1
|
Lee H, Lee HH, Ma Y, Eskandarian L, Gaudet K, Tian Q, Krijnen EA, Russo AW, Salat DH, Klawiter EC, Huang SY. Age-related alterations in human cortical microstructure across the lifespan: Insights from high-gradient diffusion MRI. Aging Cell 2024:e14267. [PMID: 39118344 DOI: 10.1111/acel.14267] [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: 03/07/2024] [Revised: 06/16/2024] [Accepted: 06/24/2024] [Indexed: 08/10/2024] Open
Abstract
The human brain undergoes age-related microstructural alterations across the lifespan. Soma and Neurite Density Imaging (SANDI), a novel biophysical model of diffusion MRI, provides estimates of cell body (soma) radius and density, and neurite density in gray matter. The goal of this cross-sectional study was to assess the sensitivity of high-gradient diffusion MRI toward age-related alterations in cortical microstructure across the adult lifespan using SANDI. Seventy-two cognitively unimpaired healthy subjects (ages 19-85 years; 40 females) were scanned on the 3T Connectome MRI scanner with a maximum gradient strength of 300mT/m using a multi-shell diffusion MRI protocol incorporating 8 b-values and diffusion time of 19 ms. Intra-soma signal fraction obtained from SANDI model-fitting to the data was strongly correlated with age in all major cortical lobes (r = -0.69 to -0.60, FDR-p < 0.001). Intra-soma signal fraction (r = 0.48-0.63, FDR-p < 0.001) and soma radius (r = 0.28-0.40, FDR-p < 0.04) were significantly correlated with cortical volume in the prefrontal cortex, frontal, parietal, and temporal lobes. The strength of the relationship between SANDI metrics and age was greater than or comparable to the relationship between cortical volume and age across the cortical regions, particularly in the occipital lobe and anterior cingulate gyrus. In contrast to the SANDI metrics, all associations between diffusion tensor imaging (DTI) and diffusion kurtosis imaging metrics and age were low to moderate. These results suggest that high-gradient diffusion MRI may be more sensitive to underlying substrates of neurodegeneration in the aging brain than DTI and traditional macroscopic measures of neurodegeneration such as cortical volume and thickness.
Collapse
Affiliation(s)
- Hansol Lee
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Hong-Hsi Lee
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Yixin Ma
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Laleh Eskandarian
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Kyla Gaudet
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Qiyuan Tian
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Eva A Krijnen
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Andrew W Russo
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - David H Salat
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| |
Collapse
|
2
|
Jirsaraie RJ, Gatavins MM, Pines AR, Kandala S, Bijsterbosch JD, Marek S, Bogdan R, Barch DM, Sotiras A. Mapping the neurodevelopmental predictors of psychopathology. Mol Psychiatry 2024:10.1038/s41380-024-02682-7. [PMID: 39107582 DOI: 10.1038/s41380-024-02682-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 07/13/2024] [Accepted: 07/22/2024] [Indexed: 08/10/2024]
Abstract
Neuroimaging research has uncovered a multitude of neural abnormalities associated with psychopathology, but few prediction-based studies have been conducted during adolescence, and even fewer used neurobiological features that were extracted across multiple neuroimaging modalities. This gap in the literature is critical, as deriving accurate brain-based models of psychopathology is an essential step towards understanding key neural mechanisms and identifying high-risk individuals. As such, we trained adaptive tree-boosting algorithms on multimodal neuroimaging features from the Lifespan Human Connectome Developmental (HCP-D) sample that contained 956 participants between the ages of 8 to 22 years old. Our feature space consisted of 1037 anatomical, 1090 functional, and 192 diffusion MRI features, which were used to derive models that separately predicted internalizing symptoms, externalizing symptoms, and the general psychopathology factor. We found that multimodal models were the most accurate, but all brain-based models of psychopathology yielded out-of-sample predictions that were weakly correlated with actual symptoms (r2 < 0.15). White matter microstructural properties, including orientation dispersion indices and intracellular volume fractions, were the most predictive of general psychopathology, followed by cortical thickness and functional connectivity. Spatially, the most predictive features of general psychopathology were primarily localized within the default mode and dorsal attention networks. These results were mostly consistent across all dimensions of psychopathology, except orientation dispersion indices and the default mode network were not as heavily weighted in the prediction of internalizing and externalizing symptoms. Taken with prior literature, it appears that neurobiological features are an important part of the equation for predicting psychopathology but relying exclusively on neural markers is clearly not sufficient, especially among adolescent samples with subclinical symptoms. Consequently, risk factor models of psychopathology may benefit from incorporating additional sources of information that have also been shown to explain individual differences, such as psychosocial factors, environmental stressors, and genetic vulnerabilities.
