner. AD pairs displayed significant and enduring learning across trials, with increased accuracy and decreased time to complete trials, in a manner indistinguishable from healthy comparison pairs, resulting in efficient and economical communication. The observed learning here most likely draws on neural resources outside the medial temporal lobes. These interactive communication sessions provide a potent learning environment with significant implications for memory intervention.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimer's disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers

The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.

APOE ε4 is associated with disproportionate progressive hippocampal atrophy in AD

Objectives

To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates.

Methods

MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into “progressors” (MCI-P) if diagnosed with AD within 36 months or “stable” (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated.

Results

Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P.

Conclusions

These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD.

Common genetic variation of the APOE gene and personality

BACKGROUND

A recent study yielded first evidence that personality plays an important role in explaining the influence of a prominent APOE polymorphism on cognitive decline and Alzheimer's disease (AD) in elderly humans. Adding to this, two earlier studies examined this polymorphism in the context of individual differences in temperament traits in young humans with mixed results. In general, research linking the prominent APOE ϵ2, ϵ3 and ϵ4 variants and human personality is of special interest, because an influence of this gene and its prominent polymorphism on personality in young adulthood could be of diagnostic value to predict AD and its development in later years.

RESULTS

In the present study N = 531 participants provided buccal swabs and filled in a self-report inventory measuring the Five Factor Model of Personality. No association between common genetic variations of the APOE gene (in detail the genotypes ϵ3/ϵ3, ϵ2/ϵ3 and ϵ3/ϵ4) and personality could be observed. The remaining genotypes, including the high risk constellation ϵ4/ϵ4 for AD, were too seldom to be tested.

CONCLUSIONS

In sum, the present study yielded no evidence for a direct link between common genetic variants of the APOE gene and personality in young adulthood.

APOE-epsilon4 and aging of medial temporal lobe gray matter in healthy adults older than 50 years

Atrophy of the hippocampus and surrounding temporal regions occurs in Alzheimer's disease (AD). APOE ε4, the major genetic risk factor for late-onset AD, has been associated with smaller volume in these regions before amyloidosis can be detected by AD biomarkers. To examine APOE ε4 effects in relation to aging, we performed a longitudinal magnetic resonance imaging study involving cognitively normal adults (25 APOE ε4 carriers and 31 ε3 homozygotes), initially aged 51-75 years. We used growth curve analyses, which can provide information about APOE ε4-related differences initially and later in life. Hippocampal volume was the primary outcome; nearby medial temporal regions were secondary outcomes. Brain-derived neurotrophic factor, val66met was a secondary covariate. APOE ε4 carriers had significantly smaller initial hippocampal volumes than ε3 homozygotes. Rate of hippocampal atrophy was not greater in the APOE ε4 group, although age-related atrophy was detected in the overall sample. The findings add to the growing evidence that effects of APOE ε4 on hippocampal size begin early in life, underscoring the importance of early interventions to increase reserve.

Effect of APOE genotype status on targeted clinical trials outcomes and efficiency in dementia and mild cognitive impairment resulting from Alzheimer's disease

BACKGROUND

The apolipoprotein E (APOE) ε4 genotype has been recommended as a potential inclusion or exclusion criterion in targeted clinical trials for Alzheimer's disease (AD) and mild cognitive impairment (MCI) resulting from AD, and has been implemented in trials of immunotherapeutic agents.

METHODS

We tested this recommendation with clinical trial simulations using participants from a meta-database of 19 studies to create trial samples with APOE ε4 proportions ranging from 0% (all noncarriers) to 100% (all carriers). For each percentage of APOE ε4 carriers, we resampled the database randomly for 1000 trials for each trial scenario, planning for 18- or 24-month trials with samples from 50 to 400 patients per treatment or placebo group, up to 40% dropouts, and outcomes on the Alzheimer's Disease Assessment Scale, cognitive subscale (ADAS-cog) with effect sizes from 0.15 to 0.75, and calculated statistical power.

