1
|
Timmers I, Biggs EE, Bruckert L, Tremblay-McGaw AG, Zhang H, Borsook D, Simons LE. Probing white matter microstructure in youth with chronic pain and its relation to catastrophizing using neurite orientation dispersion and density imaging. Pain 2024; 165:2494-2506. [PMID: 38718105 PMCID: PMC11511653 DOI: 10.1097/j.pain.0000000000003269] [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: 08/03/2023] [Accepted: 03/25/2024] [Indexed: 10/26/2024]
Abstract
ABSTRACT Chronic pain is common in young people and can have a major life impact. Despite the burden of chronic pain, mechanisms underlying chronic pain development and persistence are still poorly understood. Specifically, white matter (WM) connectivity has remained largely unexplored in pediatric chronic pain. Using diffusion-weighted imaging, this study examined WM microstructure in adolescents (age M = 15.8 years, SD = 2.8 years) with chronic pain (n = 44) compared with healthy controls (n = 24). Neurite orientation dispersion and density imaging modeling was applied, and voxel-based whole-white-matter analyses were used to obtain an overview of potential alterations in youth with chronic pain and tract-specific profile analyses to evaluate microstructural profiles of tracts of interest more closely. Our main findings are that (1) youth with chronic pain showed widespread elevated orientation dispersion compared with controls in several tracts, indicative of less coherence; (2) signs of neurite density tract-profile alterations were observed in several tracts of interest, with mainly higher density levels in patients; and (3) several WM microstructural alterations were associated with pain catastrophizing in the patient group. Implicated tracts include both those connecting cortical and limbic structures (uncinate fasciculus, cingulum, anterior thalamic radiation), which were associated with pain catastrophizing, as well as sensorimotor tracts (corticospinal tract). By identifying alterations in the biologically informative WM microstructural metrics orientation dispersion and neurite density, our findings provide important and novel mechanistic insights for understanding the pathophysiology underlying chronic pain. Taken together, the data support alterations in fiber organization as a meaningful characteristic, contributing process to the chronic pain state.
Collapse
Affiliation(s)
- Inge Timmers
- Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Emma E. Biggs
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Lisa Bruckert
- Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Alexandra G. Tremblay-McGaw
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Hui Zhang
- Department of Computer Science, University College London, London, United Kingdom
| | - David Borsook
- Center for Pain and the Brain, Boston Children’s Hospital, Boston, MA, United States
| | - Laura E. Simons
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
| |
Collapse
|
2
|
Mangini L, Lawrence R, Lopez ME, Graham TC, Bauer CR, Nguyen H, Su C, Ramphal J, Crawford BE, Hartl TA. Galactokinase 1 is the source of elevated galactose-1-phosphate and cerebrosides are modestly reduced in a mouse model of classic galactosemia. JIMD Rep 2024; 65:280-294. [PMID: 38974607 PMCID: PMC11224506 DOI: 10.1002/jmd2.12438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 05/02/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
Classic galactosemia (CG) arises from loss-of-function mutations in the Galt gene, which codes for the enzyme galactose-1-phosphate uridylyltransferase (GALT), a central component in galactose metabolism. The neonatal fatality associated with CG can be prevented by galactose dietary restriction, but for decades it has been known that limiting galactose intake is not a cure and patients often have lasting complications. Even on a low-galactose diet, GALT's substrate galactose-1-phosphate (Gal1P) is elevated and one hypothesis is that elevated Gal1P is a driver of pathology. Here we show that Gal1P levels were elevated above wildtype (WT) in Galt mutant mice, while mice doubly mutant for Galt and the gene encoding galactokinase 1 (Galk1) had normal Gal1P levels. This indicates that GALK1 is necessary for the elevated Gal1P in CG. Another hypothesis to explain the pathology is that an inability to metabolize galactose leads to diminished or disrupted galactosylation of proteins or lipids. Our studies reveal that levels of a subset of cerebrosides-galactosylceramide 24:1, sulfatide 24:1, and glucosylceramide 24:1-were modestly decreased compared to WT. In contrast, gangliosides were unaltered. The observed reduction in these 24:1 cerebrosides may be relevant to the clinical pathology of CG, since the cerebroside galactosylceramide is an important structural component of myelin, the 24:1 species is the most abundant in myelin, and irregularities in white matter, of which myelin is a constituent, have been observed in patients with CG. Therefore, impaired cerebroside production may be a contributing factor to the brain damage that is a common clinical feature of the human disease.
Collapse
Affiliation(s)
- Linley Mangini
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Roger Lawrence
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Manuel E. Lopez
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Timothy C. Graham
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Christopher R. Bauer
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Hang Nguyen
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Cheng Su
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - John Ramphal
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Brett E. Crawford
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Tom A. Hartl
- Research and Early DevelopmentBioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| |
Collapse
|
3
|
Mazzini S, Yadnik S, Timmers I, Rubio-Gozalbo E, Jansma BM. Altered neural oscillations in classical galactosaemia during sentence production. J Inherit Metab Dis 2024; 47:690-702. [PMID: 38600724 DOI: 10.1002/jimd.12740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 03/13/2024] [Accepted: 04/02/2024] [Indexed: 04/12/2024]
Abstract
Classical galactosaemia (CG) is a hereditary disease in galactose metabolism that despite dietary treatment is characterized by a wide range of cognitive deficits, among which is language production. CG brain functioning has been studied with several neuroimaging techniques, which revealed both structural and functional atypicalities. In the present study, for the first time, we compared the oscillatory dynamics, especially the power spectrum and time-frequency representations (TFR), in the electroencephalography (EEG) of CG patients and healthy controls while they were performing a language production task. Twenty-one CG patients and 19 healthy controls described animated scenes, either in full sentences or in words, indicating two levels of complexity in syntactic planning. Based on previous work on the P300 event related potential (ERP) and its relation with theta frequency, we hypothesized that the oscillatory activity of patients and controls would differ in theta power and TFR. With regard to behavior, reaction times showed that patients are slower, reflecting the language deficit. In the power spectrum, we observed significant higher power in patients in delta (1-3 Hz), theta (4-7 Hz), beta (15-30 Hz) and gamma (30-70 Hz) frequencies, but not in alpha (8-12 Hz), suggesting an atypical oscillatory profile. The time-frequency analysis revealed significantly weaker event-related theta synchronization (ERS) and alpha desynchronization (ERD) in patients in the sentence condition. The data support the hypothesis that CG language difficulties relate to theta-alpha brain oscillations.
Collapse
Affiliation(s)
- Sara Mazzini
- Neurobiology of Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sai Yadnik
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Inge Timmers
- Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands
| | - Estela Rubio-Gozalbo
- Department of Pediatrics and Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Bernadette M Jansma
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
4
|
Derks B, Kumar VS, Yadnik S, Panis B, Bosch AM, Cassiman D, Janssen MCH, Schuhmann T, Rubio-Gozalbo ME, Jansma BM. Impact of theta transcranial alternating current stimulation on language production in adult classic galactosemia patients. J Inherit Metab Dis 2024; 47:703-715. [PMID: 38659221 DOI: 10.1002/jimd.12742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 03/19/2024] [Accepted: 04/04/2024] [Indexed: 04/26/2024]
Abstract
Patients with classic galactosemia (CG), an inborn error of galactose metabolism, suffer from impairments in cognition, including language processing. Potential causes are atypical brain oscillations. Recent electroencephalogram (EEG) showed differences in the P300 event-related-potential (ERP) and alterations in the alpha/theta-range during speech planning. This study investigated whether transcranial alternating current stimulation (tACS) at theta-frequency compared to sham can cause a normalization of the ERP post stimulation and improves language performance. Eleven CG patients and fourteen healthy controls participated in two tACS-sessions (theta 6.5 Hz/sham). They were engaged in an active language task, describing animated scenes at three moments, that is, pre/during/post stimulation. Pre and post stimulation, behavior (naming accuracy, voice-onset-times; VOT) and mean-amplitudes of ERP were compared, by means of a P300 time-window analysis and cluster-based-permutation testing during speech planning. The results showed that theta stimulation, not sham, significantly reduced naming error-percentage in patients, not in controls. Theta did not systematically speed up naming beyond a general learning effect, which was larger for the patients. The EEG analysis revealed a significant pre-post stimulation effect (P300/late positivity), in patients and during theta stimulation only. In conclusion, theta-tACS improved accuracy in language performance in CG patients compared to controls and altered the P300 and late positive ERP-amplitude, suggesting a lasting effect on neural oscillation and behavior.
Collapse
Affiliation(s)
- Britt Derks
- Department of Pediatrics, Maastricht University Medical Centre+, MosaKids Children's Hospital, Maastricht, The Netherlands
- Department Clinical Genetics, Maastricht University Medical Centre+, Maastricht, The Netherlands
- GROW, Maastricht University, Maastricht, The Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member and United for Metabolic Diseases Member, Udine, Italy
| | - Varsha Shashi Kumar
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Sai Yadnik
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Bianca Panis
- Department of Pediatrics, Maastricht University Medical Centre+, MosaKids Children's Hospital, Maastricht, The Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member and United for Metabolic Diseases Member, Udine, Italy
| | - Annet M Bosch
- Department of Paediatrics, Division of Metabolic Diseases, Amsterdam UMC location University of Amsterdam, Emma Children's Hospital, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Inborn errors of metabolism, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development Research Institute, Amsterdam, The Netherlands
| | - David Cassiman
- Department of Gastroenterology-Hepatology and Adult Metabolic Center, University Hospital Leuven, Leuven, Belgium
| | - Mirian C H Janssen
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Teresa Schuhmann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics, Maastricht University Medical Centre+, MosaKids Children's Hospital, Maastricht, The Netherlands
- GROW, Maastricht University, Maastricht, The Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member and United for Metabolic Diseases Member, Udine, Italy
| | - Bernadette M Jansma
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
5
|
Pristner M, Wasinger D, Seki D, Klebermaß-Schrehof K, Berger A, Berry D, Wisgrill L, Warth B. Neuroactive metabolites and bile acids are altered in extremely premature infants with brain injury. Cell Rep Med 2024; 5:101480. [PMID: 38518769 PMCID: PMC11031385 DOI: 10.1016/j.xcrm.2024.101480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 10/02/2023] [Accepted: 02/27/2024] [Indexed: 03/24/2024]
Abstract
The gut microbiome is associated with pathological neurophysiological evolvement in extremely premature infants suffering from brain injury. The exact underlying mechanism and its associated metabolic signatures in infants are not fully understood. To decipher metabolite profiles linked to neonatal brain injury, we investigate the fecal and plasma metabolome of samples obtained from a cohort of 51 extremely premature infants at several time points, using liquid chromatography (LC)-high-resolution mass spectrometry (MS)-based untargeted metabolomics and LC-MS/MS-based targeted analysis for investigating bile acids and amidated bile acid conjugates. The data are integrated with 16S rRNA gene amplicon gut microbiome profiles as well as patient cytokine, growth factor, and T cell profiles. We find an early onset of differentiation in neuroactive metabolites between infants with and without brain injury. We detect several bacterially derived bile acid amino acid conjugates in plasma and feces. These results provide insights into the early-life metabolome of extremely premature infants.
Collapse
Affiliation(s)
- Manuel Pristner
- Department of Food Chemistry and Toxicology, University of Vienna, 1090 Vienna, Austria
| | - Daniel Wasinger
- Department of Food Chemistry and Toxicology, University of Vienna, 1090 Vienna, Austria
| | - David Seki
- Center for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, Division of Microbial Ecology, University of Vienna, 1090 Vienna, Austria; Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna, 1090 Vienna, Austria
| | - Katrin Klebermaß-Schrehof
- Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Comprehensive Center for Pediatrics, Medical University of Vienna, 1090 Vienna, Austria
| | - Angelika Berger
- Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Comprehensive Center for Pediatrics, Medical University of Vienna, 1090 Vienna, Austria
| | - David Berry
- Center for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, Division of Microbial Ecology, University of Vienna, 1090 Vienna, Austria; Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna, 1090 Vienna, Austria
| | - Lukas Wisgrill
- Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Comprehensive Center for Pediatrics, Medical University of Vienna, 1090 Vienna, Austria
| | - Benedikt Warth
- Department of Food Chemistry and Toxicology, University of Vienna, 1090 Vienna, Austria.
| |
Collapse
|
6
|
Wei X, Wang S, Zhang M, Yan Y, Wang Z, Wei W, Tuo H, Wang Z. Gait impairment-related axonal degeneration in Parkinson's disease by neurite orientation dispersion and density imaging. NPJ Parkinsons Dis 2024; 10:45. [PMID: 38413647 PMCID: PMC10899173 DOI: 10.1038/s41531-024-00654-w] [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: 07/06/2023] [Accepted: 02/06/2024] [Indexed: 02/29/2024] Open
Abstract
Microstructural alterations in the brain networks of Parkinson's disease (PD) patients are correlated with gait impairments. Evaluate microstructural alterations in the white matter (WM) fiber bundle tracts using neurite orientation dispersion and density imaging (NODDI) technique in PD versus healthy controls (HC). In this study, 24 PD patients and 29 HC were recruited. NODDI and high-resolution 3D structural images were acquired for each participant. The NODDI indicators, including the intracellular neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISO), were compared between the two groups. Diffusion-weighted (DW) images were preprocessed using MRtrix 3.0 software and the orientation distribution function to trace the main nerve fiber tracts in PD patients. Quantitative gait and clinical assessment scales were used to compare the medication "ON" and "OFF" states of PD patients. The NDI, ODI, and ISO values of the WM fiber bundles were significantly higher in PD patients compared to HC. Fiber bundles, including the anterior thalamic radiation, corticospinal tract, superior longitudinal fasciculus, forceps major, cingulum, and inferior longitudinal fasciculus, were found to be significantly affected in PD. The NDI changes of PD patients were well correlated with stride lengths in the "ON" state; ODI changes were correlated with the stride time in the "ON" and "OFF" states and ISO changes were correlated with the stride time and cadence in the "ON" state. In conclusion, combination of NODDI technique and gait parameters can help detect gait impairment in PD patients early and accurately.
Collapse
Grants
- 82202097 National Natural Science Foundation of China (National Science Foundation of China)
- 82071257 National Natural Science Foundation of China (National Science Foundation of China)
- Beijing Scholars Program is the highest-level talent development program approved by the Beijing Municipal People’s Government. It aims to cultivate a group of scientists, engineers, and renowned experts who are at the forefront of global science and technology, possess innovative capabilities, and have international advanced levels. The program provides intellectual support for the construction of a globally influential science and technology innovation center.
- Beijing Hospitals Authority’ Youth Programme is one of the three major talent development programs, namely "Qingmiao, Dengfeng, Shiming," launched by the Beijing Hospital Management Center in 2015. This program aims to support and cultivate young talents and provide a development platform for the growth of young talents in municipal hospitals through various training initiatives. Training Fund for Open Projects at Clinical Institutes and Departments of Capital Medical University is a research support fund program for young doctors opened by Capital Medical University, targeting different specialties, colleges, and departments.
