Explore the vast range of titles available.

Parkinson’s disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson’s disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson’s disease. Neurotransmitter receptor distributions help explain structural and functional brain alterations in Parkinson’s disease. Distinct multi-receptor profiles are associated with the severity of motor, and visuospatial, psychiatric and memory symptoms.

Due to the marked interpersonal neuropathologic and clinical heterogeneity of Parkinson's disease (PD), current interventions are not personalized and fail to benefit all patients. Furthermore, we continue to lack well-established methods and clinical tests to tailor interventions at the individual level in PD. Here, we identify the genetic determinants of individual-tailored treatment needs derived from longitudinal multimodal neuroimaging data in 294 PD patients (PPMI data). Advanced multivariate statistical analysis revealed that both genomic and blood transcriptomic data significantly explain ( P  < 0.01, FWE-corrected) the interindividual variability in therapeutic needs associated with dopaminergic, functional, and structural brain reorganization. We confirmed a high overlap between the identified highly predictive molecular pathways and determinants of levodopa clinical responsiveness, including well-known (Wnt signaling, angiogenesis, dopaminergic activity) and recently discovered (immune markers, gonadotropin-releasing hormone receptor) pathways/components. In addition, the observed strong correspondence between the identified genomic and baseline-transcriptomic determinants of treatment needs/response supports the genome's active role at the time of patient evaluation (i.e., beyond individual genetic predispositions at birth). This study paves the way for effectively combining genomic, transcriptomic and neuroimaging data for implementing successful individually tailored interventions in PD and extending our pathogenetic understanding of this multifactorial and heterogeneous disorder.

To determine if there are sex differences in myelin in Parkinson's disease, and whether these explain some of the previously-described sex differences in clinical presentation.ObjectiveTo determine if there are sex differences in myelin in Parkinson's disease, and whether these explain some of the previously-described sex differences in clinical presentation.Thirty-three subjects (23 males, 10 females) with Parkinson's disease underwent myelin water fraction (MWF) imaging, an MRI scanning technique of in vivo myelin content. MWF of 20 white matter regions of interest (ROIs) were assessed. Motor symptoms were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS). Principal component analysis, logistic and multiple linear regressions, and t-tests were used to determine which white matter ROIs differed between sexes, the clinical features associated with these myelin changes, and if overall MWF and MWF laterality differed between males and females.MethodsThirty-three subjects (23 males, 10 females) with Parkinson's disease underwent myelin water fraction (MWF) imaging, an MRI scanning technique of in vivo myelin content. MWF of 20 white matter regions of interest (ROIs) were assessed. Motor symptoms were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS). Principal component analysis, logistic and multiple linear regressions, and t-tests were used to determine which white matter ROIs differed between sexes, the clinical features associated with these myelin changes, and if overall MWF and MWF laterality differed between males and females.Consistent with prior reports, tremor and bradykinesia were more likely seen in females, whereas rigidity and axial symptoms were more likely seen in males in our cohort. MWF of the thalamic radiation, cingulum, cingulum hippocampus, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate were significant in predicting sex. Overall MWF and asymmetry of MWF was greater in males. MWF differences between sexes were associated with tremor symptomatology and asymmetry of motor performance.ResultsConsistent with prior reports, tremor and bradykinesia were more likely seen in females, whereas rigidity and axial symptoms were more likely seen in males in our cohort. MWF of the thalamic radiation, cingulum, cingulum hippocampus, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate were significant in predicting sex. Overall MWF and asymmetry of MWF was greater in males. MWF differences between sexes were associated with tremor symptomatology and asymmetry of motor performance.Sex differences in myelin are associated with tremor and asymmetry of motor presentation. While preliminary, our results suggest that further investigation of the role of biological sex in myelin pathology and clinical presentation in Parkinson's disease is warranted.ConclusionSex differences in myelin are associated with tremor and asymmetry of motor presentation. While preliminary, our results suggest that further investigation of the role of biological sex in myelin pathology and clinical presentation in Parkinson's disease is warranted.

