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Jiao B, Ouyang Z, Liu Q, Xu T, Wan M, Ma G, Zhou L, Guo J, Wang J, Tang B, Zhao Z, Shen L. Integrated analysis of gut metabolome, microbiome, and brain function reveal the role of gut-brain axis in longevity. Gut Microbes 2024; 16:2331434. [PMID: 38548676 PMCID: PMC10984123 DOI: 10.1080/19490976.2024.2331434] [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: 10/09/2023] [Accepted: 03/13/2024] [Indexed: 04/02/2024] Open
Abstract
The role of microbiota-gut-brain axis in modulating longevity remains undetermined. Here, we performed a multiomics analysis of gut metagenomics, gut metabolomics, and brain functional near-infrared spectroscopy (fNIRS) in a cohort of 164 participants, including 83 nonagenarians (NAs) and 81 non-nonagenarians (NNAs) matched with their spouses and offspring. We found that 438 metabolites were significantly different between the two groups; among them, neuroactive compounds and anti-inflammatory substances were enriched in NAs. In addition, increased levels of neuroactive metabolites in NAs were significantly associated with NA-enriched species that had three corresponding biosynthetic potentials: Enterocloster asparagiformis, Hungatella hathewayi and Oxalobacter formigenes. Further analysis showed that the altered gut microbes and metabolites were linked to the enhanced brain connectivity in NAs, including the left dorsolateral prefrontal cortex (DLPFC)-left premotor cortex (PMC), left DLPFC-right primary motor area (M1), and right inferior frontal gyrus (IFG)-right M1. Finally, we found that neuroactive metabolites, altered microbe and enhanced brain connectivity contributed to the cognitive preservation in NAs. Our findings provide a comprehensive understanding of the microbiota-gut-brain axis in a long-lived population and insights into the establishment of a microbiome and metabolite homeostasis that can benefit human longevity and cognition by enhancing functional brain connectivity.
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Affiliation(s)
- Bin Jiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Centre of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Ziyu Ouyang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qianqian Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Tianyan Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Meidan Wan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Guangrong Ma
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Centre of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Junling Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Centre of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Centre of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha, China
| | - Zhixiang Zhao
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Engineering Research Centre of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha, China
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Waner JL, Hausman HK, Kraft JN, Hardcastle C, Evangelista ND, O'Shea A, Albizu A, Boutzoukas EM, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, DeKosky ST, Hishaw GA, Wu SS, Marsiske M, Cohen R, Alexander GE, Porges EC, Woods AJ. Connecting memory and functional brain networks in older adults: a resting-state fMRI study. GeroScience 2023; 45:3079-3093. [PMID: 37814198 PMCID: PMC10643735 DOI: 10.1007/s11357-023-00967-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 09/29/2023] [Indexed: 10/11/2023] Open
Abstract
Limited research exists on the association between resting-state functional network connectivity in the brain and learning and memory processes in advanced age. This study examined within-network connectivity of cingulo-opercular (CON), frontoparietal control (FPCN), and default mode (DMN) networks, and verbal and visuospatial learning and memory in older adults. Across domains, we hypothesized that greater CON and FPCN connectivity would associate with better learning, and greater DMN connectivity would associate with better memory. A total of 330 healthy older adults (age range = 65-89) underwent resting-state fMRI and completed the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) in a randomized clinical trial. Total and delayed recall scores were assessed from baseline data, and a learning ratio calculation was applied to participants' scores. Average CON, FPCN, and DMN connectivity values were obtained with CONN Toolbox. Hierarchical regressions controlled for sex, race, ethnicity, years of education, and scanner site, as this was a multi-site study. Greater within-network CON connectivity was associated with better verbal learning (HVLT-R Total Recall, Learning Ratio), visuospatial learning (BVMT-R Total Recall), and visuospatial memory (BVMT-R Delayed Recall). Greater FPCN connectivity was associated with better visuospatial learning (BVMT-R Learning Ratio) but did not survive multiple comparison correction. DMN connectivity was not associated with these measures of learning and memory. CON may make small but unique contributions to learning and memory across domains, making it a valuable target in future longitudinal studies and interventions to attenuate memory decline. Further research is necessary to understand the role of FPCN in learning and memory.
