A key question for the scientific study of consciousness is whether it is possible to identify specific features in brain activity that are uniquely linked to conscious experience. This question has important implications for the development of markers to detect covert consciousness in unresponsive patients. In this regard, many studies have focused on investigating the neural response to complex auditory regularities. One noteworthy example is the local global paradigm, which allows for the investigation of auditory regularity encoding at the 'global' level, based on the repetition of groups of sounds. The inference of global regularities is thought to depend on conscious access to such complex auditory stimuli as mostly shown in chronic stages of disorders of consciousness patients. However, whether global regularity encoding can identify covert consciousness along the consciousness spectrum including earlier stages of these disorders remains controversial. Here, we aim to fill this gap by investigating whether the inference of global auditory regularities can occur in acute coma, in the absence of consciousness, and how this may be modulated by the severity of the patients' clinical condition and consciousness level measured using the Full Outline of UnResponsiveness (FOUR) score. We will acquire 63-channel continuous electroencephalography to measure the neural response to global auditory regularity in comatose patients (N = 30) during the first day after cardiac arrest, when patients are unconscious, sedated and under normothermia, and during the second day (with reduced or absent sedation and body temperature control). We hypothesize that global regularity encoding will persist in the absence of consciousness independent of patient outcome, observed as above chance decoding of the neural response to global regularities using multivariate decoding analyses. We further hypothesize that decoding performance will positively correlate with the FOUR score, which indexes consciousness level, and typically improves between the first and second day after coma onset following cardiac arrest in patients with favourable outcome. In an exploratory analysis, we will also evaluate whether global regularity encoding may be influenced by the patients' clinical management, specifically sedation, also shown to affect global deviance detection. Our results will shed light on the neurophysiological correlates of complex auditory regularity processing in unconscious patients and on the link to residual levels of consciousness during the underexplored state of coma upon the first days after cardiac arrest.
The brain-age gap, i.e. the difference between the brain age estimated from structural MRI data and the chronological age of an individual, has been proposed as a summary measure of brain integrity in neurodegenerative diseases. Here, we aimed to determine the brain-age gap in genetic and idiopathic Parkinson's disease and its association with surrogate markers of Alzheimer's disease and Parkinson's disease pathology and with rates of cognitive and motor function decline. We studied 1200 cases from the Parkinson's Progression Markers Initiative cohort, including idiopathic Parkinson's disease, asymptomatic and clinical mutation carriers in the leucine-rich repeat kinase 2 gene (LRRK2) and the glucocerebrosidase gene (GBA), and normal controls using a cohort study design. For comparison, we studied 187 Alzheimer's disease dementia cases and 254 controls from the Alzheimer's Disease Neuroimaging Initiative cohort. We used Bayesian ANOVA to determine associations of the brain-age gap with diagnosis, and baseline measures of motor and cognitive function, dopamine transporter activity and CSF markers of Alzheimer's disease type amyloid-β42 and phosphotau pathology. Associations of brain-age gap with rates of cognitive and motor function decline were determined using Bayesian generalized mixed effect models. The brain-age gap in idiopathic Parkinson's disease patients was 0.7 years compared to controls, but 5.9 years in Alzheimer's disease dementia cases. In contrast, asymptomatic LRRK2 individuals had a 1.1. year younger brain age than controls. Across all cases, the brain-age gap was associated with motor impairment and (in the clinically manifest PD cases) reduced dopamine transporter activity, but less with CSF amyloid-β42 and phosphotau. In idiopathic Parkinson's disease cases, however, the brain-age gap was associated with lower CSF amyloid-β42 levels. In sporadic and genetic Parkinson's disease cases, a higher brain-age gap was associated with faster decline in episodic memory, and executive and motor function, whereas in asymptomatic LRRK2 cases, a smaller brain-age gap was associated with faster cognitive decline. In conclusion, brain age was sensitive to Alzheimer's disease like rather than Parkinson's disease like brain atrophy. Once an individual had idiopathic Parkinson's disease, their brain age was associated with markers of Alzheimer's disease rather than Parkinson's disease. Asymptomatic LRRK2 cases had seemingly younger brains than controls, and in these cases, younger brain age was associated with poorer cognitive outcome. This suggests that the term brain age is misleading when applied to disease stages where reactive brain changes with apparent volume increases rather than atrophy may drive the calculation of the brain age.
This scientific commentary refers to 'The joint memory effect: challenging the selfish stigma in Huntington's disease?', by Dalléry et al. (https://doi.org/10.1093/braincomms/fcae440).
