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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Post-mortem T2*- weighted MRI imaging of cortical iron reflects severity of Alzheimer’s Disease

The value of iron-based MRI changes for the diagnosis and staging of Alzheimers disease (AD) depends on an association between cortical iron accumulation and AD pathology. Therefore, this study determined the cortical distribution pattern of MRI contrast changes in cortical regions selected based on the known distribution pattern of tau pathology and investigated whether MRI contrast changes reflect the underlying AD pathology in the different lobes.[Formula]-weighted MRI was performed on post-mortem cortical tissue of controls, late-onset AD, and early-onset AD followed by histology and correlation analyses. Combining ex-vivo high-resolution MRI and histopathology revealed that: LOAD and EOAD have a different distribution pattern of AD pathological hallmarks and MRI contrast changes over the cortex, with EOAD showing more severe MRI changes; (2) per lobe, severity of AD pathological hallmarks correlates with iron accumulation, and hence with MRI. Therefore, iron-sensitive MRI sequences allow detection of the cortical distribution pattern of AD pathology ex-vivo.\n\nAbbreviations

neuroscience↗

bioRxiv2018

Neuropathology and cognitive performance in centenarians

AbstractWith aging, the incidence of neuropathological hallmarks of neurodegenerative diseases increases in the brains of cognitively healthy individuals. It is currently unclear to what extent these hallmarks associate with symptoms of disease at extreme ages. Forty centenarians from the 100-plus Study cohort agreed to post-mortem brain donation. Centenarians self-reported to be cognitive healthy at baseline, which was confirmed by a proxy. Objective ante-mortem measurements of cognitive performance were associated with the prevalence, distribution and quantity of age- and AD-related neuropathological hallmarks. Despite self-reported cognitive health, objective neuropsychological testing suggested varying levels of ante-mortem cognitive functioning. Post-mortem, we found that most neuropathological hallmarks related to age and neurodegenerative diseases such as A{beta} and Tau pathology, as well as atherosclerosis, were abundantly present in most or all centenarians, whereas Lewy body and pTDP-43 pathology were scarce. We observed that increased pathology loads correlated across pathology subtypes, and an overall trend of higher pathology loads to associate with a lower cognitive test performance. This trend was carried especially by the presence of neurofibrillary tangles (NFTs) and granulovacuolar degeneration (GVD) and to a lesser extent by A{beta}-associated pathologies. Cerebral Amyloid Angiopathy (CAA) specifically associated with lower executive functioning in the centenarians. In conclusion, we find that while the centenarians in this cohort escaped or delayed cognitive impairment until extreme ages, their brains reveal varying levels of disease-associated neuropathological hallmarks, some of which associate with cognitive performance.

neuroscience↗

bioRxiv2017

Dopaminergic drug effects on probability weighting during risky decision-making

Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioural addiction characterized by excessive risk-taking behaviour. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighing during decision-making. Healthy controls (n = 21) and pathological gamblers (n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D2/D3 receptor antagonist sulpiride, in a double-blind, counter-balanced, design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e. they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although in the placebo condition, gamblers consistently underweighted losing probabilities. Overall, our results reveal that dopamine D2/D3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision-making.\n\nSignificance statementDopamine has been implicated in risky decision-making and gambling addiction, but the exact mechanisms underlying this influence remain partly elusive. Here we tested the hypothesis that dopamine modulates subjective probability weighting, by examining the effect of a dopaminergic drug on risk-taking behaviour, both in healthy individuals and pathological gamblers. We found that selectively blocking dopamine D2/D3 receptors diminished the typically observed distortion of winning probabilities, characterized by an overweighting of low probabilities and underweighting of high probabilities. This made participants more linear in their subjective estimation of probabilities, and thus more rational in their decision-making behaviour. Healthy participants and pathological gamblers did not differ in their risk-taking behaviour, except in the placebo condition in which gamblers consistently underweighted losing probabilities.

neuroscience↗

bioRxiv2018

A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons

1Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.\n\n2 Author summaryMany pathological conditions, such as epilepsy and cortical spreading depression, are linked to abnormal extracellular ion concentrations in the brain. Understanding the underlying principles of such conditions may prove important in developing treatments for these illnesses, which incur societal costs of tens of billions annually. In order to investigate the role of ion-concentration dynamics in the pathological conditions, one must measure the spatial distribution of all ion concentrations over time. This remains challenging experimentally, which makes computational modeling an attractive tool. We have previously introduced the Kirchhoff-Nernst-Planck framework, an efficient framework for modeling electrodiffusion. In this study, we introduce a 3-dimensional version of this framework and use it to model the electrodiffusion of ions surrounding a morphologically detailed neuron. The simulation covered a 1 mm3 cylinder of tissue for over a minute and was performed in less than a day on a standard desktop computer, demonstrating the frameworks efficiency. We believe this to be an important step on the way to understanding phenomena involving ion concentration shifts at the tissue level.