RESULTS

Enrichment of clinical trial participants based on APOE ε4 carrier status resulted in minimal increases in power compared with enrolling participants with the APOE ε3 genotype only or enrolling patients without regard to APOE genotype. Increased screening requirements to enhance the sample would offset gains in power.

CONCLUSIONS

Although samples enriched for APOE ε4 carriers in AD or MCI clinical trials showed slightly more cognitive impairment and greater decline using the number APOE ε4 alleles as an inclusion criterion most likely would not result in more efficient trials, and trials would take longer because fewer patients would be available. The APOE ε4/εX (where X = 2, 3 or 4) genotype could be useful, however, as an explanatory variable or covariate if warranted by a drug's action.

Sex modifies the APOE-related risk of developing Alzheimer disease

OBJECTIVE

The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer disease (AD). Case-control studies suggest the APOE4 link to AD is stronger in women. We examined the APOE4-by-sex interaction in conversion risk (from healthy aging to mild cognitive impairment (MCI)/AD or from MCI to AD) and cerebrospinal fluid (CSF) biomarker levels.

METHODS

Cox proportional hazards analysis was used to compute hazard ratios (HRs) for an APOE-by-sex interaction on conversion in controls (n = 5,496) and MCI patients (n = 2,588). The interaction was also tested in CSF biomarker levels of 980 subjects from the Alzheimer's Disease Neuroimaging Initiative.

RESULTS

Among controls, male and female carriers were more likely to convert to MCI/AD, but the effect was stronger in women (HR = 1.81 for women; HR = 1.27 for men; interaction: p = 0.011). The interaction remained significant in a predefined subanalysis restricted to APOE3/3 and APOE3/4 genotypes. Among MCI patients, both male and female APOE4 carriers were more likely to convert to AD (HR = 2.16 for women; HR = 1.64 for men); the interaction was not significant (p = 0.14). In the subanalysis restricted to APOE3/3 and APOE3/4 genotypes, the interaction was significant (p = 0.02; HR = 2.17 for women; HR = 1.51 for men). The APOE4-by-sex interaction on biomarker levels was significant for MCI patients for total tau and the tau-to-Aβ ratio (p = 0.009 and p = 0.02, respectively; more AD-like in women).

INTERPRETATION

APOE4 confers greater AD risk in women. Biomarker results suggest that increased APOE-related risk in women may be associated with tau pathology. These findings have important clinical implications and suggest novel research approaches into AD pathogenesis.

A focus on structural brain imaging in the Alzheimer's disease neuroimaging initiative

In recent years, numerous laboratories and consortia have used neuroimaging to evaluate the risk for and progression of Alzheimer's disease (AD). The Alzheimer's Disease Neuroimaging Initiative is a longitudinal, multicenter study that is evaluating a range of biomarkers for use in diagnosis of AD, prediction of patient outcomes, and clinical trials. These biomarkers include brain metrics derived from magnetic resonance imaging (MRI) and positron emission tomography scans as well as metrics derived from blood and cerebrospinal fluid. We focus on Alzheimer's Disease Neuroimaging Initiative studies published between 2011 and March 2013 for which structural MRI was a major outcome measure. Our main goal was to review key articles offering insights into progression of AD and the relationships of structural MRI measures to cognition and to other biomarkers in AD. In Supplement 1, we also discuss genetic and environmental risk factors for AD and exciting new analysis tools for the efficient evaluation of large-scale structural MRI data sets such as the Alzheimer's Disease Neuroimaging Initiative data.

Why looking at the whole hippocampus is not enough-a critical role for anteroposterior axis, subfield and activation analyses to enhance predictive value of hippocampal changes for Alzheimer's disease diagnosis

The hippocampus is one of the earliest affected brain regions in Alzheimer's disease (AD) and its dysfunction is believed to underlie the core feature of the disease-memory impairment. Given that hippocampal volume is one of the best AD biomarkers, our review focuses on distinct subfields within the hippocampus, pinpointing regions that might enhance the predictive value of current diagnostic methods. Our review presents how changes in hippocampal volume, shape, symmetry and activation are reflected by cognitive impairment and how they are linked with neurogenesis alterations. Moreover, we revisit the functional differentiation along the anteroposterior longitudinal axis of the hippocampus and discuss its relevance for AD diagnosis. Finally, we indicate that apart from hippocampal subfield volumetry, the characteristic pattern of hippocampal hyperactivation associated with seizures and neurogenesis changes is another promising candidate for an early AD biomarker that could become also a target for early interventions.

