Results 91 to 100 of about 9,664,759 (367)

Cognitive Resilience in Apolipoprotein ε4 Carrier Women Predicted by Neuron‐Derived Extracellular Vesicles

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The Apolipoprotein (APOE) ε4 allele is the strongest genetic risk factor for late‐onset Alzheimer's disease (AD); however, many ε4 carriers remain cognitively intact into old age. Leveraging plasma neuron‐derived extracellular vesicles (NDEVs), we sought to identify biomarkers of cognitive resilience and their interplay with APOE ...
Apostolos Manolopoulos, Maja Mustapic, Carlos Nogueras‐Ortiz, Francheska Delgado‐Peraza, Krishna A. Pucha, Pamela J. Yao, Joseph Blommer, Michael P. Vreones, William York, De' Larrian Knight, Stephen R. Rapp, Aladdin H. Shadyab, JoAnn E. Manson, Ramon Casanova, Robert B. Wallace, Luigi Ferrucci, Susan M. Resnick, Dimitrios Kapogiannis   +17 more
wiley   +1 more source

Characterizing biomarker features of cognitively normal individuals with ventriculomegaly

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 2018
Introduction The clinical significance of ventriculomegaly in cognitively normal elderly individuals remains unclear. Methods We selected cognitively normal individuals (n = 425) from the Alzheimer's Disease Neuroimaging Initiative database and ...
Xiaofeng Li, Maowen Ba, Kok Pin Ng, Sulantha Mathotaarachchi, Tharick A. Pascoal, Pedro Rosa‐Neto, Serge Gauthier, Alzheimer's Disease Neuroimaging Initiative   +7 more
doaj   +1 more source

Insulin resistance is related to cognitive decline but not change in CSF biomarkers of Alzheimer's disease in non‐demented adults

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 2021
Introduction We investigated whether insulin resistance (IR) was associated with longitudinal age‐related change in cognition and biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration in middle‐aged and older adults who were non‐demented
Gilda E. Ennis, Rebecca L. Koscik, Yue Ma, Erin M. Jonaitis, Carol A. Van Hulle, Tobey J. Betthauser, Allison M. Randall, Nathaniel Chin, Corinne D. Engelman, Rozalyn Anderson, Ivonne Suridjan, Gwendlyn Kollmorgen, Bradley T. Christian, Cynthia M. Carlsson, Sanjay Asthana, Sterling C. Johnson, Henrik Zetterberg, Kaj Blennow, Barbara B. Bendlin   +18 more
doaj   +1 more source

Serum Neurofilament Light Chain in Multiple Sclerosis: Superiority of Age‐ and BMI‐Corrected Z Scores/Percentiles Over Absolute Cutoff Values for Prediction of Treatment Response

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Prognostication of disease course and prediction of treatment response in multiple sclerosis is an unmet need. We compared the performance of serum neurofilament light chain Z scores (age‐ and BMI‐adjusted) with absolute concentrations for the prediction of response to disease‐modifying therapy.
Maximilian Einsiedler, Aleksandra Maleska Maceski, Sofia Sandgren, Johanna Oechtering, Sabine Schaedelin, Lisa Hofer, Amar Zadic, Juan Francisco Vilchez Gomez, Lester Melie‐Garcia, Alessandro Cagol, Riccardo Galbusera, Sebastian Finkener, Patrice Lalive, Marjolaine Uginet, Stefanie Müller, Caroline Pot, Amandine Mathias, Renaud Du Pasquier, Robert Hoepner, Andrew Chan, Giulio Disanto, Chiara Zecca, Marcus D’Souza, Lars G. Hemkens, Tobias Derfuss, Özgür Yaldizli, Patrick Roth, Claudio Gobbi, David Brassat, Björn Tackenberg, Henrik Zetterberg, Tjalf Ziemssen, Heinz Wiendl, Klaus Berger, Marco Hermesdorf, Fredrik Piehl, Ludwig Kappos, Cristina Granziera, Ahmed Abdelhak, David Leppert, Eline A. J. Willemse, Pascal Benkert, Jens Kuhle, Swiss Multiple Sclerosis Cohort Study (SMSC)   +43 more
wiley   +1 more source

