Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson's disease.
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ABSTRACT:
SUBMITTER: Cascone AD
PROVIDER: S-EPMC8410800 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCognitive impairment (CI) is one of the most feared and debilitating complications of PD. No therapy has been shown to slow or prevent CI in PD.ObjectiveTo determine associations between modifiable comorbidities, including cardiovascular disease risk factors, mood disorders, and sleep characteristics, and rate of cognitive decline in Parkinson's disease (PD).MethodsData from the Parkinson's Progression Markers Initiative (PPMI) cohort was queried for baseline cardiovascular disease risk factors, mood disorders, and sleep characteristics. Linear mixed- effects models (LME) were used to examine the association between baseline factors and change in cognition, evaluated by the Montreal Cognitive Assessment (MoCA) over time. Baseline comorbidities found to affect MoCA decline were assessed for an association with focal cognitive domains using LME.ResultsHigher Body Mass Index (BMI) (β = -0.009, P = 0.039), State Trait Anxiety Inventory (STAI) (β = -0.005, P < 0.001), Geriatric Depression Scale (GDS) (β = -0.034, P < 0.001), Epworth Sleepiness Scale (ESS) (β = -0.017, P = 0.003), and REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) (β = -0.037, P < 0.001) were associated with faster rates of MoCA decline. Using established cut-offs for clinically significant symptoms, being overweight, or the presence of depression, excessive day time sleepiness (EDS), and possible REM sleep behavior disorder (pRBD), were all associated with faster rate of cognitive decline.ConclusionSeveral modifiable baseline comorbidities are associated with faster rate of CI over time in patients with PD. These associations identify potential opportunities for early intervention that could influence CI in PD.
| S-EPMC7853194 | biostudies-literature
Project description:Background: Cognitive deficits are prominent non-motor symptoms in Parkinson's disease (PD) and have been shown to involve the neurovascular unit (NVU). However, there is a lack of sufficient neuroimaging research on the associated modulating mechanisms. The objective of this study was to identify the contribution of neurovascular decoupling to the pathogenesis of cognitive decline in PD. Methods: Regional homogeneity (ReHo), a measure of neuronal activity, and cerebral blood flow (CBF), a measure of vascular responses, were obtained from patients with PD with mild cognitive impairment (MCI) and normal cognition (NC) as well as matched healthy controls (HCs). Imaging metrics of neurovascular coupling (global and regional CBF-ReHo correlation coefficients and CBF-ReHo ratios) were compared among the groups. Results: Neurovascular coupling was impaired in patients with PD-MCI with a decreased global CBF-ReHo correlation coefficient relative to HC subjects (P < 0.05). Regional dysregulation was specific to the PD-MCI group and localized to the right middle frontal gyrus, right middle cingulate cortex, right middle occipital gyrus, right inferior parietal gyrus, right supramarginal gyrus, and right angular gyrus (P < 0.05). Compared with HC subjects, patients with PD-MCI showed higher CBF-ReHo ratios in the bilateral lingual gyri (LG), bilateral putamen, and left postcentral gyrus and lower CBF-ReHo ratios in the right superior temporal gyrus, bilateral middle temporal gyri, bilateral parahippocampal gyri, and right inferior frontal gyrus. Relative to the HC and PD-NC groups, the PD-MCI group showed an increased CBF-ReHo ratio in the left LG, which was correlated with poor visual-spatial performance (r = -0.36 and P = 0.014). Conclusion: The involvement of neurovascular decoupling in cognitive impairment in PD is regionally specific and most prominent in the visual-spatial cortices, which could potentially provide a complementary understanding of the pathophysiological mechanisms underlying cognitive deficits in PD.
| S-EPMC8636132 | biostudies-literature
Project description:ObjectivesCognitive decline is common in Parkinson's disease (PD), but the underlying mechanisms for this complication are incompletely understood. Genotypes affecting dopamine transmission may be of importance. This study investigates whether genotypes associated with reduced prefrontal dopaminergic tone and/or reduced dopamine D2-receptor availability (Catechol-O-methyltransferase [COMT] Val158 Met genotype and DRD2 C957 T genotype) affect the development of cognitive deficits in PD.Materials and methodsOne hundred and 34 patients with idiopathic PD, participating in a regional, population-based study of incident parkinsonism, underwent genotyping. After extensive baseline investigations (including imaging and biomarker analyses), the patients were followed prospectively during 6-10 years with neuropsychological evaluations, covering six cognitive domains. Cognitive decline (defined as the incidence of either Parkinson's disease mild cognitive impairment [PD-MCI] or dementia [PDD], diagnosed according to published criteria and blinded to genotype) was studied as the primary outcome.ResultsBoth genotypes affected cognition, as shown by Cox proportional hazards models. While the COMT 158 Val/Val genotype conferred an increased risk of mild cognitive impairment in patients with normal cognition at baseline (hazard ratio: 2.13, P = .023), the DRD2 957 T/T genotype conferred an overall increased risk of PD dementia (hazard ratio: 3.22, P < .001). The poorer cognitive performance in DRD2 957 T/T carriers with PD occurred mainly in episodic memory and attention.ConclusionsThe results favor the hypothesis that dopamine deficiency in PD not only relate to mild cognitive deficits in frontostriatal functions, but also to a decline in memory and attention. This could indicate that dopamine deficiency impairs a wide network of brain areas.
