Long-term safety of MRI-guided administration of AAV2-GDNF and gadoteridol in the putamen of individuals with Parkinson's disease.

Direct putaminal infusion of adeno-associated virus vector (serotype 2) (AAV2) containing the human glial cell line-derived neurotrophic factor (GDNF) transgene was studied in a phase I clinical trial of participants with advanced Parkinson's disease (PD). Convection-enhanced delivery of AAV2-GDNF with a surrogate imaging tracer (gadoteridol) was used to track infusate distribution during real-time intraoperative magnetic resonance imaging (iMRI). Pre-, intra-, and serial postoperative (up to 5 years after infusion) MRI were analyzed in 13 participants with PD treated with bilateral putaminal co-infusions (52 infusions in total) of AAV2-GDNF and gadoteridol (infusion volume, 450 mL per putamen). Real-time iMRI confirmed infusion cannula placement, anatomic quantification of volumetric perfusion within the putamen, and direct visualization of off-target leakage or cannula reflux (which permitted corresponding infusion rate/cannula adjustments). Serial post-treatment MRI assessment (n = 13) demonstrated no evidence of cerebral parenchyma toxicity in the corresponding regions of AAV2-GDNF and gadoteridol co-infusion or surrounding regions over long-term follow-up. Direct confirmation of key intraoperative safety and efficacy parameters underscores the safety and tissue targeting value of real-time imaging with co-infused gadoteridol and putative therapeutic agents (i.e., AAV2-GDNF). This delivery-imaging platform enhances safety, permits delivery personalization, improves therapeutic distribution, and facilitates assessment of efficacy and dosing effect.

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer's disease.

Recent reports have suggested that the reactivation of otherwise transcriptionally silent transposable elements (TEs) might induce brain degeneration, either by dysregulating the expression of genes and pathways implicated in cognitive decline and dementia or through the induction of immune-mediated neuroinflammation resulting in the elimination of neural and glial cells. In the work we present here, we test the hypothesis that differentially expressed TEs in blood could be used as biomarkers of cognitive decline and development of AD. To this aim, we used a sample of aging subjects (age > 70) that developed late-onset Alzheimer's disease (LOAD) over a relatively short period of time (12-48 months), for which blood was available before and after their phenoconversion, and a group of cognitive stable subjects as controls. We applied our developed and validated customized pipeline that allows the identification, characterization, and quantification of the differentially expressed (DE) TEs before and after the onset of manifest LOAD, through analyses of RNA-Seq data. We compared the level of DE TEs within more than 600,000 TE-mapping RNA transcripts from 25 individuals, whose specimens we obtained before and after their phenotypic conversion (phenoconversion) to LOAD, and discovered that 1790 TE transcripts showed significant expression differences between these two timepoints (logFC ± 1.5, logCMP > 5.3, nominal p value < 0.01). These DE transcripts mapped both over- and under-expressed TE elements. Occurring before the clinical phenoconversion, this TE storm features significant increases in DE transcripts of LINEs, LTRs, and SVAs, while those for SINEs are significantly depleted. These dysregulations end with signs of manifest LOAD. This set of highly DE transcripts generates a TE transcriptional profile that accurately discriminates the before and after phenoconversion states of these subjects. Our findings suggest that a storm of DE TEs occurs before phenoconversion from normal cognition to manifest LOAD in risk individuals compared to controls, and may provide useful blood-based biomarkers for heralding such a clinical transition, also suggesting that TEs can indeed participate in the complex process of neurodegeneration.

TGFß Drives Metabolic Perturbations during Epithelial Mesenchymal Transition in Pancreatic Cancer: TGFß Induced EMT in PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy wherein a majority of patients present metastatic disease at diagnosis. Although the role of epithelial to mesenchymal transition (EMT), mediated by transforming growth factor beta (TGFß), in imparting an aggressive phenotype to PDAC is well documented, the underlying biochemical pathway perturbations driving this behaviour have not been elucidated. We used high-resolution mass spectrometry (HRMS) based molecular phenotyping approach in order to delineate metabolic changes concomitant to TGFß-induced EMT in pancreatic cancer cells. Strikingly, we observed robust changes in amino acid and energy metabolism that may contribute to tumor invasion and metastasis. Somewhat unexpectedly, TGFß treatment resulted in an increase in intracellular levels of retinoic acid (RA) that in turn resulted in increased levels of extracellular matrix (ECM) proteins including fibronectin (FN) and collagen (COL1). These findings were further validated in plasma samples obtained from patients with resectable pancreatic cancer. Taken together, these observations provide novel insights into small molecule dysregulation that triggers a molecular cascade resulting in increased EMT-like changes in pancreatic cancer cells, a paradigm that can be potentially targeted for better clinical outcomes.

