Statistical modeling to adjust for time trends in adaptive platform trials utilizing non-concurrent controls

Utilizing non-concurrent controls in the analysis of late-entering experimental arms in platform trials has recently received considerable attention, both on academic and regulatory levels. While incorporating this data can lead to increased power and lower required sample sizes, it might also introduce bias to the effect estimators if temporal drifts are present in the trial. Aiming to mitigate the potential calendar time bias, we propose various frequentist model-based approaches that leverage the non-concurrent control data, while adjusting for time trends. One of the currently available frequentist models incorporates time as a categorical fixed effect, separating the duration of the trial into periods, defined as time intervals bounded by any treatment arm entering or leaving the platform. In this work, we propose two extensions of this model. First, we consider an alternative definition of the time covariate by dividing the trial into fixed-length calendar time intervals. Second, we propose alternative methods to adjust for time trends. In particular, we investigate adjusting for autocorrelated random effects to account for dependency between closer time intervals and employing spline regression to model time with a smooth polynomial function. We evaluate the performance of the proposed approaches in a simulation study and illustrate their use by means of a case study

An autopsy-confirmed case of progressive supranuclear palsy with predominant postural instability

Postural instability and supranuclear gaze palsy represent the key symptoms of Richardson's syndrome, the most frequent clinical manifestation of progressive supranuclear palsy (PSP). However, a proportion of PSP patients never develops ocular motor symptoms, which prevents clinicians from establishing the diagnosis during lifetime according to current diagnostic criteria. We present one instructive autopsy-confirmed PSP case with prospective video-documented clinical course, showing striking temporal divergence of initially present postural instability and delayed development of ocular motor dysfunction. Brain imaging and autopsy findings were typical of PSP, but the temporal sequence of symptoms was unusual with isolated postural instability predominating the clinical course for many years and slowing of vertical saccades/supranuclear gaze palsy evolving not until the 9th/11th year after disease onset. Although other differential diagnoses were unlikely, this patient did not pass the threshold for possible or probable diagnosis of PSP according to current diagnostic criteria until very late in the disease course. This first well documented, autopsy confirmed case of PSP with predominant postural instability further expands the clinical spectrum of PSP and points out the need of new clinical diagnostic criteria with sufficient sensitivity and specificity for an early and reliable diagnosis

FGF2 Affects Parkinson's Disease-Associated Molecular Networks Through Exosomal Rab8b/Rab31

Ras-associated binding (Rab) proteins are small GTPases that regulate the trafficking of membrane components during endocytosis and exocytosis including the release of extracellular vesicles (EVs). Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorder in the elderly population, where pathological proteins such as alpha-synuclein (alpha-Syn) are transmitted in EVs from one neuron to another neuron and ultimately across brain regions, thereby facilitating the spreading of pathology. We recently demonstrated fibroblast growth factor-2 (FGF2) to enhance the release of EVs and delineated the proteomic signature of FGF2-triggered EVs in cultured primary hippocampal neurons. Out of 235 significantly upregulated proteins, we found that FGF2 specifically enriched EVs for the two Rab family membersRab8bandRab31. Consequently, we investigated the interactions ofRab8bandRab31using a network analysis approach in order to estimate the global influence of their enrichment in EVs. To achieve this, we have demarcated a protein-protein interaction network (PPiN) for these Rabs and identified the proteins associated with PD in various cellular components of the central nervous system (CNS), in different brain regions, and in the enteric nervous system (ENS). A total of 126 direct or indirect interactions were reported for two Rab candidates, out of which 114 areRab8binteractions and 54 areRab31interactions, ultimately resulting in an individual interaction score (IS) of 90.48 and 42.86%, respectively. Conclusively, these results for the first time demonstrate the relevance of FGF2-induced Rab-enrichment in EVs and its potential to regulate PD pathophysiology

