Sylvester, Hunter C

Abstract Although slower gait speed is associated with cognitive impairment, endurance may be more predictive in older adults with faster gait speed. We examined moderating effects of endurance on the relationship of gait speed with incident mild cognitive impairment (MCI) or dementia in cognitively normal ARIC participants (n = 2242, mean age=78.6 + 4.3, 58% female, 19% Black). At the sixth exam, endurance was assessed as distance walked at a fast pace (Two Minute Walk, 2MW); usual 4-meter gait speed was also assessed. Cognitive status was adjudicated during the 6th-9th exams (mean follow-up 5.1 years). Multinomial logistic regression models with a 2MW-x-gait speed interaction term estimated relative risk ratios (RRR) of MCI and dementia relative to normal cognition per SD higher gait speed or 2MW distance, adjusting for demographic and cardiovascular factors. Results used representative continuous gait speed and continuous 2MW distance values. Longer 2MW distance was associated with lower risk of MCI and dementia at gait speed <1m/s [e.g. gait speed=0.8: MCI RRR=0.59, 95%CI(0.42, 0.83); dementia RRR=0.29, (0.13, 0.63)] and with dementia at gait speed>1m/s [gait speed=1.2: RRR=0.28, (0.09, 0.81)], but not with MCI (RRR=0.85, (0.57, 1.26)]. Conversely, faster gait speed was associated with lower risk of MCI at low 2MW [100 m; RRR=0.84, (0.74, 0.94)], but was attenuated at high 2MW (150 m; RRR=0.91, (0.84, 1.00)]. A 2MW-x-gait speed interaction term was supported (p = 0.04), primarily driven by differential MCI associations. Combining endurance and gait speed may be especially helpful in identifying cognitively normal older adults at risk for impending early-stage cognitive impairment.

Abstract Faster gait speed and better endurance have been cross-sectionally and jointly associated with a lower likelihood of dementia. However, gait speed associations plateau above 1m/s, suggesting gait speed may be less predictive at near normal speeds. This study examined prospective associations of gait speed, endurance, and moderating effects of endurance on gait speed associations with incident dementia among ARIC participants without dementia at Visit 6 (2016-2017) who completed assessments of endurance ( 2- Minute Walk (2MW), meters) and usual-pace 4-meter gait speed (m/s) (n = 2767, mean age 78+/- 4.3 years, 43% male, 18% Black). Dementia was adjudicated using neuropsychological tests, functional assessments, informant interviews, and medical/vital record surveillance over a median of 3.3 years follow-up. Cox regression models estimated the hazard ratio (HR, 95% CI) for dementia, incorporating gait speed, 2MW, gait speed-by-2MW interaction, demographic, and cardiovascular factors. In separate models, each standard deviation higher 2MW [HR = 0.62, (0.50,0.76)] and faster gait speed [HR = 0.63, (0.50,0.81)] were associated with lower incident dementia risk. However, when jointly adjusting for 2MW and gait speed, higher 2MW was associated with a 32% lower incident dementia risk [HR = 0.68,(0.51, 0.90)], but faster gait speed was not statistically associated with incident dementia [HR = 0.85, (0.62,1.16)]. Moderating effects were not supported (gait speed-x-2MW interaction, p = 0.14). Although both endurance and gait speed predict dementia, endurance may be more informative across the gait speed spectrum, whereas gait speed may be more feasible for clinical settings. Longer follow-up and more dementia events may better inform differential utilities of gait speed and endurance measures.

Abstract Background Alzheimer’s Disease (AD) progression is conceptualized as a cascade of sigmoidal (S‐shaped) curves, with biomarkers shifting sequentially from normal to abnormal states. Estimating these curves requires sophisticated modeling, with challenges including (1) selecting appropriate sigmoidal‐type functions, (2) achieving algorithmic convergence, and (3) producing clinically useful parameters. We compare commonly used sigmoidal‐functions and effects on novel estimates of early and late AD‐biomarker progression ages. Method Using 3,999 Amyloid PET (PiB SUVR) measurements from 1,367 Mayo Clinic Study of Aging participants, we compared model fits (AIC, BIC) between logistic and hyperbolic functions using Non‐Linear Mixed Effect (NLME) models with subject‐specific age‐shifts. We defined novel “initial” and “maximum” acceleration points (IAP and MAP) to compare clinically “earlier” and “later” AD‐progression ages between sigmoidal‐curves. The MAP uses the maximum second‐derivative point, reflecting the age of fastest acceleration in biomarker accumulation. The IAP is defined as the first point where the second derivative of the sigmoidal‐curve exceeds a clinical threshold (here, 5% velocity increase per year), indicating onset age of early accelerated biomarker accumulation. Estimates for C 2 N plasma p ‐tau217 were also attempted (1,306 measurements on 457 participants). Models adjusted for sex and APOE4‐positivity. Result In the larger PET sample, the hyperbola had lower AIC/BIC (better fit), but showed a decreasing early PiB‐SUVR trend (Table 1A, Figure 1). Ages of late MAP were comparable, as were sex and APOE4+ related PiB‐SUVR‐curve shifts. Age of early AD‐onset was estimated 1.5 years earlier for logistic (IAP=63.6) versus hyperbola (IAP=65.1) functions. The logistic function always converged, while the hyperbolic function did not converge for p ‐tau217 in the smaller C 2 N sample. Early‐onset and late‐progression ages were 7‐8 years later for p ‐tau217 versus PiB‐SUVR using logistic‐curves. Conclusion Late AD‐progression and covariate‐related shifts in progression were comparable across models, suggesting robustness to sigmoid choice. In contrast, estimates of early AD‐onset may be more dependent on functional form. While logistic‐sigmoids inherently increase monotonically, hyperbolas do not, here estimating a decline in initial amyloid trend. Future work may explore adding biologically informed constraints to flexible sigmoidal‐functions, and alternative Bayesian approaches, to optimize both model fit and estimation of early AD‐onset age.