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Wu TS, Wu PH, Lin HF, Chen WC, Huang TH, Lin MY, Chuang YS, Yang FPG, Chiu YW, Chang JM, Kuo MC, Lin YT. Cerebral white matter burden is linked to cognitive function in patients undergoing hemodialysis. Ann Med 2024; 56:2310142. [PMID: 38324920 PMCID: PMC10851831 DOI: 10.1080/07853890.2024.2310142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 01/21/2024] [Indexed: 02/09/2024] Open
Abstract
INTRODUCTION Chronic kidney disease is related to neurodegeneration and structural changes in the brain which might lead to cognitive decline. The Fazekas scale used for assessing white matter hyperintensities (WMHs) was associated with poor cognitive performance. Therefore, this study investigated the associations between the mini-mental status examination (MMSE), Montreal cognitive assessment (MoCA), cognitive abilities screening instrument (CASI), and Fazekas scale in patients under hemodialysis (HD). METHODS The periventricular (PV) WMHs and deep WMHs (DWMHs) in brain magnetic resonance images of 59 patients under dialysis were graded using the Fazekas scale. Three cognition function tests were also performed, then multivariable ordinal regression and logistic regression were used to identify the associations between cognitive performance and the Fazekas scale. RESULTS There were inverse associations between the three cognitive function tests across the Fazekas scale of PVWMHs (p = .037, .006, and .008 for MMSE, MoCA, and CASI, respectively), but the associations were attenuated in the DWMHs group. In CASI, significant differences were identified in short-term memory, mental manipulation, abstract thinking, language, spatial construction, and name fluency in the PVWMHs group. However, DWMHs were only significantly correlated with abstract thinking and short-term memory. CONCLUSION An inverse correlation existed between the Fazekas scale, predominantly in PVWMHs, and cognition in patients undergoing HD. The PVWMHs were associated with cognitive performance assessed by MMSE, MoCA, and CASI, as well as with subdomains of CASI such as memory, language and name fluency in patients undergoing HD.
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Affiliation(s)
- Tsai-Shan Wu
- Department of General Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ping-Hsun Wu
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- Center for Big Data Research, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - Hsiu-Fen Lin
- Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Wen-Ching Chen
- Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Teng-Hui Huang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Ming-Yen Lin
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Yun-Shiuan Chuang
- Center for Big Data Research, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Fan-Pei Gloria Yang
- Department of Foreign Languages and Literature, National Tsing Hua University, Hsinchu, Taiwan
- Center for Cognition and Mind Sciences, National Tsing Hua University, Hsinchu, Taiwan
- Department of Radiology, Graduate School of Dentistry, Osaka University, Suita, Japan
| | - Yi-Wen Chiu
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jer-Ming Chang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Mei-Chuan Kuo
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Yi-Ting Lin
- Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- Center for Big Data Research, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
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Oh DJ, Han JW, Kim JS, Kim TH, Kwak KP, Kim BJ, Kim SG, Kim JL, Moon SW, Park JH, Ryu SH, Youn JC, Lee DY, Lee DW, Lee SB, Lee JJ, Jhoo JH, Kim KW. Masticatory Function, Sex, and Risk of Dementia Among Older Adults: A Population-Based Cohort Study. J Korean Med Sci 2024; 39:e246. [PMID: 39315441 PMCID: PMC11419966 DOI: 10.3346/jkms.2024.39.e246] [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: 06/06/2024] [Accepted: 07/14/2024] [Indexed: 09/25/2024] Open
Abstract
BACKGROUND A decline in masticatory function may indicate brain dysfunction related to dementia, but the relationship between masticatory function and dementia risk remains unclear. This study aimed to investigate whether masticatory function is associated with the risk of cognitive decline and dementia. METHODS Data were obtained from the nationwide prospective cohort study of randomly sampled community-dwelling Koreans aged ≥ 60 years. The 5,064 non-demented participants, whose number of chewing cycles per bite was assessed by clinical interview, were followed for 8 years with biennial assessments of cognitive performance and clinical diagnoses of all-cause dementia and Alzheimer's disease (AD). Structural brain magnetic resonance imaging was collected from a subset of cohort participants and their spouses for imaging analyses. RESULTS Males who chewed ≥ 30 cycles/bite had faster decline in global cognition and memory function and were at higher risk for incident all-cause dementia (hazard ratio [HR], 2.91; 95% confidence interval [CI], 1.18-7.18) and AD (HR, 3.22; 95% CI, 1.14-9.11) compared to males with less than 10 cycles/bite. Additionally, increased chewing cycles in males were associated with reduced brain volume, particularly in regions involved in compensatory cognitive control of mastication. There was no significant association between chewing cycles and the risk of dementia or brain volume in females. CONCLUSION Older men who frequently chew their meals could be considered a notable population at risk for dementia who should be carefully assessed for their cognitive trajectories.
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Affiliation(s)
- Dae Jong Oh
- Workplace Mental Health Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Jun Sung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Tae Hui Kim
- Department of Psychiatry, Yonsei University Wonju Severance Christian Hospital, Wonju, Korea
| | - Kyung Phil Kwak
- Department of Psychiatry, Dongguk University Gyeongju Hospital, Gyeongju, Korea
| | - Bong Jo Kim
- Department of Psychiatry, Gyeongsang National University School of Medicine, Jinju, Korea
| | - Shin Gyeom Kim
- Department of Neuropsychiatry, Soonchunhyang University Bucheon Hospital, Bucheon, Korea
| | - Jeong Lan Kim
- Department of Psychiatry, College of Medicine, Chungnam National University, Daejeon, Korea
| | - Seok Woo Moon
- Department of Psychiatry, Konkuk University Chungju Hospital, School of Medicine, Konkuk University, Chungju, Korea
| | - Joon Hyuk Park
- Department of Neuropsychiatry, Jeju National University Hospital, Jeju, Korea
| | - Seung-Ho Ryu
- Department of Psychiatry, Konkuk University Medical Center, School of Medicine, Konkuk University, Seoul, Korea
| | - Jong Chul Youn
- Department of Neuropsychiatry, Kyunggi Provincial Hospital for the Elderly, Yongin, Korea
| | - Dong Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Korea
| | - Dong Woo Lee
- Department of Psychiatry, Inje University Sanggye Paik Hospital, Seoul, Korea
| | - Seok Bum Lee
- Department of Psychiatry, Dankook University Hospital, Cheonan, Korea
| | - Jung Jae Lee
- Department of Psychiatry, Dankook University Hospital, Cheonan, Korea
| | - Jin Hyeong Jhoo
- Department of Psychiatry, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, Korea
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Korea.
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3
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Lin SJ, Gillespie NA, Notestine R, Gamst AC, Chen AM, McEvoy LK, Panizzon MS, Elman JA, Glatt SJ, Hagler DJ, Neale MC, Franz CE, Kremen WS, Fennema-Notestine C. The genetic and environmental etiology of novel frequency-driven regional parcellations of abnormal white matter. Am J Med Genet B Neuropsychiatr Genet 2024:e33004. [PMID: 39148448 DOI: 10.1002/ajmg.b.33004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 06/28/2024] [Accepted: 08/05/2024] [Indexed: 08/17/2024]
Abstract
The prevalence of white matter disease increases with age and is associated with cerebrovascular disease, cognitive decline, and risk for dementia. MRI measures of abnormal signal in the white matter (AWM) provide estimates of damage, however, regional patterns of AWM may be differentially influenced by genetic or environmental factors. With our data-driven regional parcellation approach, we created a probability distribution atlas using Vietnam Era Twin Study of Aging (VETSA) data (n = 475, mean age 67.6 years) and applied a watershed algorithm to define separate regional parcellations. We report biometrical twin modeling for five anatomically distinct regions: (1) Posterior, (2) Superior frontal and parietal, (3) Anterior and inferior frontal with deep areas, (4) Occipital, and (5) Anterior periventricular. We tested competing multivariate hypotheses to identify unique influences and to explain sources of covariance among the parcellations. Family aggregation could be entirely explained by additive genetic influences, with additive genetic variance (heritability) ranging from 0.69 to 0.79. Most genetic correlations between parcellations ranged from moderate to high (rg = 0.57-0.85), although two were small (rg = 0.35-0.39), consistent with varying degrees of unique genetic influences. This proof-of-principle investigation demonstrated the value of our novel, data-driven parcellations, with identifiable genetic and environmental differences, for future exploration.
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Affiliation(s)
- Shu-Ju Lin
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Richmond, Virginia, USA
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Randy Notestine
- Computational and Applied Statistics Laboratory (CASL) at the San Diego Supercomputer Center (SDSC), La Jolla, California, USA
| | - Anthony C Gamst
- Computational and Applied Statistics Laboratory (CASL) at the San Diego Supercomputer Center (SDSC), La Jolla, California, USA
- Department of Mathematics, University of California, San Diego, La Jolla, California, USA
| | - Anna M Chen
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Linda K McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, California, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, California, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
| | - Stephen J Glatt
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab), Departments of Psychiatry and Behavioral Sciences, Neuroscience and Physiology, and Public Health and Preventive Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, California, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Richmond, Virginia, USA
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, California, USA
- Department of Radiology, University of California, San Diego, La Jolla, California, USA
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Pai YT, Matsuda H, Pai MC. Using eZIS to Predict Progression from MCI to Dementia in Three Years. Diagnostics (Basel) 2024; 14:1780. [PMID: 39202268 PMCID: PMC11353283 DOI: 10.3390/diagnostics14161780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 07/21/2024] [Accepted: 08/09/2024] [Indexed: 09/03/2024] Open
Abstract
(1) Background: Mild cognitive impairment (MCI) due to Alzheimer's disease (AD) progresses to dementia at a higher annual rate, while other MCIs may remain stable or even improve over time. Discriminating progressive from non-progressive cases of MCI is crucial and challenging. (2) Methods: A retrospective study of individuals with MCI was conducted at a university hospital located in southern Taiwan. The researchers collected demographic data, comorbidities, the scores of cognitive tests, three easy Z-score imaging system (eZIS) indicators (severity, extent, and ratio), Fazekas scale scores, mesial temporal atrophy (MTA) scores, clinical outcomes including deterioration of Cognitive Abilities Screening Instrument, Mini-mental State Examination, Clinical Dementia Rating Sum of Box scores, and the conversion from MCI to dementia. Those who converted to dementia in three years and non-converters were compared by the three eZIS indicators to test the predictive utility, and the clinical outcomes were evaluated by regression and ROC curve analysis. (3) Results: The three eZIS indicators were significantly higher in the group of progressive MCI than in stable MCI. eZIS severity is positively correlated with a deterioration in the scores of the Cognitive Abilities Screening Instrument and Clinical Dementia Rating Sum of Box. eZIS severity is also positively correlated with conversion from MCI to dementia. The AUC for severity is 0.719, and the optimal cutoff value of severity for predicting conversion is 1.22. (4) Conclusions: During three years of follow-up, MCI individuals with greater eZIS severity were significantly associated with worse cognitive assessment scores and a higher conversion rate to dementia.
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Affiliation(s)
- Ya-Tang Pai
- National Cheng Kung University Hospital, Tainan 704, Taiwan;
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 333, Taiwan
| | - Hiroshi Matsuda
- Department of Biofunctional Imaging, Fukushima Medical University, Fukushima 960-1295, Japan;
| | - Ming-Chyi Pai
- Division of Behavioral Neurology, Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
- Alzheimer’s Disease Research Center, National Cheng Kung University Hospital, Tainan 704, Taiwan
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5
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Winter SF, Gardner MM, Karschnia P, Vaios EJ, Grassberger C, Bussière MR, Nikolic K, Pongpitakmetha T, Ehret F, Kaul D, Boehmerle W, Endres M, Shih HA, Parsons MW, Dietrich J. Unique brain injury patterns after proton vs photon radiotherapy for WHO grade 2-3 gliomas. Oncologist 2024:oyae195. [PMID: 39126664 DOI: 10.1093/oncolo/oyae195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/26/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Central nervous system (CNS) injury following brain-directed radiotherapy remains a major challenge. Proton radiotherapy (PRT) minimizes radiation to healthy brain, potentially limiting sequelae. We characterized CNS radiotoxicity, including radiation-induced leukoencephalopathy (RIL), brain tissue necrosis (TN), and cerebral microbleeds (CMB), in glioma patients treated with PRT or photons (XRT). PATIENTS AND METHODS Thirty-four patients (19 male; median age 39.6 years) with WHO grade 2-3 gliomas treated with partial cranial radiotherapy (XRT [n = 17] vs PRT[n = 17]) were identified and matched by demographic/clinical criteria. Radiotoxicity was assessed longitudinally for 3 years post-radiotherapy via serial analysis of T2/FLAIR- (for RIL), contrast-enhanced T1- (for TN), and susceptibility (for CMB)-weighted MRI sequences. RIL was rated at whole-brain and hemispheric levels using a novel Fazekas scale-informed scoring system. RESULTS The scoring system proved reliable (ICC > 0.85). Both groups developed moderate-to-severe RIL (62%[XRT]; 71%[PRT]) within 3 years; however, XRT was associated with persistent RIL increases in the contralesional hemisphere, whereas contralesional hemispheric RIL plateaued with PRT at 1-year post-radiotherapy (t = 2.180; P = .037). TN rates were greater with PRT (6%[XRT] vs 18%[PRT]; P = ns). CMB prevalence (76%[XRT]; 71%[PRT]) and burden (mean #CMB: 4.0[XRT]; 4.2[PRT]) were similar; however, XRT correlated with greater contralesional hemispheric CMB burden (27%[XRT]; 17%[PRT]; X2 = 4.986; P = .026), whereas PRT-specific CMB clustered at the radiation field margin (X2 = 14.7; P = .002). CONCLUSIONS CNS radiotoxicity is common and progressive in glioma patients. Injury patterns suggest radiation modality-specificity as RIL, TN, and CMB exhibit unique spatiotemporal differences following XRT vs PRT, likely reflecting underlying dosimetric and radiobiological differences. Familiarity with such injury patterns is essential to improve patient management. Prospective studies are needed to validate these findings and assess their impacts on neurocognitive function.
