scholarly journals Cerebrospinal fluid biomarkers in Parkinson’s disease with freezing of gait: an exploratory analysis

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
J. M. Hatcher-Martin ◽  
J. L. McKay ◽  
A. F. Pybus ◽  
B. Sommerfeld ◽  
J. C. Howell ◽  
...  

AbstractWe explore the association between three Alzheimer’s disease-related and ten inflammation-related CSF markers and freezing of gait (FOG) in patients with Parkinson’s disease (PD). The study population includes PD patients with FOG (PD-FOG, N = 12), without FOG (PD-NoFOG, N = 19), and healthy controls (HC, N = 12). Age and PD duration are not significantly different between groups. After adjusting for covariates and multiple comparisons, the anti-inflammatory marker, fractalkine, is significantly decreased in the PD groups compared to HC (P = 0.002), and further decreased in PD-FOG compared to PD-NoFOG (P = 0.007). The Alzheimer’s disease-related protein, Aβ42, is increased in PD-FOG compared to PD-NoFOG and HC (P = 0.001). Group differences obtained in individual biomarker analyses are confirmed with multivariate discriminant partial least squares regression (P < 0.001). High levels of Aβ42 in PD-FOG patients supports an increase over time from early to advanced state. Low levels of fractalkine might suggest anti-inflammatory effect. These findings warrant replication.

2020 ◽  
Author(s):  
J. M. Hatcher-Martin ◽  
J.L. McKay ◽  
B. Sommerfeld ◽  
J.C. Howell ◽  
F. C. Goldstein ◽  
...  

AbstractObjectiveTo evaluate the association of Alzheimer’s disease-related and inflammation-related cerebrospinal fluid (CSF) markers with freezing of gait (FOG) in patients with Parkinson’s disease (PD).MethodThe study population included well-characterized PD patients with FOG (PD-FOG), without FOG (PD-NoFOG) and healthy controls (HC). CSF was collected using standard protocols. Three Alzheimer’s disease-related markers and 10 inflammation-related markers were measured in a Luminex 200 platform. Differences in marker expression across groups were evaluated with multivariate linear models.ResultsCSF was collected from PD-FOG (N=12), PD-NoFOG (N=20) and HC (N=11) for analysis. Age was not significantly different between the three groups. Duration of PD was not significantly different between the two PD groups. After adjusting for covariates and multiple comparisons, the anti-inflammatory marker, fractalkine, was significantly decreased in the PD groups compared to HC (P=0.022), and further decreased in PD-FOG compared to PD-NoFOG or HC (P=0.032). The Alzheimer’s disease-related protein, Aβ42, was increased in PD-FOG compared to PD-NoFOG or HC (P=0.004). p-Tau181 was also decreased in both PD groups compared to HC (P=0.010).ConclusionsWe found high levels of Aβ42 in PD-FOG patients and cross-sectional data which supports an increase over time from early to advanced state. We also found low levels of fractalkine which might suggest anti-inflammatory effect. This is the first time an association between fractalkine and FOG has been shown. Whether these changes are specific to FOG requires further exploration.


2010 ◽  
Vol 3 (6) ◽  
pp. 1812-1841 ◽  
Author(s):  
Amy H. Moore ◽  
Matthew J. Bigbee ◽  
Grace E. Boynton ◽  
Colin M. Wakeham ◽  
Hilary M. Rosenheim ◽  
...  

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 6088
Author(s):  
Xinqian He ◽  
Fan Yang ◽  
Xin’an Huang

Biflavonoids, composed of two monoflavonoid residues, occur naturally in angiosperms, bryophytes, ferns, and gymnosperms. More than 592 biflavonoids have been structurally elucidated, and they can be classified into two groups of C-C and C-linear fragments-C, based on whether the linker between the two residues contains an atom. As the linker can be established on two arbitrary rings from different residues, the C-C type contains various subtypes, as does the C-linear fragment-C type. Biflavonoids have a wide range of pharmacological activities, including anti-inflammatory, antioxidant, antibacterial, antiviral, antidiabetic, antitumor, and cytotoxic properties, and they can be applied in Alzheimer’s disease and Parkinson’s disease. This review mainly summarizes the distribution and chemistry of biflavonoids; additionally, their bioactivities, pharmacokinetics, and synthesis are discussed.


2013 ◽  
Vol 8 ◽  
pp. BMI.S11422 ◽  
Author(s):  
Chera L. Maarouf ◽  
Thomas G. Beach ◽  
Charles H. Adler ◽  
Michael Malek-Ahmadi ◽  
Tyler A. Kokjohn ◽  
...  