neuroscience↗

bioRxiv2018

ZIKA VIRUS INFECTION AT MID-GESTATION RESULTS IN FETAL CEREBRAL CORTICAL INJURY AND FETAL DEATH IN THE OLIVE BABOON.

Zika virus (ZIKV) infection during pregnancy in humans is associated with an increased incidence of congenital anomalies including microcephaly as well as fetal death and miscarriage and collectively has been referred to a Congenital Zika Syndrome (CZS). Animal models for ZIKV infection in pregnancy have been developed including mice and macaques. While microcephaly has been achieved in mice via direct injection of ZIKV into the fetal brain or via interference with interferon signaling, in macaques the primary fetal CZS outcome are ocular defects. In the present study we develope the olive baboon (Papio anubis), as a model for the vertical transfer of ZIKV during pregnancy. We infected four mid-gestation, timed-pregnant baboons with the French Polynesian ZIKV isolate (104 ffu) and examined the acute phase of vertical transfer by stopping the study of one dam at 7 days post infection (dpi), two at 14 dpi and one at 21 dpi. All dams exhibited mild to moderate rash and conjunctivitis; three of four dams exhibited viremia at 7 dpi. Of the three dams studied to 14 to 21 days, only one still exhibited viremia on day 14. Vertical transfer of ZIKV to the fetus was found in two pregnancies; in one, vertical transfer was associated with fetal death at [~]14 dpi. In the other, vertical transfer was observed at 21 dpi. Both fetuses had ZIKV RNA in the fetal cerebral cortex as well as other tissues. The 21 dpi fetal cerebral cortex exhibited notable defects in radial glia, radial glial fibers, loss and or damage of immature oligodendrocytes and a loss in neuroprogenitor cells (NPCs). In addition, indices of pronounced neuroinflammation were observed including astrogliosis, increased microglia and IL-6 expression. The dams studied to 14 dpi (n=2) and 21 dpi (n=1) exhibited a anti-ZIKV IgM response and IgG response (21 dpi) that included transfer of the IgG to the fetal compartment (cord blood). The severity of systemic inflammatory response (cytokines and chemokines) reflected the vertical transfer of ZIKV in the two pregnancies. As such, these events likely represent the early mechanisms that lead to microcephaly and/or other CNS pathologies in a primate infected with ZIKV and are the first to be described in a non-human primate during the acute phase of ZIKV infection with a contemporaneous ZIKV strain. The baboon thus represents a major NHP for advancing as a model for ZIKV induced brain pathologies to contrast and compare to humans as well as other NHPs such as macaques.\n\nAUTHOR SUMMARYZika virus is endemic in the Americas, primarily spread through mosquitos and sexual contact. Zika virus infection during pregnancy in women is associated with a variety of fetal pathologies now referred to as Congenital Zika Syndrome (CZS), with the most severe pathology being fetal microcephaly. Developing model organisms that faithfully recreate Zika infection in humans is critical for future development of treatments and preventions. In our present study, we infected Olive baboons at mid-gestation with Zika virus and studied the acute period of viremia and transfer of Zika virus to the fetus during the first three weeks after infection to better understand the timing and mechanisms leading to CZS. We observed Zika virus transfer to fetuses resulting in fetal death in one pregnancy and in a second pregnancy, significant damage to the frontal cortex of the fetal brain consistent with development of microcephaly, closely resembling infection in pregnant women. Our baboon model differs from macaque non-human primate models where the primary fetal outcome during pregnancy following infection with contemporary strains of Zika virus is ocular pathology. Thus, the baboon provides a promising new non-human primate model to further compare and contrast the consequences of Zika virus infection in pregnancy to humans and macaques to better understand the disease.

neuroscience↗

bioRxiv2018

Microglia limit lesion expansion and promote functional recovery after spinal cord injury in mice