What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus

What can be expected in normal aging, and where does normal aging stop and pathological neurodegeneration begin? With the slow progression of age-related dementias such as Alzheimer's disease (AD), it is difficult to distinguish age-related changes from effects of undetected disease. We review recent research on changes of the cerebral cortex and the hippocampus in aging and the borders between normal aging and AD. We argue that prominent cortical reductions are evident in fronto-temporal regions in elderly even with low probability of AD, including regions overlapping the default mode network. Importantly, these regions show high levels of amyloid deposition in AD, and are both structurally and functionally vulnerable early in the disease. This normalcy-pathology homology is critical to understand, since aging itself is the major risk factor for sporadic AD. Thus, rather than necessarily reflecting early signs of disease, these changes may be part of normal aging, and may inform on why the aging brain is so much more susceptible to AD than is the younger brain. We suggest that regions characterized by a high degree of life-long plasticity are vulnerable to detrimental effects of normal aging, and that this age-vulnerability renders them more susceptible to additional, pathological AD-related changes. We conclude that it will be difficult to understand AD without understanding why it preferably affects older brains, and that we need a model that accounts for age-related changes in AD-vulnerable regions independently of AD-pathology.

Mapping the effect of the apolipoprotein E genotype on 4-year atrophy rates in an Alzheimer disease-related brain network

PURPOSE

To determine the effect of the apolipoprotein E (APOE) genotype on atrophy rates of specific brain gray matter regions hypothesized to be key components of cognitive networks disrupted in Alzheimer disease.

MATERIALS AND METHODS

The Alzheimer's Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All subjects and their legal representatives gave written informed consent prior to data collection. The authors analyzed data from 237 subjects (mean age, 79.9 years; 40% female) with mild cognitive impairment (MCI) in the ADNI database and assessed the effect of the APOE ε4 and ε2 alleles on regional brain atrophy rates over a 12-48-month period. Brain regions were selected a priori: 15 experimental and five control regions were included. Regional atrophy rates were derived by using a fully automated algorithm applied to T1-weighted magnetic resonance (MR) imaging data. Analysis consisted of mixed-effects linear regression with repeated measures; results were adjusted for multiple testing with Bonferroni correction.

RESULTS

Thirteen of 15 experimental regions showed a significant effect of ε4 for higher atrophy rates (P < .001 for all). Cohen d values ranged from 0.26 to 0.42, with the largest effects seen in the amygdalae and hippocampi. The transverse temporal cortex showed a trend (P = .02, but did not survive Bonferroni correction) for a protective effect (Cohen d value = 0.15) of ε2. No control region showed an APOE effect.

CONCLUSION

The APOE ε4 allele is associated with accelerated rates of atrophy in 13 distinct brain regions in limbic and neocortical areas. This suggests the possibility of a genotype-specific network of related brain regions that undergo faster atrophy in MCI and potentially contribute to cognitive decline. Online supplemental material is available for this article.

Integration and relative value of biomarkers for prediction of MCI to AD progression: spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers

