Association Between COVID-19 and Neurological Diseases: Evidence from Large-Scale Mendelian Randomization Analysis and Single-Cell RNA Sequencing Analysis.

Observational studies have suggested that SARS-CoV-2 infection increases the risk of neurological diseases, but it remains unclear whether the association is causal. The present study aims to evaluate the causal relationships between SARS-CoV-2 infections and neurological diseases and analyzes the potential routes of SARS-CoV-2 entry at the cellular level. We performed Mendelian randomization (MR) analysis with CAUSE method to investigate causal relationship of SARS-CoV-2 infections with neurological diseases. Then, we conducted single-cell RNA sequencing (scRNA-seq) analysis to obtain evidence of potential neuroinvasion routes by measuring SARS-CoV-2 receptor expression in specific cell subtypes. Fast gene set enrichment analysis (fGSEA) was further performed to assess the pathogenesis of related diseases. The results showed that the COVID-19 is causally associated with manic (delta_elpd, - 0.1300, Z-score: - 2.4; P = 0.0082) and epilepsy (delta_elpd: - 2.20, Z-score: - 1.80; P = 0.038). However, no significant effects were observed for COVID-19 on other traits. Moreover, there are 23 cell subtypes identified through the scRNA-seq transcriptomics data of epilepsy, and SARS-CoV-2 receptor TTYH2 was found to be specifically expressed in oligodendrocyte and astrocyte cell subtypes. Furthermore, fGSEA analysis showed that the cell subtypes with receptor-specific expression was related to methylation of lysine 27 on histone H3 (H3K27ME3), neuronal system, aging brain, neurogenesis, and neuron projection. In summary, this study shows causal links between SARS-CoV-2 infections and neurological disorders such as epilepsy and manic, supported by MR and scRNA-seq analysis. These results should be considered in further studies and public health measures on COVID-19 and neurological diseases.

Peroxymonosulfate activation by walnut shell activated carbon supported nano zero-valent iron for the degradation of tetracycline: Performance, degradation pathway and mechanism.

In this study, activated carbon (WS-AC) was prepared from walnut shell. Nano-zero-valent iron (nZVI) was loaded on walnut shell activated carbon by liquid phase reduction method and used as catalyst (WS-AC/nZVI) to activate peroxymonosulfate (PMS) to efficiently degrade tetracycline (TC) in solution. The composite material with a mass ratio of WS-AC to nZVI of 1:1 has the highest catalytic performance for activating PMS to degrade TC. The results showed that under the conditions of TC concentration of 100 ppm, PMS dosage of 0.2 mM and WS-AC/nZVI dosage of 0.1 g/L, the removal efficiency of TC could reach 81%. Based on quenching experiments and electron spin resonance (EPR), it was verified that •OH, SO4•- and 1O2 bound on the catalyst surface were the main reactive oxygen species during the reaction. The intermediate products of TC were identified by liquid chromatography-mass spectrometry (HPLC-MS) and DFT calculation, and the possible degradation pathway of TC was proposed. The catalyst still maintained high removal efficiency of TC after four cycles of experiments, and the minimal iron loss on the surface of the catalyst indicated that it had good stability. The efficient and stable WS-AC/nZVI activated PMS showed great potential in the degradation of antibiotics.

Transcriptome comparative analysis of amygdala-hippocampus in depression: A rat model induced by chronic unpredictable mild stress (CUMS).

BACKGROUND: Depression is a common and complex mental disease, and its pathogenesis involves several brain regions. Abnormalities in the amygdala-hippocampal neural circuits have been shown to be involved in depression. However, the underlying molecular mechanisms remain unclear. METHODS: A rat model was used to determine the transcriptome changes in the amygdala-hippocampal neural network under chronic unpredictable mild stress (CUMS). Depression-related modules in this neural network were identified using weighted gene co-expression network analysis (WGCNA). Difference and enrichment analyses were used to determine differential gene expression in the two brain regions. RESULTS: The modules in the amygdala and hippocampus associated with depression-like behavior contained 363 and 225 genes, respectively. Forty-two differentially expressed genes were identified in the amygdala candidate module and 37 in the hippocampus. Enrichment analysis showed that candidate genes in the amygdala were associated with neuronal myelination and candidate genes in the hippocampus were associated with synaptic transmission. Finally, based on module hub gene statistics, differential gene expression, and protein-protein interaction networks, 11 central genes were found in the amygdala candidate module, and one central gene was found in the hippocampal module. LIMITATIONS: Our study was based on a rat CUMS model. Further evidence is needed to prove that our results are applicable to patients with depression. CONCLUSION: This study identified critical modules and central genes involved in the amygdala-hippocampal circuit in the context of depression, and may provide further understanding of the pathogenesis of depression and help identify potential targets for antidepressant therapy.

