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Glucagon-like peptide-1 receptor agonists for major neurocognitive disorders.
Disease-modifying treatments for major neurocognitive disorders, including Alzheimer's disease, Parkinson's disease and other cognitive deficits, are among the main unmet needs in modern medicine. Glucagon-like peptide-1 receptor agonists (GLP-1RAs), currently licensed for the treatment of type 2 diabetes mellitus and obesity, offer a novel, multilayered mechanism for intervention in neurodegeneration through intermediate, aetiology-agnostic pathways, likely involving metabolic, inflammatory and several other relevant neurobiological processes. In vitro and animal studies have revealed promising signals of neuroprotection, with preliminary supportive evidence emerging from recent pharmacoepidemiological investigations and clinical trials. In this article, we comprehensively review studies that investigate the impact of GLP-1RAs on the various aetiologies of cognitive impairment and dementia syndromes. Focusing on evidence from human studies, we highlight how brain energy homeostasis, neurogenesis, synaptic functioning, neuroinflammation and other cellular stress responses, pathological protein aggregates, proteostasis, cerebrovascular system and blood-brain barrier dynamics may underlie GLP-1RA putative neuroprotective effects. We then report and appraise evidence from clinical studies, including observational investigations, clinical trials and pooled analyses. Finally, we discuss current challenges and perspectives ahead for research and clinical implementation of GLP-1RAs for the care of people with major neurocognitive disorders, including their individual brain penetrance potential, the need for response biomarkers and disease stage-based indications, their possible non-specific effects on brain health, their profile in terms of adverse events and other unwanted effects, the lack of long-term data for efficacy and safety, and issues surrounding cost and availability of treatment.
Cognitive and neuropsychiatric profiles distinguish atypical parkinsonian syndromes.
Atypical parkinsonian syndromes are distinguished from Parkinson's disease by additional neurological signs and characteristic underlying neuropathology. However, they can be diagnostically challenging, rapidly progressive, and are often diagnosed late in disease course. Their different demographic features and prognoses are well studied, but the accompanying cognitive and psychiatric features may also facilitate diagnosis. Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) may cause cognitive and behavioural manifestations that overlap with frontotemporal dementia, including non-fluent aphasia, apathy and impulsivity. Clinical diagnostic criteria have limited sensitivity, with pathologically confirmed PSP often having presented an initial clinical syndrome other than PSP-Richardson's syndrome. Here we integrate cross-sectional multi-centre baseline data from the PROSPECT and Oxford Discovery cohorts. This allowed us to compare cognitive and psychiatric features across a total of 1138 people with PSP, CBS, multiple-system atrophy (MSA), and idiopathic Parkinson's disease (PD). Data from the different cohorts were harmonised and compared using multiple linear regression. There were five key results. 1. Different syndromes showed distinctive cognitive profiles, using readily applicable 'bedside' screening tools. Frontal executive dysfunction was most evident in PSP, visuospatial deficits in CBS, with milder deficits in memory and executive function in MSA, as compared with PD. 2. The most prevalent neuropsychiatric features were depression and anxiety in CBS, apathy in PSP, with sleep disturbances common in PD. As expected, apathy correlated positively with impulsivity across all disorders. Neuropsychiatric features were generally better at discriminating between atypical parkinsonian syndromes than were the cognitive domains. 3. Both cognitive function and motor severity declined with disease duration, and motor function predicted cognition in PSP, CBS and PD but not in MSA, suggesting that in MSA cognitive and motor dysfunction are decoupled. 4. Plasma neurofilament light chain (NFL) levels, measured in a subset of patients, correlated with cognitive deficits in PSP, but not motor deficits. 5. Cognitive deficits contributed to the impairment in activities of daily living after controlling for motor severity, with every two points on the MoCA worsening the Schwab and England score by one point. In anticipation of future neuroprotective therapies, we present a classifier to improve diagnostic accuracy for atypical parkinsonian syndromes in vivo. Longitudinal cohort studies with resources for neuropathological gold-standard diagnosis remain important to validate better diagnostic tools for people with PSP, CBD, MSA and atypical parkinsonism.