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Affiliation(s)
- Jori L Waner
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Jessica N Kraft
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Cheshire Hardcastle
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Emanuel M Boutzoukas
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Emily J Van Etten
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Pradyumna K Bharadwaj
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Hyun Song
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Samantha G Smith
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Steven T DeKosky
- Department of Neurology and McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Georg A Hishaw
- Department of Psychiatry, College of Medicine, University of Arizona, Tucson, AZ, USA
- Department of Neurology, College of Medicine, University of Arizona, Tucson, AZ, USA
| | - Samuel S Wu
- Department of Biostatistics, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Michael Marsiske
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Ronald Cohen
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Gene E Alexander
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Eric C Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, PO Box 100196, 1249 Center Drive, Gainesville, FL, 32610-0165, USA.
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA.
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Yang X, Wu H, Song Y, Chen S, Ge H, Yan Z, Yuan Q, Liang X, Lin X, Chen J. Functional MRI-specific alterations in frontoparietal network in mild cognitive impairment: an ALE meta-analysis. Front Aging Neurosci 2023; 15:1165908. [PMID: 37448688 PMCID: PMC10336325 DOI: 10.3389/fnagi.2023.1165908] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/16/2023] [Indexed: 07/15/2023] Open
Abstract
Background Mild cognitive impairment (MCI) depicts a transitory phase between healthy elderly and the onset of Alzheimer's disease (AD) with worsening cognitive impairment. Some functional MRI (fMRI) research indicated that the frontoparietal network (FPN) could be an essential part of the pathophysiological mechanism of MCI. However, damaged FPN regions were not consistently reported, especially their interactions with other brain networks. We assessed the fMRI-specific anomalies of the FPN in MCI by analyzing brain regions with functional alterations. Methods PubMed, Embase, and Web of Science were searched to screen neuroimaging studies exploring brain function alterations in the FPN in MCI using fMRI-related indexes, including the amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity. We integrated distinctive coordinates by activating likelihood estimation, visualizing abnormal functional regions, and concluding functional alterations of the FPN. Results We selected 29 studies and found specific changes in some brain regions of the FPN. These included the bilateral dorsolateral prefrontal cortex, insula, precuneus cortex, anterior cingulate cortex, inferior parietal lobule, middle temporal gyrus, superior frontal gyrus, and parahippocampal gyrus. Any abnormal alterations in these regions depicted interactions between the FPN and other networks. Conclusion The study demonstrates specific fMRI neuroimaging alterations in brain regions of the FPN in MCI patients. This could provide a new perspective on identifying early-stage patients with targeted treatment programs. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023432042, identifier: CRD42023432042.
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Affiliation(s)
- Xinyi Yang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Huimin Wu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Song
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Shanshan Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Honglin Ge
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zheng Yan
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qianqian Yuan
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xuhong Liang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xingjian Lin
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Department of Radiology, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
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Deery HA, Di Paolo R, Moran C, Egan GF, Jamadar SD. The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging. Psychophysiology 2023; 60:e14159. [PMID: 36106762 PMCID: PMC10909558 DOI: 10.1111/psyp.14159] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 12/23/2022]
Abstract
The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.
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Affiliation(s)
- Hamish A. Deery
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Robert Di Paolo
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Chris Moran
- Peninsula Clinical School, Central Clinical SchoolMonash UniversityFrankstonVictoriaAustralia
- Department of Geriatric MedicinePeninsula HealthFrankstonVictoriaAustralia
| | - Gary F. Egan
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
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Resting-state network connectivity changes in drug-naive Parkinson's disease patients with probable REM sleep behavior disorder. J Neural Transm (Vienna) 2023; 130:43-51. [PMID: 36474090 DOI: 10.1007/s00702-022-02565-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/01/2022] [Indexed: 12/12/2022]
Abstract
Epidemiological studies have shown that Parkinson's disease (PD) patients with probable REM sleep behavior disorder (pRBD) present an increased risk of worse cognitive progression over the disease course. The aim of this study was to investigate, using resting-state functional MRI (RS-fMRI), the functional connectivity (FC) changes associated with the presence of pRBD in a cohort of newly diagnosed, drug-naive and cognitively unimpaired PD patients compared to healthy controls (HC). Fifty-six drug-naïve patients (25 PD-pRBD+ and 31 PD-pRBD-) and 23 HC underwent both RS-fMRI and clinical assessment. Single-subject and group-level independent component analysis was used to analyze intra- and inter-network FC differences within the major large-scale neurocognitive networks, namely the default mode (DMN), frontoparietal (FPN), salience (SN) and executive-control (ECN) networks. Widespread FC changes were found within the most relevant neurocognitive networks in PD patients compared to HC. Moreover, PD-pRBD+ patients showed abnormal intrinsic FC within the DMN, ECN and SN compared to PD-pRBD-. Finally, PD-pRBD+ patients showed functional decoupling between left and right FPN. In the present study, we revealed that FC changes within the most relevant neurocognitive networks are already detectable in early drug-naïve PD patients, even in the absence of clinical overt cognitive impairment. These changes are even more evident in PD patients with RBD, potentially leading to profound impairment in cognitive processing and cognitive/behavioral integration, as well as to fronto-striatal maladaptive compensatory mechanisms.
