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      Alterations in metabolic pathways and networks in Alzheimer's disease

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          Abstract

          The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD ( n=40), mild cognitive impairment (MCI, n=36) and control ( n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.

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          Innovation: Metabolomics: the apogee of the omics trilogy.

          Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and are shaping our understanding of cell biology, physiology and medicine.
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            Glutathione dysregulation and the etiology and progression of human diseases.

            Glutathione (GSH) plays an important role in a multitude of cellular processes, including cell differentiation, proliferation, and apoptosis, and as a result, disturbances in GSH homeostasis are implicated in the etiology and/or progression of a number of human diseases, including cancer, diseases of aging, cystic fibrosis, and cardiovascular, inflammatory, immune, metabolic, and neurodegenerative diseases. Owing to the pleiotropic effects of GSH on cell functions, it has been quite difficult to define the role of GSH in the onset and/or the expression of human diseases, although significant progress is being made. GSH levels, turnover rates, and/or oxidation state can be compromised by inherited or acquired defects in the enzymes, transporters, signaling molecules, or transcription factors that are involved in its homeostasis, or from exposure to reactive chemicals or metabolic intermediates. GSH deficiency or a decrease in the GSH/glutathione disulfide ratio manifests itself largely through an increased susceptibility to oxidative stress, and the resulting damage is thought to be involved in diseases, such as cancer, Parkinson's disease, and Alzheimer's disease. In addition, imbalances in GSH levels affect immune system function, and are thought to play a role in the aging process. Just as low intracellular GSH levels decrease cellular antioxidant capacity, elevated GSH levels generally increase antioxidant capacity and resistance to oxidative stress, and this is observed in many cancer cells. The higher GSH levels in some tumor cells are also typically associated with higher levels of GSH-related enzymes and transporters. Although neither the mechanism nor the implications of these changes are well defined, the high GSH content makes cancer cells chemoresistant, which is a major factor that limits drug treatment. The present report highlights and integrates the growing connections between imbalances in GSH homeostasis and a multitude of human diseases.
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              Partial Correlation Estimation by Joint Sparse Regression Models.

              In this paper, we propose a computationally efficient approach -space(Sparse PArtial Correlation Estimation)- for selecting non-zero partial correlations under the high-dimension-low-sample-size setting. This method assumes the overall sparsity of the partial correlation matrix and employs sparse regression techniques for model fitting. We illustrate the performance of space by extensive simulation studies. It is shown that space performs well in both non-zero partial correlation selection and the identification of hub variables, and also outperforms two existing methods. We then apply space to a microarray breast cancer data set and identify a set of hub genes which may provide important insights on genetic regulatory networks. Finally, we prove that, under a set of suitable assumptions, the proposed procedure is asymptotically consistent in terms of model selection and parameter estimation.
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                Author and article information

                Journal
                Transl Psychiatry
                Transl Psychiatry
                Translational Psychiatry
                Nature Publishing Group
                2158-3188
                April 2013
                09 April 2013
                1 April 2013
                : 3
                : 4
                : e244
                Affiliations
                [1 ]Department of Psychiatry and Behavioral Sciences, Duke University , Durham, NC, USA
                [2 ]Duke Institute for Brain Sciences, Duke University , Durham, NC, USA
                [3 ]Department of Systems Biochemistry, Bedford VA Medical Center , Bedford, MA, USA
                [4 ]Weil Medical College, Cornell University , New York, NY, USA
                [5 ]Program in Neurobiology and Behavioral Disorders, Duke-NUS Graduate Medical School , Singapore, Singapore
                [6 ]Bioinformatics Research Center, Department of Statistics, North Carolina State University , Raleigh, NC, USA
                [7 ]Penn Memory Center, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, USA
                [8 ]Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, USA
                [9 ]Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, USA
                [10 ]Center for Neurodegenerative Disease Research, Institute on Aging and Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, USA
                [11 ]Department of Neurology, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA, USA
                Author notes
                [* ]Psychiatry and Behavioral Sciences, Duke University Medical Center , Box 3903, Durham, NC 27710, USA. E-mail: rima.kaddurahdaouk@ 123456duke.edu
                [12]

                Co-second authors.

                Article
                tp201318
                10.1038/tp.2013.18
                3641405
                23571809
                d4766aec-17dc-4fd9-96e8-4b9fdc281658
                Copyright © 2013 Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

                History
                : 04 October 2012
                : 07 December 2012
                : 01 January 2013
                Categories
                Original Article

                Clinical Psychology & Psychiatry
                alzheimer's disease,metabolomics,partial network reconstruction,pathway analysis

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