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Bahri M, Farrahi H, Mahdavinataj H, Batouli SAH. Eight brain structures mediate the age-related alterations of the working memory: forward and backward digit span tasks. Front Psychol 2024; 15:1377342. [PMID: 39295767 PMCID: PMC11409254 DOI: 10.3389/fpsyg.2024.1377342] [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: 01/27/2024] [Accepted: 08/19/2024] [Indexed: 09/21/2024] Open
Abstract
Introduction Working memory (WM) as one of the executive functions is an essential neurocognitive ability for daily life. Findings have suggested that aging is often associated with working memory and neural decline, but the brain structures and resting-state brain networks that mediate age-related differences in WM remain unclear. Methods A sample consisting of 252 healthy participants in the age range of 20 to 70years was used. Several cognitive tasks, including the n-back task and the forward and backward digit span tests were used. Also, resting-state functional imaging, as well as structural imaging using a 3T MRI scanner, were performed, resulting in 85 gray matter volumes and five resting-state networks, namely the anterior and posterior default mode, the right and left executive control, and the salience networks. Also, mediation analyses were used to investigate the role of gray matter volumes and resting-state networks in the relationship between age and WM. Results Behaviorally, aging was associated with decreased performance in the digit span task. Also, aging was associated with a decreased gray matter volume in 80 brain regions, and with a decreased activity in the anterior default mode network, executive control, and salience networks. Importantly, the path analysis showed that the GMV of the medial orbitofrontal, precentral, parieto-occipital, amygdala, middle occipital, posterior cingulate, and thalamus areas mediated the age-related differences in the forward digit span task, and the GMV of superior temporal gyrus mediated the age-related differences in the backward digit span task. Discussion This study identified the brain structures mediating the relationship between age and working memory, and we hope that our research provides an opportunity for early detection of individuals at risk of age-related memory decline.
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Affiliation(s)
- Maryam Bahri
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Hassan Farrahi
- Kavosh Cognitive Behavior Sciences and Addiction Research Center, Department of Psychiatry, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Hami Mahdavinataj
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Hossein Batouli
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
- BrainEE Research Group, Tehran University of Medical Sciences, Tehran, Iran
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Liu Y, Qing Z, Qin R, Chen H, Ye Q, Li M, Luo C, Liu R, Xu Y, Zhao H, Zhang B. Module-level structural and functional alternations in amnestic mild cognitive impairment. CHINESE JOURNAL OF ACADEMIC RADIOLOGY 2024; 7:264-276. [DOI: 10.1007/s42058-024-00160-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 06/02/2024] [Accepted: 06/21/2024] [Indexed: 11/07/2024]
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Zhang R, Liu S, Mousavi SM. Cognitive Dysfunction and Exercise: From Epigenetic to Genetic Molecular Mechanisms. Mol Neurobiol 2024; 61:6279-6299. [PMID: 38286967 DOI: 10.1007/s12035-024-03970-7] [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: 11/16/2023] [Accepted: 01/19/2024] [Indexed: 01/31/2024]
Abstract
Maintaining good health is crucial, and exercise plays a vital role in achieving this goal. It offers a range of positive benefits for cognitive function, regardless of age. However, as our population ages and life expectancy increases, cognitive impairment has become a prevalent issue, often coexisting with age-related neurodegenerative conditions. This can result in devastating consequences such as memory loss, difficulty speaking, and confusion, greatly hindering one's ability to lead an ordinary life. In addition, the decrease in mental capacity has a significant effect on an individual's physical and emotional well-being, greatly reducing their overall level of contentment and causing a significant financial burden for communities. While most current approaches aim to slow the decline of cognition, exercise offers a non-pharmacological, safe, and accessible solution. Its effects on cognition are intricate and involve changes in the brain's neural plasticity, mitochondrial stability, and energy metabolism. Moreover, exercise triggers the release of cytokines, playing a significant role in the body-brain connection and its impact on cognition. Additionally, exercise can influence gene expression through epigenetic mechanisms, leading to lasting improvements in brain function and behavior. Herein, we summarized various genetic and epigenetic mechanisms that can be modulated by exercise in cognitive dysfunction.
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Affiliation(s)
- Runhong Zhang
- Department of Physical Education, Luliang University, Lishi, 033000, Shanxi, China.
| | - Shangwu Liu
- Department of Physical Education, Luliang University, Lishi, 033000, Shanxi, China
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Karoly HC, Kirk‐Provencher KT, Schacht JP, Gowin JL. Alcohol and brain structure across the lifespan: A systematic review of large-scale neuroimaging studies. Addict Biol 2024; 29:e13439. [PMID: 39317645 PMCID: PMC11421948 DOI: 10.1111/adb.13439] [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: 02/22/2024] [Revised: 08/29/2024] [Accepted: 09/01/2024] [Indexed: 09/26/2024]
Abstract
Alcohol exposure affects brain structure, but the extent to which its effects differ across development remains unclear. Several countries are considering changes to recommended guidelines for alcohol consumption, so high-quality evidence is needed. Many studies have been conducted among small samples, but recent efforts have been made to acquire large samples to characterize alcohol's effects on the brain on a population level. Several large-scale consortia have acquired such samples, but this evidence has not been synthesized across the lifespan. We conducted a systematic review of large-scale neuroimaging studies examining effects of alcohol exposure on brain structure at multiple developmental stages. We included studies with an alcohol-exposed sample of at least N = 100 from the following consortia: ABCD, ENIGMA, NCANDA, IMAGEN, Framingham Offspring Study, HCP and UK BioBank. Twenty-seven studies were included, examining prenatal (N = 1), adolescent (N = 9), low-to-moderate-level adult (N = 11) and heavy adult (N = 7) exposure. Prenatal exposure was associated with greater brain volume at ages 9-10, but contemporaneous alcohol consumption during adolescence and adulthood was associated with smaller volume/thickness. Both low-to-moderate consumption and heavy consumption were characterized by smaller volume and thickness in frontal, temporal and parietal regions, and reductions in insula, cingulate and subcortical structures. Adolescent consumption had similar effects, with less consistent evidence for smaller cingulate, insula and subcortical volume. In sum, prenatal exposure was associated with larger volume, while adolescent and adult alcohol exposure was associated with smaller volume and thickness, suggesting that regional patterns of effects of alcohol are similar in adolescence and adulthood.
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Affiliation(s)
- Hollis C. Karoly
- Department of PsychologyColorado State UniversityFort CollinsColoradoUSA
| | - Katelyn T. Kirk‐Provencher
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Joseph P. Schacht
- Department of Psychiatry, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Joshua L. Gowin
- Department of Radiology, School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
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Vickery S, Patil KR, Dahnke R, Hopkins WD, Sherwood CC, Caspers S, Eickhoff SB, Hoffstaedter F. The uniqueness of human vulnerability to brain aging in great ape evolution. SCIENCE ADVANCES 2024; 10:eado2733. [PMID: 39196942 PMCID: PMC11352902 DOI: 10.1126/sciadv.ado2733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 07/24/2024] [Indexed: 08/30/2024]
Abstract
Aging is associated with progressive gray matter loss in the brain. This spatially specific, morphological change over the life span in humans is also found in chimpanzees, and the comparison between these great ape species provides a unique evolutionary perspective on human brain aging. Here, we present a data-driven, comparative framework to explore the relationship between gray matter atrophy with age and recent cerebral expansion in the phylogeny of chimpanzees and humans. In humans, we show a positive relationship between cerebral aging and cortical expansion, whereas no such relationship was found in chimpanzees. This human-specific association between strong aging effects and large relative cortical expansion is particularly present in higher-order cognitive regions of the ventral prefrontal cortex and supports the "last-in-first-out" hypothesis for brain maturation in recent evolutionary development of human faculties.
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Affiliation(s)
- Sam Vickery
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
- Division of Physiotherapy, Department of Applied Health Sciences, Hochschule für Gesundheit (University of Applied Sciences), Bochum, Germany
| | - Kaustubh R. Patil
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
| | - Robert Dahnke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Jena, Germany
- Structural Brain Mapping Group, Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - William D. Hopkins
- Department of Comparative Medicine, Michale E. Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Systems Neuroscience, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany
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Liu F, Liu Y, Shen X, Du J, Zhang H, Hou X. Ovariectomy exacerbates the disturbance of excitation- inhibition balance in the brain of APP/PS-1/tau mice. Front Mol Neurosci 2024; 17:1391082. [PMID: 39262829 PMCID: PMC11389216 DOI: 10.3389/fnmol.2024.1391082] [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: 02/24/2024] [Accepted: 08/05/2024] [Indexed: 09/13/2024] Open
Abstract
Introduction The prevalence of Alzheimer's disease (AD) is significantly gender-differentiated, with the number of female AD patients far exceeding that of males, accounting for two-thirds of the total prevalence. Although postmenopausal AD mice have been shown to have more prominent pathologic features and memory impairments than normal AD mice, the relevant molecular mechanisms leading to these outcomes have not been well elucidated. In the present study, we used the disturbance of excitation-inhibition balance in the postmenopausal brain as an entry point to explore the link between estrogen deficiency, disorders of the glutamatergic-GABAergic nervous system, and memory impairment. Methods Wild-type (WT) mice and APP/PS1/tau (3 × Tg-AD) mice (10 months old) were randomly divided into four groups: WT+Sham group, WT+OVX group, 3 × Tg-AD+Sham group and 3 × Tg-AD+OVX group. Ovariectomy (OVX) was performed in the WT+OVX group and the 3 × Tg-AD+OVX group, and sham surgery was performed in the WT+Sham group and the 3 × Tg-AD+Sham group. The learning and memory ability and the anxiety and depression-like behavior changes of mice were evaluated by behavioral experiments, and the association between estrogen-estrogen receptors pathway and glutamatergic/GABAergic nervous system and female AD was evaluated by neurochemical experiments. Results In WT and 3 × Tg-AD mice, OVX resulted in impaired learning and memory abilities and anxiety and depression-like behaviors; reduced estrogen levels and downregulated the expression of estrogen receptors; upregulated the expression of amyloid-β, amyloid precursor protein, presenilin 1, and p-tau; upregulated the expression of Bcl-2-associated X protein and downregulated the expression of B-cell lymphoma-2, promoting cell apoptosis; reduced the number of neuronal dendrites and downregulated the expression of postsynaptic density protein-95; more importantly, OVX increased brain glutamate levels but downregulated the expression of N-methyl-D-aspartate receptor-2B, excitatory amino acid transporter 1, excitatory amino acid transporter 2, γ-aminobutyric acid receptor-A and γ-aminobutyric acid receptor-B. Conclusion Our results suggested that OVX-induced estrogen-estrogen receptors pathway disruption caused learning and memory impairment and anxiety and depression-like behaviors, upregulated the expression of AD pathological markers, promoted apoptosis, destroyed neuronal structure, and most importantly, caused glutamatergic/GABAergic nervous system disorders.