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Pirani A, Nasreddine Z, Neviani F, Fabbo A, Rocchi MB, Bertolotti M, Tulipani C, Galassi M, Belvedere Murri M, Neri M. MoCA 7.1: Multicenter Validation of the First Italian Version of Montreal Cognitive Assessment. J Alzheimers Dis Rep 2022; 6:509-520. [PMID: 36186724 PMCID: PMC9484132 DOI: 10.3233/adr-210053] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 07/13/2022] [Indexed: 12/04/2022] Open
Abstract
Background: The early detection of neurocognitive disorders, especially when mild, is a key issue of health care systems including the Italian Dementia National Plan. The Mini-Mental State Examination (MMSE), i.e., the reference screening tool for dementia in Italian Memory Clinics, has low sensitivity in detecting mild cognitive impairment (MCI) or mild dementia. Objective: Availability of a 10-minute screening test sensitive to MCI and mild dementia, such as the Montreal Cognitive Assessment (MoCA), is relevant in the field. This study presents initial validity and reliability data for the Italian version of MoCA 7.1 that is being collected as part of a large ongoing longitudinal study to evaluate the rate of incident MCI and dementia in older adults. Methods: MoCA 7.1 and MMSE were administered to cognitive impaired patients (n = 469; 214 with MCI, 255 with dementia; mean age: 75.5; 52% females,) and healthy older adults (n = 123, mean age: 69.7, 64 % females). Results: Test-retest (0.945, p < 0.001) and inter-rater (0.999, p < 0.001) reliability of MoCA 7.1, assessed on randomly selected participants with normal cognition, MCI, dementia, were significant. MoCA 7.1 showed adequate sensitivity (95.3%) and specificity (84.5%) in detecting MCI compared to MMSE (sensitivity: 53.8%; specificity: 87.5%). The Area Under the Curve of MoCA 7.1 was significantly greater than that of MMSE (0.963 versus 0.742). MoCA 7.1 showed similar results in detecting both MCI and dementia. Conclusion: MoCA 7.1 is a reliable and useful tool that can aid in the diagnosis of MCI and dementia in the Italian population.
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Affiliation(s)
- Alessandro Pirani
- Center for Cognitive Disorders and Dementia, Health County of Ferrara, Cento, Italy
- Alzheimer’s Association “Francesco Mazzuca”, Cento, (Fe), Italy
| | | | - Francesca Neviani
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
| | - Andrea Fabbo
- Dementia Program, HealthTrust, Health County of Modena, Italy
| | | | - Marco Bertolotti
- Division of Geriatric Medicine, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia and University Hospital of Modena, Modena, Italy
- Center for Gerontological Evaluation and Research, University of Modena and Reggio Emilia, Modena, Italy
| | - Cristina Tulipani
- Center for Cognitive Disorders and Dementia, Health County of Ferrara, Cento, Italy
- Alzheimer’s Association “Francesco Mazzuca”, Cento, (Fe), Italy
| | - Matteo Galassi
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
| | - Martino Belvedere Murri
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Italy
| | - Mirco Neri
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
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7
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Zhang X, Guan Q, Li Y, Zhang J, Zhu W, Luo Y, Zhang H. Aberrant Cross-Tissue Functional Connectivity in Alzheimer’s Disease: Static, Dynamic, and Directional Properties. J Alzheimers Dis 2022; 88:273-290. [DOI: 10.3233/jad-215649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: BOLD signals in the gray matter (GM) and white matter (WM) are tightly coupled. However, our understanding of the cross-tissue functional network in Alzheimer’s disease (AD) is limited. Objective: We investigated the changes of cross-tissue functional connectivity (FC) metrics for the GM regions susceptible to AD damage. Methods: For each GM region in the default mode (DMN) and limbic networks, we obtained its low-order static FC with any WM region, and the high-order static FC between any two WM regions based on their FC pattern similarity with multiple GM regions. The dynamic and directional properties of cross-tissue FC were then acquired, specifically for the regional pairs whose low- or high-order static FCs showed significant differences between AD and normal control (NC). Moreover, these cross-tissue FC metrics were correlated with voxel-based GM volumes and MMSE in all participants. Results: Compared to NC, AD patients showed decreased low-order static FCs between the intra-hemispheric GM-WM pairs (right ITG-right fornix; left MoFG-left posterior corona radiata), and increased low-order static, dynamic, and directional FCs between the inter-hemispheric GM-WM pairs (right MTG-left superior/posterior corona radiata). The high-order static and directional FCs between the left cingulate bundle-left tapetum were increased in AD, based on their FCs with the GMs of DMN. Those decreased and increased cross-tissue FC metrics in AD had opposite correlations with memory-related GM volumes and MMSE (positive for the decreased and negative for the increased). Conclusion: Cross-tissue FC metrics showed opposite changes in AD, possibly as useful neuroimaging biomarkers to reflect neurodegenerative and compensatory mechanisms.
