Guofan Xu

A generalized form of context-dependent psychophysiological interactions (gPPI): a comparison to standard approaches.

Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike information criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings.

Predictive Markers for AD in a Multi-Modality Framework: An Analysis of MCI Progression in the ADNI Population

Alzheimers Disease (AD) and other neurodegenerative diseases affect over 20 million people worldwide, and this number is projected to significantly increase in the coming decades. Proposed imaging-based markers have shown steadily improving levels of sensitivity/specificity in classifying individual subjects as AD or normal. Several of these efforts have utilized statistical machine learning techniques, using brain images as input, as means of deriving such AD-related markers. A common characteristic of this line of research is a focus on either (1) using a single imaging modality for classification, or (2) incorporating several modalities, but reporting separate results for each. One strategy to improve on the success of these methods is to leverage all available imaging modalities together in a single automated learning framework. The rationale is that some subjects may show signs of pathology in one modality but not in another-by combining all available images a clearer view of the progression of disease pathology will emerge. Our method is based on the Multi-Kernel Learning (MKL) framework, which allows the inclusion of an arbitrary number of views of the data in a maximum margin, kernel learning framework. The principal innovation behind MKL is that it learns an optimal combination of kernel (similarity) matrices while simultaneously training a classifier. In classification experiments MKL outperformed an SVM trained on all available features by 3%-4%. We are especially interested in whether such markers are capable of identifying early signs of the disease. To address this question, we have examined whether our multi-modal disease marker (MMDM) can predict conversion from Mild Cognitive Impairment (MCI) to AD. Our experiments reveal that this measure shows significant group differences between MCI subjects who progressed to AD, and those who remained stable for 3 years. These differences were most significant in MMDMs based on imaging data. We also discuss the relationship between our MMDM and an individuals conversion from MCI to AD.

Reliability and Precision of Pseudo-continuous Arterial Spin Labeling Perfusion MRI on 3.0 T and Comparison with 15O-water PET in Elderly Subjects at Risk for Alzheimer’s Disease

Arterial spin labeling (ASL) offers MRI measurement of cerebral blood flow (CBF) in vivo, and may offer clinical diagnostic utility in populations such as those with early Alzheimers disease (AD). In the current study, we investigated the reliability and precision of a pseudo‐continuous ASL (pcASL) sequence that was performed two or three times within one hour on eight young normal control subjects, and 14 elderly subjects including 11 with normal cognition, one with AD and two with Mild Cognitive Impairment (MCI). Six of these elderly subjects including one AD, two MCIs and three controls also received 15O‐water positron emission tomography (PET) scans 2 h before their pcASL MR scan. The instrumental reliability of pcASL was evaluated with the intraclass correlation coefficient (ICC). The ICCs were greater than 0.90 in pcASL global perfusion measurements for both the young and the elderly groups. The cross‐modality perfusion imaging comparison yielded very good global and regional agreement in global gray matter and the posterior cingulate cortex. Significant negative correlation was found between age and the gray/white matter perfusion ratio (r = –0.62, p < 0.002). The AD and MCI patients showed the lowest gray/white matter perfusion ratio among all the subjects. The data suggest that pcASL provides a reliable whole brain CBF measurement in young and elderly adults whose results converge with those obtained with the traditional 15O‐water PET perfusion imaging method. pcASL perfusion MRI offers an alternative method for non‐invasive in vivo examination of early pathophysiological changes in AD. Copyright

Insulin Resistance, Brain Atrophy, and Cognitive Performance in Late Middle–Aged Adults