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Affiliation(s)
- Sebastian F Winter
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Clinician Scientist Program, 10117 Berlin, Germany
| | - Melissa M Gardner
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Department of Psychiatry, Psychology Assessment Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
| | - Philipp Karschnia
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Department of Neurosurgery, Ludwig-Maximilians-University Munich, 81377 Munich, Germany
| | - Eugene J Vaios
- Department of Radiation Oncology, Duke Cancer Institute, Durham, NC 27710, United States
| | - Clemens Grassberger
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
| | - Marc R Bussière
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
| | - Katarina Nikolic
- Department of Neurology, Universitätsklinikum St. Pölten, 3100 Sankt Pölten, Austria
| | - Thanakit Pongpitakmetha
- Department of Pharmacology, Faculty of Medicine, Chulalongkorn University, 10330 Bangkok, Thailand
- Chula Neuroscience Center, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, 10330 Bangkok, Thailand
| | - Felix Ehret
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, 13353 Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, a partnership between DKFZ and Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - David Kaul
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology, 13353 Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, a partnership between DKFZ and Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Wolfgang Boehmerle
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Matthias Endres
- Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Center for Stroke Research Berlin, 10117 Berlin, Germany
- ExcellenceCluster NeuroCure, 10117 Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Partner Site Berlin, 10117 Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, 10117 Berlin, Germany
- German Centre for Mental Health (DZPH), Partner Site Berlin, 10117 Berlin, Germany
| | - Helen A Shih
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
| | - Michael W Parsons
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
- Department of Psychiatry, Psychology Assessment Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
| | - Jorg Dietrich
- Division of Neuro-Oncology, Mass General Cancer Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
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Liu S, Luo X, Chong JSX, Jiaerken Y, Youn SH, Zhang M, Zhou JH. Brain structure, amyloid, and behavioral features for predicting clinical progression in subjective cognitive decline. Hum Brain Mapp 2024; 45:e26765. [PMID: 38958401 PMCID: PMC11220833 DOI: 10.1002/hbm.26765] [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: 10/09/2023] [Revised: 05/28/2024] [Accepted: 06/10/2024] [Indexed: 07/04/2024] Open
Abstract
As a potential preclinical stage of Alzheimer's dementia, subjective cognitive decline (SCD) reveals a higher risk of future cognitive decline and conversion to dementia. However, it has not been clear whether SCD status increases the clinical progression of older adults in the context of amyloid deposition, cerebrovascular disease (CeVD), and psychiatric symptoms. We identified 99 normal controls (NC), 15 SCD individuals who developed mild cognitive impairment in the next 2 years (P-SCD), and 54 SCD individuals who did not (S-SCD) from ADNI database with both baseline and 2-year follow-up data. Total white matter hyperintensity (WMH), WMH in deep (DWMH) and periventricular (PWMH) regions, and voxel-wise grey matter volumes were compared among groups. Furthermore, using structural equation modelling method, we constructed path models to explore SCD-related brain changes longitudinally and to determine whether baseline SCD status, age, and depressive symptoms affect participants' clinical outcomes. Both SCD groups showed higher baseline amyloid PET SUVR, baseline PWMH volumes, and larger increase of PWMH volumes over time than NC. In contrast, only P-SCD had higher baseline DWMH volumes and larger increase of DWMH volumes over time than NC. No longitudinal differences in grey matter volume and amyloid was observed among NC, S-SCD, and P-SCD. Our path models demonstrated that SCD status contributed to future WMH progression. Further, baseline SCD status increases the risk of future cognitive decline, mediated by PWMH; baseline depressive symptoms directly contribute to clinical outcomes. In conclusion, both S-SCD and P-SCD exhibited more severe CeVD than NC. The CeVD burden increase was more pronounced in P-SCD. In contrast with the direct association of depressive symptoms with dementia severity progression, the effects of SCD status on future cognitive decline may manifest via CeVD pathologies. Our work highlights the importance of multi-modal longitudinal designs in understanding the SCD trajectory heterogeneity, paving the way for stratification and early intervention in the preclinical stage. PRACTITIONER POINTS: Both S-SCD and P-SCD exhibited more severe CeVD at baseline and a larger increase of CeVD burden compared to NC, while the burden was more pronounced in P-SCD. Baseline SCD status increases the risk of future PWMH and DWMH volume accumulation, mediated by baseline PWMH and DWMH volumes, respectively. Baseline SCD status increases the risk of future cognitive decline, mediated by baseline PWMH, while baseline depression status directly contributes to clinical outcome.
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Grants
- U01 AG024904 NIA NIH HHS
- W81XWH-12-2-0012 DoD Alzheimer's Disease Neuroimaging Initiative (Department of Defense)
- A20G8b0102 Research, Innovation and Enterprise (RIE) 2020 Advanced Manufacturing and Engineering (AME) Programmatic Fund (Agency for Science, Technology and Research (A*STAR), Singapore)
- NMRC/OFLCG19May-0035 National Medical Research Council, Singapore
- NMRC/CIRG/1485/2018 National Medical Research Council, Singapore
- NMRC/CSA-SI/0007/2016 National Medical Research Council, Singapore
- NMRC/MOH-00707-01 National Medical Research Council, Singapore
- NMRC/CG/435M009/2017-NUH/NUHS National Medical Research Council, Singapore
- CIRG21nov-0007 National Medical Research Council, Singapore
- HLCA23Feb-0004 National Medical Research Council, Singapore
- Yong Loo Lin School of Medicine Research Core Funding (National University of Singapore, Singapore)
- 82271936 National Natural Science Foundation of China
- 2022ZQ057 Zhejiang Provincial Administration of Traditional Chinese Medicine - Youth Talent Fund Project
- MOE-T2EP40120-0007 Ministry of Education, Singapore
- T2EP2-0223-0025 Ministry of Education, Singapore
- MOE-T2EP20220-0001 Ministry of Education, Singapore
- Alzheimer's Disease Neuroimaging Initiative (National Institutes of Health)
- DoD Alzheimer's Disease Neuroimaging Initiative (Department of Defense)
- National Medical Research Council, Singapore
- National Natural Science Foundation of China
- Ministry of Education, Singapore
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Affiliation(s)
- Siwei Liu
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Xiao Luo
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Joanna Su Xian Chong
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Yeerfan Jiaerken
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Shim Hee Youn
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
| | - Minming Zhang
- Department of Radiology, Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Juan Helen Zhou
- Centre for Sleep and CognitionCentre for Translational Magnetic Resonance Research, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Human Potential Translational Research ProgramDepartment of MedicineNational University of SingaporeSingaporeSingapore
- Department of Electrical and Computer EngineeringIntegrative Sciences and Engineering Programme (ISEP), NUS Graduate SchoolNational University of SingaporeSingaporeSingapore
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7
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Li C, Wang J, Han X, Li Y, Liu K, Zhao M, Gong T, Hou T, Wang Y, Cong L, Song L, Du Y. Development and validation of a diagnostic model for cerebral small vessel disease among rural older adults in China. Front Neurol 2024; 15:1388653. [PMID: 39036632 PMCID: PMC11258008 DOI: 10.3389/fneur.2024.1388653] [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: 02/21/2024] [Accepted: 06/26/2024] [Indexed: 07/23/2024] Open
Abstract
Objectives Cerebral small vessel disease (CSVD) visible on MRI can be asymptomatic. We sought to develop and validate a model for detecting CSVD in rural older adults. Methods This study included 1,192 participants in the MRI sub-study within the Multidomain Interventions to Delay Dementia and Disability in Rural China. Total sample was randomly divided into training set and validation set. MRI markers of CSVD were assessed following the international criteria, and total CSVD burden was assessed on a scale from 0 to 4. Logistic regression analyses were used to screen risk factors and develop the diagnostic model. A nomogram was used to visualize the model. Model performance was assessed using the area under the receiver-operating characteristic curve (AUC), calibration plot, and decision curve analysis. Results The model included age, high blood pressure, white blood cell count, neutrophil-to-lymphocyte ratio (NLR), and history of cerebral infarction. The AUC was 0.71 (95% CI, 0.67-0.76) in the training set and 0.69 (95% CI, 0.63-0.76) in the validation set. The model showed high coherence between predicted and observed probabilities in both the training and validation sets. The model had higher net benefits than the strategy assuming all participants either at high risk or low risk of CSVD for probability thresholds ranging 50-90% in the training set, and 65-98% in the validation set. Conclusion A model that integrates routine clinical factors could detect CSVD in older adults, with good discrimination and calibration. The model has implication for clinical decision-making.
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Affiliation(s)
- Chunyan Li
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Jiafeng Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Xiaodong Han
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yuanjing Li
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Keke Liu
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Mingqing Zhao
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Tao Gong
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Tingting Hou
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Yongxiang Wang
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Lin Cong
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Lin Song
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Yifeng Du
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
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8
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Hannan J, Busby N, Roth R, Wilmskoetter J, Newman-Norlund R, Rorden C, Bonilha L, Fridriksson J. Under pressure: the interplay of hypertension and white matter hyperintensities with cognition in chronic stroke aphasia. Brain Commun 2024; 6:fcae200. [PMID: 38894950 PMCID: PMC11184349 DOI: 10.1093/braincomms/fcae200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 05/08/2024] [Accepted: 06/07/2024] [Indexed: 06/21/2024] Open
Abstract
While converging research suggests that increased white matter hyperintensity load is associated with poorer cognition, and the presence of hypertension is associated with increased white matter hyperintensity load, the relationship among hypertension, cognition and white matter hyperintensities is not well understood. We sought to determine the effect of white matter hyperintensity burden on the relationship between hypertension and cognition in individuals with post-stroke aphasia, with the hypothesis that white matter hyperintensity load moderates the relationship between history of hypertension and cognitive function. Health history, Fazekas scores for white matter hyperintensities and Wechsler Adult Intelligence Scale Matrix Reasoning subtest scores for 79 people with aphasia collected as part of the Predicting Outcomes of Language Rehabilitation study at the Center for the Study of Aphasia Recovery at the University of South Carolina and the Medical University of South Carolina were analysed retrospectively. We found that participants with a history of hypertension had increased deep white matter hyperintensity severity (P < 0.001), but not periventricular white matter hyperintensity severity (P = 0.116). Moderation analysis revealed that deep white matter hyperintensity load moderates the relationship between high blood pressure and Wechsler Adult Intelligence Scale scores when controlling for age, education, aphasia severity and lesion volume. The interaction is significant, showing that a history of high blood pressure and severe deep white matter hyperintensities together are associated with poorer Matrix Reasoning scores. The overall model explains 41.85% of the overall variation in Matrix Reasoning score in this group of participants. These findings underscore the importance of considering cardiovascular risk factors in aphasia treatment, specifically hypertension and its relationship to brain health in post-stroke cognitive function.
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Affiliation(s)
- Jade Hannan
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | | | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Leonardo Bonilha
- Department of Pharmacology, Physiology, and Neuroscience, University of South Carolina School of Medicine, Columbia, SC 29209, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
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9
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Chen J, Li J, Wang X, Fu X, Ke J, Li J, Wen J, Cheng K, Li S, Shi Z. Heme Oxygenase-1 Gene (GT)n Polymorphism Linked to Deep White Matter Hyperintensities, Not Periventricular Hyperintensities. J Am Heart Assoc 2024; 13:e033981. [PMID: 38818928 PMCID: PMC11255616 DOI: 10.1161/jaha.123.033981] [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: 12/13/2023] [Accepted: 05/01/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND Oxidative stress plays a principal role in the pathogenesis of white matter hyperintensities (WMHs). The induction of heme oxygenase-1 (HO-1) gene in the brain represents 1 of the pivotal mechanisms to counteract the noxious effects of reactive oxygen species, and the transcriptional modulation of HO-1 induction depends on the length of a GT-repeat (GT)n in the promoter region. We investigated whether the HO-1 gene (GT)n polymorphism is associated with the risk of WMHs. METHODS AND RESULTS A total of 849 subjects from the memory clinic were consecutively enrolled, and the HO-1 (GT)n genotype was determined. WMHs were assessed with the Fazekas scale and further divided into periventricular WMHs and deep WMHs (DWMHs). Allelic HO-1 (GT)n polymorphisms were classified as short (≤24 (GT)n), median (25≤[GT]n<31), or long (31≤[GT]n). Multivariate logistic regression analysis was used to evaluate the effect of the HO-1 (GT)n variants on WMHs. The number of repetitions of the HO-1 gene (GT)n ranged from 15 to 39 with a bimodal distribution at lengths 23 and 30. The proportion of S/S genotypes was higher for moderate/severe DWMHs than none/mild DWMHs (22.22% versus 12.44%; P=0.001), but the association for periventricular WMHs was not statistically significant. Logistic regression suggested that the S/S genotype was significantly associated with moderate/severe DWMHs (S/S versus non-S/S: odds ratio, 2.001 [95% CI, 1.323-3.027]; P<0.001). The HO-1 gene (GT)n S/S genotype and aging synergistically contributed to the progression of DWMHs (relative excess risk attributable to interaction, 6.032 [95% CI, 0.149-11.915]). CONCLUSIONS Short (GT)n variants in the HO-1 gene may confer susceptibility to rather than protection from DWMHs, but not periventricular WMHs. REGISTRATION URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100045869.
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Affiliation(s)
- Junting Chen
- Department of Neurology and Memory CenterThe 10th Affiliate Hospital, Southern Medical UniversityDongguanChina
- Postgraduate SchoolGuangdong Medical UniversityZhanjiangGuangdongChina
| | - Jinrui Li
- Department of Neurology and Memory CenterThe 10th Affiliate Hospital, Southern Medical UniversityDongguanChina
- The 1st Clinical Medical SchoolSouthern Medical UniversityDongguanChina
| | - Xiaomian Wang
- Postgraduate SchoolGuangdong Medical UniversityZhanjiangGuangdongChina
| | - Xiaoli Fu
- Department of Neurology and Memory CenterThe 10th Affiliate Hospital, Southern Medical UniversityDongguanChina
| | - Jianxia Ke
- The 1st Clinical Medical SchoolSouthern Medical UniversityDongguanChina
| | - Jintao Li
- The 1st Clinical Medical SchoolSouthern Medical UniversityDongguanChina
| | - Jia Wen
- Postgraduate SchoolGuangdong Medical UniversityZhanjiangGuangdongChina
| | - Kailin Cheng
- Postgraduate SchoolGuangdong Medical UniversityZhanjiangGuangdongChina
| | - Shuen Li
- Department of Neurology and Memory CenterThe 10th Affiliate Hospital, Southern Medical UniversityDongguanChina
| | - Zhu Shi
- Department of Neurology and Memory CenterThe 10th Affiliate Hospital, Southern Medical UniversityDongguanChina
- Postgraduate SchoolGuangdong Medical UniversityZhanjiangGuangdongChina
- The 1st Clinical Medical SchoolSouthern Medical UniversityDongguanChina
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10
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Carvalho de Abreu DC, Pieruccini-Faria F, Son S, Montero-Odasso M, Camicioli R. Is white matter hyperintensity burden associated with cognitive and motor impairment in patients with parkinson's disease? A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 161:105677. [PMID: 38636832 DOI: 10.1016/j.neubiorev.2024.105677] [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: 11/29/2022] [Revised: 02/08/2024] [Accepted: 04/12/2024] [Indexed: 04/20/2024]
Abstract
White matter damage quantified as white matter hyperintensities (WMH) may aggravate cognitive and motor impairments, but whether and how WMH burden impacts these problems in Parkinson's disease (PD) is not fully understood. This study aimed to examine the association between WMH and cognitive and motor performance in PD through a systematic review and meta-analysis. We compared the WMH burden across the cognitive spectrum (cognitively normal, mild cognitive impairment, dementia) in PD including controls. Motor signs were compared in PD with low/negative and high/positive WMH burden. We compared baseline WMH burden of PD who did and did not convert to MCI or dementia. MEDLINE and EMBASE databases were used to conduct the literature search resulting in 50 studies included for data extraction. Increased WMH burden was found in individuals with PD compared with individuals without PD (i.e. control) and across the cognitive spectrum in PD (i.e. PD, PD-MCI, PDD). Individuals with PD with high/positive WMH burden had worse global cognition, executive function, and attention. Similarly, PD with high/positive WMH presented worse motor signs compared with individuals presenting low/negative WMH burden. Only three longitudinal studies were retrieved from our search and they showed that PD who converted to MCI or dementia, did not have significantly higher WMH burden at baseline, although no data was provided on WMH burden changes during the follow up. We conclude, based on cross-sectional studies, that WMH burden appears to increase with PD worse cognitive and motor status in PD.