Traumatic spinal cord injury (SCI) elicits a robust intraspinal inflammatory reaction that is dominated by at least two major subpopulations of macrophages, i.e., those derived from resident microglia and another from monocytes that infiltrate the injury site from the circulation. Previously, we implicated monocyte-derived macrophages (MDMs) as effectors of acute post-injury pathology after SCI; however, it is still unclear whether microglia also contribute to lesion pathology. Assigning distinct functional roles to microglia and MDMs in vivo has been difficult because these CNS macrophage subsets are morphologically and phenotypically similar. Here, to characterize the role that microglia play in experimental models of thoracic spinal contusion or lumbar crush injury, mice were fed vehicle chow or chow laced with a CSF1R receptor antagonist, PLX5622. Feeding PLX5622 depletes microglia. In both groups, spontaneous recovery of hindlimb motor function was evaluated for up to 8 weeks post-SCI using open-field and horizontal ladder tests. Histopathological assessment of intraspinal pathology was assessed in 8 week post-injury tissues. In both SCI models, microglia depletion exacerbated lesion pathology and impaired spontaneous recovery of hind limb function. Notably, the loss of microglia prevented astroglial encapsulation of the lesion core, which was associated with larger lesions, enhanced demyelination and neuron loss and a larger inflammatory response that was dominated by monocyte-derived macrophages. The neuroprotective and healing properties of microglia become obvious in the subacute phases of recovery; microglia depletion up to 7 days post-injury (dpi) had no apparent effect on recovery while delayed depletion from 8-28dpi exacerbated lesion pathology and significantly impaired functional recovery. These data suggest that microglia have essential tissue repair functions after SCI. Selective enhancement of microglial activities may be a novel strategy to preserve tissue and promote recovery of function after neurotrauma.

neuroscience↗

bioRxiv2026

Aberrant neuronal cell cycle re-entry induces late-onset Alzheimer's disease relevant neuropathological and gene expression changes

Aberrant neuronal cell cycle re-entry (NCCR) is an alternative pathogenic mechanism in Alzheimer disease (AD) that has gained substantial support in the literature. The pathogenic role of ectopic NCCR is supported by our past work demonstrating that SV40T-mediated NCCR in adult mice can induce numerous pathologies associated with AD. Since NCCR is chronically induced for an extended period in the mouse model which gives rise to numerous pathologies including neuroinflammation, many of these neuropathological changes could simultaneously participate in driving disease progression. We hypothesized that the NCCR is a primary pathogenic driver and that halting this disease process at a later age could be sufficient for preventing the progression of AD-related pathologies. Here we show that modulation of NCCR at a later age prevents the progression of AD pathologies, including Abeta; and tau pathologies. Furthermore, functional genomics analysis demonstrates the late-onset AD (LOAD)-relevance of NCCR. Our findings suggest that our NCCR mouse model could help identify novel therapeutic targets that could aid in preventing AD progression.

neuroscience↗

bioRxiv2018

Large-Scale Annotation of Histopathology Images from Social Media

Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease states. Area Under Receiver Operating Characteristic is 0.805-0.996 for these tasks. We repurpose the disease classifier to search for similar disease states given an image and clinical covariates. We report precision@k=1 = 0.7618{+/-}0.0018 (chance 0.397{+/-}0.004, mean{+/-}stdev). The classifiers find texture and tissue are important clinico-visual features of disease. Deep features trained only on natural images (e.g. cats and dogs) substantially improved search performance, while pathology-specific deep features and cell nuclei features further improved search to a lesser extent. We implement a social media bot (@pathobot on Twitter) to use the trained classifiers to aid pathologists in obtaining real-time feedback on challenging cases. If a social media post containing pathology text and images mentions the bot, the bot generates quantitative predictions of disease state (normal/artifact/infection/injury/nontumor, pre-neoplastic/benign/ low-grade-malignant-potential, or malignant) and lists similar cases across social media and PubMed. Our project has become a globally distributed expert system that facilitates pathological diagnosis and brings expertise to underserved regions or hospitals with less expertise in a particular disease. This is the first pan-tissue pan-disease (i.e. from infection to malignancy) method for prediction and search on social media, and the first pathology study prospectively tested in public on social media. We will share data through pathobotology.org. We expect our project to cultivate a more connected world of physicians and improve patient care worldwide.

pathology↗

bioRxiv2015

Expression weighted cell type enrichments reveal genetic and cellular nature of major brain disorders

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimers disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimers and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimers disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Neuroscience↗

bioRxiv2016

A convex optimization approach for identification of human tissue-specific interactomes