Collapse
Affiliation(s)
- Robert J Jirsaraie
- Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Martins M Gatavins
- Lifespan Brain Institute, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam R Pines
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Sridhar Kandala
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- AI for Health Institute, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Aristeidis Sotiras
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
| |
Collapse
|
3
|
Singh K, Barsoum S, Schilling KG, An Y, Ferrucci L, Benjamini D. Neuronal microstructural changes in the human brain are associated with neurocognitive aging. Aging Cell 2024; 23:e14166. [PMID: 38659245 PMCID: PMC11258428 DOI: 10.1111/acel.14166] [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: 12/18/2023] [Revised: 02/22/2024] [Accepted: 03/19/2024] [Indexed: 04/26/2024] Open
Abstract
Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
Collapse
Affiliation(s)
- Kavita Singh
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Kurt G. Schilling
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Yang An
- Brain Aging and Behavior SectionNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
| |
Collapse
|
4
|
Yu X, Przybelski SA, Reid RI, Lesnick TG, Raghavan S, Graff‐Radford J, Lowe VJ, Kantarci K, Knopman DS, Petersen RC, Jack CR, Vemuri P. NODDI in gray matter is a sensitive marker of aging and early AD changes. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12627. [PMID: 39077685 PMCID: PMC11284641 DOI: 10.1002/dad2.12627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 06/17/2024] [Accepted: 07/02/2024] [Indexed: 07/31/2024]
Abstract
INTRODUCTION Age-related and Alzheimer's disease (AD) dementia-related neurodegeneration impact brain health. While morphometric measures from T1-weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker. METHODS We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography. RESULTS Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age-related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures. DISCUSSION These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD. Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD).Free water fraction has higher sensitivity to normal brain aging.Free water fraction has stronger associations with early AD and regional tau deposition.
Collapse
Affiliation(s)
- Xi Yu
- Department of Physiology and Biomedical EngineeringMayo ClinicRochesterMinnesotaUSA
| | - Scott A. Przybelski
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Robert I. Reid
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Timothy G. Lesnick
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
| | | | | | - Val J. Lowe
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Kejal Kantarci
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - David S. Knopman
- Department of NeurologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | | | - Clifford R. Jack
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | | |
Collapse
|
5
|
Kim T, Rahimpour Jounghani A, Gozdas E, Hosseini SH. Cortical neurite microstructural correlates of time perception in healthy older adults. Heliyon 2024; 10:e32534. [PMID: 38975207 PMCID: PMC11225759 DOI: 10.1016/j.heliyon.2024.e32534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 06/04/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
The human experience is significantly impacted by timing as it structures how information is processed. Nevertheless, the neurological foundation of time perception remains largely unresolved. Understanding cortical microstructure related to timing is crucial for gaining insight into healthy aging and recognizing structural alterations that are typical of neurodegenerative diseases associated with age. Given the importance, this study aimed to determine the brain regions that are accountable for predicting time perception in older adults using microstructural measures of the brain. In this study, elderly healthy adults performed the Time-Wall Estimation task to measure time perception through average error time. We used support vector regression (SVR) analyses to predict the average error time using cortical neurite microstructures derived from orientation dispersion and density imaging based on multi-shell diffusion magnetic resonance imaging (dMRI). We found significant correlations between observed and predicted average error times for neurite arborization (ODI) and free water (FISO). Neurite arborization and free water properties in specific regions in the medial and lateral prefrontal, superior parietal, and medial and lateral temporal lobes were among the most significant predictors of timing ability in older adults. Further, our results revealed that greater branching along with lower free water in cortical structures result in shorter average error times. Future studies should assess whether these same networks are contributing to time perception in older adults with mild cognitive impairment (MCI) and whether degeneration of these networks contribute to early diagnosis or detection of dementia.
