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Khodanovich M, Naumova A, Kamaeva D, Obukhovskaya V, Vasilieva S, Schastnyy E, Kataeva N, Levina A, Kudabaeva M, Pashkevich V, Moshkina M, Tumentceva Y, Svetlik M. Neurocognitive Changes in Patients with Post-COVID Depression. J Clin Med 2024; 13:1442. [PMID: 38592295 PMCID: PMC10933987 DOI: 10.3390/jcm13051442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 02/16/2024] [Accepted: 02/20/2024] [Indexed: 04/10/2024] Open
Abstract
Background: Depression and cognitive impairment are recognized complications of COVID-19. This study aimed to assess cognitive performance in clinically diagnosed post-COVID depression (PCD, n = 25) patients using neuropsychological testing. Methods: The study involved 71 post-COVID patients with matched control groups: recovered COVID-19 individuals without complications (n = 18) and individuals without prior COVID-19 history (n = 19). A post-COVID depression group (PCD, n = 25) was identified based on psychiatric diagnosis, and a comparison group (noPCD, n = 46) included participants with neurological COVID-19 complications, excluding clinical depression. Results: The PCD patients showed gender-dependent significant cognitive impairment in the MoCA, Word Memory Test (WMT), Stroop task (SCWT), and Trail Making Test (TMT) compared to the controls and noPCD patients. Men with PCD showed worse performances on the SCWT, in MoCA attention score, and on the WMT (immediate and delayed word recall), while women with PCD showed a decline in MoCA total score, an increased processing time with less errors on the TMT, and worse immediate recall. No differences between groups in Sniffin's stick test were found. Conclusions: COVID-related direct (post-COVID symptoms) and depression-mediated (depression itself, male sex, and severity of COVID-19) predictors of decline in memory and information processing speed were identified. Our findings may help to personalize the treatment of depression, taking a patient's gender and severity of previous COVID-19 disease into account.
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Affiliation(s)
- Marina Khodanovich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
| | - Anna Naumova
- Department of Radiology, School of Medicine, South Lake Union Campus, University of Washington, 850 Republican Street, Seattle, WA 98109, USA;
| | - Daria Kamaeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
- Laboratory of Molecular Genetics and Biochemistry, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 4 Aleutskaya Street, Tomsk 634014, Russia
| | - Victoria Obukhovskaya
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
- Department of Fundamental Psychology and Behavioral Medicine, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 6340505, Russia
| | - Svetlana Vasilieva
- Department of Affective States, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 4 Aleutskaya Street, Tomsk 634014, Russia; (S.V.); (E.S.)
| | - Evgeny Schastnyy
- Department of Affective States, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 4 Aleutskaya Street, Tomsk 634014, Russia; (S.V.); (E.S.)
| | - Nadezhda Kataeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
- Department of Neurology and Neurosurgery, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 6340505, Russia
| | - Anastasia Levina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
- Medica Diagnostic and Treatment Center, 86 Sovetskaya Street, Tomsk 634510, Russia
| | - Marina Kudabaeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
| | - Valentina Pashkevich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
| | - Marina Moshkina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
| | - Yana Tumentceva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
| | - Mikhail Svetlik
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (D.K.); (V.O.); (N.K.); (A.L.); (M.K.); (V.P.); (M.M.); (Y.T.); (M.S.)