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Affiliation(s)
- Daniela Cristina Carvalho de Abreu
- Post-doctoral fellow at Gait and Brain Lab, University of Western Ontario, Canada, and Associated Professor of Physiotherapy Course, Department of Health Sciences, Rehabilitation and Functional Performance Program, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
| | - Frederico Pieruccini-Faria
- Deparment of Medicine, Schulich School of Medicine and Dentistry, The University of Western Ontario, Lawson Health Research Institute, St. Josephs Health Care, Parkwood Institute, Deputy Director of the Gait & Brain Lab, Canada
| | - Surim Son
- Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, University of Western Ontario, Statistician, Departments of Medicine, University of Western Ontario, Canada, Parkwood Institute, Lawson Health Research Institute, Canada
| | - Manuel Montero-Odasso
- Departments of Medicine, and Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, The University of Western Ontario, Canada Director of Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, Canada
| | - Richard Camicioli
- Department of Medicine, Division of Neurology, University of Alberta, Canada
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11
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Zhang J, Chen H, Wang J, Huang Q, Xu X, Wang W, Xu W, Guan Y, Liu J, Wardlaw JM, Deng Y, Xie F, Li B. Linking white matter hyperintensities to regional cortical thinning, amyloid deposition, and synaptic density loss in Alzheimer's disease. Alzheimers Dement 2024; 20:3931-3942. [PMID: 38648354 PMCID: PMC11180938 DOI: 10.1002/alz.13845] [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: 12/30/2023] [Revised: 02/16/2024] [Accepted: 03/21/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION We investigated the association between white matter hyperintensities (WMH) and regional cortical thickness, amyloid and tau deposition, and synaptic density in the WMH-connected cortex using multimodal images. METHODS We included 107 participants (59 with Alzheimer's disease [AD]; 27 with mild cognitive impairment; 21 cognitively normal controls) with amyloid beta (Aβ) positivity on amyloid positron emission tomography (PET). The cortex connected to WMH was identified using probabilistic tractography. RESULTS We found that WMH connected to the cortex with more severe regional degeneration as measured by cortical thickness, Aβ and tau deposition, and synaptic vesicle glycoprotein 2 A (SV2A) density using 18F-SynVesT-1 PET. In addition, higher ratios of Aβ in the deep WMH-connected versus WMH-unconnected cortex were significantly related to lower cognitive scores. Last, the cortical thickness of WMH-connected cortex reduced more than WMH-unconnected cortex over 12 months. DISCUSSION Our results suggest that WMH may be associated with AD-intrinsic processes of degeneration, in addition to vascular mechanisms. HIGHLIGHTS We studied white matter hyperintensities (WMHs) and WMH-connected cortical changes. WMHs are associated with more severe regional cortical degeneration. Findings suggest WMHs may be associated with Alzheimer's disease-intrinsic processes of degeneration.
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Affiliation(s)
- Junfang Zhang
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Haijuan Chen
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jie Wang
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Qi Huang
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaomeng Xu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wenjing Wang
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wei Xu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yihui Guan
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Jun Liu
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Joanna M Wardlaw
- Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghUK
- UK Dementia Research InstituteUniversity of EdinburghEdinburghUK
| | - Yulei Deng
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Fang Xie
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Binyin Li
- Department of Neurology & Institute of NeurologyRuijin Hospital affiliated with Shanghai Jiao Tong University School of MedicineShanghaiChina
- Clinical Neuroscience CenterRuijin Hospital LuWan BranchShanghai Jiao Tong University School of MedicineShanghaiChina
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12
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Du J, Qu C, Xu Z, Liu Z, Lv M, Wang D, Wei W, Duan Y, Shen J. White matter hyperintensities mediate the association between frailty and cognitive impairment in moyamoya disease. Clin Neurol Neurosurg 2024; 240:108283. [PMID: 38608350 DOI: 10.1016/j.clineuro.2024.108283] [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: 12/09/2023] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 04/14/2024]
Abstract
OBJECTIVES The relationship between cognitive function and frailty in moyamoya disease (MMD) remains unclear, and the underlying mechanism is poorly understood. This study aims to investigate whether white matter hyperintensities (WMHs) mediate the association between frailty and cognitive impairment in MMD. METHODS Patients with MMD were consecutively enrolled in our study from January 2021 to May 2023. Pre-admission frailty and cognition were assessed using the Clinical Frailty Scale (CFS) and cognitive tests, respectively. Regional deep WMH (DWMH) and periventricular WMH (PWMH) volumes were calculated using the Brain Anatomical Analysis using Diffeomorphic deformation toolbox based on SPM 12 software. Multivariate logistic regression analysis was conducted to evaluate the association between frailty and cognitive function in MMD. Mediation analysis was performed to assess whether WMHs explained the association between frailty and cognition. RESULTS A total of 85 patients with MMD were enrolled in this study. On the basis of the CFS scores, 24 patients were classified as frail, 38 as pre-frail, and 23 as robust. Significant differences were observed in learning, memory, processing speed, executive functions, and semantic memory among the three groups (p < 0.001). Frailty was independently associated with memory and executive functions (p < 0.05); even after controlling for WMH. Mediation analysis indicated that the associations of frailty with memory and executive functions were partially mediated by WMH, DWMH, and PWMH (p < 0.05). CONCLUSION Frailty is significantly correlated with a higher risk of cognitive impairment in MMD, even after adjusting for other covariates. WMHs partially mediate the association between frailty and cognitive impairment.
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Affiliation(s)
- Juan Du
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Changhua Qu
- Department of Neurology, Minda Hospital of Hubei Minzu University, Hubei, China
| | - Ziwei Xu
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Zhengxin Liu
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Mingxuan Lv
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Dan Wang
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Wenshi Wei
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China
| | - Yu Duan
- Department of Neurosurgery, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
| | - Jun Shen
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, China; Department of Neurology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
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13
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Huang WQ, Lin Q, Tzeng CM. Leukoaraiosis: Epidemiology, Imaging, Risk Factors, and Management of Age-Related Cerebral White Matter Hyperintensities. J Stroke 2024; 26:131-163. [PMID: 38836265 PMCID: PMC11164597 DOI: 10.5853/jos.2023.02719] [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: 08/18/2023] [Accepted: 01/15/2024] [Indexed: 06/06/2024] Open
Abstract
Leukoaraiosis (LA) manifests as cerebral white matter hyperintensities on T2-weighted magnetic resonance imaging scans and corresponds to white matter lesions or abnormalities in brain tissue. Clinically, it is generally detected in the early 40s and is highly prevalent globally in individuals aged >60 years. From the imaging perspective, LA can present as several heterogeneous forms, including punctate and patchy lesions in deep or subcortical white matter; lesions with periventricular caps, a pencil-thin lining, and smooth halo; as well as irregular lesions, which are not always benign. Given its potential of having deleterious effects on normal brain function and the resulting increase in public health burden, considerable effort has been focused on investigating the associations between various risk factors and LA risk, and developing its associated clinical interventions. However, study results have been inconsistent, most likely due to potential differences in study designs, neuroimaging methods, and sample sizes as well as the inherent neuroimaging heterogeneity and multi-factorial nature of LA. In this article, we provided an overview of LA and summarized the current knowledge regarding its epidemiology, neuroimaging classification, pathological characteristics, risk factors, and potential intervention strategies.
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Affiliation(s)
- Wen-Qing Huang
- Department of Central Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qing Lin
- Department of Neurology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Xiamen Clinical Research Center for Neurological Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Fujian Provincial Clinical Research Center for Brain Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- The Third Clinical College, Fujian Medical University, Fuzhou, Fujian, China
| | - Chi-Meng Tzeng
- Translational Medicine Research Center, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China
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14
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Wan H, Liu Q, Chen C, Dong W, Wang S, Shi W, Li C, Ren J, Wang Z, Cui T, Shao X. An Integrative Nomogram for Identifying Cognitive Impairment Using Seizure Type and Cerebral Small Vessel Disease Neuroimaging Markers in Patients with Late-Onset Epilepsy of Unknown Origin. Neurol Ther 2024; 13:107-125. [PMID: 38019380 PMCID: PMC10787714 DOI: 10.1007/s40120-023-00566-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/08/2023] [Indexed: 11/30/2023] Open
Abstract
INTRODUCTION Cognitive impairment (CI) is a common comorbidity in patients with late-onset epilepsy of unknown origin (LOEU). However, limited data are available on effective screening methods for CI at an early stage. We aimed to develop and internally validate a nomogram for identifying patients with LOEU at risk of CI and investigate the potential moderating effect of education on the relationship between periventricular white matter hyperintensities (PVHs) and cognitive function. METHODS We retrospectively reviewed the clinical data of 61 patients aged ≥ 55 years diagnosed with LOEU. The main outcome was CI, reflected as an adjusted Montreal Cognition Assessment score of < 26 points. A nomogram based on a multivariable logistic regression model was constructed. Its discriminative ability, calibration, and clinical applicability were tested using calibration plots, the area under the curve (AUC), and decision curves. Internal model validation was conducted using the bootstrap method. The moderating effect of education on the relationship between PVH and cognitive function was examined using hierarchical linear regression. RESULTS Forty-four of 61 (72.1%) patients had CI. A nomogram incorporating seizure type, total cerebral small vessel disease burden score, and PVH score was built to identify the risk factors for CI. The AUC of the model was 0.881 (95% confidence interval: 0.771-0.994) and 0.78 (95% confidence interval: 0.75-0.8) after internal validation. Higher educational levels blunted the negative impact of PVH on cognitive function. CONCLUSION Our nomogram provides a convenient tool for identifying patients with LOEU who are at risk of CI. Moreover, our findings demonstrate the importance of education for these patients.
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Affiliation(s)
- Huijuan Wan
- Department of Neurology, First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, People's Republic of China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Qi Liu
- Department of Neurology, First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, People's Republic of China
| | - Chao Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Wenyu Dong
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Shengsong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Weixiong Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Chengyu Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Zhanxiang Wang
- Department of Neurosurgery and Department of Neuroscience, Fujian Key Laboratory of Brain Tumors Diagnosis and Precision Treatment, Xiamen Key Laboratory of Brain Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, People's Republic of China
| | - Tao Cui
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China.
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15
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Zachariou V, Pappas C, Bauer CE, Shao X, Liu P, Lu H, Wang DJJ, Gold BT. Regional differences in the link between water exchange rate across the blood-brain barrier and cognitive performance in normal aging. GeroScience 2024; 46:265-282. [PMID: 37713089 PMCID: PMC10828276 DOI: 10.1007/s11357-023-00930-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 09/04/2023] [Indexed: 09/16/2023] Open
Abstract
The blood-brain barrier (BBB) undergoes functional changes with aging which may contribute to cognitive decline. A novel, diffusion prepared arterial spin labeling-based MRI technique can measure the rate of water exchange across the BBB (kw) and may thus be sensitive to age-related alterations in water exchange at the BBB. However, studies investigating relationships between kw and cognition have reported different directions of association. Here, we begin to investigate the direction of associations between kw and cognition in different brain regions, and their possible underpinnings, by evaluating links between kw, cognitive performance, and MRI markers of cerebrovascular dysfunction and/or damage. Forty-seven healthy older adults (age range 61-84) underwent neuroimaging to obtain whole-brain measures of kw, cerebrovascular reactivity (CVR), and white matter hyperintensity (WMH) volumes. Additionally, participants completed uniform data set (Version 3) neuropsychological tests of executive function (EF) and episodic memory (MEM). Voxel-wise linear regressions were conducted to test associations between kw and cognitive performance, CVR, and WMH volumes. We found that kw in the frontoparietal brain regions was positively associated with cognitive performance but not with CVR or WMH volumes. Conversely, kw in the basal ganglia was negatively associated with cognitive performance and CVR and positively associated with regional, periventricular WMH volume. These regionally dependent associations may relate to different physiological underpinnings in the relationships between kw and cognition in neocortical versus subcortical brain regions in older adults.
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Affiliation(s)
- Valentinos Zachariou
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA.
| | - Colleen Pappas
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Christopher E Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peiying Liu
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Danny J J Wang
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Brian T Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center On Aging, University of Kentucky, Lexington, KY, USA
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY, USA
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16
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Guo W, Wang X, Chen Y, Wang F, Qiu J, Lu W. Effect of Menopause Status on Brain Perfusion Hemodynamics. Stroke 2024; 55:260-268. [PMID: 37850361 DOI: 10.1161/strokeaha.123.044841] [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: 06/04/2023] [Accepted: 09/26/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND The menopause transition is associated with an increasing risk of cerebrovascular disorders. However, the direct effect of menopause status on brain perfusion hemodynamics remains unclear. This study aimed to explore the influence of menopause status on cerebral blood flow (CBF) using arterial spin labeling magnetic resonance imaging. METHODS In this cross-sectional study, 185 subjects underwent arterial spin labeling magnetic resonance imaging at a hospital in China between September 2020 and December 2022, including 38 premenopausal women (mean age, 47.74±2.02 years), 42 perimenopausal women (mean age, 50.62±3.15 years), 42 postmenopausal women (mean age, 54.02±4.09 years), and 63 men (mean age, 52.70±4.33 years) of a similar age range. Mean CBF values in the whole brain, gray matter, white matter, cortical gray matter, subcortical gray matter, juxtacortical white matter, deep white matter, and periventricular white matter were extracted. ANCOVA was used to compare mean CBF among the 4 groups, controlling for confounding factors. Student t test was applied to compare mean CBF between the 3 female groups and age-matched males, respectively. Multivariable regression analysis was used to analysis the effect of age, sex, and menopause status on the CBF of the whole brain, gray matter, white matter, and subregions. RESULTS Perimenopausal and postmenopausal women showed a higher proportion of white matter hyperintensities compared with the other 2 groups (P<0.001). Premenopausal women exhibited higher CBF in the whole brain, gray matter, white matter, and subregions, compared with perimenopausal, postmenopausal women and men (P≤0.001). Multivariable regression analysis demonstrated significant effect of age and insignificant effect of sex on CBF for all participants. In addition, menopause status and the interaction between age and menopause status on CBF of whole brain, gray matter, white matter, and the subregions were observed in female participants, except for the deep and periventricular white matter regions, with premenopausal women exhibited a slight increase in CBF with age, while perimenopausal and postmenopausal women exhibited declines in CBF with age. CONCLUSIONS The current findings suggest that alterations of brain perfusion hemodynamics begin during the perimenopause period, which may be due to the increased burden of white matter hyperintensities.
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Affiliation(s)
- Wei Guo
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, China (W.G., Y.C., F.W., W.L.)
| | - Xiuzhu Wang
- Department of Obstetrics, Taian City Central Hospital, China (X.W.)
| | - Yinzhong Chen
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, China (W.G., Y.C., F.W., W.L.)
| | - Feng Wang
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, China (W.G., Y.C., F.W., W.L.)
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China (J.Q.)
| | - Weizhao Lu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Taian, China (W.G., Y.C., F.W., W.L.)
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17
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Iandolo R, Avci E, Bommarito G, Sandvig I, Rohweder G, Sandvig A. Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults. Neuroimage Clin 2024; 41:103569. [PMID: 38281363 PMCID: PMC10839532 DOI: 10.1016/j.nicl.2024.103569] [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: 07/10/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. METHODS 40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. RESULTS Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. CONCLUSION WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.