This study evaluates the individual, as well as relative and joint value of indices obtained from magnetic resonance imaging (MRI) patterns of brain atrophy (quantified by the SPARE-AD index), cerebrospinal fluid (CSF) biomarkers, APOE genotype, and cognitive performance (ADAS-Cog) in progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) within a variable follow-up period up to 6 years, using data from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1). SPARE-AD was first established as a highly sensitive and specific MRI-marker of AD vs. cognitively normal (CN) subjects (AUC = 0.98). Baseline predictive values of all aforementioned indices were then compared using survival analysis on 381 MCI subjects. SPARE-AD and ADAS-Cog were found to have similar predictive value, and their combination was significantly better than their individual performance. APOE genotype did not significantly improve prediction, although the combination of SPARE-AD, ADAS-Cog and APOE ε4 provided the highest hazard ratio estimates of 17.8 (last vs. first quartile). In a subset of 192 MCI patients who also had CSF biomarkers, the addition of Aβ1-42, t-tau, and p-tau181p to the previous model did not improve predictive value significantly over SPARE-AD and ADAS-Cog combined. Importantly, in amyloid-negative patients with MCI, SPARE-AD had high predictive power of clinical progression. Our findings suggest that SPARE-AD and ADAS-Cog in combination offer the highest predictive power of conversion from MCI to AD, which is improved, albeit not significantly, by APOE genotype. The finding that SPARE-AD in amyloid-negative MCI patients was predictive of clinical progression is not expected under the amyloid hypothesis and merits further investigation.

The APOE ɛ4 allele affects complexity and functional connectivity of resting brain activity in healthy adults

The apolipoprotein E (APOE) gene is associated with structural and functional brain changes. We have used multiscale entropy (MSE) analysis to detect changes in the complexity of resting blood oxygen level-dependent (BOLD) signals associated with aging and cognitive function. In this study, we further hypothesized that the APOE genotype may affect the complexity of spontaneous BOLD activity in younger and older adults, and such altered complexity may be associated with certain changes in functional connectivity. We conducted a resting-state functional magnetic resonance imaging experiment in a cohort of 100 younger adults (aged 20-39 years; mean 27.2 ± 4.3 years; male/female: 53/47) and 112 older adults (aged 60-79 years; mean 68.4 ± 6.5 years; male/female: 54/58), and applied voxelwise MSE analysis to assess the main effect of APOE genotype on resting-state BOLD complexity and connectivity. Although the main effect of APOE genotype on BOLD complexity was not observed in younger group, we observed that older APOE ɛ4 allele carriers had significant reductions in BOLD complexity in precuneus and posterior cingulate regions, relative to noncarriers. We also observed that reduced BOLD complexity in precuneus and posterior cingulate regions was associated with increased functional connectivity to the superior and inferior frontal gyrus in the older group. These results support the compensatory recruitment hypothesis in older APOE ɛ4 carriers, and confer the impact of the APOE genotype on the temporal dynamics of brain activity in older adults.

Local label learning (LLL) for subcortical structure segmentation: application to hippocampus segmentation

Automatic and reliable segmentation of subcortical structures is an important but difficult task in quantitative brain image analysis. Multi-atlas based segmentation methods have attracted great interest due to their promising performance. Under the multi-atlas based segmentation framework, using deformation fields generated for registering atlas images onto a target image to be segmented, labels of the atlases are first propagated to the target image space and then fused to get the target image segmentation based on a label fusion strategy. While many label fusion strategies have been developed, most of these methods adopt predefined weighting models that are not necessarily optimal. In this study, we propose a novel local label learning strategy to estimate the target image's segmentation label using statistical machine learning techniques. In particular, we use a L1-regularized support vector machine (SVM) with a k nearest neighbor (kNN) based training sample selection strategy to learn a classifier for each of the target image voxel from its neighboring voxels in the atlases based on both image intensity and texture features. Our method has produced segmentation results consistently better than state-of-the-art label fusion methods in validation experiments on hippocampal segmentation of over 100 MR images obtained from publicly available and in-house datasets. Volumetric analysis has also demonstrated the capability of our method in detecting hippocampal volume changes due to Alzheimer's disease.