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Khodanovich M, Svetlik M, Naumova A, Kamaeva D, Usova A, Kudabaeva M, Anan’ina T, Wasserlauf I, Pashkevich V, Moshkina M, Obukhovskaya V, Kataeva N, Levina A, Tumentceva Y, Yarnykh V. Age-Related Decline in Brain Myelination: Quantitative Macromolecular Proton Fraction Mapping, T2-FLAIR Hyperintensity Volume, and Anti-Myelin Antibodies Seven Years Apart. Biomedicines 2023; 12:61. [PMID: 38255168 PMCID: PMC10812983 DOI: 10.3390/biomedicines12010061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/09/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Abstract
Age-related myelination decrease is considered one of the likely mechanisms of cognitive decline. The present preliminary study is based on the longitudinal assessment of global and regional myelination of the normal adult human brain using fast macromolecular fraction (MPF) mapping. Additional markers were age-related changes in white matter (WM) hyperintensities on FLAIR-MRI and the levels of anti-myelin autoantibodies in serum. Eleven healthy subjects (33-60 years in the first study) were scanned twice, seven years apart. An age-related decrease in MPF was found in global WM, grey matter (GM), and mixed WM-GM, as well as in 48 out of 82 examined WM and GM regions. The greatest decrease in MPF was observed for the frontal WM (2-5%), genu of the corpus callosum (CC) (4.0%), and caudate nucleus (5.9%). The age-related decrease in MPF significantly correlated with an increase in the level of antibodies against myelin basic protein (MBP) in serum (r = 0.69 and r = 0.63 for global WM and mixed WM-GM, correspondingly). The volume of FLAIR hyperintensities increased with age but did not correlate with MPF changes and the levels of anti-myelin antibodies. MPF mapping showed high sensitivity to age-related changes in brain myelination, providing the feasibility of this method in clinics.
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Affiliation(s)
- Marina Khodanovich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Mikhail Svetlik
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Anna Naumova
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
| | - Daria Kamaeva
- Laboratory of Molecular Genetics and Biochemistry, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk 634014, Russia;
| | - Anna Usova
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 12/1 Savinykh St., Tomsk 634009, Russia;
| | - Marina Kudabaeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Tatyana Anan’ina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Irina Wasserlauf
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Valentina Pashkevich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Marina Moshkina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Victoria Obukhovskaya
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Fundamental Psychology and Behavioral Medicine, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Nadezhda Kataeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Neurology and Neurosurgery, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Anastasia Levina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Medica Diagnostic and Treatment Center, 86 Sovetskaya st., Tomsk 634510, Russia
| | - Yana Tumentceva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
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Lawton W, Araujo O, Kufaishi Y. Language Environment and Infants' Brain Structure. J Neurosci 2023; 43:5129-5131. [PMID: 37438100 PMCID: PMC10342219 DOI: 10.1523/jneurosci.0787-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/05/2023] [Accepted: 06/08/2023] [Indexed: 07/14/2023] Open
Affiliation(s)
- Will Lawton
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Ozzy Araujo
- Undergraduate Life Sciences Program, Queen's University, Kingston, Ontario K7L 3N6, Canada
| | - Yousif Kufaishi
- Undergraduate Life Sciences Program, Queen's University, Kingston, Ontario K7L 3N6, Canada
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Soustelle L, Troalen T, Hertanu A, Ranjeva JP, Guye M, Varma G, Alsop DC, Duhamel G, Girard OM. Quantitative magnetization transfer MRI unbiased by on-resonance saturation and dipolar order contributions. Magn Reson Med 2023. [PMID: 37154400 DOI: 10.1002/mrm.29678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/22/2023] [Accepted: 04/01/2023] [Indexed: 05/10/2023]
Abstract
PURPOSE To demonstrate the bias in quantitative MT (qMT) measures introduced by the presence of dipolar order and on-resonance saturation (ONRS) effects using magnetization transfer (MT) spoiled gradient-recalled (SPGR) acquisitions, and propose changes to the acquisition and analysis strategies to remove these biases. METHODS The proposed framework consists of SPGR sequences prepared with simultaneous dual-offset frequency-saturation pulses to cancel out dipolar order and associated relaxation (T1D ) effects in Z-spectrum acquisitions, and a matched quantitative MT (qMT) mathematical model that includes ONRS effects of readout pulses. Variable flip angle and MT data were fitted jointly to simultaneously estimate qMT parameters (macromolecular proton fraction [MPF], T2,f , T2,b , R, and free pool T1 ). This framework is compared with standard qMT and investigated in terms of reproducibility, and then further developed to follow a joint single-point qMT methodology for combined estimation of MPF and T1 . RESULTS Bland-Altman analyses demonstrated a systematic underestimation of MPF (-2.5% and -1.3%, on average, in white and gray matter, respectively) and overestimation of T1 (47.1 ms and 38.6 ms, on average, in white and gray matter, respectively) if both ONRS and dipolar order effects are ignored. Reproducibility of the proposed framework is excellent (ΔMPF = -0.03% and ΔT1 = -19.0 ms). The single-point methodology yielded consistent MPF and T1 values with respective maximum relative average bias of -0.15% and -3.5 ms found in white matter. CONCLUSION The influence of acquisition strategy and matched mathematical model with regard to ONRS and dipolar order effects in qMT-SPGR frameworks has been investigated. The proposed framework holds promise for improved accuracy with reproducibility.