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Affiliation(s)
- Riccardo Iandolo
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Esin Avci
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gitta Rohweder
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Stroke Unit, Department of Medicine, St Olav's University Hospital, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway; Department of Clinical Neurosciences, Division of Neuro, Head and Neck, Umeå University Hospital, Umeå, Sweden; Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden.
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18
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Menacher A, Nichols TE, Holmes C, Ganjgahi H. Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior. J Am Stat Assoc 2024; 119:66-80. [PMID: 39132605 PMCID: PMC11315456 DOI: 10.1080/01621459.2023.2278201] [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: 07/21/2022] [Accepted: 10/24/2023] [Indexed: 08/13/2024]
Abstract
Neural demyelination and brain damage accumulated in white matter appear as hyperintense areas on T2-weighted MRI scans in the form of lesions. Modeling binary images at the population level, where each voxel represents the existence of a lesion, plays an important role in understanding aging and inflammatory diseases. We propose a scalable hierarchical Bayesian spatial model, called BLESS, capable of handling binary responses by placing continuous spike-and-slab mixture priors on spatially-varying parameters and enforcing spatial dependency on the parameter dictating the amount of sparsity within the probability of inclusion. The use of mean-field variational inference with dynamic posterior exploration, which is an annealing-like strategy that improves optimization, allows our method to scale to large sample sizes. Our method also accounts for underestimation of posterior variance due to variational inference by providing an approximate posterior sampling approach based on Bayesian bootstrap ideas and spike-and-slab priors with random shrinkage targets. Besides accurate uncertainty quantification, this approach is capable of producing novel cluster size based imaging statistics, such as credible intervals of cluster size, and measures of reliability of cluster occurrence. Lastly, we validate our results via simulation studies and an application to the UK Biobank, a large-scale lesion mapping study with a sample size of 40,000 subjects.
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Affiliation(s)
| | | | | | - Habib Ganjgahi
- Department of Statistics, University of Oxford
- Nuffield Department of Population Health, University of Oxford
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19
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Buller-Peralta I, Gregory S, Low A, Dounavi ME, Bridgeman K, Ntailianis G, Lawlor B, Naci L, Koychev I, Malhotra P, O'Brien JT, Ritchie CW, Muniz-Terrera G. Comprehensive allostatic load risk index is associated with increased frontal and left parietal white matter hyperintensities in mid-life cognitively healthy adults. Sci Rep 2024; 14:573. [PMID: 38177228 PMCID: PMC10766612 DOI: 10.1038/s41598-023-49656-3] [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: 09/14/2023] [Accepted: 12/11/2023] [Indexed: 01/06/2024] Open
Abstract
To date, there is a considerable heterogeneity of methods to score Allostatic Load (AL). Here we propose a comprehensive algorithm (ALCS) that integrates commonly used approaches to generate AL risk categories and assess associations to brain structure deterioration. In a cohort of cognitively normal mid-life adults (n = 620, age 51.3 ± 5.48 years), we developed a comprehensive composite for AL scoring incorporating gender and age differences, high quartile approach, clinical reference values, and current medications, to then generate AL risk categories. Compared to the empirical approach (ALES), ALCS showed better model fit criteria and a strong association with age and sex. ALSC categories were regressed against brain and white matter hyperintensity (WMH) volumes. Higher AL risk categories were associated with increased total, periventricular, frontal, and left parietal WMH volumes, also showing better fit compared to ALES. When cardiovascular biomarkers were removed from the ALSC algorithm, only left-frontal WMHV remained associated with AL, revealing a strong vascular burden influencing the index. Our results agree with previous evidence and suggest that sustained stress exposure enhances brain deterioration in mid-life adults. Showing better fit than ALES, our comprehensive algorithm can provide a more accurate AL estimation to explore how stress exposure enhances age-related health decline.
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Affiliation(s)
- Ingrid Buller-Peralta
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK.
| | - Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Level E4, Box 189, Cambridge, CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Level E4, Box 189, Cambridge, CB2 0QQ, UK
| | - Katie Bridgeman
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK
| | - Georgios Ntailianis
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK
| | - Brian Lawlor
- Trinity College Institute of Neuroscience, School of Psychology, Aras an Phiarsaigh, Trinity College Dublin, Dublin 2, Ireland
- Global Brain Health Institute, Trinity College Dublin, GBHI Office Room 0.60, Lloyd Building Trinity College Dublin, Dublin 2, Ireland
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Aras an Phiarsaigh, Trinity College Dublin, Dublin 2, Ireland
- Global Brain Health Institute, Trinity College Dublin, GBHI Office Room 0.60, Lloyd Building Trinity College Dublin, Dublin 2, Ireland
| | - Ivan Koychev
- Department of Psychiatry, Warneford Hospital, Oxford University, Warneford Ln, Headington, Oxford, OX3 7JX, UK
| | - Paresh Malhotra
- Department of Brain Sciences, Imperial College London, Burlington Danes, The Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Level E4, Box 189, Cambridge, CB2 0QQ, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK
- Scottish Brain Sciences, Gyleview House, 3 Redheughs Rigg, South Gyle, Edinburgh, EH12 9DQ, UK
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatients Department Level 2 Western General Hospital, The University of Edinburgh, Crewe Rd S, Edinburgh, EH4 2XU, UK
- Ohio University Heritage College of Osteopathic Medicine, 191 W Union St, Athens, OH, 45701, USA
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20
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Schindler LS, Subramaniapillai S, Ambikairajah A, Barth C, Crestol A, Voldsbekk I, Beck D, Gurholt TP, Topiwala A, Suri S, Ebmeier KP, Andreassen OA, Draganski B, Westlye LT, de Lange AMG. Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later. Front Glob Womens Health 2023; 4:1320640. [PMID: 38213741 PMCID: PMC10783171 DOI: 10.3389/fgwh.2023.1320640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p < 0.001, LDL β = 0.20, p < 0.001, triglycerides β = 0.12, p < 0.001) and HbA1c (β = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (β = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (β = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (β range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (β = -0.27, p < 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
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Affiliation(s)
- Louise S. Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ananthan Ambikairajah
- Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, Australia
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P. Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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21
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Caçoilo A, Dortdivanlioglu B, Rusinek H, Weickenmeier J. A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging. BRAIN MULTIPHYSICS 2023; 5:100072. [PMID: 37546181 PMCID: PMC10399513 DOI: 10.1016/j.brain.2023.100072] [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] [Indexed: 08/08/2023] Open
Abstract
Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm2/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.
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Affiliation(s)
- Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
| | - Berkin Dortdivanlioglu
- Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America
| | - Henry Rusinek
- Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America
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22
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Tubi MA, Wheeler K, Matsiyevskiy E, Hapenney M, Mack WJ, Chui HC, King K, Thompson PM, Braskie MN. White matter hyperintensity volume modifies the association between CSF vascular inflammatory biomarkers and regional FDG-PET along the Alzheimer's disease continuum. Neurobiol Aging 2023; 132:1-12. [PMID: 37708739 PMCID: PMC10843575 DOI: 10.1016/j.neurobiolaging.2023.08.002] [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: 02/03/2023] [Revised: 07/28/2023] [Accepted: 08/06/2023] [Indexed: 09/16/2023]
Abstract
In older adults with abnormal levels of Alzheimer's disease neuropathology, lower cerebrospinal fluid (CSF) vascular endothelial growth factor (VEGF) levels are associated with lower [¹⁸F]-fluorodeoxyglucose positron emission tomography (FDG-PET) signal, but whether this association is (1) specific to VEGF or broadly driven by vascular inflammation, or (2) modified by vascular risk (e.g., white matter hyperintensities [WMHs]) remains unknown. To address this and build upon our past work, we evaluated whether 5 CSF vascular inflammation biomarkers (vascular cell adhesion molecule 1, VEGF, C-reactive protein, fibrinogen, and von Willebrand factor)-previously associated with CSF amyloid levels-were related to FDG-PET signal and whether WMH volume modified these associations in 158 Alzheimer's Disease Neuroimaging Initiative participants (55-90 years old, 39 cognitively normal, 80 mild cognitive impairment, 39 Alzheimer's disease). We defined regions both by cortical boundary and by the 3 major vascular territories: anterior, middle, and posterior cerebral arteries. We found that WMH volume had interactive effects with CSF biomarkers (VEGF and C-reactive protein) on FDG-PET throughout the cortex in both vascular territories and conventionally defined regions of interest.
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Affiliation(s)
- Meral A Tubi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Koral Wheeler
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth Matsiyevskiy
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Matthew Hapenney
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Wendy J Mack
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Helena C Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kevin King
- Department of Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Meredith N Braskie
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
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Bruno A, Prabu P, Vedala K, Sethuraman S, Nichols FT. Distribution of cerebral age-related white matter changes in relation to risk factors in stroke patients. Clin Neurol Neurosurg 2023; 235:108018. [PMID: 37924721 DOI: 10.1016/j.clineuro.2023.108018] [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: 06/19/2023] [Revised: 10/20/2023] [Accepted: 10/21/2023] [Indexed: 11/06/2023]
Abstract
INTRODUCTION The distribution of cerebral age-related white matter changes (ARWMC) may be indicative of the underlying etiology and could suggest optimal interventions. We aimed to determine if left ventricular hypertrophy (LVH), a marker of uncontrolled hypertension, along with additional risk factors are associated with the distribution of cerebral ARWMC. METHODS We analyzed data of 172 patients from a hospital stroke registry who had acute stroke and brain MRI. We classified lesion location as superficial (frontal, parieto-occipital, or temporal) or deep (basal nuclei) using the ARWMC scale. We defined a superficial ARWMC index as the superficial minus the deep score. We excluded infratentorial lesions and patients with bilateral strokes. Regression analysis analyzed LVH and other relevant clinical factors for independent association with the superficial ARWMC index. RESULTS The superficial ARWMC scores ranged from 0 to 6, the deep scores from 0 to 3, and the superficial ARWMC index from -2 to 6. We categorized the superficial ARWMC index as -2 to 1 (n = 65), 2 (n = 50), and 3 - 6 (n = 57). In bivariate analysis, ARWMC distribution was significantly associated with older age, lower household income (HI), and lower serum triglyceride (TG) levels. In multiple logistic regression analysis, higher superficial ARWMC index was significantly associated with lower HI (OR 10.72, 95 % CI 2.30-49.85), lower serum low density cholesterol (LDL) (OR 0.86, 95 % CI 0.75-0.98, per 10 mg/dL), and lower serum TG levels (OR 0.91, 95 % CI 0.85-0.99, per 10 mg/dL). The area under the curve in receiver operating characteristic analysis (95 % CI) for HI was 0.63 (0.49-0.76), LDL level 0.64 (0.51-0.77), and TG level 0.77 (0.65-0.88). CONCLUSION In this study, LVH was not associated with the distribution of cerebral ARWMC. Using an alternate classification of ARWMC distribution and analyzing additional risk factors in larger studies may yield further discoveries.
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Affiliation(s)
- Askiel Bruno
- Department of Neurology, Medical College of Georgia at Augusta University, Augusta, GA, United States.
| | - Pranav Prabu
- Medical College of Georgia, Augusta, GA, United States
| | | | - Sankara Sethuraman
- Department of Mathematics, Augusta University, Augusta, GA, United States
| | - Fenwick T Nichols
- Department of Neurology, Medical College of Georgia at Augusta University, Augusta, GA, United States
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Schroyen G, Sleurs C, Ottenbourgs T, Leenaerts N, Nevelsteen I, Melis M, Smeets A, Deprez S, Sunaert S. Changes in leukoencephalopathy and serum neurofilament after (neo)adjuvant chemotherapy for breast cancer. Transl Oncol 2023; 37:101769. [PMID: 37651891 PMCID: PMC10480307 DOI: 10.1016/j.tranon.2023.101769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Previous case studies have provided evidence for chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective research is lacking. Hence, we investigated leukoencephalopathy before and after chemotherapy and its association with a serum neuroaxonal damage marker. METHODS This prospective cohort study included 40 patients receiving chemotherapy for breast cancer, and two age- and education-matched control groups, recruited between 2018 and 2021 (31-64 years of age). The latter control groups consisted of 39 chemotherapy-naïve patients and 40 healthy women. Fluid-attenuated inversion-recovery magnetic resonance imaging was used for lesion volumetry (total, juxtacortical, periventricular, infratentorial, and deep white matter) and blood serum to measure neurofilament light chain (NfL) levels. Acquisition took place pre-chemotherapy and three months and one-year post-chemotherapy, or at corresponding intervals. Within/between group differences were compared using robust mixed-effects modeling, and associations between total lesion volume and serum-NfL with linear regression. RESULTS Stronger increases in deep white matter lesion volumes were observed shortly post-chemotherapy, compared with healthy women (ßstandardized=0.09, pFDR<0.001). Increases in total lesion volume could mainly be attributed to enlargement of existing lesions (mean±SD, 0.12±0.16 mL), rather than development of new lesions (0.02±0.02 mL). A stronger increase in serum-NfL concentration was observed shortly post-chemotherapy compared with both control groups (ß>0.70, p<0.004), neither of which showed any changes over time, whereas a decrease was observed compared with healthy women one-year post-chemotherapy (ß=-0.54, p = 0.002). Serum-NfL concentrations were associated with lesion volume one-year post-chemotherapy (or at matched timepoint; ß=0.36, p = 0.010), whereas baseline or short-term post-therapy levels or changes were not. CONCLUSION These results underscore the possibility of chemotherapy-induced leukoencephalopathy months post-treatment, as well as the added value of serum-NfL as a prognostic marker for peripheral/central neurotoxicity. TRANSLATIONAL RELEVANCE Previous case studies have provided evidence of chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective studies to estimate longitudinal changes are currently missing. In this study, we used longitudinal fluid-attenuated inversion-recovery magnetic resonance imaging to assess white matter lesion volumes in patients treated for non-metastatic breast cancer and healthy women. Our findings demonstrate that chemotherapy-treated patients exhibit stronger increases in lesion volumes compared with healthy women, specifically in deep white matter, at three months post-chemotherapy. Increases could mainly be attributed to enlargement of existing lesions, rather than development of new lesions. Last, serum concentrations of neurofilament light chain, a neuroaxonal damage marker, increased shortly after chemotherapy and long-term post-chemotherapy levels were associated with lesion volumes. These findings highlight the potential of this non-invasive serum marker as a prognostic marker for peripheral and/or central neurotoxicity. Implementation in clinical practice could aid in therapeutic decisions, assessing disease activity, or monitoring treatment response.
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Affiliation(s)
- Gwen Schroyen
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Charlotte Sleurs
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; Tilburg University, Department of Cognitive Neuropsychology, Tilburg, the Netherlands; KU Leuven, Department of Oncology, Leuven, Belgium
| | - Tine Ottenbourgs
- KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Nicolas Leenaerts
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; KU Leuven, Department of Neurosciences, Mind-Body Research, Leuven, Belgium; KU Leuven, University Psychiatric Center, Leuven, Belgium; University Hospitals Leuven, Department of Psychiatry, Leuven, Belgium
| | - Ines Nevelsteen
- University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Oncology, Leuven, Belgium; University Hospitals Leuven, Department of Oncology, Surgical Oncology, Leuven, Belgium
| | - Michelle Melis
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Ann Smeets
- University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Oncology, Leuven, Belgium; University Hospitals Leuven, Department of Oncology, Surgical Oncology, Leuven, Belgium
| | - Sabine Deprez
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium.
| | - Stefan Sunaert
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium; University Hospitals Leuven, Department of Radiology, Leuven, Belgium
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25
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Parent O, Bussy A, Devenyi GA, Dai A, Costantino M, Tullo S, Salaciak A, Bedford S, Farzin S, Béland ML, Valiquette V, Villeneuve S, Poirier J, Tardif CL, Dadar M, Chakravarty MM. Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging. Brain Commun 2023; 5:fcad279. [PMID: 37953840 PMCID: PMC10636521 DOI: 10.1093/braincomms/fcad279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/05/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.