OBJECTIVE Insulin resistance dysregulates glucose uptake and other functions in brain areas affected by Alzheimer disease. Insulin resistance may play a role in Alzheimer disease etiopathogenesis. This longitudinal study examined whether insulin resistance among late middle–aged, cognitively healthy individuals was associated with 1) less gray matter in Alzheimer disease–sensitive brain regions and 2) worse cognitive performance. RESEARCH DESIGN AND METHODS Homeostasis model assessment of insulin resistance, gray matter volume, and the Rey Auditory Verbal Learning Test (RAVLT) were acquired in 372 participants at baseline and a consecutive subset of 121 individuals ~4 years later. Voxel-based morphometry and tensor-based morphometry were used, respectively, to test the association of insulin resistance with baseline brain volume and progressive gray matter atrophy. RESULTS Higher insulin resistance predicted less gray matter at baseline and 4 years later in medial temporal lobe, prefrontal cortices, precuneus, and other parietal gyri. A region-of-interest analysis, independent of the voxel-wise analyses, confirmed that higher insulin resistance was related to medial temporal lobe atrophy. Atrophy itself corresponded to cognitive deficits in the RAVLT. Temporal lobe atrophy that was predicted by higher insulin resistance significantly mediated worse RAVLT encoding performance. CONCLUSIONS These results suggest that insulin resistance in an asymptomatic, late middle–aged cohort is associated with progressive atrophy in regions affected by early Alzheimer disease. Insulin resistance may also affect the ability to encode episodic information by negatively influencing gray matter volume in medial temporal lobe.

White Matter in Aging and Cognition: A Cross-sectional Study of Microstructure in Adults Aged Eighteen to Eighty-Three

Structural brain change and concomitant cognitive decline are the seemingly unavoidable escorts of aging. Despite accumulating studies detailing the effects of age on the brain and cognition, the relationship between white matter features and cognitive function in aging have only recently received attention and remain incompletely understood. White matter microstructure can be measured with diffusion tensor imaging (DTI), but whether DTI can provide unique information on brain aging that is not explained by white matter volume is not known. In the current study, the relationship between white matter microstructure, age, and neuropsychological function was assessed using DTI in a statistical framework that employed white matter volume as a voxel-wise covariate in a sample of 120 healthy adults across a broad age range (18–83). Memory function and executive function were modestly correlated with the DTI measures while processing speed showed the greatest extent of correlation. The results suggest that age-related white matter alterations underlie age-related declines in cognitive function. Mean diffusivity and fractional anisotropy in several white matter brain regions exhibited a nonlinear relationship with age, while white matter volume showed a primarily linear relationship with age. The complex relationships between cognition, white matter microstructure, and white matter volume still require further investigation.

Effects of Hypoperfusion in Alzheimer's Disease

The role of hypoperfusion in Alzheimers disease (AD) is a vital component to understanding the pathogenesis of this disease. Disrupted perfusion is not only evident throughout disease manifestation, it is also demonstrated during the pre-clinical phase of AD (i.e., mild cognitive impairment) as well as in cognitively healthy persons at high-risk for developing AD due to family history or genetic factors. Studies have used a variety of imaging modalities (e.g., SPECT, MRI, PET) to investigate AD, but with its recent technological advancements and non-invasive use of blood water as an endogenous tracer, arterial spin labeling (ASL) MRI has become an imaging technique of growing popularity. Through numerous ASL studies, it is now known that AD is associated with both global and regional cerebral hypoperfusion and that there is considerable overlap between the regions implicated in the disease state (consistently reported in precuneus/posterior cingulate and lateral parietal cortex) and those implicated in disease risk. Debate exists as to whether decreased blood flow in AD is a cause or consequence of the disease. Nonetheless, hypoperfusion in AD is associated with both structural and functional changes in the brain and offers a promising putative biomarker that could potentially identify AD in its pre-clinical state and be used to explore treatments to prevent, or at least slow, the progression of the disease. Finally, given that perfusion is a vascular phenomenon, we provide insights from a vascular lesion model (i.e., stroke) and illustrate the influence of disrupted perfusion on brain structure and function and, ultimately, cognition in AD.

The effect of TOMM40 poly-T length on gray matter volume and cognition in middle-aged persons with APOE ɛ3/ɛ3 genotype

Apolipoprotein E (APOE) genotypes are associated with variable risk of developing late‐onset Alzheimers disease (LOAD), with APOE epsilon 4 (APOE ɛ4) having higher risk. A variable poly‐T length polymorphism at rs10524523, within intron 6 of the translocase of the outer mitochondrial membrane (TOMM40) gene, has been shown to influence age of onset in LOAD, with very long (VL) poly‐T length associated with earlier disease onset, and short poly‐T length associated with later onset. In this study, we tested the hypothesis that brain and cognitive changes suggestive of presymptomatic LOAD may be associated with this TOMM40 polymorphism.