Collapse
Affiliation(s)
| | | | - Elveda Gozdas
- C-BRAIN Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1520 Page Mill Rd., Stanford, CA, 94304-5795, United States
| | - S.M. Hadi Hosseini
- C-BRAIN Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1520 Page Mill Rd., Stanford, CA, 94304-5795, United States
| |
Collapse
|
6
|
Brown C, Das S, Xie L, Nasrallah I, Detre J, Chen‐Plotkin A, Shaw L, McMillan C, Yushkevich P, Wolk D. Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease. Alzheimers Dement 2024; 20:4147-4158. [PMID: 38747539 PMCID: PMC11180947 DOI: 10.1002/alz.13832] [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: 11/21/2023] [Revised: 02/21/2024] [Accepted: 03/18/2024] [Indexed: 05/28/2024]
Abstract
INTRODUCTION Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages. METHODS Participants had dMRI and either beta-amyloid PET or plasma biomarkers of Alzheimer's pathology within 18 months of MRI. Microstructure was measured in portions of the medial temporal lobe (MTL) with high neurofibrillary tangle (NFT) burden based on a previously developed post mortem 3D-map. Regressions examined relationships between microstructure and markers of Alzheimer's pathology in preclinical disease and then across disease stages. RESULTS There was higher isometric volume fraction in amyloid-positive compared to amyloid-negative cognitively unimpaired individuals in high tangle MTL regions. Similarly, plasma biomarkers and 18F-flortaucipir were associated with microstructural changes in preclinical disease. Additional microstructural effects were seen across disease stages. DISCUSSION Combining a post mortem atlas of NFT pathology with microstructural measures allows for detection of neurodegeneration in preclinical Alzheimer's disease. Highlights Typical markers of neurodegeneration are not sensitive in preclinical Alzheimer's. dMRI measured microstructure in regions with high NFT. Microstructural changes occur in medial temporal regions in preclinical disease. Microstructural changes occur in other typical Alzheimer's regions in later stages. Combining post mortem pathology atlases with in vivo MRI is a powerful framework.
Collapse
Affiliation(s)
- Christopher Brown
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sandhitsu Das
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Long Xie
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Siemens HealthineersDigital Technology and InnovationPrincetonNew JerseyUSA
| | - Ilya Nasrallah
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John Detre
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Alice Chen‐Plotkin
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Leslie Shaw
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey McMillan
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Paul Yushkevich
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David Wolk
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| |
Collapse
|
7
|
Brendstrup-Brix K, Ulv Larsen SM, Lee HH, Knudsen GM. Perivascular space diffusivity and brain microstructural measures are associated with circadian time and sleep quality. J Sleep Res 2024:e14226. [PMID: 38676409 DOI: 10.1111/jsr.14226] [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: 10/18/2023] [Revised: 04/04/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024]
Abstract
The glymphatic system is centred around brain cerebrospinal fluid flow and is enhanced during sleep, and the synaptic homeostasis hypothesis proposes that sleep acts on brain microstructure by selective synaptic downscaling. While so far primarily studied in animals, we here examine in humans if brain diffusivity and microstructure is related to time of day, sleep quality and cognitive performance. We use diffusion weighted images from 916 young healthy individuals, aged between 22 and 37 years, collected as part of the Human Connectome Project to assess diffusion tensor image analysis along the perivascular space index, white matter fractional anisotropy, intra-neurite volume fraction and extra-neurite mean diffusivity. Next, we examine if these measures are associated with circadian time of acquisition, the Pittsburgh Sleep Quality Index (high scores correspond to low sleep quality) and age-adjusted cognitive function total composite score. Consistent with expectations, we find that diffusion tensor image analysis along the perivascular space index and orbitofrontal grey matter extra-neurite mean diffusivity are negatively and white matter fractional anisotropy positively correlated with circadian time. Further, we find that grey matter intra-neurite volume fraction correlates positively with Pittsburgh Sleep Quality Index, and that this correlation is driven by sleep duration. Finally, we find positive correlations between grey matter intra-neurite volume fraction and cognitive function total composite score, as well as negative interaction effects between cognitive function total composite score and Pittsburgh Sleep Quality Index on grey matter intra-neurite volume fraction. Our findings propose that perivascular flow is under circadian control and that sleep downregulates the intra-neurite volume in healthy adults with positive impact on cognitive function.