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Affiliation(s)
- Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | | | - Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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Pieczonka K, Khazaei M, Fehlings MG. Promoting the Differentiation of Neural Progenitor Cells into Oligodendrocytes through the Induction of Olig2 Expression: A Transcriptomic Study Using RNA-seq Analysis. Cells 2023; 12:cells12091252. [PMID: 37174652 PMCID: PMC10177465 DOI: 10.3390/cells12091252] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/28/2023] [Accepted: 04/17/2023] [Indexed: 05/15/2023] Open
Abstract
Oligodendrocytes are the myelinating cells of the central nervous system that facilitate efficient signal transduction. The loss of these cells and the associated myelin sheath can lead to profound functional deficits. Moreover, oligodendrocytes also play key roles in mediating glial-neuronal interactions, which further speaks to their importance in health and disease. Neural progenitor cells (NPCs) are a promising source of cells for the treatment of oligodendrocyte-related neurological diseases due to their ability to differentiate into a variety of cell types, including oligodendrocytes. However, the efficiency of oligodendrocyte differentiation is often low. In this study, we induced the expression of the Olig2 transcription factor in tripotent NPCs using a doxycycline-inducible promoter, such that the extent of oligodendrocyte differentiation could be carefully regulated. We characterized the differentiation profile and the transcriptome of these inducible oligodendrogenic NPCs (ioNPCs) using a combination of qRT-PCR, immunocytochemistry and RNA sequencing with gene ontology (GO) and gene set enrichment analysis (GSEA). Our results show that the ioNPCs differentiated into a significantly greater proportion of oligodendrocytes than the NPCs. The induction of Olig2 expression was also associated with the upregulation of genes involved in oligodendrocyte development and function, as well as the downregulation of genes involved in other cell lineages. The GO and GSEA analyses further corroborated the oligodendrocyte specification of the ioNPCs.
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Affiliation(s)
- Katarzyna Pieczonka
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Mohamad Khazaei
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Michael G Fehlings
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M5T 1P5, Canada
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Drobyshevsky A, Synowiec S, Goussakov I, Lu J, Gascoigne D, Aksenov DP, Yarnykh V. Temporal trajectories of normal myelination and axonal development assessed by quantitative macromolecular and diffusion MRI: Ultrastructural and immunochemical validation in a rabbit model. Neuroimage 2023; 270:119974. [PMID: 36848973 PMCID: PMC10103444 DOI: 10.1016/j.neuroimage.2023.119974] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023] Open
Abstract
INTRODUCTION Quantitative and non-invasive measures of brain myelination and maturation during development are of great importance to both clinical and translational research communities. While the metrics derived from diffusion tensor imaging, are sensitive to developmental changes and some pathologies, they remain difficult to relate to the actual microstructure of the brain tissue. The advent of advanced model-based microstructural metrics requires histological validation. The purpose of the study was to validate novel, model-based MRI techniques, such as macromolecular proton fraction mapping (MPF) and neurite orientation and dispersion indexing (NODDI), against histologically derived indexes of myelination and microstructural maturation at various stages of development. METHODS New Zealand White rabbit kits underwent serial in-vivo MRI examination at postnatal days 1, 5, 11, 18, and 25, and as adults. Multi-shell, diffusion-weighted experiments were processed to fit NODDI model to obtain estimates, intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Macromolecular proton fraction (MPF) maps were obtained from three source (MT-, PD-, and T1-weighted) images. After MRI sessions, a subset of animals was euthanized and regional samples of gray and white matter were taken for western blot analysis, to determine myelin basic protein (MBP), and electron microscopy, to estimate axonal, myelin fractions and g-ratio. RESULTS MPF of white matter regions showed a period of fast growth between P5 and P11 in the internal capsule, with a later onset in the corpus callosum. This MPF trajectory was in agreement with levels of myelination in the corresponding brain region, as assessed by western blot and electron microscopy. In the cortex, the greatest increase of MPF occurred between P18 and P26. In contrast, myelin, according to MBP western blot, saw the largest hike between P5 and P11 in the sensorimotor cortex and between P11 and P18 in the frontal cortex, which then seemingly plateaued after P11 and P18 respectively. G-ratio by MRI markers decreased with age in the white matter. However, electron microscopy suggest a relatively stable g-ratio throughout development. CONCLUSION Developmental trajectories of MPF accurately reflected regional differences of myelination rate in different cortical regions and white matter tracts. MRI-derived estimation of g-ratio was inaccurate during early development, likely due to the overestimation of axonal volume fraction by NODDI due to the presence of a large proportion of unmyelinated axons.