Mitochondrial haplotypes associated with biomarkers for Alzheimer's disease

Various studies have suggested that the mitochondrial genome plays a role in late-onset Alzheimer's disease, although results are mixed. We used an endophenotype-based approach to further characterize mitochondrial genetic variation and its relationship to risk markers for Alzheimer's disease. We analyzed longitudinal data from non-demented, mild cognitive impairment, and late-onset Alzheimer's disease participants in the Alzheimer's Disease Neuroimaging Initiative with genetic, brain imaging, and behavioral data. We assessed the relationship of structural MRI and cognitive biomarkers with mitochondrial genome variation using TreeScanning, a haplotype-based approach that concentrates statistical power by analyzing evolutionarily meaningful groups (or clades) of haplotypes together for association with a phenotype. Four clades were associated with three different endophenotypes: whole brain volume, percent change in temporal pole thickness, and left hippocampal atrophy over two years. This is the first study of its kind to identify mitochondrial variation associated with brain imaging endophenotypes of Alzheimer's disease. Our results provide additional evidence that the mitochondrial genome plays a role in risk for Alzheimer's disease.

Neuroimaging predictors of brain amyloidosis in mild cognitive impairment

OBJECTIVE

To identify a neuroimaging signature predictive of brain amyloidosis as a screening tool to identify individuals with mild cognitive impairment (MCI) that are most likely to have high levels of brain amyloidosis or to be amyloid-free.

METHODS

The prediction model cohort included 62 MCI subjects screened with structural magnetic resonance imaging (MRI) and (11) C-labeled Pittsburgh compound B positron emission tomography (PET). We identified an anatomical shape variation-based neuroimaging predictor of brain amyloidosis and defined a structural MRI-based brain amyloidosis score (sMRI-BAS). Amyloid beta positivity (Aβ(+) ) predictive power of sMRI-BAS was validated on an independent cohort of 153 MCI patients with cerebrospinal fluid Aβ1-42 biomarker data but no amyloid PET scans. We compared the Aβ(+) predictive power of sMRI-BAS to those of apolipoprotein E (ApoE) genotype and hippocampal volume, the 2 most relevant candidate biomarkers for the prediction of brain amyloidosis.

RESULTS

Anatomical shape variations predictive of brain amyloidosis in MCI embraced a characteristic spatial pattern known for high vulnerability to Alzheimer disease pathology, including the medial temporal lobe, temporal-parietal association cortices, posterior cingulate, precuneus, hippocampus, amygdala, caudate, and fornix/stria terminals. Aβ(+) prediction performance of sMRI-BAS and ApoE genotype jointly was significantly better than the performance of each predictor separately (area under the curve [AUC] = 0.88 vs AUC = 0.70 and AUC = 0.81, respectively) with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds. Performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (AUC = 0.56).

INTERPRETATION

As one of the first attempts to use an imaging technique that does not require amyloid-specific radioligands for identification of individuals with brain amyloidosis, our findings could lead to development of multidisciplinary/multimodality brain amyloidosis biomarkers that are reliable, minimally invasive, and widely available.

Evaluating Alzheimer's disease progression using rate of regional hippocampal atrophy

Alzheimer's disease (AD) is characterized by neurofibrillary tangle and neuropil thread deposition, which ultimately results in neuronal loss. A large number of magnetic resonance imaging studies have reported a smaller hippocampus in AD patients as compared to healthy elderlies. Even though this difference is often interpreted as atrophy, it is only an indirect measurement. A more direct way of measuring the atrophy is to use repeated MRIs within the same individual. Even though several groups have used this appropriate approach, the pattern of hippocampal atrophy still remains unclear and difficult to relate to underlying pathophysiology. Here, in this longitudinal study, we aimed to map hippocampal atrophy rates in patients with AD, mild cognitive impairment (MCI) and elderly controls. Data consisted of two MRI scans for each subject. The symmetric deformation field between the first and the second MRI was computed and mapped onto the three-dimensional hippocampal surface. The pattern of atrophy rate was similar in all three groups, but the rate was significantly higher in patients with AD than in control subjects. We also found higher atrophy rates in progressive MCI patients as compared to stable MCI, particularly in the antero-lateral portion of the right hippocampus. Importantly, the regions showing the highest atrophy rate correspond to those that were described to have the highest burden of tau deposition. Our results show that local hippocampal atrophy rate is a reliable biomarker of disease stage and progression and could also be considered as a method to objectively evaluate treatment effects.