Collapse
Affiliation(s)
- Kristoffer Brendstrup-Brix
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sara Marie Ulv Larsen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Gitte Moos Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
8
|
Cheng Y, Lin L, Jiang S, Huang P, Zhang J, Xin J, Xu H, Wang Y, Pan X. Aberrant microstructural integrity of white matter in mild and severe orthostatic hypotension: A NODDI study. CNS Neurosci Ther 2024; 30:e14586. [PMID: 38421091 PMCID: PMC10851318 DOI: 10.1111/cns.14586] [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: 10/08/2023] [Revised: 12/11/2023] [Accepted: 12/20/2023] [Indexed: 03/02/2024] Open
Abstract
OBJECTIVE Scarce evidence is available to elucidate the association between the abnormal microstructure of white matter (WM) and cognitive performance in patients with orthostatic hypotension (OH). This study investigated the microstructural integrity of WM in patients with mild OH (MOH) and severe OH (SOH) and evaluated the association of abnormal WM microstructure with the broad cognitive domains and cognition-related plasma biomarkers. METHODS Our study included 72 non-OH (NOH), 17 MOH, and 11 SOH participants. Across the groups, the WM integrity was analyzed by neurite orientation dispersion and density imaging (NODDI), and differences in WM microstructure were evaluated by nonparametric tests and post hoc models. The correlations between WM microstructure and broad cognitive domains and cognition-related plasma biomarkers were assessed by Spearman's correlation analysis. RESULTS The abnormal WM microstructure was localized to the WM fiber bundles in MOH patients but distributed widely in SOH cohorts (p < 0.05). Further analysis showed that the neurite density index of the left cingulate gyrus was negatively associated with amyloid β-40, glial fibrillary acidic protein, neurofilament light chain, phospho-tau181 (p < 0.05) but positively with global cognitive function (MOCA, MMSE, AER-III), memory, attention, language, language fluency, visuospatial function and amyloid β-40 / amyloid β-42 (p < 0.05). Additionally, other abnormal WM microstructures of OH were associated with broad cognitive domains and cognition-related plasma biomarkers to varying degrees. CONCLUSION The findings evidence that abnormal WM microstructures may present themselves as early as in the MOH phase and that these structural abnormalities are associated with cognitive functions and cognition-related plasma biomarkers.
