Associations of Gait Speed with Neuroimaging Biomarkers: Findings from the LifeAfter90 (LA90) Study

Abstract Background Gait speed is a well‐known marker of cognitive function and mortality in older adults. However, its association with neuroimaging biomarkers is understudied. We tested associations between gait speed and biomarkers of neurodegeneration, cerebrovascular injury and amyloid accumulation in the oldest old. Method The LifeAfter90 Study (2018‐2022) included a neuroimaging subsample of 103 participants aged 90 and older. Gait speed (meters/second) was measured twice per visit using the 4‐Meter Walk Test and we used the average gait speed score from the visit closest to each participant's neuroimaging scan date. Hippocampal volumes (total, right and left hippocampus) and measures of white matter integrity (log‐white matter hyperintensities (WMH), fractional anisotropy (FA)) were measured with 3T MRI and amyloid standardized uptake value ratio (SUVR) with florbetapir PET. Hippocampal volumes and WMH were adjusted for intracranial volume. Linear regression models tested associations between gait speed and brain imaging markers, adjusting for age, sex/gender, race/ethnicity, and education. Sex‐stratified models were used to explore potential differences in these associations by sex. Result Mean age of participants was 92.5(±2.3) years, and 59.2% were women (Table 1). Overall, gait speed was not significantly associated with any brain regions of interest (Figure 1). Although not statistically significant, faster gait speed suggested better white matter integrity (β logWMH = ‐0.59, 95% CI ‐1.28, 0.10; β FA =0.27, 95% CI ‐0.54, 1.09) and lower amyloid‐SUVR (β amyloid = ‐0.10, 95% CI ‐0.33, 0.12). In contrast, it was associated with lower hippocampal volumes (β total = ‐0.30, 95% CI ‐1.24, 0.64; β right = ‐0.13, 95% CI ‐1.04, 0.79; β left = ‐0.41, 95% CI ‐1.37, 0.55) (Figure 1). In the stratified analysis, faster gait speed was significantly associated with lower WMH volume in females (β logWMH = ‐1.00, 95% CI ‐1.91, ‐0.10) but not in males (β logWMH = ‐0.12, 95% CI ‐1.46, 1.21). Conclusion Although gait speed was not associated with specific neuroimaging biomarkers in the overall cohort, faster gait speed was associated with lower WMH in females. This study underscores the need to further investigate gait speed as an accessible indicator of neuropathological changes, especially in 90+ populations where neuroimaging might be challenging.

Authors

Institutions

Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70856_106701
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Associations of Gait Speed with Neuroimaging Biomarkers: Findings from the LifeAfter90 (LA90) Study

Hilary Colbeth, Yi Lor, Kristen M. George, Alexander Ivan B. Posis et al.
Alzheimer s & Dementia
Balance, Gait, and Falls Prevention
article

Associations of Gait Speed with Neuroimaging Biomarkers: Findings from the LifeAfter90 (LA90) Study

Hilary Colbeth, Yi Lor, Kristen M. George, Alexander Ivan B. Posis, Rifat Binte Alam, Batool Rizvi, María M. M. Corrada, Rachel A. Whitmer, Paola Gilsanz
article en

Abstract

Abstract Background Gait speed is a well‐known marker of cognitive function and mortality in older adults. However, its association with neuroimaging biomarkers is understudied. We tested associations between gait speed and biomarkers of neurodegeneration, cerebrovascular injury and amyloid accumulation in the oldest old. Method The LifeAfter90 Study (2018‐2022) included a neuroimaging subsample of 103 participants aged 90 and older. Gait speed (meters/second) was measured twice per visit using the 4‐Meter Walk Test and we used the average gait speed score from the visit closest to each participant's neuroimaging scan date. Hippocampal volumes (total, right and left hippocampus) and measures of white matter integrity (log‐white matter hyperintensities (WMH), fractional anisotropy (FA)) were measured with 3T MRI and amyloid standardized uptake value ratio (SUVR) with florbetapir PET. Hippocampal volumes and WMH were adjusted for intracranial volume. Linear regression models tested associations between gait speed and brain imaging markers, adjusting for age, sex/gender, race/ethnicity, and education. Sex‐stratified models were used to explore potential differences in these associations by sex. Result Mean age of participants was 92.5(±2.3) years, and 59.2% were women (Table 1). Overall, gait speed was not significantly associated with any brain regions of interest (Figure 1). Although not statistically significant, faster gait speed suggested better white matter integrity (β logWMH = ‐0.59, 95% CI ‐1.28, 0.10; β FA =0.27, 95% CI ‐0.54, 1.09) and lower amyloid‐SUVR (β amyloid = ‐0.10, 95% CI ‐0.33, 0.12). In contrast, it was associated with lower hippocampal volumes (β total = ‐0.30, 95% CI ‐1.24, 0.64; β right = ‐0.13, 95% CI ‐1.04, 0.79; β left = ‐0.41, 95% CI ‐1.37, 0.55) (Figure 1). In the stratified analysis, faster gait speed was significantly associated with lower WMH volume in females (β logWMH = ‐1.00, 95% CI ‐1.91, ‐0.10) but not in males (β logWMH = ‐0.12, 95% CI ‐1.46, 1.21). Conclusion Although gait speed was not associated with specific neuroimaging biomarkers in the overall cohort, faster gait speed was associated with lower WMH in females. This study underscores the need to further investigate gait speed as an accessible indicator of neuropathological changes, especially in 90+ populations where neuroimaging might be challenging.

Alzheimer s & DementiaVol. 21(S2)
Kaiser Permanente (US), University of California, Irvine (US), University of California, Davis (US)
Openalex Percentile: Top 20%
Balance, Gait, and Falls Prevention
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Associations of Gait Speed with Neuroimaging Biomarkers: Findings from the LifeAfter90 (LA90) Study — Hilary Colbeth, Yi Lor, et al. · Alzheimer s & Dementia (2025) | TGRS Research Map | TGRS