Collapse
Affiliation(s)
- Xuan Wei
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Shiya Wang
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Mingkai Zhang
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Ying Yan
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zheng Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Wei Wei
- Division of Science and Technology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Houzhen Tuo
- Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| |
Collapse
|
7
|
Panis B, Vos EN, Barić I, Bosch AM, Brouwers MCGJ, Burlina A, Cassiman D, Coman DJ, Couce ML, Das AM, Demirbas D, Empain A, Gautschi M, Grafakou O, Grunewald S, Kingma SDK, Knerr I, Leão-Teles E, Möslinger D, Murphy E, Õunap K, Pané A, Paci S, Parini R, Rivera IA, Scholl-Bürgi S, Schwartz IVD, Sdogou T, Shakerdi LA, Skouma A, Stepien KM, Treacy EP, Waisbren S, Berry GT, Rubio-Gozalbo ME. Brain function in classic galactosemia, a galactosemia network (GalNet) members review. Front Genet 2024; 15:1355962. [PMID: 38425716 PMCID: PMC10902464 DOI: 10.3389/fgene.2024.1355962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
Classic galactosemia (CG, OMIM #230400, ORPHA: 79,239) is a hereditary disorder of galactose metabolism that, despite treatment with galactose restriction, affects brain function in 85% of the patients. Problems with cognitive function, neuropsychological/social emotional difficulties, neurological symptoms, and abnormalities in neuroimaging and electrophysiological assessments are frequently reported in this group of patients, with an enormous individual variability. In this review, we describe the role of impaired galactose metabolism on brain dysfunction based on state of the art knowledge. Several proposed disease mechanisms are discussed, as well as the time of damage and potential treatment options. Furthermore, we combine data from longitudinal, cross-sectional and retrospective studies with the observations of specialist teams treating this disease to depict the brain disease course over time. Based on current data and insights, the majority of patients do not exhibit cognitive decline. A subset of patients, often with early onset cerebral and cerebellar volume loss, can nevertheless experience neurological worsening. While a large number of patients with CG suffer from anxiety and depression, the increased complaints about memory loss, anxiety and depression at an older age are likely multifactorial in origin.
Collapse
Affiliation(s)
- Bianca Panis
- Department of Pediatrics, MosaKids Children’s Hospital, Maastricht University Medical Centre, Maastricht, Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- United for Metabolic Diseases (UMD), Amsterdam, Netherlands
| | - E. Naomi Vos
- Department of Pediatrics, MosaKids Children’s Hospital, Maastricht University Medical Centre, Maastricht, Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- United for Metabolic Diseases (UMD), Amsterdam, Netherlands
- Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, Netherlands
- GROW School for Oncology and Reproduction, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Ivo Barić
- Department of Pediatrics, University Hospital Center Zagreb, Croatia, and School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Annet M. Bosch
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- United for Metabolic Diseases (UMD), Amsterdam, Netherlands
- Department of Pediatrics, Division of Metabolic Diseases, Emma Children’s Hospital, Amsterdam University Medical Center, Amsterdam Gastroenterology Endocrinology Metabolism, Inborn Errors of Metabolism, Amsterdam, Netherlands
| | - Martijn C. G. J. Brouwers
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Department of Internal Medicine, Division of Endocrinology and Metabolic Disease, Maastricht University Medical Centre, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, Netherlands
| | - Alberto Burlina
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Division of Inherited Metabolic Diseases, Reference Centre Expanded Newborn Screening, University Hospital Padova, Padova, Italy
| | - David Cassiman
- Laboratory of Hepatology, Department of Chronic Diseases, Metabolism and Ageing, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - David J. Coman
- Queensland Children’s Hospital, Children’s Health Queensland, Brisbane, QLD, Australia
| | - María L. Couce
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Department of Pediatrics, Diagnosis and Treatment Unit of Congenital Metabolic Diseases, University Clinical Hospital of Santiago de Compostela, IDIS-Health Research Institute of Santiago de Compostela, CIBERER, RICORS Instituto Salud Carlos III, Santiago de Compostela, Spain
| | - Anibh M. Das
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Department of Paediatrics, Pediatric Metabolic Medicine, Hannover Medical School, Hannover, Germany
| | - Didem Demirbas
- Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Manton Center for Orphan Disease Research, Boston, MA, United States
| | - Aurélie Empain
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Department of Paediatrics, Metabolic and Nutrition Unit, Division of Endocrinology, Diabetes and Metabolism, University Hospital for Children Queen Fabiola, Bruxelles, Belgium
| | - Matthias Gautschi
- Department of Paediatrics, Institute of Clinical Chemistry, Inselspital, Bern University Hospital, Swiss Reference Centre for Inborn Errors of Metabolism, Site Bern, Division of Pediatric Endocrinology, Diabetes and Metabolism, University of Bern, Bern, Switzerland
| | - Olga Grafakou
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- IEM Clinic, Arch Makarios III Hospital, Nicosia, Cyprus
| | - Stephanie Grunewald
- Metabolic Unit Great Ormond Street Hospital and Institute for Child Health, University College London, London, United Kingdom
| | - Sandra D. K. Kingma
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Centre for Metabolic Diseases, University Hospital Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ina Knerr
- National Centre for Inherited Metabolic Disorders, Children’s Health Ireland at Temple Street, University College Dublin, Dublin, Ireland
| | - Elisa Leão-Teles
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Reference Centre of Inherited Metabolic Diseases, Centro Hospitalar Universitário São João, Porto, Portugal
| | - Dorothea Möslinger
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Elaine Murphy
- Charles Dent Metabolic Unit, National Hospital for Neurology and Neurosurgery (NHNN), London, United Kingdom
| | - Katrin Õunap
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Genetics and Personalized Medicine Clinic, Faculty of Medicine, Tartu University Hospital, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Adriana Pané
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Endocrinology and Nutrition Department, Hospital Clínic de Barcelona, Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Sabrina Paci
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Inborn Errors of Metabolism, Clinical Department of Pediatrics, San Paolo Hospital - ASST Santi Paolo e Carlo, University of Milan, Milan, Italy
| | - Rossella Parini
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Rare Diseases Unit, Department of Internal Medicine, San Gerardo Hospital IRCCS, Monza, Italy
| | - Isabel A. Rivera
- iMed.ULisboa–Instituto de Investigação do Medicamento, Faculdade de Farmácia, Universidade de Lisboa, Lisboa, Portugal
| | - Sabine Scholl-Bürgi
- Department of Child and Adolescent Health, Division of Pediatrics I-Inherited Metabolic Disorders, Medical University Innsbruck, Innsbruck, Austria
| | - Ida V. D. Schwartz
- Medical Genetics Service, Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
| | - Triantafyllia Sdogou
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Newborn Screening Department, Institute of Child Health, Athens, Greece
| | - Loai A. Shakerdi
- Adult Metabolics/Genetics, National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University Hospital, Dublin, Ireland
| | - Anastasia Skouma
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- Newborn Screening Department, Institute of Child Health, Athens, Greece
| | - Karolina M. Stepien
- Salford Royal Organisation, Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom
| | - Eileen P. Treacy
- School of Medicine, Trinity College Dublin, National Rare Diseases Office, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Susan Waisbren
- Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Manton Center for Orphan Disease Research, Boston, MA, United States
| | - Gerard T. Berry
- Division of Genetics and Genomics, Boston Children’s Hospital, Harvard Medical School, Manton Center for Orphan Disease Research, Boston, MA, United States
| | - M. Estela Rubio-Gozalbo
- Department of Pediatrics, MosaKids Children’s Hospital, Maastricht University Medical Centre, Maastricht, Netherlands
- European Reference Network for Hereditary Metabolic Disorders (MetabERN) Member, Padova, Italy
- United for Metabolic Diseases (UMD), Amsterdam, Netherlands
- Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, Netherlands
- GROW School for Oncology and Reproduction, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| |
Collapse
|
8
|
Teixeira LF, Prauchner GRK, Gusso D, Wyse ATS. Classical Hereditary galactosemia: findings in patients and animal models. Metab Brain Dis 2024; 39:239-248. [PMID: 37702899 DOI: 10.1007/s11011-023-01281-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 08/21/2023] [Indexed: 09/14/2023]
Abstract
Classic galactosemia is a rare inborn error of metabolism that affects the metabolism of galactose, a sugar derived from milk and derivates. Classic galactosemia is caused by variants of the GALT gene, which lead to absent or misfolded forms of the ubiquitously present galactose-1-phosphate uridylyltransferase enzyme (GALT) driving galactose metabolites to accumulate, damaging cells from neurons to hepatocytes. The disease has different prevalence around the world due to different allele frequencies among populations and its symptoms range from cognitive and psychomotor impairment to hepatic, ophthalmological, and bone structural damage. The practice of newborn screening still varies among countries, dairy restriction treatment is a consensus despite advances in preclinical treatment strategies. Recent clinical studies in Duarte variant suggest dairy restriction could be reconsidered in these cases. Despite noteworthy advances in the classic galactosemia understanding, preclinical trials are still crucial to fully understand the pathophysiology of the disease and help propose new treatments. This review aims to report a comprehensive analysis of past studies and state of art research on galactosemia screening, its clinical and preclinical trials, and treatments with the goal of shedding light on this complex and multisystemic innate error of the metabolism.
Collapse
Affiliation(s)
- Lucas Ferreira Teixeira
- Laboratory of Neuroprotection and Neurometabolic Diseases, Department of Biochemistry - Wyse's Lab - ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600-Anexo, Porto Alegre, RS, 90035-003, Brazil
| | - Gustavo R Krupp Prauchner
- Laboratory of Neuroprotection and Neurometabolic Diseases, Department of Biochemistry - Wyse's Lab - ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600-Anexo, Porto Alegre, RS, 90035-003, Brazil
| | - Darlan Gusso
- Laboratory of Neuroprotection and Neurometabolic Diseases, Department of Biochemistry - Wyse's Lab - ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600-Anexo, Porto Alegre, RS, 90035-003, Brazil
| | - Angela T S Wyse
- Laboratory of Neuroprotection and Neurometabolic Diseases, Department of Biochemistry - Wyse's Lab - ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Rua Ramiro Barcelos, 2600-Anexo, Porto Alegre, RS, 90035-003, Brazil.
- Departamento de Bioquímica, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-Anexo, Porto Alegre, RS, CEP 90035-003, Brazil.
| |
Collapse
|
9
|
Karafyllis I, Nuoffer JM, Michelis JP, Chilver-Stainer L. Untreated Classic Galactosemia: A Rare Cause of Adult-Onset Progressive Cerebellar Ataxia - A Case Report. Case Rep Neurol 2024; 16:55-62. [PMID: 38444718 PMCID: PMC10914380 DOI: 10.1159/000536679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 01/24/2024] [Indexed: 03/07/2024] Open
Abstract
Introduction Identifying the underlying etiology of nonfamilial adult-onset progressive cerebellar ataxia is often challenging because neurologists must consider almost all nongenetic and genetic causes of ataxia. Case Presentation A 39-year-old woman was hospitalized for progressive ataxia with pyramidal and cognitive dysfunction after a right arm shaking and coordination problem deteriorated progressively over 1.5 years. The patient's medical history included amenorrhea, cataracts, developmental delays, consanguinity of the parents, motor coordination issues, and diarrhea and vomiting in infancy. An important finding that enabled us to solve the diagnostic conundrum was the elevated carbohydrate-deficient transferrin levels in the lack of alcohol-related symptoms, which also occur in untreated carbohydrate metabolism disorders, sometimes with ataxia as a leading symptom. The decreased erythrocyte galactose-1-phosphate uridyltransferase (GALT) enzyme activity and the elevated erythrocyte galactose-1-phosphate (Gal-1P) concentration led to the final diagnosis of galactosemia, a rare metabolic disorder. The patient's condition stayed stable with strict adherence to lactose-free and galactose-restricted diets, regular physiotherapy, and speech therapy, despite attempts to control the crippling tremor. Conclusion This case highlights the importance of considering rare diseases based on unexplained clinical and laboratory findings. Newborn screening does not change the long-term complications of early-treated classical galactosemia. A small percentage of these patients develop ataxia tremor syndrome.
Collapse
Affiliation(s)
- Ioannis Karafyllis
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Neurology, Cantonal Hospital Olten, Olten, Switzerland
| | - Jean-Marc Nuoffer
- Department of Pediatric Endocrinology, Diabetology and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- University Institute of Clinical Chemistry, University of Bern, Bern, Switzerland
| | - Joan-Philipp Michelis
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Lara Chilver-Stainer
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| |
Collapse
|
10
|
Alsameen MH, Gong Z, Qian W, Kiely M, Triebswetter C, Bergeron CM, Cortina LE, Faulkner ME, Laporte JP, Bouhrara M. C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter. Front Neurol 2023; 14:1205426. [PMID: 37602266 PMCID: PMC10435293 DOI: 10.3389/fneur.2023.1205426] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 07/14/2023] [Indexed: 08/22/2023] Open
Abstract
Purpose Neurite orientation dispersion and density imaging (NODDI) provides measures of neurite density and dispersion through computation of the neurite density index (NDI) and the orientation dispersion index (ODI). However, NODDI overestimates the cerebrospinal fluid water fraction in white matter (WM) and provides physiologically unrealistic high NDI values. Furthermore, derived NDI values are echo-time (TE)-dependent. In this work, we propose a modification of NODDI, named constrained NODDI (C-NODDI), for NDI and ODI mapping in WM. Methods Using NODDI and C-NODDI, we investigated age-related alterations in WM in a cohort of 58 cognitively unimpaired adults. Further, NDI values derived using NODDI or C-NODDI were correlated with the neurofilament light chain (NfL) concentration levels, a plasma biomarker of axonal degeneration. Finally, we investigated the TE dependence of NODDI or C-NODDI derived NDI and ODI. Results ODI derived values using both approaches were virtually identical, exhibiting constant trends with age. Further, our results indicated a quadratic relationship between NDI and age suggesting that axonal maturation continues until middle age followed by a decrease. This quadratic association was notably significant in several WM regions using C-NODDI, while limited to a few regions using NODDI. Further, C-NODDI-NDI values exhibited a stronger correlation with NfL concentration levels as compared to NODDI-NDI, with lower NDI values corresponding to higher levels of NfL. Finally, we confirmed the previous finding that NDI estimation using NODDI was dependent on TE, while NDI derived values using C-NODDI exhibited lower sensitivity to TE in WM. Conclusion C-NODDI provides a complementary method to NODDI for determination of NDI in white matter.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| |
Collapse
|
11
|
Stellingwerff MD, Pouwels PJW, Roosendaal SD, Barkhof F, van der Knaap MS. Quantitative MRI in leukodystrophies. Neuroimage Clin 2023; 38:103427. [PMID: 37150021 PMCID: PMC10193020 DOI: 10.1016/j.nicl.2023.103427] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies.
Collapse
Affiliation(s)
- Menno D Stellingwerff
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Petra J W Pouwels
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Stefan D Roosendaal
- Amsterdam UMC Location University of Amsterdam, Department of Radiology, Meibergdreef 9, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; University College London, Institutes of Neurology and Healthcare Engineering, London, UK
| | - Marjo S van der Knaap
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Vrije Universiteit Amsterdam, Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, De Boelelaan 1105, Amsterdam, the Netherlands.
| |
Collapse
|
12
|
Optical Coherence Tomography: Retinal Imaging Contributes to the Understanding of Brain Pathology in Classical Galactosemia. J Clin Med 2023; 12:jcm12052030. [PMID: 36902816 PMCID: PMC10004555 DOI: 10.3390/jcm12052030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 02/23/2023] [Accepted: 03/01/2023] [Indexed: 03/08/2023] Open
Abstract
It remains unresolved whether central nervous system involvement in treated classical galactosemia (CG) is a progressive neurodegenerative process. This study aimed to investigate retinal neuroaxonal degeneration in CG as a surrogate of brain pathology. Global peripapillary retinal nerve fibre layer (GpRNFL) and combined ganglion cell and inner plexiform layer (GCIPL) were analysed in 11 CG patients and 60 controls (HC) using spectral-domain optical coherence tomography. Visual acuity (VA) and low-contrast VA (LCVA) were acquired to test visual function. GpRNFL and GCIPL did not differ between CG and HC (p > 0.05). However, in CG, there was an effect of intellectual outcome on GCIPL (p = 0.036), and GpRNFL and GCIPL correlated with neurological rating scale scores (p < 0.05). A single-case follow-up analysis showed GpRNFL (0.53-0.83%) and GCIPL (0.52-0.85%) annual decrease beyond the normal aging effect. VA and LCVA were reduced in CG with intellectual disability (p = 0.009/0.006), likely due to impaired visual perception. These findings support that CG is not a neurodegenerative disease, but that brain damage is more likely to occur early in brain development. To clarify a minor neurodegenerative component in the brain pathology of CG, we propose multicenter cross-sectional and longitudinal studies using retinal imaging.