| S-EPMC5763317 | biostudies-literature
Project description:Introduction: Functional imaging studies have demonstrated the recruitment of additional neural resources as a possible mechanism to compensate for age and Alzheimer's disease (AD)-related cerebral pathology, the efficacy of which is potentially modulated by underlying structural network connectivity. Additionally, structural network efficiency (SNE) is associated with intelligence across the lifespan, which is a known factor for resilience to cognitive decline. We hypothesized that SNE may be a surrogate of the physiological basis of resilience to cognitive decline in elderly persons without dementia and with age- and AD-related cerebral pathology.Methods: We included 85 cognitively normal elderly subjects or mild cognitive impairment (MCI) patients submitted to baseline diffusion imaging, liquor specimens, amyloid-PET and longitudinal cognitive assessments. SNE was calculated from baseline MRI scans using fiber tractography and graph theory. Mixed linear effects models were estimated to investigate the association of higher resilience to cognitive decline with higher SNE and the modulation of this association by increased cerebral amyloid, liquor tau or WMHV. Results: For the majority of cognitive outcome measures, higher SNE was associated with higher resilience to cognitive decline (p-values: 0.011-0.039). Additionally, subjects with higher SNE showed more resilience to cognitive decline at higher cerebral amyloid burden (p-values: <0.001-0.036) and lower tau levels (p-values: 0.002-0.015).Conclusion: These results suggest that SNE to some extent may quantify the physiological basis of resilience to cognitive decline most effective at the earliest stages of AD, namely at increased amyloid burden and before increased tauopathy.
| S-EPMC7937862 | biostudies-literature
Project description:The role of genetic factors in cognitive decline associated with Parkinson's disease (PD) is unclear. We examined whether variations in apolipoprotein E (APOE), microtubule-associated protein tau (MAPT), or catechol-O-methytransferase (COMT) genotypes are associated with cognitive decline in PD. We performed a prospective cohort study of 212 patients with a clinical diagnosis of PD. The primary outcome was change in Mattis Dementia Rating Scale version 2 score. Linear mixed-effects models and survival analysis were used to test for associations between genotypes and change in cognitive function over time. The ?4 allele of APOE was associated with more rapid decline (loss of 2.9; 95% confidence interval [CI]: 1.7-4.1) of more points per year; P < 0.001) in total score and an increased risk of a ? 10 point drop during the follow-up period (hazard ratio, 2.8; 95% CI: 1.4-5.4; P = 0.003). MAPT haplotype and COMT genotype were associated with measures of memory and attention, respectively, over the entire follow-up period, but not with the overall rate of cognitive decline. These results confirm and extend previously described genetic associations with cognitive decline in PD and imply that individual genes may exert effects on specific cognitive domains or at different disease stages. Carrying at least one APOE ?4 allele is associated with more rapid cognitive decline in PD, supporting the idea of a component of shared etiology between PD dementia and Alzheimer's disease. Clinically, these results suggest that genotyping can provide information about the risk of future cognitive decline for PD patients.
| S-EPMC3323737 | biostudies-literature
Project description:Cognitive decline is common with the progression of Parkinson's disease (PD). Different candidate biomarkers are currently studied for the risk of dementia in PD. Several studies have shown that quantitative EEG (QEEG) is a promising predictor of PD-related cognitive decline. In this paper we briefly outline the basics of QEEG analysis and analyze the recent publications addressing the predictive value of QEEG in the context of cognitive decline in PD. The MEDLINE database was searched for relevant publications from January 01, 2005, to March 02, 2015. Twenty-four studies reported QEEG findings in various cognitive states in PD. Spectral and connectivity markers of QEEG could help to discriminate between PD patients with different level of cognitive decline. QEEG variables correlate with tools for cognitive assessment over time and are associated with significant hazard ratios to predict PD-related dementia. QEEG analysis shows high test-retest reliability and avoids learning effects associated with some neuropsychological testing; it is noninvasive and relatively easy to repeat.
