scholarly journals Higher serum total cholesterol levels in late middle age are associated with glucose hypometabolism in brain regions affected by Alzheimer's disease and normal aging

NeuroImage ◽  
2010 ◽  
Vol 49 (1) ◽  
pp. 169-176 ◽  
Author(s):  
Eric M. Reiman ◽  
Kewei Chen ◽  
Jessica B.S. Langbaum ◽  
Wendy Lee ◽  
Cole Reschke ◽  
...  
1998 ◽  
Vol 17 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Irma-Leena Notkola ◽  
Raimo Sulkava ◽  
Juha Pekkanen ◽  
Timo Erkinjuntti ◽  
Christian Ehnholm ◽  
...  

2014 ◽  
Vol 34 (7) ◽  
pp. 1169-1179 ◽  
Author(s):  
Felix Carbonell ◽  
Arnaud Charil ◽  
Alex P Zijdenbos ◽  
Alan C Evans ◽  
Barry J Bedell ◽  
...  

Positron emission tomography (PET) studies using [18F]2-fluoro-2-deoxyglucose (FDG) have identified a well-defined pattern of glucose hypometabolism in Alzheimer's disease (AD). The assessment of the metabolic relationship among brain regions has the potential to provide unique information regarding the disease process. Previous studies of metabolic correlation patterns have demonstrated alterations in AD subjects relative to age-matched, healthy control subjects. The objective of this study was to examine the associations between β-amyloid, apolipoprotein ε4 (APOE ε4) genotype, and metabolic correlations patterns in subjects diagnosed with mild cognitive impairment (MCI). Mild cognitive impairment subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were categorized into β-amyloid-low and β-amyloid-high groups, based on quantitative analysis of [18F]florbetapir PET scans, and APOE ε4 non-carriers and carriers based on genotyping. We generated voxel-wise metabolic correlation strength maps across the entire cerebral cortex for each group, and, subsequently, performed a seed-based analysis. We found that the APOE ε4 genotype was closely related to regional glucose hypometabolism, while elevated, fibrillar β-amyloid burden was associated with specific derangements of the metabolic correlation patterns.


Neurology ◽  
1999 ◽  
Vol 52 (9) ◽  
pp. 1861-1861 ◽  
Author(s):  
L. Backman ◽  
J. L. R. Andersson ◽  
L. Nyberg ◽  
B. Winblad ◽  
A. Nordberg ◽  
...  

2007 ◽  
Vol 55 (1) ◽  
pp. 133-135 ◽  
Author(s):  
Francesco Panza ◽  
Cristiano Capurso ◽  
Alessia D'Introno ◽  
Anna M. Colacicco ◽  
Dorotea De Candia ◽  
...  

2021 ◽  
pp. 1-10
Author(s):  
Michelle M. Dunk ◽  
Ira Driscoll ◽  

Background: APOE ɛ4 allele confers greatest genetic risk for Alzheimer’s disease (AD), yet mechanisms underlying this risk remain elusive. APOE is involved in lipid metabolism, and literature suggest relationships between high total cholesterol, APOE, and AD. Further investigation is needed to elucidate the potential role of total cholesterol in AD risk. Objective: To investigate the relationship between total cholesterol and APOE-related AD risk in the Alzheimer’s Disease Neuroimaging Initiative. Methods: Participants (N = 1,534) were classified as controls (cognitively normal; N = 404), early mild cognitive impairment (MCI; N = 294), late MCI (N = 539), or AD (N = 297). Total cholesterol levels were compared across APOE genotype and diagnosis. Mendelian randomization was performed to examine causality between total cholesterol and AD risk using APOE as a genetic instrument. Results: Total cholesterol was higher in APOE4+ compared to APOE3 and APOE2+ (ps < 0.04) carriers. Those with AD and late MCI (ps < 0.001) had higher total cholesterol than the control group. Comparing APOE4+ to APOE3 carriers, the predicted odds ratios per mg/dL greater total cholesterol were 1.11 for MCI (95% confidence interval, 1.04–7.32), 1.05 for early MCI (1.01–3.22), 1.13 for late MCI (1.05–11.70), 1.21 for AD (1.09–54.05), and 1.13 for composite dementia (MCI or AD; 1.06–11.59) (ps < 0.05, F-statistics>10). Conclusion: Higher total cholesterol may be a significant contributor to AD risk, particularly in APOE4 carriers who, based on existing literature, tend to have impaired cholesterol metabolism. Our findings highlight a possible mechanism by which APOE confers AD risk and indicate potential for AD risk modification through maintenance of healthy total cholesterol levels.


2008 ◽  
Vol 4 ◽  
pp. T538-T538
Author(s):  
Lidia Glodzik ◽  
Wai Tsui ◽  
Lisa Mosconi ◽  
Miroslaw Brys ◽  
Susan De Santi ◽  
...  

2006 ◽  
Vol 41 (9) ◽  
pp. 805-806 ◽  
Author(s):  
Francesco Panza ◽  
Cristiano Capurso ◽  
Alessia D’Introno ◽  
Anna M. Colacicco ◽  
Federico Vasquez ◽  
...  

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.


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