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Affiliation(s)
- Alexander Drobyshevsky
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA.
| | - Sylvia Synowiec
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Ivan Goussakov
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Jing Lu
- Department of Pediatrics, University of Chicago, Chicago, IL, USA
| | - David Gascoigne
- Center for Basic MR Research, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Daniil P Aksenov
- Center for Basic MR Research, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, USA
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Drobyshevsky A, Synowiec S, Goussakov I, Yarnykh V. Developmental and regional dependence of macromolecular proton fraction and fractional anisotropy in fixed brain tissue. NMR IN BIOMEDICINE 2023:e4915. [PMID: 36895100 DOI: 10.1002/nbm.4915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 01/24/2023] [Accepted: 02/04/2023] [Indexed: 05/06/2023]
Abstract
An important advantage of imaging fixed tissue is a gain in signal-to-noise ratio and in resolution due to unlimited scan time. However, the fidelity of quantitative MRI parameters in fixed brain tissue, particularly in developmental settings, requires validation. Macromolecular proton fraction (MPF) and fractional anisotropy (FA) indices are quantitative markers of myelination and axonal integrity relevant to preclinical and clinical research. The goal of this study was to assert the correspondence of MR-derived markers of brain development MPF and FA between in vivo and fixed tissue measures. MPF and FA were compared in several white and gray matter structures of the normal mouse brain at 2, 4, and 12 weeks of age. At each developmental stage, in vivo imaging was performed, followed by paraformaldehyde fixation and a second imaging session. MPF maps were acquired from three source images (magnetization transfer weighted, proton density weighted, and T1 weighted), and FA was obtained from diffusion tensor imaging. The MPF and FA values, measured in the cortex, striatum, and major fiber tracts, were compared before and after fixation using Bland-Altman plots, regression analysis, and analysis of variance. MPF values of the fixed tissue were consistently greater than those from in vivo measurements. Importantly, this bias varied significantly with brain region and the developmental stage of the tissue. At the same time, FA values were preserved after fixation, across tissue types and developmental stages. The results of this study suggest that MPF and FA in fixed brain tissue can be used as a proxy for in vivo measurements, but additional considerations should be made to correct for the bias in MPF.