Association between BrainAGE and Alzheimer's disease biomarkers

Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
INTRODUCTION The brain age gap estimation (BrainAGE) method uses a machine learning model to generate an age estimate from structural magnetic resonance imaging (MRI) scans. The goal was to study the association of brain age with Alzheimer's disease (AD)
Yousaf Abughofah, Rachael Deardorff, Aaron Vosmeier, Savannah Hottle, Jeffrey L. Dage, Desarae Dempsey, Liana G. Apostolova, Jared Brosch, David Clark, Martin Farlow, Tatiana Foroud, Sujuan Gao, Sophia Wang, Henrik Zetterberg, Kaj Blennow, Andrew J. Saykin, Shannon L. Risacher   +16 more
doaj   +1 more source

Cytokine, Chemokine, and Neurofilament Light Chain Signatures in LGI1 Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives To investigate the value of cytokine, chemokine, and neurofilament light chain (NfL) concentrations in predicting relapse risk, chronic epilepsy, and functional impairment in LGI1 autoimmune encephalitis (AE). Methods Cytokines/chemokines (IL‐1‐beta, IL‐2, IL‐4, IL‐5, IL‐6, IL‐8/CXCL8, IL‐10, IL‐12p70, IL‐13, IL‐17A, GM‐CSF, TNF ...
Albert Aboseif, Georgios Mangioris, Binxia Yang, Vanessa K. Pazdernik, Jeffrey W. Britton, Divyanshu Dubey, Eoin P. Flanagan, Sarosh R. Irani, Gregory S. Day, Charles L. Howe, A. Sebastian López‐Chiriboga, Andrew McKeon, John R. Mills, Yahel Segal, Michel Toledano, Ivana Vodopivec, Sean J. Pittock, Anastasia Zekeridou   +17 more
wiley   +1 more source

Quick assessment for systematic test statistic inflation/deflation due to null model misspecifications in genome-wide environment interaction studies.

PLoS ONE, 2019
Gene-environment (GxE) interaction is one potential explanation for the missing heritability problem. A popular approach to genome-wide environment interaction studies (GWEIS) is based on regression models involving interactions between genetic variants ...
Masao Ueki, Masahiro Fujii, Gen Tamiya, for Alzheimer’s Disease Neuroimaging Initiative and the Alzheimer’s Disease Metabolomics Consortium   +3 more
doaj   +1 more source

Cognitive decline across five cognitive batteries: Sample size implications for clinical trials

Alzheimer’s & Dementia: Translational Research & Clinical Interventions
INTRODUCTION We evaluated the statistical power for a theoretical randomized trial of anti‐amyloid treatment in preclinical Alzheimer's Disease across five cognitive composites in preclinical Alzheimer's Disease across five cognitive composites ...
Andrea R. Zammit, Ana W. Capuano, Lisa L. Barnes, Julie A. Schneider, Reisa A. Sperling, David A. Bennett, Francine Grodstein   +6 more
doaj   +1 more source

Revealing heterogeneity of brain imaging phenotypes in Alzheimer's disease based on unsupervised clustering of blood marker profiles.

PLoS ONE, 2019
Alzheimer's disease (AD) affects millions of people and is a major rising problem in health care worldwide. Recent research suggests that AD could have different subtypes, presenting differences in how the disease develops.
Gerard Martí-Juan, Gerard Sanroma, Gemma Piella, Alzheimer’s Disease Neuroimaging Initiative and the Alzheimer’s Disease Metabolomics Consortium   +3 more
doaj   +1 more source

Mitochondrial dysfunction - the beginning of the end in Alzheimer's disease? Separate and synergistic modes of tau and amyloid-β toxicity

Alzheimer's Research & Therapy, 2011
The pathology of Alzheimer's disease (AD) is characterized by amyloid plaques (aggregates of amyloid-β (Aβ)) and neurofibrillary tangles (aggregates of tau) and is accompanied by mitochondrial dysfunction, but the mechanisms underlying this dysfunction ...
Anne Eckert, K. Schmitt, Jürgen Götz
semanticscholar   +1 more source