The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

CSF biomarker associations with change in hippocampal volume and precuneus thickness: implications for the Alzheimer's pathological cascade

Neurofibrillary tangles (NFT) and amyloid plaques are hallmark neuropathological features of Alzheimer's disease (AD). There is some debate as to which neuropathological feature comes first in the disease process, with early autopsy studies suggesting that NFT develop first, and more recent neuroimaging studies supporting the early role of amyloid beta (Aβ) deposition. Cerebrospinal fluid (CSF) biomarkers of Aβ₄₂ and hyperphosphorylated tau (p-tau) have been shown to serve as in vivo proxy measures of amyloid plaques and NFT, respectively. The aim of this study was to examine the association between CSF biomarkers and rate of atrophy in the precuneus and hippocampus. These regions were selected because the precuneus appears to be affected early and severely by Aβ deposition, and the hippocampus similarly by NFT pathology. We predicted (1) baseline Aβ₄₂ would be related to accelerated rate of cortical thinning in the precuneus and volume loss in the hippocampus, with the latter relationship expected to be weaker, (2) baseline p-tau(181p) would be related to accelerated rate of hippocampal atrophy and cortical thinning in the precuneus, with the latter relationship expected to be weaker. Using all ADNI cohorts, we fitted separate linear mixed-effects models for changes in hippocampus and precuneus longitudinal outcome measures with baseline CSF biomarkers modeled as predictors. Results partially supported our hypotheses: Both baseline p-tau(181p) and Aβ₄₂ were associated with hippocampal atrophy over time. Neither p-tau(181p) nor Aβ₄₂ were significantly related to cortical thinning in the precuneus over time. However, follow-up analyses demonstrated that having abnormal levels of both Aβ₄₂ and p-tau(181p) was associated with an accelerated rate of atrophy in both the hippocampus and precuneus. Results support early effects of Aβ in the Alzheimer's disease process, which are less apparent than and perhaps dependent on p-tau effects as the disease progresses. However, amyloid deposition alone may be insufficient for emergence of significant morphometric changes and clinical symptoms.

Vascular and Alzheimer's disease markers independently predict brain atrophy rate in Alzheimer's Disease Neuroimaging Initiative controls

This study assessed relationships among white matter hyperintensities (WMH), cerebrospinal fluid (CSF), Alzheimer's disease (AD) pathology markers, and brain volume loss. Subjects included 197 controls, 331 individuals with mild cognitive impairment (MCI), and 146 individuals with AD with serial volumetric 1.5-T MRI. CSF Aβ1-42 (n = 351) and tau (n = 346) were measured. Brain volume change was quantified using the boundary shift integral (BSI). We assessed the association between baseline WMH volume and annualized BSI, adjusting for intracranial volume. We also performed multiple regression analyses in the CSF subset, assessing the relationships of WMH and Aβ1-42 and/or tau with BSI. WMH burden was positively associated with BSI in controls (p = 0.02) but not MCI or AD. In multivariable models, WMH (p = 0.003) and Aβ1-42 (p = 0.001) were independently associated with BSI in controls; in MCI Aβ1-42 (p < 0.001) and tau (p = 0.04) were associated with BSI. There was no evidence of independent effects of WMH or CSF measures on BSI in AD. These data support findings that vascular damage is associated with increased brain atrophy in the context of AD pathology in pre-dementia stages.

Cerebrospinal fluid proteins predict longitudinal hippocampal degeneration in early-stage dementia of the Alzheimer type

OBJECTIVE

Biomarkers are needed to improve the sensitivity and accuracy of diagnosis, and also prognosis, in individuals with early Alzheimer disease (AD). Measures of brain structure and disease-related proteins in the cerebrospinal fluid (CSF) have been proposed as biomarkers, yet relatively little is known about the relationships between such measures. The present study was conducted to assess the relationship between CSF Aβ and tau protein levels and longitudinal measures of hippocampal structure in individuals with and without very mild dementia of the Alzheimer type.