Genome-Wide Analysis for the Regulation of Gene Alternative Splicing by DNA Methylation Level in Glioma and its Prognostic Implications.

Glioma is a primary high malignant intracranial tumor with poorly understood molecular mechanisms. Previous studies found that both DNA methylation modification and gene alternative splicing (AS) play a key role in tumorigenesis of glioma, and there is an obvious regulatory relationship between them. However, to date, no comprehensive study has been performed to analyze the influence of DNA methylation level on gene AS in glioma on a genome-wide scale. Here, we performed this study by integrating DNA methylation, gene expression, AS, disease risk methylation at position, and clinical data from 537 low-grade glioma (LGG) and glioblastoma (GBM) individuals. We first conducted a differential analysis of AS events and DNA methylation positions between LGG and GBM subjects, respectively. Then, we evaluated the influence of differential methylation positions on differential AS events. Further, Fisher's exact test was used to verify our findings and identify potential key genes in glioma. Finally, we performed a series of analyses to investigate influence of these genes on the clinical prognosis of glioma. In total, we identified 130 glioma-related genes whose AS significantly affected by DNA methylation level. Eleven of them play an important role in glioma prognosis. In short, these results will help to better understand the pathogenesis of glioma.

The roles of immune system and autoimmunity in pulmonary arterial hypertension: A review.

Pulmonary arterial hypertension (PAH) is a chronic disease characterized by increased pulmonary artery pressure which if left untreated, can lead to poor quality of life and ultimately death. It is a group of conditions and includes idiopathic PAH, familial/hereditary PAH and associated PAH. The condition has been studied for many years and its association with the immune system and in particular autoimmunity has been investigated. The mechanisms for the pathobiology of PAH are unclear although research has highlighted the role of adaptive and innate immune systems in its development. Diagnostics and therapeutic approaches range from cytokine treatments to the use of immunomodulating drugs, although there is still scope for improvements in the field. This article discusses the mechanisms linked to PAH, its association with other conditions and recent therapeutic interventions.

Genome-wide Identification and Analysis of Splicing QTLs in Multiple Sclerosis by RNA-Seq Data.

Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions in the central nervous system. Recently, the dysregulation of alternative splicing (AS) in the brain has been found to significantly influence the progression of MS. Moreover, previous studies demonstrate that many MS-related variants in the genome act as the important regulation factors of AS events and contribute to the pathogenesis of MS. However, by far, no genome-wide research about the effect of genomic variants on AS events in MS has been reported. Here, we first implemented a strategy to obtain genomic variant genotype and AS isoform average percentage spliced-in values from RNA-seq data of 142 individuals (51 MS patients and 91 controls). Then, combing the two sets of data, we performed a cis-splicing quantitative trait loci (sQTLs) analysis to identify the cis-acting loci and the affected differential AS events in MS and further explored the characteristics of these cis-sQTLs. Finally, the weighted gene coexpression network and gene set enrichment analyses were used to investigate gene interaction pattern and functions of the affected AS events in MS. In total, we identified 5835 variants affecting 672 differential AS events. The cis-sQTLs tend to be distributed in proximity of the gene transcription initiation site, and the intronic variants of them are more capable of regulating AS events. The retained intron AS events are more susceptible to influence of genome variants, and their functions are involved in protein kinase and phosphorylation modification. In summary, these findings provide an insight into the mechanism of MS.

Effective recycling of Co and Sr from Co/Sr-bearing wastewater via an integrated Fe coagulation and hematite precipitation approach.

