Abstract Repurposed noradrenergic drugs have been proposed to treat neuropsychiatric symptoms in Parkinson’s disease and related conditions. While there is evidence that these drugs can be beneficial for cognition in selected patients, questions remain about their cardiovascular effects. Here we tested whether heart rate variability (HRV) is altered in people with Parkinson’s disease, following a single-dose challenge with the noradrenaline reuptake inhibitor atomoxetine (40 mg, oral). Consistent with previous work, our cohort of people with idiopathic Parkinson’s disease (n=15) had lower HRV than healthy controls (n=22). Select markers of decreased HRV in people with Parkinson’s disease were associated with reduced integrity of the caudal locus coeruleus, measured using neuromelanin-sensitive ultra-high field 7T magnetic resonance imaging. Following a randomised double-blind placebo-controlled crossover challenge in the Parkinson’s disease group, short term resting HRV was not significantly altered following atomoxetine. Using Bayesian statistical inference, we demonstrated confidence in the preservation of HRV across measures in the time, frequency, and non-linear domains. Our findings are in favour of a safe cardiovascular profile for atomoxetine in Parkinson’s disease, further supporting noradrenergic modulation as a viable treatment strategy for neuropsychiatric symptoms in Parkinson’s disease and related disorders.
With the evolution of ultra-low-field MRI and the recognition of antenatal maternal anaemia as an important driver of altered neurodevelopment in toddlers and children, it is critical to determine whether these effects are detectable at ultra-low-field (64 mT) in infancy. The aim of this study was to assess the impact of antenatal maternal anaemia on infant brain structure across the first 2 years of life, using high-field (3 T) and ultra-low-field (64 mT) MRI. This neuroimaging substudy was embedded within Khula, an observational population-based birth cohort in South Africa. Pregnant women were enrolled antenatally and postnatally. Mother-child dyads (n = 394) were followed prospectively with a subsample attending neuroimaging at ∼3, 6, 12, 18 and 24 months of age. Anaemia was classified using World Health Organization thresholds, and neuroimaging data were processed using MiniMORPH. Linear mixed-effects models were used to investigate associations between antenatal maternal anaemia status and absolute regional infant brain volumes using high-field and ultra-low-field MRI. In repeated measures high-field (n = 195) and ultra-low-field (n = 341) infant neuroimaging subsamples, the prevalence of antenatal maternal anaemia was 28.24% (37/131) and 29.76% (61/205), respectively. Maternal anaemia in pregnancy was associated with altered child brain structure across both MRI systems, with group differences becoming detectable at ∼12 months. In the ultra-low-field subsample, infants born to anaemic mothers had 3.77% smaller intracranial volume (β = -0.24, P = 0.004) and 3.32% smaller putamen volumes (β = -0.18, P = 0.040) across the first 2 years of life. The interaction between antenatal maternal anaemia and age was significant for the caudate nucleus (β = -0.13, P = 0.038) and corpus callosum (β = -0.15, P = 0.007). Antenatal maternal anaemia was associated with 3.70% and 4.29% smaller caudate nucleus volumes at 18 and 24 months of age, respectively. Similarly, infants born to anaemic mothers had 4.39% smaller corpus callosum volumes by 12 months and 6.27% smaller corpus callosum volumes by 24 months. Postnatal child anaemia and antenatal maternal iron deficiency status were not associated with total or regional child brain volumes in the ultra-low-field subsample from this cohort. Maternal anaemia remained a robust predictor of volume differences in sensitivity analyses. This study is the first to demonstrate that the impact of maternal anaemia in pregnancy on child brain structure is detectable as early as infancy. The implications of this research are 2-fold: (i) informing the feasibility of ultra-low-field MRI in low- and middle-income countries and (ii) the timing and optimization of targeted recommendations for anaemia management in practice and policy.
Epilepsy patients suffer from spontaneous and recurrent seizures. In some cases, after seizures, a transient post-ictal state associated with cognitive deficits develops. Moreover, seizure-induced alterations in brain structure and function may give rise to neurological comorbidities associated with epilepsy. Nevertheless, the mechanisms underlying neurological comorbidities in epilepsy broadly and the post-ictal state specifically are not well understood. Here we used a well-established model of acutely induced seizures in larval zebrafish to reveal how seizures modulate a neural circuit implementing a specific sensorimotor transformation, the escape response. Using in vivo calcium imaging, we found that the responsivity of Mauthner cells, hindbrain command-like neurons that normally evoke fast and strong escape responses, to startling stimuli was reduced following seizures. Moreover, we observed a global reduction in post-seizure responsivity of neurons to the stimuli and in spontaneous neural activity. To identify structural correlates of these changes, we used expansion microscopy to characterize synaptic inputs to the Mauthner cells. Using this approach, we discovered that seizures increased the density of receptors in glycinergic inhibitory synapses onto these cells, expected to increase synaptic strength. This enhancement may compensate for the lack of GABAergic inhibition during the seizure. In addition, inducing the disassembly of glycinergic synapses by post-seizure strychnine treatment, reversed the effect of reduced neural responsivity. Put together, these data show that, at both the synaptic and circuit levels, inhibitory drive is strengthened after seizure termination, giving rise to a post-ictal state similar to that defined in humans. Consequently, sensory sensitivity is reduced, and post-seizure behavioural deficits are expected. These results reveal a potential target for pharmacological interventions that may mitigate neurological deficits in epilepsy when the seizures themselves cannot be prevented.
