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Network Neuroscience (Cambridge, Mass.) 2024[This corrects the article DOI: 10.1162/netn_a_00224.].
[This corrects the article DOI: 10.1162/netn_a_00224.].
PubMed: 38952811
DOI: 10.1162/netn_x_00380 -
Clinical Epidemiology 2024Frozen shoulder may be an early preclinical symptom of Parkinson's disease (PD).
BACKGROUND
Frozen shoulder may be an early preclinical symptom of Parkinson's disease (PD).
OBJECTIVE
To examine PD risk after frozen shoulder diagnosis and to evaluate this disorder as a possible manifestation of parkinsonism preceding the clinical recognition of PD and possible target for screening.
METHODS
Danish population-based medical registries were used to identify patients aged ≥40 years with a first-time frozen shoulder diagnosis (1995-2016). A comparison cohort was randomly selected from the general population matched on age and sex. To address detection bias and the specificity of frozen shoulder diagnosis, we performed a sensitivity analysis, using similar matching criteria to select a cohort of patients with back pain diagnosis. The outcome was incident PD. Cumulative incidences and adjusted hazard ratios (HRs) were estimated with 95% confidence intervals (CIs).
RESULTS
We identified 37,041 individuals with frozen shoulder, 370,410 general population comparators, and 111,101 back pain comparators. The cumulative incidence of PD at 0-22 years follow-up was 1.51% in the frozen shoulder cohort, 1.03% in the general population cohort, and 1.32% in the back pain cohort. For frozen shoulder versus general population, adjusted HRs were 1.94 (CI: 1.20-3.13) at 0-1 years and 1.45 (CI: 1.24-1.70) at 0-22 years follow-up. For frozen shoulder versus back pain, adjusted HRs were 0.89 (CI: 0.54-1.46) and 1.01 (CI: 0.84-1.21), respectively.
CONCLUSION
Patients with frozen shoulder had an increased PD risk compared with the general population, although the absolute risks were low. Frozen shoulder might sometimes represent early manifestations of PD. Detection bias probably cannot account for the increased PD risk during the long-term follow-up.
PubMed: 38952571
DOI: 10.2147/CLEP.S463571 -
Frontiers in Aging Neuroscience 2024Studying the spatiotemporal patterns of amyloid accumulation in the brain over time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography...
INTRODUCTION
Studying the spatiotemporal patterns of amyloid accumulation in the brain over time is crucial in understanding Alzheimer's disease (AD). Positron Emission Tomography (PET) imaging plays a pivotal role because it allows for the visualization and quantification of abnormal amyloid beta (Aβ) load in the living brain, providing a powerful tool for tracking disease progression and evaluating the efficacy of anti-amyloid therapies. Generative artificial intelligence (AI) can learn complex data distributions and generate realistic synthetic images. In this study, we demonstrate for the first time the potential of Generative Adversarial Networks (GANs) to build a low-dimensional representation space that effectively describes brain amyloid load and its dynamics.
METHODS
Using a cohort of 1,259 subjects with AV45 PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we develop a 3D GAN model to project images into a latent representation space and generate back synthetic images. Then, we build a progression model on the representation space based on non-parametric ordinary differential equations to study brain amyloid evolution.
RESULTS
We found that global SUVR can be accurately predicted with a linear regression model only from the latent representation space ( = 0.08 ± 0.01). We generated synthetic PET trajectories and illustrated predicted Aβ change in four years compared with actual progression.
DISCUSSION
Generative AI can generate rich representations for statistical prediction and progression modeling and simulate evolution in synthetic patients, providing an invaluable tool for understanding AD, assisting in diagnosis, and designing clinical trials. The aim of this study was to illustrate the huge potential that generative AI has in brain amyloid imaging and to encourage its advancement by providing use cases and ideas for future research tracks.
PubMed: 38952479
DOI: 10.3389/fnagi.2024.1410844 -
Aging & Mental Health Jul 2024The current study aimed to evaluate the relationship between subjective cognitive complaints (SCC) and compensatory strategy (CS) use in a diverse sample of non-Latinx...
