Plasma-Enabled Carbon Nanostructures for Early Diagnosis of Neurodegenerative Diseases.
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ABSTRACT:
SUBMITTER: Pineda S
PROVIDER: S-EPMC5455823 | biostudies-other | 2014 Jun
REPOSITORIES: biostudies-other
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Project description:Genetics has led to a new focus regarding approaches to the most prevalent diseases today. Ascertaining the molecular secrets of neurodegenerative diseases will lead to developing drugs that will change natural history, thereby affecting the quality of life and mortality of patients. The sequencing of candidate genes in patients suffering neurodegenerative pathologies is faster, more accurate, and has a lower cost, thereby enabling algorithms to be proposed regarding the risk of neurodegeneration onset in healthy persons including the year of onset and neurodegeneration severity. Next generation sequencing has resulted in an explosion of articles regarding the diagnosis of neurodegenerative diseases involving exome sequencing or sequencing a whole gene for correlating phenotypical expression with genetic mutations in proteins having key functions. Many of them occur in neuronal glia, which can trigger a proinflammatory effect leading to defective proteins causing sporadic or familial mutations. This article reviews the genetic diagnosis techniques and the importance of bioinformatics in interpreting results from neurodegenerative diseases. Risk scores must be established in the near future regarding diseases with a high incidence in healthy people for defining prevention strategies or an early start for giving drugs in the absence of symptoms.
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Project description:Plasma membrane repair is an essential cellular mechanism that reseals membrane disruptions after a variety of insults, and compromised repair capacity can contribute to the progression of many diseases. Neurodegenerative diseases are marked by membrane damage from many sources, reduced membrane integrity, elevated intracellular calcium concentrations, enhanced reactive oxygen species production, mitochondrial dysfunction, and widespread neuronal death. While the toxic intracellular effects of these changes in cellular physiology have been defined, the specific mechanism of neuronal death in certain neurodegenerative diseases remains unclear. An abundance of recent evidence indicates that neuronal membrane damage and pore formation in the membrane are key contributors to neurodegenerative disease pathogenesis. In this review, we have outlined evidence supporting the hypothesis that membrane damage is a contributor to neurodegenerative diseases and that therapeutically enhancing membrane repair can potentially combat neuronal death.
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Project description:The two most generally diagnosed Neurodegenerative diseases are the Alzheimer and Parkinson diseases. So this paper presents a fully automated early screening system based on the Capsule network for the classification of these two Neurodegenerative diseases. In this study, we hypothesized that the Neurodegenerative diseases-Caps system based on the Capsule network architecture accurately performs the multiclass i.e. three class classification into either the Alzheimer class or Parkinson class or Healthy control and delivers better results in comparison other deep transfer learning models. The real motivation behind choosing the capsule network architecture is its more resilient nature towards the affine transformations as well as rotational & translational invariance, which commonly persists in the medical image datasets. Apart from this, the capsule networks overcomes the pooling layers related deficiencies from which conventional CNNs are mostly affected and unable to delivers accurate results especially in the tasks related to image classification. The various Computer aided systems based on machine learning for the classification of brain tumors and other types of cancers are already available. Whereas for the classification of Neurodegenerative diseases, the amount of research done is very limited and the number of persons suffering from this type of diseases are increasing especially in developing countries like India, China etc. So there is a need to develop an early screening system for the correct multiclass classification into Alzheimer's, Parkinson's and Normal or Healthy control cases. The Alzheimer disease and Parkinson progression (ADPP) dataset is used in this research study for the training of the proposed Neurodegenerative diseases-Caps system. This ADPP dataset is developed with the aid of both the Parkinson's Progression Markers Initiative (PPMI) and Alzheimer's disease Neuroimaging Initiative (ADNI) databases. There is no such early screening system exist yet, which can perform the accurate classification of these two Neurodegenerative diseases. For the sake of genuine comparison, other popular deep transfer learning models like VGG19, VGG16, ResNet50 and InceptionV3 are implemented and also trained over the same ADPP dataset. The proposed Neurodegenerative diseases-Caps system deliver accuracies of 97.81, 98, 96.81% for the Alzheimer, Parkinson and Healthy control or Normal cases with 70/30 (training/validation split) and performs way better as compare to the other popular Deep transfer learning models.Supplementary informationThe online version contains supplementary material available at 10.1007/s11571-022-09787-1.
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Project description:Hexanucleotide expansion in C9orf72 has been related to several phenotypes to date, complicating the clinical recognition of these neurodegenerative disorders. An early diagnosis can improve the management of patients, promoting early administration of therapeutic supportive strategies. Here, we report known clinical presentations of C9orf72-related neurodegenerative disorders, pointing out suggestive phenotypes that can benefit the genetic characterization of patients. Considering the high variability of C9orf72-related disorder, frequent and rare manifestations are described, with detailed clinical, instrumental evaluation, and supportive therapeutical approaches. Furthermore, to improve the understanding of molecular pathways of the disease and potential therapeutical targets, a detailed description of the cellular mechanisms related to the pathological effect of C9orf72 is reported. New promising therapeutical strategies and ongoing studies are reported highlighting their molecular role in cellular pathological pathways of C9orf72. These therapeutic approaches are particularly promising because they seem to stop the disease before neuronal damage. The knowledge of clinical and molecular features of C9orf72-related neurodegenerative disorders improves the therapeutical application of known strategies and will lay the basis for the development of new potential therapies.