Plasma Sphingomyelins in Late-Onset Alzheimer's Disease.

BACKGROUND: Altered plasma levels of sphingolipids, including sphingomyelins (SM), have been found in mouse models of Alzheimer's disease (AD) and in AD patient plasma samples. OBJECTIVE: This study assesses fourteen plasma SM species in a late-onset AD (LOAD) patient cohort (n = 138). METHODS: Specimens from control, preclinical, and symptomatic subjects were analyzed using targeted mass-spectrometry-based metabolomic methods. RESULTS: Total plasma SM levels were not significantly affected by age or cognitive status. However, one metabolite that has been elevated in manifest AD in several recent studies, SM OHC14:1, was reduced significantly in pre-clinical AD and MCI relative to normal controls. CONCLUSION: We recommend additional comprehensive plasma lipidomics in experimental and clinical biospecimens related to LOAD that might advance the utility of plasma sphingomyelin levels in molecular phenotyping and interpretations of pathobiological mechanisms.

A Community-Based Study Identifying Metabolic Biomarkers of Mild Cognitive Impairment and Alzheimer's Disease Using Artificial Intelligence and Machine Learning.

BACKGROUND: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new, biologically, and clinically relevant biomarkers for AD detection and classification. OBJECTIVE: Utilizing artificial intelligence and machine learning, we aim to assess whether a panel of metabolites as detected in plasma can be used as an objective and clinically feasible tool for the diagnosis of mild cognitive impairment (MCI) and AD. METHODS: Using a community-based sample cohort acquired from different sites across the US, we adopted an approach combining Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR), Liquid Chromatography coupled with Mass Spectrometry (LC-MS) and various machine learning statistical approaches to identify a biomarker panel capable of identifying those patients with AD and MCI from healthy controls. RESULTS: Of the 212 measured metabolites, 5 were identified as optimal to discriminate between controls, and individuals with MCI or AD. Our models performed with AUC values in the range of 0.72-0.76, with the sensitivity and specificity values ranging from 0.75-0.85 and 0.69-0.81, respectively. Univariate and pathway analysis identified lipid metabolism as the most perturbed biochemical pathway in MCI and AD. CONCLUSION: A comprehensive method of acquiring metabolomics data, coupled with machine learning techniques, has identified a strong panel of diagnostic biomarkers capable of identifying individuals with MCI and AD. Further, our data confirm what other groups have reported, that lipid metabolism is significantly perturbed in those individuals suffering with dementia. This work may provide additional insight into AD pathogenesis and encourage more in-depth analysis of the AD lipidome.

GDNF and Parkinson's Disease: Where Next? A Summary from a Recent Workshop.

The concept of repairing the brain with growth factors has been pursued for many years in a variety of neurodegenerative diseases including primarily Parkinson's disease (PD) using glial cell line-derived neurotrophic factor (GDNF). This neurotrophic factor was discovered in 1993 and shown to have selective effects on promoting survival and regeneration of certain populations of neurons including the dopaminergic nigrostriatal pathway. These observations led to a series of clinical trials in PD patients including using infusions or gene delivery of GDNF or the related growth factor, neurturin (NRTN). Initial studies, some of which were open label, suggested that this approach could be of value in PD when the agent was injected into the putamen rather than the cerebral ventricles. In subsequent double-blind, placebo-controlled trials, the most recent reporting in 2019, treatment with GDNF did not achieve its primary end point. As a result, there has been uncertainty as to whether GDNF (and by extrapolation, related GDNF family neurotrophic factors) has merit in the future treatment of PD. To critically appraise the existing work and its future, a special workshop was held to discuss and debate this issue. This paper is a summary of that meeting with recommendations on whether there is a future for this therapeutic approach and also what any future PD trial involving GDNF and other GDNF family neurotrophic factors should consider in its design.

Advancing gene therapies, methods, and technologies for Parkinson's Disease and other neurological disorders.

INTRODUCTION: Vector-based intracerebral gene therapies are being used to treat specific neurodegenerative conditions such as Parkinson's Disease (PD). This review presents a basis for central nervous system (CNS) gene therapy treatments of neurodegenerative diseases such as PD, as well as the need for novel skill sets and health delivery strategies within the clinical neurosciences (neurology and neurosurgery) to meet future demand for such therapies. STATE OF THE ART: Preclinical vector-based gene therapy approaches have been translated into clinical trials for PD and other neurodegenerative conditions. Unfortunately, such trials, and parallel efforts using other therapeutics, have yet to provide a breakthrough. Image-guided convection enhanced delivery (CED) optimises the parenchymal distribution of gene therapies applied within the CNS, and may ultimately provide such a breakthrough. CLINICAL IMPLICATIONS: Currently, image-guided CED and gene therapy are not part of training programmes for most neurosurgeons and neurologists. As a result, few medical centres and hospitals have sufficiently experienced teams to participate in gene transfer clinical trials for PD or other neurological conditions. If CNS gene therapies prove to be efficacious for PD and/or other conditions, the demand for such treatments will overwhelm the available number of experienced clinical neuroscience teams and treatment centres. FUTURE DIRECTIONS: Expanded indications and demand for CNS gene therapies will require a worldwide educational effort to supplement the training of clinical neuroscience practitioners. Initially, a limited number of Centres of Excellence will need to establish relevant educational training requirements and best practice for such therapeutic approaches. Advanced technologies, including robotics and artificial intelligence, are especially germane in this regard, and will expand the treatment team's capabilities while assisting in the safe and timely care of those afflicted.

