Neuromodulation via Conditional Release of Endocannabinoids in the Spinal Locomotor Network

AbstractEndocannabinoids act as retrograde signals to modulate synaptic transmission. Little is known, however, about their significance in integrated network activity underlying motor behavior. We have examined the physiological effects of endocannabinoids in a neuronal network underlying locomotor behavior using the isolated lamprey spinal cord. Our results show that endocannabinoids are released during locomotor activity and participate in setting the baseline burst rate. They are released in response to mGluR1 activation and act as retrograde messengers. This conditional release of endocannabinoids can transform motoneurons and crossing interneurons into modulatory neurons by enabling them to regulate their inhibitory synaptic inputs and thus contribute to the modulation of the locomotor burst frequency. These results provide evidence that endocannabinoid retrograde signaling occurs within the locomotor network and contributes to motor pattern generation and regulation in the spinal cord

A Caged Ret Kinase Inhibitor and its Effect on Motoneuron Development in Zebrafish Embryos

Proto-oncogene tyrosine-protein kinase receptor RET is implicated in the development and maintenance of neurons of the central and peripheral nervous systems. Attaching activity-compromising photocleavable groups (caging) to inhibitors could allow for external spatiotemporally controlled inhibition using light, potentially providing novel information on how these kinase receptors are involved in cellular processes. Here, caged RET inhibitors were obtained from 3-substituted pyrazolopyrimidine-based compounds by attaching photolabile groups to the exocyclic amino function. The most promising compound displayed excellent inhibitory effect in cell-free, as well as live-cell assays upon decaging. Furthermore, inhibition could be efficiently activated with light in vivo in zebrafish embryos and was shown to effect motoneuron development

Demographically adjusted Rey-Osterrieth Complex Figure Test norms in a Swedish and Norwegian cohort aged 49-77?years and comparison with North American norms

Introduction: The Rey–Osterrieth Complex Figure Test (RCFT) is one of the most commonly used neuropsychological tests in Sweden and Norway. However, no publications provide normative data for this population. The objective of this study was to present demographically adjusted norms for a Swedish and Norwegian population and to evaluate these in an independent comparison group. Methods: The RCFT was administrated to 344 healthy controls recruited from the Swedish Gothenburg MCI study, the Norwegian Dementia Disease Initiation study, and the Swedish Cardiopulmonary Bioimage Study. Age ranged from 49 to 77 years (mean = 62.4 years, SD = 5.0 years), and education ranged from 6 to 24 years (mean = 13.3 years, SD = 3.0 years). Using a regression-based procedure, we investigated the effects of age, sex, and years of education on test performance. We compared and evaluated our Swedish and Norwegian norms with North American norms in an independent comparison group of 145 individuals. Results: In healthy controls, age and education were associated with performance on the RCFT. When comparing normative RCFT performance in an independent comparison group, North American norms generally overestimated immediate and delayed recall performance. In contrast, our Swedish and Norwegian norms appear to better take into account factors of age and education. Conclusions: We presented demographically adjusted norms for the RCFT in a Swedish and Norwegian sample. This is the first normative study of the RCFT that presents normative data for this population. In addition, we showed that North American norms might produce inaccurate normative estimations in an independent comparison group

Demographically adjusted Rey–Osterrieth Complex Figure Test norms in a Swedish and Norwegian cohort aged 49–77 years and comparison with North American norms

Introduction The Rey–Osterrieth Complex Figure Test (RCFT) is one of the most commonly used neuropsychological tests in Sweden and Norway. However, no publications provide normative data for this population. The objective of this study was to present demographically adjusted norms for a Swedish and Norwegian population and to evaluate these in an independent comparison group. Methods The RCFT was administrated to 344 healthy controls recruited from the Swedish Gothenburg MCI study, the Norwegian Dementia Disease Initiation study, and the Swedish Cardiopulmonary Bioimage Study. Age ranged from 49 to 77 years (mean = 62.4 years, SD = 5.0 years), and education ranged from 6 to 24 years (mean = 13.3 years, SD = 3.0 years). Using a regression-based procedure, we investigated the effects of age, sex, and years of education on test performance. We compared and evaluated our Swedish and Norwegian norms with North American norms in an independent comparison group of 145 individuals. Results In healthy controls, age and education were associated with performance on the RCFT. When comparing normative RCFT performance in an independent comparison group, North American norms generally overestimated immediate and delayed recall performance. In contrast, our Swedish and Norwegian norms appear to better take into account factors of age and education. Conclusions We presented demographically adjusted norms for the RCFT in a Swedish and Norwegian sample. This is the first normative study of the RCFT that presents normative data for this population. In addition, we showed that North American norms might produce inaccurate normative estimations in an independent comparison group

Amyloid-β, Tau, and Cognition in Cognitively Normal Older Individuals: Examining the Necessity to Adjust for Biomarker Status in Normative Data

We investigated whether amyloid-β (Aβ) and tau affected cognition in cognitively normal (CN) individuals, and whether norms for neuropsychological tests based on biomarker-negative individuals would improve early detection of dementia. We included 907 CN individuals from 8 European cohorts and from the Alzheimer's disease Neuroimaging Initiative. All individuals were aged above 40, had Aβ status and neuropsychological data available. Linear mixed models were used to assess the associations of Aβ and tau with five neuropsychological tests assessing memory (immediate and delayed recall of Auditory Verbal Learning Test, AVLT), verbal fluency (Verbal Fluency Test, VFT), attention and executive functioning (Trail Making Test, TMT, part A and B). All test except the VFT were associated with Aβ status and this influence was augmented by age. We found no influence of tau on any of the cognitive tests. For the AVLT Immediate and Delayed recall and the TMT part A and B, we calculated norms in individuals without Aβ pathology (Aβ- norms), which we validated in an independent memory-clinic cohort by comparing their predictive accuracy to published norms. For memory tests, the Aβ- norms rightfully identified an additional group of individuals at risk of dementia. For non-memory test we found no difference. We confirmed the relationship between Aβ and cognition in cognitively normal individuals. The Aβ- norms for memory tests in combination with published norms improve prognostic accuracy of dementia

Inflammatory biomarkers in Alzheimer's disease plasma.

INTRODUCTION: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers. METHODS: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. RESULTS: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). DISCUSSION: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology

Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ 4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo

A metabolite-based machine learning approach to diagnose Alzheimer’s-type dementia in blood: Results from the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort

INTRODUCTION: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer’s Disease (AD). Here we set out to test the performance of metabolites in blood to categorise AD when compared to CSF biomarkers. METHODS: This study analysed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n=883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV). RESULTS: On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively. DISCUSSION: This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction:Plasma biomarkers for Alzheimer’s disease (AD) diagnosis/stratification are a“Holy Grail” of AD research and intensively sought; however, there are no well-established plasmamarkers.Methods:A hypothesis-led plasma biomarker search was conducted in the context of internationalmulticenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL;259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.Results:Ten analytes showed significant intergroup differences. Logistic regression identified five(FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD andCTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI(AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Twoanalytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).Discussion:Plasma markers of inflammation and complement dysregulation support diagnosis andoutcome prediction in AD and MCI. Further replication is needed before clinical translatio