P3-101: CROSS-SECTIONAL BIOMARKER CHARACTERIZATION OF MILD COGNITIVE IMPAIRMENT PATIENTS IN WP5 PHARMACOG/E-ADNI STUDY

2014 ◽  
Vol 10 ◽  
pp. P665-P665 ◽  
Author(s):  
Samantha Galluzzi ◽  
Moira Marizzoni ◽  
Claudio Babiloni ◽  
David Bartrés-Faz ◽  
Olivier Blin ◽  
...  
2020 ◽  
Vol 17 (6) ◽  
pp. 556-565
Author(s):  
Yujie Guo ◽  
Pengfei Li ◽  
Xiaojun Ma ◽  
Xiaochen Huang ◽  
Zhuoheng Liu ◽  
...  

Background: The present study was designed to examine the association of circulating cholesterol with cognitive function in non-demented community aging adults. Methods: This was a cross-sectional study including 1754 Chinese adults aged 55-80 years. The association between serum cholesterol levels and cognitive function was examined. Participants were categorized into four groups according to the quartile of circulating TC (total cholesterol), High Density Lipoprotein Cholesterol (HDL-c), Low Density Lipoprotein Cholesterol (LDL-c) levels and HDLc/ LDL-c ratio. The difference in cognitive performance among the groups was compared. Logistic regression model was used to determine the association of circulating cholesterol level with the risk of Mild Cognitive Impairment (MCI). Results: Mild increase of serum LDL-c level correlated with better visual and executive, language, memory and delayed recall abilities. Higher circulating TC and HDL-c levels were found to be associated with poorer cognitive function, especially in aging female subjects. Higher circulating TC, HDL-c and HDL/LDL ratio indicated an increased risk of MCI, especially in female subjects. Conclusion: Slight increase in circulating LDL-c level might benefit cognitive function in aging adults. However, higher circulating TC and HDL-c levels might indicate a decline of cognitive function, especially in aging female subjects.


2021 ◽  
Author(s):  
James E. Galvin ◽  
Stephanie Chrisphonte ◽  
Iris Cohen ◽  
Keri K. Greenfield ◽  
Michael J. Kleiman ◽  
...  

BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e046879
Author(s):  
Bernhard Grässler ◽  
Fabian Herold ◽  
Milos Dordevic ◽  
Tariq Ali Gujar ◽  
Sabine Darius ◽  
...  

IntroductionThe diagnosis of mild cognitive impairment (MCI), that is, the transitory phase between normal age-related cognitive decline and dementia, remains a challenging task. It was observed that a multimodal approach (simultaneous analysis of several complementary modalities) can improve the classification accuracy. We will combine three noninvasive measurement modalities: functional near-infrared spectroscopy (fNIRS), electroencephalography and heart rate variability via ECG. Our aim is to explore neurophysiological correlates of cognitive performance and whether our multimodal approach can aid in early identification of individuals with MCI.Methods and analysisThis study will be a cross-sectional with patients with MCI and healthy controls (HC). The neurophysiological signals will be measured during rest and while performing cognitive tasks: (1) Stroop, (2) N-back and (3) verbal fluency test (VFT). Main aims of statistical analysis are to (1) determine the differences in neurophysiological responses of HC and MCI, (2) investigate relationships between measures of cognitive performance and neurophysiological responses and (3) investigate whether the classification accuracy can be improved by using our multimodal approach. To meet these targets, statistical analysis will include machine learning approaches.This is, to the best of our knowledge, the first study that applies simultaneously these three modalities in MCI and HC. We hypothesise that the multimodal approach improves the classification accuracy between HC and MCI as compared with a unimodal approach. If our hypothesis is verified, this study paves the way for additional research on multimodal approaches for dementia research and fosters the exploration of new biomarkers for an early detection of nonphysiological age-related cognitive decline.Ethics and disseminationEthics approval was obtained from the local Ethics Committee (reference: 83/19). Data will be shared with the scientific community no more than 1 year following completion of study and data assembly.Trial registration numberClinicalTrials.gov, NCT04427436, registered on 10 June 2020, https://clinicaltrials.gov/ct2/show/study/NCT04427436.


2009 ◽  
Vol 5 (4S_Part_13) ◽  
pp. P383-P383
Author(s):  
Simon Forstmeier ◽  
Michael Wagner ◽  
Wolfgang Maier ◽  
Hendrik Van Den Bussche ◽  
Birgitt Wiese ◽  
...  

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