Faculty Bibliography

OBJECTIVES: structural abnormalities in the hippocampus have been implicated in the pathophysiology of major depressive disorder (MDD). The brain-derived neurotrophic factor (BDNF) val66met polymorphism may contribute to these abnormalities and therefore confer vulnerability to MDD. This study examined whether there is a relationship among BDNF genotype, hippocampal volumes, and MDD in older adults. METHODS: thirty-three older adults with MDD and 23 psychiatrically normal comparison subjects were studied. Structural magnetic resonance imaging analysis was used to quantify hippocampal volumes. A repeated-measures analysis of covariance examined the relationships among BDNF val66met (val/val, met carrier), diagnosis (depressed, nondepressed), and hippocampal volumes (right, left). Age, gender, education, and whole brain volume were included as covariates. RESULTS: elderly MDD BDNF val/val homozygotes had significantly higher right hippocampal volumes compared with nondepressed val/val subjects. However, there was no difference between the depressed and healthy nondepressed met carriers. In addition, depressed met carriers had an earlier age of onset of depressive illness than val/val homozygotes, but age of onset did not moderate the relationship between hippocampal volumes and MDD diagnosis. CONCLUSION: these results provide preliminary evidence of a neuroprotective role of the val/val genotype, suggesting that neurotrophic factor production protects against pathophysiological processes triggered by depression in older adults with later age of onset of MDD. The BDNF val66met polymorphism may play a salient role in structural alterations of the hippocampus in older adults with MDD

BACKGROUND: White matter abnormalities may interfere with limbic-cortical balance and contribute to chronic depressive syndromes in the elderly. This study sought to clarify the relationship of SH to treatment response. We hypothesized that patients who failed to remit during a 12-week controlled treatment trial of escitalopram would exhibit greater SH burden than patients who remitted. METHODS: The participants were 42 non-demented individuals with non-psychotic major depression and 25 elderly comparison subjects. After a 2-week single blind placebo period, subjects who still had a Hamilton Depression Rating Scale (HDRS) of 18 or greater received escitalopram 10mg daily for 12 weeks. Remission was defined as a HDRS score of 7 or below for 2 consecutive weeks. FLAIR sequences were acquired on a 1.5 T scanner and total SH were quantified using a semi-automated thresholding method. RESULTS: The patient sample consisted of 22 depressed patients who achieved remission during the study and 20 depressed patients who remained symptomatic. ANCOVA, with age and gender as covariates, revealed that depressed subjects had greater total SH burden relative to non-depressed controls. Furthermore, patients who failed to remit following escitalopram treatment had significantly greater SH burden than both patients who remitted and elderly comparison subjects, whereas SH burden did not differ between depressed patients who remitted and elderly comparison subjects. LIMITATIONS: Patients were treated with a fixed dose of antidepressants and the index of SH is an overall measure that does not permit examination of the relationship of regional SH to treatment remission. DISCUSSION: SH may contribute to a 'disconnection state' both conferring vulnerability to and perpetuating late-life depression

A significant proportion of patients with schizophrenia demonstrate abnormalities in dorsal prefrontal regions including the dorsolateral prefrontal and dorsal anterior cingulate cortices. However, it is less clear to what extent abnormalities are exhibited in ventral prefrontal and limbic regions, despite their involvement in social cognitive dysfunction and aggression, which represent problem domains for patients with schizophrenia. Previously, we found that reduced white matter integrity in right inferior frontal regions was associated with higher levels of aggression. Here, we used resting-state functional magnetic resonance imaging to examine amygdala/ventral prefrontal cortex (vPFC) functional connectivity (FC) and its relation to aggression in schizophrenia. Twenty-one healthy controls and 25 patients with schizophrenia or schizoaffective disorder participated. Aggression was measured using the Buss Perry Aggression Questionnaire. Regions of interest were placed in the amygdala based on previously published work. A voxelwise FC analysis was performed in which the mean time series across voxels for this bilateral amygdala seed was entered as a predictor in a multiple regression model with motion parameters and global, cerebrospinal fluid, and white matter signals as covariates. Patients showed significant reductions in FC between amygdala and vPFC regions. Moreover, in patients, the strength of this connection showed a significant inverse relationship with aggression, such that lower FC was associated with higher levels of self-rated aggression. Similar results were obtained for 2 other measures--Life History of Aggression and total arrests. These results suggest that amygdala/vPFC FC is compromised in schizophrenia and that this compromise is associated with aggression

OBJECTIVE: The polymorphism BDNF val66met of the brain derived neurotrophic factor (BDNF) is common, may increase the risk for depression, and affects BDNF secretion, critical for neuronal survival, plasticity, neurogenesis, and synaptic connectivity. Our objectives were: 1) to test the hypothesis that BDNF(val/met) status influences the remission rate of geriatric depression; 2) to explore whether the relationship between BDNF allelic status to remission is influenced by the presence of microstructural white matter abnormalities. METHOD: Non-demented older subjects with major depression had a 2-week placebo period, after which those with a Hamilton Depression Rating Scale (HDRS) of 18 or greater received escitalopram 10 mg daily for 12 weeks. Fractional anisotropy was determined in specific regions using the Reproducible Object Quantification Scheme (ROQS) software that operates on non-normalized data. RESULTS: BDNF(met) carriers were more likely to achieve remission than BDNF(val/val) homozygotes after 12 weeks of treatment with escitalopram 10 mg daily. Microstructural abnormalities in the corpus callosum, left superior corona radiata, and right inferior longitudinal fasciculum were also associated with lower remission rate. However, there were no significant interactions between BDNF(val66met) status and microstructural abnormalities in predicting remission. LIMITATIONS: Small number of subjects, focus on a single BDNF polymorphism, fixed antidepressant dose. CONCLUSIONS: Depressed older BDNF(met) carriers had a higher remission rate than BDNF(val/val) homozygotes. This effect was not related to microstructural white matter abnormalities, which predicted remission independently. We speculate that the relationship between BDNF(val66met) and remission is due to different effects of BDNF in brain structures related to mood regulation

Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis' demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved, cost-effective fMRI denoising procedures

Recent genetics research focusing on schizophrenia has led to candidate cognitive and neuroimaging variables as intermediate phenotypes or 'endophenotype' markers for the illness. Among other stringent criteria, to be an endophenotype, a marker must demonstrate heritability. In an effort to explore the validity of a selection of cognitive and neuroimaging endophenotypes, the present study was designed to determine estimates of their heritability. One hundred fourteen subjects, including 27 with schizophrenia and 39 unaffected relatives from 23 multiplex schizophrenia families, participated in a comprehensive neuropsychological test battery and structural brain imaging with diffusion tensor imaging (DTI). Variables were selected if they previously have been demonstrated to show differences between people with schizophrenia and normal controls. Significant evidence of heritability was confirmed for overall cognitive function ('g'), as well as expressive and receptive language, verbal and visual memory, processing speed and cognitive inhibition. In addition, significant heritability estimates were determined for specific regions in the frontal, central, parietal, and occipital areas. These results suggest that the variables chosen may be useful endophenotypes for genetic and early detection studies, although further work with larger cohorts should be conducted to show that deficits in these functions and structures also segregate with schizophrenia within families and thus fully satisfy the definition of an endophenotype. In addition, other cognitive and neuroimaging variables that were not studied here may be candidates for schizophrenia endophenotypes

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's 'functional connectome.' Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/