Isabel Martín-Fuentes, Patricio Solis-Urra, Emilio J Ruiz-Malagón, Andrea Coca-Pulido, Angel Toval, Beatriz Fernandez-Gamez, Marcos Olvera-Rojas, Darío Bellón, Alessandro Sclafani, Jose Mora-Gonzalez, Lucía Sánchez-Aranda, Javier Sanchez-Martinez, José Pablo Martínez-Barbero, Manuel Gómez-Río, Teresa Liu-Ambrose, Kirk I Erickson, Francisco B Ortega, Irene Esteban-Cornejo
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This study aims to examine the associations between gait variability parameters (derived from stride length, step length, step time, and gait velocity) and GMV and its associations with cognitive function in cognitively normal older adults.</p><p><strong>Research design and methods: </strong>Eighty-seven older adults (48 female) aged 65-80 from the AGUEDA trial participated in this cross-sectional analysis. The Optogait system was used to record gait parameters. T1-weighted brain images were acquired magnetic resonance imaging scanner, and GMV was calculated by whole-brain voxel-based morphometric analysis using SPM12. Cognitive function was calculated from different cognitive tests.</p><p><strong>Results: </strong>Greater stride length variability was associated with lower GMV (<i>p</i> < .001) in clusters located in the supramarginal gyrus (<i>t</i> = 4.014, <i>k</i> = 179, β = -0.494) and hippocampus (<i>t</i> = 3.670, <i>k</i> = 334, β = -0.394), whereas greater step length variability was linked to lower GMV in the parahippocampal gyrus (<i>t</i> = 3.624, <i>k</i> = 76, β = -0.410). However, greater step time variability was associated with greater GMV in the supplementary motor area (<i>t</i> = 4.117, <i>k</i> = 274, β = 0.449). Gait velocity variability did not show any association with GMV. Furthermore, greater GMV in the supramarginal gyrus was associated with better working memory (β = 0.252, <i>p</i> = .008); greater GMV in the hippocampus was associated with better attentional/inhibitory control (β = 0.275, <i>p</i> = .010); and greater GMV in the parahippocampal gyrus was associated with better EF (β = 0.212, <i>p</i> = .035), attentional/inhibitory control (β = 0.241, <i>p</i> = .019), and working memory (β = 0.233, <i>p</i> = .027).</p><p><strong>Discussion and implications: </strong>These results suggest that gait variability could be an indicator of neurocognitive decline in older adults. Understanding these associations is essential for early dementia detection and sheds light on the complex interplay between physical function, brain health, and cognitive function during aging.</p>","PeriodicalId":13596,"journal":{"name":"Innovation in Aging","volume":"9 6","pages":"igaf045"},"PeriodicalIF":4.9000,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246678/pdf/","citationCount":"0","resultStr":"{\"title\":\"Gait Variability Is Associated With Gray Matter Volumes Implicated in Cognitive Function: A Cross-Sectional Analysis From the AGUEDA Trial.\",\"authors\":\"Isabel Martín-Fuentes, Patricio Solis-Urra, Emilio J Ruiz-Malagón, Andrea Coca-Pulido, Angel Toval, Beatriz Fernandez-Gamez, Marcos Olvera-Rojas, Darío Bellón, Alessandro Sclafani, Jose Mora-Gonzalez, Lucía Sánchez-Aranda, Javier Sanchez-Martinez, José Pablo Martínez-Barbero, Manuel Gómez-Río, Teresa Liu-Ambrose, Kirk I Erickson, Francisco B Ortega, Irene Esteban-Cornejo\",\"doi\":\"10.1093/geroni/igaf045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objectives: </strong>Aging is associated with both gait impairments and cognitive decline; however, the relationship between specific gait variability parameters, gray matter volume (GMV), and cognitive function remains poorly understood. 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引用次数: 0
摘要
背景和目的：衰老与步态障碍和认知能力下降有关；然而，特定步态变异性参数、灰质体积（GMV）和认知功能之间的关系仍然知之甚少。本研究旨在研究认知正常老年人的步态变异性参数（步幅、步长、步时间和步态速度）和GMV之间的关系及其与认知功能的关系。研究设计和方法：来自AGUEDA试验的87名65-80岁老年人（48名女性）参与了本横断面分析。光步态系统用于记录步态参数。磁共振成像扫描仪获取t1加权脑图像，利用SPM12基于全脑体素的形态计量分析计算GMV。通过不同的认知测试计算认知功能。结果：较大的步长变异性与较低的海马GMV （p t = 4.014, k = 179, β = -0.494）和海马GMV （t = 3.670, k = 334, β = -0.394）相关，而较大的步长变异性与较低的海马旁回GMV相关（t = 3.624, k = 76, β = -0.410）。然而，步长变异性越大，辅助运动区GMV越大（t = 4.117, k = 274, β = 0.449）。步态速度变异性与GMV没有任何关联。此外，更大的边缘上回GMV与更好的工作记忆相关（β = 0.252, p = 0.008）；海马GMV越大，注意/抑制控制越好（β = 0.275, p = 0.010）；海马旁回GMV大与良好的EF （β = 0.212, p = 0.035）、注意/抑制控制（β = 0.241, p = 0.019）和工作记忆（β = 0.233, p = 0.027）相关。讨论和启示：这些结果表明，步态变异性可能是老年人神经认知能力下降的一个指标。了解这些关联对于早期发现痴呆症至关重要，并揭示衰老过程中身体功能、大脑健康和认知功能之间复杂的相互作用。
