Davangere P. Devanand

Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease.

Objective: To evaluate the utility of MRI hippocampal and entorhinal cortex atrophy in predicting conversion from mild cognitive impairment (MCI) to Alzheimer disease (AD). Methods: Baseline brain MRI was performed in 139 patients with MCI, broadly defined, and 63 healthy controls followed for an average of 5 years (range 1 to 9 years). Results: Hippocampal and entorhinal cortex volumes were each largest in controls, intermediate in MCI nonconverters, and smallest in MCI converters to AD (37 of 139 patients converted to AD). In separate Cox proportional hazards models, covarying for intracranial volume, smaller hippocampal volume (risk ratio [RR] 3.62, 95% CI 1.93 to 6.80, p < 0.0001), and entorhinal cortex volume (RR 2.43, 95% CI 1.56 to 3.79, p < 0.0001) each predicted time to conversion to AD. Similar results were obtained for hippocampal and entorhinal cortex volume in patients with MCI with Mini-Mental State Examination (MMSE) scores ≥ 27 out of 30 (21% converted to AD) and in the subset of patients with amnestic MCI (35% converted to AD). In the total patient sample, when both hippocampal and entorhinal volume were entered into an age-stratified Cox model with sex, MMSE, education, and intracranial volume, smaller hippocampal volume (RR 2.21, 95% CI 1.14 to 4.29, p < 0.02) and entorhinal cortex volume (RR 2.48, 95% CI 1.54 to 3.97, p < 0.0002) predicted time to conversion to AD. Similar results were obtained in a Cox model that also included Selective Reminding Test (SRT) delayed recall and Wechsler Adult Intelligence Scale-Revised (WAIS-R) Digit Symbol as predictors. Based on logistic regression models in the 3-year follow-up sample, for a fixed specificity of 80%, the sensitivities for MCI conversion to AD were as follows: age 43.3%, MMSE 43.3%, age + MMSE 63.7%, age + MMSE + SRT delayed recall + WAIS-R Digit Symbol 80.6% (79.6% correctly classified), hippocampus + entorhinal cortex 66.7%, age + MMSE + hippocampus + entorhinal cortex 76.7% (85% correctly classified), age + MMSE + SRT delayed recall + WAIS-R Digit Symbol + hippocampus + entorhinal cortex 83.3% (86.8% correctly classified). Conclusions: Smaller hippocampal and entorhinal cortex volumes each contribute to the prediction of conversion to Alzheimer disease. Age and cognitive variables also contribute to prediction, and the added value of hippocampal and entorhinal cortex volumes is small. Nonetheless, combining these MRI volumes with age and cognitive measures leads to high levels of predictive accuracy that may have potential clinical application.

Combining early markers strongly predicts conversion from mild cognitive impairment to Alzheimer's disease.

BACKGROUND The utility of combining early markers to predict conversion from mild cognitive impairment (MCI) to Alzheimers Disease (AD) remains uncertain. METHODS Included in the study were 148 outpatients with MCI, broadly defined, followed at 6-month intervals. Hypothesized baseline predictors for follow-up conversion to AD (entire sample: 39/148 converters) were cognitive test performance, informant report of functional impairment, apolipoprotein E genotype, olfactory identification deficit, and magnetic resonance imaging (MRI) hippocampal and entorhinal cortex volumes. RESULTS In the 3-year follow-up patient sample (33/126 converters), five of eight hypothesized predictors were selected by backward and stepwise logistic regression: Pfeffer Functional Activities Questionnaire (FAQ; informant report of functioning), University of Pennsylvania Smell Identification Test (UPSIT; olfactory identification), Selective Reminding Test (SRT) immediate recall (verbal memory), MRI hippocampal volume, and MRI entorhinal cortex volume. For 10% false positives (90% specificity), this five-predictor combination showed 85.2% sensitivity, combining age and Mini-Mental State Examination (MMSE) showed 39.4% sensitivity; combining age, MMSE, and the three clinical predictors (SRT immediate recall, FAQ, and UPSIT) showed 81.3% sensitivity. Area under ROC curve was greater for the five-predictor combination (.948) than age plus MMSE (.821; p = .0009) and remained high in subsamples with MMSE > or = 27/30 and amnestic MCI. CONCLUSIONS The five-predictor combination strongly predicted conversion to AD and was markedly superior to combining age and MMSE. Combining the clinically administered measures also led to strong predictive accuracy. If independently replicated, the findings have potential utility for early detection of AD.

