Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors

Longitudinal changes in medial temporal cortical thickness in normal subjects with the APOE-4 polymorphism

People with the apolipoprotein-Eε4 (APOE-4) genetic risk for Alzheimer's disease show morphologic differences in medial temporal lobe regions when compared to non-carriers of the allele. Using a high-resolution MRI and cortical unfolding approach, our aim was to determine the rate of cortical thinning among medial temporal lobe subregions over the course of 2 years. We hypothesized that APOE-4 genetic risk would contribute to longitudinal cortical thickness change in the subiculum and entorhinal cortex, regions preferentially susceptible to Alzheimer's disease related pathology. Thirty-two cognitively intact subjects, mean age 61 years, 16 APOE-4 carriers, 16 non-carriers, underwent baseline and follow-up MRI scans. Over this relatively brief interval, we found significantly greater cortical thinning in the subiculum and entorhinal cortex of APOE-4 carriers when compared to non-carriers of the allele. Average cortical thinning across all medial temporal lobe subregions combined was also significantly greater for APOE-4 carriers. This finding is consistent with the hypothesis that carrying the APOE-4 allele renders subjects at a higher risk for developing Alzheimer's disease

Anti-inflammatories in Alzheimer’s disease – potential therapy or spurious correlate?

Epidemiological evidence suggests non-steroidal anti-inflammatories (NSAIDs) reduce the risk of Alzheimer’s disease. However, clinical trials have found no evidence of NSAID efficacy. This incongruence may be due to the wrong NSAIDs being tested in robust clinical trials or the epidemiological findings being caused by confounding factors. Therefore, this study used logistic regression and the innovative approach of negative binomial generalised linear mixed modelling to investigate both prevalence and cognitive decline, respectively, in the Alzheimer’s Disease NeuroImaging dataset for each commonly used NSAID and paracetamol. Use of most NSAIDs were associated with reduced Alzheimer’s disease prevalence yet no effect on cognitive decline was observed. Paracetamol had a similar effect on prevalence to these NSAIDs suggesting this association is independent of the anti-inflammatory effects and that previous results may be due to spurious associations. Interestingly, diclofenac use was significantly associated with both reduce incidence and slower cognitive decline warranting further research into the potential therapeutic effects of diclofenac in Alzheimer’s disease

Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease

The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed – 562 subjects at 1.5 T, a 75 subject group that also had manual segmentation and 111 subjects at 3 T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were −1.1%/year for healthy controls, −3.0%/year for mildly cognitively impaired and −5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5 T and 3 T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered

ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease

Biomarkers are the only feasible way to detect and monitor presymptomatic Alzheimer's disease (AD). No single biomarker can predict future cognitive decline with an acceptable level of accuracy. In addition to designing powerful multimodal diagnostic platforms, a careful investigation of the major sources of disease heterogeneity and their influence on biomarker changes is needed. Here we investigated the accuracy of a novel multimodal biomarker classifier for differentiating cognitively normal (NC), mild cognitive impairment (MCI) and AD subjects with and without stratification by ApoE4 genotype. 111 NC, 182 MCI and 95 AD ADNI participants provided both structural MRI and CSF data at baseline. We used an automated machine-learning classifier to test the ability of hippocampal volume and CSF Aβ, t-tau and p-tau levels, both separately and in combination, to differentiate NC, MCI and AD subjects, and predict conversion. We hypothesized that the combined hippocampal/CSF biomarker classifier model would achieve the highest accuracy in differentiating between the three diagnostic groups and that ApoE4 genotype will affect both diagnostic accuracy and biomarker selection. The combined hippocampal/CSF classifier performed better than hippocampus-only classifier in differentiating NC from MCI and NC from AD. It also outperformed the CSF-only classifier in differentiating NC vs. AD. Our amyloid marker played a role in discriminating NC from MCI or AD but not for MCI vs. AD. Neurodegenerative markers contributed to accurate discrimination of AD from NC and MCI but not NC from MCI. Classifiers predicting MCI conversion performed well only after ApoE4 stratification. Hippocampal volume and sex achieved AUC = 0.68 for predicting conversion in the ApoE4-positive MCI, while CSF p-tau, education and sex achieved AUC = 0.89 for predicting conversion in ApoE4-negative MCI. These observations support the proposed biomarker trajectory in AD, which postulates that amyloid markers become abnormal early in the disease course while markers of neurodegeneration become abnormal later in the disease course and suggests that ApoE4 could be at least partially responsible for some of the observed disease heterogeneity. © 2013 The Authors

