Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults
IntroductionIntegrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic...
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2021.796067/full |
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| author | Ronald C. Eldridge Karan Uppal Mahsa Shokouhi M. Ryan Smith Xin Hu Zhaohui S. Qin Dean P. Jones Ihab Hajjar |
| author_facet | Ronald C. Eldridge Karan Uppal Mahsa Shokouhi M. Ryan Smith Xin Hu Zhaohui S. Qin Dean P. Jones Ihab Hajjar |
| author_sort | Ronald C. Eldridge |
| collection | DOAJ |
| description | IntroductionIntegrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a “metabolic map” of the brain in prodromal AD.MethodsIn 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.ResultsThe multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).ConclusionBy integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches. |
| first_indexed | 2024-12-20T10:28:13Z |
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| id | doaj.art-d9ed96ecf70c489c905dfa652a01582d |
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| language | English |
| last_indexed | 2024-12-20T10:28:13Z |
| publishDate | 2022-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-d9ed96ecf70c489c905dfa652a01582d2022-12-21T19:43:47ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652022-01-011310.3389/fnagi.2021.796067796067Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired AdultsRonald C. Eldridge0Karan Uppal1Mahsa Shokouhi2M. Ryan Smith3Xin Hu4Zhaohui S. Qin5Dean P. Jones6Ihab Hajjar7Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, United StatesDivision of Pulmonary, Allergy, Critical Care, and Sleep Medicine, School of Medicine, Emory University, Atlanta, GA, United StatesDepartment of Neurology, School of Medicine, Emory University, Atlanta, GA, United StatesDivision of Pulmonary, Allergy, Critical Care, and Sleep Medicine, School of Medicine, Emory University, Atlanta, GA, United StatesDivision of Pulmonary, Allergy, Critical Care, and Sleep Medicine, School of Medicine, Emory University, Atlanta, GA, United StatesDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, United StatesDivision of Pulmonary, Allergy, Critical Care, and Sleep Medicine, School of Medicine, Emory University, Atlanta, GA, United StatesDepartment of Neurology, School of Medicine, Emory University, Atlanta, GA, United StatesIntroductionIntegrating brain imaging with large scale omics data may identify novel mechanisms of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We integrated and analyzed brain magnetic resonance imaging (MRI) with cerebrospinal fluid (CSF) metabolomics to elucidate metabolic mechanisms and create a “metabolic map” of the brain in prodromal AD.MethodsIn 145 subjects (85 cognitively normal controls and 60 with MCI), we derived voxel-wise gray matter volume via whole-brain structural MRI and conducted high-resolution untargeted metabolomics on CSF. Using a data-driven approach consisting of partial least squares discriminant analysis, a multiomics network clustering algorithm, and metabolic pathway analysis, we described dysregulated metabolic pathways in CSF mapped to brain regions associated with MCI in our cohort.ResultsThe multiomics network algorithm clustered metabolites with contiguous imaging voxels into seven distinct communities corresponding to the following brain regions: hippocampus/parahippocampal gyrus (three distinct clusters), thalamus, posterior thalamus, parietal cortex, and occipital lobe. Metabolic pathway analysis indicated dysregulated metabolic activity in the urea cycle, and many amino acids (arginine, histidine, lysine, glycine, tryptophan, methionine, valine, glutamate, beta-alanine, and purine) was significantly associated with those regions (P < 0.05).ConclusionBy integrating CSF metabolomics data with structural MRI data, we linked specific AD-susceptible brain regions to disrupted metabolic pathways involving nitrogen excretion and amino acid metabolism critical for cognitive function. Our findings and analytical approach may extend drug and biomarker research toward more multiomics approaches.https://www.frontiersin.org/articles/10.3389/fnagi.2021.796067/fullMRI imagingmetabolomics (OMICS)multiomics analysismild cognition impairmentamino acids (AA)Alzheimer’s disease |
| spellingShingle | Ronald C. Eldridge Karan Uppal Mahsa Shokouhi M. Ryan Smith Xin Hu Zhaohui S. Qin Dean P. Jones Ihab Hajjar Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults Frontiers in Aging Neuroscience MRI imaging metabolomics (OMICS) multiomics analysis mild cognition impairment amino acids (AA) Alzheimer’s disease |
| title | Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults |
| title_full | Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults |
| title_fullStr | Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults |
| title_full_unstemmed | Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults |
| title_short | Multiomics Analysis of Structural Magnetic Resonance Imaging of the Brain and Cerebrospinal Fluid Metabolomics in Cognitively Normal and Impaired Adults |
| title_sort | multiomics analysis of structural magnetic resonance imaging of the brain and cerebrospinal fluid metabolomics in cognitively normal and impaired adults |
| topic | MRI imaging metabolomics (OMICS) multiomics analysis mild cognition impairment amino acids (AA) Alzheimer’s disease |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2021.796067/full |
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