Amyloid‐β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest‐old

Abstract

Objective To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition. Methods We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [18F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas. Results Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy. Interpretation These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.

Bridging Patterns of Neurocognitive Aging Across the Older Adult Lifespan

“…Slower rates of memory decline have also been associated with larger baseline whole brain volume across the older adult lifespan (Carmichael et al, 2012). Cross-sectional studies similarly report that oldest-old adults with larger hippocampus volumes have better episodic memory performance (Eguchi et al, 2019) and faster processing speeds (Legdeur et al, 2020;Pelkmans et al, 2021), comparable to what has been reported in younger-old adults (Carr et al, 2017;Gorbach et al, 2017;O'Shea et al, 2016).…”

“…Several studies have shown that fewer WMH and better microstructure (e.g., higher FA, lower diffusivity) relates to better cognitive performance into advanced age, with the most studied cognitive domains being episodic memory, executive functions, and processing speed (Table 2). For example, within oldest-old adults, those with slower rates of memory decline also had fewer baseline WMH across the brain (Pelkmans et al, 2021). Better episodic memory performance has also been related specifically to better medial temporal white matter microstructure (65-98 years; Merenstein et al, 2021), as well as better hippocampal gray matter microstructure across the older adult (56-99 years; Reas et al, 2021) and entire (4-93 years; Langnes et al, 2020) lifespan.…”

“…Their results have predominantly revealed positive associations with hippocampal volume or medial temporal cortical thickness using a variety of study designs (cross-sectional, longitudinal) and age groups (entire lifespan, older adult lifespan, oldest-old only). For example, slower rates of episodic memory decline assessed longitudinally were seen within oldest-old adults with fewer changes in hippocampal volume (Legdeur et al, 2019) and higher baseline medial temporal and anterior cingulate cortical thickness (Pelkmans et al, 2021). Slower rates of memory decline have also been associated with larger baseline whole brain volume across the older adult lifespan (Carmichael et al, 2012).…”

“…For executive functions, older adults who accumulated fewer brain-wide WMH over time had smaller declines in performance (Carmichael et al, 2012), although the association between WMH burden and executive functions may be weaker in oldest-old adults (Legdeur et al, 2019). For processing speed, faster performance within oldest-old adults has been associated with fewer brain-wide WMH (Pelkmans et al, 2021) and better microstructure of the corticospinal tract (Lövdén et al, 2014), uncinate and superior longitudinal fasciculi (Rosano et al, 2015), and whole brain white matter (Venkatraman et al, 2011). Relationships between microstructure and processing speed in individuals across the older adult lifespan remained significant after accounting for the future development of dementia (Haynes et al, 2017) or excluding individuals meeting criteria for preclinical dementia (Laukka et al, 2013), suggesting that these effects are not solely driven by pathological aging.…”

Bridging patterns of neurocognitive aging across the older adult lifespan

“…Slower rates of episodic memory decline assessed longitudinally have been reported within oldest-old adults with fewer changes in hippocampal volume (Legdeur et al, 2019) and higher baseline medial temporal and anterior cingulate cortical thickness (Pelkmans et al, 2021). Slower rates of memory decline have also been associated with larger baseline whole brain volume across the older adult lifespan (Carmichael et al, 2012).…”