Screening for DSM-IV-TR cognitive disorder NOS in Parkinson's disease using the Mattis Dementia Rating Scale.

OBJECTIVE: This study explores the utility of the Mattis Dementia Rating Scale (MDRS) as a screening tool for the Diagnostic and Statistical Manual for Mental Disorders 4th edition (DSM-IV-TR) diagnosis cognitive disorder not otherwise specified (NOS) in Parkinson's disease (PD). METHODS: A total of 125 individuals with PD were diagnosed using DSM-IV-TR criteria for cognitive disorder NOS and dementia. Receiver operating characteristics (ROC) tested the discriminant validity of the MDRS, with the clinician's diagnosis serving as the gold standard. RESULTS: The MDRS ROC curve to discriminate subjects with cognitive disorder NOS from non-demented subjects had an area under the curve of 0.59 (standard error = 0.08, 95% CI: 0.43-0.74). CONCLUSIONS: The MDRS is not effective for identifying PD patients with cognitive disorder NOS without dementia.

Two-stage decompositions for the analysis of functional connectivity for fMRI with application to Alzheimer's disease risk.

Functional connectivity is the study of correlations in measured neurophysiological signals. Altered functional connectivity has been shown to be associated with a variety of cognitive and memory impairments and dysfunction, including Alzheimer's disease. In this manuscript we use a two-stage application of the singular value decomposition to obtain data driven population-level measures of functional connectivity in functional magnetic resonance imaging (fMRI). The method is computationally simple and amenable to high dimensional fMRI data with large numbers of subjects. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and their associated loadings. We further demonstrate the utility of these decompositions in a functional logistic regression model. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found an indication of alternative connectivity in clinically asymptomatic at-risk subjects when compared to controls, which was not significant in the light of multiple comparisons adjustment. The relevant brain network loads primarily on the temporal lobe and overlaps significantly with the olfactory areas and temporal poles.

Modified test statistics by inter-voxel variance shrinkage with an application to f MRI.

Functional magnetic resonance imaging (f MRI) is a noninvasive technique which is commonly used to quantify changes in blood oxygenation and flow coupled to neuronal activation. One of the primary goals of f MRI studies is to identify localized brain regions where neuronal activation levels vary between groups. Single voxel t-tests have been commonly used to determine whether activation related to the protocol differs across groups. Due to the generally limited number of subjects within each study, accurate estimation of variance at each voxel is difficult. Thus, combining information across voxels is desirable in order to improve efficiency. Here, we construct a hierarchical model and apply an empirical Bayesian framework for the analysis of group f MRI data, employing techniques used in high-throughput genomic studies. The key idea is to shrink residual variances by combining information across voxels and subsequently to construct an improved test statistic. This hierarchical model results in a shrinkage of voxel-wise residual sample variances toward a common value. The shrunken estimator for voxel-specific variance components on the group analyses outperforms the classical residual error estimator in terms of mean-squared error. Moreover, the shrunken test statistic decreases false-positive rates when testing differences in brain contrast maps across a wide range of simulation studies. This methodology was also applied to experimental data regarding a cognitive activation task.

Effect of handedness on fMRI activation in the medial temporal lobe during an auditory verbal memory task.

Several studies have shown marked differences in the neural localization of language functions in the brains of left-handed individuals when compared with right-handers. Previous experiments involving functional lateralization have demonstrated cerebral blood flow patterns that differ concordantly with subject handedness while performing language-related tasks. The effect of handedness on function in specific stages of memory processing, however, is a largely unexplored area. We used a paired-associates verbal memory task to elicit activation of neural areas related to declarative memory, examining the hypothesis that there are differences in activation in the medial temporal lobe (MTL) between handedness groups. 15 left-handed and 25 right-handed healthy adults were matched for all major demographic and neuropsychological variables. Functional and structural imaging data were acquired and analyzed for group differences within MTL subregions. Our results show that activation of the MTL during declarative memory processing varies with handedness. While both groups showed activation in left and right MTL subregions, the left-handed group showed a statistically significant increase in the left hippocampus and amygdala during both encoding and recall. No increases in activation were found in the right-handed group. This effect was found in the absence of any differences in performance on the verbal memory task, structural volumetric disparities, or functional asymmetries. This provides evidence of functional differences between left-handers and right-handers, which extends to declarative memory processes.

Familial risk for Alzheimer's disease alters fMRI activation patterns.