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Affiliation(s)
- Fuwang Liu
- School of Pharmaceutical Sciences and Institute of Materia Medica, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Yanman Liu
- School of Pharmaceutical Sciences and Institute of Materia Medica, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xuri Shen
- School of Pharmaceutical Sciences and Institute of Materia Medica, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Jiarui Du
- School of Pharmaceutical Sciences and Institute of Materia Medica, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Hanting Zhang
- Department of Pharmacology, School of Pharmacy, Qingdao University, Qingdao, Shandong, China
| | - Xueqin Hou
- School of Pharmaceutical Sciences and Institute of Materia Medica, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
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García-Gutiérrez F, Hernández-Lorenzo L, Cabrera-Martín MN, Matias-Guiu JA, Ayala JL. Predicting changes in brain metabolism and progression from mild cognitive impairment to dementia using multitask Deep Learning models and explainable AI. Neuroimage 2024; 297:120695. [PMID: 38942101 DOI: 10.1016/j.neuroimage.2024.120695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 06/18/2024] [Indexed: 06/30/2024] Open
Abstract
BACKGROUND The prediction of Alzheimer's disease (AD) progression from its early stages is a research priority. In this context, the use of Artificial Intelligence (AI) in AD has experienced a notable surge in recent years. However, existing investigations predominantly concentrate on distinguishing clinical phenotypes through cross-sectional approaches. This study aims to investigate the potential of modeling additional dimensions of the disease, such as variations in brain metabolism assessed via [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET), and utilize this information to identify patients with mild cognitive impairment (MCI) who will progress to dementia (pMCI). METHODS We analyzed data from 1,617 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had undergone at least one FDG-PET scan. We identified the brain regions with the most significant hypometabolism in AD and used Deep Learning (DL) models to predict future changes in brain metabolism. The best-performing model was then adapted under a multi-task learning framework to identify pMCI individuals. Finally, this model underwent further analysis using eXplainable AI (XAI) techniques. RESULTS Our results confirm a strong association between hypometabolism, disease progression, and cognitive decline. Furthermore, we demonstrated that integrating data on changes in brain metabolism during training enhanced the models' ability to detect pMCI individuals (sensitivity=88.4%, specificity=86.9%). Lastly, the application of XAI techniques enabled us to delve into the brain regions with the most significant impact on model predictions, highlighting the importance of the hippocampus, cingulate cortex, and some subcortical structures. CONCLUSION This study introduces a novel dimension to predictive modeling in AD, emphasizing the importance of projecting variations in brain metabolism under a multi-task learning paradigm.
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Affiliation(s)
| | | | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain.
| | - Jordi A Matias-Guiu
- Department of Neurology, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain.
| | - José L Ayala
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain.
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Allison EY, Al-Khazraji BK. Association of Arterial Stiffness Index and Brain Structure in the UK Biobank: A 10-Year Retrospective Analysis. Aging Dis 2024; 15:1872-1884. [PMID: 37307821 PMCID: PMC11272205 DOI: 10.14336/ad.2023.0419] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/19/2023] [Indexed: 06/14/2023] Open
Abstract
Arterial stiffening and changes in brain structure both occur with normal aging and can be exacerbated via acquired health conditions. While cross-sectional associations exist, the longitudinal relationship between arterial stiffness and brain structure remains unclear. In this study, we investigated 1) associations between baseline arterial stiffness index (ASI) and brain structure (global and regional grey matter volumes (GMV), white matter hyperintensities (WMH)) 10-years post-baseline (10.4±0.8 years) and 2) associations between the 10-year change in ASI from baseline and brain structure 10-years post-baseline in 650 healthy middle- to older-aged adults (53.4±7.5 years) from the UK Biobank. We observed significant associations between baseline ASI and GMV (p<0.001) and WMH (p=0.0036) 10-years post-baseline. No significant associations between 10-year change in ASI and brain structure (global GMV p=0.24; WMH volume p=0.87) were observed. There were significant associations of baseline ASI in 2 of 60 regional brain volumes analyzed (right posterior superior temporal gyrus p=0.001; left superior lateral occipital cortex p<0.001). Strong associations with baseline ASI, but not changes in ASI over 10-years, suggest arterial stiffness at the entry point of older adulthood is more impactful on brain structure 10-years later compared to age-related stiffening. Based on these associations, we suggest clinical monitoring and potential intervention for reducing arterial stiffness should occur in midlife to reduce vascular contributions to structural changes in the brain, supporting a healthy trajectory of brain aging. Our findings also support use of ASI as a surrogate for gold standard measures in showing overall relationships between arterial stiffness and brain structure.
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Affiliation(s)
- Elric Y Allison
- Department of Kinesiology, Faculty of Science, McMaster University, Hamilton, ON, Canada
| | - Baraa K Al-Khazraji
- Department of Kinesiology, Faculty of Science, McMaster University, Hamilton, ON, Canada
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Martinec Nováková L, Georgi H, Vlčková K, Kopeček M, Babuská A, Havlíček J. Small effects of olfactory identification and discrimination on global cognitive and executive performance over 1 year in aging people without a history of age-related cognitive impairment. Physiol Behav 2024; 282:114579. [PMID: 38710351 DOI: 10.1016/j.physbeh.2024.114579] [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: 01/25/2024] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/08/2024]
Abstract
Olfactory and cognitive performance share neural correlates profoundly affected by physiological aging. However, whether odor identification and discrimination scores predict global cognitive status and executive function in healthy older people with intact cognition is unclear. Therefore, in the present study, we set out to elucidate these links in a convenience sample of 204 independently living, cognitively intact healthy Czech adults aged 77.4 ± 8.7 (61-97 years) over two waves of data collection (one-year interval). We used the Czech versions of the Montreal Cognitive Assessment (MoCA) to evaluate global cognition, and the Prague Stroop Test (PST), Trail Making Test (TMT), and several verbal fluency (VF) tests to assess executive function. As a subsidiary aim, we aimed to examine the contribution of olfactory performance towards achieving a MoCA score above vs. below the published cut-off value. We found that the MoCA scores exhibited moderate associations with both odor identification and discrimination. Furthermore, odor identification significantly predicted PST C and C/D scores. Odor discrimination significantly predicted PST C/D, TMT B/A, and standardized composite VF scores. Our findings demonstrate that olfaction, on the one hand, and global cognition and executive function, on the other, are related even in healthy older people.
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Affiliation(s)
- Lenka Martinec Nováková
- Department of Psychology and Life Sciences, Faculty of Humanities, Charles University, Pátkova 2137/5, 182 00 Prague 8 - Libeň, Czech Republic; Department of Chemical Education and Humanities, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6 - Dejvice, Czech Republic.
| | - Hana Georgi
- Prague College of Psychosocial Studies, Hekrova 805, 149 00 Prague 4, Czech Republic
| | - Karolína Vlčková
- Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Ruská 87, 100 00 Prague 10 - Vršovice, Czech Republic; Thomayer Teaching Hospital, Vídeňská 800, 140 59 Prague 4 - Krč, Czech Republic
| | - Miloslav Kopeček
- Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Ruská 87, 100 00 Prague 10 - Vršovice, Czech Republic; National Institute of Mental Health, Topolová 748, 250 67 Klecany, Czech Republic
| | - Anna Babuská
- Department of Zoology, Faculty of Science, Charles University, Viničná 7, 128 00 Prague 2, Czech Republic
| | - Jan Havlíček
- Department of Zoology, Faculty of Science, Charles University, Viničná 7, 128 00 Prague 2, Czech Republic
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Zhou Y, She R, Mei Z, Liu D, Ge J. Crosstalk between ferroptosis and necroptosis in cerebral ischemia/reperfusion injury and Naotaifang formula exerts neuroprotective effect via HSP90-GCN2-ATF4 pathway. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 130:155399. [PMID: 38850632 DOI: 10.1016/j.phymed.2024.155399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 01/04/2024] [Accepted: 01/28/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Cerebral ischemia/reperfusion injury (CIRI) is a sequence of pathophysiological processes after blood recanalization in the patients with ischemic stroke, and has become the hinder for the rehabilitation. Naotaifang formula (NTF) has exhibited the clinical effectiveness for this disease. However, its action effects and molecular mechanisms against CIRI are not fully elucidated. PURPOSE The research was to clarify the crosstalk between ferroptosis and necroptosis in CIRI, and uncover the mechanism underlying the neuroprotection of NTF. METHODS This study established MCAO/R rat models with various reperfusion times. Western blot, transmission electron microscope, laser speckle imaging, immunofluorescence, immunohistochemistry and pathological staining were conducted to detect and analyze the obtained results. Subsequently, various NTF doses were used to intervene in MCAO/R rats, and biology experiments, such as western blot, Evans blue, immunofluorescence and immunohistochemistry, were used to analyze the efficacy of NTF doses. The effect of NTF was further clarified through in vitro experiments. Eventually, HT22 cells that suffered OGD/R were subjected to pre-treatment with plasmids overexpressing HSP90, MLKL, and GPX4 to indicate the interaction among ferroptosis and necroptosis. RESULTS There was a gradual increase in the Zea Longa score and cerebral infarction volume following CIRI with prolonged reperfusion. Furthermore, the expression of factors associated with pro-ferroptosis and pro-necroptosis was upregulated in the cortex and hippocampus. NTF alleviated ferroptosis and necroptosis in a dose-dependent manner, downregulated HSP90 levels, reduced blood-brain barrier permeability, and thus protected nerve cells from CIRI. The results in vitro research aligned with those of the in vivo research. HSP90 and MLKL overexpression promoted necroptosis and ferroptosis while activating the GCN2-ATF4 pathway. GPX4 overexpression had no effect on necroptosis or the associated signaling pathway. The administration of NTF alone, as well as its combination with the overexpression of HSP90, MLKL, or GPX4 plasmids, decreased the expression levels of factors associated with pro-ferroptosis and pro-necroptosis and reduced the protein levels of the HSP90-GCN2-ATF4 pathway. Moreover, the regulatory effects of the NTF alone group on GSH, ferrous iron, and GCN2 were more significant compared with those of the HSP90 overexpression combination group. CONCLUSION Ferroptosis and necroptosis were gradually aggravated following CIRI with prolonged reperfusion. MLKL overexpression may promote ferroptosis and necroptosis, while GPX4 overexpression may have little effect on necroptosis. HSP90 overexpression accelerated both forms of cell death via the HSP90-GCN2-ATF4 pathway. NTF alleviated ferroptosis and necroptosis to attenuate CIRI by regulating the HSP90-GCN2-ATF4 pathway. Our research provided evidence for the potential of drug development by targeting HSP90, MLKL, and GPX4 to protect against ischemic stroke.
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Affiliation(s)
- Yue Zhou
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Department of Scientific Research, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Changsha 410006, China
| | - Ruining She
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China
| | - Zhigang Mei
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.
| | - Danhong Liu
- Medical School, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China
| | - Jinwen Ge
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China; Hunan Academy of Chinese Medicine, Changsha, Hunan 410013, China.
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Wu S, Wang L, Liu S, Qi J, Shi F, Zhuang H, Qian Y, Mei L, Zhang M. Relationship between domain-specific physical activity and cognitive function in older adults - findings from NHANES 2011-2014. Front Public Health 2024; 12:1390511. [PMID: 39114526 PMCID: PMC11303168 DOI: 10.3389/fpubh.2024.1390511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 07/08/2024] [Indexed: 08/10/2024] Open
Abstract
Objective To determine the relationship between domain-specific physical activity (PA) (e.g., occupational PA [OPA], transport-related PA [TPA], and recreational PA [RPA]) and cognitive function in older adults. Methods The data was obtained from the 2011-2014 cycle of the NHANES. We utilized weighted multivariate linear regression models among the included 2,924 people aged 60 years or older for our purposes. Results RPA and total PA according to WHO guidelines were associated with verbal fluency (RPA β: 1.400, 95% CI: 0.776, 2.024, p = 0.002; total PA β: 1.115, 95% CI: 0.571, 1.659, p = 0.001), processing speed and executive function (RPA β: 2.912, 95% CI. 1.291, 4.534, p = 0.005; total PA β: 2.974, 95% CI: 1.683, 4.265, p < 0.001) were positively correlated, and total PA was correlated with delayed memory performance (β: 0.254, 95% CI: 0.058, 0.449, p = 0.019). No significant association was observed between OPA, TPA, and various aspects of cognitive function among individuals over 60 years. Conclusion There was no noteworthy correlation discovered between OPA and TPA in relation to cognitive function. However, RPA and total PA exhibited significant associations with verbal fluency, processing speed, and executive function. Additionally, maintaining PA levels ranging from 600 to 1,200 MET-min/week would yield the most favorable outcomes for cognitive function.
