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Chen AM, Gajdošík M, Ahmed W, Ahn S, Babb JS, Blessing EM, Boutajangout A, de Leon MJ, Debure L, Gaggi N, Gajdošík M, George A, Ghuman M, Glodzik L, Harvey P, Juchem C, Marsh K, Peralta R, Rusinek H, Sheriff S, Vedvyas A, Wisniewski T, Zheng H, Osorio R, Kirov II. Retrospective analysis of Braak stage- and APOE4 allele-dependent associations between MR spectroscopy and markers of tau and neurodegeneration in cognitively unimpaired elderly. Neuroimage 2024; 297:120742. [PMID: 39029606 PMCID: PMC11404707 DOI: 10.1016/j.neuroimage.2024.120742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 06/28/2024] [Accepted: 07/16/2024] [Indexed: 07/21/2024] Open
Abstract
PURPOSE The pathological hallmarks of Alzheimer's disease (AD), amyloid, tau, and associated neurodegeneration, are present in the cortical gray matter (GM) years before symptom onset, and at significantly greater levels in carriers of the apolipoprotein E4 (APOE4) allele. Their respective biomarkers, A/T/N, have been found to correlate with aspects of brain biochemistry, measured with magnetic resonance spectroscopy (MRS), indicating a potential for MRS to augment the A/T/N framework for staging and prediction of AD. Unfortunately, the relationships between MRS and A/T/N biomarkers are unclear, largely due to a lack of studies examining them in the context of the spatial and temporal model of T/N progression. Advanced MRS acquisition and post-processing approaches have enabled us to address this knowledge gap and test the hypotheses, that glutamate-plus-glutamine (Glx) and N-acetyl-aspartate (NAA), metabolites reflecting synaptic and neuronal health, respectively, measured from regions on the Braak stage continuum, correlate with: (i) cerebrospinal fluid (CSF) p-tau181 level (T), and (ii) hippocampal volume or cortical thickness of parietal lobe GM (N). We hypothesized that these correlations will be moderated by Braak stage and APOE4 genotype. METHODS We conducted a retrospective imaging study of 34 cognitively unimpaired elderly individuals who received APOE4 genotyping and lumbar puncture from pre-existing prospective studies at the NYU Grossman School of Medicine between October 2014 and January 2019. Subjects returned for their imaging exam between April 2018 and February 2020. Metabolites were measured from the left hippocampus (Braak II) using a single-voxel semi-adiabatic localization by adiabatic selective refocusing sequence; and from the bilateral posterior cingulate cortex (PCC; Braak IV), bilateral precuneus (Braak V), and bilateral precentral gyrus (Braak VI) using a multi-voxel echo-planar spectroscopic imaging sequence. Pearson and Spearman correlations were used to examine the relationships between absolute levels of choline, creatine, myo-inositol, Glx, and NAA and CSF p-tau181, and between these metabolites and hippocampal volume or parietal cortical thicknesses. Covariates included age, sex, years of education, Fazekas score, and months between CSF collection and MRI exam. RESULTS There was a direct correlation between hippocampal Glx and CSF p-tau181 in APOE4 carriers (Pearson's r = 0.76, p = 0.02), but not after adjusting for covariates. In the entire cohort, there was a direct correlation between hippocampal NAA and hippocampal volume (Spearman's r = 0.55, p = 0.001), even after adjusting for age and Fazekas score (Spearman's r = 0.48, p = 0.006). This relationship was observed only in APOE4 carriers (Pearson's r = 0.66, p = 0.017), and was also retained after adjustment (Pearson's r = 0.76, p = 0.008; metabolite-by-carrier interaction p = 0.03). There were no findings in the PCC, nor in the negative control (late Braak stage) regions of the precuneus and precentral gyrus. CONCLUSIONS Our findings are in line with the spatially- and temporally-resolved Braak staging model of pathological severity in which the hippocampus is affected earlier than the PCC. The correlations, between MRS markers of synaptic and neuronal health and, respectively, T and N pathology, were found exclusively within APOE4 carriers, suggesting a connection with AD pathological change, rather than with normal aging. We therefore conclude that MRS has the potential to augment early A/T/N staging, with the hippocampus serving as a more sensitive MRS target compared to the PCC.
