Associations of Neurological Biomarkers in Serum With Gait Measures: The Cardiovascular Health Study.

BACKGROUND: Gait impairment leads to increased mobility decline and may have neurological contributions. This study explores how neurological biomarkers are related to gait in older adults. METHODS: We studied participants in the Cardiovascular Health Study, a population-based cohort of older Americans, who underwent a serum biomarker assessment from samples collected in 1996-1997 for neurofilament light chain (NfL), glial fibrillary acidic protein, ubiquitin carboxy-terminal hydrolase L1, and total tau (n = 1 959, mean age = 78.0 years, 60.8% female). In a subsample (n = 380), cross-sectional associations with quantitative gait measures were explored. This subsample was assessed on a mat for gait speed, step length, double support time, step time, step length variability, and step time variability. Gait speed was also measured over a 15-ft walkway annually from 1996-1997 to 1998-1999 for longitudinal analyses. Linear regression models assessed cross-sectional associations of biomarkers with gait measures, whereas mixed effects models assessed longitudinal gait speed change from baseline to 1998-1999. RESULTS: Neurofilament light chain was significantly associated with annual gait speed decline (standardized ß = -0.64 m/s, 95% CI: [-1.23, -0.06]) after adjustment for demographic and health factors. Among gait mat-assessed phenotypes, NfL was also cross-sectionally associated with gait speed (ß = 0.001 m/s [0.0003, 0.002]) but not with other gait measures. None of the remaining biomarkers were significantly related to gait in either longitudinal or cross-sectional analyses. CONCLUSIONS: Higher NfL levels were related to greater annual gait speed decline. Gait speed decline may be related to axonal degeneration. The clinical utility of NfL should be explored.

Biomechanical Stress Profiling of Coronary Atherosclerosis: Identifying a Multifactorial Metric to Evaluate Plaque Rupture Risk.

OBJECTIVES: The purpose of this study was to derive a biomechanical stress metric that was based on the multifactorial assessment of coronary plaque morphology, likely related to the propensity of plaque rupture in patients. BACKGROUND: Plaque rupture, the most frequent cause of coronary thrombosis, occurs at locations of elevated tensile stress in necrotic core fibroatheromas (NCFAs). Finite element modeling (FEM), typically used to calculate tensile stress, is computationally intensive and impractical as a clinical tool for locating rupture-prone plaques. This study derived a multifactorial stress equation (MSE) that accurately computes peak stress in NCFAs by combining the influence of several morphological parameters. METHODS: Intravascular ultrasound and optical frequency domain imaging were conducted in 30 patients, and plaque morphological parameters were defined in 61 NCFAs. Multivariate regression analysis was applied to derive the MSE and compute a peak stress metric (PSM) that was based on the analysis of plaque morphological parameters. The accuracy of the MSE was determined by comparing PSM with FEM-derived peak stress values. The ability of the PSM in locating plaque rupture sites was tested in 3 additional patients. RESULTS: The following parameters were found to be independently associated with peak stress: fibrous cap thickness (p < 0.0001), necrotic core angle (p = 0.024), necrotic core thickness (p < 0.0001), lumen area (p < 0.0001), necrotic core including calcium areas (p = 0.017), and plaque area (p = 0.003). The PSM showed excellent correlation (R = 0.85; p < 0.0001) with FEM-derived peak stress, thus confirming the accuracy of the MSE. In only 56% (n = 34) of plaques, the thinnest fibrous cap thickness was a determining parameter in identifying the cross section with highest PSM. In coronary segments with plaque ruptures, the MSE precisely located the rupture site. CONCLUSIONS: The MSE shows potential to calculate the PSM in coronary lesions rapidly. However, further studies are warranted to investigate the use of biomechanical stress profiling for the prognostic evaluation of patients with atherosclerosis.