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Affiliation(s)
- Sijun Wu
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Lin Wang
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Shijie Liu
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Juancai Qi
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Fengrui Shi
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Huiqi Zhuang
- School of Physical Education, Wuhan University of Technology, Wuhan, China
| | - Youling Qian
- School of Physical Education, Hubei Minzu University, Enshi, China
| | - Linqi Mei
- School of Physical Education, Hubei University, Wuhan, China
| | - Maolin Zhang
- School of Wushu, Shandong Sport University, Jinan, China
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Yan QQ, Liu TL, Liu LL, Wei YS, Zhao YD, Yu C, Zhong ZG, Huang JL, Wu DP. Mitochondrial Treatment Improves Cognitive Impairment Induced by Lipopolysaccharide in Mice. Mol Neurobiol 2024:10.1007/s12035-024-04368-1. [PMID: 39037529 DOI: 10.1007/s12035-024-04368-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 07/15/2024] [Indexed: 07/23/2024]
Abstract
Neuroinflammation has been proven to drive cognitive impairment associated with neurodegenerative diseases. It has been demonstrated that mitochondrial dysfunction is associated with cognitive impairment caused by neuroinflammation. We hypothesized that the transfer of exogenous mitochondria may be beneficial to the therapy of cognitive impairment induced by neuroinflammation. In the study, the effect of exogenous mitochondria on cognitive impairment induced by neuroinflammation was investigated. The results showed that mitochondrial treatment ameliorated the cognitive performance of lipopolysaccharide (LPS)-treated mice. Additionally, mitochondrial therapy attenuated neuronal injury and down-regulated the expression of proinflammatory cytokines, including TNF-α and pro- and cleaved IL-1β, and the expression of Iba-1 and GFAP in the hippocampus and cortex of LPS-treated mice. Additionally, mitochondrial treatment increased mitochondrial ΔΨm, ATP level, and SOD activity and attenuated MDA level and ROS production in the brains of LPS-treated mice. The study reports the beneficial effect of mitochondrial treatment against cognitive impairment of LPS-treated mice, thereby providing a potential strategy for the treatment of cognitive impairment caused by neuroinflammation.
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Affiliation(s)
- Qiu-Qing Yan
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Tian-Long Liu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Ling-Ling Liu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yan-Su Wei
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Yuan-Dan Zhao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Chao Yu
- School of Basic Medicine, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China
| | - Zhen-Guo Zhong
- Scientific Research Center of Traditional Chinese Medicine, Guangxi University of Chinese Medicine, Nanning, 530200, Guangxi, China
| | - Jin-Lan Huang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Xuzhou Ruihu Health Management Consulting Co., Ltd, Xuzhou, 221002, Jiangsu, China.
| | - Deng-Pan Wu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Pharmacy School, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
- Xuzhou Ruihu Health Management Consulting Co., Ltd, Xuzhou, 221002, Jiangsu, China.
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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.
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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
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Korbmacher M, van der Meer D, Beck D, Askeland-Gjerde DE, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer's Disease in the UK Biobank. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100323. [PMID: 39132576 PMCID: PMC11313202 DOI: 10.1016/j.bpsgos.2024.100323] [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: 03/21/2024] [Revised: 03/24/2024] [Accepted: 04/16/2024] [Indexed: 08/13/2024] Open
Abstract
Background During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging. Methods We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer's disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data. Results Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages. Conclusions We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.
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Affiliation(s)
- Max Korbmacher
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Daniel E. Askeland-Gjerde
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
| | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ole A. Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ivan I. Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
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Pipoly M, Lee HK, Hazeltine E, Voss MW. Educational Attainment Moderates Task-State Control Network Connectivity Relations to Response Conflict Among Healthy Older Adults. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae077. [PMID: 38721999 PMCID: PMC11176974 DOI: 10.1093/geronb/gbae077] [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: 07/12/2023] [Indexed: 06/15/2024] Open
Abstract
OBJECTIVES Older adult executive function varies widely due to brain and cognitive aging. Variance in older adult executive function is linked to increased response conflict from cognitive and brain aging. Cognitive reserve (CR) is a theoretical protective mechanism that lessens brain aging's impact on cognition and is associated with greater educational attainment. Recent work in rest-state functional magnetic resonance imaging (fMRI) suggests CR proxies moderate the relationship between functional connectivity (FC) and cognitive performance. Brain network FC in "control networks," including the salience (SN), dorsal attention and frontoparietal networks, are associated with cognitive processes in older adults. CR is hypothesized to maintain cognitive processing in part through changes in how brain networks respond to cognitive demands. However, it is unclear how CR proxies like educational attainment are related to control network FC during performance when cognitive demands are increased relative to rest. Because CR is expressed more in those with higher education, we hypothesized stronger control network FC would relate to better performance, where this relationship would be strongest among the most educated. METHODS We collected flanker task data during fMRI to assess the impact of a CR proxy (i.e., educational attainment) on response conflict among older adult subjects (n = 42, age = 65-80). RESULTS Linear mixed-effects models showed more educated older adults with greater SN-FC had a smaller flanker effect (i.e., less influence of distractors; p < .001) during task performance. DISCUSSION For the first time, we show that educational attainment moderates the relationship between task-state SN-FC and executive function among older adults.
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Affiliation(s)
- Marco Pipoly
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
- Interdisciplinary Graduate Program in Neuroscience, University of Iowa, Iowa City, Iowa, USA
| | - Hyun Kyu Lee
- Department of Research and Development, Posit Science Inc., San Francisco, California, USA
| | - Eliot Hazeltine
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
- Interdisciplinary Graduate Program in Neuroscience, University of Iowa, Iowa City, Iowa, USA
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
- Interdisciplinary Graduate Program in Neuroscience, University of Iowa, Iowa City, Iowa, USA
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Nicola L, Loo SJQ, Lyon G, Turknett J, Wood TR. Does resistance training in older adults lead to structural brain changes associated with a lower risk of Alzheimer's dementia? A narrative review. Ageing Res Rev 2024; 98:102356. [PMID: 38823487 DOI: 10.1016/j.arr.2024.102356] [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: 03/10/2024] [Accepted: 05/27/2024] [Indexed: 06/03/2024]
Abstract
Dementia, particularly Alzheimer's Disease (AD), has links to several modifiable risk factors, especially physical inactivity. When considering the relationship between physcial activity and dementia risk, cognitive benefits are generally attributed to aerobic exercise, with resistance exercise (RE) receiving less attention. This review aims to address this gap by evaluating the impact of RE on brain structures and cognitive deficits associated with AD. Drawing insights from randomized controlled trials (RCTs) utilizing structural neuroimaging, the specific influence of RE on AD-affected brain structures and their correlation with cognitive function are discussed. Preliminary findings suggest that RE induces structural brain changes in older adults that could reduce the risk of AD or mitigate AD progression. Importantly, the impacts of RE appear to follow a dose-response effect, reversing pathological structural changes and improving associated cognitive functions if performed at least twice per week for at least six months, with greatest effects in those already experiencing some element of cognitive decline. While more research is eagerly awaited, this review contributes insights into the potential benefits of RE for cognitive health in the context of AD-related changes in brain structure and function.
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Affiliation(s)
| | | | | | | | - Thomas R Wood
- Department of Pediatrics, University of Washington, Seattle, WA, USA; Institute for Human and Machine Cognition, Pensacola, FL, USA.
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Keeler JL, Bahnsen K, Wronski ML, Bernardoni F, Tam F, Arold D, King JA, Kolb T, Poitz DM, Roessner V, Treasure J, Himmerich H, Ehrlich S. Longitudinal changes in brain-derived neurotrophic factor (BDNF) but not cytokines contribute to hippocampal recovery in anorexia nervosa above increases in body mass index. Psychol Med 2024; 54:2242-2253. [PMID: 38450444 DOI: 10.1017/s0033291724000394] [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] [Indexed: 03/08/2024]
Abstract
BACKGROUND Physical sequelae of anorexia nervosa (AN) include a marked reduction in whole brain volume and subcortical structures such as the hippocampus. Previous research has indicated aberrant levels of inflammatory markers and growth factors in AN, which in other populations have been shown to influence hippocampal integrity. METHODS Here we investigated the influence of concentrations of two pro-inflammatory cytokines (tumor necrosis factor-alpha [TNF-α] and interleukin-6 [IL-6]) and brain-derived neurotrophic factor (BDNF) on the whole hippocampal volume, as well as the volumes of three regions (the hippocampal body, head, and tail) and 18 subfields bilaterally. Investigations occurred both cross-sectionally between acutely underweight adolescent/young adult females with AN (acAN; n = 82) and people recovered from AN (recAN; n = 20), each independently pairwise age-matched with healthy controls (HC), and longitudinally in acAN after partial renourishment (n = 58). Hippocampal subfield volumes were quantified using FreeSurfer. Concentrations of molecular factors were analyzed in linear models with hippocampal (subfield) volumes as the dependent variable. RESULTS Cross-sectionally, there was no evidence for an association between IL-6, TNF-α, or BDNF and between-group differences in hippocampal subfield volumes. Longitudinally, increasing concentrations of BDNF were positively associated with longitudinal increases in bilateral global hippocampal volumes after controlling for age, age2, estimated total intracranial volume, and increases in body mass index (BMI). CONCLUSIONS These findings suggest that increases in BDNF may contribute to global hippocampal recovery over and above increases in BMI during renourishment. Investigations into treatments targeted toward increasing BDNF in AN may be warranted.
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Affiliation(s)
- Johanna Louise Keeler
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Klaas Bahnsen
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Marie-Louis Wronski
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Friederike Tam
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Dominic Arold
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Theresa Kolb
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - David M Poitz
- Institute for Clinical Chemistry and Laboratory Medicine, TU Dresden, Dresden, Germany
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Janet Treasure
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Hubertus Himmerich
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
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Lee HK, Basak C, Grant SJ, Ray NR, Skolasinska PA, Oehler C, Qin S, Sun A, Smith ET, Sherard GH, Rivera-Dompenciel A, Merzenich M, Voss MW. The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae075. [PMID: 38686621 PMCID: PMC11165429 DOI: 10.1093/geronb/gbae075] [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: 07/24/2023] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults. METHODS One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64). RESULTS After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure. DISCUSSION Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT. CLINICAL TRIAL REGISTRATION NCT03197454.