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Affiliation(s)
- Xingxing Zhang
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
| | - Qing Guan
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
- Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Yingjia Li
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
| | - Jianfeng Zhang
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
| | - Wanlin Zhu
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuejia Luo
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
| | - Haobo Zhang
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen, China
- Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
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8
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Varela-López B, Cruz-Gómez ÁJ, Lojo-Seoane C, Díaz F, Pereiro A, Zurrón M, Lindín M, Galdo-Álvarez S. Cognitive reserve, neurocognitive performance, and high-order resting-state networks in cognitively unimpaired aging. Neurobiol Aging 2022; 117:151-164. [DOI: 10.1016/j.neurobiolaging.2022.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 10/18/2022]
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9
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Merenstein JL, Bennett IJ. Bridging patterns of neurocognitive aging across the older adult lifespan. Neurosci Biobehav Rev 2022; 135:104594. [PMID: 35227712 PMCID: PMC9888009 DOI: 10.1016/j.neubiorev.2022.104594] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/27/2022] [Accepted: 02/23/2022] [Indexed: 02/02/2023]
Abstract
Magnetic resonance imaging (MRI) studies of brain and neurocognitive aging rarely include oldest-old adults (ages 80 +). But predictions of neurocognitive aging theories derived from MRI findings in younger-old adults (ages ~55-80) may not generalize into advanced age, particularly given the increased prevalence of cognitive impairment/dementia in the oldest-old. Here, we reviewed the MRI literature in oldest-old adults and interpreted findings within the context of regional variation, compensation, brain maintenance, and reserve theories. Structural MRI studies revealed regional variation in brain aging as larger age effects on medial temporal and posterior regions for oldest-old than younger-old adults. They also revealed that brain maintenance explained preserved cognitive functioning into the tenth decade of life. Very few functional MRI studies examined compensatory activity in oldest-old adults who perform as well as younger groups, although there was evidence that higher brain reserve in oldest-old adults may mediate effects of brain aging on cognition. Despite some continuity, different cognitive and neural profiles across the older adult lifespan should be addressed in modern neurocognitive aging theories.
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10
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Hardcastle C, Hausman HK, Kraft JN, Albizu A, O'Shea A, Boutzoukas EM, Evangelista ND, Langer K, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, Porges E, DeKosky ST, Hishaw GA, Wu SS, Marsiske M, Cohen R, Alexander GE, Woods AJ. Proximal improvement and higher-order resting state network change after multidomain cognitive training intervention in healthy older adults. GeroScience 2022; 44:1011-1027. [PMID: 35258771 PMCID: PMC9135928 DOI: 10.1007/s11357-022-00535-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 02/18/2022] [Indexed: 01/01/2023] Open
Abstract
Prior randomized control trials have shown that cognitive training interventions resulted in improved proximal task performance, improved functioning of activities of daily living, and reduced dementia risk in healthy older adults. Neural correlates implicated in cognitive training include hub brain regions of higher-order resting state networks including the default mode network, dorsal attention network, frontoparietal control network, and cingulo-opercular network. However, little is known about resting state network change after cognitive training, or the relation between functional brain changes and improvement in proximal task performance. We assessed the 1) change in proximal task performance, 2) change in higher-order resting state network connectivity via functional magnetic resonance imaging, and 3) association between these variables after a multidomain attention/speed-of-processing and working memory randomized control trial in a sample of 58 healthy older adults. Participants in the cognitive training group improved significantly on seven out of eight training tasks immediately after the training intervention with the largest magnitude of improvement in a divided attention/speed-of-processing task, the Double Decision task. Only the frontoparietal control network had significantly strengthened connectivity in the cognitive training group at the post-intervention timepoint. Lastly, higher frontoparietal control network connectivity was associated with improved Double Decision task performance after training in the cognitive training group. These findings show that the frontoparietal control network may strengthen after multidomain cognitive training interventions, and this network may underlie improvements in divided attention/speed-of-processing proximal improvement.