Collapse
Affiliation(s)
- Yingzhe Cheng
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
| | - Lin Lin
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
| | - Shaofan Jiang
- Department of RadiologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for TumorsFujian Medical UniversityFuzhou CityChina
| | - Peilin Huang
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
| | - Jiejun Zhang
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
- Center for GeriatricsHainan General HospitalHainanChina
| | - Jiawei Xin
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
| | - Haibin Xu
- Fujian Medical UniversityFuzhou CityChina
| | - Yanping Wang
- Department of EndocrinologyFujian Medical University Union HospitalFuzhou CityChina
| | - Xiaodong Pan
- Department of Neurology, Center for Cognitive NeurologyFujian Medical University Union HospitalFuzhou CityChina
- Fujian Institute of GeriatricsFujian Medical University Union HospitalFuzhou CityChina
- Institute of Clinical NeurologyFujian Medical UniversityFuzhou CityChina
- Fujian Key Laboratory of Molecular NeurologyFujian Medical UniversityFuzhou CityChina
| |
Collapse
|
9
|
Singh K, Barsoum S, Schilling KG, An Y, Ferrucci L, Benjamini D. Neuronal microstructural changes in the human brain are associated with neurocognitive aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575206. [PMID: 38260525 PMCID: PMC10802615 DOI: 10.1101/2024.01.11.575206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
Collapse
Affiliation(s)
- Kavita Singh
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yang An
- Brain Aging and Behavior Section, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| |
Collapse
|
10
|
Anderson JA, Rashidi-Ranjbar N, Nazeri A, Chad JA, Zhukovsky P, Mulsant BH, Herrmann N, Mah L, Flint AJ, Fischer CE, Pollock BG, Rajji TK, Voineskos AN. Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:374-384. [PMID: 38298786 PMCID: PMC10829634 DOI: 10.1016/j.bpsgos.2023.08.018] [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: 04/28/2023] [Revised: 08/15/2023] [Accepted: 08/27/2023] [Indexed: 02/02/2024] Open
Abstract
Background Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss. Methods We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging). Results Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups. Conclusions The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.
Collapse
Affiliation(s)
- John A.E. Anderson
- Department of Cognitive Science, Carleton University, Ottawa, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Neda Rashidi-Ranjbar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
| | - Arash Nazeri
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri (AN)
| | - Jordan A. Chad
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Benoit H. Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Nathan Herrmann
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Linda Mah
- Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Alastair J. Flint
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
| | - Corinne E. Fischer
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Bruce G. Pollock
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Tarek K. Rajji
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - PACt-MD Study Group
- Department of Cognitive Science, Carleton University, Ottawa, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri (AN)
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
11
|
Zhong S, Lou J, Ma K, Shu Z, Chen L, Li C, Ye Q, Zhou L, Shen Y, Ye X, Zhang J. Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis. Brain Imaging Behav 2023; 17:764-777. [PMID: 37752311 DOI: 10.1007/s11682-023-00805-2] [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: 09/14/2023] [Indexed: 09/28/2023]
Abstract
The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.
Collapse
Affiliation(s)
- Shuchang Zhong
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jingjing Lou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ke Ma
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Zhenyu Shu
- Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Lin Chen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Chao Li
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Qing Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Liang Zhou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ye Shen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jie Zhang
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
| |
Collapse
|
12
|
Nair AK, Van Hulle CA, Bendlin BB, Zetterberg H, Blennow K, Wild N, Kollmorgen G, Suridjan I, Busse WW, Dean DC, Rosenkranz MA. Impact of asthma on the brain: evidence from diffusion MRI, CSF biomarkers and cognitive decline. Brain Commun 2023; 5:fcad180. [PMID: 37377978 PMCID: PMC10292933 DOI: 10.1093/braincomms/fcad180] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 04/27/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