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Affiliation(s)
- Hyun Kyu Lee
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | | | - Sarah-Jane Grant
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Nicholas R Ray
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Chris Oehler
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
| | - Shuo Qin
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Andrew Sun
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Evan T Smith
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - G Hulon Sherard
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Mike Merzenich
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
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Sun L, Zhao T, Liang X, Xia M, Li Q, Liao X, Gong G, Wang Q, Pang C, Yu Q, Bi Y, Chen P, Chen R, Chen Y, Chen T, Cheng J, Cheng Y, Cui Z, Dai Z, Deng Y, Ding Y, Dong Q, Duan D, Gao JH, Gong Q, Han Y, Han Z, Huang CC, Huang R, Huo R, Li L, Lin CP, Lin Q, Liu B, Liu C, Liu N, Liu Y, Liu Y, Lu J, Ma L, Men W, Qin S, Qiu J, Qiu S, Si T, Tan S, Tang Y, Tao S, Wang D, Wang F, Wang J, Wang P, Wang X, Wang Y, Wei D, Wu Y, Xie P, Xu X, Xu Y, Xu Z, Yang L, Yuan H, Zeng Z, Zhang H, Zhang X, Zhao G, Zheng Y, Zhong S, He Y. Functional connectome through the human life span. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.12.557193. [PMID: 37745373 PMCID: PMC10515818 DOI: 10.1101/2023.09.12.557193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.
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Affiliation(s)
- Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Qian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chenxuan Pang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qian Yu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Pindong Chen
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Rui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Zhengjia Dai
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yao Deng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ruiwang Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, China
- Department of Education and Research, Taipei City Hospital, Taipei, China
| | - Qixiang Lin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Chao Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Yong Liu
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Jing Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji’nan, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haibo Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Suyu Zhong
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | | | | | | | | | | | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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70
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Zhang X, Wang Z, Zou J, Zhang L, Ning JH, Jiang B, Liang Y, Zhang YZ. Association between physical frailty and cortical structure in middle-aged and elderly people: a Mendelian randomization study. Front Aging Neurosci 2024; 16:1395553. [PMID: 38841102 PMCID: PMC11150765 DOI: 10.3389/fnagi.2024.1395553] [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: 03/04/2024] [Accepted: 05/06/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Physical weakness is associated with cortical structures, but the exact causes remain to be investigated. Therefore, we utilized Mendelian randomization (MR) analysis to uncover the underlying connection between frailty and cortical structures. Methods The Genome-Wide Association Study (GWAS) on frailty pooled data from publicly available sources such as the UK Biobank and included five indicators of frailty: weakness, walking speed, weight loss, physical activity, and exhaustion. GWAS data on cerebral cortical structure were obtained from the ENIGMA consortium, and we assessed the causal relationship between hereditary frailty and cortical surface area (SA) or cortical thickness (TH). Inverse variance weighting (IVW) was used as the primary estimate, and heterogeneity and multidimensionality were monitored by MR-PRESSO to detect outliers. Additionally, MR-Egger, Cochran's Q test, and weighted median were employed. Results At the aggregate level, there was no causal relationship between frailty and cortical thickness or surface area. At the regional level, frailty was associated with the thickness of the middle temporal lobe, parahippocampus, rostral middle frontal lobe, lower parietal lobe, anterior cingulate gyrus, upper temporal lobe, lateral orbital frontal cortex, pericardial surface area, rostral middle frontal lobe, upper temporal lobe, rostral anterior cingulate gyrus, lower parietal lobe, and upper parietal lobe. These results were nominally significant, and sensitivity analyses did not detect any multidirectionality or heterogeneity, suggesting that the results of our analyses are reliable. Discussion The results of our analyses suggest a potential causal relationship between somatic weakness and multiple regions of cortical structure. However, the specific mechanisms of influence remain to be investigated. Preliminary results from our analysis suggest that the effects of physical frailty on cortical structures are influenced by various factors related to frailty exposure. This relationship has been documented, and it is therefore both feasible and meaningful to build on existing research to explore the clinical significance of the relationship.
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Affiliation(s)
- Xin Zhang
- College of Basic Medical Sciences, Dali University, Dali, Yunnan, China
| | - Zhen Wang
- College of Basic Medical Sciences, Dali University, Dali, Yunnan, China
| | - Jing Zou
- The First Affiliated Hospital of Dali University, Dali, Yunnan, China
| | - Le Zhang
- College of Basic Medical Sciences, Dali University, Dali, Yunnan, China
| | - Jing-Hua Ning
- College of Basic Medical Sciences, Dali University, Dali, Yunnan, China
| | - Bei Jiang
- Yunnan Key Laboratory of Screening and Research on Anti-pathogenic Plant Resources from West Yunnan (Cultivation), Dali, Yunnan, China
| | - Yi Liang
- Princess Margaret Cancer Centre, TMDT-MaRS Centre, University Health Network, Toronto, ON, Canada
| | - Yu-Zhe Zhang
- College of Basic Medical Sciences, Dali University, Dali, Yunnan, China
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71
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Ashraf AA, Aljuhani M, Hubens CJ, Jeandriens J, Parkes HG, Geraki K, Mahmood A, Herlihy AH, So PW. Inflammation subsequent to mild iron excess differentially alters regional brain iron metabolism, oxidation and neuroinflammation status in mice. Front Aging Neurosci 2024; 16:1393351. [PMID: 38836051 PMCID: PMC11148467 DOI: 10.3389/fnagi.2024.1393351] [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: 02/28/2024] [Accepted: 04/26/2024] [Indexed: 06/06/2024] Open
Abstract
Iron dyshomeostasis and neuroinflammation, characteristic features of the aged brain, and exacerbated in neurodegenerative disease, may induce oxidative stress-mediated neurodegeneration. In this study, the effects of potential priming with mild systemic iron injections on subsequent lipopolysaccharide (LPS)-induced inflammation in adult C57Bl/6J mice were examined. After cognitive testing, regional brain tissues were dissected for iron (metal) measurements by total reflection X-ray fluorescence and synchrotron radiation X-Ray fluorescence-based elemental mapping; and iron regulatory, ferroptosis-related, and glia-specific protein analysis, and lipid peroxidation by western blotting. Microglial morphology and astrogliosis were assessed by immunohistochemistry. Iron only treatment enhanced cognitive performance on the novel object location task compared with iron priming and subsequent LPS-induced inflammation. LPS-induced inflammation, with or without iron treatment, attenuated hippocampal heme oxygenase-1 and augmented 4-hydroxynonenal levels. Conversely, in the cortex, elevated ferritin light chain and xCT (light chain of System Xc-) were observed in response to LPS-induced inflammation, without and with iron-priming. Increased microglial branch/process lengths and astrocyte immunoreactivity were also increased by combined iron and LPS in both the hippocampus and cortex. Here, we demonstrate iron priming and subsequent LPS-induced inflammation led to iron dyshomeostasis, compromised antioxidant function, increased lipid peroxidation and altered neuroinflammatory state in a brain region-dependent manner.
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Affiliation(s)
- Azhaar Ahmad Ashraf
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Manal Aljuhani
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Chantal J Hubens
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jérôme Jeandriens
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Human Biology and Toxicology, Faculty of Medicine, University of Mons, Mons, Belgium
| | - Harold G Parkes
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Kalotina Geraki
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot, United Kingdom
| | - Ayesha Mahmood
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | | | - Po-Wah So
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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72
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Guo X, Ding Y, Xu W, Wang D, Yu H, Lin Y, Chang S, Zhang Q, Zhang Y. Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers. J Neuroradiol 2024; 51:265-273. [PMID: 37722591 DOI: 10.1016/j.neurad.2023.09.002] [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: 07/08/2023] [Revised: 09/14/2023] [Accepted: 09/15/2023] [Indexed: 09/20/2023]
Abstract
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a single marker and can not discover meaningful hidden information in radiographic images. This study focuses on the application of radiomics, an advanced imaging analysis technique, combined with automated machine learning to predict BAG. Our methods achieve a promising result with a mean absolute error of 1.509 using the Alzheimer's Disease Neuroimaging Initiative dataset. Furthermore, we find that the hippocampus and parahippocampal gyrus play a significant role in predicting age with interpretable method called SHapley Additive exPlanations. Additionally, our investigation of age prediction discrepancies between patients with Alzheimer's disease (AD) and those with mild cognitive impairment (MCI) reveals a notable correlation with clinical cognitive assessment scale scores. This suggests that BAG has the potential to serve as a biomarker to support the diagnosis of AD and MCI. Overall, this study presents valuable insights into the application of neuroimaging models in the diagnosis of neurodegenerative diseases.
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Affiliation(s)
- Xiaoliang Guo
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yanhui Ding
- School of Information Science and Engineering, Shandong Normal University, Jinan, China.
| | - Weizhi Xu
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Dong Wang
- School of Artificial Intelligence, Beijing University of Posts and Telecommunication, Beijing, China
| | - Huiying Yu
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yongkang Lin
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Shulei Chang
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Qiqi Zhang
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yongxin Zhang
- School of Mathematics and Statistics, Shandong Normal University, Jinan, China.
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73
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Anderson T, Sharma S, Kelberman MA, Ware C, Guo N, Qin Z, Weinshenker D, Parent MB. Obesity during preclinical Alzheimer's disease development exacerbates brain metabolic decline. J Neurochem 2024; 168:801-821. [PMID: 37391269 DOI: 10.1111/jnc.15900] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 05/29/2023] [Accepted: 06/13/2023] [Indexed: 07/02/2023]
Abstract
Alzheimer's disease (AD) is the most common form of dementia. Obesity in middle age increases AD risk and severity, which is alarming given that obesity prevalence peaks at middle age and obesity rates are accelerating worldwide. Midlife, but not late-life obesity increases AD risk, suggesting that this interaction is specific to preclinical AD. AD pathology begins in middle age, with accumulation of amyloid beta (Aβ), hyperphosphorylated tau, metabolic decline, and neuroinflammation occurring decades before cognitive symptoms appear. We used a transcriptomic discovery approach in young adult (6.5 months old) male and female TgF344-AD rats that overexpress mutant human amyloid precursor protein and presenilin-1 and wild-type (WT) controls to determine whether inducing obesity with a high-fat/high-sugar "Western" diet during preclinical AD increases brain metabolic dysfunction in dorsal hippocampus (dHC), a brain region vulnerable to the effects of obesity and early AD. Analyses of dHC gene expression data showed dysregulated mitochondrial and neurotransmission pathways, and up-regulated genes involved in cholesterol synthesis. Western diet amplified the number of genes that were different between AD and WT rats and added pathways involved in noradrenergic signaling, dysregulated inhibition of cholesterol synthesis, and decreased intracellular lipid transporters. Importantly, the Western diet impaired dHC-dependent spatial working memory in AD but not WT rats, confirming that the dietary intervention accelerated cognitive decline. To examine later consequences of early transcriptional dysregulation, we measured dHC monoamine levels in older (13 months old) AD and WT rats of both sexes after long-term chow or Western diet consumption. Norepinephrine (NE) abundance was significantly decreased in AD rats, NE turnover was increased, and the Western diet attenuated the AD-induced increases in turnover. Collectively, these findings indicate obesity during prodromal AD impairs memory, potentiates AD-induced metabolic decline likely leading to an overproduction of cholesterol, and interferes with compensatory increases in NE transmission.
