OBJECTIVES: The abnormal eating behaviors are revealed in neurodegenerative disease, especially frontotemporal dementia. Several studies have demonstrated that structural changes are related to functional changes in regulation of feeding. But areas in determining eating disorder in dementia remain unclear. We applied voxel-based morphometry (VBM) to assess brain tissue abnormalities in neurodegenerative patients with abnormal eating behaviors. METHODS: We assessed abnormal eating behaviors of sixty three patients with dementia using the modified Manchester Behavior Questionnaire. Volumetric brain magnetic resonance imaging was performed in all patients and gray matter changes were assessed using VBM. RESULTS: Dementia patients with eating problems showed gray matter loss predominantly involving right insula, right anterior cingulate, right superior medial frontal cortex, right orbitofrontal cortex. Overeats scores were associated with atrophy of right anterior cingulate, right superior orbitofrontal cortex, right superior medial frontal cortex, right insula, and right putamen. CONCLUSION: This results suggest that right orbitofrontal cortex, insula, anterior cingulate, striatum regions integrate sensory and motivational information regarding food. The dementia patients with abnormal eating behaviors may be explained by disruption of this integrating system.

OBJECTIVES: Obsessive-compulsive(OC) symptoms have yet to be directly studied in neurodegenerative conditions involving behavioral changes. To examine regional abnormalities in the brains of dementia patients with OC symptoms, we assessed the gray matter density using voxel-based morphometry(VBM). METHODS: We performed brain magnetic resonance imaging(MRI) with VBM analysis in 106 dementia patients with OC behaviors. In this study, OC behaviors were investigated in patients with neurodegenerative disease using the modified Manchester Behavior Questionnaire. RESULTS: The OC behavior scores were correlated with structural brain volume using VBM. The total OC symptom score correlated negatively with the volume of both putamens, the right middle orbitofrontal gyrus, both anterior cingulate cortices, and the left insula(p<0.001, uncorrected). No gray matter reductions were associated specifically with the OC symptom sub-categories. CONCLUSIONS: Our results suggest that abnormalities in these brain regions may play an important role in the pathophysiology of OCD in neurodegenerative disease. This is the first lesion study to investigate the neural basis of OCD behaviors in neurodegenerative disease.
Brain ; Dementia ; Humans ; Neurodegenerative Diseases* ; Putamen ; Questionnaires

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics com-munity. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.