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Affiliation(s)
- Olivier Parent
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Aurélie Bussy
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Gabriel Allan Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Dai
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Manuela Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Stephanie Tullo
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Salaciak
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Saashi Bedford
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sarah Farzin
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Marie-Lise Béland
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Vanessa Valiquette
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sylvia Villeneuve
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Judes Poirier
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Molecular Neurobiology Unit, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Medicine, McGill University, Montreal, Quebec H4A 3J1, Canada
| | - Christine Lucas Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
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26
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Ottavi TP, Pepper E, Bateman G, Fiorentino M, Brodtmann A. Consensus statement for the management of incidentally found brain white matter hyperintensities in general medical practice. Med J Aust 2023; 219:278-284. [PMID: 37604652 DOI: 10.5694/mja2.52079] [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: 12/16/2022] [Revised: 06/09/2023] [Accepted: 06/30/2023] [Indexed: 08/23/2023]
Abstract
INTRODUCTION There is a paradigm shift in our understanding of white matter hyperintensities (WMH) found on brain imaging. They were once thought to be a normal phenomenon of ageing and, therefore, warranted no further investigation. However, evidence now suggests these lesions are markers of poor brain and cardiovascular health, portending an increased risk of stroke, cognitive decline, depression and death. Nevertheless, no specific guidelines exist for the management of incidentally found WMH for general medical practitioners and other clinicians ordering brain magnetic resonance imaging scans for diverse clinical indications. Informed by a literature review and expert opinion gleaned from stroke neurologists, medical and imaging specialists, and general practitioners, we present our consensus statement to guide the management of incidentally found WMH in adults. MAIN RECOMMENDATIONS When incidental WMH are found on brain imaging: Perform a detailed history and examination to screen for neurological events. Investigate for potential undiagnosed or undertreated cardiovascular risk factors, especially hypertension and diabetes mellitus. Commence intensive and individualised cardiovascular risk management when risk factors are uncovered. Treat underlying risk factors via accepted guidelines but note that antiplatelet and anticoagulant medications should not be prescribed for incidental WMH in the absence of an alternative indication. CHANGES TO MANAGEMENT AS A RESULT OF THIS CONSENSUS STATEMENT A brain health opportunity. We consider the discovery of incidental WMH on brain imaging to represent an opportunity to investigate for common cardiovascular risk factors and to optimise brain health. This can be commenced and monitored by the general practitioner or physician without delay in waiting for an outpatient neurology review.
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Wang X, Wang Y, Gao D, Zhao Z, Wang H, Wang S, Liu S. Characterizing the penumbras of white matter hyperintensities in patients with cerebral small vessel disease. Jpn J Radiol 2023; 41:928-937. [PMID: 37160589 PMCID: PMC10468925 DOI: 10.1007/s11604-023-01419-w] [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: 11/10/2022] [Accepted: 03/24/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE The white matter hyperintensity penumbra (WMH-P) is the subtly changed normal-appearing white matter (NAWM) that surrounds white matter hyperintensities (WMHs). The goal of this study was to define WMH-P in cerebral small vessel disease (CSVD) by arterial spin labeling (ASL) and diffusion tensor imaging (DTI)/diffusion kurtosis imaging (DKI). MATERIALS AND METHODS We prospectively analyzed 42 patients with CSVD. To determine the range of cerebral blood flow (CBF) and DTI/DKI penumbras around white matter hyperintensities, we generated NAWM layer masks from periventricular WMHs (PVWMHs) and deep WMHs (DWMHs). Mean values of CBF, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis, and radial kurtosis within the WMHs and their corresponding NAWM layer masks were analyzed. Paired sample t tests were used for analysis, and differences were considered statistically significant if the associated p value was ≤ 0.05. RESULTS For DWMHs, the CBF penumbras were 13 mm, and the DTI/DKI penumbras were 8 mm. For PVWMHs, the CBF penumbras were 14 mm, and the DTI/DKI penumbras were 14 mm. CONCLUSIONS Our findings revealed that DTI/DKI and ASL can show structural and blood flow changes in brain tissue surrounding WMHs. In DWMHs, the blood flow penumbra was larger than the structural penumbra, while in PVWMHs, the blood flow penumbra was almost the same as the structural penumbra.
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Affiliation(s)
- Xin Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China.
| | - Yu Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Deyu Gao
- North China University of Technology, Tangshan City, 063000, Hebei Province, China
| | - Zhichao Zhao
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Haiping Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Sujie Wang
- Department of Neurology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Shiguang Liu
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
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28
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Hosseinpour Z, Oladosu O, Liu WQ, Pike GB, Yong VW, Metz LM, Zhang Y. Distinct characteristics and severity of brain magnetic resonance imaging lesions in women and men with multiple sclerosis assessed using verified texture analysis measures. Front Neurol 2023; 14:1213377. [PMID: 37638198 PMCID: PMC10449451 DOI: 10.3389/fneur.2023.1213377] [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: 04/27/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023] Open
Abstract
Background and goal In vivo characterization of brain lesion types in multiple sclerosis (MS) has been an ongoing challenge. Based on verified texture analysis measures from clinical magnetic resonance imaging (MRI), this study aimed to develop a method to identify two extremes of brain MS lesions that were approximately severely demyelinated (sDEM) and highly remyelinated (hREM), and compare them in terms of common clinical variables. Method Texture analysis used an optimized gray-level co-occurrence matrix (GLCM) method based on FLAIR MRI from 200 relapsing-remitting MS participants. Two top-performing metrics were calculated: texture contrast and dissimilarity. Lesion identification applied a percentile approach according to texture values calculated: ≤ 25 percentile for hREM and ≥75 percentile for sDEM. Results The sDEM had a greater total normalized volume yet smaller average size, and worse MRI texture than hREM. In lesion distribution mapping, the two lesion types appeared to overlap largely in location and were present the most in the corpus callosum and periventricular regions. Further, in sDEM, the normalized volume was greater and in hREM, the average size was smaller in men than women. There were no other significant results in clinical variable-associated analyses. Conclusion Percentile statistics of competitive MRI texture measures may be a promising method for probing select types of brain MS lesion pathology. Associated findings can provide another useful dimension for improved measurement and monitoring of disease activity in MS. The different characteristics of sDEM and hREM between men and women likely adds new information to the literature, deserving further confirmation.
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Affiliation(s)
- Zahra Hosseinpour
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Olayinka Oladosu
- Department of Neuroscience, Faculty of Graduate Studies, University of Calgary, Calgary, AB, Canada
| | - Wei-qiao Liu
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - G. Bruce Pike
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - V. Wee Yong
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Luanne M. Metz
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Yunyan Zhang
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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29
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Moniruzzaman M, Kadota A, Hisamatsu T, Segawa H, Kondo K, Torii S, Miyagawa N, Fujiyoshi A, Yano Y, Watanabe Y, Shiino A, Nozaki K, Ueshima H, Miura K. Relationship between Serum Irisin Levels and MRI-Measured Cerebral Small Vessel Disease in Japanese Men. J Atheroscler Thromb 2023; 30:1045-1056. [PMID: 36384910 PMCID: PMC10406628 DOI: 10.5551/jat.63824] [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: 07/14/2022] [Accepted: 09/30/2022] [Indexed: 08/04/2023] Open
Abstract
AIM Irisin, an exercise-induced myokine, is a potential neurotrophic factor; however, its relationship with cerebral small vessel disease (CSVD) remains unknown. Therefore, we investigated whether serum irisin levels are associated with CSVD in healthy Japanese men. METHODS We analyzed data from 720 men free of stroke and participated in this observational study. Serum irisin levels were measured by enzyme-linked immunosorbent assay. CSVD was assessed on deep and subcortical white matter hyperintensities (DSWMHs), periventricular hyperintensities (PVHs), lacunar infarcts (LIs), and cerebral microbleeds (CMBs) on brain magnetic resonance imaging. We calculated the total CSVD score (ranges 0-4) to express the total CSVD burden. We computed the adjusted odds ratios (ORs), with 95% confidence intervals (CIs), of the total CSVD score and individual CSVD features using logistic regression models according to the quartiles of irisin (reference: Q1). RESULTS Serum irisin levels were associated with lower ORs of higher (vs. zero or lower score) total CSVD score, with the lowest risk (OR, 0.63; 95% CI, 0.41-0.97) being observed in Q3 compared to Q1 after adjustment of potential covariates. Similar results were obtained for younger adults (<65 years). Among individual CSVD features, irisin was associated with a reduced risk of LIs in the total sample and PVHs, LIs, and CMBs in younger adults. No relationship was observed in older adults (≥ 65 years). CONCLUSIONS Serum irisin levels were associated with less burden of total CSVD in healthy Japanese men. Serum irisin levels were also related with a reduced risk of PVHs, LIs, and CMBs, but not DSWMHs.
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Affiliation(s)
- Mohammad Moniruzzaman
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Aya Kadota
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | | | - Hiroyoshi Segawa
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
| | - Keiko Kondo
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Sayuki Torii
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Naoko Miyagawa
- Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Akira Fujiyoshi
- Department of Hygiene, School of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Yuichiro Yano
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
| | - Yoshiyuki Watanabe
- Department of Radiology, Shiga University of Medical Science, Shiga, Japan
| | - Akihiko Shiino
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Kazuhiko Nozaki
- Department of Neurosurgery, Shiga University of Medical Science, Shiga, Japan
| | - Hirotsugu Ueshima
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
| | - Katsuyuki Miura
- NCD Epidemiology Research Center (NERC), Shiga University of Medical Science, Shiga, Japan
- Department of Public Health, Shiga University of Medical Science, Shiga, Japan
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30
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Hannan J, Wilmskoetter J, Fridriksson J, Hillis AE, Bonilha L, Busby N. Brain health imaging markers, post-stroke aphasia and Cognition: A scoping review. Neuroimage Clin 2023; 39:103480. [PMID: 37536153 PMCID: PMC10412866 DOI: 10.1016/j.nicl.2023.103480] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 08/05/2023]
Abstract
For the past decade, brain health has been an emerging line of scientific inquiry assessing the impact of age-related neurostructural changes on cognitive decline and recovery from brain injury. Typically, compromised brain health is attributed to the presence of small vessel disease (SVD) and brain tissue atrophy, which are represented by various neuroimaging features. However, to date, the relationship between brain health markers and chronic aphasia severity remains unclear. Thus, the goal of this scoping review was to assess the current body of evidence regarding the relationship between SVD-related brain health biomarkers and post-stroke aphasia and cognition. In all, 187 articles were identified from 3 databases, of which 16 articles met the criteria for inclusion. Among these studies, 11 focused on cognition rather than aphasia, while 2 investigated both. Of the 10 studies that used white matter hyperintensities (WMHs) as an indicator of SVD severity, 8 studies (80%) demonstrated a relationship between WMH load and worse cognition in stroke patients. Interestingly, among the studies that specifically investigated aphasia, all 5 studies (100%) demonstrated a relationship between SVD and worse language performance. They also indicated that factors other than brain health (e.g., lesion, age, time post onset) played an important role in determining aphasia severity at a single timepoint. These findings suggest that brain health is likely a crucial factor in the context of aphasia recovery, possibly indicating the necessity of cognitive reserve thresholds for the multimodal cognitive demands associated with language recovery. While SVD and structural brain health are not commonly considered as predictors of aphasia severity, more comprehensive models incorporating brain health have the potential to improve prognosis of post-stroke cognitive and language deficits. Given the variability in the existing literature, a uniform grading system for overall SVD would be beneficial for future research on the mechanisms related to brain networks and neuroplasticity, and their translational impact.
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Affiliation(s)
- Jade Hannan
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Physical Medicine, Rehabilitation, and Cognitive Science, Johns Hopkins University, Baltimore, MD, USA
| | | | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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31
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Owens CD, Pinto CB, Detwiler S, Mukli P, Peterfi A, Szarvas Z, Hoffmeister JR, Galindo J, Noori J, Kirkpatrick AC, Dasari TW, James J, Tarantini S, Csiszar A, Ungvari Z, Prodan CI, Yabluchanskiy A. Cerebral small vessel disease pathology in COVID-19 patients: A systematic review. Ageing Res Rev 2023; 88:101962. [PMID: 37224885 PMCID: PMC10202464 DOI: 10.1016/j.arr.2023.101962] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/20/2023] [Accepted: 05/21/2023] [Indexed: 05/26/2023]
Abstract
Cerebral small vessel disease (CSVD) is the leading cause of vascular cognitive impairment and is associated with COVID-19. However, contributing factors that often accompany CSVD pathology in COVID-19 patients may influence the incidence of cerebrovascular complications. Thus, a mechanism linking COVID-19 and CSVD has yet to be uncovered and differentiated from age-related comorbidities (i.e., hypertension), and medical interventions during acute infection. We aimed to evaluate CSVD in acute and recovered COVID-19 patients and to differentiate COVID-19-related cerebrovascular pathology from the above-mentioned contributing factors by assessing the localization of microbleeds and ischemic lesions/infarctions in the cerebrum, cerebellum, and brainstem. A systematic search was performed in December 2022 on PubMed, Web of Science, and Embase using a pre-established search criterion related to history of, or active COVID-19 with CSVD pathology in adults. From a pool of 161 studies, 59 met eligibility criteria and were included. Microbleeds and ischemic lesions had a strong predilection for the corpus callosum and subcortical/deep white matter in COVID-19 patients, suggesting a distinct CSVD pathology. These findings have important implications for clinical practice and biomedical research as COVID-19 may independently, and through exacerbation of age-related mechanisms, contribute to increased incidence of CSVD.