Author Correction: Plasma microRNA markers of upper limb recovery following human stroke.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Infuse-as-you-go convective delivery to enhance coverage of elongated brain targets: technical note.

OBJECTIVE: To develop and assess a convective delivery technique that enhances the effectiveness of drug delivery to nonspherical brain nuclei, the authors developed an occipital "infuse-as-you-go" approach to the putamen and compared it to the currently used transfrontal approach. METHODS: Eleven nonhuman primates received a bilateral putamen injection of adeno-associated virus with 2 mM gadolinium-DTPA by real-time MR-guided convective perfusion via either a transfrontal (n = 5) or occipital infuse-as-you-go (n = 6) approach. RESULTS: MRI provided contemporaneous assessment and monitoring of putaminal infusions for transfrontal (2 to 3 infusion deposits) and occipital infuse-as-you-go (stepwise infusions) putaminal approaches. The infuse-as-you-go technique was more efficient than the transfrontal approach (mean 35 ± 1.1 vs 88 ± 8.3 minutes [SEM; p < 0.001]). More effective perfusion of the postcommissural and total putamen was achieved with the infuse-as-you-go versus transfronatal approaches (100-µl infusion volumes; mean posterior commissural coverage 76.2% ± 5.0% vs 32.8% ± 2.9% [p < 0.001]; and mean total coverage 53.5% ± 3.0% vs 38.9% ± 2.3% [p < 0.01]). CONCLUSIONS: The infuse-as-you-go approach, paralleling the longitudinal axis of the target structure, provides a more effective and efficient method for convective infusate coverage of elongated, irregularly shaped subcortical brain nuclei.

Development of a novel frameless skull-mounted ball-joint guide array for use in image-guided neurosurgery.

OBJECTIVE: Successful convection-enhanced delivery of therapeutic agents to subcortical brain structures requires accurate cannula placement. Stereotactic guiding devices have been developed to accurately target brain nuclei. However, technologies remain limited by a lack of MRI compatibility, or by devices' size, making them suboptimal for direct gene delivery to brain parenchyma. The goal of this study was to validate the accuracy of a novel frameless skull-mounted ball-joint guide array (BJGA) in targeting the nonhuman primate (NHP) brain. METHODS: Fifteen MRI-guided cannula insertions were performed on 9 NHPs, each targeting the putamen. Optimal trajectories were planned on a standard MRI console using 3D multiplanar baseline images. After cannula insertion, the intended trajectory was compared to the final trajectory to assess deviation (euclidean error) of the cannula tip. RESULTS: The average cannula tip deviation was 1.18 ± 0.60 mm (mean ± SD) as measured by 2 independent reviewers. Topological analysis showed a superior, posterior, and rightward directional bias, and the intra- and interclass correlation coefficients were > 0.85, indicating valid and reliable intra- and interobserver evaluation. CONCLUSIONS: The data demonstrate that the BJGA can be used to reliably target subcortical brain structures by using MRI guidance, with accuracy comparable to current frameless stereotactic systems. The size and versatility of the BJGA, combined with a streamlined workflow, allows for its potential applicability to a variety of intracranial neurosurgical procedures, and for greater flexibility in executing MRI-guided experiments within the NHP brain.

Fetal Bovine Serum-Derived Extracellular Vesicles Persist within Vesicle-Depleted Culture Media.

It is known that culture media (CM) promotes cellular growth, adhesion, and protects explanted primary brain cells from in vitro stresses. The fetal bovine serum (FBS) supplement used in most CM, however, contains significant quantities of extracellular vesicles (EVs) that confound quantitative and qualitative analyses from the EVs produced by the cultured cells. We quantitatively tested the ability of common FBS EV-depletion protocols to remove exogenous EVs from FBS-supplemented CM and evaluated the influence such methods have on primary astrocyte culture growth and viability. We assessed two methodologies utilized for FBS EV removal prior to adding to CM: (1) an 18-h ultracentrifugation (UC); and (2) a commercial EV-depleted FBS (Exo-FBS™). Our analysis demonstrated that Exo-FBS™ CM provided the largest depletion (75%) of total FBS EVs, while still providing 6.92 × 108 ± 1.39 × 108 EVs/mL. In addition, both UC and Exo-FBS™ CM resulted in poor primary astrocyte cell growth and viability in culture. The two common FBS EV-depletion methods investigated, therefore, not only contaminate in vitro primary cell-derived EV analyses, but also provide a suboptimal environment for primary astrocyte cell growth and viability. It appears likely that future CM optimization, using a serum-free alternative, might be required to advance analyses of cell-specific EVs isolated in vitro.