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Affiliation(s)
- Thea Anderson
- Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Sumeet Sharma
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Michael A Kelberman
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Christopher Ware
- Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Nanxi Guo
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA
| | - Zhaohui Qin
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, USA
| | - David Weinshenker
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Marise B Parent
- Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
- Department of Psychology, Georgia State University, Georgia, USA
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Yan Y, He X, Xu Y, Peng J, Zhao F, Shao Y. Comparison between morphometry and radiomics: detecting normal brain aging based on grey matter. Front Aging Neurosci 2024; 16:1366780. [PMID: 38685908 PMCID: PMC11056505 DOI: 10.3389/fnagi.2024.1366780] [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: 01/07/2024] [Accepted: 04/04/2024] [Indexed: 05/02/2024] Open
Abstract
Objective Voxel-based morphometry (VBM), surface-based morphometry (SBM), and radiomics are widely used in the field of neuroimage analysis, while it is still unclear that the performance comparison between traditional morphometry and emerging radiomics methods in diagnosing brain aging. In this study, we aimed to develop a VBM-SBM model and a radiomics model for brain aging based on cognitively normal (CN) individuals and compare their performance to explore both methods' strengths, weaknesses, and relationships. Methods 967 CN participants were included in this study. Subjects were classified into the middle-aged group (n = 302) and the old-aged group (n = 665) according to the age of 66. The data of 360 subjects from the Alzheimer's Disease Neuroimaging Initiative were used for training and internal test of the VBM-SBM and radiomics models, and the data of 607 subjects from the Australian Imaging, Biomarker and Lifestyle, the National Alzheimer's Coordinating Center, and the Parkinson's Progression Markers Initiative databases were used for the external tests. Logistics regression participated in the construction of both models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the two model performances. The DeLong test was used to compare the differences in AUCs between models. The Spearman correlation analysis was used to observe the correlations between age, VBM-SBM parameters, and radiomics features. Results The AUCs of the VBM-SBM model and radiomics model were 0.697 and 0.778 in the training set (p = 0.018), 0.640 and 0.789 in the internal test set (p = 0.007), 0.736 and 0.737 in the AIBL test set (p = 0.972), 0.746 and 0.838 in the NACC test set (p < 0.001), and 0.701 and 0.830 in the PPMI test set (p = 0.036). Weak correlations were observed between VBM-SBM parameters and radiomics features (p < 0.05). Conclusion The radiomics model achieved better performance than the VBM-SBM model. Radiomics provides a good option for researchers who prioritize performance and generalization, whereas VBM-SBM is more suitable for those who emphasize interpretability and clinical practice.
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Affiliation(s)
| | | | | | | | | | - Yuan Shao
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
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Basaia S, Zavarella M, Rugarli G, Sferruzza G, Cividini C, Canu E, Cacciaguerra L, Bacigaluppi M, Martino G, Filippi M, Agosta F. Caudate functional networks influence brain structural changes with aging. Brain Commun 2024; 6:fcae116. [PMID: 38665962 PMCID: PMC11043654 DOI: 10.1093/braincomms/fcae116] [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: 08/17/2023] [Revised: 02/22/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
Neurogenesis decline with aging may be associated with brain atrophy. Subventricular zone neuron precursor cells possibly modulate striatal neuronal activity via the release of soluble molecules. Neurogenesis decay in the subventricular zone may result in structural alterations of brain regions connected to the caudate, particularly to its medial component. The aim of this study was to investigate how the functional organization of caudate networks relates to structural brain changes with aging. One hundred and fifty-two normal subjects were recruited: 52 young healthy adults (≤35 years old), 42 middle-aged (36 ≤ 60 years old) and 58 elderly subjects (≥60 years old). In young adults, stepwise functional connectivity was used to characterize regions that connect to the medial and lateral caudate at different levels of link-step distances. A statistical comparison between the connectivity of medial and lateral caudate in young subjects was useful to define medial and lateral caudate connected regions. Atrophy of medial and lateral caudate connected regions was estimated in young, middle-aged and elderly subjects using T1-weighted images. Results showed that middle-aged and elderly adults exhibited decreased stepwise functional connectivity at one-link step from the caudate, particularly in the frontal, parietal, temporal and occipital brain regions, compared to young subjects. Elderly individuals showed increased stepwise functional connectivity in frontal, parietal, temporal and occipital lobes compared to both young and middle-aged adults. Additionally, elderly adults displayed decreased stepwise functional connectivity compared to middle-aged subjects in specific parietal and subcortical areas. Moreover, in young adults, the medial caudate showed higher direct connectivity to the basal ganglia (left thalamus), superior, middle and inferior frontal and inferior parietal gyri (medial caudate connected region) relative to the lateral caudate. Considering the opposite contrast, lateral caudate showed stronger connectivity to the basal ganglia (right pallidum), orbitofrontal, rostral anterior cingulate and insula cortices (lateral caudate connected region) compared to medial caudate. In elderly subjects, the medial caudate connected region showed greater atrophy relative to the lateral caudate connected region. Brain regions linked to the medial caudate appear to be more vulnerable to aging than lateral caudate connected areas. The adjacency to the subventricular zone may, at least partially, explain these findings. Stepwise functional connectivity analysis can be useful to evaluate the role of the subventricular zone in network disruptions in age-related neurodegenerative disorders.
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Affiliation(s)
- Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Matteo Zavarella
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Giulia Rugarli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
| | - Giacomo Sferruzza
- Vita-Salute San Raffaele University, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neuroimmunology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Marco Bacigaluppi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neuroimmunology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Gianvito Martino
- Vita-Salute San Raffaele University, 20132 Milan, Italy
- Neuroimmunology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
- Vita-Salute San Raffaele University, 20132 Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
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Capogna E, Sørensen Ø, Watne LO, Roe J, Strømstad M, Idland AV, Halaas NB, Blennow K, Zetterberg H, Walhovd KB, Fjell AM, Vidal-Piñeiro D. Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583291. [PMID: 38496633 PMCID: PMC10942348 DOI: 10.1101/2024.03.04.583291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.
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Affiliation(s)
- Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - James Roe
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Marie Strømstad
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Ane Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Campus UllevÅl, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
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Maruoka H, Hattori T, Hase T, Takahashi K, Ohara M, Orimo S, Yokota T. Aberrant morphometric networks in Alzheimer's disease have hemispheric asymmetry and age dependence. Eur J Neurosci 2024; 59:1332-1347. [PMID: 38105486 DOI: 10.1111/ejn.16225] [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: 04/08/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is associated with abnormal accumulations of hyperphosphorylated tau and amyloid-β proteins, resulting in unique patterns of atrophy in the brain. We aimed to elucidate some characteristics of the AD's morphometric networks constructed by associating different morphometric features among brain areas and evaluating their relationship to Mini-Mental State Examination total score and age. Three-dimensional T1-weighted (3DT1) image data scanned by the same 1.5T magnetic resonance imaging (MRI) were obtained from 62 AD patients and 41 healthy controls (HCs) and were analysed by using FreeSurfer. The associations of the extracted six morphometric features between regions were estimated by correlation coefficients. The global and local graph theoretical measures for this network were evaluated. Associations between graph theoretical measures and age, sex and cognition were evaluated by multiple regression analysis in each group. Global measures of integration: global efficiency and mean information centrality were significantly higher in AD patients. Local measures of integration: node global efficiency and information centrality were significantly higher in the entorhinal cortex, fusiform gyrus and posterior cingulate cortex of AD patients but only in the left hemisphere. All global measures were correlated with age in AD patients but not in HCs. The information centrality was associated with age in AD's broad brain regions. Our results showed that altered morphometric networks due to AD are left-hemisphere dominant, suggesting that AD pathogenesis has a left-right asymmetry. Ageing has a unique impact on the morphometric networks in AD patients. The information centrality is a sensitive graph theoretical measure to detect this association.
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Affiliation(s)
- Hiroyuki Maruoka
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Neurology, Kanto Central Hospital, Tokyo, Japan
| | - Takaaki Hattori
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takeshi Hase
- Innovative Human Resource Development Division, Institute of Education, Tokyo Medical and Dental University, Tokyo, Japan
- Faculty of Pharmacy, Keio University, Tokyo, Japan
- Research, The Systems Biology Institute, Tokyo, Japan
- Research, SBX BioSciences, Vancouver, British Columbia, Canada
| | - Kunihiko Takahashi
- Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masahiro Ohara
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
| | - Satoshi Orimo
- Department of Neurology, Kanto Central Hospital, Tokyo, Japan
| | - Takanori Yokota
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Science, Tokyo Medical and Dental University, Tokyo, Japan
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Feng J, Huang Y, Zhang X, Yang Q, Guo Y, Xia Y, Peng C, Li C. Research and application progress of radiomics in neurodegenerative diseases. META-RADIOLOGY 2024; 2:100068. [DOI: 10.1016/j.metrad.2024.100068] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2025]
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Lindberg O, Ahlner F, Tsevis T, Pereira JB, Westman E, Skoog I, Wahlund LO. Effects of current alcohol use on brain volume among older adults in the Gothenburg H70 Birth Cohort study 2014-16. Eur Arch Psychiatry Clin Neurosci 2024; 274:363-373. [PMID: 37725137 PMCID: PMC10914911 DOI: 10.1007/s00406-023-01691-x] [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: 03/02/2023] [Accepted: 08/26/2023] [Indexed: 09/21/2023]
Abstract
Brain gray- and white matter changes is well described in alcohol-dependent elderly subjects; however, the effect of lower levels of alcohol consumption on the brain is poorly understood. We investigated the impact of different amounts of weekly alcohol consumption on brain structure in a population-based sample of 70-year-olds living in Gothenburg, Sweden. Cross-sectional data from 676 participants from The Gothenburg H70 Birth Cohort Study 2014-16 were included. Current alcohol consumers were divided into seven groups based on self-reported weekly amounts of alcohol consumption in grams (g) (0-50 g/week, used as reference group, 51-100 g/week, 101-150 g/week, 151-200 g/week, 201-250 g/week, 251-300 g/week, and > 300 g/week). Subcortical volumes and cortical thickness were assessed on T1-weighted structural magnetic resonance images using FreeSurfer 5.3, and white matter integrity assessed on diffusion tensor images, using tract-based statistics in FSL. General linear models were carried out to estimate associations between alcohol consumption and gray- and white matter changes in the brain. Self-reported consumption above 250 g/week was associated with thinning in the bilateral superior frontal gyrus, the right precentral gyrus, and the right lateral occipital cortex, in addition to reduced fractional anisotropy (FA) and increased mean diffusivity (MD) diffusively spread in many tracts all over the brain. No changes were found in subcortical gray matter structures. These results suggest that there is a non-linear relationship between alcohol consumption and structural brain changes, in which loss of cortical thickness only occur in non-demented 70-year-olds who consume more than 250 g/week.
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Affiliation(s)
- Olof Lindberg
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Neo Floor 7 SE, 141 83, Huddinge, Stockholm, Sweden.
