scholarly journals Comparison of PC and iPad administrations of the Cogstate Brief Battery in the Mayo Clinic Study of Aging: Assessing cross-modality equivalence of computerized neuropsychological tests

2018 ◽  
Vol 33 (6) ◽  
pp. 1102-1126 ◽  
Author(s):  
Nikki H. Stricker ◽  
Emily S. Lundt ◽  
Kelly K. Edwards ◽  
Mary M. Machulda ◽  
Walter K. Kremers ◽  
...  
2021 ◽  
pp. 1-11
Author(s):  
Xuewei Wang ◽  
Hai Bui ◽  
Prashanthi Vemuri ◽  
Jonathan Graff-Radford ◽  
Clifford R. Jack Jr ◽  
...  

Background: Lipid alterations contribute to Alzheimer’s disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. Objective: To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groups Methods: Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Results: Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Conclusion: Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.


2016 ◽  
Vol 55 (2) ◽  
pp. 559-567 ◽  
Author(s):  
Rodolfo Savica ◽  
Alexandra M.V. Wennberg ◽  
Clinton Hagen ◽  
Kelly Edwards ◽  
Rosebud O. Roberts ◽  
...  

2009 ◽  
Vol 5 (4S_Part_12) ◽  
pp. P354-P355
Author(s):  
Kejal Kantarci ◽  
Ronald C. Petersen ◽  
Ali R. Samikoglu ◽  
Maria M. Shiung ◽  
Scott A. Przybelski ◽  
...  

2019 ◽  
Vol 15 ◽  
pp. P1141-P1142
Author(s):  
Mary M. Machulda ◽  
Emily S. Lundt ◽  
Sabrina M. Albertson ◽  
Anthony J. Spychalla ◽  
Michelle M. Mielke ◽  
...  

2014 ◽  
Vol 10 ◽  
pp. P527-P527 ◽  
Author(s):  
Nathanael Tigistu Feder ◽  
Mairead M. Bartley ◽  
Jazmin I. Acosta ◽  
Rosebud O. Roberts ◽  
David S. Knopman ◽  
...  

2015 ◽  
Vol 45 (4) ◽  
pp. 1237-1245 ◽  
Author(s):  
Maria Vassilaki ◽  
Ruth H. Cha ◽  
Jeremiah A. Aakre ◽  
Terry M. Therneau ◽  
Yonas E. Geda ◽  
...  

2008 ◽  
Vol 30 (1) ◽  
pp. 58-69 ◽  
Author(s):  
Rosebud O. Roberts ◽  
Yonas E. Geda ◽  
David S. Knopman ◽  
Ruth H. Cha ◽  
V. Shane Pankratz ◽  
...  

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2067-2067
Author(s):  
Alissa Butts ◽  
Jeremy A. Syrjanen ◽  
Jeremiah Aakre ◽  
Paul D. Brown ◽  
Clifford R. Jack ◽  
...  

2067 Background: An estimated 2% of the general population has a meningioma (Vernooij et al. 2007), which accounts for about 36% of all primary intracranial tumors (Ostrom et al. 2015). The most established risk factors are older age and female gender. One small study identified gender but no other risk factors with meningioma (Krampla et al 2004). A larger study using the Iowa Women’s Health study data found lower levels of physical activity, greater body mass index (BMI), greater height and uterine fibroids were associated with meningioma (Johnson et al. 2011). We sought to replicate these findings and to identify additional risk factors related to meningioma in a large population-based sample. Methods: Study participants were enrolled in the Mayo Clinic Study of Aging (MCSA), a population-based sample of Olmsted County, Minnesota residents used to study prevalence, incidence, and risk-factors for Mild Cognitive Impairment and dementia and includes a variety of medical factors. Using a text search of radiologists’ notes of 2,402 MCSA individuals, mean age 77±8 years and scanned between 2004-2014.We identified 52 subjects who had at least one meningioma. We estimated the association of selected potential risk factors with presence of meningioma using odds ratios and 95% confidence intervals from logistic regression models adjusted for age and gender, which informed the multivariable models. Results: In the initial models, significant risk factors identified included BMI (as a continuous variable) (OR = 1.06 95%CI 1.01 to 1.12), taking NSAIDS (OR = 2.11, 95%CI 1.13 to 3.95), aspirin (OR = 1.90, 95%CI 1.04 to 3.46), and blood pressure lowering medication (OR = 2.06, 95%CI 1.07 to 3.99). Protective factors included male gender (OR = 0.51, 95%CI 0.29 to 0.90), coronary artery disease (CAD; OR = 0.46, 95%CI 0.22 to 0.97) and higher Beck Anxiety Inventory (BAI) total score (OR = 0.88, 95%CI 0.78 to 0.98). Simultaneous adjustment for these factors in a multivariable model did not attenuate these associations. Conclusions: Findings reveal gender and BMI as risk factors for meningioma. Additionally, certain medications such as NSAIDS and BP lowering medications warrant follow up as potential factors related to development of meningioma.


2012 ◽  
Vol 8 (4S_Part_17) ◽  
pp. P622-P622
Author(s):  
Ronald Petersen ◽  
David Knopman ◽  
Clifford Jack ◽  
Heather Wiste ◽  
Stephen Weigand ◽  
...  
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