At the interface of sensory and motor dysfunctions and Alzheimer's disease

Recent evidence indicates that sensory and motor changes may precede the cognitive symptoms of Alzheimers disease (AD) by several years and may signify increased risk of developing AD. Traditionally, sensory and motor dysfunctions in aging and AD have been studied separately. To ascertain the evidence supporting the relationship between age‐related changes in sensory and motor systems and the development of AD and to facilitate communication between several disciplines, the National Institute on Aging held an exploratory workshop titled “Sensory and Motor Dysfunctions in Aging and AD.” The scientific sessions of the workshop focused on age‐related and neuropathologic changes in the olfactory, visual, auditory, and motor systems, followed by extensive discussion and hypothesis generation related to the possible links among sensory, cognitive, and motor domains in aging and AD. Based on the data presented and discussed at this workshop, it is clear that sensory and motor regions of the central nervous system are affected by AD pathology and that interventions targeting amelioration of sensory‐motor deficits in AD may enhance patient function as AD progresses.

Covariance PET patterns in early Alzheimer's disease and subjects with cognitive impairment but no dementia: utility in group discrimination and correlations with functional performance.

Although multivariate analytic techniques might identify diagnostic patterns that are not captured by univariate methods, they have rarely been used to study the neural correlates of Alzheimers disease (AD) or cognitive impairment. Nonquantitative H2(15)O PET scans were acquired during rest in 17 probable AD subjects selected for mild severity [mean-modified Mini Mental Status Examination (mMMS) 46/57; SD 5.1], 16 control subjects (mMMS 54; SD 2.5) and 23 subjects with minimal to mild cognitive impairment but no dementia (mMMS 53; SD 2.8). Expert clinical reading had low success in discriminating AD and controls. There were no significant mean flow differences among groups in traditional univariate SPM Noxel-wise analyses or region of interest (ROI) analyses. A covariance pattern was identified whose mean expression was significantly higher in the AD as compared to controls (P = 0.03; sensitivity 76-94%; specificity 63-81%). Sites of increased concomitant flow included insula, cuneus, pulvinar, lingual, fusiform, superior occipital and parahippocampal gyri, whereas decreased concomitant flow was found in cingulate, inferior parietal lobule, middle and inferior frontal, supramarginal and precentral gyri. The covariance analysis-derived pattern was then prospectively applied to the cognitively impaired subjects: as compared to subjects with Clinical Dementia Rating (CDR) = 0, subjects with CDR = 0.5 had significantly higher mean covariance pattern expression (P = 0.009). Expression of this pattern correlated inversely with Selective Reminding Test total recall (r = -0.401, P = 0.002), delayed recall (r = -0.351, P = 0.008) and mMMS scores (r = -0.401, P = 0.002) in all three groups combined. We conclude that patients with AD may differentially express resting cerebral blood flow covariance patterns even at very early disease stages. Significant alterations in expression of resting flow covariance patterns occur even for subjects with cognitive impairment. Expression of covariance patterns correlates with cognitive and functional performance measures, holding promise for meaningful associations with underlying biopathological processes.

MRI hippocampal and entorhinal cortex mapping in predicting conversion to Alzheimer's disease ☆

OBJECTIVE Using MRI surface morphometry mapping, to evaluate local deformations of the hippocampus, parahippocampal gyrus, and entorhinal cortex in predicting conversion from mild cognitive impairment (MCI) to Alzheimers disease (AD). METHODS Baseline brain MRI with surface morphological analysis was performed in 130 outpatients with MCI, broadly defined, and 61 healthy controls followed for an average of 4 years in a single site study. RESULTS Patients with MCI differed from controls in several regions of the hippocampus and entorhinal cortex, and to a lesser extent in the parahippocampal gyrus. In the MCI sample, Cox regression models were conducted for time to conversion comparing converters to AD (n=31) and non-converters (n=99), controlling for age, sex and education. Converters showed greater atrophy in the head of the hippocampus, predominantly in the CA1 region and subiculum, and in the entorhinal cortex, especially in the anterior-inferior pole bilaterally. When distances of specific points representing localized inward deformation were entered together with the corresponding hippocampal or entorhinal cortex volume in the same Cox regression model, the distances remained highly significant whereas the volumes of the corresponding structures were either marginally significant or not significant. Inclusion of cognitive or memory measures or apolipoprotein E ε4 genotype as covariates, or restricting the sample to patients with amnestic MCI (24 converters and 81 non-converters) did not materially change the findings. In the 3-year follow-up sample of patients with MCI, logistic regression analyses using the same measures and covariates yielded similar results. INTERPRETATION These findings indicate selective early involvement of the CA1 and subiculum regions of the hippocampus and provide new information on early anterior pole involvement in the entorhinal cortex in incipient AD. Fine-grained surface morphometry of medial temporal lobe structures may be superior to volumetric assessment in predicting conversion to AD in patients clinically diagnosed with MCI.