Alzheimer's disease poses a looming crisis for the health care system as well as society in general. The low efficacy of current treatments for those already affected with this disease has prompted the suggestion that interventions might be more successful if they were applied before the development of significant pathology, that is, when individuals are clinically asymptomatic. Currently, the field requires a sensitive and specific diagnostic tool for identifying those individuals destined to develop this disease. As a first step, we present here an analysis of cross-sectional data for 95 asymptomatic offspring (50-75 years of age) of autopsy-confirmed late-onset familial Alzheimer's disease cases and 90 age-matched controls, studied with functional magnetic resonance imaging (fMRI) to investigate brain activation patterns. Analysis of activation in response to a paired-associates memory paradigm found significantly different patterns in these groups. At-risk individuals showed more intense and extensive activation in the frontal and temporal lobes including the hippocampus during memory encoding, an increase unrelated to the APOE epsilon4 allele. They also showed decreased activation particularly in the cingulum and thalamus during both the encoding and recall phases of the task. These results demonstrate that asymptomatic individuals, at genetic risk for development of late-onset Alzheimer's disease by virtue of familial clustering, show functional activation patterns distinct from those without such risk more than a decade before their parent's onset age. While longitudinal study is needed to determine whether these patterns, or a subset of them, are predictive of disease onset, these findings suggest that functional neuroimaging holds promise as a method of identifying pre-clinical Alzheimer's disease.

Evidence for parent of origin effect in late-onset Alzheimer disease.

Evidence for a parent of origin effect in Alzheimer disease was obtained from a sample of 148 sibships on which affection status of the parents was sought using family history interviews. The parent study recruited families with two or more affected sibs for late onset AD utilizing rigorous diagnostic criteria. In 74 families, there was evidence of an affected parent, 49 maternal and 25 paternal. Genome scan data were analyzed for the sample as a whole and for the maternal and paternal families separately, using Genehunter-ASM. Seven regions with Z(lr) scores >or=2 were identified, four in maternal families (chr. 10,12,19,20) and three in paternal families (chr. 1,7,13). With the exception of the chromosome 10 finding, analysis by parent of origin greatly increased evidence of linkage in areas showing no linkage in the overall analyses. For example, a chr. 12 region reached a LOD = 2.29 among maternal families whereas the same region showed a LOD = 0.3 when all families were analyzed together. The strongest findings among maternal families (chr. 10 and 12) were followed up with fine mapping that resulted in an increase in maximum LOD scores from 2.7-3.2 on chr. 10, and 2.29-2.42 on chr. 12. These analyses highlight the importance of parent of origin effects in late-onset AD families and identify several genomic regions that may include genes linked to late-onset AD specific to disease transmission from the mother and require further investigation.

The role of test accuracy in predicting acceptance of genetic susceptibility testing for Alzheimer's disease.

A survey questionnaire regarding perceptions of risk and genetic susceptibility to Alzheimer's disease (AD) was completed by 518 offspring of AD cases from families with multiple affected, ascertained as part of a genetic linkage study of late onset AD. The questionnaire focused on respondents' perceptions of their own risk for AD as well as on the properties of real and hypothetical susceptibility tests, including error rates for false-positive and false-negative test results. Our findings showed that about 20% of the sample would refuse a susceptibility test with zero error rates, about 40% would accept tests with very high error rates in both directions, and the remainder would exercise some discrimination. Acceptance of high test error rates was significantly associated with male gender, low education, and high perceived lifetime risk of AD. In a previous paper related to this work, we showed that physicians caring for these families exercised much more discrimination in judging the acceptability of genetic tests they would offer to these same respondents. The findings show that there is a pressing need to educate the public, particularly those with relatives affected by a complex disease, to expect standards of accuracy for genetic tests comparable to those that prevail in other diagnostic and prognostic testing efforts in the broad field of clinical medicine.

Spatial Bayesian Variable Selection Models on Functional Magnetic Resonance Imaging Time-Series Data.

A common objective of fMRI (functional magnetic resonance imaging) studies is to determine subject-specific areas of increased blood oxygenation level dependent (BOLD) signal contrast in response to a stimulus or task, and hence to infer regional neuronal activity. We posit and investigate a Bayesian approach that incorporates spatial and temporal dependence and allows for the task-related change in the BOLD signal to change dynamically over the scanning session. In this way, our model accounts for potential learning effects in addition to other mechanisms of temporal drift in task-related signals. We study the properties of the model through its performance on simulated and real data sets.

Analysis of group ICA-based connectivity measures from fMRI: application to Alzheimer's disease.

Functional magnetic resonance imaging (fMRI) is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer's disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer's disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.

Covariate-adjusted nonparametric analysis of magnetic resonance images using Markov chain Monte Carlo.

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain under minimal assumptions. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our nonparametric method to remove potential bias due to the observed covariates is presented.

A Bayesian hierarchical framework for spatial modeling of fMRI data.

Applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric, neurological, and substance abuse disorders and their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. Complementary approaches consider the ensemble of voxels constituting an anatomically defined region of interest (ROI) or summary statistics, such as means or quantiles, of the ROI. In this work, we present a Bayesian extension of voxel-level analyses that offers several notable benefits. Among these, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance matrix for regional mean parameters allows for the study of inter-regional (long-range) correlations, and the model employs an exchangeable correlation structure to capture intra-regional (short-range) correlations. Estimation is performed using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling. We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer's disease.

Altered fMRI activation during mental rotation in those at genetic risk for Alzheimer disease.

OBJECTIVE: This study was undertaken to examine differential functional MRI patterns in those at genetic risk for Alzheimer disease (AD), specifically investigating parietal lobe activation, a brain region with changes noted in the early stages of AD. METHODS: This study uses functional MRI to investigate blood oxygenation level dependent changes in the parietal lobe in a high-risk sample of 18 asymptomatic offspring of autopsy-confirmed AD cases, compared to 15 matched controls. The cognitive activation paradigm was a mental rotation task, which requires individuals to rotate three-dimensional cube stimuli to judge their similarity. RESULTS: We found no differences in either reaction time or performance accuracy between groups. However, the at-risk individuals showed increases in activation in the right superior parietal lobule (BA 7), the right insula (BA 13), the right middle frontal gyrus (BA 10), and the right inferior frontal gyrus (BA 47). CONCLUSIONS: We present evidence for a compensatory mechanism for those at increased risk for Alzheimer disease (AD). This study examines and confirms parietal changes with increased risk for late-onset AD, despite normal cognitive performance. Added to the previous findings from this group, these results demonstrate the sensitivity of functional imaging measures to brain changes that are not yet reflected in cognitive performance, which may ultimately serve as an important indicator of disease.

Clinical features associated with impulse control disorders in Parkinson disease.

In patients with Parkinson disease (PD), impulse control disorders (ICDs) such as hypersexuality and pathologic gambling and shopping can be devastating complications of antiparkinsonian treatment. To improve their detection, we investigated clinical features associated with ICDs. Subjects were participants in a longitudinal study of PD. ICDs were associated with use of dopamine agonists and depressed mood, disinhibition, irritability, and appetite disturbance.

Further evidence of a maternal parent-of-origin effect on chromosome 10 in late-onset Alzheimer's disease.

The chromosome 10q region has recently received a great deal of attention in late-onset Alzheimer's disease (LOAD), given the growing evidence of linkage to LOAD, or to A-beta levels, reported by several groups. In a recent paper we reported evidence of linkage in this region in our subset of the NIMH AD genetics initiative pedigrees, approaching genome-wide significance (non-parametric LOD score = 3.27), when only families with maternal disease origin were analyzed [Bassett et al. (2002); Am J Med Genet 114:679-686]. We have now extended this work, using an independent subset of NIMH AD pedigrees from the University of Alabama at Birmingham (UAB), and show further evidence of linkage using parent-of-origin information. As in our Hopkins sample, maternal but not paternal pedigrees show significantly increased linkage in the chromosome 10q region compared to the unstratified sample. Combining data from our previous fine-mapping work on this region and five new markers genotyped in all pedigrees results in a non-parametric LOD score of 3.73 in the same region, a value that reaches genome wide significance for linkage, with an empirical P value = 0.003. These results support our earlier findings and narrow the region of interest. In combination with findings from other groups, these results provide further evidence that this chromosome 10 region harbors a gene implicated in LOAD, and our use of parent-of-origin information has been useful in further narrowing the region of interest.

Brain activation in offspring of AD cases corresponds to 10q linkage.

Previously, we reported evidence of genetic heterogeneity in late-onset familial Alzheimer's disease, based on sex of affected parent, demonstrating linkage to chromosome 10q, a region identified by other groups and implicated as a quantitative trait loci for Abeta levels, in families with an affected mother. Using functional magnetic resonance imaging and a memory encoding task, we now show differential brain activation patterns among asymptomatic offspring which correspond to the previous linkage finding. These results suggest the possibility that activation patterns may prove useful as a preclinical quantitative trait related to the putative familial late-onset AD gene in this chromosome 10 region.

Physicians' propensity to offer genetic testing for Alzheimer's disease: results from a survey.

PURPOSE: Examine physician knowledge, preferences, and use of genetic tests for Alzheimer's disease (AD). METHODS: Survey of 426 community-based physicians treating AD patients. RESULTS: Majority gave inaccurate estimates of AD risk. Medical specialty predicted appropriate use of current tests. Recommending substances to prevent memory loss was related to acceptance of error-free tests. High patient loads and familiarity with genetic tests predicted lower tolerance for test error. CONCLUSION: Physicians do not endorse indiscriminate genetic susceptibility testing for AD. However, insufficient knowledge of disease risk, etiology, genetic susceptibility, and use of existing tests indicated a need for further physician education in this area.