Collapse
|
13
|
Delnoy B, Haskovic M, Vanoevelen J, Steinbusch LKM, Vos EN, Knoops K, Zimmermann LJI, Noga M, Lefeber DJ, Martini PGV, Coelho AI, Rubio‐Gozalbo ME. Novel mRNA therapy restores GALT protein and enzyme activity in a zebrafish model of classic galactosemia. J Inherit Metab Dis 2022; 45:748-758. [PMID: 35527402 PMCID: PMC9541528 DOI: 10.1002/jimd.12512] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 11/24/2022]
Abstract
Messenger RNA (mRNA) has emerged as a novel therapeutic approach for inborn errors of metabolism. Classic galactosemia (CG) is an inborn error of galactose metabolism caused by a severe deficiency of galactose-1-phosphate:uridylyltransferase (GALT) activity leading to neonatal illness and chronic impairments affecting the brain and female gonads. In this proof of concept study, we used our zebrafish model for CG to evaluate the potential of human GALT mRNA (hGALT mRNA) packaged in two different lipid nanoparticles to restore GALT expression and activity at early stages of development. Both one cell-stage and intravenous single-dose injections resulted in hGALT protein expression and enzyme activity in the CG zebrafish (galt knockout) at 5 days post fertilization (dpf). Moreover, the levels of galactose-1-phosphate (Gal-1-P) and galactonate, metabolites that accumulate because of the deficiency, showed a decreasing trend. LNP-packaged mRNA was effectively translated and processed in the CG zebrafish without signs of toxicity. This study shows that mRNA therapy restores GALT protein and enzyme activity in the CG zebrafish model, and that the zebrafish is a suitable system to test this approach. Further studies are warranted to assess whether repeated injections safely mitigate the chronic impairments of this disease.
Collapse
Affiliation(s)
- Britt Delnoy
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
- GROW, Maastricht UniversityMaastrichtthe Netherlands
| | - Minela Haskovic
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
- GROW, Maastricht UniversityMaastrichtthe Netherlands
| | - Jo Vanoevelen
- GROW, Maastricht UniversityMaastrichtthe Netherlands
- Department of Clinical GeneticsMaastricht University Medical Center+Maastrichtthe Netherlands
| | - Laura K. M. Steinbusch
- Department of Clinical GeneticsMaastricht University Medical Center+Maastrichtthe Netherlands
| | - Esther Naomi Vos
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
| | - Kèvin Knoops
- Microscopy CORE LaboratoryMaastricht UniversityMaastrichtthe Netherlands
| | - Luc J. I. Zimmermann
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
- GROW, Maastricht UniversityMaastrichtthe Netherlands
| | - Marek Noga
- Translational Metabolic LaboratoryRadboud University Medical CenterNijmegenthe Netherlands
| | - Dirk J. Lefeber
- Translational Metabolic LaboratoryRadboud University Medical CenterNijmegenthe Netherlands
- Department of NeurologyDonders Institute for Brain, Cognition and Behavior, Radboud University Medical CenterNijmegenthe Netherlands
| | | | - Ana I. Coelho
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
| | - Maria Estela Rubio‐Gozalbo
- Department of PediatricsMaastricht University Medical Center+Maastrichtthe Netherlands
- GROW, Maastricht UniversityMaastrichtthe Netherlands
- Department of Clinical GeneticsMaastricht University Medical Center+Maastrichtthe Netherlands
| |
Collapse
|
14
|
Brosnan MB, Shalev N, Ramduny J, Sotiropoulos SN, Chechlacz M. Right fronto-parietal networks mediate the neurocognitive benefits of enriched environments. Brain Commun 2022; 4:fcac080. [PMID: 35474852 PMCID: PMC9035529 DOI: 10.1093/braincomms/fcac080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 01/10/2022] [Accepted: 03/25/2022] [Indexed: 11/13/2022] Open
Abstract
Exposure to enriched environments throughout a lifetime, providing so-called reserve, protects against cognitive decline in later years. It has been hypothesized that high levels of alertness necessitated by enriched environments might strengthen the right fronto-parietal networks to facilitate this neurocognitive resilience. We have previously shown that enriched environments offset age-related deficits in selective attention by preserving grey matter within right fronto-parietal regions. Here, using neurite orientation dispersion and density imaging, we examined the relationship between enriched environments, microstructural properties of fronto-parietal white matter association pathways (three branches of the superior longitudinal fasciculus), structural brain health (atrophy), and attention (alertness, orienting and executive control) in a group of older adults. We show that exposure to enriched environments is associated with a lower orientation dispersion index within the right superior longitudinal fasciculus 1 which in turn mediates the relationship between enriched environments and alertness, as well as grey and white matter atrophy. This suggests that enriched environments may induce white matter plasticity (and prevent age-related dispersion of axons) within the right fronto-parietal networks to facilitate the preservation of neurocognitive health in later years.
Collapse
Affiliation(s)
- Méadhbh B. Brosnan
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Nir Shalev
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jivesh Ramduny
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Stamatios N. Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- National Institute for Health Research (NIHR), Nottingham Biomedical Research Centre, Queen’s Medical Centre, Nottingham, UK
| | - Magdalena Chechlacz
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
- School of Psychology, University of Birmingham, Birmingham, UK
| |
Collapse
|
15
|
Rikitake M, Hata J, Iida M, Seki F, Ito R, Komaki Y, Yamada C, Yoshimaru D, Okano HJ, Shirakawa T. Analysis of Brain Structure and Neural Organization in Dystrophin-Deficient Model Mice with Magnetic Resonance Imaging at 7 T. Open Neuroimag J 2022. [DOI: 10.2174/18744400-v15-e2202040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Background:
Dystrophin strengthens muscle cells; however, in muscular dystrophy, dystrophin is deficient due to an abnormal sugar chain. This abnormality occurs in skeletal muscle and in brain tissue.
Objective:
This study aimed to non-invasively analyze the neural organization of the brain in muscular dystrophy. We used a mouse model of muscular dystrophy to study whether changes in brain structure and neurodegeneration following dystrophin deficiency can be assessed by 7T magnetic resonance imaging.
Methods:
C57BL/10-mdx (X chromosome-linked muscular dystrophy) mice were used as the dystrophic mouse model and healthy mice were used as controls. Ventricular enlargement is one of the most common brain malformations in dystrophin-deficient patients. Therefore, we examined whether ventricular enlargement was observed in C57BL/10-mdx using transverse-relaxation weighted images. Brain parenchyma analysis was performed using diffusion MRI with diffusion tensor images and neurite orientation dispersion and density imaging. Parenchymal degeneration was assessed in terms of directional diffusion, nerve fiber diffusion, and dendritic scattering density.
Results:
For the volume of brain ventricles analyzed by T2WI, the average size was 1.5 times larger in mdx mice compared to control mice. In the brain parenchyma, a significant difference (p < 0.05) was observed in parameters indicating disturbances in the direction of nerve fibers and dendritic scattering density in the white matter region.
Conclusion:
Our results show that changes in brain structure due to dystrophin deficiency can be assessed in detail without tissue destruction by combining diffusion tensor images and neurite orientation dispersion and density imaging analyses.
Collapse
|
16
|
Radetz A, Mladenova K, Ciolac D, Gonzalez-Escamilla G, Fleischer V, Ellwardt E, Krämer J, Bittner S, Meuth SG, Muthuraman M, Groppa S. Linking Microstructural Integrity and Motor Cortex Excitability in Multiple Sclerosis. Front Immunol 2021; 12:748357. [PMID: 34712236 PMCID: PMC8546169 DOI: 10.3389/fimmu.2021.748357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 09/23/2021] [Indexed: 11/15/2022] Open
Abstract
Motor skills are frequently impaired in multiple sclerosis (MS) patients following grey and white matter damage with cortical excitability abnormalities. We applied advanced diffusion imaging with 3T magnetic resonance tomography for neurite orientation dispersion and density imaging (NODDI), as well as diffusion tensor imaging (DTI) in 50 MS patients and 49 age-matched healthy controls to quantify microstructural integrity of the motor system. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. As measures of cognitive-motor performance, we conducted neuropsychological assessments including the Nine-Hole Peg Test, Trail Making Test part A and B (TMT-A and TMT-B) and the Symbol Digit Modalities Test (SDMT). Patients were evaluated clinically including assessments with the Expanded Disability Status Scale. A hierarchical regression model revealed that lower neurite density index (NDI) in primary motor cortex, suggestive for axonal loss in the grey matter, predicted higher motor thresholds, i.e. reduced excitability in MS patients (p = .009, adjusted r² = 0.117). Furthermore, lower NDI was indicative of decreased cognitive-motor performance (p = .007, adjusted r² = .142 for TMT-A; p = .009, adjusted r² = .129 for TMT-B; p = .006, adjusted r² = .142 for SDMT). Motor WM tracts of patients were characterized by overlapping clusters of lowered NDI (p <.05, Cohen's d = 0.367) and DTI-based fractional anisotropy (FA) (p <.05, Cohen's d = 0.300), with NDI exclusively detecting a higher amount of abnormally appearing voxels. Further, orientation dispersion index of motor tracts was increased in patients compared to controls, suggesting a decreased fiber coherence (p <.05, Cohen's d = 0.232). This study establishes a link between microstructural characteristics and excitability of neural tissue, as well as cognitive-motor performance in multiple sclerosis. We further demonstrate that the NODDI parameters neurite density index and orientation dispersion index detect a larger amount of abnormally appearing voxels in patients compared to healthy controls, as opposed to the classical DTI parameter FA. Our work outlines the potential for microstructure imaging using advanced biophysical models to forecast excitability alterations in neuroinflammation.
Collapse
Affiliation(s)
- Angela Radetz
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Kalina Mladenova
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Laboratory of Neurobiology and Medical Genetics, Nicolae Testemițanu State University of Medicine and Pharmacy, Chişinău, Moldova
- Department of Neurology, Institute of Emergency Medicine, Chişinău, Moldova
| | - Gabriel Gonzalez-Escamilla
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Vinzenz Fleischer
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Erik Ellwardt
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology, Institute of Translational Neurology, University Hospital Münster, Münster, Germany
| | - Stefan Bittner
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sven G. Meuth
- Department of Neurology, Institute of Translational Neurology, University Hospital Münster, Münster, Germany
- Department of Neurology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Muthuraman Muthuraman
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Neuroimaging and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| |
Collapse
|
17
|
Treacy EP, Vencken S, Bosch AM, Gautschi M, Rubio‐Gozalbo E, Dawson C, Nerney D, Colhoun HO, Shakerdi L, Pastores GM, O'Flaherty R, Saldova R. Abnormal N-glycan fucosylation, galactosylation, and sialylation of IgG in adults with classical galactosemia, influence of dietary galactose intake. JIMD Rep 2021; 61:76-88. [PMID: 34485021 PMCID: PMC8411110 DOI: 10.1002/jmd2.12237] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Classical galactosemia (CG) (OMIM #230400) is a rare disorder of carbohydrate metabolism, due to deficiency of galactose-1-phosphate uridyltransferase (EC 2.7.7.12). The pathophysiology of the long-term complications, mainly cognitive, neurological, and female infertility remains poorly understood. OBJECTIVES This study investigated (a) the association between specific IgG N-glycosylation biomarkers (glycan peaks and grouped traits) and CG patients (n = 95) identified from the GalNet Network, using hydrophilic interaction ultraperformance liquid chromatography and (b) a further analysis of a GALT c.563A-G/p.Gln188Arg homozygous cohort (n = 49) with correlation with glycan features with patient Full Scale Intelligence Quotient (FSIQ), and (c) with galactose intake. RESULTS A very significant decrease in galactosylation and sialylation and an increase in core fucosylation was noted in CG patients vs controls (P < .005). Bisected glycans were decreased in the severe GALT c.563A-G/p.Gln188Arg homozygous cohort (n = 49) (P < .05). Logistic regression models incorporating IgG glycan traits distinguished CG patients from controls. Incremental dietary galactose intake correlated positively with FSIQ for the p.Gln188Arg homozygous CG cohort (P < .005) for a dietary galactose intake of 500 to 1000 mg/d. Significant improvements in profiles with increased galactose intake were noted for monosialylated, monogalactosylated, and monoantennary glycans. CONCLUSION These results suggest that N-glycosylation abnormalities persist in CG patients on dietary galactose restriction which may be modifiable to a degree by dietary galactose intake.
Collapse
Affiliation(s)
- Eileen P. Treacy
- National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University HospitalDublinIreland
- Department of PaediatricsTrinity College DublinDublinIreland
- UCD School of MedicineUniversity College DublinDublinIreland
| | | | - Annet M. Bosch
- Department of Pediatrics, Division of Metabolic DisordersEmma Children's Hospital, Amsterdam Gastroenterology, Endocrinology & Metabolism, Amsterdam UMC, University of AmsterdamAmsterdamThe Netherlands
| | - Matthias Gautschi
- Department of Paediatrics and Institute of Clinical ChemistryInselspital, University Hospital BernBernSwitzerland
| | - Estela Rubio‐Gozalbo
- Department of Pediatrics/Laboratory of Clinical GeneticsMaastricht University Medical CentreMaastrichtThe Netherlands
| | - Charlotte Dawson
- Department of EndocrinologyUniversity Hospitals Birmingham NHS Foundation TrustBirminghamUK
| | - Darragh Nerney
- National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University HospitalDublinIreland
| | - Hugh Owen Colhoun
- NIBRT GlycoScience Group, National Institute for Bioprocessing, Research and TrainingDublinIreland
| | - Loai Shakerdi
- National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University HospitalDublinIreland
| | - Gregory M. Pastores
- National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University HospitalDublinIreland
| | - Roisin O'Flaherty
- NIBRT GlycoScience Group, National Institute for Bioprocessing, Research and TrainingDublinIreland
- Department of ChemistryMaynooth UniversityKildareIreland
| | - Radka Saldova
- NIBRT GlycoScience Group, National Institute for Bioprocessing, Research and TrainingDublinIreland
- UCD School of Medicine, College of Health and Agricultural Sciences (CHAS), University College Dublin (UCD)DublinIreland
| |
Collapse
|
18
|
Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Graff-Radford J, Schwarz CG, Knopman DS, Mielke MM, Machulda MM, Petersen RC, Jack CR, Vemuri P. Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain Commun 2021; 3:fcab106. [PMID: 34136811 PMCID: PMC8202149 DOI: 10.1093/braincomms/fcab106] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/24/2021] [Accepted: 04/12/2021] [Indexed: 01/20/2023] Open
Abstract
White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.
