Background: Brain-predicted age estimates are used to quantify an individual's brain age compared to a normative trajectory. We have recently shown that brain age from structural MRI is elevated in autosomal dominant Alzheimer disease (ADAD), a unique sample that allows the study of AD progression independently of age-related confounds. Resting-state functional connectivity (FC) may capture a biphasic response to sporadic AD, and thus may complement structural measures of brain aging in ADAD.
Method: We trained a Gaussian Process Regression (GPR) model to predict age from FC in 271 regions of interest in 779 cognitively unimpaired, amyloid-negative, non-ADAD participants. We applied the model in a cohort of 256 ADAD mutation carriers (MCs) and 200 familial non-carrier controls (NCs) from the Dominantly Inherited Alzheimer Network (DIAN). We then assessed whether the brain age gap (FC-BAG; difference between predicted and actual age) varied based on mutation status, cognitive status, or estimated years until symptom onset (EYO). We also explored its associations with markers of amyloid (PiB PET, CSF amyloid-ß-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament light (NfL)), and cognition (global neuropsychological composite and CDR®-sum of boxes).
Result: The model accurately predicted age in the training set (r = 0.77), validation set (r = 0.76), and DIAN NCs (r = 0.82), Figure 1. FC-BAG was elevated in symptomatic MCs (p < .001), but only marginal elevation was observed in asymptomatic MCs (p = 0.047), Figure 2. In symptomatic MCs, FC-BAG weakly associated with pTau-181 in CSF (r = 0.34, p = 0.0046) and plasma (r = 0.26, p = 0.02), but no other associations with AD biomarkers or cognition were observed, Figure 3.
Conclusion: FC-BAG was elevated in symptomatic ADAD, consistent with recent demonstrations in sporadic AD. However, we did not detect a predicted biphasic response to presymptomatic ADAD pathology. This inconsistency may be driven by differences between AD forms or by low reliability of FC, which may result in low statistical power and inconsistent brain-behavior relationships. FC-based BAG offers unique benefits but ultimately does not function as a reliable model for observing advanced aging in preclinical ADAD.
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http://dx.doi.org/10.1002/alz.093634 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
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Materials And Methods: A total of 321 subjects were enrolled in this study.
BMC Gastroenterol
January 2025
Department of Gastroenterology, Pomeranian Medical University in Szczecin, Unii Lubelskiej 1, Szczecin, 71-254, Poland.
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Methods: We conducted a cross-sectional study of 2070 Caucasian patients (58.
J Headache Pain
January 2025
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.
View Article and Find Full Text PDFBMC Geriatr
January 2025
Unit 4-Department of Geriatric Medicine, the Fourth People's Hospital of Chengdu, Chengdu City, China.
Background: With the aging of society, cognitive impairment in elderly people is becoming increasingly common and has caused major public health problems. The screening of cognitive impairment in elderly people and its related influencing factors can aid in the development of relevant intervention and improvement strategies.
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Reprod Sci
January 2025
Department of Biology, Faculty of Science, University of Qom, Qom, 3716146611, Iran.
Fluoxetine is used in the management of depression, anxiety and other mood disorders by increasing serotonin levels in the brain and can cause sexual side effects by changing the homeostasis of sex hormones and increasing oxidative stress. Since many men who take fluoxetine are of reproductive age and sperm are exposed to fluoxetine for a considerable time, this study aimed to examine the in vitro effects of fluoxetine on human sperm biochemical markers and sperm parameters. Semen samples from 30 fertile men were divided into three groups: a positive control group, a negative control group and a fluoxetine-treated group.
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