The dynamic modulation of large-scale network activity, which is inherent to cognitive processes, is disrupted in Parkinson's disease. Subthalamic deep brain stimulation can either improve or deteriorate cognition, particularly executive function, with these effects often going unnoticed during acute parameter optimization. This highlights the need for longer stimulation periods and more focused research on the underlying cortical mechanisms, which remain underexplored. This study was a prospective clinical trial involving nineteen people with Parkinson's disease, who were evaluated off their medication at preoperative baseline and 6 months after deep brain stimulation implantation. Brain activity related to verbal and visuospatial working memory tasks was recorded using electroencephalography at both baseline and during follow-up evaluations conducted under stimulation. The follow-up assessments were carried out following 3-week periods of either omnidirectional or directional stimulation, applied in a randomized, double-blind, crossover design. Average postoperative working memory performance remained stable at the group level regardless of the stimulation condition for both verbal and visuospatial working memory tasks. However, at the individual level, higher alpha and beta power at baseline was associated with slower visuospatial working memory reaction time at follow-up. Additionally, reductions in theta and beta power during stimulation at follow-up correlated with better verbal working memory accuracy during the task and compared with baseline, respectively. These findings suggest that task-related electroencephalography may provide candidate physiological markers of individual working memory trajectories after subthalamic deep brain stimulation. Oscillatory brain activity may help to characterize stimulation-related cognitive variability beyond motor outcomes, but these exploratory findings require validation in larger cohorts before they can inform stimulation programming or closed-loop treatment strategies. Registration: ClinicalTrials.gov: NCT03548506.
Adrenoleukodystrophy (ALD) is an X-linked recessive disease caused by defects in the ABCD1 gene, leading to the accumulation of very long-chain fatty acids in the nervous system, adrenal glands, blood and other tissues. Male ALD patients may present with either the severe neurological phenotype of cerebral ALD, characterized by inflammatory demyelination in the white matter and rapid neurological deterioration, or milder forms, such as adrenomyeloneuropathy. We aimed to identify early brain changes in asymptomatic ALD patients prior to the clinical onset of cerebral ALD or adrenomyeloneuropathy by exploratory analysis of multimodal MRI data. Multimodal MRI data-including structural images, diffusion tensor imaging, magnetization transfer imaging and MR spectroscopy-were obtained from asymptomatic ALD patients during regular follow-up MRIs. Longitudinal MRI data were analysed from 12 asymptomatic ALD patients aged 10-18 years who did not develop a cerebral ALD phenotype during our surveillance and from 12 healthy age-matched male controls. Volumetric analyses of brain structures were performed using structural MRI data, as well as region-of-interest measurements on diffusion tensor imaging, magnetization transfer imaging and MR spectroscopy data. Statistical analysis was performed using linear mixed-effects models. Volumetry indicated increased white matter volume in asymptomatic ALD patients. Diffusion tensor imaging analysis revealed increased values of radial and mean diffusivity in the supratentorial white matter. Magnetization transfer saturation values derived from magnetization transfer imaging metrics were increased in the cortical and subcortical grey matter, but not in the white matter. MR spectroscopy showed increased inositol levels in the frontal white matter. Our diffusion tensor imaging and MR spectroscopy data indicate early white matter pathology in adolescent asymptomatic ALD patients. Among these findings, increased white matter volume and, in addition, elevated magnetization transfer saturation values in the grey matter are novel MRI phenotypes associated with asymptomatic ALD. These results suggest that not only white matter but also grey matter can be pathologically altered even before the onset of neurological phenotypes. Multimodal MRI parameters therefore constitute promising biomarkers for the assessment of pre-symptomatic brain tissue alterations in ALD and may be useful in future clinical studies targeting early therapeutic intervention.