- Neuropsychiatric Epidemiology, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Centre for Ageing and Health (AgeCap), Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
| | - Felicia Ahlner
- Neuropsychiatric Epidemiology, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Centre for Ageing and Health (AgeCap), Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Theofanis Tsevis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Neo Floor 7 SE, 141 83, Huddinge, Stockholm, Sweden
| | - Joana B Pereira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Neo Floor 7 SE, 141 83, Huddinge, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Neo Floor 7 SE, 141 83, Huddinge, Stockholm, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Centre for Ageing and Health (AgeCap), Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Neo Floor 7 SE, 141 83, Huddinge, Stockholm, Sweden
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Satizabal CL, Beiser AS, Fletcher E, Seshadri S, DeCarli C. A novel neuroimaging signature for ADRD risk stratification in the community. Alzheimers Dement 2024; 20:1881-1893. [PMID: 38147416 PMCID: PMC10984488 DOI: 10.1002/alz.13600] [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: 02/06/2023] [Revised: 11/20/2023] [Accepted: 11/21/2023] [Indexed: 12/28/2023]
Abstract
INTRODUCTION Early risk stratification for clinical dementia could lead to preventive therapies. We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer's disease (AD) and related dementias (ARDR). METHODS An MRI ADRD signature was derived from cortical thickness maps in Framingham Heart Study (FHS) participants with AD dementia and matched controls. The signature was related to the risk of ADRD and cognitive function in FHS. Results were replicated in the University of California Davis Alzheimer's Disease Research Center (UCD-ADRC) cohort. RESULTS Participants in the bottom quartile of the signature had more than three times increased risk for ADRD compared to those in the upper three quartiles (P < 0.001). Greater thickness in the signature was related to better general cognition (P < 0.01) and episodic memory (P = 0.01). Results replicated in UCD-ADRC. DISCUSSION We identified a robust neuroimaging biomarker for persons at increased risk of ADRD. Other cohorts will further test the validity of this biomarker.
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Affiliation(s)
- Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Alexa S. Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Evan Fletcher
- IDeA LaboratoryDepartment of NeurologyUniversity of California DavisDavisCaliforniaUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Charles DeCarli
- IDeA LaboratoryDepartment of NeurologyUniversity of California DavisDavisCaliforniaUSA
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Mao Z, Gao ZX, Ji T, Huan S, Yin GP, Chen L. Bidirectional two-sample mendelian randomization analysis identifies causal associations of MRI-based cortical thickness and surface area relation to NAFLD. Lipids Health Dis 2024; 23:58. [PMID: 38395962 PMCID: PMC10885469 DOI: 10.1186/s12944-024-02043-x] [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: 12/08/2023] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) patients have exhibited extra-hepatic neurological changes, but the causes and mechanisms remain unclear. This study investigates the causal effect of NAFLD on cortical structure through bidirectional two-sample Mendelian randomization analysis. METHODS Genetic data from 778,614 European individuals across four NAFLD studies were used to determine genetically predicted NAFLD. Abdominal MRI scans from 32,860 UK Biobank participants were utilized to evaluate genetically predicted liver fat and volume. Data from the ENIGMA Consortium, comprising 51,665 patients, were used to evaluate the associations between genetic susceptibility, NAFLD risk, liver fat, liver volume, and alterations in cortical thickness (TH) and surface area (SA). Inverse-variance weighted (IVW) estimation, Cochran Q, and MR-Egger were employed to assess heterogeneity and pleiotropy. RESULTS Overall, NAFLD did not significantly affect cortical SA or TH. However, potential associations were noted under global weighting, relating heightened NAFLD risk to reduced parahippocampal SA and decreased cortical TH in the caudal middle frontal, cuneus, lingual, and parstriangularis regions. Liver fat and volume also influenced the cortical structure of certain regions, although no Bonferroni-adjusted p-values reached significance. Two-step MR analysis revealed that liver fat, AST, and LDL levels mediated the impact of NAFLD on cortical structure. Multivariable MR analysis suggested that the impact of NAFLD on the cortical TH of lingual and parstriangularis was independent of BMI, obesity, hyperlipidemia, and diabetes. CONCLUSION This study provides evidence that NAFLD causally influences the cortical structure of the brain, suggesting the existence of a liver-brain axis in the development of NAFLD.
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Affiliation(s)
- Zun Mao
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, P. R. China
| | - Zhi-Xiang Gao
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, P. R. China
| | - Tong Ji
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, P. R. China
| | - Sheng Huan
- Department of Anesthesiology and Perioperative Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, P. R. China
| | - Guo-Ping Yin
- Department of Anesthesiology, Nanjing Second Hospital, Nanjing, 210000, P. R. China.
| | - Long Chen
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, P. R. China.
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82
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Wu HY, Huang CM, Hsu AL, Chen CN, Wu CW, Chen JH. Functional neuroplasticity of facilitation and interference effects on inhibitory control following 3-month physical exercise in aging. Sci Rep 2024; 14:3682. [PMID: 38355770 PMCID: PMC10866924 DOI: 10.1038/s41598-024-53974-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 02/07/2024] [Indexed: 02/16/2024] Open
Abstract
Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention; however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilitation and interference.
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Affiliation(s)
- Hong-Yi Wu
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Ai-Ling Hsu
- Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chiao-Nan Chen
- Department of Physical Therapy and Assistive Technology, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Changwei W Wu
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, New Taipei, Taiwan.
- Research Center of Sleep Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
| | - Jyh-Horng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
- Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
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Jia H, Li Z, Guo F, Hua Z, Zhou X, Li X, Li R, Liu Q, Liu Y, Dong H. Cortical structure and the risk of amyotrophic lateral sclerosis: A bidirectional Mendelian randomization study. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110872. [PMID: 37827425 DOI: 10.1016/j.pnpbp.2023.110872] [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: 02/15/2023] [Revised: 09/06/2023] [Accepted: 10/08/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Current observational studies indicate progressive brain atrophy is closely associated with the clinical feature of amyotrophic lateral sclerosis. However, it is unclear whether the changes in cortical structure are the cause or result of ALS. Our study aimed to investigate the causal relationship between cortical structure and ALS risk using a bidirectional two-sample MR study. METHODS We collected publicly available genome-wide association studies' summary statistics for cortical structure from UK Biobank and ENIGMA consortium (n = 33,992) and ALS from the Project MinE (n = 138,086). We used the inverse variance weighted method (IVW) as primary analysis in order to evaluate the causal effects. In addition, the weighted median and MR Egger methods were performed to ensure the robustness and reliability of the IVW results. RESULTS We found the decreased surface of the paracentral lobule and thickness of the frontal pole and middle temporal lobe were suggestively associated with an increased risk of ALS as well as the increased surface of medial orbitofrontal and middle temporal lobe. In another aspect, the causalities between the susceptibility to ALS and the volume of the transverse temporal gyrus and superior temporal gyrus were negative. Besides, the susceptibility to ALS might also contribute to an increased thickness of the postcentral gyrus and superior parietal gyrus. CONCLUSION In this two-sample MR analysis, we observed that multiple cortical brain regions are associated with a higher ALS risk. Further research into the underlying mechanisms is required to back up our findings.
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Affiliation(s)
- Hongning Jia
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China; Department of Neurology, Cangzhou Central Hospital, Cangzhou, Hebei, China
| | - Zhiguang Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; Department of Neurology, Xingtai Third Hospital, Xingtai, China
| | - Fei Guo
- Department of Basic Medicine, Xingtai Medical College, Xingtai, China
| | - Zixin Hua
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Xiaomeng Zhou
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Xin Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Rui Li
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Qi Liu
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China
| | - Yaling Liu
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China.
| | - Hui Dong
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China; The Key Laboratory of Clinical Neurology, Ministry of Education, Shijiazhuang, Hebei, China; Key Laboratory of Neurology of Hebei Province, Shijiazhuang, Hebei, China.
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Davidson TL, Stevenson RJ. Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction. Int J Mol Sci 2024; 25:1991. [PMID: 38396670 PMCID: PMC10888241 DOI: 10.3390/ijms25041991] [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: 01/03/2024] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.
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Affiliation(s)
- Terry L. Davidson
- Department of Neuroscience, Center for Neuroscience and Behavior, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA
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Ye Z, Zeng Q, Ning L, Huang W, Su Q. Systolic blood pressure is associated with abnormal alterations in brain cortical structure: Evidence from a Mendelian randomization study. Eur J Intern Med 2024; 120:92-98. [PMID: 37852841 DOI: 10.1016/j.ejim.2023.10.018] [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: 08/13/2023] [Revised: 09/09/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Hypertension has been recognized as a significant risk factor for cerebrovascular diseases and cognitive decline. However, the specific impact of hypertension, systolic/diastolic blood pressure, pulse pressure (PP) and mean arterial pressure (MAP) on brain cortical structure remains unclear. Mendelian randomization (MR) provides a robust approach to investigate the causal relationship between blood pressure components and brain cortical changes. METHODS In this MR study, data from large-scale genome-wide association studies for blood pressure components and neuroimaging were utilized to conduct our analyses. We leveraged genetic variants associated specifically with hypertension (122,620 cases and 332,683 controls), systolic (469,767 individuals), diastolic (490,469 individuals) blood pressure, PP (810,865 individuals) and MAP (over 1 million individuals) to evaluate their effects on brain cortex surficial area (51,665 individuals) and cortex thickness (51,665 individuals). RESULTS Our findings revealed a significant correlation between systolic blood pressure and abnormal reduction in brain cortex surficial area (β=-1330.69, 95% confident interval [CI]: -2655.35 to -6.02, p = 0.0489); however, no significant relationship was found between systolic blood pressure and brain cortex thickness (β=-0.0078, 95% CI: -0.0178 to 0.0022, p = 0.1287). Additionally, no significant associations were observed between hypertension (β=-200.05, p = 0.6884; β=-0.0051, p = 0.1179, respectively), diastolic blood pressure (β=-460.63, p = 0.5160; β=0.0047, p = 0.2448, respectively), PP (β=1041.84, p = 0.3725; β=-0.0112, p = 0.2212, respectively), MAP (β=-18.84, p = 0.8841; β=0.0002, p = 0.7654, respectively) and both brain cortex surficial area and brain cortex thickness. CONCLUSION Our MR study provides evidence supporting the hypothesis that systolic blood pressure, rather than diastolic blood pressure, PP or MAP, is associated with abnormal changes in brain cortical structure.
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Affiliation(s)
- Ziliang Ye
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Qing Zeng
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Limeng Ning
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Wanzhong Huang
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China
| | - Qiang Su
- Department of Cardiology, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, No. 85 Hedi Road, Nanning, Guangxi 530021, China.
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86
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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.
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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
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87
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Fjell AM. Aging Brain from a Lifespan Perspective. Curr Top Behav Neurosci 2024; 68:349-370. [PMID: 38797799 DOI: 10.1007/7854_2024_476] [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] [Indexed: 05/29/2024]
Abstract
Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.
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Affiliation(s)
- Anders Martin Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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88
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Dai Y, Hsu YC, Fernandes BS, Zhang K, Li X, Enduru N, Liu A, Manuel AM, Jiang X, Zhao Z. Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach. J Alzheimers Dis 2024; 97:1807-1827. [PMID: 38306043 PMCID: PMC11649026 DOI: 10.3233/jad-231020] [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] [Indexed: 02/03/2024]
Abstract
Background The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. Objective To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. Methods We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. Results We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Conclusions Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.
