Homa Seyedmirzaei, Amirhossein Salmannezhad, Hamidreza Ashayeri, Ali Shushtari, Bita Farazinia, Mohammad Mahdi Heidari, Amirali Momayezi, Sara Shaki Baher
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引用次数: 0
Abstract
Growth-associated protein 43 (GAP-43) is found in the axonal terminal of neurons in the limbic system, which is affected in people with Alzheimer’s disease (AD). We assumed GAP-43 may contribute to AD progression and serve as a biomarker. So, in a two-year follow-up study, we assessed GAP-43 changes and whether they are correlated with tensor-based morphometry (TBM) findings in patients with mild cognitive impairment (MCI). We included MCI and cognitively normal (CN) people with available baseline and follow-up cerebrospinal fluid (CSF) GAP-43 and TBM findings from the ADNI database. We assessed the difference between the two groups and correlations in each group at each time point. CSF GAP-43 and TBM measures were similar in the two study groups in all time points, except for the accelerated anatomical region of interest (ROI) of CN subjects that were significantly greater than those of MCI. The only significant correlations with GAP-43 observed were those inverse correlations with accelerated and non-accelerated anatomical ROI in MCI subjects at baseline. Plus, all TBM metrics decreased significantly in all study groups during the follow-up in contrast to CSF GAP-43 levels. Our study revealed significant associations between CSF GAP-43 levels and TBM indices among people of the AD spectrum.
期刊介绍:
Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.