MotivationAnalysis of organism-specific interactomes has yielded novel insights into cellular function and coordination, understanding of pathology, and identification of markers and drug targets. Genes, however, can exhibit varying levels of cell-type specificity in their expression, and their coordinated expression manifests in tissue-specific function and pathology. Tissue-specific/ selective interaction mechanisms have significant applications in drug discovery, as they are more likely to reveal drug targets. Furthermore, tissue-specific transcription factors (tsTFs) are significantly implicated in human disease, including cancers. Finally, disease genes and protein complexes have the tendency to be differentially expressed in tissues in which defects cause pathology. These observations motivate the construction of refined tissue-specific interactomes from organism-specific interactomes.\n\nResultsWe present a novel technique for constructing human tissue-specific interactomes. Using a variety of validation tests (ESEA, GO Enrichment, Disease-Gene Subnetwork Compactness), we show that our proposed approach significantly outperforms state of the art techniques. Finally, using case studies of Alzheimers and Parkinsons diseases, we show that tissue-specific interactomes derived from our study can be used to construct pathways implicated in pathology and demonstrate the use of these pathways in identifying novel targets.\n\nAvailabilityhttp://www.cs.purdue.edu/homes/mohammas/projects/ActPro.html

Systems Biology↗

bioRxiv2016

Zika Fetal Neuropathogenesis: Etiology of a Viral Syndrome

The ongoing Zika Virus epidemic in the Americas, and the observed association with both fetal abnormalities (primary microcephaly) and adult autoimmune pathology (Guillain-Barre syndrome) has brought attention to this neglected pathogen. While initial case studies generated significant interest in the Zika virus outbreak, larger prospective epidemiology and basic virology studies examining the mechanisms of Zika viral infection and associated pathophysiology are only now starting to be published. In this review, we analyze Zika fetal neuropathogenesis from a comparative pathology perspective, using the historic metaphor of \"TORCH\" viral pathogenesis to provide context. By drawing parallels to other viral infections of the fetus, we identify common themes and mechanisms that may illuminate the observed pathology. The existing data on the susceptibility of various cells to both Zika and other flavivirus infections are summarized. Finally, we highlight relevant aspects of the known molecular mechanisms of flavivirus replication.\n\nKey Learning PointsO_LIViral TORCH pathogens reveal common patterns of fetal pathophysiology and vertical transmission which are relevant to Zika Virus fetal neuropathogenesis.\nC_LIO_LIThe teratogenic effects of Zika Virus infection during the first trimester may involve infection of the trophoblast, viral translocation across the placenta, migration of infected cells resulting in embryonic infection, or indirect effects associated with high levels of inflammatory cytokines produced by infected placenta.\nC_LIO_LIPre-existing maternal non-neutralizing antibody to Zika virus may enhance the probability of infection or more severe disease in the fetus.\nC_LIO_LIAXL has been identified as a major receptor for Zika Virus.\nC_LIO_LIZika virus activation of Toll Like Receptor 3 (TLR-3) pathways in central nervous system cells may trigger apoptosis and attenuate neurogenesis, directly contributing to fetal neuropathology.\nC_LIO_LIFlaviviruses subvert host autophagy and noncoding RNA regulatory pathways.\nC_LIO_LIRecognition of viral sequences by regulatory RNA binding proteins such as Musashi may have a role in Zika pathogenesis and host tissue tropism.\nC_LIO_LIEvidence from other TORCH viral pathogen studies indicate multiple plausible hypotheses for transplacental infection by Zika virus during the second or third trimester, including transcytosis of non-neutralizing antibody-coated Zika virus complexes.\nC_LI\n\nKey ReferencesAdibi JJ, Marques ET Jr, Cartus A, Beigi RH. Teratogenic effects of the Zika virus and the role of the placenta. Lancet 2016; 387: 1587-90 (Hypothesis)\nAdams Waldorf KM, McAdams RM. Influence of infection during pregnancy on fetal development. Reproduction. 2013 Oct 1;146(5) (Review)\nHamel R, Dejarnac O, Wichit S, Ekchariyawat P, Neyret A, Luplertlop N, et al. Biology of Zika Virus Infection in Human Skin Cells. J Virol. 2015;89(17):8880-96.\nMlakar J, Korva M, Tul N, Popovi[c] M, Polj[s]ak-Prijatelj M, Mraz J, et al. Zika Virus Associated with Microcephaly. N Engl J Med. 2016 Feb 10.\nPaul LM, Carlin ER, Jenkins MM, Tan AL, Barcellona CM, Nicholson CO, Trautmann L, Michael SF, Isern S. Dengue Virus Antibodies Enhance Zika Virus Infection. bioRxiv doi: http://dx.doi.org/10.1101/050112\nCrow YJ, Manel N. Aicardi-Goutieres syndrome and the type I interferonopathies. Nat Rev Immunol. 2015;15(7):429-40.\nTonduti D, Orcesi S, Jenkinson EM, Dorboz I, Renaldo F, Panteghini C, et al. Clinical, radiological and possible pathological overlap of cystic leukoencephalopathy without megalencephaly and Aicardi-Goutieres syndrome. Eur J Paediatr Neurol. 2016.\nCipolat Mis MS, Brajkovic S, Frattini E, Di Fonzo A, Corti S. Autophagy in motor neuron disease: Key pathogenetic mechanisms and therapeutic targets. Molecular and Cellular Neurosciences. 2016;72:84-90.\nDang J, Tiwari SK, Lichinchi G, Qin Y, Patil VS, Eroshkin AM, Rana TM. Zika Virus Depletes Neural Progenitors in Human Cerebral Organoids through Activation of the Innate Immune Receptor TLR3. Cell Stem Cell. 2016: 19: 1-8.\nVianna FS, Schuler-Faccini L, Leite JC, de Sousa SH, da Costa LM, Dias MF, et al. Recognition of the phenotype of thalidomide embryopathy in countries endemic for leprosy: new cases and review of the main dysmorphological findings. Clin Dysmorphol. 2013;22(2):59-63.