Flocculant overdose has been considered an inefficient technique for precipitating heavy metals from wastewater at low levels due to the high yield of hazardous waste sludge that should be treated properly before it can be disposed of safely in landfills. This problem was effectively solved in this study via a novel method that recycles sludge separately into high-purity hematite and heavy metal-bearing products. The wastewater, which contained 10.3 mg/L of Co and 4.8 mg/L of Sr, was coagulated by adding ferric salt to generate Co/Sr-bearing sludge. The sludge was dissolved in HNO3, followed by hydrothermal treatment with the addition of organic matter (e.g. methanol or isopropanol). Without the addition of organic matter, only 56.5% of total Fe was removed as irregular hematite particles, whilst Co/Sr remained unchanged in the acid. Over 99.5% of total Fe was eliminated as hematite nanoparticles with 97.7% Fe2O3 content, but more than 98% Co/Sr remained in the acid when methanol with a molar ratio (Mmethanol/MFe) of 5 was added. Nearly 100% Co was precipitated by adjusting the pH of the acid to 8 to generate Co hydroxide with 83.9% purity. Meanwhile, the residual Sr was further precipitated by adding Na2CO3 to generate SrCO3 with 96.8% purity. Isopropanol achieved total Fe removal similar to that of methanol. The optimal molar ratio (MIsopropanol/MFe) was 1, which corresponded to the removal of 98.7% total Fe. Methanol and isopropanol can react with NO3- in acid to reduce NO2- concentration and improve acid pH, promoting hydrolysis followed by the crystallisation of ferric Fe with hematite as the final product. This paper is the first report on an environment-friendly method for enriching Co/Sr without generating any waste.

Genome-Wide Identification and Analysis of the Methylation of lncRNAs and Prognostic Implications in the Glioma.

Glioma is characterized by rapid cell proliferation and extensive infiltration among brain tissues, but the molecular pathology has been still poorly understood. Previous studies found that DNA methylation modifications play a key role in contributing to the pathogenesis of glioma. On the other hand, long noncoding RNAs (lncRNAs) has been discovered to be associated with some key tumorigenic processes of glioma. Moreover, genomic methylation can influence expression and functions of lncRNAs, which contributes to the pathogenesis of many complex diseases. However, to date, no systematic study has been performed to detect the methylation of lncRNAs and its influences in glioma on a genome-wide scale. Here, we selected the methylation data, clinical information, expression of lncRNAs, and DNA methylation regulatory proteins of 537 glioma patients from TCGA and TANRIC databases. Then, we performed a differential analysis of lncRNA expression and methylated regions between low-grade glioma (LGG) and glioblastoma multiform (GBM) subjects, respectively. Next, we further identified and verified potential key lncRNAs contributing the pathogenesis of glioma involved in methylation modifications by an annotation and correlation analysis, respectively. In total, 18 such lncRNAs were identified, and 7 of them have been demonstrated to be functionally linked to the pathogenesis of glioma by previous studies. Finally, by the univariate Cox regression, LASSO regression, clinical correlation, and survival analysis, we found that all these 18 lncRNAs are high-risk factors for clinical prognosis of glioma. In summary, this study provided a strategy to explore the influence of lncRNA methylation on glioma, and our findings will be benefit to improve understanding of its pathogenesis.

Genome-wide identification and analysis of the eQTL lncRNAs in multiple sclerosis based on RNA-seq data.

The pathogenesis of multiple sclerosis (MS) is significantly regulated by long noncoding RNAs (lncRNAs), the expression of which is substantially influenced by a number of MS-associated risk single nucleotide polymorphisms (SNPs). It is thus hypothesized that the dysregulation of lncRNA induced by genomic variants may be one of the key molecular mechanisms for the pathology of MS. However, due to the lack of sufficient data on lncRNA expression and SNP genotypes of the same MS patients, such molecular mechanisms underlying the pathology of MS remain elusive. In this study, a bioinformatics strategy was applied to obtain lncRNA expression and SNP genotype data simultaneously from 142 samples (51 MS patients and 91 controls) based on RNA-seq data, and an expression quantitative trait loci (eQTL) analysis was conducted. In total, 2383 differentially expressed lncRNAs were identified as specifically expressing in brain-related tissues, and 517 of them were affected by SNPs. Then, the functional characterization, secondary structure changes and tissue and disease specificity of the cis-eQTL SNPs and lncRNA were assessed. The cis-eQTL SNPs were substantially and specifically enriched in neurological disease and intergenic region, and the secondary structure was altered in 17.6% of all lncRNAs in MS. Finally, the weighted gene coexpression network and gene set enrichment analyses were used to investigate how the influence of SNPs on lncRNAs contributed to the pathogenesis of MS. As a result, the regulation of lncRNAs by SNPs was found to mainly influence the antigen processing/presentation and mitogen-activated protein kinases (MAPK) signaling pathway in MS. These results revealed the effectiveness of the strategy proposed in this study and give insight into the mechanism (SNP-mediated modulation of lncRNAs) underlying the pathology of MS.