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Project description:BackgroundNeurodegenerative Langerhans Cell Histiocytosis (ND-LCH) is a rare, unpredictable consequence that may devastate the quality of life of patients cured from LCH. We prospectively applied a multidisciplinary diagnostic work-up to early identify and follow-up patients with ND-LCH, with the ultimate goal of better determining the appropriate time for starting therapy.MethodsWe studied 27 children and young adults with either ND-LCH verified by structural magnetic resonance imaging (MRI) (group 1) or specific risk factors for (diabetes insipidus, craniofacial bone lesions), but no evidence of, neurodegenerative MRI changes (group 2). All patients underwent clinical, neurophysiological and MRI studies.ResultsSeventeen patients had MRI alterations typical for ND-LCH. Nine showed neurological impairment but only three were symptomatic; 11 had abnormal somatosensory evoked potentials (SEPs), and five had abnormal brainstem auditory evoked potentials (BAEPs). MR spectroscopy (MRS) showed reduced cerebellar NAA/Cr ratio in nine patients. SEPs showed sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for predicting ND-LCH of 70.6% (95%CI, 44.0%-89.7%), 100% (69.2%-100%), 100% (73.5%-100%), and 66.7% (38.4%-88.2%), respectively. Repeated investigations in group 1 revealed increasingly abnormal EP parameters, or neurological examination, or both, in nine of fifteen patients while MRI remained unchanged in all but one patient.ConclusionA targeted MRI study should be performed in all patients with risk factors for ND-LCH for early identification of demyelination. The combined use of SEPs and careful neurological evaluation may represent a valuable, low-cost, well-tolerated and easily available methodology to monitor patients from pre-symptomatic to symptomatic stages. We suggest a multidisciplinary protocol including clinical, MRS, and neurophysiological investigations to identify a population target for future therapeutic trials.
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Project description:Neurodegenerative diseases of the central nervous system are characterised by pathogenetic cellular and molecular changes in specific areas of the brain that lead to the dysfunction and/or loss of explicit neuronal populations. Despite exhibiting different clinical profiles and selective neuronal loss, common features such as abnormal protein deposition, dysfunctional cellular transport, mitochondrial deficits, glutamate excitotoxicity and inflammation are observed in most, if not all, neurodegenerative disorders, suggesting converging pathways of neurodegeneration. We have generated comparative genome-wide gene expression data for Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, multiple sclerosis, Parkinson’s disease and schizophrenia using an extensive cohort of well characterised post-mortem CNS tissues. The analysis of whole genome expression patterns across these major disorders offers an outstanding opportunity not only to look into exclusive disease specific changes, but more importantly to uncover potential common molecular pathogenic mechanisms that could be targeted for therapeutic gain. Surprisingly, no dysregulated gene that passed our selection criteria was found in common across all 6 diseases using our primary method of analysis. However, 61 dysregulated genes were shared when comparing five and four diseases. Our analysis indicates firstly the involvement of common neuronal homeostatic, survival and synaptic plasticity pathways. Secondly, we report changes to immunoregulatory and immunomodulatory pathways in all diseases. Our secondary method of analysis confirmed significant up-regulation of a number of genes in diseases presenting degeneration and showed that somatostatin was downregulated in all 6 diseases. The latter is supportive of a general role for neuroinflammation in the pathogenesis and/or response to neurodegeneration. Unravelling the detailed nature of the molecular changes regulating inflammation in the CNS is key to the development of novel therapeutic approaches for these chronic conditions. A total of 113 cases were selected retrospectively on the basis of a confirmed clinical and neuropathological diagnosis and snap-frozen brain blocks were provided by various tissue banks within the BrainNet Europe network. Total RNA was extracted from dissected snap-frozen tissue (< 100 mg) by the individual laboratories according to a BNE optimised common protocol using the RNeasy(r) tissue lipid mini kit (Qiagen Ltd, Crawley, UK) according to the manufacturer's instructions, and was stored at -80C until further use. Gene expression analysis was performed on the RNA samples using the Illumina whole genome HumanRef8 v2 BeadChip (Illumina, London, UK). All the labelling and hybridisation of the samples was carried out in a single experiment by the Imperial College group to reduce the technical variability. RNA samples were prepared for array analysis using the Illumina TotalPrep(tm)-96 RNA Amplification Kit (Ambion/Applied Biosystems, Warrington, UK). Finally, the BeadChips we re scanned using the Illumina BeadArray Reader. The data was extracted using BeadStudio 3.2 (Illumina). Data normalisation and gene differential expression analyses were conducted using the Rosetta error models available in the Rosetta Resolver(r) system (Rosetta Biosoftware, Seattle, Wa, USA). Two samples presented very low signal expression most likely due to hybridization problems and did not pass the quality control test. They are not represented here. One of the 2 samples was a replicate, therefore there was loss of only 1 case bringing the grand total of cases used to 112 (total of samples of 118 including 6 replicates).
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