Developmental Biology↗

bioRxiv2016

Sensory neuron fate is developmentally perturbed by Gars mutations causing human neuropathy

Charcot-Marie-Tooth disease type 2D (CMT2D) is a peripheral nerve disorder caused by dominant, toxic, gain-of-function mutations in the widely expressed, housekeeping gene, GARS. The mechanisms underlying selective nerve pathology in CMT2D remain unresolved, as does the cause of the mild-to-moderate sensory involvement that distinguishes CMT2D from the allelic disorder distal spinal muscular atrophy type V. To elucidate the mechanism responsible for the underlying afferent nerve pathology, we examined the sensory nervous system in CMT2D mice. We show that the equilibrium between functional subtypes of sensory neuron in dorsal root ganglia is distorted by Gars mutations, leading to sensory defects in peripheral tissues and correlating with overall disease severity. CMT2D mice display changes in sensory behaviour concordant with the afferent imbalance, which is present at birth and non-progressive, indicating that sensory neuron identity is prenatally perturbed and that a critical developmental insult is key to the afferent pathology. This suggests that both neurodevelopmental and neurodegenerative mechanisms contribute to CMT2D pathogenesis, and thus has profound implications for the timing of future therapeutic treatments.\n\nSignificance StatementCharcot-Marie-Tooth disease (CMT) is a collection of genetically diverse inherited nerve disorders with the unifying feature of peripheral neuron degeneration. The mechanisms triggering this motor and sensory nerve dysfunction remain unresolved, as does the reason for the lack of sensory pathology observed in distal hereditary motor neuropathies, which can be associated with CMT genes. To unravel the mechanisms leading to afferent deterioration, we have studied the sensory nervous system of CMT Type 2D mice. Our work indicates that the specific cellular identity of sensory nerves is perturbed in mutant mice pre-natally. CMT therefore manifests through the complex interplay between malfunctioning developmental, maturation, and survival programs, which has important ramifications for therapeutic timing.

Neuroscience↗

bioRxiv2017

Insular cortex sub-region-dependent distribution pattern of α-synuclein immunoreactivity in Parkinson’s disease and dementia with Lewy bodies