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Affiliation(s)
- Cameron D Owens
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Camila Bonin Pinto
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Sam Detwiler
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Peter Mukli
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Anna Peterfi
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Zsofia Szarvas
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Jordan R Hoffmeister
- Department of Psychiatry and Behavioral Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Juliette Galindo
- Department of Psychiatry and Behavioral Sciences, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jila Noori
- Dean McGee Eye Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Angelia C Kirkpatrick
- Cardiovascular Section, Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Veterans Affairs Medical Center, Oklahoma City, OK, USA
| | - Tarun W Dasari
- Cardiovascular Section, Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Judith James
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Arthritis & Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA; Department of Internal Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Stefano Tarantini
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary; The Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Anna Csiszar
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Zoltan Ungvari
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Departments of Public Health, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary; Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Calin I Prodan
- Veterans Affairs Medical Center, Oklahoma City, OK, USA; Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Andriy Yabluchanskiy
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; The Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA; Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Wang W, Shi L, Ma H, Zhu S, Ge Y, Xu K. Comparison of the clinical value of MRI and plasma markers for cognitive impairment in patients aged ≥75 years: a retrospective study. PeerJ 2023; 11:e15581. [PMID: 37366421 PMCID: PMC10290829 DOI: 10.7717/peerj.15581] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/26/2023] [Indexed: 06/28/2023] Open
Abstract
Background Dementia has become the main cause of disability in older adults aged ≥75 years. Cerebral small vessel disease (CSVD) is involved in cognitive impairment (CI) and dementia and is a cause of vascular CI (VCI), which is manageable and its onset and progression can be delayed. Simple and effective markers will be beneficial to the early detection and intervention of CI. The aim of this study is to investigate the clinical application value of plasma amyloid β1-42 (Aβ42), phosphorylated tau 181 (p-tau181) and conventional structural magnetic resonance imaging (MRI) parameters for cognitive impairment (CI) in patients aged ≥75 years. Methods We retrospectively selected patients who visited the Affiliated Hospital of Xuzhou Medical University and were clinically diagnosed with or without cognitive dysfunction between May 2018 and November 2021. Plasma indicators (Aβ42 and p-tau181) and conventional structural MRI parameters were collected and analyzed. Multivariate logistic regression and receiver operator characteristic (ROC) curve were used to evaluate the diagnostic value. Results One hundred and eighty-four subjects were included, including 54 cases in CI group and 130 cases in noncognitive impairment (NCI) groups, respectively. Univariate logistic regression analysis revealed that the percentages of Aβ42+, P-tau 181+, and Aβ42+/P-tau181+ showed no significant difference between the groups of CI and NCI (all P > 0.05). Multivariate logistic regression analysis showed that moderate/severe periventricular WMH (PVWMH) (OR 2.857, (1.365-5.983), P = 0.005), lateral ventricle body index (LVBI) (OR 0.413, (0.243-0.700), P = 0.001), and cortical atrophy (OR 1.304, (1.079-1.575), P = 0.006) were factors associated with CI. The combined model including PVWMH, LVBI, and cortical atrophy to detect CI and NCI showed an area under the ROC curve (AUROC) is 0.782, with the sensitivity and specificity 68.5% and 78.5%, respectively. Conclusion For individuals ≥75 years, plasma Aβ42 and P-tau181 might not be associated with cognitive impairment, and MRI parameters, including PVWMH, LVBI and cortical atrophy, are related to CI. The cognitive statuses of people over 75 years old were used as the endpoint event in this study. Therefore, it can be considered that these MRI markers might have more important clinical significance for early assessment and dynamic observation, but more studies are still needed to verify this hypothesis.
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Affiliation(s)
- Wei Wang
- Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Institute of Medical Imaging and Digital Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Lin Shi
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shangdong, China
| | - Hong Ma
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Institute of Medical Imaging and Digital Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Shiguang Zhu
- Department of Neurology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yaqiong Ge
- GE Healthcare, Precision Health Institution, Shanghai, China
| | - Kai Xu
- Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Institute of Medical Imaging and Digital Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
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Botz J, Lohner V, Schirmer MD. Spatial patterns of white matter hyperintensities: a systematic review. Front Aging Neurosci 2023; 15:1165324. [PMID: 37251801 PMCID: PMC10214839 DOI: 10.3389/fnagi.2023.1165324] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/24/2023] [Indexed: 05/31/2023] Open
Abstract
Background White matter hyperintensities are an important marker of cerebral small vessel disease. This disease burden is commonly described as hyperintense areas in the cerebral white matter, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging data. Studies have demonstrated associations with various cognitive impairments, neurological diseases, and neuropathologies, as well as clinical and risk factors, such as age, sex, and hypertension. Due to their heterogeneous appearance in location and size, studies have started to investigate spatial distributions and patterns, beyond summarizing this cerebrovascular disease burden in a single metric-its volume. Here, we review the evidence of association of white matter hyperintensity spatial patterns with its risk factors and clinical diagnoses. Design/methods We performed a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We used the standards for reporting vascular changes on neuroimaging criteria to construct a search string for literature search on PubMed. Studies written in English from the earliest records available until January 31st, 2023, were eligible for inclusion if they reported on spatial patterns of white matter hyperintensities of presumed vascular origin. Results A total of 380 studies were identified by the initial literature search, of which 41 studies satisfied the inclusion criteria. These studies included cohorts based on mild cognitive impairment (15/41), Alzheimer's disease (14/41), Dementia (5/41), Parkinson's disease (3/41), and subjective cognitive decline (2/41). Additionally, 6 of 41 studies investigated cognitively normal, older cohorts, two of which were population-based, or other clinical findings such as acute ischemic stroke or reduced cardiac output. Cohorts ranged from 32 to 882 patients/participants [median cohort size 191.5 and 51.6% female (range: 17.9-81.3%)]. The studies included in this review have identified spatial heterogeneity of WMHs with various impairments, diseases, and pathologies as well as with sex and (cerebro)vascular risk factors. Conclusion The results show that studying white matter hyperintensities on a more granular level might give a deeper understanding of the underlying neuropathology and their effects. This motivates further studies examining the spatial patterns of white matter hyperintensities.
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Affiliation(s)
- Jonas Botz
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
| | - Valerie Lohner
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Markus D. Schirmer
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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da Silva PHR, de Leeuw FE, Zotin MCZ, Neto OMP, Leoni RF, Tuladhar AM. Neural Substrates of Psychomotor Speed Deficits in Cerebral Small Vessel Disease: A Brain Disconnectome Mapping Study. Brain Topogr 2023:10.1007/s10548-023-00961-0. [PMID: 37156893 DOI: 10.1007/s10548-023-00961-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/11/2023] [Indexed: 05/10/2023]
Abstract
It remains unknown which factors influence how brain disconnectivity derived from White Matter Hyperintensity (WMH) lesions leads to psychomotor speed dysfunction, one of the earliest and most common cognitive manifestations in the cerebral Small Vessel Disease (cSVD) population. While the burden of WMH has been strongly linked to psychomotor speed performance, the effect that different locations and volumes of WMH may have on cSVD-related cognitive impairment remains unclear. Therefore, we aimed to explore (1) whether global WMH, deep WMH (DWMH), and periventricular (PVWMH) volumes display different psychomotor speed associations; (2) whether tract-specific WMH volume shows stronger cognitive associations compared with global measures of WMH volume; (3) whether specific patterns of WMH location lead to different degrees of disconnectivity. Using the BCBToolkit, we investigated which pattern of distribution and which locations of WMH lesion result in impaired psychomotor speed in a well-characterized sample (n = 195) of cSVD patients without dementia. Two key findings emerge from our study. First, global (and not tract-specific) measures of WMH volume were associated with psychomotor speed performance. Second, disconnection maps revealed the involvement of callosal tracts, association and projection fibers, and frontal and parietal cortical brain areas related to psychomotor speed, while the lesion location influenced such associations. In conclusion, psychomotor deficits are affected differently by WMH burden and topographic distribution through brain disconnection in non-demented cSVD patients.
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Affiliation(s)
| | - Frank-Erik de Leeuw
- Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Maria Clara Zanon Zotin
- Department of Neurology, J. Philip Kistler Stroke Research Center, MGH, Boston, MA, USA
- Department of Medical Imaging, Hematology and Clinical Oncology, Ribeirão Preto Medical School, Ribeirão Preto, Brazil
| | - Octavio Marques Pontes Neto
- Department of Neurosciences and Behavioural Sciences, Hospital das Clínicas - Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | | | - Anil M Tuladhar
- Department of Neurology (A.M.T, Donders Center for Medical Neuroscience, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
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35
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Cho J, Jang H, Noh Y, Lee SK, Koh SB, Kim SY, Kim C. Associations of Particulate Matter Exposures With Brain Gray Matter Thickness and White Matter Hyperintensities: Effect Modification by Low-Grade Chronic Inflammation. J Korean Med Sci 2023; 38:e159. [PMID: 37096314 PMCID: PMC10125794 DOI: 10.3346/jkms.2023.38.e159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 03/13/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Numerous studies have shown the effect of particulate matter exposure on brain imaging markers. However, little evidence exists about whether the effect differs by the level of low-grade chronic systemic inflammation. We investigated whether the level of c-reactive protein (CRP, a marker of systemic inflammation) modifies the associations of particulate matter exposures with brain cortical gray matter thickness and white matter hyperintensities (WMH). METHODS We conducted a cross-sectional study of baseline data from a prospective cohort study including adults with no dementia or stroke. Long-term concentrations of particulate matter ≤ 10 µm in diameter (PM10) and ≤ 2.5 µm (PM2.5) at each participant's home address were estimated. Global cortical thickness (n = 874) and WMH volumes (n = 397) were estimated from brain magnetic resonance images. We built linear and logistic regression models for cortical thickness and WMH volumes (higher versus lower than median), respectively. Significance of difference in the association between the CRP group (higher versus lower than median) was expressed as P for interaction. RESULTS Particulate matter exposures were significantly associated with a reduced global cortical thickness only in the higher CRP group among men (P for interaction = 0.015 for PM10 and 0.006 for PM2.5). A 10 μg/m3 increase in PM10 was associated with the higher volumes of total WMH (odds ratio, 1.78; 95% confidence interval, 1.07-2.97) and periventricular WMH (2.00; 1.20-3.33). A 1 μg/m3 increase in PM2.5 was associated with the higher volume of periventricular WMH (odds ratio, 1.66; 95% confidence interval, 1.08-2.56). These associations did not significantly differ by the level of high sensitivity CRP. CONCLUSION Particulate matter exposures were associated with a reduced global cortical thickness in men with a high level of chronic inflammation. Men with a high level of chronic inflammation may be susceptible to cortical atrophy attributable to particulate matter exposures.
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Affiliation(s)
- Jaelim Cho
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea
| | - Heeseon Jang
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Young Noh
- Department of Neurology, Gachon University Gil Medical Center, Incheon, Korea
| | - Seung-Koo Lee
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang-Baek Koh
- Department of Occupational and Environmental Medicine, Wonju Severance Christian Hospital, Wonju College of Medicine, Yonsei University, Wonju, Korea
| | - Sun-Young Kim
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Changsoo Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea
- Institute of Human Complexity and Systems Science, Yonsei University, Incheon, Korea.
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Carvalho de Abreu DC, Pieruccini-Faria F, Sarquis-Adamson Y, Black A, Fraser J, Van Ooteghem K, Cornish B, Grimes D, Jog M, Masellis M, Steeves T, Nanayakkara N, Ramirez J, Scott C, Holmes M, Ozzoude M, Berezuk C, Symons S, Mohammad Hassan Haddad S, Arnott SR, Binns M, Strother S, Beaton D, Sunderland K, Theyers A, Tan B, Zamyadi M, Levine B, Orange JB, Roberts AC, Lou W, Sujanthan S, Breen DP, Marras C, Kwan D, Adamo S, Peltsch A, Troyer AK, Black SE, McLaughlin PM, Lang AE, McIlroy W, Bartha R, Montero-Odasso M. White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative. Eur J Neurol 2023; 30:920-933. [PMID: 36692250 DOI: 10.1111/ene.15692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 12/29/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND AND PURPOSE The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years. METHODS Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale. RESULTS Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline. CONCLUSION White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.
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Affiliation(s)
- Daniela Cristina Carvalho de Abreu
- Gait and Brain Lab, Division of Geriatric Medicine, and Lawson Health Research Institute, Parkwood Institute, University of Western Ontario, Ontario, London, Canada
- Department of Physical Therapy, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Frederico Pieruccini-Faria
- Gait and Brain Lab, Division of Geriatric Medicine, and Lawson Health Research Institute, Parkwood Institute, University of Western Ontario, Ontario, London, Canada
- Gait and Brain Laboratory, Lawson Health Research Institute, London, Ontario, Canada
| | | | - Alanna Black
- Gait and Brain Laboratory, Lawson Health Research Institute, London, Ontario, Canada
| | - Julia Fraser
- Neuroscience, Mobility and Balance Laboratory, Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - Karen Van Ooteghem
- Neuroscience, Mobility and Balance Laboratory, Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - Benjamin Cornish
- Neuroscience, Mobility and Balance Laboratory, Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - David Grimes
- Department of Medicine (Neurology), Ottawa Hospital Research Institute, University of Ottawa Brain and Mind Research Institute, Ottawa, Ontario, Canada
| | - Mandar Jog
- Division of Neurology, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Mario Masellis
- Cognitive and Movement Disorders Clinic, Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Thomas Steeves
- Division of Neurology, Department of Medicine, St Michael's Hospital and University of Toronto, Toronto, Ontario, Canada
| | - Nuwan Nanayakkara
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Christopher Scott
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Melissa Holmes
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Miracle Ozzoude
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Courtney Berezuk
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | - Sean Symons
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | | | - Stephen R Arnott
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Malcolm Binns
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Stephen Strother
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Derek Beaton
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Kelly Sunderland
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Athena Theyers
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Brian Tan
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Brian Levine
- Rotman Research Institute at Baycrest Hospital University of Toronto, Toronto, Ontario, Canada
| | - Joseph B Orange
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Canadian Centre for Activity and Aging, Western University, London, Ontario, Canada
| | - Angela C Roberts
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Canadian Centre for Activity and Aging, Western University, London, Ontario, Canada
- Department of Computer Science, Western University, London, Ontario, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Sujeevini Sujanthan
- Department of Ophthalmology and Visual Sciences, Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Connie Marras
- Edmond J Safra Program in Parkinson's Disease, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada
| | - Sabrina Adamo
- Graduate Department of Psychological Clinical Science, University of Toronto Scarborough, Toronto, Ontario, Canada
| | - Alicia Peltsch
- Faculty of Engineering and Applied Science, Queen's University, Kingston, Ontario, Canada
| | - Angela K Troyer
- Neuropsychology and Cognitive Health Program, Baycrest Health Sciences, Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Sandra E Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology), Sunnybrook Research Institute, Sunnybrook HSC, University of Toronto, Toronto, Ontario, Canada
| | | | - Anthony E Lang
- Division of Neurology, Department of Medicine, Edmond J Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
| | - William McIlroy
- Neuroscience, Mobility and Balance Laboratory, Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Robarts Research Institute, Western University, London, Canada
| | | | - Manuel Montero-Odasso
- Gait and Brain Lab, Division of Geriatric Medicine, and Lawson Health Research Institute, Parkwood Institute, University of Western Ontario, Ontario, London, Canada
- Gait and Brain Laboratory, Lawson Health Research Institute, London, Ontario, Canada
- Division of Geriatric Medicine, Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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Li Z, Wang W, Sang F, Zhang Z, Li X. White matter changes underlie hypertension-related cognitive decline in older adults. Neuroimage Clin 2023; 38:103389. [PMID: 37004321 PMCID: PMC10102561 DOI: 10.1016/j.nicl.2023.103389] [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: 02/03/2023] [Revised: 03/18/2023] [Accepted: 03/25/2023] [Indexed: 03/31/2023]
Abstract
Hypertension has been well recognized as a risk factor for cognitive impairment and dementia. Although the underlying mechanisms of hypertension-affected cognitive deterioration are not fully understood, white matter changes (WMCs) seem to play an important role. WMCs include low microstructural integrity and subsequent white matter macrostructural lesions, which are common on brain imaging in hypertensive patients and are critical for multiple cognitive domains. This article provides an overview of the impact of hypertension on white matter microstructural and macrostructural changes and its link to cognitive dysfunction. Hypertension may induce microstructural changes in white matter, especially for the long-range fibers such as anterior thalamic radiation (ATR) and inferior fronto-occipital fasciculus (IFOF), and then macrostructural abnormalities affecting different lobes, especially the periventricular area. Different regions' WMCs would further exert different effects to specific cognitive domains and accelerate brain aging. As a modifiable risk factor, hypertension might provide a new perspective for alleviating and delaying cognitive impairment.