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Affiliation(s)
- Yulin Dai
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
| | - Yu-Chun Hsu
- Center for Secure Artificial Intelligence for Healthcare,
School of Biomedical Informatics, The University of Texas Health Science Center at
Houston, Houston, TX, USA
| | - Brisa S. Fernandes
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
| | - Kai Zhang
- Center for Secure Artificial Intelligence for Healthcare,
School of Biomedical Informatics, The University of Texas Health Science Center at
Houston, Houston, TX, USA
| | - Xiaoyang Li
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
- Department of Biostatistics and Data Science, School of
Public Health, The University of Texas Health Science Center at Houston, Houston,
TX, USA
| | - Nitesh Enduru
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
- Department of Epidemiology, Human Genetics and
Environmental Sciences, School of Public Health, The University of Texas Health
Science Center at Houston, Houston, TX, USA
| | - Andi Liu
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
- Department of Epidemiology, Human Genetics and
Environmental Sciences, School of Public Health, The University of Texas Health
Science Center at Houston, Houston, TX, USA
| | - Astrid M. Manuel
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
| | - Xiaoqian Jiang
- Center for Secure Artificial Intelligence for Healthcare,
School of Biomedical Informatics, The University of Texas Health Science Center at
Houston, Houston, TX, USA
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of
Biomedical Informatics, The University of Texas Health Science Center at Houston,
Houston, TX, USA
- Department of Epidemiology, Human Genetics and
Environmental Sciences, School of Public Health, The University of Texas Health
Science Center at Houston, Houston, TX, USA
- Department of Biomedical Informatics, Vanderbilt University
Medical enter, Nashville, TN, USA
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89
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Kim SA, Maeda M, Murata F, Fujii T, Ueda E, Ono R, Fukuda H. Impact of Concurrent Visual and Hearing Impairment on Incident Alzheimer's Disease: The LIFE Study. J Alzheimers Dis 2024; 98:197-207. [PMID: 38363608 PMCID: PMC10977410 DOI: 10.3233/jad-230806] [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] [Accepted: 12/30/2023] [Indexed: 02/17/2024]
Abstract
Background The prevalence of Alzheimer's disease (AD) is increasing in Japan due to population aging. The association between sensory impairment and incident AD remains unclear. Objective This study aimed to investigate the impact of sensory impairment on incident AD. Methods We analyzed residents of five municipalities participating in the Longevity Improvement & Fair Evidence (LIFE) Study. The participants comprised individuals who had newly applied for long-term care needs certification between 2017 and 2022 and had no cognitive impairment upon application or AD diagnosis within the preceding six months. Participants were classified according to sensory impairment status: visual impairment (VI), hearing impairment (HI), neither sensory impairment (NSI), and dual sensory impairment (DSI). The month succeeding the certification application was set as the index month, and the interval from that month until AD onset was assessed. Multivariable Cox proportional hazards analysis was performed to calculate the risk of AD onset according to sensory impairment status while adjusting for sex, age, dependence level, self-reliance level, and comorbidities. Results Among 14,186 participants, we identified 1,194 (8.4%) who developed AD over a median follow-up period of 22.6 months. VI and HI only were not associated with incident AD. However, DSI conferred a significantly higher risk (HR: 1.6, CI: 1.1-2.2, p = 0.008) of AD onset than NSI. Conclusions Individuals with concurrent DSI have a higher risk of developing AD than those with single or NSI. Preventing and treating sensory impairment may not only improve functional outcomes, but could also help to reduce the future risk of AD.
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Affiliation(s)
- Sung-a Kim
- Department of Healthcare Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- St. Mary’s Research Center, Kurume, Japan
| | - Megumi Maeda
- Department of Healthcare Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Fumiko Murata
- Department of Healthcare Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takayuki Fujii
- Department of Neurology, Neurological Institute, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Emi Ueda
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Rei Ono
- Kobe University Graduate School of Health Sciences, Hyogo, Japan
- Department of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan
| | - Haruhisa Fukuda
- Department of Healthcare Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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90
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Moon HS, Mahzarnia A, Stout J, Anderson RJ, Strain M, Tremblay JT, Han ZY, Niculescu A, MacFarlane A, King J, Ashley-Koch A, Clark D, Lutz MW, Badea A. Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics. Brain Struct Funct 2024; 229:231-249. [PMID: 38091051 PMCID: PMC11082910 DOI: 10.1007/s00429-023-02731-x] [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: 08/08/2023] [Accepted: 11/03/2023] [Indexed: 01/31/2024]
Abstract
APOE allelic variation is critical in brain aging and Alzheimer's disease (AD). The APOE2 allele associated with cognitive resilience and neuroprotection against AD remains understudied. We employed a multipronged approach to characterize the transition from middle to old age in mice with APOE2 allele, using behavioral assessments, image-derived morphometry and diffusion metrics, structural connectomics, and blood transcriptomics. We used sparse multiple canonical correlation analyses (SMCCA) for integrative modeling, and graph neural network predictions. Our results revealed brain sub-networks associated with biological traits, cognitive markers, and gene expression. The cingulate cortex emerged as a critical region, demonstrating age-associated atrophy and diffusion changes, with higher fractional anisotropy in males and middle-aged subjects. Somatosensory and olfactory regions were consistently highlighted, indicating age-related atrophy and sex differences. The hippocampus exhibited significant volumetric changes with age, with differences between males and females in CA3 and CA1 regions. SMCCA underscored changes in the cingulate cortex, somatosensory cortex, olfactory regions, and hippocampus in relation to cognition and blood-based gene expression. Our integrative modeling in aging APOE2 carriers revealed a central role for changes in gene pathways involved in localization and the negative regulation of cellular processes. Our results support an important role of the immune system and response to stress. This integrative approach offers novel insights into the complex interplay among brain connectivity, aging, and sex. Our study provides a foundation for understanding the impact of APOE2 allele on brain aging, the potential for detecting associated changes in blood markers, and revealing novel therapeutic intervention targets.
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Affiliation(s)
- Hae Sol Moon
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Ali Mahzarnia
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Jacques Stout
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, USA
| | - Robert J Anderson
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Madison Strain
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Jessica T Tremblay
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Zay Yar Han
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Andrei Niculescu
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Anna MacFarlane
- Department of Neuroscience, Duke University, Durham, NC, USA
| | - Jasmine King
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Allison Ashley-Koch
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Darin Clark
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Michael W Lutz
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
| | - Alexandra Badea
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA.
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, USA.
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA.
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91
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Elliott ML, Nielsen JA, Hanford LC, Hamadeh A, Hilbert T, Kober T, Dickerson BC, Hyman BT, Mair RW, Eldaief MC, Buckner RL. Precision Brain Morphometry Using Cluster Scanning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.23.23300492. [PMID: 38234845 PMCID: PMC10793507 DOI: 10.1101/2023.12.23.23300492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.
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Affiliation(s)
- Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jared A Nielsen
- Department of Psychology, Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Lindsay C Hanford
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Aya Hamadeh
- Baylor College of Medicine, Houston, TX 77030
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Bradley T Hyman
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
| | - Ross W Mair
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Athinoula A. Martinos Center for Biomedical Imaging
| | - Mark C Eldaief
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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92
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Moon HS, Mahzarnia A, Stout J, Anderson RJ, Badea CT, Badea A. Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.13.571574. [PMID: 38168445 PMCID: PMC10760088 DOI: 10.1101/2023.12.13.571574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Alzheimer's disease (AD) remains one of the most extensively researched neurodegenerative disorders due to its widespread prevalence and complex risk factors. Age is a crucial risk factor for AD, which can be estimated by the disparity between physiological age and estimated brain age. To model AD risk more effectively, integrating biological, genetic, and cognitive markers is essential. Here, we utilized mouse models expressing the major APOE human alleles and human nitric oxide synthase 2 to replicate genetic risk for AD and a humanized innate immune response. We estimated brain age employing a multivariate dataset that includes brain connectomes, APOE genotype, subject traits such as age and sex, and behavioral data. Our methodology used Feature Attention Graph Neural Networks (FAGNN) for integrating different data types. Behavioral data were processed with a 2D Convolutional Neural Network (CNN), subject traits with a 1D CNN, brain connectomes through a Graph Neural Network using quadrant attention module. The model yielded a mean absolute error for age prediction of 31.85 days, with a root mean squared error of 41.84 days, outperforming other, reduced models. In addition, FAGNN identified key brain connections involved in the aging process. The highest weights were assigned to the connections between cingulum and corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex. Our study demonstrates the feasibility of predicting brain age in models of aging and genetic risk for AD. To verify the validity of our findings, we compared Fractional Anisotropy (FA) along the tracts of regions with the highest connectivity, the Return-to-Origin Probability (RTOP), Return-to-Plane Probability (RTPP), and Return-to-Axis Probability (RTAP), which showed significant differences between young, middle-aged, and old age groups. Younger mice exhibited higher FA, RTOP, RTAP, and RTPP compared to older groups in the selected connections, suggesting that degradation of white matter tracts plays a critical role in aging and for FAGNN's selections. Our analysis suggests a potential neuroprotective role of APOE2, relative to APOE3 and APOE4, where APOE2 appears to mitigate age-related changes. Our findings highlighted a complex interplay of genetics and brain aging in the context of AD risk modeling.
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Affiliation(s)
- Hae Sol Moon
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Ali Mahzarnia
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Jacques Stout
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Robert J Anderson
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Cristian T. Badea
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Alexandra Badea
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Quantitative Imaging and Analysis Laboratory, Department of Radiology, Duke University School of Medicine, Durham, NC, USA
- Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, USA
- Department of Neurology, Duke University School of Medicine, Durham, NC, USA
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93
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Wang D, Xu K, Dang M, Sang F, Chen K, Zhang Z, Li X. Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly. Cereb Cortex 2023; 33:11329-11338. [PMID: 37859548 PMCID: PMC11486686 DOI: 10.1093/cercor/bhad369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/18/2023] [Accepted: 09/19/2023] [Indexed: 10/21/2023] Open
Abstract
It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.
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Affiliation(s)
- Dandan Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Kai Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- School of Artificial Intelligence, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Mingxi Dang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Kewei Chen
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Banner Alzheimer’s Institute, Phoenix, AZ 85006, United States
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
- Beijing Aging Brain Rejuvenation Initiative (BABRI) Center, Beijing Normal University, No. 19, Xinjiekouwai St, Haidian District, Beijing, 100875, P.R. China
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94
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Aksnes M, Capogna E, Vidal-Piñeiro D, Chaudhry FA, Myrstad M, Idland AV, Halaas NB, Dakhil S, Blennow K, Zetterberg H, Walhovd KB, Watne LO, Fjell AM. Matrix metalloproteinases are associated with brain atrophy in cognitively unimpaired individuals. Neurobiol Aging 2023; 131:11-23. [PMID: 37549446 DOI: 10.1016/j.neurobiolaging.2023.05.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/28/2023] [Accepted: 05/20/2023] [Indexed: 08/09/2023]
Abstract
Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been linked to age-related neurodegeneration and Alzheimer's disease (AD), but their role in normal aging is poorly understood. We used linear mixed models to determine if baseline or rate of yearly change in cerebrospinal fluid (CSF) levels of MMP-2; MMP-3; MMP-10; TIMP-123 (composite of TIMP-1, TIMP-2, and TIMP-3); or TIMP-4 predicted changes in bilateral entorhinal cortex thickness, hippocampal volume, or lateral ventricle volume in cognitively unimpaired individuals. We also assessed effects on the CSF AD biomarkers amyloid-β42 and phosphorylated tau181. Low baseline levels of MMP-3 predicted larger ventricle volumes and more entorhinal cortex thinning. Increased CSF MMP-2 levels over time predicted more entorhinal thinning, hippocampal atrophy, and ventricular expansion, while increased TIMP-123 over time predicted ventricular expansion. No MMP/TIMPs predicted changes in CSF AD biomarkers. Notably, we show for the first time that longitudinal increases in MMP-2 and TIMP-123 levels may predict age-associated brain atrophy. In conclusion, MMPs and TIMPs may play a role in brain atrophy in cognitively unimpaired aging.