The insular cortex is a heterogeneous and widely connected brain region. It plays a role in autonomic, cognitive, emotional and somatosensory functions. Its complex and unique cytoarchitecture includes a periallocortical agranular, pro-isocortical dysgranular, and isocortical granular sub-regions. In Parkinsons disease (PD), the insula shows -synuclein inclusions in advanced stages of the disease and its atrophy correlates with cognitive deficits. However, little is known regarding its regional neuropathological characteristics and vulnerability in Lewy body diseases. The aim of this study is to assess the distribution pattern of -synuclein pathology in the insular sub-regions and the selective vulnerability of its different cell types in PD and dementia with Lewy bodies (DLB). Human post-mortem insular tissues from 10 donors with incidental Lewy body disease (iLBD), PD, DLB, and age-matched controls were immunostained for -synuclein and glial fibrillary acid protein (GFAP). Results showed that a decreasing gradient of -synuclein pathology was present from agranular to granular sub-regions in iLBD, PD and PD with dementia (PDD) donors. The agranular insula was heavily inflicted, revealing various -synuclein immunoreactive morphological structures, predominantly Lewy neurites (LNs), and astroglial synucleinopathy. While dysgranular and granular sub-regions showed a decreasing gradient of inclusions and more Lewy bodies (LBs) in deeper layers. In DLB, this gradient was less pronounced and severe pathology was observed in the granular insula compared to PDD and regardless of disease stage. Protoplasmic astrocytes showed -synuclein inclusions and severe degenerative changes increasing with disease severity. While few von Economo neurons (VENs) in the fronto-insular region revealed inclusions, particularly in PDD patients. Our study reports novel findings on the differential involvement of the insular sub-regions in PD and particular involvement of the agranular sub-region, VENs and astrocytes. Thus, the differential cellular architecture of the insular sub-regions portrays the topographic variation and vulnerability to -synuclein pathology in Lewy body diseases.

neuroscience↗

bioRxiv2017

Propagation of Beta/Gamma Rhythms in the Cortico-Basal Ganglia Circuits of the Parkinsonian Rat

Some motor impairments associated with Parkinsons disease are thought to arise from pathological activity in the neuronal networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in Parkinsonism, we investigated changes to the directed connectivity in these networks following dopamine depletion. We recorded local field potentials in the cortex and basal ganglia of anesthetized rats rendered Parkinsonian by injection of 6-hydroxydopamine (6-OHDA), with dopamine-intact rats as controls. We performed systematic analyses of the networks using a novel tool for estimation of directed neural interactions, as well as a conditioned variant which permits the analysis of the dependence of a connection upon a third reference signal. We find evidence of the dopamine dependency of both low beta (14-20 Hz) and high beta/low gamma (20-40 Hz) directed interactions within the BG and cortico-BG networks. Notably, 6-OHDA lesions were associated with enhancement of the cortical \"hyperdirect\" connection to the subthalamic nucleus (STN), as well the STNs feedback to the cortex and striatum. We find beta synchronization to be robust to conditioning using signals from any one structure. Conversely, we find that high beta/gamma drive from the cortex to subcortical regions is weakened by 6-OHDA lesions and is susceptible to conditioning. Furthermore, we provide evidence that gamma is routed from striatum in a pathway that is independent of STN. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in Parkinsonism.\n\nNew & NoteworthyWe present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aims of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinsons disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a \"short-circuiting\" of the network that gives rise to the conditions from which pathological synchronization may arise.

neuroscience↗

bioRxiv2018

Data-driven approaches improve Tau-PET biomarkers in Alzheimer’s disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions-of-interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post-mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data-driven method to identify spatial patterns of tau-PET distribution, and to compare these patterns to previously published \"pathology-driven\" ROIs. Tau-PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimers disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18F]AV1451 uptake in the data-driven clusters, and in 35 previously published pathology-driven ROIs, was extracted from ADNI [18F]AV1451 scans. We performed linear models comparing [18F]AV1451 signal across all 40 ROIs to several tests of global cognition, adjusting for age, sex and education. Two data-driven ROIs consistently demonstrated the strongest or near-strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data-driven, one pathology-driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18F]AV1451-PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.

neuroscience↗

bioRxiv2018

The trade-off between neural computation and oscillatory coordination.

Neural oscillations can improve the fidelity of neural coding by grouping action potentials into synchronous windows of activity but this same effect can interfere with coding when action potentials become "over-synchronized". Diseases ranging from Parkinsons to epilepsy suggest such over-synchronization can lead to pathological outcomes, but the precise boundary separating healthy from pathological synchrony remains an open theoretical problem. In this paper, we focus on measuring the costs of translating from an aperiodic code to a rhythmic one and use the errors introduced in this translation to predict the rise of pathological results. We study a simple model of entrainment featuring a pacemaker population coupled to biophysical neurons. This model shows that "error" in individual cells computations can be traded for population-level synchronization of spike-times. But in this model error and synchronization are not traded linearly, but nonlinearly. The bulk of synchronization happens early with relatively low error. To predict this phenomenon we conceive of "voltage budget analysis", where small time windows of membrane voltage in single cells can be partitioned into "oscillatory" and "computational" terms. By comparing these terms we discover a set of inequalities that align with an inflection point in the curve of measured errors. In particular, when the entrainment and computational voltage terms are equal, the error curve plateaus. We show this point serves as a reliable natural boundary to define pathological synchrony in neurons. We also derive optimal algorithms for exchanging computational error with population synchrony. New and Noteworthy. We establish exact conditions for when rhythmic entrainment of precise spike-times in a neural population will improve or harm its ability to communicate.

