Midlife sensory and motor functions improve prediction of blood-based measures of neurodegeneration and Alzheimer's disease in late middle-age.

INTRODUCTION: We assessed whether midlife sensory and motor functions added to prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS) improve risk predictions of 10-year changes in biomarkers of neurodegeneration and Alzheimer's disease. METHODS: Longitudinal data of N = 1529 (mean age 49years) Beaver Dam Offspring Study participants from baseline, 5-year, and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function measures improves CAIDE or FRS risk predictions of 10-year incidence of biomarker positivity of serum-based neurofilament light chain (NfL) and amyloid beta (Aß)42/Aß40 using logistic regression. RESULTS: Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved NfL and Aß42/Aß40 positivity predictions in adults above the age of 55. DISCUSSION: Including midlife sensory and motor function improved long-term biomarker positivity predictions. Non-invasive sensory and motor assessments could contribute to cost-effective screening tools that identify individuals at risk for neurodegeneration early to target interventions and preventions. Highlights: Sensory and motor measures improve risk prediction models of neurodegenerative biomarkersSensory and motor measures improve risk prediction models of AD biomarkersPrediction improvements were strongest in late midlife (adults >55 years of age)Sensory and motor assessments may help identify high-risk individuals early.

Midlife sensory and motor functions improve long-term predictions of cognitive decline and incidence of cognitive impairment.

INTRODUCTION: We aimed to assess whether midlife sensory and motor functions improve risk prediction of 10-year cognitive decline and impairment when added to risk prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS). METHODS: Longitudinal data of N = 1529 (mean age 49 years; 54% women) Beaver Dam Offspring Study (BOSS) participants from baseline, 5 and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function improves CAIDE or FRS risk predictions of 10-year cognitive decline or cognitive impairment incidence using logistic regressions. RESULTS: Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved areas under the curve for cognitive decline and impairment models. DISCUSSION: Including midlife sensory and motor function improved risk predictions of long-term cognitive decline and impairment in middle-aged to older adults. Sensory and motor assessments could contribute to cost-effective and non-invasive screening tools that identify high-risk individuals earlier to target intervention and prevention strategies. Highlights: Sensory and motor measures improve risk prediction models of cognitive decline.Sensory and motor measures improve risk prediction models of cognitive impairment.Prediction improvements were strongest in midlife (adults < 55 years of age).Sensory and motor changes may help identify high-risk individuals early.

Lifestyle and factors of vascular and metabolic health and inflammation are associated with sensorineural-neurocognitive aging in older adults.

This study's aim was to identify risk factors associated with sensorineural and neurocognitive function (brain aging) in older adults. In N = 1,478 Epidemiology of Hearing Loss Study participants (aged 64-100 years, 59% women), we conducted sensorineural and cognitive tests, which were combined into a summary measure using Principal Component Analysis (PCA). Participants with a PCA score <-1 standard deviation (SD) were considered to have brain aging. Incident brain aging was defined as PCA score <-1 SD at 5-year follow-up among participants who had a PCA score ≥-1 SD at baseline. Logistic regression and Poisson models were used to estimate associations between baseline risk factors of lifestyle, vascular and metabolic health, and inflammation and prevalent or incident brain aging, respectively. In an age-sex adjusted multivariable model, not consuming alcohol (odds ratio(OR) = 1.77, 95% confidence Interval (CI) = 1.18,2.66), higher interleukin-6 levels (OR = 1.30, 95% CI = 1.03,1.64), and depressive symptoms (OR = 2.44, 95% CI = 1.63,3.67) were associated with a higher odds of having brain aging, while higher education had protective effects (OR = 0.55, 95% CI = 0.33,0.94). A history of stroke, arterial stiffness, and obesity were associated with an increased risk of developing brain aging during the five years of follow-up. Lifestyle, vascular, metabolic and inflammatory factors were associated with brain aging in older adults, which adds to the evidence of shared pathways for sensorineural and neurocognitive declines in aging. Targeting these shared central processing etiological factors with interventions may lead to retention of better neurological function, benefiting multiple systems, i.e., hearing, smell, and cognition, ultimately helping older adults retain independence and higher quality of life longer.