Collapse
Affiliation(s)
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA.,Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | |
Collapse
|
19
|
Rossi-Espagnet MC, Sudhakar S, Fontana E, Longo D, Davison J, Petengill AL, Bevivino E, Pacheco FT, da Rocha AJ, Hanagandi P, Soldatelli M, Mankad K, do Amaral LLF. Neuroradiologic Phenotyping of Galactosemia: From the Neonatal Form to the Chronic Stage. AJNR Am J Neuroradiol 2021; 42:590-596. [PMID: 33478945 DOI: 10.3174/ajnr.a7016] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 10/23/2020] [Indexed: 11/07/2022]
Abstract
Galactosemia is a rare genetic condition caused by mutation of enzymes involved in galactose and glucose metabolism. The varying clinical spectrum reflects the genetic complexity of this entity manifesting as acute neonatal toxicity syndrome, requiring prompt diagnosis and treatment, to more insidious clinical scenarios as observed in the subacute and chronic presentations. The current literature predominantly focuses on the long-standing sequelae of this disease. The purpose of this multicenter clinical report comprising 17 patients with galactosemia is to highlight the MR imaging patterns encompassing the whole spectrum of galactosemia, emphasizing the 3 main clinical subtypes: 1) acute neonatal presentation, with predominant white matter edema; 2) subacute clinical onset with a new finding called the "double cap sign"; and 3) a chronic phase of the disease with heterogeneous imaging findings. The knowledge of these different patterns together with MR spectroscopy and the clinical presentation may help in prioritizing galactosemia over other neonatal metabolic diseases and prevent possible complications.
Collapse
Affiliation(s)
- M C Rossi-Espagnet
- From the Neuroradiology Unit (M.C.R.-E., E.F., D.L.)
- Neuroradiology Unit (M.C.R.-E.), Neuroscience, Mental Health and Sensory Organs Department, University Sapienza, Rome, Italy
| | | | - E Fontana
- From the Neuroradiology Unit (M.C.R.-E., E.F., D.L.)
| | - D Longo
- From the Neuroradiology Unit (M.C.R.-E., E.F., D.L.)
| | - J Davison
- Paediatric Metabolic Medicine (J.D.), Great Ormond Street Hospital National Health Service Foundation Trust, London, UK
| | - A L Petengill
- Neuroradiology Department, (A.L.P., F.T.P., A.J.d.R., L.L.F.d.A.), Hospital da Santa Casa de Misericórdia de São Paulo, São Paulo, Brazil
| | - E Bevivino
- Division of Metabolism (E.B.), Bambino Gesù' Children's Hospital, Rome, Italy
| | - F T Pacheco
- Neuroradiology Department, (A.L.P., F.T.P., A.J.d.R., L.L.F.d.A.), Hospital da Santa Casa de Misericórdia de São Paulo, São Paulo, Brazil
| | - A J da Rocha
- Neuroradiology Department, (A.L.P., F.T.P., A.J.d.R., L.L.F.d.A.), Hospital da Santa Casa de Misericórdia de São Paulo, São Paulo, Brazil
| | - P Hanagandi
- Department of Medical Imaging (P.H.), King Abdulaziz Medical City, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - M Soldatelli
- Neuroradiology Department (M.S., L.L.F.d.A.), BP Medicina Diagnóstica, Hospital da Beneficência Portuguesa de São Paulo, São Paulo, Brazil
| | - K Mankad
- Neuroradiology Unit (S.S., K.M.)
| | - L L F do Amaral
- Neuroradiology Department, (A.L.P., F.T.P., A.J.d.R., L.L.F.d.A.), Hospital da Santa Casa de Misericórdia de São Paulo, São Paulo, Brazil
- Neuroradiology Department (M.S., L.L.F.d.A.), BP Medicina Diagnóstica, Hospital da Beneficência Portuguesa de São Paulo, São Paulo, Brazil
| |
Collapse
|
20
|
Qian W, Khattar N, Cortina LE, Spencer RG, Bouhrara M. Nonlinear associations of neurite density and myelin content with age revealed using multicomponent diffusion and relaxometry magnetic resonance imaging. Neuroimage 2020; 223:117369. [PMID: 32931942 PMCID: PMC7775614 DOI: 10.1016/j.neuroimage.2020.117369] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 09/07/2020] [Accepted: 09/08/2020] [Indexed: 12/18/2022] Open
Abstract
Most magnetic resonance imaging (MRI) studies investigating the relationship between regional brain myelination or axonal density and aging have relied upon nonspecific methods to probe myelin and axonal content, including diffusion tensor imaging and relaxation time mapping. While these studies have provided pivotal insights into changes in cerebral architecture with aging and pathology, details of the underlying microstructural alterations have not been fully elucidated. In the current study, we used the BMC-mcDESPOT analysis, a direct and specific multicomponent relaxometry method for imaging of myelin water fraction (MWF), a marker of myelin content, and NODDI, an emerging multicomponent diffusion technique, for neurite density index (NDI) imaging, a proxy of axonal density. We investigated age-related differences in MWF and NDI in several white matter brain regions in a cohort of cognitively unimpaired participants over a wide age range. Our results indicate a quadratic, inverted U-shape, relationship between MWF and age in all brain regions investigated, suggesting that myelination continues until middle age followed by a decrease at older ages, in agreement with previous work. We found a similarly complex regional association between NDI and age, with several cerebral structures also exhibiting a quadratic, inverted U-shape, relationship. This novel observation suggests an increase in axonal density until the fourth decade of age followed by a rapid loss at older ages. We also observed that these age-related differences in MWF and NDI vary across different brain regions, as expected. Finally, our study indicates no significant association between MWF and NDI in most cerebral structures investigated, although this association approached significance in a limited number of brain regions, indicating the complementary nature of their information and encouraging further investigation. Overall, we find evidence of nonlinear associations between age and myelin or axonal density in a sample of well-characterized adults, using direct myelin and axonal content imaging methods.
Collapse
Affiliation(s)
- Wenshu Qian
- Magnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA
| | - Nikkita Khattar
- Magnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA
| | - Luis E Cortina
- Magnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA
| | - Richard G Spencer
- Magnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, Laboratory of Clinical Investigations, National Institute on Aging, National Institutes of Health, NIA, NIH, 251 Bayview Blvd., Baltimore, MD 21224, USA.
| |
Collapse
|
21
|
Welsink-Karssies MM, Schrantee A, Caan MWA, Hollak CEM, Janssen MCH, Oussoren E, de Vries MC, Roosendaal SD, Engelen M, Bosch AM. Gray and white matter are both affected in classical galactosemia: An explorative study on the association between neuroimaging and clinical outcome. Mol Genet Metab 2020; 131:370-379. [PMID: 33199205 DOI: 10.1016/j.ymgme.2020.11.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 11/01/2020] [Accepted: 11/01/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Classical Galactosemia (CG) is an inherited disorder of galactose metabolism caused by a deficiency of the galactose-1-phosphate uridylyltransferase (GALT) enzyme resulting in neurocognitive complications. As in many Inborn Errors of Metabolism, the metabolic pathway of CG is well-defined, but the pathophysiology and high variability in clinical outcome are poorly understood. The aim of this study was to investigate structural changes of the brain of CG patients on MRI and their association with clinical outcome. METHODS In this prospective cohort study an MRI protocol was developed to evaluate gray matter (GM) and white matter (WM) volume of the cerebrum and cerebellum, WM hyperintensity volume, WM microstructure and myelin content with the use of conventional MRI techniques, diffusion tensor imaging (DTI) and quantitative T1 mapping. The association between several neuroimaging parameters and both neurological and intellectual outcome was investigated. RESULTS Twenty-one patients with CG (median age 22 years, range 8-47) and 24 controls (median age 30, range 16-52) were included. Compared to controls, the WM of CG patients was lower in volume and the microstructure of WM was impaired both in the whole brain and corticospinal tract (CST) and the lower R1 values of WM, GM and the CST were indicative of less myelin. The volume of WM lesions were comparable between patients and controls. The 9/16 patients with a poor neurological outcome (defined as the presence of a tremor and/or dystonia), demonstrated a lower WM volume, an impaired WM microstructure and lower R1 values of the WM indicative of less myelin content compared to 7/16 patients without movement disorders. In 15/21 patients with a poor intellectual outcome (defined as an IQ < 85) both GM and WM were affected with a lower cerebral and cerebellar WM and GM volume compared to 6/21 patients with an IQ ≥ 85. Both the severity of the tremor (as indicated by the Tremor Rating Scale) and IQ (as continuous measure) were associated with several neuroimaging parameters such as GM volume, WM volume, CSF volume, WM microstructure parameters and R1 values of GM and WM. CONCLUSION In this explorative study performed in patients with Classical Galactosemia, not only WM but also GM pathology was found, with more severe brain abnormalities on MRI in patients with a poor neurological and intellectual outcome. The finding that structural changes of the brain were associated with the severity of long-term complications indicates that quantitative MRI techniques could be of use to explain neurological and cognitive dysfunction as part of the disease spectrum. Based on the clinical outcome of patients, the absence of widespread WM lesions and the finding that both GM and WM are affected, CG could be primarily a GM disease with secondary damage to the WM as a result of neuronal degeneration. To investigate this further the course of GM and WM should be evaluated in longitudinal research, which could also clarify if CG is a neurodegenerative disease.
Collapse
Affiliation(s)
- Mendy M Welsink-Karssies
- Department of Pediatrics, Division of Metabolic Disorders, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Matthan W A Caan
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Biomedical Engineering, Amsterdam University Medical Center, location AMC, Amsterdam, the Netherlands
| | - Carla E M Hollak
- Department of Internal Medicine, Division of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Mirian C H Janssen
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Esmee Oussoren
- Department of Pediatrics, Center for Lysosomal and Metabolic Diseases, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Maaike C de Vries
- Department of Pediatrics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Stefan D Roosendaal
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Marc Engelen
- Department of Pediatrics, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Annet M Bosch
- Department of Pediatrics, Division of Metabolic Disorders, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| |
Collapse
|
22
|
Ahtam B, Waisbren SE, Anastasoaie V, Berry GT, Brown M, Petrides S, Afacan O, Prabhu SP, Schomer D, Grant PE, Greenstein PE. Identification of neuronal structures and pathways corresponding to clinical functioning in galactosemia. J Inherit Metab Dis 2020; 43:1205-1218. [PMID: 32592186 DOI: 10.1002/jimd.12279] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/05/2020] [Accepted: 06/24/2020] [Indexed: 12/27/2022]
Abstract
Classic galactosemia (OMIM# 230400) is an autosomal recessive disorder due to galactose-1-phosphate uridyltransferase deficiency. Newborn screening and prompt treatment with a galactose-free diet prevent the severe consequences of galactosemia, but clinical outcomes remain suboptimal. Five men and five women with classic galactosemia (mean age = 27.2 ± 5.47 years) received comprehensive neurological and neuropsychological evaluations, electroencephalogram (EEG) and magnetic resonance imaging (MRI). MRI data from nine healthy controls (mean age = 30.22 ± 3.52 years) were used for comparison measures. Galactosemia subjects experienced impaired memory, language processing, visual-motor skills, and increased anxiety. Neurological examinations revealed tremor and dysarthria in six subjects. In addition, there was ataxia in three subjects and six subjects had abnormal gait. Mean full scale IQ was 80.4 ± 17.3. EEG evaluations revealed right-sided abnormalities in five subjects and bilateral abnormalities in one subject. Compared to age- and gender-matched controls, subjects with galactosemia had reduced volume in left cerebellum white matter, bilateral putamen, and left superior temporal sulcus. Galactosemia patients also had lower fractional anisotropy and higher radial diffusivity values in the dorsal and ventral language networks compared to the controls. Furthermore, there were significant correlations between neuropsychological test results and the T1 volume and diffusivity scalars. Our findings help to identify anatomic correlates to motor control, learning and memory, and language in subjects with galactosemia. The results from this preliminary assessment may provide insights into the pathophysiology of this inborn error of metabolism.
Collapse
Affiliation(s)
- Banu Ahtam
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Newborn Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Susan E Waisbren
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Vera Anastasoaie
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Gerard T Berry
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Matthew Brown
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Stephanie Petrides
- Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Onur Afacan
- Computational Radiology Laboratory, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Sanjay P Prabhu
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Donald Schomer
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - P Ellen Grant
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Newborn Medicine, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Patricia E Greenstein
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
23
|
Welsink-Karssies MM, Ferdinandusse S, Geurtsen GJ, Hollak CEM, Huidekoper HH, Janssen MCH, Langendonk JG, van der Lee JH, O'Flaherty R, Oostrom KJ, Roosendaal SD, Rubio-Gozalbo ME, Saldova R, Treacy EP, Vaz FM, de Vries MC, Engelen M, Bosch AM. Deep phenotyping classical galactosemia: clinical outcomes and biochemical markers. Brain Commun 2020; 2:fcaa006. [PMID: 32954279 PMCID: PMC7425409 DOI: 10.1093/braincomms/fcaa006] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 12/06/2019] [Accepted: 12/28/2019] [Indexed: 02/02/2023] Open
Abstract
Early diagnosis and dietary treatment do not prevent long-term complications, which mostly affect the central nervous system in classical galactosemia patients. The clinical outcome of patients is highly variable, and there is an urgent need for prognostic biomarkers. The aim of this study was first to increase knowledge on the natural history of classical galactosemia by studying a cohort of patients with varying geno- and phenotypes and second to study the association between clinical outcomes and two possible prognostic biomarkers. In addition, the association between abnormalities on brain MRI and clinical outcomes was investigated. Classical galactosemia patients visiting the galactosemia expertise outpatient clinic of the Amsterdam University Medical Centre were evaluated according to the International Classical Galactosemia guideline with the addition of an examination by a neurologist, serum immunoglobulin G N-glycan profiling and a brain MRI. The biomarkers of interest were galactose-1-phosphate levels and N-glycan profiles, and the clinical outcomes studied were intellectual outcome and the presence or absence of movement disorders and/or primary ovarian insufficiency. Data of 56 classical galactosemia patients are reported. The intellectual outcome ranged from 45 to 103 (mean 77 ± 14) and was <85 in 62%. Movement disorders were found in 17 (47%) of the 36 tested patients. In females aged 12 years and older, primary ovarian insufficiency was diagnosed in 12 (71%) of the 17 patients. Significant differences in N-glycan peaks were found between controls and patients. However, no significant differences in either N-glycans or galactose-1-phosphate levels were found between patients with a poor (intellectual outcome < 85) and normal intellectual outcome (intellectual outcome ≥ 85), and with or without movement disorders or primary ovarian insufficiency. The variant patients detected by newborn screening, with previously unknown geno- and phenotypes and currently no long-term complications, demonstrated significantly lower galactose-1-phospate levels than classical patients (P < 0.0005). Qualitative analysis of the MRI's demonstrated brain abnormalities in 18 of the 21 patients, more severely in patients with a lower intellectual outcome and/or with movement disorders. This study demonstrates a large variability in clinical outcome, which varies from a below average intelligence, movement disorders and in females primary ovarian insufficiency to a normal clinical outcome. In our cohort of classical galactosemia patients, galactose-1-phosphate levels and N-glycan variations were not associated with clinical outcomes, but galactose-1-phosphate levels did differentiate between classical and variant patients detected by newborn screening. The correlation between brain abnormalities and clinical outcome should be further investigated by quantitative analysis of the MR images. The variability in clinical outcome necessitates individual and standardized evaluation of all classical galactosemia patients.