Statistical integration of multi-omics and drug screening data from cell lines

Data integration methods are used to obtain a unified summary of multiple datasets. For multi-modal data, we propose a computational workflow to jointly analyze datasets from cell lines. The workflow comprises a novel probabilistic data integration method, named POPLS-DA, for multi-omics data.The workflow is motivated by a study on synucleinopathies where transcriptomics, proteomics, and drug screening data are measured in affected LUHMES cell lines and controls. The aim is to highlight potentially druggable pathways and genes involved in synucleinopathies. First, POPLS-DA is used to prioritize genes and proteins that best distinguish cases and controls. For these genes, an integrated interaction network is constructed where the drug screen data is incorporated to highlight druggable genes and pathways in the network. Finally, sfunctional enrichment analyses are performed to identify clusters of synaptic and lysosome-related genes and proteins targeted by the protective drugs. POPLS-DA is compared to other single- and multi-omics approaches.We found that HSPA5, a member of the heat shock protein 70 family, was one of the most targeted genes by the validated drugs, in particular by AT1-blockers. HSPA5 and AT1-blockers have been previously linked to alpha-synuclein pathology and Parkinson's disease, showing the relevance of our findings.Our computational workflow identified new directions for therapeutic targets for synucleinopathies. POPLS-DA provided a larger interpretable gene set than other single- and multi-omic approaches. An implementation based on R and markdown is freely available online. We present a computational workflow that combines the analysis of different types of data measured in cell line studies with non-overlapping samples. We apply the workflow to measurements of gene expression, protein abundances, and a screening of a wide range of FDA-approved drugs. These different types of data are obtained from LUHMES brain cells and jointly analyzed to discover new treatment options in synucleinopathies, such as Parkinson's disease. Our workflow includes a new probabilistic method, named POPLS-DA. POPLS-DA combines the analysis of the genes and proteins to pinpoint a set of relevant genes and proteins that can distinguish affected and non-affected cells. Compared to other approaches, POPLS-DA found a larger set of genes relevant to the disease. Further, we constructed a network that connects the relevant genes and proteins that interact with each other. We incorporate the drug screening data to highlight which part of the network is relevant to the disease and druggable. Through additional analysis of the functionality, we discovered that the genes and proteins that are targeted by protective drugs share relevant properties, namely they are synaptic and lysosome-related genes. Notably, we found that specific types of drugs, namely AT1-blockers such as Telmisartan, are protective and target the network of relevant genes and proteins. These drugs are approved by the FDA and readily available to further investigate their potential in treating synucleinopathies. We further found that a gene named HSPA5, a member of the heat shock protein 70 family, is highly targeted by the protective drugs. This gene has been linked to Parkinson's disease in previous scientific literature. Our computational workflow and the implementation in R and markdown are freely available online

Validation of mobile eye-tracking as novel and efficient means for differentiating progressive supranuclear palsy from Parkinson's disease

Background: The decreased ability to carry out vertical saccades is a key symptom of Progressive Supranuclear Palsy (PSP). Objective measurement devices can help to reliably detect subtle eye movement disturbances to improve sensitivity and specificity of the clinical diagnosis. The present study aims at transferring findings from restricted stationary video-oculography (VOG) to a wearable head-mounted device, which can be readily applied in clinical practice. Methods: We investigated the eye movements in 10 possible or probable PSP patients, 11 Parkinson's disease (PD) patients, and 10 age-matched healthy controls (HCs) using a mobile, gaze-driven video camera setup (EyeSeeCam). Ocular movements were analyzed during a standardized fixation protocol and in an unrestricted real-life scenario while walking along a corridor. Results: The EyeSeeCam detected prominent impairment of both saccade velocity and amplitude in PSP patients, differentiating them from PD and HCs. Differences were particularly evident for saccades in the vertical plane, and stronger for saccades than for other eye movements. Differences were more pronounced during the standardized protocol than in the real-life scenario. Conclusions: Combined analysis of saccade velocity and saccade amplitude during the fixation protocol with the EyeSeeCam provides a simple, rapid (<20 s), and reliable tool to differentiate clinically established PSP patients from PD and HCs. As such, our findings prepare the ground for using wearable eye-tracking in patients with uncertain diagnoses