Co-pathology is frequent in Lewy body disease, which includes clinical diagnoses of both Parkinson's disease and dementia with Lewy bodies. Measuring concomitant pathology in vivo can improve clinical and research diagnoses and prediction of cognitive trajectories. Tau PET imaging may serve a dual role in Lewy body disease by measuring cortical tau aggregation as well as assessing dopaminergic loss attributed to binding to neuromelanin within substantia nigra. We sought to characterize 18F-PI-2620, a next generation PET tracer, in individuals with Lewy body disease. We recruited 141 participants for 18F-PI-2620 PET scans from the Stanford Alzheimer's Disease Research Center and the Stanford Aging and Memory Study, most of whom also had β-amyloid status available (139/141) from PET or cerebrospinal fluid. We compared 18F-PI-2620 uptake within entorhinal cortex, inferior temporal cortex, precuneus and lingual gyrus, as well as substantia nigra, across participants with Lewy body disease [Parkinson's disease (n = 29), dementia with Lewy bodies (n = 14)] and Alzheimer's disease (n = 28), in addition to cognitively unimpaired healthy older adults (n = 70). Mean bilateral signal was extracted from cortical regions of interest in 18F-PI-2620 standard uptake value ratio (inferior cerebellar grey reference) images normalized to template space. A subset of participants received cognitive testing and/or the Movement Disorders Society Unified Parkinson's Disease Rating Scale Part III motor exam (off medication). 18F-PI-2620 uptake was low overall in Lewy body disease and correlated with β-amyloid PET in temporal lobe regions and precuneus. Moreover, inferior temporal 18F-PI-2620 uptake was significantly elevated in β-amyloid positive relative to β-amyloid negative participants with Lewy body disease. Temporal lobe 18F-PI-2620 signal was not associated with memory in Lewy body disease, but uptake within precuneus and lingual gyrus was associated with worse executive function and attention/working memory performance. Finally, substantia nigra 18F-PI-2620 signal was significantly reduced in participants with Parkinson's disease, and lower substantia nigra signal was associated with greater motor impairment. These findings suggest that although levels are lower than in Alzheimer's disease, small elevations in cortical tau are associated with cognitive function in Lewy body disease relevant domains, and that reduced 18F-PI-2620 binding in substantia nigra may represent loss of dopaminergic neurons. Cortical tau and neuromelanin binding within substantia nigra represent two unique signals in the same PET image that may be informative in the context of cognitive and motor deficits, respectively, in Lewy body disease.
The preclinical phase of Alzheimer's disease represents a crucial time window for therapeutic intervention but requires the identification of clinically relevant biomarkers that are sensitive to the effects of disease-modifying drugs. Amyloid peptide and tau proteins, the main histological hallmarks of Alzheimer's disease, have been widely used as biomarkers of anti-amyloid and anti-tau drugs. However, these biomarkers do not fully capture the multiple biological pathways of the brain. Indeed, robust amyloid-target engagement by anti-amyloid monoclonal antibodies has recently translated into modest cognitive and clinical benefits in Alzheimer's disease patients, albeit with potentially life-threatening side effects. Moreover, targeting the tau pathway has yet to result in any positive clinical outcomes. Findings from computational neuroscience have demonstrated that brain regions do not work in isolation but are interconnected within complex network structures. Brain connectivity studies suggest that misfolded proteins can spread through these connections, leading to the hypothesis that Alzheimer's disease is a pathology of network disconnectivity. Based on these assumptions, here we discuss how incorporating brain connectivity outcomes could better capture global brain functionality and, in conjunction with traditional Alzheimer's disease biomarkers, could facilitate the clinical development of new disease-modifying anti-Alzheimer's disease drugs.
Hypoxia triggers blood-brain barrier disruption and a strong microglial activation response around leaky cerebral blood vessels. These events are greatly amplified in aged mice which is translationally relevant because aged patients are far more likely to suffer hypoxic events from heart or lung disease, and because of the pathogenic role of blood-brain barrier breakdown in vascular dementia. Importantly, it is currently unclear if disrupted cerebral blood vessels spontaneously repair and if they do, whether surrounding microglia deactivates. In this study, we addressed these questions by exposing aged (20 months old) mice to chronic mild hypoxia (8% O2) for 7 days and then returned them to normoxic conditions for 7 or 14 days, before evaluating blood-brain barrier disruption and microglial activation at the different timepoints. Seven days chronic mild hypoxia triggered marked blood-brain barrier disruption, as measured by extravascular leak of fibrinogen and red blood cells, which led to enhanced microglial activation, as measured by Mac-1 and CD68 levels. Interestingly, while return to normoxia promoted spontaneous repair of damaged blood vessels, the surrounding microglia remained persistently activated and were slow to deactivate. Chronic mild hypoxia also triggered neuronal loss that resulted in irreversible cognitive decline as measured by the novel object recognition test. Taken together, these findings describe an important disconnect between vascular repair and microglial deactivation in aged mice, which likely contributes to prolonged neuroinflammation. As hypoxia occurs in many age-related conditions, our data have important implications for the pathogenic role of hypoxia in the induction and progression of vascular dementia.