Cognitive impairment is among the most common non-motor symptoms in parkinsonism and Parkinson's disease, ranging from subjective complaints to dementia. Although several predictive factors have been described, their prognostic relevance remains uncertain. This study aimed to examine the predictive association between clinical features and the risk of dementia and determine the incidence of dementia in a population-based cohort of incident Parkinsonism cases. Patients with parkinsonism onset between 1991 and 2020 were identified using the Rochester Epidemiology Project records-linkage system. Subjects with cognitive impairment preceding motor symptoms onset or concomitant Alzheimer's disease were excluded. Diagnoses of dementia and mild cognitive impairment were established using neuropsychological testing or brief cognitive screening. Development of dementia was assessed using a Cox proportional hazards regression model. Associations between dementia and each risk factor were individually estimated in adjusted Cox models. All risk factors were also included in a least absolute shrinkage and selection operator penalized multivariable Cox model. A total of 1104 patients were included: 153 (13.9%) developed mild cognitive impairment, and 543 (49.2%) developed dementia during follow-up. The cumulative incidence of dementia was 30.3% at 5 years, 48.6% at 10 years, 61.4% at 15 years and 69.3% at 20 years, indicating that a considerable portion of patients remained free of dementia after a prolonged follow-up. The majority of patients with dementia were males (61.5%), and older age at disease onset was associated with risk of dementia (hazard ratio [HR] = 1.32, P < 0.001 per 5-year increment). In the penalized model, dementia risk was significantly higher among individuals presenting with impaired postural reflexes (HR = 1.26, P = 0.014), consistent with a poorer prognosis in akinetic-rigid-predominant parkinsonism. Eye movement abnormalities, including reduced ocular range of motion (HR = 1.86, P < 0.001) and smooth pursuit alterations (HR = 1.34, P = 0.024), were also associated with dementia. Non-motor symptoms, including rapid eye movement sleep behaviour disorder (HR = 1.51, P < 0.001), orthostatic hypotension (HR = 1.30, P = 0.009) and constipation (HR = 1.24, P = 0.022), were linked to dementia risk, supporting a potential involvement of non-dopaminergic and central autonomic pathways in cognitive decline. These findings were largely confirmed in the Parkinson's disease/Parkinson's disease with dementia group, in which 77 (13.5%) developed mild cognitive impairment and 249 (43.5%) developed dementia. Among these patients, smooth pursuit alterations, reduced ocular range of motion, orthostatic hypotension and constipation were associated with dementia.
Identification of gene expression changes in postmortem brain tissue of Alzheimer's disease donors compared to controls has implicated numerous biological pathways for Alzheimer's disease pathophysiology. Nonetheless, there is still limited understanding of how gene expression dysregulation underpins specific proteinopathies core to Alzheimer's disease. Here, we investigate brain transcriptomic changes in a well-characterized cohort of Alzheimer's disease donors to identify genes and networks that associate with Alzheimer's disease endophenotypes, including neuropathology measures (Braak stage, Thal phase and cerebral amyloid angiopathy score) and Alzheimer's disease-related brain protein levels (Apolipoprotein E, Amyloid-β 40, Amyloid-β 42, tau and phospho-Tau). Bulk transcriptome measures were collected from the temporal cortex tissue of 477 Alzheimer's disease donors. Following quality control, transcriptome-wide association studies were performed for each endophenotype. We used weighted gene co-expression network analysis to build co-expression networks and integrated transcriptome with epigenetic and genetic data from the same donors. We detected a total of 5740 Bonferroni-significant temporal cortex gene associations with Alzheimer's disease endophenotypes, most of which were with brain tau levels. We discovered tau-associated co-expression modules enriched in known and novel Alzheimer's disease pathways. We found that a beneficial (or neutral) brain biochemical state of higher total tau and lower phospho-Tau is associated with increased levels of synaptic, DNA damage/repair, nucleic acid metabolism and myelin processes. In contrast, in a detrimental state with lower total and higher phospho-Tau, there is upregulation of vascular and immune, and downregulation of mitochondrial and myelin pathways. There are brain gene expression perturbations that are associated with Alzheimer's disease endophenotypes. While some of these associations are common across multiple endophenotypes, many are distinct for different Alzheimer's disease-related proteins. Based on these findings, we propose a hypothetical model of dynamic brain gene expression changes that track with progressive Alzheimer's disease proteostasis. These expression changes hold potential to serve as dynamic, precision biomarkers of brain Alzheimer's disease progression. This study demonstrates the potential of integrative multi-omics and deep Alzheimer's disease endophenotypes in well-characterized brain tissues to precisely uncover the complex biology of Alzheimer's disease.