High-resolution diffusion imaging in the unfixed post-mortem infant brain at 7 T
Diffusion MRI of the infant brain allows investigation of the organizational structure of maturing fibers during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. Technical development for post-mortem diffusion MRI has primarily focused on scanning of fixed tissue, which is robust to effects like temperature drift that can cause unfixed tissue to degrade. The ability to scan unfixed tissue in the intact body would enable post-mortem studies without organ donation, but poses new technical challenges. This paper describes our approach to scan setup, protocol optimization, and tissue protection in the context of the Developing Human Connectome Project (dHCP) of neonates. A major consideration was the need to preserve the integrity of unfixed tissue during scanning in light of energy deposition at ultra-high magnetic field strength. We present results from one of the first two subjects recruited to the study, who died on postnatal day 46 at 29+6 weeks postmenstrual age, demonstrating high-quality diffusion MRI data. We find altered diffusion properties consistent with post-mortem changes reported previously. Preliminary voxel-wise and tractography analyses are presented with comparison to age-matched in vivo dHCP data. These results show that high-quality, high-resolution post-mortem data of unfixed tissue can be acquired to explore the developing human brain.
Angiotensin receptor blockade modulates resting state functional connectivity in the memory network rather than fear network - implications for posttraumatic stress disorder.
Population-based studies have shown that the intake of Angiotensin-II receptor blockers (ARBs), commonly used to treat high blood pressure, is associated with reduced post-traumatic stress disorder (PTSD) symptoms. However, the underlying neural mechanisms remain unclear. While PTSD development is characterized by maladaptive processing within brain networks associated with fear processing and memory formation during trauma exposure, there is increasing evidence that such aberrations manifest in altered resting state functional connectivity (rsFC) of brain regions in these networks. In this double-blind placebo-controlled study in 45 healthy volunteers with high trait-anxiety, we investigated whether the ARB losartan would affect rsFC in prominent seeds of the fear and memory network, counteracting effects seen in PTSD. Seed selection was informed by established rsFC aberrations seen in PTSD and consisted of the hippocampus and the parahippocampal gyrus (memory network), as well the amygdala and insula (fear network). Our results showed that a single dose of the ARB losartan decreased rsFC in the memory network from modulatory structures in the frontal cortex: losartan decreased rsFC (i) between the hippocampus and the inferior frontal gyrus involved in threat processing and memory intrusion development, and (ii) between the parahippocampal gyrus and the dorsolateral prefrontal cortex involved in top-down control. There were no drug effects on the fear network seeds. These findings may imply that ARB preserves adaptive memory function during trauma.
Confidence and Insight into Working Memories Are Shaped by Attention and Recent Performance.
Working memory is capacity limited, and our ability to access information from working memory is variable, but selective attention to working memory contents can improve performance. People are able to make introspective judgments regarding the quality of their memories, and these judgments are linked to objective memory performance. However, it remains unknown whether benefits of internally directed attention on memory performance occur alongside commensurate changes in introspective judgments. Across two experiments, we used retrospective cues (retrocues) during working-memory maintenance to direct attention to items in memory. We then examined their consequence on introspective judgments. In the second experiment, we provided trial-wise feedback on performance. We found that selective attention improved confidence judgments and not just performance of the probed item. We were also able to judge participants' genuine insight into working-memory contents through the correlation between confidence judgments and memory quality. Neurophysiologically, alpha desynchronization correlated first with memory error and then confidence during retrocueing, suggesting a sequential process of attentional enhancement of memory contents and introspective insight. Furthermore, we showed that participants can use feedback on the accuracy of confidence judgments to update their beliefs across time, according to performance. Our results emphasize flexibility in working memory by showing we can selectively modulate our confidence about its contents based on internally directed attention or objective feedback.
Human gaze tracks attentional focusing in memorized visual space.
Brain areas that control gaze are also recruited for covert shifts of spatial attention1-9. In the external space of perception, there is a natural ecological link between the control of gaze and spatial attention, as information sampled at covertly attended locations can inform where to look next2,10,11. Attention can also be directed internally to representations held within the spatial layout of visual working memory12-16. In such cases, the incentive for using attention to direct gaze disappears, as there are no external targets to scan. Here we investigate whether the oculomotor system of the brain also participates in attention focusing within the internal space of memory. Paradoxically, we reveal this participation through gaze behaviour itself. We demonstrate that selecting an item from visual working memory biases gaze in the direction of the memorized location of that item, despite there being nothing to look at and location memory never explicitly being probed. This retrospective 'gaze bias' occurs only when an item is not already in the internal focus of attention, and it predicts the performance benefit associated with the focusing of internal attention. We conclude that the oculomotor system also participates in focusing attention within memorized space, leaving traces all the way to the eyes.
Concurrent visual and motor selection during visual working memory guided action.