neuroscience↗

bioRxiv2018

Computational Modeling of the Dynamic Biomarker Cascade in Alzheimer’s Disease

BackgroundAlzheimers disease (AD) is a major public health concern and there is an urgent need to better understand its complex biology and develop effective therapies. AD progression can be tracked in patients though validated imaging and spinal fluid biomarkers of pathology and neuronal loss. We still, however, lack a coherent quantitative model that explains how these biomarkers interact and evolve over time. Such a model could potentially help identify the major drivers of disease in individual patients and simulate response to therapy prior to entry in clinical trials. A current theory of AD biomarker progression, known as the dynamic biomarker cascade model, hypothesizes AD biomarkers evolve in a sequential, but temporally overlapping manner. A computational model incorporating assumptions about the underlying biology of this theory and its variations would be useful to test and refine its accuracy with longitudinal biomarker data from clinical trials.\n\nMethodsWe implemented a causal model to simulate time-dependent biomarker data under the descriptive assumptions of the dynamic biomarker cascade theory. We modeled pathologic biomarkers (beta-amyloid and tau), neuronal loss biomarkers and cognitive impairment as non-linear first order ordinary differential equations (ODEs) to include amyloid-dependent and non-dependent neurodegenerative cascades. We tested the feasibility of the model by adjusting its parameters to simulate three specific natural history scenarios in early-onset autosomal dominant AD and late-onset AD, and determine whether computed biomarker trajectories agreed with current assumptions of AD biomarker progression. We also simulated the effects of anti-amyloid therapy in late-onset AD.\n\nResultsThe computational model of early-onset AD demonstrated the initial appearance of amyloid, followed by biomarkers of tau and neurodegeneration, followed by onset of cognitive decline based on cognitive reserve, as predicted by prior literature. Similarly, the late-onset AD computational models demonstrated the first appearance of amyloid or non-amyloid-related tauopathy, depending on the magnitude of comorbid pathology, and also closely matched the biomarker cascades predicted by prior literature. Forward simulation of anti-amyloid therapy in symptomatic late-onset AD failed to demonstrate any slowing in progression of cognitive decline, consistent with prior failed clinical trials in symptomatic patients.\n\nConclusionWe have developed and computationally implemented a mathematical causal model of the dynamic biomarker cascade theory in AD. We demonstrate the feasibility of this model by simulating biomarker evolution and cognitive decline in early and late-onset natural history scenarios, as well as in a treatment scenario targeted at core AD pathology. Models resulting from this causal approach can be further developed and refined using patient data from longitudinal biomarker studies, and may in the future play a key role in personalizing approaches to treatment.

neuroscience↗

bioRxiv2018

Multilabel multiclass classification of OCT images augmented with age, gender and visual acuity data

Optical Coherence Tomography (OCT) imaging of the retina is in widespread clinical use to diagnose a wide range of retinal pathologies and several previous studies have used deep learning to create systems that can accurately classify retinal OCT as indicative of one of these pathologies. However, patients often exhibit multiple pathologies concurrently. Here, we designed a novel neural network algorithm that performs multiclass and multilabel classification of retinal images from OCT images in four common retinal pathologies: epiretinal membrane, diabetic macular edema, dry age-related macular degeneration and neovascular age-related macular degeneration. Furthermore, clinicians often also use additional information about the patient for diagnosis. Second contribution of this study is improvement of multiclass, multilabel classification augmented with information about the patient: age, visual acuity and gender. We compared two training strategies: a network pre-trained with ImageNet was used for transfer learning, or the network was trained from randomly initialized weights. Transfer learning does not perform better in this case, because many of the low-level filters are tuned to colors, and the OCT images are monochromatic. Finally, we provide a transparent and interpretable diagnosis by highlighting the regions recognized by the neural network.

physiology↗