Multimorbidity Is Associated with Preclinical Alzheimer’s Disease Neuroimaging Biomarkers

Abstract

Background: Identifying comorbidities that influence preclinical Alzheimer’s disease (AD) can give some insight into the AD early stages trajectories to allow new treatment venues and to guide public health systems to prevent subsequent dementia. Objective: To examine the association of multimorbidity with AD neuroimaging markers in cognitively normal older adults. Methods: This study had a cross-sectional design. Data regarding 14 comorbidities were obtained for all 318 adults aged 70–85 years, recruited from the community to an ongoing prospective monocentric cohort. They underwent standardized neuropsychological and neuroimaging assessment with automated methods that measured hippocampal volumes, white matter hyperintensity volumes, fluorodeoxyglucose positron emission tomography (FDG-PET) standardized uptake values (SUV) in AD signature regions, and amyloid positron emission tomography (amyloid-PET) SUV ratios. Linear regression was used to assess the association of multimorbidity with AD neuroimaging biomarkers. Results: Multimorbidity is signif icantly associated with lower hippocampal volumes (–0.03 ± 0.01; p = 0.012; R² = 0.017) and lower FDG-PET SUV (–0.027 ± 0.009; p = 0.005; R² = 0.022), with no association with amyloid deposition (0.001 ± 0.007; p = 0.884; R² = 0.0001). Taken individually, obesity and excessive alcohol use are associated with lower FDG-PET values, whereas obstructive sleep apnea and mood disorders are related to lower amyloid-PET SUV ratios. Conclusion: Multimorbidity is associated with preclinical AD imaging markers of neurodegeneration, but not with amyloid.

Accumulation of Cerebrospinal Fluid Glycerophospholipids and Sphingolipids in Cognitively Healthy Participants With Alzheimer’s Biomarkers Precedes Lipolysis in the Dementia Stage

“…Data normalization was performed using MetaboAnalyst software. Briefly, GP and SP data were converted to tab-delimited text (.txt) before import into the MetaboAnalyst Statistical Analysis platform (Mendes et al, 2018;Chong and Xia, 2020). Data normalization and scaling used globalized logarithm transformation (glog) and mean-centering to obtain a Gaussian distribution and compare lipid levels over several orders of magnitude in the SF and NP fractions.…”

White matter alterations in Alzheimer’s disease without concomitant pathologies

“…The combination of AD and cerebrovascular disease is very common [43‐49]. Other clinical co‐morbidities include arterial hypertension (HTA), type II diabetes, cardiac, hepatic and renal failure and respiratory insufficiency; pathological co‐morbidities include neurodegenerative disorders with abnormal protein aggregates such as other tauopathies, Lewy body diseases and TDP‐43 proteinopathies, among others and hippocampal sclerosis [50‐56].…”

Regional Cerebral Perfusion and Cerebrovascular Reactivity in Elderly Controls With Subtle Cognitive Deficits

“…The biological significance of these observations remains matter of debate. Cortical hypometabolism is a core feature in preclinical AD and is associated with worst clinical evolution (Ewers et al, 2013; Besson et al, 2015; Mendes et al, 2018). However, increased glucose metabolism was also reported in amyloid-negative amnestic MCI cases and is thought to reflect compensatory mechanism to the neuronal damage occurring early in the disease process (for review see Ashraf et al, 2015).…”