A Case of Early-Onset Alzheimer's Disease with MAPT P301L Mutation and Literature Review

Background: Early-onset Alzheimer's disease is defined as Parkinson's disease that begins at an age of 65 or younger. Currently, among the reports on early-onset Alzheimer's disease related genes, mutations of APP, PSEN1 and PSEN2 genes are relatively common, However, the mutation of MAPT P301L causes early-onset Alzheimer's disease, which has not been reported so far. Case report: We have found a clinical case of a 30-year-old male who suddenly developed cognitive impairment and progressed rapidly within 2 years, leaving him unable to take care of himself. The patient underwent examinations of blood and cerebrospinal fluid routine, biochemistry and immunoassay, as well as imaging examinations of MRI, FDGPET and PIBPET. PIB-PET indicated diffuse heterogeneous radionuclivity in cerebral cortex, and positive PIB imaging was considered. Sequencing results suggested that there was a heterozygous mutation in the MAPT gene of the patient, which was located in Chr17-44087755, and c.902C>T. Conclusion: We speculated that EOAD of this patient may be related to the P301L mutation on MAPT.

Predicting Parkinson’s Disease Related Genes Based on PyFeat and Gradient Boosted Decision Tree (GBDT)

Identifying genes related to Parkinson's disease (PD) is an active and effective research topic in biomedical analysis, which plays a critical role in diagnosis and treatment. In recent years, many studies have proposed different techniques for predicting disease-related genes. However, a few of these techniques are designed or developed for PD gene prediction. Most of these PD techniques are developed to identify only protein genes and discard long non-coding (lncRNA) genes, which play an essential role in biological processes and the Transformation and development of diseases. This paper proposes a novel prediction system to identify protein and lncRNA genes related to PD that can aid in an early diagnosis. First, we preprocessed the genes into DNA FASTA sequences from the UCSC genome browser and removed the redundancies. Second, we extracted some significant features of DNA FASTA sequences using five numerical mapping techniques with Fourier transform and PyFeat method with Adaboost technique as feature selection. Finally, the features were fed to the gradient boosted decision tree (GBDT) to diagnose different tested cases. Seven performance metrics are used to evaluate the performance of the proposed system. The proposed system achieved an average accuracy (ACC) equals 78.1%, the area under the curve (AUC) equals 84.9%, the area under precision-recall (AUPR) equals 85.0%, F1-score equals 78.2%, Matthews correlation coefficient (MCC) equals 0.564, Sensitivity (SEN) equals 79.1%, and specificity (SPC) equals 77.1%. The experiments demonstrate promising results compared with other systems. The predicted top-rank protein and lncRNA genes are verified based on a literature review.

Landscape of human spinal cord cell type diversity at midgestation

Understanding spinal cord generation and assembly is essential to elucidate how motor behavior is controlled and how disorders arise. The cellular landscape of the human spinal cord remains, however, insufficiently explored. Here, we profiled the midgestation human spinal cord with single cell-resolution and discovered, even at this fetal stage, remarkable heterogeneity across and within cell types. Glia displayed diversity related to positional identity along the dorso-ventral and rostro-caudal axes, while astrocytes with specialized transcriptional programs mapped onto distinct histological domains. We discovered a surprisingly early diversification of alpha (α) and gamma (γ) motor neurons that control and modulate contraction of muscle fibers, which was suggestive of accelerated developmental timing in human spinal cord compared to rodents. Together with mapping of disease-related genes, this transcriptional profile of the developing human spinal cord opens new avenues for interrogating the cellular basis of motor control and related disorders in humans.

Sgt1 Regulates α-Synuclein Subcellular Localization and Expression of Parkinson’s Disease Related Genes, PINK1 and PARK9

The SGT1 protein is highly expressed in the mammalian brain, particularly in neurons of the hippocampus and cortex, and in Purkinje cells of the cerebellum. There are literature data indicating that the protein may be involved in pathogenesis of neurodegenerative disorders such as Parkinson’s disease (PD). In the present work we have found that SGT1 protected cells from the toxicity of rotenone, an agent that evokes behavioral and histopathological symptoms of PD. To gain more insight into the possible mechanism underlying the protective action of SGT1 we looked at α-synuclein subcellular distribution in HEK293 cells with an altered SGT1 level. By immunofluorescent staining we have found that in HEK293 cells overexpressing SGT1 α-synuclein was mainly localized in the cytoplasm while in control cells it was present in the nucleus. Accordingly, when SGT1 expression was silenced, α-synuclein was predominantly present in the nucleus. These results were then confirmed by subcellular fractionation and Western blot analysis. Moreover, we have found that altered level of SGT1 in HEK293 cells influenced the expression of PD related genes, PINK1 and PARK9. Altogether, our results point to SGT1 as an important factor that might be involved in the pathogenesis of Parkinson’s disease (PD).

