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Shichkova P, Coggan JS, Markram H, Keller D. Brain Metabolism in Health and Neurodegeneration: The Interplay Among Neurons and Astrocytes. Cells 2024; 13:1714. [PMID: 39451233 PMCID: PMC11506225 DOI: 10.3390/cells13201714] [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: 08/01/2024] [Revised: 08/31/2024] [Accepted: 10/14/2024] [Indexed: 10/26/2024] Open
Abstract
The regulation of energy in the brain has garnered substantial attention in recent years due to its significant implications in various disorders and aging. The brain's energy metabolism is a dynamic and tightly regulated network that balances energy demand and supply by engaging complementary molecular pathways. The crosstalk among these pathways enables the system to switch its preferred fuel source based on substrate availability, activity levels, and cell state-related factors such as redox balance. Brain energy production relies on multi-cellular cooperation and is continuously supplied by fuel from the blood due to limited internal energy stores. Astrocytes, which interface with neurons and blood vessels, play a crucial role in coordinating the brain's metabolic activity, and their dysfunction can have detrimental effects on brain health. This review characterizes the major energy substrates (glucose, lactate, glycogen, ketones and lipids) in astrocyte metabolism and their role in brain health, focusing on recent developments in the field.
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Affiliation(s)
- Polina Shichkova
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, 1202 Geneva, Switzerland
| | - Jay S. Coggan
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, 1202 Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, 1202 Geneva, Switzerland
- Laboratory of Neural Microcircuitry, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Daniel Keller
- Blue Brain Project, École Polytechnique Fédérale de Lausanne, 1202 Geneva, Switzerland
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Spence JS, Turner MP, Rypma B, D'Esposito M, Chapman SB. Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics. Cereb Cortex 2024; 34:bhad435. [PMID: 37968568 DOI: 10.1093/cercor/bhad435] [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: 06/23/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/17/2023] Open
Abstract
The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.
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Affiliation(s)
- Jeffrey S Spence
- Center for BrainHealth, 2200 West Mockingbird Road, Dallas, TX 75235, United States
| | - Monroe P Turner
- Center for BrainHealth, 2200 West Mockingbird Road, Dallas, TX 75235, United States
| | - Bart Rypma
- Center for BrainHealth, 2200 West Mockingbird Road, Dallas, TX 75235, United States
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute and Department of Psychology, University of California Berkeley, 175 Li Ka Shing Center, MC#3370, Berkeley, CA 94720, United States
| | - Sandra Bond Chapman
- Center for BrainHealth, 2200 West Mockingbird Road, Dallas, TX 75235, United States
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Hammond TC, Green SJ, Jacobs Y, Chlipala GE, Xing X, Heil S, Chen A, Aware C, Flemister A, Stromberg A, Balchandani P, Lin AL. Gut microbiome association with brain imaging markers, APOE genotype, calcium and vegetable intakes, and obesity in healthy aging adults. Front Aging Neurosci 2023; 15:1227203. [PMID: 37736325 PMCID: PMC10510313 DOI: 10.3389/fnagi.2023.1227203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/17/2023] [Indexed: 09/23/2023] Open
Abstract
Introduction Advanced age is a significant factor in changes to brain physiology and cognitive functions. Recent research has highlighted the critical role of the gut microbiome in modulating brain functions during aging, which can be influenced by various factors such as apolipoprotein E (APOE) genetic variance, body mass index (BMI), diabetes, and dietary intake. However, the associations between the gut microbiome and these factors, as well as brain structural, vascular, and metabolic imaging markers, have not been well explored. Methods We recruited 30 community dwelling older adults between age 55-85 in Kentucky. We collected the medical history from the electronic health record as well as the Dietary Screener Questionnaire. We performed APOE genotyping with an oral swab, gut microbiome analysis using metagenomics sequencing, and brain structural, vascular, and metabolic imaging using MRI. Results Individuals with APOE e2 and APOE e4 genotypes had distinct microbiota composition, and higher level of pro-inflammatory microbiota were associated higher BMI and diabetes. In contrast, calcium- and vegetable-rich diets were associated with microbiota that produced short chain fatty acids leading to an anti-inflammatory state. We also found that important gut microbial butyrate producers were correlated with the volume of the thalamus and corpus callosum, which are regions of the brain responsible for relaying and processing information. Additionally, putative proinflammatory species were negatively correlated with GABA production, an inhibitory neurotransmitter. Furthermore, we observed that the relative abundance of bacteria from the family Eggerthellaceae, equol producers, was correlated with white matter integrity in tracts connecting the brain regions related to language, memory, and learning. Discussion These findings highlight the importance of gut microbiome association with brain health in aging population and could have important implications aimed at optimizing healthy brain aging through precision prebiotic, probiotic or dietary interventions.
