Understanding Of Related Diseases Research Articles

ScENT for Revealing Gene Clusters From Single-Cell RNA-Seq Data.

Recently, the fast development of single-cell RNA-seq (scRNA-seq) techniques has enabled high-resolution transcriptomic statistical analysis of individual cells in heterogeneous tissues, which can help researchers to explore the relationship between genes and human diseases. The emerging scRNA-seq data results in new analysis methods aiming to identify cell-level clustering and annotations. However, there are few methods developed to gain insights into the gene-level clusters with biological significance. This study proposes a new deep learning-based framework, scENT (single cell gENe clusTer), to identify significant gene clusters from single-cell RNA-seq data. We started with clustering the scRNA-seq data into multiple optimal groups, followed by a gene set enrichment analysis to identify classes of over-represented genes. Considering high-dimensional data with extensive zeros and dropout issues, scENT integrates perturbation in the learning process of clustering scRNA-seq data to improve its robustness and performance. Experimental results show that scENT outperformed other benchmarking methods on simulation data. To validate the biological insights of scENT, we applied it to the public experimental scRNA-seq data profiled from patients with Alzheimer's disease and brain metastasis. scENT successfully identified novel functional gene clusters and associated functions, facilitating the discovery of prospective mechanisms and the understanding of related diseases.

Amino Acid Solute Carrier Transporters in Inflammation and Autoimmunity.

The past decade exposed the importance of many homeostasis and metabolism related proteins in autoimmunity disease and inflammation. Solute carriers (SLCs) are a group of membrane channels that can transport amino acids, the building blocks of proteins, nutrients, and neurotransmitters. This review summarizes the role of SLCs amino acid transporters in inflammation and autoimmunity disease. In detail, the importance of Glutamate transporters SLC1A1, SLC1A2, and SLC1A3, mainly expressed in the brain where they help prevent glutamate excitotoxicity, is discussed in the context of central nervous system disorders such as multiple sclerosis. Similarly, the cationic amino acid transporter SLC7A1 (CAT1), which is an important arginine transporter for T cells, and SLC7A2 (CAT2), essential for innate immunity. SLC3 family proteins, which bind with light chains from the SLC7 family (SLC7A5, SLC7A7 and SLC7A11) to form heteromeric amino acid transporters, are also explored to describe their roles in T cells, NK cells, macrophages and tumor immunotherapies. Altogether, the link between SLC amino acid transporters with inflammation and autoimmunity may contribute to a better understanding of underlying mechanism of disease and provide novel potential therapeutic avenues. Significance Statement SIGNIFICANCE STATEMENT In this review, we summarize the link between SLC amino acid transporters and inflammation and immune responses, specially SLC1 family members and SLC7 members. Studying the link may contribute to a better understanding of related diseases and provide potential therapeutic targets and useful to the researchers who have interest in the involvement of amino acids in immunity.

Analyze the national directory of rare diseases, define the diagnostic role of the stomatologists

A rare disease, also referred to as an orphan disease, is defined as the disease with a low prevalence or that affects a small percentage of the population. It is a well model of human disease, which can facilitate the in-depth study and understanding of related diseases. Therefore, five Chinese governmental authorities, including the National Health Commission of the People's Republic of China, jointly issued the "First National Directory of Rare Diseases" (the First List) on May 11, 2018. The First List covers 121 rare indications. In the analysis of the directory, we found that among the 121 diseases, there are 51 (42.2%) with oral characterization. Oral manifestations mainly include craniofacial abnormalities, dentition (dental) abnormalities, oral soft tissue lesions, jaw bone lesions, salivary gland related diseases, etc., even some of them are the first, earliest and inevitable clinical manifestations of some patients with rare diseases. In order to strengthen the understanding of stomatological counterparts on the importance of the national directory of rare diseases and deeply understand the important and irreplaceable role of stomatologists in the diagnosis and treatment of rare diseases, the present review article is specifically written to introduce the oral characterization of the rare diseases listed in the catalogue, aiming at improving the diagnosis and treatment capabilities of these diseases by peers and benefiting the public.

Ball python nidovirus: a candidate etiologic agent for severe respiratory disease in Python regius.

ABSTRACTA severe, sometimes fatal respiratory disease has been observed in captive ball pythons (Python regius) since the late 1990s. In order to better understand this disease and its etiology, we collected case and control samples and performed pathological and diagnostic analyses. Electron micrographs revealed filamentous virus-like particles in lung epithelial cells of sick animals. Diagnostic testing for known pathogens did not identify an etiologic agent, so unbiased metagenomic sequencing was performed. Abundant nidovirus-like sequences were identified in cases and were used to assemble the genome of a previously unknown virus in the order Nidovirales. The nidoviruses, which were not previously known to infect nonavian reptiles, are a diverse order that includes important human and veterinary pathogens. The presence of the viral RNA was confirmed in all diseased animals (n = 8) but was not detected in healthy pythons or other snakes (n = 57). Viral RNA levels were generally highest in the lung and other respiratory tract tissues. The 33.5-kb viral genome is the largest RNA genome yet described and shares canonical characteristics with other nidovirus genomes, although several features distinguish this from related viruses. This virus, which we named ball python nidovirus (BPNV), will likely establish a new genus in Torovirinae subfamily. The identification of a novel nidovirus in reptiles contributes to our understanding of the biology and evolution of related viruses, and its association with lung disease in pythons is a promising step toward elucidating an etiology for this long-standing veterinary disease.

Abstract 052: Genome-wide Methylation Study of Body Mass Index (BMI) in African American Adults: Preliminary Data from the ARIC Study

Background and Objective: DNA methylation patterns are influenced by environmental factors, alter gene expression, and can point to genomic regions affected by behavioral and lifestyle factors, such as obesity. However, analytic strategies for high dimensional methylation data are still evolving. Here we present preliminary analyses examining cross-sectional associations between DNA methylation level and BMI in African-American adults enrolled in the Atherosclerosis Risk in Communities (ARIC) study. Methods: BMI was measured at the same study visit as the DNA sample used for analysis. We used the Illumina Infinium HumanMethylation450 BeadChip to measure average methylation levels (beta values) in bisulfite-converted peripheral blood DNA obtained from participants from the Jackson, MS and Forsyth County, NC field centers. After excluding outlier samples and CpG sites using quality control filters, a model adjusting BMI (continuous) for batch (plate) and a model additionally adjusting for a small set of potential confounders (age, sex, center, smoking) were tested, with average beta value as the dependent variable. Robust standard errors were used for statistical testing and Bonferroni-corrected p value for significance was p<1 x 10 -7 . Results: A total of 2,873 individuals and 473,788 CpG sites entered the analysis. In the minimally-adjusted analysis, there were over 300 regions distributed across all 22 autosomes with at least one significant association between BMI and CpG methylation. Adjusting for confounders sharply reduced the evidence for association to a total of approximately 20 regions on 11 autosomes. Conclusion: Use of the 450K methylation BeadChip in large epidemiologic cohorts has potential to help identify genes that are transcriptionally altered by common behavioral factors such as obesity, leading to improved understanding of related diseases. However, whereas genetic associations with disease are generally unconfounded by demographic and other covariate factors, methylation associations can be strongly affected by selection of covariates as well as other analytic choices.