OBJECTIVES
The current study aimed to evaluate the relationship between subjective cognitive complaints (SCC) and compensatory strategy (CS) use in a diverse sample of non-Latinx White (NLW), Black, and Latinx American older adults.
METHOD
807 older adults ( = 65.38, 62.7% female) were recruited through Amazon's Mechanical Turk (MTurk) and Qualtrics Panel to complete questionnaires on SCC and CS use. Kruskall-Wallis tests were used to evaluate differences in SCC across groups given non-normal distributions. Analysis of variance (ANOVA) was used to evaluate group differences in CS use. The PROCESS macro for SPSS was used to examine whether demographic factors moderated the relationship between SCC and CS use.
RESULTS
NLWs reported higher levels of SCC and greater overall use of CS in comparison to Latinx and Black individuals. Several demographic and psychosocial factors including age, ethno-racial group, education, and anxiety level were found to be associated with CS use. Education was found to moderate the association between SCC and CS use.
CONCLUSION
Inconsistent with prior studies, our study found that NLWs reported the highest levels of SCC. CS were used across all racial/ethnic groups, but the frequency of CS use may be impacted by education level. While all education groups increased their CS in response to higher levels of SCC, this increase was more substantial for those with lower levels of education. Future work should consider individuals' cultural and educational background when examining SCC and/or developing CS-based intervention for the aging population.
PubMed: 38952264
DOI: 10.1080/13607863.2024.2367060 -
Physical Chemistry Chemical Physics :... Jul 2024The hallmark of amyloidosis, such as Alzheimer's disease and Parkinson's disease, is the deposition of amyloid fibrils in various internal organs. The onset of the...
The hallmark of amyloidosis, such as Alzheimer's disease and Parkinson's disease, is the deposition of amyloid fibrils in various internal organs. The onset of the disease is related to the strength of cytotoxicity caused by toxic amyloid species. Furthermore, amyloid fibrils show polymorphism, where some types of fibrils are cytotoxic while others are not. It is thus essential to understand the molecular mechanism of cytotoxicity, part of which is caused by the interaction between amyloid polymorphic fibrils and cell membranes. Here, using amyloid polymorphs of hen egg white lysozyme, which is associated with hereditary systemic amyloidosis, showing different levels of cytotoxicity and liposomes of DMPC and DMPG, changes in the secondary structure of the polymorphs and the structural state of phospholipid membranes caused by the interaction were investigated using vacuum-ultraviolet circular dichroism (VUVCD) and Laurdan fluorescence measurements, respectively. Analysis has shown that the more cytotoxic polymorph increases the antiparallel β-sheet content and causes more disorder in the membrane structure while the other less cytotoxic polymorph shows the opposite structural changes and causes less structural disorder in the membrane. These results suggest a close correlation between the structural properties of amyloid fibrils and the degree of structural disorder of phospholipid membranes, both of which are involved in the fundamental process leading to amyloid cytotoxicity.
PubMed: 38952218
DOI: 10.1039/d4cp00965g -
Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.Zhongguo Ying Yong Sheng Li Xue Za Zhi... Jul 2024The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has... (Review)
Review
The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means of identifying these crippling illnesses. As a subset of computational intelligence, machine-learning algorithms have become very effective tools for the analysis of large datasets that include genetic, imaging, and clinical data. Moreover, multi-modal data integration, which includes information from brain imaging (MRI, PET scans), genetic profiles, and clinical evaluations, is made easier by computational intelligence. A thorough knowledge of the course of the illness is made possible by this consolidative method, which also facilitates the creation of predictive models for early medical evaluation and outcome prediction. Furthermore, there has been a great deal of promise shown by the use of artificial intelligence to neuroimaging analysis. Sophisticated image processing methods combined with machine learning algorithms make it possible to identify functional and structural anomalies in the brain, which often act as early indicators of neurodegenerative diseases. This chapter examines how computational intelligence plays a critical role in improving the diagnosis of neurodegenerative diseases such as Parkinson's, Alzheimer's, etc. To sum up, computational intelligence provides a revolutionary approach for improving the identification of neurodegenerative illnesses. In the battle against these difficult disorders, embracing and improving these computational techniques will surely pave the path for more individualized therapy and more therapies that are successful.