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Affiliation(s)
- Zilin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Wenxiao Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China.
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38
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Yu MC, Chuang YF, Wu SC, Ho CF, Liu YC, Chou CJ. White matter hyperintensities in cholinergic pathways are associated with dementia severity in e4 carriers but not in non-carriers. Front Neurol 2023; 14:1100322. [PMID: 36864910 PMCID: PMC9971995 DOI: 10.3389/fneur.2023.1100322] [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: 11/16/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
Background and objectives Among individuals with Alzheimer's disease (AD), APOE e4 carriers with increased white matter hyperintensities (WMHs) may selectively be at increased risk of cognitive impairment. Given that the cholinergic system plays a crucial role in cognitive impairment, this study aimed to identify how APOE status modulates the associations between dementia severity and white matter hyperintensities in cholinergic pathways. Methods From 2018 to 2022, we recruited participants (APOE e4 carriers, n = 49; non-carriers, n = 117) from the memory clinic of Cardinal Tien Hospital, Taipei, Taiwan. Participants underwent brain MRI, neuropsychological testing, and APOE genotyping. In this study, we applied the visual rating scale of the Cholinergic Pathways Hyperintensities Scale (CHIPS) to evaluate WMHs in cholinergic pathways compared with the Fazekas scale. Multiple regression was used to assess the influence of CHIPS score and APOE carrier status on dementia severity based on Clinical Dementia Rating-Sum of Boxes (CDR-SB). Results After adjusting for age, education and sex, higher CHIPS scores tended to be associated with higher CDR-SB in APOE e4 carriers but not in the non-carrier group. Conclusions Carriers and non-carriers present distinct associations between dementia severity and WMHs in cholinergic pathways. In APOE e4 carriers, increased white matter in cholinergic pathways are associated with greater dementia severity. In non-carriers, WMHs exhibit less predictive roles for clinical dementia severity. WMHs on the cholinergic pathway may have a different impact on APOE e4 carriers vs. non-carriers.
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Affiliation(s)
- Ming-Chun Yu
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taiwan
| | - Yi-Fang Chuang
- Institute of Public Health, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - Shu-Ching Wu
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taiwan
| | - Cheng-Feng Ho
- Department of Radiology, Cardinal Tien Hospital, New Taipei City, Taiwan
| | - Yi-Chien Liu
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taiwan,Medical School of Fu-Jen University, New Taipei City, Taiwan,Geriatric Behavioral Neurology Project, Tohoku University New Industry Hatchery Center (NICHe), Sendai, Japan,*Correspondence: Yi-Chien Liu ✉
| | - Chia-Ju Chou
- Department of Neurology, Cardinal Tien Hospital, New Taipei City, Taiwan
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39
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Jacob MA, Cai M, Bergkamp M, Darweesh SKL, Gelissen LMY, Marques J, Norris DG, Duering M, Esselink RAJ, Tuladhar AM, de Leeuw FE. Cerebral Small Vessel Disease Progression Increases Risk of Incident Parkinsonism. Ann Neurol 2023; 93:1130-1141. [PMID: 36762437 DOI: 10.1002/ana.26615] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 02/05/2023] [Accepted: 02/08/2023] [Indexed: 02/11/2023]
Abstract
OBJECTIVE Cerebral small vessel disease (SVD) is associated with motor impairments and parkinsonian signs cross-sectionally, however, there are little longitudinal data on whether SVD increases risk of incident parkinsonism itself. We investigated the relation between baseline SVD severity as well as SVD progression, and incident parkinsonism over a follow-up of 14 years. METHODS This study included 503 participants with SVD, and without parkinsonism at baseline, from the RUN DMC prospective cohort study. Baseline inclusion was performed in 2006 and follow-up took place in 2011, 2015, and 2020, including magnetic resonance imaging (MRI) and motor assessments. Parkinsonism was diagnosed according to the UK Brain Bank criteria, and stratified into vascular parkinsonism (VaP) and idiopathic Parkinson's disease (IPD). Linear mixed-effect models were constructed to estimate individual rate changes of MRI-characteristics. RESULTS Follow-up for incident parkinsonism was near-complete (99%). In total, 51 (10.2%) participants developed parkinsonism (33 VaP, 17 IPD, and 1 progressive supranuclear palsy). Patients with incident VaP had higher SVD burden compared with patients with IPD. Higher baseline white matter hyperintensities (hazard ratio [HR] = 1.46 per 1-SD increase, 95% confidence interval [CI] = 1.21-1.78), peak width of skeletonized mean diffusivity (HR = 1.66 per 1-SD increase, 95% CI = 1.34-2.05), and presence of lacunes (HR = 1.84, 95% CI = 0.99-3.42) were associated with increased risk of all-cause parkinsonism. Incident lacunes were associated with incident VaP (HR = 4.64, 95% CI = 1.32-16.32). INTERPRETATION Both baseline SVD severity and SVD progression are independently associated with long-term parkinsonism. Our findings indicate a causal role of SVD in parkinsonism. Future studies are needed to examine the underlying pathophysiology of this relation. ANN NEUROL 2023.
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Affiliation(s)
- Mina A Jacob
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mengfei Cai
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Mayra Bergkamp
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sirwan K L Darweesh
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Liza M Y Gelissen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José Marques
- Center for Cognitive Neuroimaging, Cognition and Behaviour, Nijmegen, The Netherlands
| | - David G Norris
- Center for Cognitive Neuroimaging, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Rianne A J Esselink
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anil M Tuladhar
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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40
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Association between White Matter Hyperintensities Burden and Cognitive Function in Adult Asymptomatic Moyamoya Disease. J Clin Med 2023; 12:jcm12031143. [PMID: 36769790 PMCID: PMC9917657 DOI: 10.3390/jcm12031143] [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: 12/09/2022] [Revised: 12/31/2022] [Accepted: 01/12/2023] [Indexed: 02/04/2023] Open
Abstract
Background and Purpose: White matter hyperintensities (WMH) caused by chronic cerebral hypoperfusion are common in Moyamoya disease (MMD) patients, but WMH burden with comprehensive cognition in adult asymptomatic MMD remains unknown. This study tried to investigate the association between the WMH burden and cognitive function in adult asymptomatic MMD. Methods: Sixty-four adult asymptomatic MMD patients without surgical revascularization were enrolled in this study and underwent a 3T MRI scan and complete cognitive tests from 2021 to 2022. WMH volume was extracted with brain anatomical analysis using the diffeomorphic deformation (BAAD) toolbox, which works on SPM 12 software. Multivariable linear regression analysis was performed to assess the association between WMH burden and cognitive function in asymptomatic MMD. Results: Firstly, our data showed that lower education levels and higher WMH burden were strongly related to global cognitive impairment after adjusting for other variables. Secondly, WMH severity was significantly associated with several domains of neurocognitive function, including memory, semantic memory, and executive function. Finally, when stratified by sex, the female participants with WMH severity had lower cognitive performance in all areas than male participants. Conclusions: These results suggest that WMH burden was highly correlated with global cognition, memory, semantic memory, and executive function in asymptomatic MMD. Especially in female participants, the relationship became more evident.
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41
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Dong Y, Li Y, Liu K, Han X, Liu R, Ren Y, Cong L, Zhang Q, Hou T, Song L, Tang S, Shi L, Luo Y, Kalpouzos G, Laukka EJ, Winblad B, Wang Y, Du Y, Qiu C. Anosmia, mild cognitive impairment, and biomarkers of brain aging in older adults. Alzheimers Dement 2023; 19:589-601. [PMID: 36341691 DOI: 10.1002/alz.12777] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/14/2022] [Accepted: 07/21/2022] [Indexed: 11/10/2022]
Abstract
Olfactory impairment is a potential marker for prodromal dementia, but the underlying mechanisms are poorly understood. This population-based study included 4214 dementia-free participants (age ≥65 years). Olfaction was assessed using the 16-item Sniffin' Sticks identification test. In the subsamples, we measured plasma amyloid beta (Aβ)40, Aβ42, total tau, and neurofilament light chain (NfL; n = 1054); and quantified hippocampal, entorhinal cortex, and white matter hyperintensity (WMH) volumes, and Alzheimer's disease (AD)-signature cortical thickness (n = 917). Data were analyzed with logistic and linear regression models. In the total sample, mild cognitive impairment (MCI) was diagnosed in 1102 persons (26.2%; amnestic MCI, n = 931; non-amnestic MCI, n = 171). Olfactory impairment was significantly associated with increased likelihoods of MCI, amnestic MCI, and non-amnestic MCI. In the subsamples, anosmia was significantly associated with higher plasma total tau and NfL concentrations, smaller hippocampal and entorhinal cortex volumes, and greater WMH volume, and marginally with lower AD-signature cortical thickness. These results suggest that cerebral neurodegenerative and microvascular lesions are common neuropathologies linking anosmia with MCI in older adults.
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Affiliation(s)
- Yi Dong
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Yuanjing Li
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Keke Liu
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Xiaolei Han
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Rui Liu
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Yifei Ren
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Qinghua Zhang
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, China.,Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yishan Luo
- BrainNow Research Institute, Shenzhen, China
| | - Grégoria Kalpouzos
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Erika J Laukka
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Bengt Winblad
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China.,Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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Kuroda T, Ono K, Honma M, Asano M, Mori Y, Futamura A, Yano S, Kanemoto M, Hieda S, Baba Y, Izumizaki M, Murakami H. Cerebral white matter lesions and regional blood flow are associated with reduced cognitive function in early-stage cognitive impairment. Front Aging Neurosci 2023; 15:1126618. [PMID: 36875693 PMCID: PMC9978183 DOI: 10.3389/fnagi.2023.1126618] [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: 12/18/2022] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
Background Differences in the extent of cerebral white matter lesions (WML) and regional cerebral blood flow (rCBF) in early-stage cognitive impairment (ESCI) contribute to the prognosis of cognitive decline; however, it is unclear precisely how WML and rCBF affect cognitive decline in ESCI. Objective We examined the association between WML, rCBF, and cognitive impairment in the ESCI, using path analysis to clarify how these variables affect each other. Methods Eighty-three patients who consulted our memory clinic regarding memory loss were included in this study based on the Clinical Dementia Rating. Participants underwent the Mini-Mental State Examination (MMSE), brain magnetic resonance imaging (MRI) for voxel-based morphometry analysis, and brain perfusion single-photon emission computed tomography (SPECT) for rCBF evaluation in cortical regions, using 3D stereotactic surface projection (3D-SSP) analysis. Results Path analysis was performed on the MRI voxel-based morphometry and SPECT 3D-SSP data, showing a significant correlation between both and MMSE scores. In the most suitable model (GFI = 0.957), correlations were observed between lateral ventricular (LV-V) and periventricular WML (PvWML-V) volumes [standardized coefficient (SC) = 0.326, p = 0.005], LV-V and rCBF of the anterior cingulate gyrus (ACG-rCBF; SC = 0.395, p < 0.0001), and ACG-rCBF and PvWML-V (SC = 0.231, p = 0.041). Furthermore, a direct relationship between PvWML-V and MMSE scores was identified (SC = -0.238, p = 0.026). Conclusion Significant interrelationships were observed among the LV-V, PvWML-V, and ACG-rCBF that directly affected the MMSE score in the ESCI. The mechanisms behind these interactions and the impact of PvWML-V on cognitive function require further investigation.
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Affiliation(s)
- Takeshi Kuroda
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Kenjiro Ono
- Department of Neurology, Kanazawa University Graduate School of Medical Sciences, Kanazawa, Japan
| | - Motoyasu Honma
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
| | - Miki Asano
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Yukiko Mori
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Akinori Futamura
- Department of Neurology, Showa University Fujigaoka Hospital, Kanagawa, Japan
| | - Satoshi Yano
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Mizuki Kanemoto
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Sotaro Hieda
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
| | - Yasuhiko Baba
- Department of Neurology, Showa University Fujigaoka Hospital, Kanagawa, Japan
| | - Masahiko Izumizaki
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
| | - Hidetomo Murakami
- Department of Neurology, Showa University School of Medicine, Tokyo, Japan
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Newton P, Tchounguen J, Pettigrew C, Lim C, Lin Z, Lu H, Moghekar A, Albert M, Soldan A. Regional White Matter Hyperintensities and Alzheimer's Disease Biomarkers Among Older Adults with Normal Cognition and Mild Cognitive Impairment. J Alzheimers Dis 2023; 92:323-339. [PMID: 36744337 PMCID: PMC10041440 DOI: 10.3233/jad-220846] [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] [Accepted: 12/29/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) frequently co-occurs with other brain pathologies. Recent studies suggest there may be a mechanistic link between AD and small vessel cerebrovascular disease (CVD), as opposed to simply the overlap of two disorders. OBJECTIVE We investigated the cross-sectional relationship between white matter hyperintensity (WMH) volumes (markers of CVD) and cerebrospinal fluid (CSF) biomarkers of AD. METHODS WMH volumes were assessed globally and regionally (i.e., frontal, parietal, temporal, occipital, and limbic). CSF AD biomarkers (i.e., Aβ 40, Aβ 42, Aβ 42/Aβ 40 ratio, phosphorylated tau-181 [p-tau181], and total tau [t-tau]) were measured among 152 non-demented individuals (134 cognitively unimpaired and 18 with mild cognitive impairment (MCI)). RESULTS Linear regression models showed that among all subjects, higher temporal WHM volumes were associated with AD biomarkers (higher levels of p-tau181, t-tau, and Aβ 40), particularly among APOE ɛ 4 carriers (independent of Aβ 42 levels). Higher vascular risk scores were associated with greater parietal and frontal WMH volumes (independent of CSF AD biomarker levels). Among subjects with MCI only, parietal WMH volumes were associated with a lower level of Aβ 42/Aβ 40. In addition, there was an association between higher global WMH volumes and higher CSF t-tau levels among younger participants versus older ones (∼<65 versus 65+ years), independent of Aβ 42/Aβ 40 and p-tau181. CONCLUSION These findings suggest that although WMH are primarily related to systemic vascular risk and neurodegeneration (i.e., t-tau), AD-specific pathways may contribute to the formation of WMH in a regionally-specific manner, with neurofibrillary tangles (i.e., p-tau) playing a role in temporal WMHs and amyloid (i.e., Aβ 42/Aβ 40) in parietal WMHs.