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Affiliation(s)
- Anna M Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA
| | - Martin Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Wajiha Ahmed
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Sinyeob Ahn
- Siemens Medical Solutions USA Inc., Malvern, PA, USA
| | - James S Babb
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Esther M Blessing
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Healthy Brain Aging and Sleep Center, NYU Langone Health, New York, NY, USA
| | - Allal Boutajangout
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA; Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Mony J de Leon
- Retired Director, Center for Brain Health, Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Ludovic Debure
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Naomi Gaggi
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Healthy Brain Aging and Sleep Center, NYU Langone Health, New York, NY, USA
| | - Mia Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Ajax George
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Mobeena Ghuman
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Lidia Glodzik
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Patrick Harvey
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Radiology, Columbia University, New York, NY, USA
| | - Karyn Marsh
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Rosemary Peralta
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alok Vedvyas
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Thomas Wisniewski
- Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA; Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
| | - Helena Zheng
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA
| | - Ricardo Osorio
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA; Healthy Brain Aging and Sleep Center, NYU Langone Health, New York, NY, USA.
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, USA; Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, USA; Center for Cognitive Neurology, Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA; Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA.
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Vidyasagar R, Fazollahi A, Desmond P, Moffat B, Bush AI, Ayton S. Single-session reproducibility of MR spectroscopy measures of glutathione in the mesial temporal lobe with MEGA-PRESS. J Neuroimaging 2024; 34:224-231. [PMID: 38174904 DOI: 10.1111/jon.13179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 12/03/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND AND PURPOSE Magnetic resonance spectroscopy (MRS) measures neurochemicals in vivo. Glutathione (GSH) is a neuroprotective chemical shown to vary significantly in patients with Alzheimer's disease (AD). This work investigates the reproducibility of GSH measures in the mesial temporal lobe (MTL) to identify its potential clinical utility. METHODS MRS data were acquired from eight healthy volunteers (31.1 ± 5.2 years; 4 male/female) using Mescher-Garwood-Point Resolved Spectroscopy (MEGA-PRESS) from the MTL in the left hemisphere across two scan sessions in the same visit. Total N-acetylaspartate (tNAA), choline (tCho), creatine (tCr), and GSH were quantified. Reproducibility of quantifications of these neurochemicals were tested using coefficient of variance (CV) between scan sessions. Reproducibility of voxel placement on the left MTL was calculated by measuring the tissue overlap and percent of hippocampus within that voxel. CV measured across different scan sessions in each individual, with a CV<15% was accepted as "good" reproducibility. Paired t-tests were carried out to establish the significant differences between the two scans across each individual with p<.05 as significant. RESULTS TNAA (%CV = 7.2; p = .5), tCr (%CV = 7.8; p = .6) and tCho (%CV = 9.3; p = .4), and GSH (%CV = 22; p = .1). The dice coefficient that reflects the level of overlap of hippocampal tissue in the voxel was shown to be 0.8 ± 0.1. Voxel tissue composition were: Scan 1 (cerebrospinal fluid [CSF]: 5 ± 1%, white matter [WM]: 52 ± 3%, gray matter [GM]: 43 ± 3%); Scan 2 (CSF: 5 ± 1%, WM: 52 ± 4%, GM: 44 ± 4%). CONCLUSION The data suggest measures of abundant metabolites in the MTL using the MEGA-PRESS sequence has a high reproducibility. Reproducibility of GSH in this area was poorer requiring care when interpreting measures of GSH in the MTL for clinical translational purposes.
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Affiliation(s)
- Rishma Vidyasagar
- Radiology Department, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Amir Fazollahi
- Radiology Department, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Patricia Desmond
- Radiology Department, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Bradford Moffat
- Melbourne Biomedical Centre Imaging Unit, Department of Radiology, Melbourne Medical School, University of Melbourne, Melbourne, Victoria, Australia
| | - Ashley I Bush
- The Florey Institute of Neuroscience and Mental Health and University of Melbourne, Melbourne, Victoria, Australia
| | - Scott Ayton
- The Florey Institute of Neuroscience and Mental Health and University of Melbourne, Melbourne, Victoria, Australia
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Gudmundson AT, Koo A, Virovka A, Amirault AL, Soo M, Cho JH, Oeltzschner G, Edden RAE, Stark CEL. Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease. Anal Biochem 2023; 676:115227. [PMID: 37423487 PMCID: PMC10561665 DOI: 10.1016/j.ab.2023.115227] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023]
Abstract
Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.
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Affiliation(s)
- Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Annie Koo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Anna Virovka
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Alyssa L Amirault
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Madelene Soo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Jocelyn H Cho
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA.
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