Alterations in metabolic pathways and networks in Alzheimer’s disease
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 profil...
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Published in | Translational psychiatry Vol. 3; no. 4; p. e244 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
09.04.2013
Nature Publishing Group |
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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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AbstractList | 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.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. 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. 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. |
Author | Trojanowski, J Q Rozen, S G Doraiswamy, P M Bogdanov, M Arnold, S E Motsinger-Reif, A A Zhu, H Appleby, D Churchill, E Kling, M A Kaddurah-Daouk, R Matson, W Lei, Z Oki, N O Sharma, S |
Author_xml | – sequence: 1 givenname: R surname: Kaddurah-Daouk fullname: Kaddurah-Daouk, R email: rima.kaddurahdaouk@duke.edu organization: Department of Psychiatry and Behavioral Sciences, Duke University, Duke Institute for Brain Sciences, Duke University – sequence: 2 givenname: H surname: Zhu fullname: Zhu, H organization: Department of Psychiatry and Behavioral Sciences, Duke University – sequence: 3 givenname: S surname: Sharma fullname: Sharma, S organization: Department of Systems Biochemistry, Bedford VA Medical Center – sequence: 4 givenname: M surname: Bogdanov fullname: Bogdanov, M organization: Department of Psychiatry and Behavioral Sciences, Duke University, Weil Medical College, Cornell University – sequence: 5 givenname: S G surname: Rozen fullname: Rozen, S G organization: Program in Neurobiology and Behavioral Disorders, Duke-NUS Graduate Medical School – sequence: 6 givenname: W surname: Matson fullname: Matson, W organization: Department of Systems Biochemistry, Bedford VA Medical Center – sequence: 7 givenname: N O surname: Oki fullname: Oki, N O organization: Department of Statistics, Bioinformatics Research Center, North Carolina State University – sequence: 8 givenname: A A surname: Motsinger-Reif fullname: Motsinger-Reif, A A organization: Department of Statistics, Bioinformatics Research Center, North Carolina State University – sequence: 9 givenname: E surname: Churchill fullname: Churchill, E organization: Department of Psychiatry and Behavioral Sciences, Duke University – sequence: 10 givenname: Z surname: Lei fullname: Lei, Z organization: Program in Neurobiology and Behavioral Disorders, Duke-NUS Graduate Medical School – sequence: 11 givenname: D surname: Appleby fullname: Appleby, D organization: Penn Memory Center, Perelman School of Medicine, University of Pennsylvania – sequence: 12 givenname: M A surname: Kling fullname: Kling, M A organization: Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania – sequence: 13 givenname: J Q surname: Trojanowski fullname: Trojanowski, J Q organization: Institute on Aging and Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania – sequence: 14 givenname: P M surname: Doraiswamy fullname: Doraiswamy, P M organization: Department of Psychiatry and Behavioral Sciences, Duke University, Duke Institute for Brain Sciences, Duke University – sequence: 15 givenname: S E surname: Arnold fullname: Arnold, S E organization: Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Department of Neurology, Perelman School of Medicine, University of Pennsylvania |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23571809$$D View this record in MEDLINE/PubMed |
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Keywords | partial network reconstruction pathway analysis metabolomics Alzheimer's disease |
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Publisher | Nature Publishing Group UK Nature Publishing Group |
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SubjectTerms | 631/378/2649 631/443/376 631/45/320 692/699/375/365/1283 Aged Aged, 80 and over Alzheimer Disease - cerebrospinal fluid Alzheimer Disease - metabolism Alzheimer's disease Behavioral Sciences Biological Psychology Biomarkers - cerebrospinal fluid Case-Control Studies Chromatography, Liquid Cognitive Dysfunction - cerebrospinal fluid Cognitive Dysfunction - metabolism Female Humans Male Medicine Medicine & Public Health Metabolic Networks and Pathways Metabolomics Middle Aged Neuropsychological Tests Neurosciences Original original-article Pharmacotherapy Prospective Studies Psychiatry |
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