Topics: Humans; Neurodegenerative Diseases; Computational Biology; Neuroimaging; Machine Learning; Algorithms; Artificial Intelligence; Brain; Image Processing, Computer-Assisted; Magnetic Resonance Imaging
PubMed: 38952174
DOI: 10.62958/j.cjap.2024.008 -
Annals of Clinical and Translational... Jul 2024To examine the associations of renin-angiotensin system (RAS) inhibitor use with postmortem brain insulin signaling and neuropathology.
OBJECTIVE
To examine the associations of renin-angiotensin system (RAS) inhibitor use with postmortem brain insulin signaling and neuropathology.
METHODS
Among Religious Orders Study participants, 150 deceased and autopsied older individuals (75 with diabetes matched to 75 without by age at death, sex, and education) had measurements of insulin receptor substrate-1 (IRS-1) and RAC-alpha serine/threonine protein kinase (AKT1) collected in the prefrontal cortex using ELISA and immunohistochemistry. Alzheimer's disease (AD), brain infarcts, and cerebral vessel pathology data were assessed by systematic neuropathologic evaluations. RAS inhibitor use was determined based on visual inspection of medication containers during study visits. The associations of RAS inhibitor use with brain insulin signaling measures and neuropathology were examined using adjusted regression analyses.
RESULTS
Of the 90 RAS inhibitor users (54 with diabetes), 65 had used only angiotensin-converting enzyme inhibitors, 11 only angiotensin II receptor blockers, and 14 used both. RAS inhibitor use was associated with lower pTAKT1/total AKT1, but not with pSIRS-1/total IRS-1 or the density of cells stained positive for pS IRS-1. RAS inhibitor use was not associated with the level of global AD pathology or amyloid beta burden, but it was associated with a lower tau-neurofibrillary tangle density. Additionally, we found a significant interaction between diabetes and RAS inhibitors on tangle density. Furthermore, AKT1 phosphorylation partially mediated the association of RAS inhibitor use with tau tangle density. Lastly, RAS inhibitor use was associated with more atherosclerosis, but not with other cerebral blood vessel pathologies or cerebral infarcts.
INTERPRETATION
Late-life RAS inhibitor use may be associated with lower brain AKT1 phosphorylation and fewer neurofibrillary tangles.
PubMed: 38952081
DOI: 10.1002/acn3.52132 -
Aging Cell Jul 2024Alzheimer's disease (AD) is a neurodegenerative disorder associated with behavioral and cognitive impairments. Unfortunately, the drugs the Food and Drug Administration...
Alzheimer's disease (AD) is a neurodegenerative disorder associated with behavioral and cognitive impairments. Unfortunately, the drugs the Food and Drug Administration currently approved for AD have shown low effectiveness in delaying the progression of the disease. The focus has shifted to non-pharmacological interventions (NPIs) because of the challenges associated with pharmacological treatments for AD. One such intervention is environmental enrichment (EE), which has been reported to restore cognitive decline associated with AD effectively. However, the therapeutic mechanisms by which EE improves symptoms associated with AD remain unclear. Therefore, this study aimed to reveal the mechanisms underlying the alleviating effects of EE on AD symptoms using histological, proteomic, and neurotransmitter-related analyses. Wild-type (WT) and 5XFAD mice were maintained in standard housing or EE conditions for 4 weeks. First, we confirmed the mitigating effects of EE on cognitive impairment in an AD animal model. Then, histological analysis revealed that EE reduced Aβ accumulation, neuroinflammation, neuronal death, and synaptic loss in the AD brain. Moreover, proteomic analysis by liquid chromatography-tandem mass spectrometry showed that EE enhanced synapse- and neurotransmitter-related networks and upregulated synapse- and neurotransmitter-related proteins in the AD brain. Furthermore, neurotransmitter-related analyses showed an increase in acetylcholine and serotonin concentrations as well as a decrease in polyamine concentration in the frontal cortex and hippocampus of 5XFAD mice raised under EE conditions. Our findings demonstrate that EE restores cognitive impairment by alleviating AD pathology and regulating synapse-related proteins and neurotransmitters. Our study provided neurological evidence for the application of NPIs in treating AD.
