Antineuronal antibody screening in early onset-cognitive decline

2016 ◽  
Vol 51 (7) ◽  
pp. 736-737
Author(s):  
Faith Ng ◽  
James G Scott ◽  
George Bruxner
Keyword(s):  
Cognitive Decline ◽  
Early Onset ◽  
Antibody Screening ◽  
Antineuronal Antibody

Cannabidiol Ameliorates Cognitive Function via Regulation of IL-33 and TREM2 Upregulation in a Murine Model of Alzheimer’s Disease

2021 ◽  
pp. 1-5
Author(s):  
Hesam Khodadadi ◽  
Évila Lopes Salles ◽  
Abbas Jarrahi ◽  
Vincenzo Costigliola ◽  
MB Khan ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Cognitive Decline ◽  
Murine Model ◽  
Early Onset ◽  
Behavioral Tests ◽  
Translational Model ◽  
Therapeutic Modalities ◽  
Model Of Alzheimer’S Disease ◽  
5Xfad Mice ◽  
Motor Outcomes

There is a dire need for due innovative therapeutic modalities to improve outcomes of AD patients. In this study, we tested whether cannabidiol (CBD) improves outcomes in a translational model of familial AD and to investigate if CBD regulates interleukin (IL)-33 and triggering receptor expressed on myeloid cells 2 (TREM2), which are associated with improved cognitive function. CBD was administered to 5xFAD mice, which recapitulate early onset, familial AD. Behavioral tests and immunoassays were used to evaluate cognitive and motor outcomes. Our findings suggest that CBD treatment enhanced IL-33 and TREM2 expression, ameliorated the symptoms of AD, and retarded cognitive decline.

Challenging the notion of an early-onset of cognitive decline

2009 ◽  
Vol 30 (4) ◽  
pp. 521-524 ◽  
Author(s):  
Lars-Göran Nilsson ◽  
Ola Sternäng ◽  
Michael Rönnlund ◽  
Lars Nyberg
Keyword(s):  
Cognitive Decline ◽  
Early Onset

Early onset APOE E4-negative Alzheimer’s disease patients show faster cognitive decline on non-memory domains

2015 ◽  
Vol 25 (7) ◽  
pp. 1010-1017 ◽  
Author(s):  
Lieke L. Smits ◽  
Yolande A.L. Pijnenburg ◽  
Annelies E. van der Vlies ◽  
Esther L.G.E. Koedam ◽  
Femke H. Bouwman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Early Onset

scholarly journals Computational Causal Modeling of the Dynamic Biomarker Cascade in Alzheimer’s Disease

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Jeffrey R. Petrella ◽  
Wenrui Hao ◽  
Adithi Rao ◽  
P. Murali Doraiswamy
Keyword(s):  
Clinical Trials ◽  
Natural History ◽  
Cognitive Decline ◽  
Computational Model ◽  
Early Onset ◽  
Causal Model ◽  
Late Onset ◽  
Neuronal Loss ◽  
Prior Literature ◽  
Longitudinal Biomarker