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Affiliation(s)
- Alexander Drobyshevsky
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Sylvia Synowiec
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Ivan Goussakov
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, USA
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Huber E, Corrigan NM, Yarnykh VL, Ferjan Ramírez N, Kuhl PK. Language Experience during Infancy Predicts White Matter Myelination at Age 2 Years. J Neurosci 2023; 43:1590-1599. [PMID: 36746626 PMCID: PMC10008053 DOI: 10.1523/jneurosci.1043-22.2023] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 01/06/2023] [Accepted: 01/06/2023] [Indexed: 02/08/2023] Open
Abstract
Parental input is considered a key predictor of language achievement during the first years of life, yet relatively few studies have assessed the effects of parental language input and parent-infant interactions on early brain development. We examined the relationship between measures of parent and child language, obtained from naturalistic home recordings at child ages 6, 10, 14, 18, and 24 months, and estimates of white matter myelination, derived from quantitative MRI at age 2 years (mean = 26.30 months, SD = 1.62, N = 22). Analysis of the white matter focused on dorsal pathways associated with expressive language development and long-term language ability, namely, the left arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Frequency of parent-infant conversational turns (CT) uniquely predicted myelin density estimates in both the AF and SLF. Moreover, the effect of CT remained significant while controlling for total adult speech and child speech-related utterances, suggesting a specific role for interactive language experience, rather than simply speech exposure or production. An exploratory analysis of 18 additional tracts, including the right AF and SLF, indicated a high degree of anatomic specificity. Longitudinal analyses of parent and child language variables indicated an effect of CT as early as 6 months of age, as well as an ongoing effect over infancy. Together, these results link parent-infant conversational turns to white matter myelination at age 2 years, and suggest that early, interactive experiences with language uniquely contribute to the development of white matter associated with long-term language ability.SIGNIFICANCE STATEMENT Children's earliest experiences with language are thought to have profound and lasting developmental effects. Recent studies suggest that intervention can increase the quality of parental language input and improve children's learning outcomes. However, important questions remain about the optimal timing of intervention, and the relationship between specific aspects of language experience and brain development. We report that parent-infant turn-taking during home language interactions correlates with myelination of language related white matter pathways through age 2 years. Effects were independent of total speech exposure and infant vocalizations and evident starting at 6 months of age, suggesting that structured language interactions throughout infancy may uniquely support the ongoing development of brain systems critical to long-term language ability.
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Affiliation(s)
- Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, Washington 98195
| | - Naja Ferjan Ramírez
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Linguistics, University of Washington, Seattle, Washington 98195
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington 98195
- Department of Speech & Hearing Sciences, University of Washington, Seattle, Washington 98195
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9
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Sukstanskii AL, Yablonskiy DA. Microscopic theory of spin-spin and spin-lattice relaxation of bound protons in cellular and myelin membranes-A lateral diffusion model (LDM). Magn Reson Med 2023; 89:370-383. [PMID: 36094730 PMCID: PMC9826187 DOI: 10.1002/mrm.29430] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/26/2022] [Accepted: 08/08/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE Deciphering salient features of biological tissue cellular microstructure in health and diseases is an ultimate goal of MRI. While most MRI approaches are based on studying MR properties of tissue "free" water indirectly affected by tissue microstructure, other approaches, such as magnetization transfer (MT), directly target signals from tissue-forming macromolecules. However, despite three-decades of successful applications, relationships between MT measurements and tissue microstructure remain elusive, hampering interpretation of experimental results. The goal of this paper is to develop microscopic theory connecting the structure of cellular and myelin membranes to their MR properties. THEORY AND METHODS Herein we introduce a lateral diffusion model (LDM) that explains the T2 (spin-spin) and T1 (spin-lattice) MRI relaxation properties of the macromolecular-bound protons by their dipole-dipole interaction modulated by the lateral diffusion of long lipid molecules forming cellular and myelin membranes. RESULTS LDM predicts anisotropic T1 and T2 relaxation of membrane-bound protons. Moreover, their T2 relaxation cannot be described in terms of a standard R2 = 1/T2 relaxation rate parameter, but rather by a relaxation rate function R2 (t) that depends on time t after RF excitation, having, in the main approximation, a logarithmic behavior: R2 (t) ∼ lnt. This anisotropic non-linear relaxation leads to an absorption lineshape that is different from Super-Lorentzian traditionally used in interpreting MT experiments. CONCLUSION LDM-derived analytical equations connect the membrane-bound protons T1 and T2 relaxation with dynamic distances between protons in neighboring membrane-forming lipid molecules and their lateral diffusion. This sheds new light on relationships between MT parameters and microstructure of cellular and myelin membranes.