PubMed: 38952076
DOI: 10.1111/acel.14231 -
Cell Biochemistry and Function Jul 2024This review rigorously investigates the early cerebral changes associated with Alzheimer's disease, which manifest long before clinical symptoms arise. It presents... (Review)
Review
This review rigorously investigates the early cerebral changes associated with Alzheimer's disease, which manifest long before clinical symptoms arise. It presents evidence that the dysregulation of calcium (Ca) homeostasis, along with mitochondrial dysfunction and aberrant autophagic processes, may drive the disease's progression during its asymptomatic, preclinical stage. Understanding the intricate molecular interplay that unfolds during this critical period offers a window into identifying novel therapeutic targets, thereby advancing the treatment of neurodegenerative disorders. The review delves into both established and emerging insights into the molecular alterations precipitated by the disruption of Ca balance, setting the stage for cognitive decline and neurodegeneration.
Topics: Humans; Alzheimer Disease; Mitochondria; Calcium; Mitophagy; Autophagy; Animals; Hemostasis; Homeostasis
PubMed: 38951992
DOI: 10.1002/cbf.4085 -
Alzheimer's Research & Therapy Jun 2024Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease...
BACKGROUND
Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are associated with self-reported problems with cognition as well as risk for Alzheimer's disease and related dementias (ADRD). Overlapping symptom profiles observed in cognitive disorders, psychiatric disorders, and environmental exposures (e.g., head injury) can complicate the detection of early signs of ADRD. The interplay between PTSD, head injury, subjective (self-reported) cognitive concerns and genetic risk for ADRD is also not well understood, particularly in diverse ancestry groups.
METHODS
Using data from the U.S. Department of Veterans Affairs (VA) Million Veteran Program (MVP), we examined the relationship between dementia risk factors (APOE ε4, PTSD, TBI) and subjective cognitive concerns (SCC) measured in individuals of European (n = 140,921), African (n = 15,788), and Hispanic (n = 8,064) ancestry (EA, AA, and HA, respectively). We then used data from the VA electronic medical record to perform a retrospective survival analysis evaluating PTSD, TBI, APOE ε4, and SCC and their associations with risk of conversion to ADRD in Veterans aged 65 and older.
RESULTS
PTSD symptoms (B = 0.50-0.52, p < 1E-250) and probable TBI (B = 0.05-0.19, p = 1.51E-07 - 0.002) were positively associated with SCC across all three ancestry groups. APOE ε4 was associated with greater SCC in EA Veterans aged 65 and older (B = 0.037, p = 1.88E-12). Results of Cox models indicated that PTSD symptoms (hazard ratio [HR] = 1.13-1.21), APOE ε4 (HR = 1.73-2.05) and SCC (HR = 1.18-1.37) were positively associated with risk for ADRD across all three ancestry groups. In the EA group, probable TBI also contributed to increased risk of ADRD (HR = 1.18).
CONCLUSIONS
The findings underscore the value of SCC as an indicator of ADRD risk in Veterans 65 and older when considered in conjunction with other influential genetic, clinical, and demographic risk factors.
Topics: Humans; Veterans; Stress Disorders, Post-Traumatic; Male; Female; Aged; Apolipoprotein E4; Dementia; Risk Factors; United States; Brain Injuries, Traumatic; Aged, 80 and over; Retrospective Studies
PubMed: 38951900
DOI: 10.1186/s13195-024-01512-w