Visual working memory enables us to hold onto past sensations in anticipation that these may become relevant for guiding future actions. Yet laboratory tasks have treated visual working memories in isolation from their prospective actions and have focused on the mechanisms of memory retention rather than utilization. To understand how visual memories become used for action, we linked individual memory items to particular actions and independently tracked the neural dynamics of visual and motor selection when memories became used for action. This revealed concurrent visual-motor selection, engaging appropriate visual and motor brain areas at the same time. Thus we show that items in visual working memory can invoke multiple, item-specific, action plans that can be accessed together with the visual representations that guide them, affording fast and precise memory-guided behavior.
Association between physical exercise and mental health in 1·2 million individuals in the USA between 2011 and 2015: a cross-sectional study.
BACKGROUND: Exercise is known to be associated with reduced risk of all-cause mortality, cardiovascular disease, stroke, and diabetes, but its association with mental health remains unclear. We aimed to examine the association between exercise and mental health burden in a large sample, and to better understand the influence of exercise type, frequency, duration, and intensity. METHODS: In this cross-sectional study, we analysed data from 1 237 194 people aged 18 years or older in the USA from the 2011, 2013, and 2015 Centers for Disease Control and Prevention Behavioral Risk Factors Surveillance System survey. We compared the number of days of bad self-reported mental health between individuals who exercised and those who did not, using an exact non-parametric matching procedure to balance the two groups in terms of age, race, gender, marital status, income, education level, body-mass index category, self-reported physical health, and previous diagnosis of depression. We examined the effects of exercise type, duration, frequency, and intensity using regression methods adjusted for potential confounders, and did multiple sensitivity analyses. FINDINGS: Individuals who exercised had 1·49 (43·2%) fewer days of poor mental health in the past month than individuals who did not exercise but were otherwise matched for several physical and sociodemographic characteristics (W=7·42 × 1010, p<2·2 × 10-16). All exercise types were associated with a lower mental health burden (minimum reduction of 11·8% and maximum reduction of 22·3%) than not exercising (p<2·2 × 10-16 for all exercise types). The largest associations were seen for popular team sports (22·3% lower), cycling (21·6% lower), and aerobic and gym activities (20·1% lower), as well as durations of 45 min and frequencies of three to five times per week. INTERPRETATION: In a large US sample, physical exercise was significantly and meaningfully associated with self-reported mental health burden in the past month. More exercise was not always better. Differences as a function of exercise were large relative to other demographic variables such as education and income. Specific types, durations, and frequencies of exercise might be more effective clinical targets than others for reducing mental health burden, and merit interventional study. FUNDING: Cloud computing resources were provided by Microsoft.
Biophysical effects and neuromodulatory dose of transcranial ultrasonic stimulation.
Transcranial ultrasonic stimulation (TUS) has the potential to usher in a new era for human neuroscience by allowing spatially precise and high-resolution non-invasive targeting of both deep and superficial brain regions. Currently, fundamental research on the mechanisms of interaction between ultrasound and neural tissues is progressing in parallel with application-focused research. However, a major hurdle in the wider use of TUS is the selection of optimal parameters to enable safe and effective neuromodulation in humans. In this paper, we will discuss the major factors that determine both the safety and efficacy of TUS. We will discuss the thermal and mechanical biophysical effects of ultrasound, which underlie its biological effects, in the context of their relationships with tunable parameters. Based on this knowledge of biophysical effects, and drawing on concepts from radiotherapy, we propose a framework for conceptualising TUS dose.
Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI.
Given the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is an important task in neuroimaging. Manual segmentation, though considered the gold standard, is time-consuming and error-prone, leading to the development of numerous automatic segmentation methods. However, no study has yet independently compared the performance of traditional, deep learning-based and hippocampal subfield segmentation methods within a single investigation. We evaluated 10 automatic hippocampal segmentation methods (FreeSurfer, SynthSeg, FastSurfer, FIRST, e2dhipseg, Hippmapper, Hippodeep, FreeSurfer-Subfields, HippUnfold and HSF) across 3 datasets with manually segmented hippocampus labels. Performance metrics included overlap with manual labels, correlations between manual and automatic volumes, volume similarity, diagnostic group differentiation and systematically located false positives and negatives. Most methods, especially deep learning-based ones that were trained on manual labels, performed well on public datasets but showed more error and variability on clinical data. Many methods tended to over-segment, particularly at the anterior hippocampus border, but were able to distinguish between healthy controls, MCI, and dementia patients based on hippocampal volume. Our findings highlight the challenges in hippocampal segmentation from MRI and the need for more publicly accessible datasets with manual labels across diverse ages and pathological conditions.