Abstract Efficient axonal transport is essential for maintaining neuronal function, enabling the bidirectional delivery of diverse cargoes between the cell body and distal compartments. In the neuromuscular system, neurotrophic factors regulate motor neuron survival, function, and synaptic connectivity, in part, through retrograde trafficking of activated neurotrophic factor-receptor complexes from the neuromuscular junction to the cell body. We recently demonstrated that brain-derived neurotrophic factor stimulation to muscles selectively enhances retrograde transport of signalling endosomes in fast, but not slow, motor neurons in vivo. Moreover, both axonal endosome transport and its brain-derived neurotrophic factor-mediated regulation are disrupted in mouse models of diseases impacting motor neurons, including amyotrophic lateral sclerosis and Charcot-Marie-Tooth disease. Here, we examined whether additional neurotrophic factors, when applied to distal axon terminals, share this transport-modulating property. Through imaging sciatic nerves in anaesthetised mice, we tracked the in vivo dynamics of signalling endosomes in fast and slow motor neurons via intramuscular injections of a fluorescent atoxic fragment of tetanus neurotoxin. These injections were co-administered with ciliary neurotrophic factor, hepatocyte growth factor, neurturin, or cleavage-resistant pro-brain-derived neurotrophic factor – four growth factors with known effects on motor neurons. Compared to vehicle-treated controls, pro-brain-derived neurotrophic factor, hepatocyte growth factor, and neurturin produced no detectable change in transport dynamics. In contrast, ciliary neurotrophic factor markedly reduced endosome speeds in both fast and slow motor neurons, indicating remarkable selectivity of specific neurotrophic factors in the regulation of signalling endosome transport in motor neurons. Understanding this selectivity may aid the development of muscle-targeted neurotrophic factor-based therapeutic strategies aimed at restoring axonal transport in neurodegenerative disease, peripheral neuropathy, and nerve injury.
Abstract Dominant loss-of-function mutations in DNM2 cause Charcot–Marie–Tooth neuropathy characterized by sensory and motor deficits associated with myelin and/or axonal abnormalities and muscle atrophy. Increasing DNM2 activity from embryogenesis has been reported to ameliorate neuromuscular phenotypes in the Dnm2K562E/+ Charcot–Marie–Tooth mouse; however, this model displays predominantly muscle pathology and limited nerve involvement, precluding rigorous evaluation of neuropathic mechanisms and potential therapies. Here, we performed comprehensive behavioural, electrophysiological, histological and molecular analyses to characterize the Dnm2K562E/SC− mouse, which combines systemic heterozygosity for the common K562E mutation together with Schwann cell-specific deletion of wild-type Dnm2. This model faithfully reproduces key clinical and pathological features of DNM2–Charcot–Marie–Tooth, including motor deficits, reduced general force and coordination, and severe sensory and motor conduction deficits associated with axonal loss, demyelination and inflammation. Mechanistically, we delineate a coherent pathological sequence that explains the profound functional deficits. In particular, a downregulation of the transcription factor EGR2, a master regulator of myelin gene expression, and of the myelin protein MPZ correlates with demyelination. To evaluate the therapeutic potential of DNM2 supplementation, post-symptomatic intrathecal delivery of AAV9-DNM2 driven by the Schwann cell-specific MPZ promoter was performed at 4 weeks. Although DNM2 expression increased in peripheral nerves (∼1.9-fold), no significant improvements were observed across behavioural, electrophysiological, structural or molecular parameters. Together, these findings establish the Dnm2K562E/SC− mouse as a robust preclinical model, recapitulating key features of DNM2–Charcot–Marie–Tooth, and provide crucial insight into the biological and temporal constraints that must guide future therapeutic strategies for DNM2–Charcot–Marie–Tooth.
Abstract Autologous hematopoietic stem cell transplantation (aHSCT) is an effective treatment for aggressive multiple sclerosis refractory to disease-modifying therapies. Yet, its impact on neurodegeneration remains underexplored, and few predictive biomarkers for clinical outcomes after autologous hematopoietic stem cell transplantation exist. We investigated whether autologous hematopoietic stem cell transplantation attenuates retinal neurodegeneration and whether optical coherence tomography-derived retinal measures predict disability progression after transplantation. In this single-center longitudinal cohort study, optical coherence tomography was performed in people with multiple sclerosis treated with autologous hematopoietic stem cell transplantation and non-transplanted controls with relapsing-remitting multiple sclerosis. Retinal layer atrophy rates pre-transplantation and up to 36 months post-transplantation were estimated using linear mixed-effects models and post-transplantation rates were compared with those of non-transplanted controls. Cumulative link mixed models were used to assess whether baseline retinal layer thickness predicted clinical progression after transplantation. The autologous hematopoietic stem cell transplantation cohort included 39 participants (23/39 [59%] female), comprising 23 with relapsing-remitting (15/23 [65%] female), 8 with secondary progressive (5/8 [62.5%] female), and 8 with primary progressive multiple sclerosis (3/8 [37.5%] female). The relapsing-remitting multiple sclerosis control cohort on disease-modifying treatment included 48 participants (31/48 [65%] female). In relapsing-remitting multiple sclerosis, autologous hematopoietic stem cell transplantation reduced thinning of the ganglion-cell/inner-plexiform layer by 0.65 µm/year (95% CI 0.16–1.15, p=0.010), temporal-quadrant peripapillary retinal-nerve-fiber layer by 1.22 µm/year (95% CI 0.63–1.81, p<0.001), and papillomacular bundle peripapillary retinal-nerve-fiber layer by 1.59 µm/year (95% CI 0.89–2.29, p<0.001). Post-transplantation atrophy rates of the global, temporal, and papillomacular-bundle peripapillary retinal nerve fiber layer were lower in the aHSCT cohort than in the control cohort by 0.275 µm/year (95% CI 0.048–0.502, p=0.014), 0.294 µm/year (95% CI 0.118–0.470, p=0.001), and 0.200 µm/year (95% CI 0.043–0.357, p=0.015), respectively. Higher baseline inner nuclear layer thickness predicted better disability outcomes after transplantation in both relapsing and progressive multiple sclerosis in exploratory statistical models (p<0.001). In conclusion, retinal optical coherence tomography demonstrated reduced retinal atrophy rates in relapsing-remitting multiple sclerosis after autologous hematopoietic stem cell transplantation. Higher inner nuclear layer thickness before transplantation predicted more favorable neurological outcomes, indicating that the inner nuclear layer, a retinal layer linked to inflammatory multiple sclerosis activity, may help identify patients most likely to benefit from autologous hematopoietic stem cell transplantation.