Longitudinal Morphometric Study of Genetic Influence of APOE e4 Genotype on Hippocampal Atrophy - An N=1925 Surface-based ADNI Study

abstract: The apolipoprotein E (APOE) e4 genotype is the most prevalent known genetic risk factor for Alzheimer's disease (AD). In this paper, we examined the longitudinal effect of APOE e4 on hippocampal morphometry in Alzheimer's Disease Neuroimaging Initiative (ADNI). Generally, atrophy of hippocampus has more chance occurs in AD patients who carrying the APOE e4 allele than those who are APOE e4 noncarriers. Also, brain structure and function depend on APOE genotype not just for Alzheimer's disease patients but also in health elderly individuals, so APOE genotyping is considered critical in clinical trials of Alzheimer's disease. We used a large sample of elderly participants, with the help of a new automated surface registration system based on surface conformal parameterization with holomorphic 1-forms and surface fluid registration. In this system, we automatically segmented and constructed hippocampal surfaces from MR images at many different time points, such as 6 months, 1- and 2-year follow up. Between the two different hippocampal surfaces, we did the high-order correspondences, using a novel inverse consistent surface fluid registration method. At each time point, using Hotelling's T^2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes.Dissertation/ThesisMasters Thesis Computer Science 201

MRI Measures of Neurodegeneration as Biomarkers of Alzheimer's Disease

Indiana University-Purdue University Indianapolis (IUPUI)Alzheimer’s disease (AD) is the most common age-related neurodegenerative disease. Many researchers believe that an effective AD treatment will prevent the development of disease rather than treat the disease after a diagnosis. Therefore, the development of tools to detect AD-related pathology in early stages is an important goal. In this report, MRI-based markers of neurodegeneration are explored as biomarkers of AD. In the first chapter, the sensitivity of cross-sectional MRI biomarkers to neurodegenerative changes is evaluated in AD patients and in patients with a diagnosis of mild cognitive impairment (MCI), a prodromal stage of AD. The results in Chapter 1 suggest that cross-sectional MRI biomarkers effectively measure neurodegeneration in AD and MCI patients and are sensitive to atrophic changes in patients who convert from MCI to AD up to 1 year before clinical conversion. Chapter 2 investigates longitudinal MRI-based measures of neurodegeneration as biomarkers of AD. In Chapter 2a, measures of brain atrophy rate in a cohort of AD and MCI patients are evaluated; whereas in Chapter 2b, these measures are assessed in a pre-MCI stage, namely older adults with cognitive complaints (CC) but no significant deficits. The results from Chapter 2 suggest that dynamic MRI-based measures of neurodegeneration are sensitive biomarkers for measuring progressive atrophy associated with the development of AD. In the final chapter, a novel biomarker for AD, visual contrast sensitivity, was evaluated. The results demonstrated contrast sensitivity impairments in AD and MCI patients, as well as slightly in CC participants. Impaired contrast sensitivity was also shown to be significantly associated with known markers of AD, including cognitive impairments and temporal lobe atrophy on MRI-based measures. The results of Chapter 3 support contrast sensitivity as a potential novel biomarker for AD and suggest that future studies are warranted. Overall, the results of this report support MRI-based measures of neurodegeneration as effective biomarkers for AD, even in early clinical and preclinical disease stages. Future therapeutic trials may consider utilizing these measures to evaluate potential treatment efficacy and mechanism of action, as well as for sample enrichment with patients most likely to rapidly progress towards AD