DESIGN

A single CSF sample and longitudinal magnetic resonance scans were collected. The CSF samples were assayed for tau, phosphorylated tau181 (p-tau181), Aβ1-42, and Aβ1-40 using an enzyme-linked immunosorbent assay. Large-deformation diffeomorphic metric mapping was used to generate hippocampal surfaces, and a composite hippocampal surface (previously constructed from 86 healthy participants) was used as a structural reference.

PATIENTS OR OTHER PARTICIPANTS

Thirteen participants with very mild AD (Clinical Dementia Rating, CDR 0.5) and 11 cognitively normal participants (CDR 0).

INTERVENTION

None.

MAIN OUTCOME MEASURES

Initial and rate-of-change measures of total hippocampal volume and displacement of the hippocampal surface within zones overlying the CA1, subiculum, and CA2-4+DG cellular subfields, and their correlations with initial CSF measures.

RESULTS

Lower CSF Αβ1-42 levels and higher tau/Αβ1-42 and p-tau181/Αβ1-42 ratios were strongly correlated with decreases in hippocampal volume and measures of progressive inward deformations of the CA1 subfield in participants with early AD, but not in cognitively normal participants.

CONCLUSIONS

Despite the small sample size, we found that Αβ1-42 related and tau-related CSF measures were associated with hippocampal degeneration in individuals with clinically diagnosed early AD and may reflect an association with a common underlying disease mechanism.

Recent advances in imaging Alzheimer's disease

Advances in brain imaging technology in the past five years have contributed greatly to the understanding of Alzheimer's disease (AD). Here, we review recent research related to amyloid imaging, new methods for magnetic resonance imaging analyses, and statistical methods. We also review research that evaluates AD risk factors and brain imaging, in the context of AD prediction and progression. We selected a variety of illustrative studies, describing how they advanced the field and are leading AD research in promising new directions.

Posterior cingulate glucose metabolism, hippocampal glucose metabolism, and hippocampal volume in cognitively normal, late-middle-aged persons at 3 levels of genetic risk for Alzheimer disease

OBJECTIVE

To characterize and compare measurements of the posterior cingulate glucose metabolism, the hippocampal glucose metabolism, and hippocampal volume so as to distinguish cognitively normal, late-middle-aged persons with 2, 1, or 0 copies of the apolipoprotein E (APOE) ε4 allele, reflecting 3 levels of risk for late-onset Alzheimer disease.

DESIGN

Cross-sectional comparison of measurements of cerebral glucose metabolism using 18F-fluorodeoxyglucose positron emission tomography and measurements of brain volume using magnetic resonance imaging in cognitively normal ε4 homozygotes, ε4 heterozygotes, and noncarriers.

SETTING

Academic medical center.

PARTICIPANTS

A total of 31 ε4 homozygotes, 42 ε4 heterozygotes, and 76 noncarriers, 49 to 67 years old, matched for sex, age, and educational level.

MAIN OUTCOME MEASURES

The measurements of posterior cingulate and hippocampal glucose metabolism were characterized using automated region-of-interest algorithms and normalized for whole-brain measurements. The hippocampal volume measurements were characterized using a semiautomated algorithm and normalized for total intracranial volume.

RESULTS

Although there were no significant differences among the 3 groups of participants in their clinical ratings, neuropsychological test scores, hippocampal volumes (P = .60), or hippocampal glucose metabolism measurements (P = .12), there were significant group differences in their posterior cingulate glucose metabolism measurements (P = .001). The APOE ε4 gene dose was significantly associated with posterior cingulate glucose metabolism (r = 0.29, P = .0003), and this association was significantly greater than those with hippocampal volume or hippocampal glucose metabolism (P < .05, determined by use of pairwise Fisher z tests).

CONCLUSIONS

Although our findings may depend in part on the analysis algorithms used, they suggest that a reduction in posterior cingulate glucose metabolism precedes a reduction in hippocampal volume or metabolism in cognitively normal persons at increased genetic risk for Alzheimer disease.