Our Scientific Editor reports the highlights of the Brain Conference 2026, which took place in London on 20 March 2026. This one-day event brought together neuroscientists from the UK and Europe to meet, hear state-of-the-art updates on neuroscientific and neurological research, and enjoy the opportunity to network.
The medial temporal lobe is widely recognized as an early site of pathological tau deposition, a central feature in the development of cognitive symptoms. As of now, the biological mechanisms underlying this selective vulnerability of the medial temporal lobe are not yet understood. Here, we tested whether alterations in medial temporal lobe arterial structure are associated with early tau accumulation and cognitive decline. We first applied a novel imaging methodology (super-selective arterial spin labelling) to map vascular supply to the medial temporal lobe. Next, we cross-sectionally investigated the relationship between medial temporal lobe artery diameters and tau burden, derived from magnetic resonance angiography and positron emission tomography imaging, in 151 cognitively unimpaired individuals (mean age: 67.6 years old). Finally, we examined whether artery diameter was correlated with the rate of cognitive decline in a separate cohort of 43 individuals (mean age: 74.2 years old). We found that the blood supply to the medial temporal lobe depended more on arteries from the anterior circulation than the posterior circulation. Individuals with small anterior choroidal artery diameters tended to show higher medial temporal lobe tau burden (r = -0.26, P = 0.001) and faster rates of cognitive decline (r = -0.40, P = 0.012). These results remained significant after adjusting for potential confounding factors such as amyloid burden. Our results show that anterior choroidal artery diameter may be an amyloid-independent determinant of tau pathology and cognitive decline. This suggests that the selective vulnerability of the medial temporal lobe may emerge from subpar perfusion from the anterior circulation.
Stroke is a major cause of long-term disability with variable recovery. While clinical factors such as initial severity play a role, genetic factors are increasingly recognized as important contributors to stroke recovery. Genotype studies are generally focused on a single post-stroke behavioural domain, but some genes might relate to broad mechanisms of plasticity. This study therefore aimed to identify cross-phenotypic genetic variants associated across two or more stroke recovery domains. DNA from Stroke, Stress, Rehabilitation, and Genetics study participants was genotyped, resulting in 9 814 610 variants. In order to examine cross-phenotypic results, we first conducted genome-wide association studies on the six recovery domains: motor (grip force), cognition (Telephone Montreal Cognitive Assessment), depression (Patient Health Questionnaire-8), stress (Primary Care Post-Traumatic Stress Disorder Screen), functional status (Stroke Impact Scale-Activities of Daily Living), and disability (modified Rankin Scale 0-2 versus 3-6), some of which were tested longitudinally, yielding nine phenotypes. Models were adjusted for age, sex, initial severity (NIH Stroke Scale score), and ancestry. Cross-phenotype associations were identified by evaluating single nucleotide polymorphisms (SNPs) associated (P < 5e-5) with multiple phenotypes. To determine how these genetic variants may relate to biological mechanisms of recovery, we conducted gene enrichment analyses. Participants (n = 565, 59% male) had mild-moderate initial stroke severity (median acute NIH Stroke Scale score = 4). After accounting for the correlation structure among the nine phenotypes, we observed 319 cross-phenotypic SNPs, 3.45 times the expected number. Five of the cross-phenotypic SNPs were linked to genes relevant to neural development, function and plasticity, e.g. ERICH1 (rs11778883-C), FOX3 (rs55726768-G), LIFR-AS1 (rs76401391-T), RPS6KA2 (rs113518460-C) and TUBGCP2 (rs147150392-C), as were enrichments in RAB5-EEA1, CTNNA1-CTNNB1, CIN85-SH3GL2 and ELMO1-DOCK2 complexes. Multiple gene enrichments were found, e.g. Stroke Impact Scale-Activities of Daily Living and Patient Health Questionnaire 8 at 3 months were enriched for CREB phosphorylation, which is important for long-term potentiation. We identified cross-phenotypic SNPs associated with multiple behavioural domains of stroke recovery. Some of these genes encode, or regulate, druggable proteins. These genetic factors are not well captured by clinical or neuroimaging assessments and so provide a unique window into stroke recovery. These findings, if validated, suggest that some genes may be broadly important to stroke recovery.