Statistical integration of multi-omics and drug screening data from cell lines

Data integration methods are used to obtain a unified summary of multiple datasets. For multi-modal data, we propose a computational workflow to jointly analyze datasets from cell lines. The workflow comprises a novel probabilistic data integration method, named POPLS-DA, for multi-omics data. The workflow is motivated by a study on synucleinopathies where transcriptomics, proteomics, and drug screening data are measured in affected LUHMES cell lines and controls. The aim is to highlight potentially druggable pathways and genes involved in synucleinopathies. First, POPLS-DA is used to prioritize genes and proteins that best distinguish cases and controls. For these genes, an integrated interaction network is constructed where the drug screen data is incorporated to highlight druggable genes and pathways in the network. Finally, sfunctional enrichment analyses are performed to identify clusters of synaptic and lysosome-related genes and proteins targeted by the protective drugs. POPLS-DA is compared to other single- and multi-omics approaches. We found that HSPA5, a member of the heat shock protein 70 family, was one of the most targeted genes by the validated drugs, in particular by AT1-blockers. HSPA5 and AT1-blockers have been previously linked to α-synuclein pathology and Parkinson's disease, showing the relevance of our findings. Our computational workflow identified new directions for therapeutic targets for synucleinopathies. POPLS-DA provided a larger interpretable gene set than other single- and multi-omic approaches. An implementation based on R and markdown is freely available online

Comprehensive miRNome-wide profiling in a neuronal cell model of synucleinopathy implies involvement of cell cycle genes

Growing evidence suggests that epigenetic mechanisms like microRNA-mediated transcriptional regulation contribute to the pathogenesis of parkinsonism. In order to study the influence of microRNAs (miRNAs), we analyzed the miRNome 2 days prior to major cell death in α-synuclein-overexpressing Lund human mesencephalic neurons, a well-established cell model of Parkinson\u27s disease (PD), by next-generation sequencing. The expression levels of 23 miRNAs were significantly altered in α-synuclein-overexpressing cells, 11 were down- and 12 upregulated

GBA-associated PD: chances and obstacles for targeted treatment strategies.

Given the clear role of GBA in the pathogenesis of Parkinson's disease (PD) and its impact on phenotypical characteristics, this review provides an overview of the current knowledge of GBA-associated PD with a special focus on clinical trajectories and the underlying pathological mechanisms. Importantly, differences and characteristics based on mutation severity are recognized, and current as well as potential future treatment options are discussed. These findings will inform future strategies for patient stratification and cohort enrichment as well as suitable outcome measures when designing clinical trials

Mitochondrial damage by α-synuclein causes cell death in human dopaminergic neurons

Evolving concepts on Parkinson's disease (PD) pathology suggest that α-synuclein (aSYN) promote dopaminergic neuron dysfunction and death through accumulating in the mitochondria. However, the consequence of mitochondrial aSYN localisation on mitochondrial structure and bioenergetic functions in neuronal cells are poorly understood. Therefore, we investigated deleterious effects of mitochondria-targeted aSYN in differentiated human dopaminergic neurons in comparison with wild-type (WT) aSYN overexpression and corresponding EGFP (enhanced green fluorescent protein)-expressing controls. Mitochondria-targeted aSYN enhanced mitochondrial reactive oxygen species (ROS) formation, reduced ATP levels and showed severely disrupted structure and function of the dendritic neural network, preceding neuronal death. Transmission electron microscopy illustrated distorted cristae and many fragmented mitochondria in response to WT-aSYN overexpression, and a complete loss of cristae structure and massively swollen mitochondria in neurons expressing mitochondria-targeted aSYN. Further, the analysis of mitochondrial bioenergetics in differentiated dopaminergic neurons, expressing WT or mitochondria-targeted aSYN, elicited a pronounced impairment of mitochondrial respiration. In a pharmacological compound screening, we found that the pan-caspase inhibitors QVD and zVAD-FMK, and a specific caspase-1 inhibitor significantly prevented aSYN-induced cell death. In addition, the caspase inhibitor QVD preserved mitochondrial function and neuronal network activity in the human dopaminergic neurons overexpressing aSYN. Overall, our findings indicated therapeutic effects by caspase-1 inhibition despite aSYN-mediated alterations in mitochondrial morphology and function

Automatic covariance pattern analysis outperforms visual reading of 18 F‐fluorodeoxyglucose‐positron emission tomography (FDG‐PET) in variant progressive supranuclear palsy

Background: To date, studies on positron emission tomography (PET) with F-18-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS). Objectives: To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern. Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample. Conclusions: Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. (C) 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society