Potential Metabolomic Linkage in Blood between Parkinson's Disease and Traumatic Brain Injury.

The etiologic basis for sporadic forms of neurodegenerative diseases has been elusive but likely represents the product of genetic predisposition and various environmental factors. Specific gene-environment interactions have become more salient owing, in part, to the elucidation of epigenetic mechanisms and their impact on health and disease. The linkage between traumatic brain injury (TBI) and Parkinson's disease (PD) is one such association that currently lacks a mechanistic basis. Herein, we present preliminary blood-based metabolomic evidence in support of potential association between TBI and PD. Using untargeted and targeted high-performance liquid chromatography-mass spectrometry we identified metabolomic biomarker profiles in a cohort of symptomatic mild TBI (mTBI) subjects (n = 75) 3⁻12 months following injury (subacute) and TBI controls (n = 20), and a PD cohort with known PD (n = 20) or PD dementia (PDD) (n = 20) and PD controls (n = 20). Surprisingly, blood glutamic acid levels in both the subacute mTBI (increased) and PD/PDD (decreased) groups were notably altered from control levels. The observed changes in blood glutamic acid levels in mTBI and PD/PDD are discussed in relation to other metabolite profiling studies. Should our preliminary results be replicated in comparable metabolomic investigations of TBI and PD cohorts, they may contribute to an "excitotoxic" linkage between TBI and PD/PDD.

Plasma microRNA markers of upper limb recovery following human stroke.

Preclinical investigators have implicated several microRNAs as regulators of gene expression promoting neural plasticity following experimental stroke in rodent models. Our goal was to determine whether similar microRNAs might be identifiable in plasma of humans with variable recovery from stroke. Plasma was collected 19 days post-stroke from 27 participants with mild-moderate upper extremity impairment enrolled in the Critical Periods After Stroke Study (CPASS). MicroRNA expression was assessed using TaqMan microRNA assays. Good clinical recovery was defined as ≥6 point change in the Action Research Arm Test (ARAT) score from baseline to 6 months, with 22 subjects showing good and 5 showing poor recovery. When comparing the good versus poor recovery groups, six microRNAs showed significantly increased expression - miR-371-3p, miR-524, miR-520g, miR-1255A, miR-453, and miR-583, while 3 showed significantly decreased expression - miR-941, miR-449b, and miR-581. MiR-371-3p and miR-941 have previously been associated with neural repair mechanisms; none of the significant microRNAs have previously been associated with stroke. The 9 microRNAs converge on pathways associated with axonal guidance, developmental biology, and cancer. We conclude that plasma microRNAs may be informative regarding human neural repair mechanisms during stroke recovery and probably differ from those seen in experimental stroke models.

Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development.

Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.

Plasma metabolomic biomarkers accurately classify acute mild traumatic brain injury from controls.

Past and recent attempts at devising objective biomarkers for traumatic brain injury (TBI) in both blood and cerebrospinal fluid have focused on abundance measures of time-dependent proteins. Similar independent determinants would be most welcome in diagnosing the most common form of TBI, mild TBI (mTBI), which remains difficult to define and confirm based solely on clinical criteria. There are currently no consensus diagnostic measures that objectively define individuals as having sustained an acute mTBI. Plasma metabolomic analyses have recently evolved to offer an alternative to proteomic analyses, offering an orthogonal diagnostic measure to what is currently available. The purpose of this study was to determine whether a developed set of metabolomic biomarkers is able to objectively classify college athletes sustaining mTBI from non-injured teammates, within 6 hours of trauma and whether such a biomarker panel could be effectively applied to an independent cohort of TBI and control subjects. A 6-metabolite panel was developed from biomarkers that had their identities confirmed using tandem mass spectrometry (MS/MS) in our Athlete cohort. These biomarkers were defined at ≤6 hours following mTBI and objectively classified mTBI athletes from teammate controls, and provided similar classification of these groups at the 2, 3, and 7 days post-mTBI. The same 6-metabolite panel, when applied to a separate, independent cohort provided statistically similar results despite major differences between the two cohorts. Our confirmed plasma biomarker panel objectively classifies acute mTBI cases from controls within 6 hours of injury in our two independent cohorts. While encouraged by our initial results, we expect future studies to expand on these initial observations.