The conversion of native prion protein (PrP) into its misfolded isoform, scrapie (PrPSc) and its intracellular accumulation represent central events in the pathogenesis of prion diseases. Reduction of native PrP in the central nervous system (CNS) has emerged as a promising strategy for treatment and prevention of prion diseases in humans. To facilitate translation into clinical practice, it is essential to identify at-risk individuals through biomarker development and to elucidate PrP behaviour across prion disease subtypes and biological fluids. Measurements of PrP in accessible biofluids, such as plasma and cerebrospinal fluid (CSF), may provide a pharmacodynamic readout and enable monitoring for PrP-targeted therapies. This study systematically quantifies PrP in plasma and CSF of individuals with sporadic and genetic prion diseases, healthy controls (HC), patients with non-neurodegenerative neurological conditions (ND) and Alzheimer's disease (AD). We analysed 136 plasma and 84 CSF samples, including HC, AD, sporadic Creutzfeldt-Jakob disease (sCJD), as well as symptomatic patients and asymptomatic carriers of the mutations D178N, E200K and P102L. Quantification of PrP was performed using a BetaPrion Human ELISA. Statistical analyses assessed differences between diagnostic groups, associations with demographic factors and PRNP codon 129 polymorphism, and diagnostic accuracy via ROC curves. Plasma PrP was significantly reduced in patients with sCJD (P = 0.043), in symptomatic patients with the E200K (P = 0.0078) and in both symptomatic and asymptomatic D178N carriers (P = 0.0002) compared to HC. Furthermore, symptomatic and asymptomatic D178N carriers had significantly lower plasma PrP levels than patients with AD (P = 0.0025 and P = 0.0041, respectively). In CSF, PrP concentrations were notably lower in D178N symptomatic patients (P = 0.0026) versus non-neurodegenerative (ND) controls. Plasma PrP levels showed no association with age, sex or disease onset and were lower in genetic prion disease patients with the methionine/valine (MV) genotype at PRNP codon 129. The diagnostic accuracy for PrP quantification in plasma as a biomarker discriminated D178N asymptomatic carriers [area under the curve (AUC) = 0.96] and D178N symptomatic patients (AUC = 0.90) from HC with excellent accuracy. In CSF, PrP quantification discriminated D178N symptomatic patients from ND with good accuracy (AUC = 0.64). Taken together, this study defines a characteristic profile of persistently low plasma and CSF PrP in D178N symptomatic and asymptomatic mutation carriers. Low plasma levels in sCJD and E200K, in contrast to P102L, are puzzling. Mutation-specific patterns of PrP need to be considered for monitoring purposes in clinical trials.
Hippocampal sclerosis is the most common histopathological diagnosis in epilepsy surgical specimens. Although hippocampal sclerosis can be identified in vivo with brain MRI, it cannot be detected by expert qualitative review in as many as 50% of cases. Quantitative features derived from structural brain MRI, such as hippocampal shape, volume, and asymmetry features, show promise in identification of hippocampal sclerosis in vivo but have had limited translation to clinical practice partly due to the need for large normative cohorts for estimation of hippocampal pathology. Using the Imaging Database for Epilepsy And Surgery cohort, which includes brain MRI scans from 442 individuals with drug-resistant focal epilepsy who underwent epilepsy surgery and 100 healthy controls acquired on multiple scanners, we evaluated the diagnostic performance of the hippocampal asymmetry index calculated using only the participant's hippocampal volumes against a gold standard histopathological diagnosis of hippocampal sclerosis. The hippocampal asymmetry index had high diagnostic performance (area under the curve for left hippocampal sclerosis = 0.95 (95% confidence interval 0.92-0.97); right hippocampal sclerosis = 0.96 (95% confidence interval 0.94-0.98) and was similar regardless of segmentation algorithm, data harmonization, and use of normative data. To facilitate validation, we provide an open-source software tool for the calculation of the hippocampal asymmetry index.