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Affiliation(s)
- Mari Aksnes
- Department of Geriatric Medicine, University of Oslo, Oslo, Norway.
| | - Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Farrukh Abbas Chaudhry
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Marius Myrstad
- Department of Internal Medicine, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway; Department of Medical Research, Bærum Hospital, Vestre Viken Hospital Trust, Gjettum, Norway
| | - Ane-Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Shams Dakhil
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Center for Neurodegenerative Diseases, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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95
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Fjell AM, Sørensen Ø, Wang Y, Amlien IK, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demuth I, Drevon CA, Ebmeier KP, Ghisletta P, Kievit R, Kühn S, Madsen KS, Mowinckel AM, Nyberg L, Sexton CE, Solé-Padullés C, Vidal-Piñeiro D, Wagner G, Watne LO, Walhovd KB. No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy. Nat Hum Behav 2023; 7:2008-2022. [PMID: 37798367 PMCID: PMC10663160 DOI: 10.1038/s41562-023-01707-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 08/31/2023] [Indexed: 10/07/2023]
Abstract
Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.
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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - Ilja Demuth
- Department of Endocrinology and Metabolic Diseases (including Division of Lipid Metabolism), Biology of Aging Working Group, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christian A Drevon
- Vitas AS, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Rogier Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Claire E Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK
- Global Brain Health Institute, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Alzheimer's Association, Chicago, IL, USA
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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96
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Demnitz N, Hulme OJ, Siebner HR, Kjaer M, Ebmeier KP, Boraxbekk CJ, Gillan CM. Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts. Neurobiol Aging 2023; 131:115-123. [PMID: 37619515 DOI: 10.1016/j.neurobiolaging.2023.07.023] [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: 02/09/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 08/26/2023]
Abstract
Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r = .37, p < 0.001; Denmark: r = .27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r = .10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.
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Affiliation(s)
- Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark.
| | - Oliver J Hulme
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; London Mathematical Laboratory, London, UK; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael Kjaer
- Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Center for Healthy Aging, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Department of Radiation Sciences, Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Claire M Gillan
- School of Psychology, Trinity College Dublin, Dublin, Ireland; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
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97
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Shoukat S, Zia MA, Uzair M, Alsubki RA, Sajid K, Shoukat S, Attia KA, Fiaz S, Ali S, Kimiko I, Ali GM. Synergistic neuroprotection by phytocompounds of Bacopa monnieri in scopolamine-induced Alzheimer's disease mice model. Mol Biol Rep 2023; 50:7967-7979. [PMID: 37535247 DOI: 10.1007/s11033-023-08674-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Accepted: 07/07/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND Millions of people around the globe are affected by Alzheimer's disease (AD). This crippling condition has no treatment despite intensive studies. Some phytocompounds have been shown to protect against Alzheimer's in recent studies. METHODS Thus, this work aimed to examine Bacopa monnieri phytocompounds' synergistic effects on neurodegeneration, antioxidant activity, and cognition in the scopolamine-induced AD mice model. The toxicity study of two phytocompounds: quercetin and bacopaside X revealed an LD50 of more than 2000 mg/kg since no deaths occurred. RESULTS The neuroprotection experiment consists of 6 groups i.e., control (saline), scopolamine (1 mg/kg), donepezil (5 mg/kg), Q (25 mg/kg), BX (20 mg/kg), and Q + BX (25 mg/kg + 20 mg/kg). Visual behavioral assessment using the Morris water maze showed that animals in the diseased model group (scopolamine) moved more slowly toward the platform and exhibited greater thigmotaxis behavior than the treatment and control groups. Likewise, the concentration of biochemical NO, GSH, and MDA improved in treatment groups concerning the diseased group. mRNA levels of different marker genes including ChAT, IL-1α, IL-1 β, TNF α, tau, and β secretase (BACE1) improved in treatment groups with respect to the disease group. CONCLUSION Both bacopaside X and quercetin synergistically have shown promising results in neuroprotection. Therefore, it is suggested that Q and BX may work synergistically due to their antioxidant and neuroprotective property.
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Affiliation(s)
- Shehla Shoukat
- Department of Plant Genomics and Biotechnology, PARC Institute of Advanced Studies in Agriculture, Affiliated with Quaid-e-Azam University, National Agriculture Research Centre, Islamabad, Pakistan.
| | - Muhammad Amir Zia
- National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre, Islamabad, Pakistan
| | - Muhammad Uzair
- National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre, Islamabad, Pakistan
| | - Roua A Alsubki
- Department of Clinical Laboratory Science, College of Applied Medical Sciences, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
| | - Kaynat Sajid
- Department of Biotechnology, University of Gujrat, Gujrat, Pakistan
| | - Sana Shoukat
- Centre for Applied Molecular Biology (CAMB), University of the Punjab, Lahore, Pakistan
| | - Kotb A Attia
- Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
| | - Sajid Fiaz
- Department of Plant Breeding and Genetics, University of Haripur, Haripur, Pakistan
| | - Shaukat Ali
- National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre, Islamabad, Pakistan.
| | - Itoh Kimiko
- Department of Plant Breeding and Genetics, University of Haripur, Haripur, Pakistan
- Institute of Science and Technology, Niigata University, Ikarashi-2, Nishi-ku, Niigata, 950-2181, Japan
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98
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Walhovd KB, Lövden M, Fjell AM. Timing of lifespan influences on brain and cognition. Trends Cogn Sci 2023; 27:901-915. [PMID: 37563042 DOI: 10.1016/j.tics.2023.07.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/04/2023] [Accepted: 07/04/2023] [Indexed: 08/12/2023]
Abstract
Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Martin Lövden
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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99
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Li T, Tao X, Sun R, Han C, Li X, Zhu Z, Li W, Huang P, Gong W. Cognitive-exercise dual-task intervention ameliorates cognitive decline in natural aging rats via inhibiting the promotion of LncRNA NEAT1/miR-124-3p on caveolin-1-PI3K/Akt/GSK3β Pathway. Brain Res Bull 2023; 202:110761. [PMID: 37714275 DOI: 10.1016/j.brainresbull.2023.110761] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/09/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023]
Abstract
Aging-related cognitive impairment (ARCI) is rapidly becoming a healthcare priority. However, there is currently no excellent cure for it. Cognitive-exercise dual-task intervention (CEDI) is a promising method to improve ARCI, while the underlying mechanisms remain unclear. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are involved in the onset, development, and rehabilitation of ARCI. This study aimed to investigate the effects of CEDI and the role of regulation of the lncRNA NEAT1/miR-124-3p on the caveolin-1-PI3K/Akt/GSK3β pathway in CEDI improving cognitive function. Forty 18-month-old natural aging rats were randomly assigned to four groups: exercise training group, cognitive training group, CEDI group, and aging control group, and underwent 12 weeks of intervention. A novel object recognition test was performed to determine the cognitive function, and the hippocampus was separated three days after the behavioral tests for further molecular detection. In an in vitro study, the mouse hippocampal neuronal cell line HT22 was cultured. MiR-124-3p and lncRNA NEAT1 were over-expressed or down-expressed, respectively. The expressions of related proteins, lncRNA, and miRNA were examined by WB and/or qRT-PCR. The results showed that compared with the aging control group, the CEDI group had a higher discrimination index, and significantly decreased the expressions of lncRNA NEAT1, and the protein expressions of caveolin-1 and p-GSK3β, while significantly increased the expressions of miR-124-3p, and the protein expressions of p-PI3K and p-Akt. Inhibition of the lncRNA NEAT1 could significantly increase the protein expressions of p-PI3K and p-Akt in HT22 cells. Upregulation of miR-124-3p decreased the protein expressions of caveolin-1 and p-GSK3β, and increased the protein expressions of p-PI3K and p-Akt significantly. Inhibition of miR-124-3p had the opposite effects. Our study demonstrated that CEDI improved cognitive function in aging rats better than a single intervention. The mechanisms of cognitive improvement could be related to the regulation of the lncRNA NEAT1/miR-124-3p on the caveolin-1-PI3K/Akt/GSK3β pathway.
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Affiliation(s)
- Tiancong Li
- Beijing Rehabilitation Hospital, Beijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China
| | - Xue Tao
- Department of Research, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Ruifeng Sun
- Beijing Rehabilitation Hospital, Beijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China
| | - Conglin Han
- Rehabilitation Medicine Academy, Weifang Medical University, Weifang, Shandong, China
| | - Xiaoling Li
- Department of Neurological Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Ziman Zhu
- Beijing Rehabilitation Hospital, Beijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China
| | - Wenshan Li
- Beijing Rehabilitation Hospital, Beijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China
| | - Peiling Huang
- Department of Neurological Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Weijun Gong
- Beijing Rehabilitation Hospital, Beijing Rehabilitation Medicine Academy, Capital Medical University, Beijing, China; Department of Neurological Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
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100
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Cong YF, Liu FW, Xu L, Song SS, Shen XR, Liu D, Hou XQ, Zhang HT. Rolipram Ameliorates Memory Deficits and Depression-Like Behavior in APP/PS1/tau Triple Transgenic Mice: Involvement of Neuroinflammation and Apoptosis via cAMP Signaling. Int J Neuropsychopharmacol 2023; 26:585-598. [PMID: 37490542 PMCID: PMC10519811 DOI: 10.1093/ijnp/pyad042] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 07/24/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND Alzheimer disease (AD) and depression often cooccur, and inhibition of phosphodiesterase-4 (PDE4) has been shown to ameliorate neurodegenerative illness. Therefore, we explored whether PDE4 inhibitor rolipram might also improve the symptoms of comorbid AD and depression. METHODS APP/PS1/tau mice (10 months old) were treated with or without daily i.p. injections of rolipram for 10 days. The animal groups were compared in behavioral tests related to learning, memory, anxiety, and depression. Neurochemical measures were conducted to explore the underlying mechanism of rolipram. RESULTS Rolipram attenuated cognitive decline as well as anxiety- and depression-like behaviors. These benefits were attributed at least partly to the downregulation of amyloid-β, Amyloid precursor protein (APP), and Presenilin 1 (PS1); lower tau phosphorylation; greater neuronal survival; and normalized glial cell function following rolipram treatment. In addition, rolipram upregulated B-cell lymphoma-2 (Bcl-2) and downregulated Bcl-2-associated X protein (Bax) to reduce apoptosis; it also downregulated interleukin-1β, interleukin-6, and tumor necrosis factor-α to restrain neuroinflammation. Furthermore, rolipram increased cAMP, PKA, 26S proteasome, EPAC2, and phosphorylation of ERK1/2 while decreasing EPAC1. CONCLUSIONS Rolipram may mitigate cognitive deficits and depression-like behavior by reducing amyloid-β pathology, tau phosphorylation, neuroinflammation, and apoptosis. These effects may be mediated by stimulating cAMP/PKA/26S and cAMP/exchange protein directly activated by cAMP (EPAC)/ERK signaling pathways. This study suggests that PDE4 inhibitor rolipram can be an effective target for treatment of comorbid AD and depression.
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Affiliation(s)
- Yi-Fan Cong
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Fu-Wang Liu
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Li Xu
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Shuang-Shuang Song
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Xu-Ri Shen
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Dong Liu
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Xue-Qin Hou
- Institute of Pharmacology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai’an, Shandong, P.R. China
| | - Han-Ting Zhang
- Department of Pharmacology, School of Pharmacy, Qingdao University, Qingdao, Shandong, P.R. China
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