The influence of parental history of Alzheimer's disease and apolipoprotein E ε4 on the BOLD signal during recognition memory

First-degree family history (FH) of sporadic Alzheimers disease and the apolipoprotein E epsilon4 allele (APOE4) are risk factors for Alzheimers disease that may affect brain function prior to onset of clinical symptoms. In this functional MRI (fMRI) study, we used an episodic recognition task that required discrimination of previously viewed (PV) and novel (NV) faces to examine differences in blood oxygen level dependent (BOLD) signal due to risk factors in 74 middle-aged cognitively normal individuals. The group effects on this recognition task were tested with a 2 x 2 ANCOVA factorial design (+FH/-FH and +APOE4/-APOE4). There were significant APOE4 and FH effects in the left dorsal posterior cingulate cortex and precuneus, where decreased risk resulted in greater activity during recollection. Recognition performance was positively correlated with BOLD signal in the left posterior hippocampus, parahippocampal-retrosplenial gyrus and left superior frontal cortex regardless of risk factors. To examine condition-specific group effects, both the PV and NV faces were tested further in separate 2 x 2 ANCOVAs. Both models revealed an APOE effect, with the -APOE4 group showing stronger signal than the +APOE4 group in anterior cingulate cortices, while a FH effect was found in the dorsal cuneus and medial frontal cortices with the -FH group showing stronger signal than the +FH group. Finally, interactions between APOE4 and FH effects were found bilaterally in the fusiform gyrus. These results suggest that risk factors and cognitive performance each influence brain activity during recognition. The findings lend further support to the idea that functional brain changes may begin far in advance of symptomatic Alzheimers disease.

Amyloid burden and neural function in people at risk for Alzheimer's Disease

To determine the relationship between amyloid burden and neural function in healthy adults at risk for Alzheimers Disease (AD), we used multimodal imaging with [C-11]Pittsburgh compound B positron emission tomography, [F-18]fluorodeoxyglucose, positron emission tomography , and magnetic resonance imaging, together with cognitive measurement in 201 subjects (mean age, 60.1 years; range, 46-73 years) from the Wisconsin Registry for Alzheimers Prevention. Using a qualitative rating, 18% of the samples were strongly positive Beta-amyloid (Aβ+), 41% indeterminate (Aβi), and 41% negative (Aβ-). Aβ+ was associated with older age, female sex, and showed trends for maternal family history of AD and APOE4. Relative to the Aβ- group, Aβ+ and Aβi participants had increased glucose metabolism in the bilateral thalamus; Aβ+ participants also had increased metabolism in the bilateral superior temporal gyrus. Aβ+ participants exhibited increased gray matter in the lateral parietal lobe bilaterally relative to the Aβ- group, and no areas of significant atrophy. Cognitive performance and self report cognitive and affective symptoms did not differ between groups. Amyloid burden can be identified in adults at a mean age of 60 years and is accompanied by glucometabolic increases in specific areas, but not atrophy or cognitive loss. This asymptomatic stage may be an opportune window for intervention to prevent progression to symptomatic AD.

A Calorie-Restricted Diet Decreases Brain Iron Accumulation and Preserves Motor Performance in Old Rhesus Monkeys

Caloric restriction (CR) reduces the pathological effects of aging and extends the lifespan in many species, including nonhuman primates, although the effect on the brain is less well characterized. We used two common indicators of aging, motor performance speed and brain iron deposition measured in vivo using MRI, to determine the potential effect of CR on elderly rhesus macaques eating restricted (n = 24; 13 males, 11 females) and standard diets (n = 17; 8 males, 9 females). Both the CR and control monkeys showed age-related increases in iron concentrations in globus pallidus (GP) and substantia nigra (SN), although the CR group had significantly less iron deposition in the GP, SN, red nucleus, and temporal cortex. A diet × age interaction revealed that CR modified age-related brain changes, evidenced as attenuation in the rate of iron accumulation in basal ganglia and parietal, temporal, and perirhinal cortex. Additionally, control monkeys had significantly slower fine motor performance on the Movement Assessment Panel, which was negatively correlated with iron accumulation in left SN and parietal lobe, although CR animals did not show this relationship. Our observations suggest that the CR-induced benefit of reduced iron deposition and preserved motor function may indicate neural protection similar to effects described previously in aging rodent and primate species.