Hyperphosphorylated tau accumulation is seen in the noradrenergic locus coeruleus from the earliest stages of Alzheimer's disease onwards and has been associated with symptoms of agitation. It is hypothesized that compensatory locus coeruleus-noradrenaline system overactivity and impaired emotion regulation could underlie agitation propensity, but to our knowledge this has not previously been investigated. A better understanding of the neurobiological underpinnings of agitation would help the development of targeted prevention and treatment strategies. Using a sample of individuals with amnestic mild cognitive impairment and probable mild Alzheimer's disease dementia from the German Center for Neurodegenerative Diseases (DZNE)-Longitudinal Cognitive Impairment and Dementia (DELCODE) study cohort (N = 309, aged 67-96 years, 51% female), we assessed cross-sectional relationships between a latent factor representing the functional integrity of an affect-related executive regulation network and agitation point prevalence and severity scores. In a subsample of individuals with locus coeruleus MRI imaging data (N = 37, aged 68-93 years, 49% female), we also investigated preliminary associations between locus coeruleus MRI contrast ratios (a measure of structural integrity, whole or divided into rostral, middle, and caudal thirds) and individual affect-related regulation network factor scores and agitation measures. Regression models controlled for effects of age and clinical disease severity and, for models including resting-state functional MRI connectivity variables, grey matter volume and education years. Agitation point prevalence showed a positive relationship with a latent factor representing the functional integrity (and a negative relationship with a corresponding structural measure) of the affect-related executive regulation network. Locus coeruleus MRI contrast ratios were positively associated with agitation severity (but only for the rostral third, in N = 13) and negatively associated with the functional affect-related executive regulation latent factor scores. Resting-state functional connectivity between a medial prefrontal cortex region and the left amygdala was related to locus coeruleus MRI contrast ratios. These findings implicate the involvement of locus coeruleus integrity and emotion dysregulation in agitation in Alzheimer's disease and support the presence of potential compensatory processes. At the neural level, there may be a dissociation between mechanisms underlying agitation risk per se and symptom severity. Further studies are needed to replicate and extend these findings, incorporating longitudinal designs, measures of autonomic function and non-linear modelling approaches to explore potential causal and context-dependent relationships across Alzheimer's disease stages.
Dementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive decline and impairs patients' daily life. Affected patients show great heterogeneity in their symptomatic progression, which hampers the identification of efficacious treatments in clinical trials. Using artificial intelligence approaches to enable clinical enrichment trials serves a promising avenue to identify treatments. In this work, we used a deep learning method to cluster the multivariate disease trajectories of 283 early dementia patients along cognitive and functional scores. Two distinct subgroups were identified that separated patients into 'slow' and 'fast' progressing individuals. These subgroups were externally validated and independently replicated in a dementia cohort comprising 2779 patients. We trained a machine learning model to predict the progression subgroup of a patient from cross-sectional data at their time of dementia diagnosis. The classifier achieved a prediction performance of 0.70 ± 0.01 area under the receiver operating characteristic curve in external validation. By emulating a hypothetical clinical trial conducting patient enrichment using the proposed classifier, we estimate its potential to decrease the required sample size. Furthermore, we balance the achieved enrichment of the trial cohort against the accompanied demand for increased patient screening. Our results show that enrichment trials targeting cognitive outcomes offer improved chances of trial success and are more than 13% cheaper compared with conventional clinical trials. The resources saved could be redirected to accelerate drug development and expand the search for remedies for cognitive impairment.
Delirium is a neuropsychiatric syndrome commonly presenting during acute illness. The pathophysiology of delirium is unknown, but neuroinflammation is suggested to play a role. In this cross-sectional study, we aimed to investigate whether cell-free DNA and markers of neutrophil extracellular traps in serum and CSF were associated with delirium and neuronal damage, assessed by neurofilament light chain. Hip fracture patients (n = 491) with a median (25, 75 percentiles) age of 83 (74, 88) years and 69% females were enrolled at Oslo University Hospital, Diakonhjemmet Hospital, Akershus University Hospital and Bærum Hospital. Delirium was assessed daily, pre- and postoperatively. Cognitively healthy adults (n = 32) with a median (25, 75 percentiles) age of 75 (70, 77) years and 53% females were included as controls. Cell-free DNA was measured by using the fluorescent nucleic acid stain Quant-iT PicoGreen® in serum and CSF. Myeloperoxidase-DNA and citrullinated histone H3 were analysed by enzyme-linked immunosorbent assay in serum. Hip fracture patients have significantly higher levels of cell-free DNA and neutrophil extracellular traps in blood than cognitively healthy controls. In hip fracture patients without dementia, cell-free DNA in CSF and serum was significantly higher in patients with (n = 68) versus without (n = 221) delirium after adjusting for age and sex (70 (59, 84) versus 62 (53, 77) ng/ml, P = 0.037) and 601 (504, 684) versus 508 (458, 572) ng/ml, P = 0.007, respectively). In the total hip fracture cohort, CSF levels of cell-free DNA and neurofilament light chain were significantly correlated after adjusting for age and sex (r = 0.441, P < 0.001). The correlation was stronger in those with delirium (r = 0.468, P < 0.001) and strongest in delirious patients without dementia (r = 0.765, P = 0.045). In delirious patients without dementia, significantly higher levels of cell-free DNA in CSF and serum were shown. The association between cell-free DNA and neurofilament light chain suggest simultaneous release of cell-free DNA and neuronal damage during delirium.