Antidepressant Medication and Executive Dysfunction: A Deleterious Interaction in Late-Life Depression

OBJECTIVES To determine whether there is differential response to placebo or citalopram among older patients with and without deficient response inhibition (DRI). DESIGN This is an 8-week, double-blind, placebo-controlled trial. SETTING Outpatient psychiatry. PARTICIPANTS Unipolar depressed patients aged 75 years and older. INTERVENTION Citalopram (20-40 mg/day) or placebo pill. MEASUREMENTS Baseline Stroop Color-Word Test and weekly 24-item Hamilton Rating Scale for Depression assessments. RESULTS Citalopram-treated patients with DRI did significantly worse than placebo-treated patients with DRI. Conversely, citalopram-treated patients without DRI did significantly better than placebo-treated patients without DRI. CONCLUSION Patients with late-life depression and DRI respond worse to selective serotonin reuptake inhibitor (SSRI) than placebo. These findings suggest that there may be a deleterious interaction between DRI and antidepressant medication in late-life depression and that the mechanism of SSRI and placebo response is different.

Depressive Symptoms, Antidepressant Use, and Brain Volumes on MRI in a Population-Based Cohort of Old Persons Without Dementia

We examined whether late-life depression, including depressive symptoms and antidepressant use, was associated with smaller total brain volume, smaller hippocampal volume, and larger white matter hyperintensity (WMH) volume in a large community-based cohort of old persons without dementia. Within the Washington/Hamilton Height-Inwood Columbia Aging Project (WHICAP), a community-based cohort study in northern Manhattan, 630 persons without dementia (mean age 80 years, SD = 5) had volumetric measures of the total brain, hippocampus, and WMH at 1.5 Tesla MRI and data on current depression, defined as a score of 4 or higher on the 10-item Center for Epidemiologic Studies-Depression (CES-D) scale, or use of antidepressants. Multiple linear regression analyses adjusted for age, gender, ethnicity, education, cardiovascular disease history, and MRI parameters showed that subjects with current depression had smaller relative total brain volume (B = -0.86%; 95% CI -1.68 to -0.05%; p < 0.05), smaller relative hippocampal volume (B = -0.07 ml; 95% CI -0.14 to 0.00 ml; p = 0.05), and larger relative WMH volume (natural logtransformed B = 0.19 ml; 95% CI 0.02 to 0.35 ml; p < 0.05). When examined separately, antidepressant use was significantly associated with smaller total brain, smaller hippocampal, and larger WMH volume, while high CES-D scores were not significantly associated with any of the brain measures, although the direction of association was similar as for antidepressant use. With the caveat that analyses were cross-sectional and we had no formal diagnosis of depression, our findings suggest that in this community-based sample of old persons without dementia, late-life depression is associated with more brain atrophy and more white matter lesions, which was mainly driven by antidepressant use.

Voxel-Based Analysis of 11C-PIB Scans for Diagnosing Alzheimer's Disease

The positron emission tomography (PET) radioligand N-methyl-11C-2-(4-methylaminophenyl)-6-hydroxybenzothiazole (also known as 11C-6-OH-BTA-1 or 11C-PIB) binds to amyloid-β (Aβ), which accumulates pathologically in Alzheimers disease (AD). Although 11C-PIB accumulation is greater in patients with AD than in healthy controls at a group level, the optimal method for discriminating between these 2 groups has, to our knowledge, not been established. We assessed the use of data-determined standardized voxels of interest (VOIs) to improve the classification capability of 11C-PIB scans on patients with AD. Methods: A total of 16 controls and 14 AD age-matched patients were recruited. All subjects underwent a 11C-PIB scan and structural MRI. Binding potential (a measure of amyloid burden) was calculated for each voxel using the Logan graphical method with cerebellar gray matter as the reference region. Voxel maps were then partial-volume corrected and spatially normalized by MRI onto a standardized template. The subjects were divided into 2 cohorts. The first cohort (control, 12; AD, 9) was used for statistical parametric mapping analysis and delineation of data-based VOIs. These VOIs were tested in the second cohort (control, 4; AD, 5) of subjects. Results: Statistical parametric mapping analysis revealed significant differences between control and AD groups. The VOI map determined from the first cohort resulted in complete separation between the control and the AD subjects in the second cohort (P < 0.02). Binding potential values based on this VOI were in the same range as other reported individual and mean cortical VOI results. Conclusion: A standardized VOI template that is optimized for control or AD group discrimination provides excellent separation of control and AD subjects on the basis of 11C-PIB uptake. This VOI template can serve as a potential replacement for manual VOI delineation and can eventually be fully automated, facilitating potential use in a clinical setting. To facilitate independent analysis and validation with more and a broader variety of subjects, this VOI template and the software for processing will be made available through the Internet.

Olfactory identification deficits and increased mortality in the community.

To examine the association between odor identification deficits and future mortality in a multiethnic community cohort of older adults.

Provisional diagnostic criteria for depression of Alzheimer's disease: description and review.

This review centers on the development of diagnostic criteria for depression of Alzheimer’s disease. It describes: risk-factors and neurobiological correlates, epidemiology, clinical characteristics and course, assessment, treatment, economics, a description of the criteria and future research directions. Overall, there is substantial evidence for depression of Alzheimer’s disease. Further research is needed to better define core symptoms, clinical course and efficacy of treatments.