&bgr;-Amyloid Burden Predicts Lower Extremity Performance Decline in Cognitively Unimpaired Older Adults

Background Motor slowing is associated with risk of Alzheimer's disease. Whether β-amyloid (Aβ) burden is associated with motor decline, independent of cognitive decline, is unknown. Methods About 59 cognitively unimpaired older participants had baseline PET-PiB scans and repeated measures of lower (usual gait speed, 400-m time, Health ABC Physical Performance Battery (HABCPPB) score, total standing balance time) and upper (mean tapping time) extremity performance during a mean follow-up of 4.7 years. Linear mixed effect models examined the relationship between baseline Aβ burden and motor decline, adjusting for age, sex, body mass index, cardiovascular risk, APOE ɛ4 status, memory decline, depressive symptoms, ankle-arm index, processing speed, executive function, and cerebrovascular disease. Results Higher mean cortical Aβ burden was associated with greater declines in gait speed and HABCPPB score and a greater increase in 400-m time. Higher Aβ of putamen was associated with declines in all lower extremity measures, including balance. Higher Aβ of dorsolateral prefrontal cortex and lateral temporal lobe was associated with declines of gait speed and 400-m time, and of precuneus with a greater increase in 400-m time. Associations remained similar after further adjustment. Conclusions In cognitively unimpaired older adults, Aβ burden overall and in specific brain regions are risk factors for lower extremity motor decline, independent of memory function. These findings provide the first empirical evidence that Aβ burden is a risk factor for mobility decline in older adults.

[1]  Jerry L. Prince,et al.  Individual estimates of age at detectable amyloid onset for risk factor assessment , 2016, Alzheimer's & Dementia.

[2]  Pierre Payoux,et al.  Relationship of regional brain β-amyloid to gait speed , 2016, Neurology.

[3]  Donald A. Wilson,et al.  At the interface of sensory and motor dysfunctions and Alzheimer's disease , 2015, Alzheimer's & Dementia.

[4]  Jeannette R. Mahoney,et al.  Neuroimaging of mobility in aging: a targeted review. , 2014, The journals of gerontology. Series A, Biological sciences and medical sciences.

[5]  C. Jack,et al.  Age-specific population frequencies of cerebral β-amyloidosis and neurodegeneration among people with normal cognitive function aged 50–89 years: a cross-sectional study , 2014, The Lancet Neurology.

[6]  Janet B W Williams,et al.  Diagnostic and Statistical Manual of Mental Disorders , 2013 .

[7]  V. Aboyans,et al.  Measurement and interpretation of the ankle-brachial index: a scientific statement from the American Heart Association. , 2012, Circulation.

[8]  C. Annweiler,et al.  Contribution of Brain Imaging to the Understanding Of Gait Disorders in Alzheimer’s Disease , 2012, American journal of Alzheimer's disease and other dementias.

[9]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease: Report of the NINCDS—ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease , 2011, Neurology.

[10]  Jeffrey Kaye,et al.  The trajectory of gait speed preceding mild cognitive impairment. , 2010, Archives of neurology.

[11]  Joseph T. Gwin,et al.  Motor control and aging: Links to age-related brain structural, functional, and biochemical effects , 2010, Neuroscience & Biobehavioral Reviews.

[12]  Jessica A. Grahn,et al.  The cognitive functions of the caudate nucleus , 2008, Progress in Neurobiology.

[13]  Christos Davatzikos,et al.  Measuring Brain Lesion Progression with a Supervised Tissue Classification System , 2008, MICCAI.

[14]  Christos Davatzikos,et al.  Computer-assisted Segmentation of White Matter Lesions in 3d Mr Images Using Support Vector Machine 1 , 2022 .

[15]  Yun Zhou,et al.  Using a reference tissue model with spatial constraint to quantify [11C]Pittsburgh compound B PET for early diagnosis of Alzheimer's disease , 2007, NeuroImage.

[16]  M. Caldwell,et al.  American Heart Association: Council on Cardiovascular Nursing , 2004, The Journal of cardiovascular nursing.

[17]  R Brookmeyer,et al.  Visual memory predicts Alzheimer’s disease more than a decade before diagnosis , 2003, Neurology.

[18]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[19]  A. Newman,et al.  Measuring Fitness in Healthy Older Adults: The Health ABC Long Distance Corridor Walk , 2001, Journal of the American Geriatrics Society.

[20]  L. Ferrucci,et al.  Measuring higher level physical function in well-functioning older adults: expanding familiar approaches in the Health ABC study. , 2001, The journals of gerontology. Series A, Biological sciences and medical sciences.

[21]  Luigi Ferrucci,et al.  Subsystems Contributing to the Decline in Ability to Walk: Bridging the Gap Between Epidemiology and Geriatric Practice in the InCHIANTI Study , 2000, Journal of the American Geriatrics Society.

[22]  S. Resnick,et al.  One-year age changes in MRI brain volumes in older adults. , 2000, Cerebral cortex.

[23]  L M Giambra,et al.  Changes in immediate visual memory predict cognitive impairment. , 1995, Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists.

[24]  D. T. Vernier,et al.  Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. , 1990, Journal of lipid research.