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Articles by J. H Kramer
Total Records ( 3 ) for J. H Kramer
  H Lavretsky , L Zheng , M. W Weiner , D Mungas , B Reed , J. H Kramer , W Jagust , H Chui and W. J. Mack
  Objective

The authors examined predictors of mortality in individuals age 50 or older with or without cognitive impairment in a 12-year prospective naturalistic study of subcortical ischemic vascular disease focusing on symptoms of depressed mood, apathy, anhedonia, or anergia.

Method

A total of 498 participants were recruited from the community and from memory clinics into a multicenter longitudinal study of subcortical ischemic vascular disease. For baseline cognitive status, 36% of participants were assessed as cognitively intact, 31% as cognitively impaired, and 33% as demented. All participants underwent a research protocol MRI, and 41% were classified as having subcortical lacunes. Depressed mood, anhedonia, anergia, and apathy were assessed at baseline using a structured behavioral assessment. Cox regression models were used to investigate the associations between neuropsychiatric symptoms and mortality, controlling for age, gender, race, education level, cognitive status, presence of vascular lacunes, and vascular risk factors.

Results

Of 498 participants, 175 (35%) died over the follow-up period, with a median survival time of 5.6 years. In the multivariate analyses, cognitive impairment, age, male gender, depressed mood, and the presence of lacunes predicted higher mortality. Participants with both lacunes and depressed mood had the shortest survival among all cognitive groups. The mortality hazard ratio for participants with depressed mood was 2.2 (95% CI=1.5–3.2) after adjustment for cognitive status, age, gender, education level, race, lacunes, and all vascular conditions.

Conclusions

These findings suggest the importance of detecting depressed mood in individuals with cerebrovascular disease and of developing more aggressive treatment and preventive interventions for this vulnerable population.

  Y Zhang , N Schuff , A. T Du , H. J Rosen , J. H Kramer , M. L Gorno Tempini , B. L Miller and M. W. Weiner
 

Frontotemporal dementia (FTD) and Alzheimer's disease are sometimes difficult to differentiate clinically because of overlapping symptoms. Using diffusion tensor imaging (DTI) measurements of fractional anisotropy (FA) can be useful in distinguishing the different patterns of white matter degradation between the two dementias. In this study, we performed MRI scans in a 4 Tesla MRI machine including T1-weighted structural images and diffusion tensor images in 18 patients with FTD, 18 patients with Alzheimer's disease and 19 cognitively normal (CN) controls. FA was measured selectively in specific fibre tracts (including corpus callosum, cingulum, uncinate and corticospinal tracts) as well as globally in a voxel-by-voxel analysis. Patients with FTD were associated with reductions of FA in frontal and temporal regions including the anterior corpus callosum (P < 0.001), bilateral anterior (left P < 0.001; right P = 0.005), descending (left P < 0.001; right P = 0.003) cingulum tracts, and uncinate tracts (left P < 0.001; right P = 0.005), compared to controls. Patients with Alzheimer's disease were associated with reductions of FA in parietal, temporal and frontal regions including the left anterior (P = 0.003) and posterior (P = 0.002) cingulum tracts, bilateral descending cingulum tracts (P < 0.001) and left uncinate tracts (P < 0.001) compared to controls. When compared with Alzheimer's disease, FTD was associated with greater reductions of FA in frontal brain regions, whereas no region in Alzheimer's disease showed greater reductions of FA when compared to FTD. In conclusion, the regional patterns of anisotropy reduction in FTD and Alzheimer's disease compared to controls suggest a characteristic distribution of white matter degradation in each disease. Moreover, the white matter degradation seems to be more prominent in FTD than in Alzheimer's disease. Taken together, the results suggest that white matter degradation measured with DTI may improve the diagnostic differentiation between FTD and Alzheimer's disease.

  J Zhou , M. D Greicius , E. D Gennatas , M. E Growdon , J. Y Jang , G. D Rabinovici , J. H Kramer , M Weiner , B. L Miller and W. W. Seeley
 

Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer’s disease cause atrophy within two major networks, an anterior ‘Salience Network’ (atrophied in behavioural variant frontotemporal dementia) and a posterior ‘Default Mode Network’ (atrophied in Alzheimer’s disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer’s disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer’s disease) and the Default Mode Network (disrupted in Alzheimer’s disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer’s disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer’s disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer’s disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal ‘test’ patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer’s disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring.

 
 
 
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