Background. Alzheimer’s disease (AD) is a major public health concern, and there is an urgent need to better understand its complex biology and develop effective therapies. AD progression can be tracked in patients through validated imaging and spinal fluid biomarkers of pathology and neuronal loss. We still, however, lack a coherent quantitative model that explains how these biomarkers interact and evolve over time. Such a model could potentially help identify the major drivers of disease in individual patients and simulate response to therapy prior to entry in clinical trials. A current theory of AD biomarker progression, known as the dynamic biomarker cascade model, hypothesizes AD biomarkers evolve in a sequential but temporally overlapping manner. A computational model incorporating assumptions about the underlying biology of this theory and its variations would be useful to test and refine its accuracy with longitudinal biomarker data from clinical trials. Methods. We implemented a causal model to simulate time-dependent biomarker data under the descriptive assumptions of the dynamic biomarker cascade theory. We modeled pathologic biomarkers (beta-amyloid and tau), neuronal loss biomarkers, and cognitive impairment as nonlinear first-order ordinary differential equations (ODEs) to include amyloid-dependent and nondependent neurodegenerative cascades. We tested the feasibility of the model by adjusting its parameters to simulate three specific natural history scenarios in early-onset autosomal dominant AD and late-onset AD and determine whether computed biomarker trajectories agreed with current assumptions of AD biomarker progression. We also simulated the effects of antiamyloid therapy in late-onset AD. Results. The computational model of early-onset AD demonstrated the initial appearance of amyloid, followed by biomarkers of tau and neurodegeneration and the onset of cognitive decline based on cognitive reserve, as predicted by the prior literature. Similarly, the late-onset AD computational models demonstrated the first appearance of amyloid or nonamyloid-related tauopathy, depending on the magnitude of comorbid pathology, and also closely matched the biomarker cascades predicted by the prior literature. Forward simulation of antiamyloid therapy in symptomatic late-onset AD failed to demonstrate any slowing in progression of cognitive decline, consistent with prior failed clinical trials in symptomatic patients. Conclusions. We have developed and computationally implemented a mathematical causal model of the dynamic biomarker cascade theory in AD. We demonstrate the feasibility of this model by simulating biomarker evolution and cognitive decline in early- and late-onset natural history scenarios, as well as in a treatment scenario targeted at core AD pathology. Models resulting from this causal approach can be further developed and refined using patient data from longitudinal biomarker studies and may in the future play a key role in personalizing approaches to treatment.

O2-04-07: Most rapid cognitive decline in APOE4 negative Alzheimer's disease with early onset

2009 ◽  
Vol 5 (4S_Part_4) ◽  
pp. P111-P112
Author(s):  
Wiesje M. van der Flier ◽  
Annelies E. van der Vlies ◽  
Esther L. Koedam ◽  
Yolande A.L. Pijnenburg ◽  
Jos W.R. Twisk ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Early Onset ◽  
Rapid Cognitive Decline

scholarly journals Latent profile analysis of cognitive decline and depressive symptoms after intracerebral hemorrhage

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sophia Keins ◽  
Jessica R. Abramson ◽  
Juan Pablo Castello ◽  
Marco Pasi ◽  
Andreas Charidimou ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Intracerebral Hemorrhage ◽  
Cognitive Decline ◽  
Early Onset ◽  
Latent Profile Analysis ◽  
Late Onset ◽  
Profile Analysis ◽  
Clinical Genetic ◽  
Dementia Risk ◽  
Latent Profile

Abstract Background Cognitive impairment and depressive symptoms are highly prevalent after Intracerebral Hemorrhage (ICH). We leveraged Latent Profile Analysis (LPA) to identify profiles for cognitive decline and depression onset after ICH. We also investigated differences in clinical, genetic and neuroimaging characteristics across patients’ profiles. Methods We analyzed data from the ICH study conducted at Massachusetts General Hospital between January 1998 and December 2019. We collected information from electronical health records, follow-up interviews, CT and MRI imaging, and APOE genotype. We conducted LPA and multinomial logistic regression analyses to: 1) identify distinct profiles for cognitive decline and depression onset after ICH; 2) identify clinical, neuroimaging and genetic factors predicting individuals’ likelihood to express a specific profile. Results We followed 784 ICH survivors for a median of 45.8 months. We identified four distinct profiles in cognitive and depressive symptoms after ICH: low depression and dementia risk, early-onset depression and dementia, late-onset depression and dementia, high depression with low dementia risk. Cerebral small vessel disease severity and APOE genotype were specifically associated with the late-onset profile (both p < 0.05). Acute hematoma characteristics (size, intraventricular extension) and functional disability were specifically associated with the early-onset profile (all p < 0.05). Conclusion We identified four distinct profiles for cognitive and depressive symptoms after ICH, each displaying specific associations with individual patients’ clinical, genetic and neuroimaging data. These associations reflect separate biological mechanisms influencing dementia and depression risk after ICH. Our findings support employing LPA in future ICH studies, and is likely applicable to stroke survivors at large.

scholarly journals Early-Onset Dementia in War Veterans: Brain Polypathology and Clinicopathologic Complexity