Gait Variability Is Associated With Gray Matter Volumes Implicated in Cognitive Function: A Cross-Sectional Analysis From the AGUEDA Trial.
Background and objectives: Aging is associated with both gait impairments and cognitive decline; however, the relationship between specific gait variability parameters, gray matter volume (GMV), and cognitive function remains poorly understood. This study aims to examine the associations between gait variability parameters (derived from stride length, step length, step time, and gait velocity) and GMV and its associations with cognitive function in cognitively normal older adults.
Research design and methods: Eighty-seven older adults (48 female) aged 65-80 from the AGUEDA trial participated in this cross-sectional analysis. The Optogait system was used to record gait parameters. T1-weighted brain images were acquired magnetic resonance imaging scanner, and GMV was calculated by whole-brain voxel-based morphometric analysis using SPM12. Cognitive function was calculated from different cognitive tests.
Results: Greater stride length variability was associated with lower GMV (p < .001) in clusters located in the supramarginal gyrus (t = 4.014, k = 179, β = -0.494) and hippocampus (t = 3.670, k = 334, β = -0.394), whereas greater step length variability was linked to lower GMV in the parahippocampal gyrus (t = 3.624, k = 76, β = -0.410). However, greater step time variability was associated with greater GMV in the supplementary motor area (t = 4.117, k = 274, β = 0.449). Gait velocity variability did not show any association with GMV. Furthermore, greater GMV in the supramarginal gyrus was associated with better working memory (β = 0.252, p = .008); greater GMV in the hippocampus was associated with better attentional/inhibitory control (β = 0.275, p = .010); and greater GMV in the parahippocampal gyrus was associated with better EF (β = 0.212, p = .035), attentional/inhibitory control (β = 0.241, p = .019), and working memory (β = 0.233, p = .027).
Discussion and implications: These results suggest that gait variability could be an indicator of neurocognitive decline in older adults. Understanding these associations is essential for early dementia detection and sheds light on the complex interplay between physical function, brain health, and cognitive function during aging.
期刊介绍：
Innovation in Aging, an interdisciplinary Open Access journal of the Gerontological Society of America (GSA), is dedicated to publishing innovative, conceptually robust, and methodologically rigorous research focused on aging and the life course. The journal aims to present studies with the potential to significantly enhance the health, functionality, and overall well-being of older adults by translating scientific insights into practical applications. Research published in the journal spans a variety of settings, including community, clinical, and laboratory contexts, with a clear emphasis on issues that are directly pertinent to aging and the dynamics of life over time. The content of the journal mirrors the diverse research interests of GSA members and encompasses a range of study types. These include the validation of new conceptual or theoretical models, assessments of factors impacting the health and well-being of older adults, evaluations of interventions and policies, the implementation of groundbreaking research methodologies, interdisciplinary research that adapts concepts and methods from other fields to aging studies, and the use of modeling and simulations to understand factors and processes influencing aging outcomes. The journal welcomes contributions from scholars across various disciplines, such as technology, engineering, architecture, economics, business, law, political science, public policy, education, public health, social and psychological sciences, biomedical and health sciences, and the humanities and arts, reflecting a holistic approach to advancing knowledge in gerontology.
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