Given the importance of sleep for the regulation of cortical excitability, altered sleep homeostasis may contribute to the development and persistence of focal epilepsy. The goal of the present study was to quantify high-density EEG markers of sleep homeostasis in patients with focal epilepsy compared to healthy age- and gender-matched controls. In particular, we investigated the ability of sleep homeostasis markers to differentiate focal epilepsy versus healthy controls and quantified the deleterious effects of nocturnal epileptiform discharges on sleep homeostasis. Thirty-nine patients with focal epilepsy and 48 healthy controls underwent overnight 256-electrode high-density EEG recordings. Statistical analysis tested for differences in overnight slow-wave activity (i.e. delta power, 1-4 Hz, and theta power, 4-8 Hz) and average slope of slow waves between patients and healthy controls. We assessed the predictive value of sleep homeostasis parameters to identify focal epilepsy at the individual level. Finally, we investigated the relationship between the frequency of epileptiform discharges and abnormal overnight declines in sleep slow-wave activity and slow-wave slope. Patients with focal epilepsy displayed higher slow-wave activity and a steeper average slope of slow wave compared to healthy controls, exhibiting slow-wave activity values at the end of the night similar to those observed in healthy controls at the beginning of the night. Among sleep homeostasis markers, the presence of high local extremes in the topographical distribution of theta values proved to be discriminative at the single-subject level for distinguishing patients from healthy controls (area under the curve = 0.84). A significant negative association was observed between left-lateralized nocturnal epileptiform discharges and the overnight decline in slow-wave activity and slow wave slope, with the most pronounced effects over the left fronto-temporal leads. Local abnormalities in sleep homeostasis may constitute a reliable biomarker for focal epilepsy. Further studies are needed to determine whether it could also be used to identify focal epilepsy early in the disease course. Furthermore, frequent epileptiform discharges during sleep may contribute to abnormalities in sleep homeostasis and thus to the persistence of cortical hyperexcitability in focal epilepsy.
NMDA receptor antibody-associated (NMDAR-Ab) encephalitis primarily affects young women and children and often requires prolonged intensive care admission. Currently available first- and second-line therapies are effective, but patients can be refractory and residual deficits are not uncommon. Although B-cell lineages and specific NMDAR (NR1 subunit) antibodies have been examined in detail, the subtypes and roles of antigen-specific T cells in providing T-cell help to drive the IgG antibody response, cytotoxic effects or other roles have not been reported. Peripheral blood mononuclear cells from eight patients and eight healthy volunteers underwent three rounds of stimulation with pooled 15-mer peptides spanning the length of the NR1 sequence. At each round of stimulation, functional CD4+ and CD8+ T-cell responses to NR1-derived peptide pools were assessed using flow cytometry. CD4+ and CD8+ T responses to NR1-derived peptide pools were identified in both patients and healthy volunteers. Patient CD4+ T-cell responses were more frequent compared to healthy volunteers after the first round of stimulation, with fewer responses after the third round. Healthy volunteer CD4+ T cells showed the opposite trend (P = 0.004, χ² test for trend). Patient CD8+ T-cell responses were also stronger than healthy volunteers after just one round of stimulation, but not thereafter. Surprisingly, both patient and healthy volunteer CD8+ T cells responded more strongly to NR1-peptide pools than CD4+ T cells. Epitope mapping after round 3 identified two NR1 peptide epitopes as targets for CD4+ T cells and eight peptide epitopes as targets for CD8+ T cells. These epitopes were distributed throughout the NR1 sequence and were distant from the well-established antibody epitope. Although the kinetics of the responses to NR1 peptides in patients may be compatible with in vivo priming of autoreactive T cells or their reduced regulation, overall, the difference between patient and healthy volunteer responses was modest. Further investigation is needed to better characterize these responses and determine their implications for disease pathogenesis, prognosis and therapy. The existence of natural responses to NR1 as a potential autoantigen, particularly in the CD8+ T-cell lineage, should also be explored.
Diffusion-weighted MRI (DWI) can offer vital quantitative biomarkers to understand paediatric brain tumours to benefit clinical management. However, extraction of these markers requires delineation of the tumour margins, which is time-consuming, requires expertise and can still be highly variable. Automated approaches using deep learning to generate these tumour regions exist, but to our knowledge, few exist using only DWI as an input modality, with none in paediatrics. This retrospective study develops an automated segmentation approach, leveraging transfer learning and multi-modal ensembling to tackle the issues specific to this DWI-only approach. Using the Imaging of Tumors study data, we analysed data from 107 paediatric brain tumour patients. Using a 3D convolutional neural network, namely DeepMedic, to perform automatic segmentations, we demonstrate the benefit of these approaches for this task. We assess the accuracy of these predicted segmentations in comparison to the 'ground truth' manual annotations, with a median Dice score of 0.63 achieved by the best-performing model. The current study highlights the potential of this approach to be implemented in future clinical decision support tools using DWI, but more work is needed to improve segmentation accuracy or establish current performance as 'sufficient' for the purposes that these segmentations are required.