2019 ◽  
Vol 79 (2) ◽  
pp. 144-162 ◽  
Author(s):  
Diego Iacono ◽  
Patricia Lee ◽  
Brian L Edlow ◽  
Nichelle Gray ◽  
Bruce Fischl ◽  
...  
Keyword(s):  
Cognitive Decline ◽  
Early Onset ◽  
Ex Vivo ◽  
Chronic Traumatic Encephalopathy ◽  
Post Traumatic Stress ◽  
Early Onset Dementia ◽  
Behavioral Abnormalities ◽  
Before And After ◽  
Clinicopathologic Findings ◽  
Pathologic Lesions

Abstract The neuropathology associated with cognitive decline in military personnel exposed to traumatic brain injury (TBI) and chronic stress is incompletely understood. Few studies have examined clinicopathologic correlations between phosphorylated-tau neurofibrillary tangles, β-amyloid neuritic plaques, neuroinflammation, or white matter (WM) lesions, and neuropsychiatric disorders in veterans. We describe clinicopathologic findings in 4 military veterans with early-onset dementia (EOD) who had varying histories of blunt- and blast-TBI, cognitive decline, behavioral abnormalities, post-traumatic stress disorder, suicidal ideation, and suicide. We found that pathologic lesions in these military-EOD cases could not be categorized as classic Alzheimer’s disease (AD), chronic traumatic encephalopathy, traumatic axonal injury, or other well-characterized clinicopathologic entities. Rather, we observed a mixture of polypathology with unusual patterns compared with pathologies found in AD or other dementias. Also, ultrahigh resolution ex vivo MRI in 2 of these 4 brains revealed unusual patterns of periventricular WM injury. These findings suggest that military-EOD cases are associated with atypical combinations of brain lesions and distribution rarely seen in nonmilitary populations. Future prospective studies that acquire neuropsychiatric data before and after deployments, as well as genetic and environmental exposure data, are needed to further elucidate clinicopathologic correlations in military-EOD.

Most rapid cognitive decline in APOE ε4 negative Alzheimer's disease with early onset

2009 ◽  
Vol 39 (11) ◽  
pp. 1907-1911 ◽  
Author(s):  
A. E. van der Vlies ◽  
E. L. G. E. Koedam ◽  
Y. A. L. Pijnenburg ◽  
J. W. R. Twisk ◽  
P. Scheltens ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Early Onset ◽  
Late Onset ◽  
Age At Onset ◽  
Apoe Genotype ◽  
Apoe Ε4 ◽  
Rapid Cognitive Decline ◽  
State Examination

BackgroundWe aimed to compare the rate of cognitive decline in patients with early and late onset Alzheimer's disease (AD) and to investigate the potentially modifying influence of the apolipoprotein E (APOE) genotype.MethodWe included 99 patients with early onset AD (age ⩽65 years) and 192 patients with late onset AD (age >65 years) who had at least two scores on the Mini-Mental State Examination (MMSE) (range 2–14) obtained at least 1 year apart. Linear mixed models were performed to investigate the rate of cognitive decline dependent on age at onset (AAO) and APOE genotype.ResultsThe mean (s.d.) age for patients with early onset AD was 57.7 (4.5) years, and 74.5 (5.1) years for patients with late onset AD. AAO was not associated with baseline MMSE [β (s.e.)=0.8 (0.5), p=0.14]. However, patients with early onset showed a faster decline on the MMSE [β (s.e.)=2.4 (0.1) points/year] than those with late onset [β (s.e.)=1.7 (0.1) points/year, p=0.00]. After stratification according to APOE genotype, APOE ε4 non-carriers with early onset showed faster cognitive decline than non-carriers with late onset [2.4 (0.3) v. 1.3 (0.3) points/year, p=0.01]. In APOE ε4 carriers, no difference in rate of cognitive decline was found between patients with early and late onset [β (s.e.)=0.2 (0.2), p=0.47].ConclusionPatients with early onset AD show more rapid cognitive decline than patients with late onset, suggesting that early onset AD follows a more aggressive course. Furthermore, this effect seems to be most prominent in patients with early onset who do not carry the genetic APOE ε4 risk factor for AD.

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