Collapse
Affiliation(s)
- Mendy M Welsink-Karssies
- Division of Metabolic Disorders, Department of Pediatrics, Emma Children's Hospital, Amsterdam, UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Sacha Ferdinandusse
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Gert J Geurtsen
- Department of Medical Psychology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Carla E M Hollak
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Hidde H Huidekoper
- Department of Pediatrics, Center for Lysosomal and Metabolic Diseases, Erasmus, MC, University Medical Center, Rotterdam, the Netherlands
| | - Mirian C H Janssen
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Janneke G Langendonk
- Department of Internal Medicine, Center for Lysosomal and Metabolic Diseases, Erasmus MC University Medical Centre, Rotterdam, the Netherlands
| | - Johanna H van der Lee
- Pediatric Clinical Research Office, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Knowledge Institute of the Dutch Association of Medical Specialists, Utrecht, the Netherlands
| | - Roisin O'Flaherty
- NIBRT GlycoScience Group, National Institute for Bioprocessing, Research and Training, Mount Merrion, Blackrock, County Dublin, Ireland
| | - Kim J Oostrom
- Psychosocial Department, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Stefan D Roosendaal
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics, Maastricht University Medical Center, Maastricht, the Netherlands.,Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Radka Saldova
- Knowledge Institute of the Dutch Association of Medical Specialists, Utrecht, the Netherlands.,UCD School of Medicine, College of Health and Agricultural Science, University College Dublin, Dublin, Ireland
| | - Eileen P Treacy
- National Centre for Inherited Metabolic Disorders, The Mater Misericordiae University Hospital, Dublin, Ireland
| | - Fred M Vaz
- Laboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Maaike C de Vries
- Department of Pediatrics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Marc Engelen
- Department of Pediatric Neurology, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Annet M Bosch
- Division of Metabolic Disorders, Department of Pediatrics, Emma Children's Hospital, Amsterdam, UMC, University of Amsterdam, Amsterdam, the Netherlands
| |
Collapse
|
24
|
Kamiya K, Hori M, Aoki S. NODDI in clinical research. J Neurosci Methods 2020; 346:108908. [PMID: 32814118 DOI: 10.1016/j.jneumeth.2020.108908] [Citation(s) in RCA: 133] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 08/08/2020] [Accepted: 08/09/2020] [Indexed: 12/11/2022]
Abstract
Diffusion MRI (dMRI) has proven to be a useful imaging approach for both clinical diagnosis and research investigating the microstructures of nervous tissues, and it has helped us to better understand the neurophysiological mechanisms of many diseases. Though diffusion tensor imaging (DTI) has long been the default tool to analyze dMRI data in clinical research, acquisition with stronger diffusion weightings beyond the DTI regimen is now possible with modern clinical scanners, potentially enabling even more detailed characterization of tissue microstructures. To take advantage of such data, neurite orientation dispersion and density imaging (NODDI) has been proposed as a way to relate the dMRI signal to tissue features via biophysically inspired modeling. The number of reports demonstrating the potential clinical utility of NODDI is rapidly increasing. At the same time, the pitfalls and limitations of NODDI, and general challenges in microstructure modeling, are becoming increasingly recognized by clinicians. dMRI microstructure modeling is a rapidly evolving field with great promise, where people from different scientific backgrounds, such as physics, medicine, biology, neuroscience, and statistics, are collaborating to build novel tools that contribute to improving human healthcare. Here, we review the applications of NODDI in clinical research and discuss future perspectives for investigations toward the implementation of dMRI microstructure imaging in clinical practice.
Collapse
Affiliation(s)
- Kouhei Kamiya
- Department of Radiology, The University of Tokyo, Tokyo, Japan; Department of Radiology, Juntendo University, Tokyo, Japan; Department of Radiology, Toho University, Tokyo, Japan.
| | - Masaaki Hori
- Department of Radiology, Juntendo University, Tokyo, Japan; Department of Radiology, Toho University, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University, Tokyo, Japan
| |
Collapse
|
25
|
Armstrong NJ, Mather KA, Sargurupremraj M, Knol MJ, Malik R, Satizabal CL, Yanek LR, Wen W, Gudnason VG, Dueker ND, Elliott LT, Hofer E, Bis J, Jahanshad N, Li S, Logue MA, Luciano M, Scholz M, Smith AV, Trompet S, Vojinovic D, Xia R, Alfaro-Almagro F, Ames D, Amin N, Amouyel P, Beiser AS, Brodaty H, Deary IJ, Fennema-Notestine C, Gampawar PG, Gottesman R, Griffanti L, Jack CR, Jenkinson M, Jiang J, Kral BG, Kwok JB, Lampe L, C M Liewald D, Maillard P, Marchini J, Bastin ME, Mazoyer B, Pirpamer L, Rafael Romero J, Roshchupkin GV, Schofield PR, Schroeter ML, Stott DJ, Thalamuthu A, Trollor J, Tzourio C, van der Grond J, Vernooij MW, Witte VA, Wright MJ, Yang Q, Morris Z, Siggurdsson S, Psaty B, Villringer A, Schmidt H, Haberg AK, van Duijn CM, Jukema JW, Dichgans M, Sacco RL, Wright CB, Kremen WS, Becker LC, Thompson PM, Mosley TH, Wardlaw JM, Ikram MA, Adams HHH, Seshadri S, Sachdev PS, Smith SM, Launer L, Longstreth W, DeCarli C, Schmidt R, Fornage M, Debette S, Nyquist PA. Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities. Stroke 2020; 51:2111-2121. [PMID: 32517579 DOI: 10.1161/strokeaha.119.027544] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
Collapse
Affiliation(s)
- Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, Perth, Australia (N.J.A.)
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | | | - Maria J Knol
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU Munich, Germany (R.M., M.D.)
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX (C.L.S., S.S.).,The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Lisa R Yanek
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia
| | - Vilmundur G Gudnason
- Icelandic Heart Association, Kopavogur (V.G.G., S.S.).,University of Iceland, Reykjavik, Iceland (V.G.G., A.V.S.)
| | - Nicole D Dueker
- Dr. John T. Macdonald Foundation Department of Human Genetics (R.L.S.), University of Miami, FL
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, Canada (L.T.E.).,Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (E.H., R.S.).,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria (E.H.)
| | - Joshua Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Neda Jahanshad
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey (N.J., P.M.T.)
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Mark A Logue
- Department of Psychiatry and Biomedical Genetics Section (M.A.L.), Boston University School of Medicine, MA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.).,National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, MA (M.A.L.)
| | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology (M.S.)
| | - Albert V Smith
- University of Iceland, Reykjavik, Iceland (V.G.G., A.V.S.)
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Leiden University Medical Center, the Netherlands.,Department of Cardiology (S.T.), Leiden University Medical Center, the Netherlands
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, TX (R.X., M.F.)
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia (D.A.).,Academic Unit for Psychiatry of Old Age, University of Melbourne, St George's Hospital, Kew, Australia (D.A.)
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Philippe Amouyel
- Lille University, Inserm, Institut Pasteur de Lille, RID-AGE - Risk Factors and Molecular Determinants of Aging-Related Diseases and Labex Distalz, France (P.A.).,Lille University, Inserm, CHU Lille, Institut Pasteur de Lille, RID-AGE (P.A.)
| | - Alexa S Beiser
- The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Dementia Centre for Research Collaboration (H.B.), University of New South Wales, Sydney, Australia
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Christine Fennema-Notestine
- Department of Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, CA.,Center for Behavior Genetics of Aging (C.F.-N.), University of California, San Diego, La Jolla, CA
| | - Piyush G Gampawar
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Austria (P.G.G., H.S.)
| | - Rebecca Gottesman
- Department of Neurology, Cerebrovascular and stroke Division (R.G.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN (C.R.J.J.)
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia
| | - Brian G Kral
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - John B Kwok
- School of Medical Sciences (J.B.K., P.R.S.), University of New South Wales, Sydney, Australia.,Brain and Mind Centre - The University of Sydney, Camperdown, NSW, Australia (J.B.K.)
| | - Leonie Lampe
- Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (L.L., V.A.W.)
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Pauline Maillard
- Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology, University of California-Davis, Davis, CA (P.M.)
| | - Jonathan Marchini
- Statistical Genetics and Methods at Regeneron Pharmaceuticals, Inc, New York, NY (J.M.)
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.).,Centre for Clinical Brain Sciences, Edinburgh Imaging, Centre for Cognitive Ageing, University of Edinburgh, United Kingdom (M.E.B., J.M.W.)
| | - Bernard Mazoyer
- Institut des Maladies Neurodégénératives, University of Bordeaux, France (B.M.)
| | - Lukas Pirpamer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (L.P.)
| | - José Rafael Romero
- The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Gennady V Roshchupkin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.)
| | - Peter R Schofield
- School of Medical Sciences (J.B.K., P.R.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | - Matthias L Schroeter
- LIFE Research Center for Civilization Disease, Leipzig, Germany (M.S.).,Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (M.L.S., A.V.).,Day Clinic for Cognitive Neurology, University Hospital Leipzig, Germany (M.L.S., A.V.)
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, United Kingdom (D.J.S.)
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Department of Developmental Disability Neuropsychiatry, School of Psychiatry (J.T.), University of New South Wales, Sydney, Australia
| | - Christophe Tzourio
- University Bordeaux, Inserm, Bordeaux Population Health Research Center, France (M.S., C.T., S.D.).,CHU de Bordeaux, Public Health Department, Medical information Department, Bordeaux, France (C.T.)
| | - Jeroen van der Grond
- Department of Radiology (J.v.d.G.), Leiden University Medical Center, the Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.)
| | - Veronica A Witte
- Collaborative Research Center 1052 Obesity Mechanisms, Faculty of Medicine, University of Leipzig, Germany (V.A.W).,Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (L.L., V.A.W.)
| | - Margaret J Wright
- Queensland Brain Institute (M.J.W.), The University of Queensland, St Lucia, QLD, Australia.,Centre for Advanced Imaging (M.J.W.), The University of Queensland, St Lucia, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Zoe Morris
- Neuroradiology Department, Department of Clinical Neurosciences, Western General Hospital, Edinburgh, United Kingdom (Z.M.)
| | - Siggi Siggurdsson
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX (C.L.S., S.S.).,The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Bruce Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Arno Villringer
- Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (M.L.S., A.V.).,Day Clinic for Cognitive Neurology, University Hospital Leipzig, Germany (M.L.S., A.V.)
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Austria (P.G.G., H.S.)
| | - Asta K Haberg
- Department of Neuromedicine and Movement Science (A.K.H.), Norwegian University of Science and Technology, Trondheim, Norway.,Department of Radiology and Nuclear Medicine (A.K.H.), Norwegian University of Science and Technology, Trondheim, Norway
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Nuffield Department of Population Health (C.M.v.D.), University of Oxford, United Kingdom
| | - J Wouter Jukema
- Department of Cardiology (J.W.J.), Leiden University Medical Center, the Netherlands.,Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, the Netherlands (J.W.J.)
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU Munich, Germany (R.M., M.D.).,German Center for Neurodegenerative Diseases, Munich, Germany (M.D.).,Munich Cluster for Systems Neurology (SyNergy), Germany (M.D.)
| | - Ralph L Sacco
- Department of Public Health Sciences, Miller School of Medicine (R.L.S.), University of Miami, FL.,Department of Neurology, Miller School of Medicine (R.L.S.), University of Miami, FL.,Evelyn F. McKnight Brain Institute, Department of Neurology (R.L.S.), University of Miami, FL
| | - Clinton B Wright
- National Institute of Neurological Disorders and Stroke (C.B.W.), National Institutes of Health, Bethesda, MD
| | - William S Kremen
- Center for Behavior Genetics of Aging (W.S.K.), University of California, San Diego, La Jolla, CA.,Department of Psychiatry (W.S.K.), University of California, San Diego, La Jolla, CA
| | - Lewis C Becker
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Paul M Thompson
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey (N.J., P.M.T.)
| | - Thomas H Mosley
- Department of Geriatric Medicine, Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson (T.H.M.)
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.).,Centre for Clinical Brain Sciences, Edinburgh Imaging, Centre for Cognitive Ageing, University of Edinburgh, United Kingdom (M.E.B., J.M.W.)
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.).,Department of Clinical Genetics, Erasmus MC, Rotterdam, the Netherlands (H.H.H.A.)
| | | | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia (P.S.S.)
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program (L.L.), National Institutes of Health, Bethesda, MD
| | - William Longstreth
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Charles DeCarli
- Alzheimer's Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience University of California at Davis (C.D.)
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (E.H., R.S.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, TX (R.X., M.F.).,Human Genetics Center, School of Public Health UT, Houston, TX (M.F.)
| | - Stephanie Debette
- University Bordeaux, Inserm, Bordeaux Population Health Research Center, France (M.S., C.T., S.D.).,Department of Neurology, CHU de Bordeaux (University Hospital), Bordeaux, France (S.D.)
| | - Paul A Nyquist
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD.,Departments of Neurology, Critical Care Medicine, Neurosurgery (P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD.,Critical Care Medicine Department (P.A.N.), National Institutes of Health, Bethesda, MD
| |
Collapse
|
26
|
Kelly CE, Thompson DK, Chen J, Josev EK, Pascoe L, Spencer-Smith MM, Adamson C, Nosarti C, Gathercole S, Roberts G, Lee KJ, Doyle LW, Seal ML, Anderson PJ. Working memory training and brain structure and function in extremely preterm or extremely low birth weight children. Hum Brain Mapp 2019; 41:684-696. [PMID: 31713952 PMCID: PMC6977425 DOI: 10.1002/hbm.24832] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 10/05/2019] [Accepted: 10/08/2019] [Indexed: 01/31/2023] Open
Abstract
This study in children born extremely preterm (EP; <28 weeks' gestational age) or extremely low birth weight (ELBW; <1,000 g) investigated whether adaptive working memory training using Cogmed® is associated with structural and/or functional brain changes compared with a placebo program. Ninety-one EP/ELBW children were recruited at a mean (standard deviation) age of 7.8 (0.4) years. Children were randomly allocated to Cogmed or placebo (45-min sessions, 5 days a week over 5-7 weeks). A subset had usable magnetic resonance imaging (MRI) data pretraining and 2 weeks posttraining (structural, n = 48; diffusion, n = 43; task-based functional, n = 18). Statistical analyses examined whether cortical morphometry, white matter microstructure and blood oxygenation level-dependent (BOLD) signal during an n-back working memory task changed from pretraining to posttraining in the Cogmed and placebo groups separately. Interaction analyses between time point and group were then performed. There was a significant increase in neurite density in several white matter regions from pretraining to posttraining in both the Cogmed and placebo groups. BOLD signal in the posterior cingulate and precuneus cortices during the n-back task increased from pretraining to posttraining in the Cogmed but not placebo group. Evidence for group-by-time interactions for the MRI measures was weak, suggesting that brain changes generally did not differ between Cogmed and placebo groups. Overall, while some structural and functional MRI changes between the pretraining and posttraining period in EP/ELBW children were observed, there was little evidence of training-induced neuroplasticity, with changes generally identified in both groups. Trial registration Australian New Zealand Clinical Trials Registry, anzctr.org.au; ACTRN12612000124831.