Identifying biomarkers that distinguish Parkinson's disease (PD) from normal control (NC) individuals has the potential to increase diagnostic sensitivity for the detection of early-stage PD. A previous proteomic study identified potential biomarkers in postmortem ventricular cerebrospinal fluid (V-CSF) from neuropathologically diagnosed PD subjects lacking Alzheimer's disease (AD) neuropathology. In the present study, we assessed these biomarkers as well as p-tau181, Aβ42, and S100B by ELISA in PD (n = 43) and NC (n = 49) cases. The p-tau181/Aβ42 ratio and ApoA-1 showed statistically significant differences between groups. Multiple regression analysis demonstrated that p-tau181/Aβ42 had a significant odds ratio: OR = 1.42 (95% confidence interval [CI], 1.12–1.84), P = 0.006. Among the molecules investigated, intriguing correlations were observed that require further investigation. Our results suggest coexistent AD CSF biomarkers within the PD group notwithstanding that it was selected to minimize AD neuropathological lesions.


2020 ◽  
Vol 88 (3) ◽  
pp. 574-587 ◽  
Author(s):  
David J. Irwin ◽  
Janel Fedler ◽  
Christopher S. Coffey ◽  
Chelsea Caspell‐Garcia ◽  
Ju Hee Kang ◽  
...  

2020 ◽  
Vol 18 (10) ◽  
pp. 758-768 ◽  
Author(s):  
Khadga Raj ◽  
Pooja Chawla ◽  
Shamsher Singh

: Tramadol is a synthetic analog of codeine used to treat pain of moderate to severe intensity and is reported to have neurotoxic potential. At therapeutic dose, tramadol does not cause major side effects in comparison to other opioid analgesics, and is useful for the management of neurological problems like anxiety and depression. Long term utilization of tramadol is associated with various neurological disorders like seizures, serotonin syndrome, Alzheimer’s disease and Parkinson’s disease. Tramadol produces seizures through inhibition of nitric oxide, serotonin reuptake and inhibitory effects on GABA receptors. Extensive tramadol intake alters redox balance through elevating lipid peroxidation and free radical leading to neurotoxicity and produces neurobehavioral deficits. During Alzheimer’s disease progression, low level of intracellular signalling molecules like cGMP, cAMP, PKC and PKA affect both learning and memory. Pharmacologically tramadol produces actions similar to Selective Serotonin Reuptake Inhibitors (SSRIs), increasing the concentration of serotonin, which causes serotonin syndrome. In addition, tramadol also inhibits GABAA receptors in the CNS has been evidenced to interfere with dopamine synthesis and release, responsible for motor symptoms. The reduced level of dopamine may produce bradykinesia and tremors which are chief motor abnormalities in Parkinson’s Disease (PD).


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.


2021 ◽  
pp. 155005942199714
Author(s):  
Lucia Zinno ◽  
Anna Negrotti ◽  
Chiara Falzoi ◽  
Giovanni Messa ◽  
Matteo Goldoni ◽  
...  

Introduction. An easily accessible and inexpensive neurophysiological technique such as conventional electroencephalography may provide an accurate and generally applicable biomarker capable of differentiating dementia with Lewy bodies (DLB) from Alzheimer’s disease (AD) and Parkinson’s disease-associated dementia (PDD). Method. We carried out a retrospective visual analysis of resting-state electroencephalography (EEG) recording of 22 patients with a clinical diagnosis of 19 probable and 3 possible DLB, 22 patients with probable AD and 21 with PDD, matched for age, duration, and severity of cognitive impairment. Results. By using the grand total EEG scoring method, the total score and generalized rhythmic delta activity frontally predominant (GRDAfp) alone or, even better, coupled with a slowing of frequency of background activity (FBA) and its reduced reactivity differentiated DLB from AD at an individual level with an high accuracy similar to that obtained with quantitative EEG (qEEG). GRDAfp alone could also differentiate DLB from PDD with a similar level of diagnostic accuracy. AD differed from PDD only for a slowing of FBA. The duration and severity of cognitive impairment did not differ between DLB patients with and without GRDAfp, indicating that this abnormal EEG pattern should not be regarded as a disease progression marker. Conclusions. The findings of this investigation revalorize the role of conventional EEG in the diagnostic workup of degenerative dementias suggesting the potential inclusion of GRDAfp alone or better coupled with the slowing of FBA and its reduced reactivity, in the list of supportive diagnostic biomarkers of DLB.


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