| S-EPMC4842380 | biostudies-literature
Project description:Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
| S-EPMC5474755 | biostudies-literature
Project description:Parkinson's disease is a neurodegenerative disorder requiring motor signs for diagnosis, but showing more widespread pathological alterations from its beginning. Compared to age-matched healthy individuals, patients with Parkinson's disease bear a 6-fold lifetime risk of dementia. For individualized counselling and treatment, prognostic biomarkers for assessing future cognitive deterioration in early stages of Parkinson's disease are needed. In a case-control study, 42 cognitively normal patients with Parkinson's disease were compared with 24 healthy control participants matched for age, sex and education. Tsallis entropy and band power of the δ, θ, α, β and γ-band were evaluated in baseline EEG at eyes-open and eyes-closed condition. As the θ-band showed the most pronounced differences between Parkinson's disease and healthy control groups, further analysis focussed on this band. Tsallis entropy was then compared across groups with 16 psychological test scores at baseline and follow-ups at 6 months and 3 years. In group comparison, patients with Parkinson's disease showed lower Tsallis entropy than healthy control participants. Cognitive deterioration at 3 years was correlated with Tsallis entropy in the eyes-open condition (P < 0.00079), whereas correlation at 6 months was not yet significant. Tsallis entropy measured in the eyes-closed condition did not correlate with cognitive outcome. In conclusion, the lower the EEG entropy levels at baseline in the eyes-open condition, the higher the probability of cognitive decline over 3 years. This makes Tsallis entropy a candidate prognostic biomarker for dementia in Parkinson's disease. The ability of the cortex to execute complex functions underlies cognitive health, whereas cognitive decline might clinically appear when compensatory capacity is exhausted.
| S-EPMC7749793 | biostudies-literature
Project description:Clinical and biochemical diversity of Parkinson's disease (PD) presents a major challenge for accurate diagnosis and prediction of its progression. We propose, develop and optimize PD clinical scores as efficient integrated progression biomarkers for prediction of the likely rate of cognitive decline in PD patients. We considered 269 drug-naïve participants from the Parkinson's Progression Marker Initiative database, diagnosed with idiopathic PD and observed between 4 and 6 years. Nineteen baseline clinical and pathological measures were systematically considered. Relative variable importance and logistic regressions were used to optimize combinations of significant baseline measures as integrated biomarkers. Parkinson's disease cognitive decline scores were designed as new clinical biomarkers using optimally categorized baseline measures. Specificities and sensitivities of the biomarkers reached ~93% for prediction of severe rate of cognitive decline (with more than 5 points decline in 4 years on the Montreal Cognitive Assessment scale), and up to ~73% for mild-to-moderate decline (between 1 and 5 points decline). The developed biomarkers and clinical scores could resolve the long-standing clinical problem about reliable prediction of PD progression into cognitive deterioration. The outcomes also provide insights into the contributions of individual clinical and pathological measures to PD progression, and will assist with better-targeted treatment regiments, stratification of clinical trial and their evaluation.
| S-EPMC6877592 | biostudies-literature
Project description:ObjectiveTo evaluate the association between baseline olfaction and both cross-sectional and longitudinal cognitive assessments, motor symptoms, non-motor symptoms (NMS), and CSF biomarkers in early Parkinson's disease (PD).MethodsParkinson's Progression Marker's Initiative (PPMI) participants underwent baseline olfactory testing with the University of Pennsylvania Smell Identification Test (UPSIT). Serial assessments included measures of motor symptoms, NMS, neuropsychological assessment, and CSF biomarkers. Up to three years follow-up data were included.ResultsAt baseline, worse olfaction (lowest tertile) was associated with more severe NMS, including anxiety and autonomic symptoms. Those in the lowest olfactory tertile were more likely to report cognitive impairment (37.4%) compared to those in the middle (24.4%) and highest olfactory tertiles (14.2%, p < 0.001). Aβ1-42 was significantly lower, and tau/Aβ1-42 ratio was higher in those with worse olfaction. In longitudinal analyses, lower UPSIT score was associated with greater decline in MoCA score (β = 0.02 [0.01, 0.03], p = 0.001) over time, as were composite measures of UPSIT score and either Aβ1-42 or tau/Aβ1-42 ratio. In a Cox proportional hazards model, a composite measure of olfaction and Aβ1-42 was a significant predictor of conversion from normal cognition to mild cognitive impairment (MCI; i.e., MoCA < 26), with subjects most impaired on both measures being 87% more likely to develop incident MCI (HR = 1.87 [1.16, 3.01], p = 0.01).ConclusionsWorse baseline olfaction is associated with long-term cognitive decline. The addition of AD CSF biomarkers to olfactory testing may increase the likelihood of identifying those at highest risk for cognitive decline and progression to MCI.
| S-EPMC4825674 | biostudies-literature