Collapse
Affiliation(s)
- Claire E Kelly
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Deanne K Thompson
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jian Chen
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Elisha K Josev
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Neurodisability and Rehabilitation, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Leona Pascoe
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Megan M Spencer-Smith
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Chris Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Susan Gathercole
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Gehan Roberts
- Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Health Services, Population Health, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Centre for Community Child Health, Royal Children's Hospital, Melbourne, Victoria, Australia
| | - Katherine J Lee
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Clinical Epidemiology & Biostatistics Unit, Murdoch Children's Research Institute, Melbourne, Australia
| | - Lex W Doyle
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.,Newborn Research, The Royal Women's Hospital, Melbourne, Victoria, Australia.,Department of Obstetrics and Gynaecology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Marc L Seal
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Peter J Anderson
- Victorian Infant Brain Studies (VIBeS), Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| |
Collapse
|
27
|
Hermans ME, Welsink-Karssies MM, Bosch AM, Oostrom KJ, Geurtsen GJ. Cognitive functioning in patients with classical galactosemia: a systematic review. Orphanet J Rare Dis 2019; 14:226. [PMID: 31627760 PMCID: PMC6798502 DOI: 10.1186/s13023-019-1215-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 09/24/2019] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Patients with the metabolic disorder classical galactosemia suffer from long-term complications despite a galactose-restricted diet, including a below average intelligence level. The aim of the current review was to investigate the incidence and profile of cognitive impairments in patients with classical galactosemia. METHOD MEDLINE, EMBASE and PsychINFO were searched up to 23 October 2018 for studies examining information processing speed, attention, memory, language, visuospatial functioning, executive functioning and social cognition in patients with confirmed classical galactosemia utilizing standardized neuropsychological tests. Data synthesis followed a narrative approach, since the planned meta-analysis was not possible due to large variability between the neuropsychological assessments. RESULTS Eleven studies were included, including case-studies. The quality of most studies was moderate to low. As a group, patients with classical galactosemia exhibit below average to low scores on all cognitive domains. A large proportion of the patients perform on an impaired level on attention, memory and vocabulary. Evidence for impairments in information processing speed, language, visuospatial functioning and aspects of executive functioning was limited due to the small number of studies investigating these cognitive functions. Social cognition was not examined at all. CONCLUSIONS Given the moderate to low quality of the included studies and the limited evidence in many cognitive domains, the incidence of cognitive impairment in patients with classical galactosemia is not yet clear. Both clinicians and researchers encountering patients with classical galactosemia need to be aware of possible cognitive impairments. Future well-designed studies are needed to determine the cognitive profile of classical galactosemia. This can be the basis for the development of intervention strategies.
Collapse
Affiliation(s)
- Merel E Hermans
- Department of Medical Psychology, Amsterdam UMC - location AMC, P.O. Box 22660, 1100 DD, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Mendy M Welsink-Karssies
- Department of Pediatrics, Amsterdam UMC - location AMC, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Annet M Bosch
- Department of Pediatrics, Amsterdam UMC - location AMC, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Kim J Oostrom
- Psychosocial Department, Emma Children's Hospital/Amsterdam UMC - location AMC, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands
| | - Gert J Geurtsen
- Department of Medical Psychology, Amsterdam UMC - location AMC, P.O. Box 22660, 1100 DD, Meibergdreef 9, 1105, AZ, Amsterdam, The Netherlands.
| |
Collapse
|
28
|
Fukutomi H, Glasser MF, Murata K, Akasaka T, Fujimoto K, Yamamoto T, Autio JA, Okada T, Togashi K, Zhang H, Van Essen DC, Hayashi T. Diffusion Tensor Model links to Neurite Orientation Dispersion and Density Imaging at high b-value in Cerebral Cortical Gray Matter. Sci Rep 2019; 9:12246. [PMID: 31439874 PMCID: PMC6706419 DOI: 10.1038/s41598-019-48671-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 08/05/2019] [Indexed: 12/19/2022] Open
Abstract
Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture.
Collapse
Affiliation(s)
- Hikaru Fukutomi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe, 650-0047 Japan ,0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Matthew F. Glasser
- 0000 0001 2355 7002grid.4367.6Department of Neuroscience, Washington University School of Medicine, Campus Box 8108, 660 South Euclid Avenue, St. Louis, MO 63110 USA ,0000 0001 2355 7002grid.4367.6Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave., St. Louis, MO 63110 USA
| | - Katsutoshi Murata
- Siemens Healthcare K.K., Gate City Osaki West Tower, 1-11-1, Osaki, Shinagawa-ku, Tokyo, 141-8644 Japan
| | - Thai Akasaka
- 0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Koji Fujimoto
- 0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Takayuki Yamamoto
- 0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Joonas A. Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe, 650-0047 Japan
| | - Tomohisa Okada
- 0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Kaori Togashi
- 0000 0004 0372 2033grid.258799.8Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kawaramachi 54, Shogoin, Sakyo-ku, Kyoto city, 606-8507 Japan
| | - Hui Zhang
- 0000000121901201grid.83440.3bCentre for Medical Image Computing and Department of Computer Science, University College London, The Front Engineering Building, Floor 3, Malet Place, London, WC1E 7JE UK
| | - David C. Van Essen
- 0000 0001 2355 7002grid.4367.6Department of Neuroscience, Washington University School of Medicine, Campus Box 8108, 660 South Euclid Avenue, St. Louis, MO 63110 USA
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 Minatojima-minamimachi, Chuo-ku, Kobe, 650-0047, Japan. .,RIKEN Compass to Healthy Life Research Complex Program, Integrated Innovation Building (IIB), 6-7-1 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo, Japan.
| |
Collapse
|
29
|
Potter NL, Nievergelt Y, VanDam M. Tongue Strength in Children With and Without Speech Sound Disorders. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2019; 28:612-622. [PMID: 31136240 PMCID: PMC6802864 DOI: 10.1044/2018_ajslp-18-0023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 05/01/2018] [Accepted: 10/23/2018] [Indexed: 06/01/2023]
Abstract
Purpose The purpose of this cross-sectional investigation was to expand the comparative database of pediatric tongue strength for children and adolescents with typical development, ages 3-17 years, and compare tongue strength among children with typical development, speech sound delay/disorders (SD), and motor speech disorders (MSDs). Method Tongue strength was measured using the Iowa Oral Performance Instrument in a total of 286 children and adolescents, 228 with typical development, 16 with SD, and 42 with MSDs, including classic galactosemia, a known risk factor for MSD ( n = 33) and idiopathic MSD ( n = 9). Results For all groups, tongue strength increased rapidly from 3 to 6.5 years of age and then continued to increase with age at a slower rate until 17 years of age. Children with SD's tongue strength did not differ from their typically developing (TD) peers. Children and adolescents with MSDs had decreased tongue strength compared to children with typical development or SD. Tongue strength was not related to severity of speech sound disorders in SD or MSD. Conclusion Weak tongue strength does not appear to contribute to speech errors in children with speech sound delays but does appear to be related to speech sound disorders that are neurologic in origin (developmental MSD).
Collapse
Affiliation(s)
- Nancy L Potter
- Department of Speech and Hearing Sciences, Washington State University Spokane
| | - Yves Nievergelt
- Department of Mathematics, Eastern Washington University, Cheney
| | - Mark VanDam
- Department of Speech and Hearing Sciences, Washington State University Spokane
| |
Collapse
|
30
|
Alexander DC, Dyrby TB, Nilsson M, Zhang H. Imaging brain microstructure with diffusion MRI: practicality and applications. NMR IN BIOMEDICINE 2019; 32:e3841. [PMID: 29193413 DOI: 10.1002/nbm.3841] [Citation(s) in RCA: 205] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Revised: 07/09/2017] [Accepted: 09/11/2017] [Indexed: 05/22/2023]
Abstract
This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.
Collapse
Affiliation(s)
- Daniel C Alexander
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK
| | - Tim B Dyrby
- Danish Research Centre for Magnetic Resonance, Center for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Markus Nilsson
- Clinical Sciences Lund, Department of Radiology, Lund University, Lund, Sweden
| | - Hui Zhang
- Centre for Medical Image Computing (CMIC), Department of Computer Science, UCL (University College London), Gower Street, London, UK
| |
Collapse
|
31
|
Abstract
This is an introduction to the special issue on cognitive impairments in inherited metabolic diseases (IMD). It provides an overview of the studies included, focusing on the possibility of selective impairments which could provide unique evidence on the specificity of neural circuitries mediating cognitive functions. It will suggest that these circuitries have different metabolic properties which make them especially apt to carry out certain functions, but also particularly susceptible to certain forms of metabolic disruption. Knowledge of selective impairments is also crucial to properly evaluate the difficulties engendered by individual diseases and track treatment outcomes. IMR research holds the promise of a more complete understanding of cognition, from cellular functioning to behaviour and of further improvements in treatment. Advances, however, will require detailed assessments, comparisons across diseases, and the integration of different levels of explanation. This will be possible only through close collaborations between centres and types of professionals.
Collapse
Affiliation(s)
- Cristina Romani
- a School of Life and Health Sciences, Aston University , Birmingham , UK
| |
Collapse
|
32
|
Xiong Y, Zhang S, Shi J, Fan Y, Zhang Q, Zhu W. Application of neurite orientation dispersion and density imaging to characterize brain microstructural abnormalities in type-2 diabetics with mild cognitive impairment. J Magn Reson Imaging 2019; 50:889-898. [PMID: 30779402 DOI: 10.1002/jmri.26687] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 02/05/2019] [Accepted: 02/05/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diffusion-tensor-imaging (DTI) is sensitive in detecting white matter changes in type-2 diabetes mellitus (T2DM). However, DTI indices can be affected by either neurite density or spatial variation. A novel diffusion MRI technique, termed neurite orientation dispersion and density imaging (NODDI), can provide distinct indices of fiber density and dispersion. PURPOSE To characterize brain microstructural alterations in T2DM patients with mild cognitive impairment (MCI) using the NODDI model. STUDY TYPE Cross-sectional. SUBJECTS Twenty T2DM patients with (DM-MCI group), 18 age- and gender-matched T2DM patients with normal cognition (DM-NC group), and 28 euglycemic healthy controls (HC). FIELD STRENGTH/SEQUENCE 3T/NODDI. ASSESSMENT Diffusion data were analyzed using tract-based-spatial-statistics (TBSS) analysis in white matter and voxel-based analysis in both white and gray matter. NODDI indices, including intracellular volume fraction (Vic) and orientation dispersion index (ODI), were estimated from multiple regions and compared among these groups. STATISTICAL TESTS Differences between groups were compared by Student's t-test, Pearson chi-square test, or analysis of variance when appropriate. Correlation analyses were performed to investigate the relationship between NODDI variables and clinical measurements. RESULTS Whole-brain TBSS revealed that 2.29% and 2.02% of the white matter regions exhibited decreased fractional anisotropy and Vic, respectively, between the DM-NC and HC, while considerably larger white matter areas showed decreased fractional anisotropy (38.38%) and Vic (34.64%) between the DM-MCI and HC (Student's t-test, P < 0.05). However, the angular variation of neurites, characterized by ODI, exhibited very little (0.1%, P < 0.05) or no difference (P > 0.05) between either the DM-MCI or DM-NC groups and HC. Decreased Vic values in the genu of the corpus callosum (R = 0.580, 0.551 and 0.586, P < 0.01) and thalamus (R = 0.570, 0.616, and 0.595, P < 0.05) correlated with glycosylated hemoglobin A1c level, disease duration, and neuropsychological scores, respectively. DATA CONCLUSION T2DM patients with cognitive decline had reduced Vic, which indicated decreased density of axons and dendrites. NODDI might be able to help probe microstructural changes in white and gray matter and provide information on diabetic encephalopathy, including those with cognitive impairment. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:889-898.
Collapse
Affiliation(s)
- Ying Xiong
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shuoqi Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jingjing Shi
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | | | - Qiang Zhang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
33
|
Mustafi SM, Harezlak J, Kodiweera C, Randolph JS, Ford JC, Wishart HA, Wu YC. Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging. Neural Regen Res 2019; 14:114-123. [PMID: 30531085 PMCID: PMC6262996 DOI: 10.4103/1673-5374.243716] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients (age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis (n = 5) or clinically isolated syndrome (n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-space analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.
Collapse
Affiliation(s)
- Sourajit M Mustafi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, IN, USA
| | - Chandana Kodiweera
- Department of Psychological and Brain Sciences and Dartmouth Brain Imaging Center, Dartmouth College, Hanover, NH, USA
| | - Jennifer S Randolph
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - James C Ford
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Heather A Wishart
- Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN; Department of Psychological and Brain Sciences and Dartmouth Brain Imaging Center, Dartmouth College, Hanover, NH, USA
| |
Collapse
|
34
|
Wu YC, Mustafi SM, Harezlak J, Kodiweera C, Flashman LA, McAllister TW. Hybrid Diffusion Imaging in Mild Traumatic Brain Injury. J Neurotrauma 2018; 35:2377-2390. [PMID: 29786463 PMCID: PMC6196746 DOI: 10.1089/neu.2017.5566] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Mild traumatic brain injury (mTBI) is an important public health problem. Although conventional medical imaging techniques can detect moderate-to-severe injuries, they are relatively insensitive to mTBI. In this study, we used hybrid diffusion imaging (HYDI) to detect white matter alterations in 19 patients with mTBI and 23 other trauma control patients. Within 15 days (standard deviation = 10) of brain injury, all subjects underwent magnetic resonance HYDI and were assessed with a battery of neuropsychological tests of sustained attention, memory, and executive function. Tract-based spatial statistics (TBSS) was used for voxel-wise statistical analyses within the white matter skeleton to study between-group differences in diffusion metrics, within-group correlations between diffusion metrics and clinical outcomes, and between-group interaction effects. The advanced diffusion imaging techniques, including neurite orientation dispersion and density imaging (NODDI) and q-space analyses, appeared to be more sensitive then classic diffusion tensor imaging. Only NODDI-derived intra-axonal volume fraction (Vic) demonstrated significant group differences (i.e., 5–9% lower in the injured brain). Within the mTBI group, Vic and a q-space measure, P0, correlated with 6 of 10 neuropsychological tests, including measures of attention, memory, and executive function. In addition, the direction of correlations differed significantly between groups (R2 > 0.71 and pinteration < 0.03). Specifically, in the control group, higher Vic and P0 were associated with better performances on clinical assessments, whereas in the mTBI group, higher Vic and P0 were associated with worse performances with correlation coefficients >0.83. In summary, the NODDI-derived axonal density index and q-space measure for tissue restriction demonstrated superior sensitivity to white matter changes shortly after mTBI. These techniques hold promise as a neuroimaging biomarker for mTBI.