We continue to lack a clear understanding on how the biological and clinical complexity of Parkinson’s disease emerges from molecular to macroscopic brain interactions. Here, we use personalized multiscale spatiotemporal computational brain models to characterize for the first time the synergistic links between genes, several multimodal neuroimaging-derived biological factors, clinical profiles, and therapeutic needs in PD. We identified genes modulating PD-caused brain reorganization in dopamine transporter level, neuronal activity integrity, microstructure, dendrite density and tissue atrophy. Inter-individual heterogeneity in the identified gene-mediated biological mechanisms was associated with five distinct configurations of PD motor and non-motor symptoms. Notably, the protein-protein interaction networks underlying both brain phenotypic and symptom configurations in PD revealed distinct hub genes including MYC, CCNA2, CCDK1, SRC, STAT3 and PSMD4 . We also studied the biological mechanisms associated with physical activities performance, observing that leisure and work activities are strongly related to neurotypical cholesterol homeostasis and inflammatory response processes, respectively. Finally, patient-tailored in silico gene perturbations revealed a set of putative disease-modifying drugs with potential to effectively treat PD across different biological levels, most of which are associated with dopamine reuptake and anti-inflammation. Our study constitutes the first self-contained multiscale spatiotemporal computational approach providing comprehensive insights into the complex multifactorial pathogenesis of PD, unraveling key biological modulators of physical and clinical deterioration, and serving as a blueprint for optimum drug selection at personalized level.

R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal's dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.

Understanding and treating heterogeneous brain disorders requires specialized techniques spanning genetics, proteomics, and neuroimaging. Designed to meet this need, NeuroPM-box is a user-friendly, open-access, multi-tool cross-platform software capable of characterizing multiscale and multifactorial neuropathological mechanisms. Using advanced analytical modeling for molecular, histopathological, brain-imaging and/or clinical evaluations, this framework has multiple applications, validated here with synthetic (N > 2900), in-vivo (N = 911) and post-mortem (N = 736) neurodegenerative data, and including the ability to characterize: (i) the series of sequential states (genetic, histopathological, imaging or clinical alterations) covering decades of disease progression, (ii) concurrent intra-brain spreading of pathological factors (e.g., amyloid, tau and alpha-synuclein proteins), (iii) synergistic interactions between multiple biological factors (e.g., toxic tau effects on brain atrophy), and (iv) biologically-defined patient stratification based on disease heterogeneity and/or therapeutic needs. This freely available toolbox (neuropm-lab.com/neuropm-box.html) could contribute significantly to a better understanding of complex brain processes and accelerating the implementation of Precision Medicine in Neurology.Iturria-Medina et al. demonstrate the validation of NeuroPM-box — an open-access, multi-tool cross-platform software that can characterize multiscale and multifactorial neuropathological mechanisms. Their tool potentially contributes to a better understanding of complex brain processes, which could accelerate the implementation of Precision Medicine.

Subthalamotomy using transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) is a novel and promising treatment for Parkinson’s Disease (PD). In this study, we investigate if baseline brain imaging features can be early predictors of tcMRgFUS-subthalamotomy efficacy, as well as which are the post-treatment brain changes associated with the clinical outcomes. Towards this aim, functional and structural neuroimaging and extensive clinical data from thirty-five PD patients enrolled in a double-blind tcMRgFUS-subthalamotomy clinical trial were analyzed. A multivariate cross-correlation analysis revealed that the baseline multimodal imaging data significantly explain ( P  < 0.005, FWE-corrected) the inter-individual variability in response to treatment. Most predictive features at baseline included neural fluctuations in distributed cortical regions and structural integrity in the putamen and parietal regions. Additionally, a similar multivariate analysis showed that the population variance in clinical improvements is significantly explained ( P  < 0.001, FWE-corrected) by a distributed network of concurrent functional and structural brain changes in frontotemporal, parietal, occipital, and cerebellar regions, as opposed to local changes in very specific brain regions. Overall, our findings reveal specific quantitative brain signatures highly predictive of tcMRgFUS-subthalamotomy responsiveness in PD. The unanticipated weight of a cortical-subcortical-cerebellar subnetwork in defining clinical outcome extends the current biological understanding of the mechanisms associated with clinical benefits.