Chronic systemic inflammation increases the risk of neurodegeneration, but the mechanisms remain unclear. Part of the challenge in reaching a nuanced understanding is the presence of multiple risk factors that interact to potentiate adverse consequences. To address modifiable risk factors and mitigate downstream effects, it is necessary, although difficult, to tease apart the contribution of an individual risk factor by accounting for concurrent factors such as advanced age, cardiovascular risk, and genetic predisposition. Using a case-control design, we investigated the influence of asthma, a highly prevalent chronic inflammatory disease of the airways, on brain health in participants recruited to the Wisconsin Alzheimer's Disease Research Center (31 asthma patients, 186 non-asthma controls, aged 45-90 years, 62.2% female, 92.2% cognitively unimpaired), a sample enriched for parental history of Alzheimer's disease. Asthma status was determined using detailed prescription information. We employed multi-shell diffusion weighted imaging scans and the three-compartment neurite orientation dispersion and density imaging model to assess white and gray matter microstructure. We used cerebrospinal fluid biomarkers to examine evidence of Alzheimer's disease pathology, glial activation, neuroinflammation and neurodegeneration. We evaluated cognitive changes over time using a preclinical Alzheimer cognitive composite. Using permutation analysis of linear models, we examined the moderating influence of asthma on relationships between diffusion imaging metrics, CSF biomarkers, and cognitive decline, controlling for age, sex, and cognitive status. We ran additional models controlling for cardiovascular risk and genetic risk of Alzheimer's disease, defined as a carrier of at least one apolipoprotein E (APOE) ε4 allele. Relative to controls, greater Alzheimer's disease pathology (lower amyloid-β42/amyloid-β40, higher phosphorylated-tau-181) and synaptic degeneration (neurogranin) biomarker concentrations were associated with more adverse white matter metrics (e.g. lower neurite density, higher mean diffusivity) in patients with asthma. Higher concentrations of the pleiotropic cytokine IL-6 and the glial marker S100B were associated with more salubrious white matter metrics in asthma, but not in controls. The adverse effects of age on white matter integrity were accelerated in asthma. Finally, we found evidence that in asthma, relative to controls, deterioration in white and gray matter microstructure was associated with accelerated cognitive decline. Taken together, our findings suggest that asthma accelerates white and gray matter microstructural changes associated with aging and increasing neuropathology, that in turn, are associated with more rapid cognitive decline. Effective asthma control, on the other hand, may be protective and slow progression of cognitive symptoms.
Collapse
Affiliation(s)
- Ajay Kumar Nair
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53703, USA
| | - Carol A Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, S-431 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 30 Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WCIE 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, Clear Water Bay, Hong Kong SAR, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, S-431 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, S-431 30 Mölndal, Sweden
| | - Norbert Wild
- Roche Diagnostics GmbH, Core Lab RED, 82377 Penzberg, Germany
| | | | - Ivonne Suridjan
- CDMA Clinical Development, Roche Diagnostics International Ltd, CH-6346, Rotkreuz, Switzerland
| | - William W Busse
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Douglas C Dean
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI 53703, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53719, USA
| |
Collapse
|
13
|
Spindler M, Thiel CM. Hypothalamic microstructure and function are related to body mass, but not mental or cognitive abilities across the adult lifespan. GeroScience 2023; 45:277-291. [PMID: 35896889 PMCID: PMC9886766 DOI: 10.1007/s11357-022-00630-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 07/20/2022] [Indexed: 02/03/2023] Open
Abstract
Physical, mental, and cognitive resources are essential for healthy aging. Aging impacts on the structural integrity of various brain regions, including the hippocampus. Even though recent rodent studies hint towards a critical role of the hypothalamus, there is limited evidence on functional consequences of age-related changes of this region in humans. Given its central role in metabolic regulation and affective processing and its connections to the hippocampus, it is plausible that hypothalamic integrity and connectivity are associated with functional age-related decline. We used data of n = 369 participants (18-88 years) from the Cambridge Centre for Ageing and Neuroscience repository to determine functional impacts of potential changes in hypothalamic microstructure across the lifespan. First, we identified age-related changes in microstructure as a function of physical, mental, and cognitive health and compared those findings to changes in hippocampal microstructure. Second, we investigated the relationship of hypothalamic microstructure and resting-state functional connectivity and related those changes to age as well as physical health. Our results showed that hypothalamic microstructure is not affected by depressive symptoms (mental health), cognitive performance (cognitive health), and comparatively stable across the lifespan, but affected by body mass (physical health). Furthermore, body mass changes connectivity to limbic regions including the hippocampus, amygdala, and nucleus accumbens, suggesting functional alterations in the metabolic and reward systems. Our results demonstrate that hypothalamic structure and function are affected by body mass, focused on neural density and dispersion, but not inflammation. Still, observed effect sizes were small, encouraging detailed investigations of individual hypothalamic subunits.