Collapse
Affiliation(s)
- Yu-Chien Wu
- 1 Department of Radiology and Imaging Sciences, Indiana University School of Medicine , Indianapolis, Indiana
| | - Sourajit M Mustafi
- 1 Department of Radiology and Imaging Sciences, Indiana University School of Medicine , Indianapolis, Indiana
| | - Jaroslaw Harezlak
- 2 Department of Epidemiology and Biostatistics, School of Public Health, Indiana University , Bloomington, Indiana
| | - Chandana Kodiweera
- 3 Dartmouth Brain Imaging Center, Dartmouth College , Hanover, New Hampshire
| | - Laura A Flashman
- 4 Department of Psychiatry, Geisel School of Medicine at Dartmouth and Dartmouth-Hitchcock Medical Center , Lebanon, New Hampshire
| | - Thomas W McAllister
- 5 Department of Psychiatry, Indiana University School of Medicine , Indianapolis, Indiana
| |
Collapse
|
35
|
Demirbas D, Coelho AI, Rubio-Gozalbo ME, Berry GT. Hereditary galactosemia. Metabolism 2018; 83:188-196. [PMID: 29409891 DOI: 10.1016/j.metabol.2018.01.025] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 01/19/2018] [Accepted: 01/24/2018] [Indexed: 10/18/2022]
Abstract
Hereditary galactosemia is an inborn error of carbohydrate metabolism. Galactose is metabolized by Leloir pathway enzymes; galactokinase (GALK), galactose-1-phosphate uridylyltransferase (GALT) and UDP-galactose 4-epimerase (GALE). The defects in these enzymes cause galactosemia in an autosomal recessive manner. The severe GALT deficiency, or classic galactosemia, is life-threatening in the newborn period. The treatment for classic galactosemia is dietary restriction of lactose. Although implementation of lactose restricted diet is efficient in resolving the acute complications, it is not sufficient to prevent long-term complications affecting the brain and female gonads, the two main target organs of damage. Implementation of molecular genetics diagnostic tools and GALT enzyme assays are instrumental in distinguishing classic galactosemia from clinical and biochemical variant forms of GALT deficiency. Better understanding of mechanisms responsible for the phenotypic variation even within the same genotype is essential to provide appropriate counseling for families. Utilization of a lactose restricted diet is also recommended for GALK deficiency and some rare forms of GALE deficiency. Novel modes of therapies are being explored; they may be beneficial if access issues to the affected tissues are circumvented and optimum use of therapeutic window is achieved.
Collapse
Affiliation(s)
- Didem Demirbas
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ana I Coelho
- Department of Pediatrics, Department of Clinical Genetics, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics, Department of Clinical Genetics, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Gerard T Berry
- Division of Genetics and Genomics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
36
|
Fukutomi H, Glasser MF, Zhang H, Autio JA, Coalson TS, Okada T, Togashi K, Van Essen DC, Hayashi T. Neurite imaging reveals microstructural variations in human cerebral cortical gray matter. Neuroimage 2018; 182:488-499. [PMID: 29448073 DOI: 10.1016/j.neuroimage.2018.02.017] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 01/08/2018] [Accepted: 02/09/2018] [Indexed: 12/27/2022] Open
Abstract
We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture.
Collapse
Affiliation(s)
- Hikaru Fukutomi
- RIKEN Center for Life Science Technologies, Kobe, Japan; Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Matthew F Glasser
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA; St. Luke's Hospital, St. Louis, MO, USA
| | - Hui Zhang
- Centre for Medical Image Computing and Department of Computer Science, University College London, UK
| | | | - Timothy S Coalson
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Tomohisa Okada
- RIKEN Center for Life Science Technologies, Kobe, Japan; Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Takuya Hayashi
- RIKEN Center for Life Science Technologies, Kobe, Japan; RIKEN Compass to Healthy Life Research Complex Program, Kobe, Japan.
| |
Collapse
|
37
|
Gatto RG, Mustafi SM, Amin MY, Mareci TH, Wu YC, Magin RL. Neurite orientation dispersion and density imaging can detect presymptomatic axonal degeneration in the spinal cord of ALS mice. FUNCTIONAL NEUROLOGY 2018; 33:155-163. [PMID: 30457969 PMCID: PMC7212765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Neurite orientation dispersion and density imaging (NODDI), a MRI multi-shell diffusion technique, has offered new insights for the study of microstructural changes in neurodegenerative diseases. Mainly, the present study aimed to determine the connection between NODDI-derived parameters and changes in white matter (WM) abnormalities at early stages of amyotrophic lateral sclerosis (ALS). Spinal cords from ALS mice (G93A-SOD1 mice) were scanned in a Bruker Avance III HD 17.6T magnet. Fluorescent axonal-tagged mice (YFP, G93A-SOD1 mice) were used for quantitative histological analysis. NODDI showed a decrease in intra-cellular volume fraction (-24%) and increases in orientation dispersion index (+35%) and isotropic volume fraction (+33%). In addition, histoathological results demonstrated a reductions in axonal area (-11%) and myelin content (-29%). A histological decrease in WM intra-axonal space (-71%) and an increase in the extra-axonal compartment (+22%) were also detected. Our studies demonstrate that NODDI may be a suitable technique for detecting presymptomatic spinal cord WM microstructural degeneration in ALS.
Collapse
Affiliation(s)
- Rodolfo G. Gatto
- Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, USA
| | - Sourajit M. Mustafi
- Department of Radiology and Imaging Sciences, Indiana University, School of Medicine Indianapolis, IN, USA
| | - Manish Y. Amin
- Department of Physics, University of Florida, Gainesville, FL, USA
| | - Thomas H. Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University, School of Medicine Indianapolis, IN, USA
| | - Richard L. Magin
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| |
Collapse
|
38
|
Exploration of the Brain in Rest: Resting-State Functional MRI Abnormalities in Patients with Classic Galactosemia. Sci Rep 2017; 7:9095. [PMID: 28831125 PMCID: PMC5567355 DOI: 10.1038/s41598-017-09242-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 07/17/2017] [Indexed: 01/01/2023] Open
Abstract
Patients with classic galactosemia, a genetic metabolic disorder, encounter cognitive impairments, including motor (speech), language, and memory deficits. We used functional magnetic resonance imaging to evaluate spontaneous functional connectivity during rest to investigate potential abnormalities in neural networks. We characterized networks using seed-based correlation analysis in 13 adolescent patients and 13 matched controls. Results point towards alterations in several networks, including well-known resting-state networks (e.g. default mode, salience, visual network). Particularly, patients showed alterations in networks encompassing medial prefrontal cortex, parietal lobule and (pre)cuneus, involved in spatial orientation and attention. Furthermore, altered connectivity of networks including the insula and superior frontal gyrus -important for sensory-motor integration and motor (speech) planning- was demonstrated. Lastly, abnormalities were found in networks involving occipital regions, linked to visuospatial capacities and working memory. Importantly, across several seeds, altered functional connectivity to the superior frontal cortex, anterior insula, parietal lobule and the (pre)cuneus was observed in patients, suggesting special importance of these brain regions. Moreover, these alterations correlated with neurocognitive test results, supporting a relation with the clinical phenotype. Our findings contribute to improved characterization of brain impairments in classic galactosemia and provide directions for further investigations.
Collapse
|
39
|
Coelho AI, Bierau J, Lindhout M, Achten J, Kramer BW, Rubio-Gozalbo ME. Classic Galactosemia: Study on the Late Prenatal Development of GALT Specific Activity in a Sheep Model. Anat Rec (Hoboken) 2017; 300:1570-1575. [PMID: 28545161 DOI: 10.1002/ar.23616] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Revised: 11/14/2016] [Accepted: 12/27/2016] [Indexed: 11/06/2022]
Abstract
Classic galactosemia results from deficient activity of galactose-1-phosphate uridylyltransferase (GALT), a key enzyme of galactose metabolism. Despite early diagnosis and early postnatal therapeutic intervention, patients still develop neurologic and fertility impairments. Prenatal developmental toxicity has been hypothesized as a determinant factor of disease. In order to shed light on the importance of prenatal GALT activity, several studies have examined GALT activity throughout development. GALT was shown to increase with gestational age in 7-28 weeks human fetuses; later stages were not investigated. Prenatal studies in animals focused exclusively on brain and hepatic GALT activity. In this study, we aim to examine GALT specific activity in late prenatal and adult stages, using a sheep model. Galactosemia acute target-organs-liver, small intestine and kidney-had the highest late prenatal activity, whereas the chronic target-organs-brain and ovary-did not exhibit a noticeable pre- or postnatal different activity compared with nontarget organs. This is the first study on GALT specific activity in the late prenatal stage for a wide variety of organs. Our findings suggest that GALT activity cannot be the sole pathogenic factor accounting for galactosemia long-term complications, and that some organs/cells might have a greater susceptibility to galactose toxicity. Anat Rec, 300:1570-1575, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Ana I Coelho
- Department of Pediatrics, Maastricht University Medical Centre, Maastricht, The Netherlands.,Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jörgen Bierau
- Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Martijn Lindhout
- Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jelle Achten
- Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Boris W Kramer
- Department of Pediatrics/Neonatology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics, Maastricht University Medical Centre, Maastricht, The Netherlands.,Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| |
Collapse
|
40
|
Slattery CF, Zhang J, Paterson RW, Foulkes AJM, Carton A, Macpherson K, Mancini L, Thomas DL, Modat M, Toussaint N, Cash DM, Thornton JS, Henley SMD, Crutch SJ, Alexander DC, Ourselin S, Fox NC, Zhang H, Schott JM. ApoE influences regional white-matter axonal density loss in Alzheimer's disease. Neurobiol Aging 2017; 57:8-17. [PMID: 28578156 PMCID: PMC5538347 DOI: 10.1016/j.neurobiolaging.2017.04.021] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 04/14/2017] [Accepted: 04/22/2017] [Indexed: 01/10/2023]
Abstract
Mechanisms underlying phenotypic heterogeneity in young onset Alzheimer disease (YOAD) are poorly understood. We used diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI) with tract-based spatial statistics to investigate apolipoprotein (APOE) ε4 modulation of white-matter damage in 37 patients with YOAD (22, 59% APOE ε4 positive) and 23 age-matched controls. Correlation between neurite density index (NDI) and neuropsychological performance was assessed in 4 white-matter regions of interest. White-matter disruption was more widespread in ε4+ individuals but more focal (posterior predominant) in the absence of an ε4 allele. NODDI metrics indicate fractional anisotropy changes are underpinned by combinations of axonal loss and morphological change. Regional NDI in parieto-occipital white matter correlated with visual object and spatial perception battery performance (right and left, both p = 0.02), and performance (nonverbal) intelligence (WASI matrices, right, p = 0.04). NODDI provides tissue-specific microstructural metrics of white-matter tract damage in YOAD, including NDI which correlates with focal cognitive deficits, and APOEε4 status is associated with different patterns of white-matter neurodegeneration.
Collapse
Affiliation(s)
- Catherine F Slattery
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK.
| | - Jiaying Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Ross W Paterson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | | | - Amelia Carton
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Kirsty Macpherson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology, London, UK
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nicolas Toussaint
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - David M Cash
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK; Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Susie M D Henley
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Sebastian J Crutch
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Daniel C Alexander
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nick C Fox
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| |
Collapse
|
41
|
Coelho AI, Rubio-Gozalbo ME, Vicente JB, Rivera I. Sweet and sour: an update on classic galactosemia. J Inherit Metab Dis 2017; 40:325-342. [PMID: 28281081 PMCID: PMC5391384 DOI: 10.1007/s10545-017-0029-3] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 02/14/2017] [Accepted: 02/20/2017] [Indexed: 02/03/2023]
Abstract
Classic galactosemia is a rare inherited disorder of galactose metabolism caused by deficient activity of galactose-1-phosphate uridylyltransferase (GALT), the second enzyme of the Leloir pathway. It presents in the newborn period as a life-threatening disease, whose clinical picture can be resolved by a galactose-restricted diet. The dietary treatment proves, however, insufficient in preventing severe long-term complications, such as cognitive, social and reproductive impairments. Classic galactosemia represents a heavy burden on patients' and their families' lives. After its first description in 1908 and despite intense research in the past century, the exact pathogenic mechanisms underlying galactosemia are still not fully understood. Recently, new important insights on molecular and cellular aspects of galactosemia have been gained, and should open new avenues for the development of novel therapeutic strategies. Moreover, an international galactosemia network has been established, which shall act as a platform for expertise and research in galactosemia. Herein are reviewed some of the latest developments in clinical practice and research findings on classic galactosemia, an enigmatic disorder with many unanswered questions warranting dedicated research.
Collapse
Affiliation(s)
- Ana I Coelho
- Department of Pediatrics and Department of Clinical Genetics, Maastricht University Medical Centre, P. Debyelaan 25, PO Box 5800, 6202 AZ, Maastricht, The Netherlands.
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics and Department of Clinical Genetics, Maastricht University Medical Centre, P. Debyelaan 25, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
| | - João B Vicente
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
| | - Isabel Rivera
- Metabolism & Genetics Group, Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
- Department of Biochemistry and Human Biology, Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
| |
Collapse
|
42
|
Harms RL, Fritz FJ, Tobisch A, Goebel R, Roebroeck A. Robust and fast nonlinear optimization of diffusion MRI microstructure models. Neuroimage 2017; 155:82-96. [PMID: 28457975 PMCID: PMC5518773 DOI: 10.1016/j.neuroimage.2017.04.064] [Citation(s) in RCA: 75] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 04/07/2017] [Accepted: 04/09/2017] [Indexed: 02/07/2023] Open
Abstract
Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of run time, fit, accuracy and precision. Parameter initialization approaches were found to be relevant especially for more complex models, such as those involving several fiber orientations per voxel. For these, a fitting cascade initializing or fixing parameter values in a later optimization step from simpler models in an earlier optimization step further improved run time, fit, accuracy and precision compared to a single step fit. This establishes and makes available standards by which robust fit and accuracy can be achieved in shorter run times. This is especially relevant for the use of diffusion microstructure modeling in large group or population studies and in combining microstructure parameter maps with tractography results. Evaluate robustness of fit, accuracy, precision for diffusion microstructure models Test three optimization algorithms and three parameter initialization strategies GPU implementation removes run time constraints; whole brain fit within minutes Powell conjugate-direction algorithm has superior fit, accuracy, precision Initialization approaches are important for crossing fiber microstructure models
Collapse
Affiliation(s)
- R L Harms
- Dept. of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, The Netherlands; Brain Innovation B.V., Maastricht, The Netherlands.
| | - F J Fritz
- Dept. of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, The Netherlands
| | - A Tobisch
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - R Goebel
- Dept. of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, The Netherlands
| | - A Roebroeck
- Dept. of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, The Netherlands
| |
Collapse
|
43
|
Reimers CD, Hähnel S, Terborg C. [Central myelination disorder in classical galactosemia : Case report of two sisters]. DER NERVENARZT 2017; 88:188-190. [PMID: 27933355 DOI: 10.1007/s00115-016-0260-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Affiliation(s)
- C D Reimers
- MVZ Neurologie, Paracelsus-Klinik Bremen, In der Vahr 65, 28329, Bremen, Deutschland.
| | - S Hähnel
- Abteilung für Neuroradiologie, Neurologische Klinik, Universitätsklinikum Heidelberg, Ruprecht-Karls-Universität, Heidelberg, Deutschland
| | - C Terborg
- Neurologische Klinik, Asklepios Klinik St. Georg, Hamburg, Deutschland
| |
Collapse
|
44
|
Chen W, Caston R, Balakrishnan B, Siddiqi A, Parmar K, Tang M, Feng M, Lai K. Assessment of ataxia phenotype in a new mouse model of galactose-1 phosphate uridylyltransferase (GALT) deficiency. J Inherit Metab Dis 2017; 40:131-137. [PMID: 27783170 PMCID: PMC5203948 DOI: 10.1007/s10545-016-9993-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Revised: 10/10/2016] [Accepted: 10/11/2016] [Indexed: 12/14/2022]
Abstract
Despite adequate dietary management, patients with classic galactosemia continue to have increased risks of cognitive deficits, speech dyspraxia, primary ovarian insufficiency, and abnormal motor development. A recent evaluation of a new galactose-1 phosphate uridylyltransferase (GALT)-deficient mouse model revealed reduced fertility and growth restriction. These phenotypes resemble those seen in human patients. In this study, we further assess the fidelity of this new mouse model by examining the animals for the manifestation of a common neurological sequela in human patients: cerebellar ataxia. The balance, grip strength, and motor coordination of GALT-deficient and wild-type mice were tested using a modified rotarod. The results were compared to composite phenotype scoring tests, typically used to evaluate neurological and motor impairment. The data demonstrated abnormalities with varying severity in the GALT-deficient mice. Mice of different ages were used to reveal the progressive nature of motor impairment. The varying severity and age-dependent impairments seen in the animal model agree with reports on human patients. Finally, measurements of the cerebellar granular and molecular layers suggested that mutant mice experience cerebellar hypoplasia, which could have resulted from the down-regulation of the PI3K/Akt signaling pathway.