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Affiliation(s)
- Tyler C. Hammond
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Department of Neuroscience, University of Kentucky, Lexington, KY, United States
| | - Stefan J. Green
- Genomics and Microbiome Core Facility, Rush University, Chicago, IL, United States
| | - Yael Jacobs
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - George E. Chlipala
- Research Informatics Core, University of Illinois Chicago, Chicago, IL, United States
| | - Xin Xing
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Department of Computer Science, University of Kentucky, Lexington, KY, United States
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Sally Heil
- School of Medicine, University of Missouri, Columbia, MO, United States
| | - Anna Chen
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
| | - Chetan Aware
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Abeoseh Flemister
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
| | - Arnold Stromberg
- Dr. Bing Zhang Department of Statistics, University of Kentucky, Lexington, KY, United States
| | - Priti Balchandani
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ai-Ling Lin
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
- Roy Blunt NextGen Precision Health, University of Missouri, Columbia, MO, United States
- Department of Radiology, University of Missouri, Columbia, MO, United States
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States
- Division of Biological Sciences, University of Missouri, Columbia, MO, United States
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Butters E, Srinivasan S, O'Brien JT, Su L, Bale G. A promising tool to explore functional impairment in neurodegeneration: A systematic review of near-infrared spectroscopy in dementia. Ageing Res Rev 2023; 90:101992. [PMID: 37356550 DOI: 10.1016/j.arr.2023.101992] [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: 04/07/2023] [Revised: 06/15/2023] [Accepted: 06/22/2023] [Indexed: 06/27/2023]
Abstract
This systematic review aimed to evaluate previous studies which used near-infrared spectroscopy (NIRS) in dementia given its suitability as a diagnostic and investigative tool in this population. From 800 identified records which used NIRS in dementia and prodromal stages, 88 studies were evaluated which employed a range of tasks testing memory (29), word retrieval (24), motor (8) and visuo-spatial function (4), and which explored the resting state (32). Across these domains, dementia exhibited blunted haemodynamic responses, often localised to frontal regions of interest, and a lack of task-appropriate frontal lateralisation. Prodromal stages, such as mild cognitive impairment, revealed mixed results. Reduced cognitive performance accompanied by either diminished functional responses or hyperactivity was identified, the latter suggesting a compensatory response not present at the dementia stage. Despite clear evidence of alterations in brain oxygenation in dementia and prodromal stages, a consensus as to the nature of these changes is difficult to reach. This is likely partially due to the lack of standardisation in optical techniques and processing methods for the application of NIRS to dementia. Further studies are required exploring more naturalistic settings and a wider range of dementia subtypes.
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Affiliation(s)
- Emilia Butters
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK; Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
| | - Sruthi Srinivasan
- Department of Electrical Engineering, University of Cambridge, 9 JJ Thomson Avenue, Cambridge CB3 0FA, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Neuroscience, University of Sheffield, 385a Glossop Rd, Broomhall, Sheffield S10 2HQ, UK
| | - Gemma Bale
- Department of Physics, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0FA, UK
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Wu S, Tyler LK, Henson RNA, Rowe JB, Cam-Can, Tsvetanov KA. Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the adult lifespan. Neurobiol Aging 2023; 121:1-14. [PMID: 36306687 PMCID: PMC7613814 DOI: 10.1016/j.neurobiolaging.2022.09.006] [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: 11/19/2021] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 10/14/2022]
Abstract
The preservation of cognitive function in old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort. As age differences in CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network were implicated in fluid reasoning. Age differences in CBF explained not only performance-related BOLD responses but also performance-independent BOLD responses. Our results suggest that CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function and preserve cognitive performance.
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Affiliation(s)
- Shuyi Wu
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK; Department of Management, School of Business, Hong Kong Baptist University, Hong Kong, China
| | - Lorraine K Tyler
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
| | - Richard N A Henson
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK
| | - James B Rowe
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Cam-Can
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK; Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK
| | - Kamen A Tsvetanov
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
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