First person – Xiuping Sun

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Xiuping Sun is first author on ‘A quantitative study of the Golgi retention of glycosyltransferases’, published in JCS. Xiuping conducted the research described in this article while a PhD candidate in Lu Lei's lab at School of Biological Sciences, Nanyang Technological University, Singapore. She is now a postdoc in the lab of Wang Jigang, Yang Qinhe at Shenzhen People's Hospital, Shenzhen, China investigating the roles of disease-related genes in neurodegenerative diseases.

The Wnt/β-catenin signaling pathway has a healing ability for periapical periodontitis

Various disease-related genes have recently been identified using single nucleotide polymorphisms (SNPs). This study identified disease-related genes by analyzing SNP using genomic DNA isolated from Japanese patients with periapical periodontitis. Results showed that the SNP in LRP5 demonstrated a significant genotypic association with periapical lesions (Fisher’s exact test, P < 0.05). We constructed an in vivo murine periapical periodontitis model to confirm the Wnt/β-catenin signaling pathway’s role in developing and healing periapical periodontitis. We observed that administration of the Wnt/β-catenin signaling pathway inhibitor enlarged the periapical lesion. Moreover, applying lithium chloride (LiCl) to root canals accelerated periapical periodontitis healing. Histological analysis demonstrated that the expression levels of Col1a1 and Runx2 increased in the LiCl application group compared to that in the control group. Furthermore, many CD45R-positive cells appeared in the periapical lesions in the LiCl application group. These results indicated that LiCl promoted the healing of periapical periodontitis by inducing bone formation and immune responses. Our findings suggest that the Wnt/β-catenin signaling pathway regulates the development of periapical periodontitis. We propose a bioactive next-generation root canal treatment agent for this dental lesion.

Transcriptome Analysis of gene in Mouse M-1 cells revealing the functional mechanism of Astragali radix extract

Background Astragali Radix (AR),the dried root of legumes, belongs to the Qi- invigorating herbs in traditional Chinese medicine and plays an important role in the treatment of many diseases. In order to understand the mechanism of action of AR extract, we used AR extract to treat M-1, mouse kidney cells, and used transcriptome sequencing technology to detect the genomic transcription level of the cells under the action of AR at different concentrations and times. Result The results showed that after a low concentration of AR treatments on the cells, the expression of genes related to cell growth and cellular immune response changed significantly, among which multiple genes are related to mitochondrial function, while high concentrations of AR affected the expression of histones and disease-related genes. It showed that the low concentration of AR extract can achieve the effect of invigorating Qi by regulating the function of mitochondria. In addition, several important genes and pathways were identified as potential targets of AR activation. Conclusion The research not only clarified the main molecular biological mechanism of AR invigorating Qi, but also provided experimental basis and cellular physiology reference for the further clinical application of AR.

Classification, diagnosis, and treatment of vascular malformations

Background: In the 1980s, vascular anomalies were divided into two major subgroups—vascular tumors and vascular malformations—based on the functional framework. This concept has been fundamental to the management of vascular anomalies and expanded and refined by the International Society for the Study of Vascular Anomalies. Vascular malformations are further sub-divided into several types; however, there are many cases with insufficient information about the disease.Current Concepts: Several instances have shown that the diagnosis of vascular malformations can be achieved after a careful evaluation of patient history and examination. However, recently developed imaging technology has been of great help in the diagnosis. Doppler ultrasonography, magnetic resonance imaging, computed tomography scan, and angiography are valuable tools for diagnostic and therapeutic planning. Advanced diagnostic and therapeutic technologies have also provided more accurate and safer diagnoses and appropriate treatment. Recently, an improved method of managing vascular malformations has emerged, based on a multidisciplinary approach, which is very useful for increasing the treatment efficacy. The development of gene research has enabled the investigation of disease-related genes and the development of new medications.Discussion and Conclusion: Accurate diagnosis of vascular malformations is one of the most crucial factors in determining treatment plan and prognosis, based on which it would be possible to achieve effective results through appropriate management and a multidisciplinary team approach.

Discovering Cerebral Ischemic Stroke Associated Genes Based on Network Representation Learning

Cerebral ischemic stroke (IS) is a complex disease caused by multiple factors including vascular risk factors, genetic factors, and environment factors, which accentuates the difficulty in discovering corresponding disease-related genes. Identifying the genes associated with IS is critical for understanding the biological mechanism of IS, which would be significantly beneficial to the diagnosis and clinical treatment of cerebral IS. However, existing methods to predict IS-related genes are mainly based on the hypothesis of guilt-by-association (GBA). These methods cannot capture the global structure information of the whole protein–protein interaction (PPI) network. Inspired by the success of network representation learning (NRL) in the field of network analysis, we apply NRL to the discovery of disease-related genes and launch the framework to identify the disease-related genes of cerebral IS. The utilized framework contains three main parts: capturing the topological information of the PPI network with NRL, denoising the gene feature with the participation of a stacked autoencoder (SAE), and optimizing a support vector machine (SVM) classifier to identify IS-related genes. Superior to the existing methods on IS-related gene prediction, our framework presents more accurate results. The case study also shows that the proposed method can identify IS-related genes.