Collapse
Affiliation(s)
- Melanie Spindler
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl Von Ossietzky Universität Oldenburg, 26129, Oldenburg, Germany.
| | - Christiane M Thiel
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl Von Ossietzky Universität Oldenburg, 26129, Oldenburg, Germany
- Cluster of Excellence "Hearing4all", Carl Von Ossietzky Universität Oldenburg, 26129, Oldenburg, Germany
- Research Centre Neurosensory Science, Carl Von Ossietzky Universität Oldenburg, 26129, Oldenburg, Germany
| |
Collapse
|
14
|
Chylinski D, Narbutas J, Balteau E, Collette F, Bastin C, Berthomier C, Salmon E, Maquet P, Carrier J, Phillips C, Lina JM, Vandewalle G, Van Egroo M. Frontal grey matter microstructure is associated with sleep slow waves characteristics in late midlife. Sleep 2022; 45:zsac178. [PMID: 35869626 PMCID: PMC9644125 DOI: 10.1093/sleep/zsac178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/13/2022] [Indexed: 07/25/2023] Open
Abstract
STUDY OBJECTIVES The ability to generate slow waves (SW) during non-rapid eye movement (NREM) sleep decreases as early as the 5th decade of life, predominantly over frontal regions. This decrease may concern prominently SW characterized by a fast switch from hyperpolarized to depolarized, or down-to-up, state. Yet, the relationship between these fast and slow switcher SW and cerebral microstructure in ageing is not established. METHODS We recorded habitual sleep under EEG in 99 healthy late midlife individuals (mean age = 59.3 ± 5.3 years; 68 women) and extracted SW parameters (density, amplitude, frequency) for all SW as well as according to their switcher type (slow vs. fast). We further used neurite orientation dispersion and density imaging (NODDI) to assess microstructural integrity over a frontal grey matter region of interest (ROI). RESULTS In statistical models adjusted for age, sex, and sleep duration, we found that a lower SW density, particularly for fast switcher SW, was associated with a reduced orientation dispersion of neurites in the frontal ROI (p = 0.018, R2β* = 0.06). In addition, overall SW frequency was positively associated with neurite density (p = 0.03, R2β* = 0.05). By contrast, we found no significant relationships between SW amplitude and NODDI metrics. CONCLUSIONS Our findings suggest that the complexity of neurite organization contributes specifically to the rate of fast switcher SW occurrence in healthy middle-aged individuals, corroborating slow and fast switcher SW as distinct types of SW. They further suggest that the density of frontal neurites plays a key role for neural synchronization during sleep. TRIAL REGISTRATION NUMBER EudraCT 2016-001436-35.
Collapse
Affiliation(s)
- Daphne Chylinski
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Justinas Narbutas
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Evelyne Balteau
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | | | - Eric Salmon
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, Liège, Belgium
| | - Julie Carrier
- CARSM, CIUSSS of Nord-de l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, University of Montreal, Canada
| | - Christophe Phillips
- GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
- GIGA-In Silico Medicine, University of Liège, Liège, Belgium
| | - Jean-Marc Lina
- CARSM, CIUSSS of Nord-de l’Île-de-Montréal, Montreal, Canada
- Department of Psychology, University of Montreal, Canada
| | - Gilles Vandewalle
- Corresponding authors. Gilles Vandewalle, GIGA-Cyclotron Research Centre-In Vivo Imaging, Bâtiment B30, Université de Liège, Allée du Six Août, 8, 4000 Liège, Belgium.
| | - Maxime Van Egroo
- Maxime Van Egroo, Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, Maastricht, The Netherlands.
| |
Collapse
|