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Affiliation(s)
- Princess Newton
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | | | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chantelle Lim
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Zixuan Lin
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Abhay Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - the BIOCARD Research Team
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
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44
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Zhang Z, Li S, Wang S. Application of Periventricular White Matter Hyperintensities Combined with Homocysteine into Predicting Mild Cognitive Impairment in Parkinson's Disease. Int J Gen Med 2023; 16:785-792. [PMID: 36879618 PMCID: PMC9985451 DOI: 10.2147/ijgm.s399307] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/21/2023] [Indexed: 03/05/2023] Open
Abstract
Purpose To verify the associations between white matter hyperintensities (WMHs), plasma homocysteine (Hcy) levels, and mild cognitive impairment (MCI) in Parkinson's disease (PD) patients and evaluate the predictive value of combination of WMHs and plasma Hcy levels for MCI. Patients and methods In this study, 387 patients with PD were divided into MCI group and non-MCI group. Their cognition was evaluated with a comprehensive neuropsychological evaluation including 10 tests. Five cognitive domains, including the memory, attention/working memory, visuospatial, executive and language domains, were evaluated using two tests for each domain. MCI was determined when at least two tests demonstrated abnormal results, either one impaired test in two different cognitive domains or two impaired tests in a single cognitive domain. Multivariate analysis was performed to determine risk factors for MCI in PD patients. The receiver operating characteristic (ROC) curve was employed to assess the predictive values, and the Z test was employed to compare the area under curve (AUC). Results MCI was identified in 195 PD patients with an incidence of 50.4%. Multivariate analysis results showed that PWMHs (OR: 5.162, 95% CI: 2.318~9.527), Hcy levels (OR: 1.189, 95% CI: 1.071~1.405) and MDS-UPDRS part III score (OR: 1.173, 95% CI: 1.062~1.394) were independently correlated with MCI in PD patients after adjusting for confounders. ROC curves showed that the AUCs of PWMHs, Hcy levels and their combination were 0.701 (SE: 0.026, 95% CI: 0.647~0.752), 0.688 (SE: 0.027, 95% CI: 0.635~0.742) and 0.879 (SE: 0.018, 95% CI: 0.844~0.915), respectively. Z test showed that the AUC of combination prediction was significantly higher than those of individual predictions (0.879 vs 0.701, Z=5.629, P<0.001; 0.879 vs 0.688, Z=5.886, P<0.001). Conclusion The combination of WMHs and plasma Hcy levels could be applied in the prediction of MCI in PD patients.
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Affiliation(s)
- Zuowen Zhang
- Department of Neurology, Chongqing University Jiangjin Hospital, Chongqing, People's Republic of China
| | - Shishuang Li
- Department of Neurology, Chongqing University Jiangjin Hospital, Chongqing, People's Republic of China
| | - Shumei Wang
- College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, People's Republic of China
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White Matter Lesions Predominantly Located in Deep White Matter Represent Embolic Etiology Rather Than Small Vessel Disease. Dement Neurocogn Disord 2023; 22:28-42. [PMID: 36814699 PMCID: PMC9939570 DOI: 10.12779/dnd.2023.22.1.28] [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: 10/13/2022] [Revised: 01/15/2023] [Accepted: 01/28/2023] [Indexed: 02/17/2023] Open
Abstract
Background and Purpose We investigated the correlation between the deep distribution of white matter hyperintensity (WMH) (dWMH: WMH in deep and corticomedullary areas, with minimal periventricular WMH) and a positive agitated saline contrast echocardiography result. Methods We retrospectively recruited participants with comprehensive dementia evaluations, an agitated saline study, and brain imaging. The participants were classified into two groups according to WMH-distributions: dWMH and dpWMH (mainly periventricular WMH with or without deep WMH.) We hypothesized that dWMH is more likely associated with embolism, whereas dpWMH is associated with small-vessel diseases. We compared the clinical characteristics, WMH-distributions, and positive rate of agitated saline studies between the two groups. Results Among 90 participants, 27 and 12 met the dWMH and dpWMH criteria, respectively. The dWMH-group was younger (62.2±7.5 vs. 78.9±7.3, p<0.001) and had a lower prevalence of hypertension (29.6% vs. 75%, p=0.008), diabetes mellitus (3.7% vs. 25%, p=0.043), and hyperlipidemia (33.3% vs. 83.3%, p=0.043) than the dpWMH-group. Regarding deep white matter lesions, the number of small lesions (<3 mm) was higher in the dWMH-group(10.9±9.7) than in the dpWMH-group (3.1±6.4) (p=0.008), and WMH was predominantly distributed in the border-zones and corticomedullary areas. Most importantly, the positive agitated saline study rate was higher in the dWMH-group than in the dpWMH-group (81.5% vs. 33.3%, p=0.003). Conclusions The dWMH-group with younger participants had fewer cardiovascular risk factors, showed more border-zone-distributions, and had a higher agitated saline test positivity rate than the dpWMH-group, indicating that corticomedullary or deep WMH-distribution with minimal periventricular WMH suggests embolic etiologies.
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Hormonal factors moderate the associations between vascular risk factors and white matter hyperintensities. Brain Imaging Behav 2022; 17:172-184. [PMID: 36542288 DOI: 10.1007/s11682-022-00751-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/27/2022] [Indexed: 12/24/2022]
Abstract
To examine the moderation effects of hormonal factors on the associations between vascular risk factors and white matter hyperintensities in men and women, separately. White matter hyperintensities were automatically segmented and quantified in the UK Biobank dataset (N = 18,294). Generalised linear models were applied to examine (1) the main effects of vascular and hormonal factors on white matter hyperintensities, and (2) the moderation effects of hormonal factors on the relationship between vascular risk factors and white matter hyperintensities volumes. In men with testosterone levels one standard deviation higher than the mean value, smoking was associated with 27.8% higher white matter hyperintensities volumes in the whole brain. In women with a shorter post-menopause duration (one standard deviation below the mean), diabetes and higher pulse wave velocity were associated with 28.8% and 2.0% more deep white matter hyperintensities, respectively. These findings highlighted the importance of considering hormonal risk factors in the prevention and management of white matter hyperintensities.
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Rimmele DL, Petersen EL, Schlemm E, Kessner SS, Petersen M, Mayer C, Cheng B, Zeller T, Waldeyer C, Behrendt CA, Gerloff C, Thomalla G. Association of Carotid Plaque and Flow Velocity With White Matter Integrity in a Middle-aged to Elderly Population. Neurology 2022; 99:e2699-e2707. [PMID: 36123124 DOI: 10.1212/wnl.0000000000201297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/10/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES It is uncertain whether there is an association of carotid plaques (CPs) and flow velocities with peak width mean diffusivity (PSMD) and white matter hyperintensities (WMH) independent of shared risk factors. We aimed to study this association controlling for biomarkers of inflammation and cardiac dysfunction and typical cardiovascular risk factors and spatial distribution. METHODS We included participants from the population-based Hamburg City Health Study, recruiting citizens between 45 and 74 years of age. Medical history was obtained from structured interviews and extended laboratory tests, physical examinations, MRI of the head, echocardiography, and abdominal and carotid ultrasound were performed. We performed multivariable regression analysis with PSMD and periventricular, deep, and total volume of WMH (pWMH, dWMH, tWMH) as dependent variables. PSMD was calculated as the difference between the 95th and 5th percentiles of MD values on the white skeleton in standard space. Volumes of WMH were determined by the application of a manually trained k-nearest neighbor segmentation algorithm. WMH measured within a distance of 1 cm from the surface of the lateral ventricles were defined as pWMH and above 1 cm as dWMH. RESULTS Two thousand six hundred twenty-three participants were included. The median age was 65 years, and 56% were women. Their median tWMH was 946 mm3(IQR:419, 2,164), PSMD 2.24 mm2/s × 10-4 (IQR: 2.04, 2.47), peak systolic velocity (PSV) of internal carotid arteries 0.70m/second (IQR:0.60, 0.81), and 35% had CPs. Adjusted for age, sex, high-sensitive CRP, NT-proBNP, and commonly measured cardiovascular risk and systemic hemodynamic factors, both CPs (B = 0.15; CI: 0.04, 0.26; p = 0.006) and low PSV (B = -0.49; CI: -0.87, -0.11; p = 0.012) were significantly associated with a higher tWMH and PSMD. Low PSV (B = -0.48; CI: -0.87, -0.1; p = 0.013) was associated with pWMH and the presence of CP with pWMH (B = 0.15; CI: 0.04, 0.26; p = 0.008) and dWMH (B = 0.42; CI: 0.11, 0.74; p < 0.009). DISCUSSION Low PSV and CP are associated with WMH and PSMD independent of cardiovascular risk factors and biomarkers of inflammation and cardiac dysfunction. This points toward pathophysiologic pathways underlying both large and small vessel disease beyond the common cardiovascular risk profile. TRIAL REGISTRATION INFORMATION The trial was submitted at clinicaltrials.gov, under NCT03934957 on January 4, 2019. The first participant was enrolled in February 2016.
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Affiliation(s)
- David Leander Rimmele
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany.
| | - Elina Larissa Petersen
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Eckhard Schlemm
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Simon S Kessner
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Marvin Petersen
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Carola Mayer
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Bastian Cheng
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Tanja Zeller
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Christoph Waldeyer
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Christian-Alexander Behrendt
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Christian Gerloff
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
| | - Götz Thomalla
- From the Department of Neurology (D.L.R., E.S., S.S.K., M.P., C.M., B.C., C.G., G.T.) and Epidemiological Study Center (E.L.P.), University Medical Center Hamburg-Eppendorf, Hamburg; Departments of Cardiology (T.Z., C.W.) and Vascular Medicine (C.-A.B.), University Heart and Vascular Center UKE Hamburg; and German Center for Cardiovascular Research (DZHK) Partner Site Hamburg/Kiel/Lübeck (T.Z., C.W.), Germany
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Phuah CL, Chen Y, Strain JF, Yechoor N, Laurido-Soto OJ, Ances BM, Lee JM. Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies. Neurology 2022; 99:e2535-e2547. [PMID: 36123127 PMCID: PMC9754646 DOI: 10.1212/wnl.0000000000201186] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-β PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into 5 unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathologic process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.
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Affiliation(s)
- Chia-Ling Phuah
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Yasheng Chen
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jeremy F Strain
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Nirupama Yechoor
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Osvaldo J Laurido-Soto
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Beau M Ances
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jin-Moo Lee
- From the Department of Neurology (C.-L.P., Y.C., J.F.S., N.Y., O.J.L.-S., B.M.A., J.-M.L.), Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, MO; NeuroGenomics and Informatics Center (C.-L.P.), Washington University School of Medicine, St. Louis, MO; Mallinckrodt Institute of Radiology (J.-M.L.), Washington University School of Medicine, St. Louis, MO; and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO.
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Griffanti L, Gillis G, O'Donoghue MC, Blane J, Pretorius PM, Mitchell R, Aikin N, Lindsay K, Campbell J, Semple J, Alfaro-Almagro F, Smith SM, Miller KL, Martos L, Raymont V, Mackay CE. Adapting UK Biobank imaging for use in a routine memory clinic setting: The Oxford Brain Health Clinic. Neuroimage Clin 2022; 36:103273. [PMID: 36451375 PMCID: PMC9723313 DOI: 10.1016/j.nicl.2022.103273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/24/2022] [Accepted: 11/20/2022] [Indexed: 11/23/2022]
Abstract
The Oxford Brain Health Clinic (BHC) is a joint clinical-research service that provides memory clinic patients and clinicians access to high-quality assessments not routinely available, including brain MRI aligned with the UK Biobank imaging study (UKB). In this work we present how we 1) adapted the UKB MRI acquisition protocol to be suitable for memory clinic patients, 2) modified the imaging analysis pipeline to extract measures that are in line with radiology reports and 3) explored the alignment of measures from BHC patients to the largest brain MRI study in the world (ultimately 100,000 participants). Adaptations of the UKB acquisition protocol for BHC patients include dividing the scan into core and optional sequences (i.e., additional imaging modalities) to improve patients' tolerance for the MRI assessment. We adapted the UKB structural MRI analysis pipeline to take into account the characteristics of a memory clinic population (e.g., high amount of white matter hyperintensities and hippocampal atrophy). We then compared the imaging derived phenotypes (IDPs) extracted from the structural scans to visual ratings from radiology reports, non-imaging factors (age, cognition) and to reference distributions derived from UKB data. Of the first 108 BHC attendees (August 2020-November 2021), 92.5 % completed the clinical scans, 88.0 % consented to use of data for research, and 43.5 % completed the additional research sequences, demonstrating that the protocol is well tolerated. The high rates of consent to research makes this a valuable real-world quality research dataset routinely captured in a clinical service. Modified tissue-type segmentation with lesion masking greatly improved grey matter volume estimation. CSF-masking marginally improved hippocampal segmentation. The IDPs were in line with radiology reports and showed significant associations with age and cognitive performance, in line with the literature. Due to the age difference between memory clinic patients of the BHC (age range 65-101 years, average 78.3 years) and UKB participants (44-82 years, average 64 years), additional scans on elderly healthy controls are needed to improve reference distributions. Current and future work aims to integrate automated quantitative measures in the radiology reports and evaluate their clinical utility.
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Affiliation(s)
- Ludovica Griffanti
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom.
| | - Grace Gillis
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - M Clare O'Donoghue
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Jasmine Blane
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom
| | - Pieter M Pretorius
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Oxford University Hospitals NHS Trust, Oxford, United Kingdom
| | | | - Nicola Aikin
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Karen Lindsay
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom
| | - Jon Campbell
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Juliet Semple
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Fidel Alfaro-Almagro
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Stephen M Smith
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Karla L Miller
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
| | - Lola Martos
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom
| | - Vanessa Raymont
- Department of Psychiatry, University of Oxford, United Kingdom; Oxford Health NHS Foundation Trust, Oxford, United Kingdom
| | - Clare E Mackay
- Department of Psychiatry, University of Oxford, United Kingdom; Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom
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Association between Serum Amyloid A Level and White Matter Hyperintensity Burden: a Cross-Sectional Analysis in Patients with Acute Ischemic Stroke. Neurol Ther 2022; 12:161-175. [PMID: 36374429 PMCID: PMC9837367 DOI: 10.1007/s40120-022-00415-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022] Open
Abstract
INTRODUCTION This work aimed to determine the potential link between white matter hyperintensity (WMH) burden and serum amyloid A (SAA) level in patients with acute ischemic stroke. METHODS Consecutive patients with acute large artery atherosclerosis (LAA) stroke between April 2021 and May 2022 were included. WMH volumes (periventricular, deep, and total) were measured using the Fazekas score and a semiautomated volumetric analysis on fluid-attenuated inversion recovery-magnetic resonance imaging. The burdens of WMH were scored to assess the dose-dependent association between SAA and WMH volume. Multivariate regression and a two-piecewise linear regression model were used to evaluate whether SAA levels are an independent predictor of WMH, and to discover the threshold effect or saturation effect of SAA levels with respect to WMH volume. RESULTS The mean age of patients was 63.2 ± 11.5 years, with 65.9% men. The median SAA level was 3.93 mg/L and the total WMH volume of 6.86 cm3. In the multivariable analysis, SAA remained an independent predictor of total WMH volume [β = 0.82, 95% confidence interval (CI) = 0.49-1.07, p < 0.001], periventricular WMH volume (adjusted β = 0.76, 95% CI = 0.46-1.07, p < 0.001), and deep WMH volume (adjusted β = 0.26, 95% CI = 0.06-0.45, p = 0.011) after controlling for confounders. Furthermore, SAA levels were associated with periventricular Fazekas score, deep Fazekas score, and Fazekas grades. Threshold effect and saturation effect analyses demonstrated a nonlinear relationship between SAA levels and periventricular white matter hyperintensity (PVWMH) volumes, with SAA levels (2.12-19.89 mg/L) having significant dose-dependent relationships with periventricular WMH volumes (adjusted β = 1.98, 95% CI = 1.12-2.84, p < 0.001). CONCLUSION SAA level ranging from 2.12 to 19.89 mg/L is dose-dependently associated with periventricular WMH development. These findings point the way forward for future research into the pathophysiology of WMH.
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