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Corrigan NM, Yarnykh VL, Huber E, Zhao TC, Kuhl PK. Brain myelination at 7 months of age predicts later language development. Neuroimage 2022; 263:119641. [PMID: 36170763 PMCID: PMC10038938 DOI: 10.1016/j.neuroimage.2022.119641] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/24/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
Between 6 and 12 months of age there are dramatic changes in infants' processing of language. The neurostructural underpinnings of these changes are virtually unknown. The objectives of this study were to (1) examine changes in brain myelination during this developmental period and (2) examine the relationship between myelination during this period and later language development. Macromolecular proton fraction (MPF) was used as a marker of myelination. Whole-brain MPF maps were obtained with 1.25 mm3 isotropic spatial resolution from typically developing children at 7 and 11 months of age. Effective myelin density was calculated from MPF based on a linear relationship known from the literature. Voxel-based analyses were used to identify longitudinal changes in myelin density and to calculate correlations between myelin density at these ages and later language development. Increases in myelin density were more predominant in white matter than in gray matter. A strong predictive relationship was found between myelin density at 7 months of age, language production at 24 and 30 months of age, and rate of language growth. No relationships were found between myelin density at 11 months, or change in myelin density between 7 and 11 months of age, and later language measures. Our findings suggest that critical changes in brain structure may precede periods of pronounced change in early language skills.
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Affiliation(s)
- Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - T Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
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Combes AJ, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J.E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Corresponding author at: 1161 21st Ave S, MCN AA1105, Nashville, TN 37232, USA.
| | - Margareta A. Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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Xiang B, Wen J, Schmidt RE, Sukstanskii AL, Mamah D, Yablonskiy DA, Cross AH. Evaluating brain damage in multiple sclerosis with simultaneous multi-angular-relaxometry of tissue. Ann Clin Transl Neurol 2022; 9:1514-1527. [PMID: 36178006 PMCID: PMC9539387 DOI: 10.1002/acn3.51621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/04/2022] [Accepted: 06/21/2022] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Multiple sclerosis (MS) is a common demyelinating central nervous system disease. MRI methods that can quantify myelin loss are needed for trials of putative remyelinating agents. Quantitative magnetization transfer MRI introduced the macromolecule proton fraction (MPF), which correlates with myelin concentration. We developed an alternative approach, Simultaneous-Multi-Angular-Relaxometry-of-Tissue (SMART) MRI, to generate MPF. Our objective was to test SMART-derived MPF metric as a potential imaging biomarker of demyelination. METHODS Twenty healthy control (HC), 11 relapsing-remitting MS (RRMS), 22 progressive MS (PMS), and one subject with a biopsied tumefactive demyelinating lesion were scanned at 3T using SMART MRI. SMART-derived MPF metric was determined in normal-appearing cortical gray matter (NAGM), normal-appearing subcortical white matter (NAWM), and demyelinating lesions. MPF metric was evaluated for correlations with physical and cognitive test scores. Comparisons were made between HC and MS and between MS subtypes. Furthermore, correlations were determined between MPF and neuropathology in the biopsied person. RESULTS SMART-derived MPF in NAGM and NAWM were lower in MS than HC (p < 0.001). MPF in NAGM, NAWM and lesions differentiated RRMS from PMS (p < 0.01, p < 0.001, p < 0.001, respectively), whereas lesion volumes did not. MPF in NAGM, NAWM and lesions correlated with the Expanded Disability Status Scale (p < 0.01, p < 0.001, p < 0.001, respectively) and nine-hole peg test (p < 0.001, p < 0.001, p < 0.01, respectively). MPF was lower in the histopathologically confirmed inflammatory demyelinating lesion than the contralateral NAWM and increased in the biopsied lesion over time, mirroring improved clinical performance. INTERPRETATION SMART-derived MPF metric holds potential as a quantitative imaging biomarker of demyelination and remyelination.
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Affiliation(s)
- Biao Xiang
- Department of RadiologyWashington UniversitySt. LouisMissouri63110USA
| | - Jie Wen
- Department of RadiologyWashington UniversitySt. LouisMissouri63110USA
| | - Robert E. Schmidt
- Department of PathologyWashington UniversitySt. LouisMissouri63110USA
| | | | - Daniel Mamah
- Department of PsychiatryWashington UniversitySt. LouisMissouri63110USA
| | | | - Anne H. Cross
- Department of NeurologyWashington UniversitySt. LouisMissouri63110USA
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