Amyotrophic lateral sclerosis (ALS) is a multisystem disease with marked pathophysiological and clinical heterogeneity, making individual and objective characterization of the degree of disease progression and disease‐related subtrajectories challenging. Here, we use in vivo multimodal neuroimaging data and computational models to generate personalized indices of ALS progression and subtrajectory. We used structural and diffusion weighted imaging of 691 participants (58% ALS) from two independent ALS data sets (North American and Utrecht cohorts) to extract regional values of grey matter (DM) density and white matter (WM) microstructural integrity. Contrastive trajectory inference (cTI) allowed us to identify and separate latent, multivariate patterns in neuroimaging features highlighting ALS‐associated pathological processes, which were used to generate subject‐specific indices of disease progression and subtrajectory. Disease subtrajectories were based on distinct patterns of alterations in neuroimaging data considering subjects at different disease progression levels. The neuroimaging‐based, personalized index of disease progression is indicative of clinical symptom severity (North American: p < 0.01 and Utrecht: p < 0.01) and displays alignment with the King's College staging system (p = 0.001 and p = 0.002). Three ALS subtrajectories were identified that displayed distinct alterations in the motor, limbic system, and widespread cortical and subcortical changes that also differed in clinical symptom manifestation. Our analysis has shown that neuroimaging data encodes subject‐specific, disease‐related patterns that can be leveraged to obtain an in vivo proxy of disease progression and putative disease subtype. Amyotrophic lateral sclerosis (ALS) is recognized as a multifaceted disease with varying symptom profiles calling for a more comprehensive understanding of ALS. We demonstrate the feasibility of extracting personalized disease progression markers as well as distinct disease subtrajectories from in vivo multimodal neuroimaging data in a heterogeneous ALS population.

Rationale of the trialAlthough the use of engineered T cells in cancer immunotherapy has greatly advanced the treatment of hematological malignancies, reaching meaningful clinical responses in the treatment of solid tumors is still challenging. We investigated the safety and tolerability of IMA202 in a first-in-human, dose escalation basket trial in human leucocyte antigen A*02:01 positive patients with melanoma-associated antigen A1 (MAGEA1)-positive advanced solid tumors.Trial designThe 2+2 trial design was an algorithmic design based on a maximally acceptable dose-limiting toxicity (DLT) rate of 25% and the sample size was driven by the algorithmic design with a maximum of 16 patients. IMA202 consists of autologous genetically modified cytotoxic CD8+ T cells expressing a T cell receptor (TCR), which is specific for a nine amino acid peptide derived from MAGEA1. Eligible patients underwent leukapheresis, T cells were isolated, transduced with lentiviral vector carrying MAGEA1-specific TCR and following lymphodepletion (fludarabine/cyclophosphamide), infused with a median of 1.4×109 specific T cells (range, 0.086×109–2.57×109) followed by interleukin 2.Safety of IMA202No DLT was observed. The most common grade 3–4 adverse events were cytopenias, that is, neutropenia (81.3%), lymphopenia (75.0%), anemia (50.0%), thrombocytopenia (50.0%) and leukopenia (25.0%). 13 patients experienced cytokine release syndrome, including one grade 3 event. Immune effector cell-associated neurotoxicity syndrome was observed in two patients and was grade 1 in both.Efficacy of IMA202Of the 16 patients dosed, 11 (68.8%) patients had stable disease (SD) as their best overall response (Response Evaluation Criteria in Solid Tumors V.1.1). Five patients had initial tumor shrinkage in target lesions and one patient with SD experienced continued shrinkage in target lesions for 3 months in total but had to be classified as progressive disease due to progressive non-target lesions. IMA202 T cells were persistent in peripheral blood for several weeks to months and were also detectable in tumor tissue. Peak persistence was higher in patients who received higher doses.ConclusionIn conclusion, IMA202 had a manageable safety profile, and it was associated with biological and potential clinical activity of MAGEA1-targeting genetically engineered TCR-T cells in a poor prognosis, multi-indication solid tumor cohort.Trial registration numbersNCT04639245, NCT05430555.

Background The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD. Methods LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability. Results Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some ‘lessons learnt’. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted). Conclusion We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.