Converging evidence supports a key pathogenic role of the glymphatic system in the accumulation of pathological aggregates in several central nervous system proteinopathies, including amyotrophic lateral sclerosis and other motor neuron diseases. This study aimed to investigate potential glymphatic impairment using diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) across motor neuron disease phenotypes, to examine its clinical correlates, and to assess its relationship with white matter damage. Fifty-seven patients with motor neuron disease and 32 age- and sex-matched healthy controls underwent a 3 Tesla brain MRI scan, including diffusion tensor imaging sequences. We obtained the DTI-ALPS index from each individual, evaluating its relationship with measures of motor and cognitive disability, site of symptom onset, cognitive status, genetic status and fractional anisotropy of white matter tracts. Comparisons between groups were evaluated using analysis of covariance adjusting for age, sex, local fractional anisotropy and white matter hyperintensity burden. Partial correlations with clinical and cognitive measures were also tested. Patients with motor neuron disease exhibited significantly lower DTI-ALPS index values relative to healthy controls (P = 0.05). Patients with bulbar onset had lower DTI-ALPS values than those with spinal onset (P = 0.017). Comparable DTI-ALPS values were found across patients with classical amyotrophic lateral sclerosis clinical presentation and predominant upper or lower motor neuron clinical presentations, with no effect of cognitive diagnosis or genetic status. DTI-ALPS exhibited a significant correlation with disease duration (r = -0.38, P = 0.01). Motor neuron disease patients presenting insomnia had significantly lower DTI-ALPS values compared to those without sleep disturbances (P = 0.002). Significant positive correlations were found between ALPS index and fractional anisotropy values across major white matter tracts, including the internal and external capsules, superior longitudinal fasciculi, anterior, posterior and superior corona radiata, posterior thalamic radiation, fornix and the genu and body of the corpus callosum. This study confirms the presence of altered interstitial fluid diffusivity dynamics across motor neuron disease phenotypes, with greater impairment observed in bulbar-onset cases, patients with longer disease duration, and those experiencing more pronounced sleep disturbances. These findings may support a potential pathogenic role of glymphatic failure in the accumulation of TAR DNA-binding protein 43 proteinopathy and widespread microstructural axonal damage in motor neuron diseases.
Brain computed tomography (CT) is an accessible and commonly utilized technique for assessing brain structure. In cases of idiopathic normal pressure hydrocephalus (iNPH), the presence of ventriculomegaly is often neuroradiologically evaluated by visual rating and manual measurement of each image. Previously, we have developed a deep-learning-model that utilizes transfer learning from magnetic resonance imaging (MRI) for CT-based intracranial tissue segmentation. Accordingly, herein we aimed to enhance the segmentation of ventricular cerebrospinal fluid (VCSF) in brain CT scans and assess the performance of automated brain CT volumetrics in iNPH patient diagnostics. This retrospective study employed a two-stage approach in developing the model. Initially, a 2D U-Net model was trained to predict VCSF segmentations from CT scans, using paired MR-VCSF labels from healthy controls. This model was subsequently refined by incorporating manually segmented lateral CT-VCSF labels from iNPH patients, building on the features learned from the initial U-Net model. The training dataset included 734 CT datasets from healthy controls paired with T1-weighted MRI scans from the Gothenburg H70 Birth Cohort Studies and 62 CT scans from iNPH patients at Uppsala University Hospital. To validate the model's performance across diverse patient populations, external clinical images including scans of 11 iNPH patients from the Universitätsmedizin Rostock, Germany, and 30 iNPH patients from the University of Alabama at Birmingham, United States were used. Further, we obtained three CT-based volumetric measures (CTVMs) related to iNPH. Our analyses demonstrated strong volumetric correlations (ρ = 0.91, P < 0.001) between automatically and manually derived CT-VCSF measurements in iNPH patients. Based on the ventricular volume, the CTVMs exhibited high accuracy in differentiating iNPH patients from controls in external clinical datasets with an AUC of 0.97 (95% CI: 0.94-1.00) and in the Uppsala University Hospital datasets with an AUC of 0.99 (95% CI: 0.98-1.00). CTVMs derived through deep learning show potential for assessing and quantifying morphological features in hydrocephalus. Critically, these measures performed comparably to gold-standard neuroradiology assessments in iNPH patients and healthy controls, even in the presence of intraventricular shunt catheters. Accordingly, such an approach may serve to improve the radiological evaluations of the diagnostic work-up and treatment response monitoring in patients with hydrocephalus. Since CT is much more widely available than MRI, our results have considerable clinical impact.
