Recently, the biased and highly selective 5-HT1A agonists, NLX-112, F13714 and F15599, have been shown to alleviate dyskinesia in rodent and primate models of Parkinson's disease, while marginally interfering with antiparkinsonian effects of levodopa. To provide more detailed information on the processes underlying the alleviation of dyskinesia, we have here investigated changes in the spectral contents of local field potentials in cortico-basal ganglia-thalamic circuits following treatment with this novel group of 5-HT1A agonists or the prototypical agonist, 8-OH-DPAT. Dyskinetic symptoms were consistently associated with 80 Hz oscillations, which were efficaciously suppressed by all 5-HT1A agonists and reappeared upon co-administration of the antagonist, WAY100635. At the same time, the peak-frequency of fast 130 Hz gamma oscillations and their cross-frequency coupling to low-frequency delta oscillations were modified to a different extent by each of the 5-HT1A agonists. These findings suggest that the common antidyskinetic effects of these drugs may be chiefly attributable to a reversal of the brain state characterized by 80 Hz gamma oscillations, whereas the differential effects on fast gamma oscillations may reflect differences in pharmacological properties that might be of potential relevance for non-motor symptoms.
Improved prediction of progression to Alzheimer's Disease (AD) among older individuals with mild cognitive impairment (MCI) is of high clinical and societal importance. We recently developed a polygenic hazard score (PHS) that predicted age of AD onset above and beyond APOE. Here, we used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to further explore the potential clinical utility of PHS for predicting AD development in older adults with MCI. We examined the predictive value of PHS alone and in combination with baseline structural magnetic resonance imaging (MRI) data on performance on the Mini-Mental State Exam (MMSE). In survival analyses, PHS significantly predicted time to progression from MCI to AD over 120 months (p = 1.07e-5), and PHS was significantly more predictive than APOE alone (p = 0.015). Combining PHS with baseline brain atrophy score and/or MMSE score significantly improved prediction compared to models without PHS (three-factor model p = 4.28e-17). Prediction model accuracies, sensitivities and area under the curve were also improved by including PHS in the model, compared to only using atrophy score and MMSE. Further, using linear mixed-effect modeling, PHS improved the prediction of change in the Clinical Dementia Rating—Sum of Boxes (CDR-SB) score and MMSE over 36 months in patients with MCI at baseline, beyond both APOE and baseline levels of brain atrophy. These results illustrate the potential clinical utility of PHS for assessment of risk for AD progression among individuals with MCI both alone, or in conjunction with clinical measures of prodromal disease including measures of cognitive function and regional brain atrophy.