Collapse
Affiliation(s)
- Wyman Chen
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Rose Caston
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA
- Dartmouth College, Hanover, NH, USA
| | - Bijina Balakrishnan
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Anwer Siddiqi
- Department of Pathology and Laboratory Medicine, University of Florida College of Medicine, Jacksonville, FL, USA
| | - Kamalpreet Parmar
- Department of Pathology and Laboratory Medicine, University of Florida College of Medicine, Jacksonville, FL, USA
| | - Manshu Tang
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Merry Feng
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Kent Lai
- Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA.
| |
Collapse
|
45
|
Timmers I, Roebroeck A, Bastiani M, Jansma B, Rubio-Gozalbo E, Zhang H. Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI. PLoS One 2016; 11:e0167884. [PMID: 28002426 PMCID: PMC5176300 DOI: 10.1371/journal.pone.0167884] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 11/22/2016] [Indexed: 11/23/2022] Open
Abstract
Neurite orientation dispersion and density imaging (NODDI) enables more specific characterization of tissue microstructure by estimating neurite density (NDI) and orientation dispersion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. We assessed the added value of NODDI parameters over FA, by contrasting group differences identified by both models. Diffusion-weighted images with multiple shells were acquired in a group of 8 healthy controls and 8 patients with an inherited metabolic disease. Both standard DTI and NODDI analyses were performed. Tract based spatial statistics (TBSS) was used for group inferences, after which overlap and unique contributions across different parameters were evaluated. Results showed that group differences in NDI and ODI were complementary, and together could explain much of the FA results. Further, compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Finally, ODI from single-shell NODDI analysis, but not NDI, was found to reproduce the group differences from the multi-shell analysis. To conclude, by using a clinically feasible acquisition and analysis protocol, we demonstrated that NODDI is of added value to standard DTI, by revealing specific microstructural substrates to white matter changes detected with FA. As the (simpler) DTI model was more sensitive in identifying group differences, NODDI is recommended to be used complementary to DTI, thereby adding greater specificity regarding microstructural underpinnings of the differences. The finding that ODI abnormalities can be identified reliably using single-shell data may allow the retrospective analysis of standard DTI with NODDI.
Collapse
Affiliation(s)
- Inge Timmers
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Rehabilitation Medicine, Maastricht University, Maastricht, the Netherlands
- * E-mail:
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht, the Netherlands
| | - Matteo Bastiani
- Oxford Centre for Functional MRI of the Brain (FMRIB Centre), University of Oxford, Headington, Oxford, United Kingdom
| | - Bernadette Jansma
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, the Netherlands
- Maastricht Brain Imaging Center (M-BIC), Maastricht, the Netherlands
| | - Estela Rubio-Gozalbo
- Department of Pediatrics and Laboratory Genetic Metabolic Diseases, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, University College London, London, United Kingdom
| |
Collapse
|
46
|
Castro MB, Ferreira BK, Cararo JH, Chipindo AE, Magenis ML, Michels M, Danielski LG, de Oliveira MR, Ferreira GC, Streck EL, Petronilho F, Schuck PF. Evidence of oxidative stress in brain and liver of young rats submitted to experimental galactosemia. Metab Brain Dis 2016; 31:1381-1390. [PMID: 27389247 DOI: 10.1007/s11011-016-9865-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 06/28/2016] [Indexed: 10/21/2022]
Abstract
Galactosemia is a disorder of galactose metabolism, leading to the accumulation of this carbohydrate. Galactosemic patients present brain and liver damage. For evaluated oxidative stress, 30-day-old males Wistar rats were divided into two groups: galactose group, that received a single injection of this carbohydrate (5 μmol/g), and control group, that received saline 0.9 % in the same conditions. One, twelve or twenty-four hours after the administration, animals were euthanized and cerebral cortex, cerebellum, and liver were isolated. After one hour, it was found a significant increase in TBA-RS levels, nitrate and nitrite and protein carbonyl contents in cerebral cortex, as well as protein carbonyl content in the cerebellum and in hepatic level of TBA-RS, and a significant decrease in nitrate and nitrite contents in cerebellum. TBA-RS levels were also found increased in all studied tissues, as well as nitrate and nitrite contents in cerebral cortex and cerebellum, that also present increased protein carbonyl content and impairments in the activity of antioxidant enzymes of rats euthanized at twelve hours. Finally, animals euthanized after twenty-four hours present an increase of TBA-RS levels in studied tissues, as well as the protein carbonyl content in cerebellum and liver. These animals also present an increased nitrate and nitrite content and impairment of antioxidant enzymes activities. Taken together, our data suggest that acute galactose administration impairs redox homeostasis in brain and liver of rats.
Collapse
Affiliation(s)
- Márcia B Castro
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil
- Universidade Regional Integrada do Alto Uruguai e das Missões, Erechim, RS, Brazil
| | - Bruna K Ferreira
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil
| | - José Henrique Cararo
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil
| | - Adália E Chipindo
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil
| | - Marina L Magenis
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil
| | - Monique Michels
- Laboratório de Fisiopatologia Experimental, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Criciúma, SC, Brazil
| | - Lucinéia G Danielski
- Laboratório de Imunopatologia Clínica e Experimental, Programa de Pós-graduação em Ciências da Saúde, Universidade do Sul de Santa Catarina, Tubarão, SC, Brazil
| | - Marcos R de Oliveira
- Departamento de Química, Instituto de Ciências Exatas e da Terra, Universidade Federal de Mato Grosso, Cuiabá, MT, Brazil
| | - Gustavo C Ferreira
- Instituto de Bioquímica Médica Leopoldo de Meis, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Emilio L Streck
- Laboratório de Bioenergética, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Criciúma, SC, Brazil
| | - Fabricia Petronilho
- Laboratório de Imunopatologia Clínica e Experimental, Programa de Pós-graduação em Ciências da Saúde, Universidade do Sul de Santa Catarina, Tubarão, SC, Brazil
| | - Patrícia F Schuck
- Laboratório de Erros Inatos do Metabolismo, Programa de Pós-graduação em Ciências da Saúde, Unidade Acadêmica de Ciências da Saúde, Universidade do Extremo Sul Catarinense, Av. Universitária, 1105, bloco S, sala 6, Criciúma, SC, 88806-000, Brazil.
| |
Collapse
|
47
|
Irie R, Tsuruta K, Hori M, Suzuki M, Kamagata K, Nakanishi A, Kamiya K, Nakajima M, Miyajima M, Arai H, Aoki S. Neurite orientation dispersion and density imaging for evaluation of corticospinal tract in idiopathic normal pressure hydrocephalus. Jpn J Radiol 2016; 35:25-30. [PMID: 27787666 DOI: 10.1007/s11604-016-0594-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 10/20/2016] [Indexed: 12/01/2022]
Abstract
PURPOSE To evaluate diffusional changes of the corticospinal tract (CST) in patients with idiopathic normal pressure hydrocephalus (iNPH) by neurite orientation dispersion and density imaging (NODDI). MATERIALS AND METHODS Nineteen patients with iNPH and 12 healthy controls were included. Diffusion MRI data for NODDI were acquired with a 3-T system, using 32 motion-probing gradient directions with six b-values (from 0 to 2500 s/mm2). The orientation dispersion index (ODI), intra-cellular volume fraction (Vic), and isotropic volume fraction (Viso) of the CST were calculated by tract-specific analysis in patients and controls. We also measured the fractional anisotropy (FA) and apparent diffusion coefficient (ADC). RESULTS The ODI of the CST (0.087 ± 0.024 vs. 0.183 ± 0.051, P < 0.01, Mann-Whitney U test) and Vic of the CST (0.551 ± 0.061 vs. 0.628 ± 0.038, P < 0.01, Mann-Whitney U test) were significantly lower in iNPH patients than in healthy controls. In receiver-operating characteristic analysis, the area under the curve (AUC) of the ODI and FA were not significantly different (Fig. 4a, 0.987 vs. 0.904, P = 0.061), and the AUC of the Vic and ADC also showed no significant difference (Fig. 4b, 0.864 vs. 0.912, P = 0.194). CONCLUSION The NODDI can effectively evaluate the condition of neurites in the CST of iNPH patients, and the ODI could be clinically useful in the diagnosis of iNPH.
Collapse
Affiliation(s)
- Ryusuke Irie
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Kohei Tsuruta
- Department of Radiological Sciences, Tokyo Metropolitan University Graduate School of Human Health Sciences, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Michimasa Suzuki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Atsushi Nakanishi
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Kouhei Kamiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Madoka Nakajima
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Masakazu Miyajima
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Hajime Arai
- Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| |
Collapse
|
48
|
Koob M, Rousseau F, Laugel V, Meyer N, Armspach JP, Girard N, Dietemann JL. Cockayne syndrome: a diffusion tensor imaging and volumetric study. Br J Radiol 2016; 89:20151033. [PMID: 27643390 DOI: 10.1259/bjr.20151033] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVE Cockayne syndrome (CS) is a rare disorder characterized by severe brain atrophy, white matter (WM) hypomyelination and basal ganglia calcifications. This study aimed to quantify atrophy and WM abnormalities using diffusion tensor imaging (DTI) and volumetric analysis, to evaluate possible differences between CS subtypes and to determine whether DTI findings may correspond to a hypomyelinating disorder. METHODS 14 patients with CS and 14 controls underwent brain MRI including DTI and a volumetric three-dimensional T1 weighted sequence. DTI analysis was made through regions of interest within the whole brain to obtain fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values and in the left centrum semiovale to obtain DTI eigenvalues. The Student's t-test was used to compare patients and controls, and CS subtypes. Given the small number of patients with CS, they were pooled into two groups: moderate (CS1/CS3) and severe (CS2/cerebro-oculo-facio-skeletal syndrome). RESULTS Total brain volume in CS was reduced by 57%, predominantly in the infratentorial area (68%) (p < 0.001). Total brain volume reduction was greater in the severe group, but there was no difference in the degree of infratentorial atrophy in the two groups (p = 0.7). Mean FA values were lower, whereas ADC was higher in most of the WM in patients with CS (p < 0.05). ADC in the splenium of the corpus callosum and the posterior limb of the internal capsule and FA in the cerebral peduncles were significantly different between the two groups (p < 0.05). Mean ADC values corresponded to a hypomyelinating disorder. All DTI eigenvalues were higher in patients with CS, mainly for transverse diffusivity (+51%) (p < 0.001). CONCLUSION DTI and volumetric analysis provide quantitative information for the characterization of CS and may be particularly useful for evaluating therapeutic intervention. Advances in knowledge: DTI combined with volumetric analysis provides additional information useful for not only the characterization of CS and distinction of clinical subtypes but also monitoring of therapeutic interventions.
Collapse
Affiliation(s)
- Mériam Koob
- 1 Service de Radiopédiatrie/Imagerie 2, CHU de Strasbourg, Hôpital de Hautepierre, Strasbourg, France.,2 Laboratoire ICube, UMR 7357/FMTS/Université de Strasbourg-CNRS, Strasbourg, France
| | - François Rousseau
- 2 Laboratoire ICube, UMR 7357/FMTS/Université de Strasbourg-CNRS, Strasbourg, France.,3 Institut Mines-Telecom, Telecom Bretagne, INSERM, LATIM UMR, Brest, France
| | - Vincent Laugel
- 4 Service de Neurologie Pédiatrique, Hôpital de Hautepierre, Strasbourg, France
| | - Nicolas Meyer
- 5 Département de santé publique, d'Informatique médicale et de biostatistiques, CHU de Strasbourg, Hôpital civil, Strasbourg, France
| | - Jean-Paul Armspach
- 2 Laboratoire ICube, UMR 7357/FMTS/Université de Strasbourg-CNRS, Strasbourg, France
| | - Nadine Girard
- 6 Service de Neuroradiologie Diagnostique et Interventionnelle, APHM Timone, Aix Marseille Université, CRMBM, UMR CNRS, Marseille, France
| | - Jean-Louis Dietemann
- 2 Laboratoire ICube, UMR 7357/FMTS/Université de Strasbourg-CNRS, Strasbourg, France.,7 Service de Neuroradiologie/Imagerie 2, CHU de Strasbourg, Hôpital de Hautepierre, Strasbourg, France
| |
Collapse
|
49
|
Timson DJ. The molecular basis of galactosemia — Past, present and future. Gene 2016; 589:133-41. [DOI: 10.1016/j.gene.2015.06.077] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Revised: 06/18/2015] [Accepted: 06/29/2015] [Indexed: 12/19/2022]
|
50
|
Timmers I, van der Korput LD, Jansma BM, Rubio-Gozalbo ME. Grey matter density decreases as well as increases in patients with classic galactosemia: A voxel-based morphometry study. Brain Res 2016; 1648:339-344. [PMID: 27502028 DOI: 10.1016/j.brainres.2016.08.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Revised: 07/13/2016] [Accepted: 08/04/2016] [Indexed: 11/17/2022]
Abstract
Brain impairments have been observed in patients with classic galactosemia, an inherited metabolic disorder resulting in a particular neuro-cognitive profile. Neuroimaging studies showed abnormalities such as diffuse white mater (WM) abnormalities and grey matter (GM) atrophy. Our current study analysed grey matter density using voxel-based morphometry (VBM) and compared the brains of eight adolescent patients with classic galactosemia with eight healthy gender- and aged-matched controls. GM density differences were found in several regions. Decreased GM density was found in the patients in the bilateral putamen and bilateral occipital cortex. Increased GM density in the patients, on the other hand, was found in the bilateral inferior frontal and medial prefrontal cortex. The anatomical profile of the abnormalities is in line with the neuro-cognitive profile of patients with classic galactosemia, including motor dysfunction, speech and language difficulties and higher order cognitive problems. Less favourable GM densities in patients (either increased or decreased compared to controls) correlated with younger age, a worse visual working memory performance, and an older age at initiation of the galactose-restricted diet. To conclude, this explorative study is the first to analyse the GM using VBM in this population, and demonstrates a mixed profile of both increased and decreased GM density in these patients.
Collapse
Affiliation(s)
- Inge Timmers
- Department of Cognitive Neuroscience, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), PO Box 616, 6200 MD Maastricht, The Netherlands.
| | - Lisanne D van der Korput
- Department of Pediatrics, Maastricht University Medical Center, PO Box 5800, 6202 AZ Maastricht, The Netherlands
| | - Bernadette M Jansma
- Department of Cognitive Neuroscience, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands; Maastricht Brain Imaging Center (M-BIC), PO Box 616, 6200 MD Maastricht, The Netherlands
| | - M Estela Rubio-Gozalbo
- Department of Pediatrics, Maastricht University Medical Center, PO Box 5800, 6202 AZ Maastricht, The Netherlands; Laboratory Genetic Metabolic Diseases, Maastricht University Medical Center, PO Box 5800, 6202 AZ Maastricht, The Netherlands
| |
Collapse
|