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Affiliation(s)
- Cheshire Hardcastle
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Jessica N Kraft
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Emanuel M Boutzoukas
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Kailey Langer
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
| | - Eric Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Steven T DeKosky
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Samuel S Wu
- Department of Biostatistics, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Michael Marsiske
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Ronald Cohen
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA
| | - Gene E Alexander
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, 1249 Center Drive, PO Box 100196, Gainesville, FL, 32610-0165, USA.
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11
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Coelho A, Fernandes HM, Magalhães R, Moreira PS, Marques P, Soares JM, Amorim L, Portugal‐Nunes C, Castanho T, Santos NC, Sousa N. Reorganization of brain structural networks in aging: A longitudinal study. J Neurosci Res 2021; 99:1354-1376. [PMID: 33527512 PMCID: PMC8248023 DOI: 10.1002/jnr.24795] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 12/31/2020] [Indexed: 12/12/2022]
Abstract
Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.
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Affiliation(s)
- Ana Coelho
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Henrique M. Fernandes
- Center for Music in the Brain (MIB)Aarhus UniversityAarhusDenmark
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Ricardo Magalhães
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Pedro S. Moreira
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - José M. Soares
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Liliana Amorim
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Carlos Portugal‐Nunes
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Teresa Castanho
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Nadine Correia Santos
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
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12
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Shaffer J. Centenarians, Supercentenarians: We Must Develop New Measurements Suitable for Our Oldest Old. Front Psychol 2021; 12:655497. [PMID: 33897565 PMCID: PMC8058349 DOI: 10.3389/fpsyg.2021.655497] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 03/11/2021] [Indexed: 12/22/2022] Open
Affiliation(s)
- Joyce Shaffer
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
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13
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Tang H, Liu T, Liu H, Jiang J, Cheng J, Niu H, Li S, Brodaty H, Sachdev P, Wen W. A slower rate of sulcal widening in the brains of the nondemented oldest old. Neuroimage 2021; 229:117740. [PMID: 33460796 DOI: 10.1016/j.neuroimage.2021.117740] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 01/09/2021] [Indexed: 11/15/2022] Open
Abstract
The relationships between aging and brain morphology have been reported in many previous structural brain studies. However, the trajectories of successful brain aging in the extremely old remain underexplored. In the limited research on the oldest old, covering individuals aged 85 years and older, there are very few studies that have focused on the cortical morphology, especially cortical sulcal features. In this paper, we measured sulcal width and depth as well as cortical thickness from T1-weighted scans of 290 nondemented community-dwelling participants aged between 76 and 103 years. We divided the participants into young old (between 76 and 84; mean = 80.35±2.44; male/female = 76/88) and oldest old (between 85 and 103; mean = 91.74±5.11; male/female = 60/66) groups. The results showed that most of the examined sulci significantly widened with increased age and that the rates of sulcal widening were lower in the oldest old. The spatial pattern of the cortical thinning partly corresponded with that of sulcal widening. Compared to females, males had significantly wider sulci, especially in the oldest old. This study builds a foundation for future investigations of neurocognitive disorders and neurodegenerative diseases in the oldest old, including centenarians.
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Affiliation(s)
- Hui Tang
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China.
| | - Hao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW Sydney, NSW 2052, Australia
| | - Jian Cheng
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
| | - Haijun Niu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China
| | - Shuyu Li
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, International Research Institute for Multidisciplinary Science, Beihang University, Beijing 100191, China
| | - Henry Brodaty
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW Sydney, NSW 2052, Australia; Dementia Centre for Research Collaboration, School of Psychiatry, UNSW Sydney, NSW 2052, Australia
| | - Perminder Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW Sydney, NSW 2052, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW Sydney, NSW 2052, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
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