Integrating the Ribonucleic Acid Sequencing Data From Various Studies for Exploring the Multiple Sclerosis-Related Long Noncoding Ribonucleic Acids and Their Functions.

Multiple sclerosis (MS) is a chronic fatal central nervous system (CNS) disease involving in complex immunity dysfunction. Recently, long noncoding RNAs (lncRNAs) were discovered as the important regulatory factors for the pathogenesis of MS. However, these findings often cannot be repeated and confirmed by the subsequent studies. We considered that the small-scale samples or the heterogeneity among various tissues may result in the divergence of the results. Currently, RNA-seq has become a powerful approach to quantify the abundances of lncRNA transcripts. Therefore, we comprehensively collected the MS-related RNA-seq data from a variety of previous studies, and integrated these data using an expression-based meta-analysis to identify the differentially expressed lncRNA between MS patients and controls in whole samples and subgroups. Then, we performed the Jensen-Shannon (JS) divergence and cluster analysis to explore the heterogeneity and expression specificity among various tissues. Finally, we investigated the potential function of identified lncRNAs for MS using weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA), and 5,420 MS-related lncRNAs specifically expressed in the brain tissue were identified. The subgroup analysis found a small heterogeneity of the lncRNA expression profiles between brain and blood tissues. The results of WGCNA and GSEA showed that a potential important function of lncRNAs in MS may be involved in the regulation of ribonucleoproteins and tumor necrosis factor cytokines receptors. In summary, this study provided a strategy to explore disease-related lncRNAs on genome-wide scale, and our findings will be benefit to improve the understanding of MS pathogenesis.

Identification of Key Long Non-Coding RNAs in the Pathology of Alzheimer's Disease and their Functions Based on Genome-Wide Associations Study, Microarray, and RNA-seq Data.

The pathogenesis of Alzheimer's disease (AD) is identified to be significantly regulated by long non-coding RNA (lncRNA) based on in vivo and clinical experiments. Single nucleotide polymorphisms (SNPs) can strongly impact expression and function of lncRNA in AD, and previous genome-wide associations studies (GWAS) have discovered substantial amount of risk SNPs associated with AD. However, current studies omit the important information about SNPs when identifying potential AD-related lncRNAs. In addition to single discovery approach and small-scale samples in these studies, the number of lncRNAs discovered as keys in AD is limited. Here, multiple computational methods were integrated to discover novel and key lncRNA of the pathology of AD. First, large-scale GWAS data involved in three ethnicities were collected from two authoritative sources, and meta-analyses were conducted to find SNPs significantly associated with AD (tag SNPs). Second, these tag SNPs together with their linkage disequilibrium information were used to discover potential lncRNAs related to AD. Third, after validation by microarray probe re-annotation of 1,282 samples and RNA-seq data analysis of 117 samples, respectively, a total of five key lncRNAs of AD were identified. Finally, possible function of these lncRNAs was predicted by genome mapping, expression quantitative trait loci, differential co-expression, and gene set enrichment analysis. Based on function prediction, four of the five key lncRNAs were identified to affect the risk of AD by regulating corresponding pathogenic genes and pathways, which are involved in regulation of amyloid-ß peptide and the immune system. In summary, these findings can facilitate the discovery of potential disease-related lncRNAs and enhance understanding of the pathogenesis of AD.

Identification of novel immune-relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis.

AIMS: Alzheimer's disease (AD) is one of the leading causes of death in elderly people. Its pathogenesis is greatly associated with the abnormality of immune system. However, only a few immune-relevant AD drug target genes have been discovered up to now, and it is speculated that there are still many potential drug target genes of AD (at least immune-relevant genes) to be discovered. Thus, this study was designed to identify novel AD drug target genes and explore their biological properties. METHODS: A combinatorial approach was adopted for the first time to discover AD drug targets by collectively considering ontology inference and network analysis. Moreover, a novel strategy limiting the distance of reasoning and in turn reducing noise interference was further proposed to improve inference performance. Potential AD drug target genes were discovered by integrating information of multiple popular databases (TTD, DrugBank, PharmGKB, AlzGene, and BioGRID). Then, the enrichment analyses of the identified drug targets genes based on nine well-known pathway-related databases were conducted to explore the function of the identified potential drug target genes. RESULTS: Eighteen potential drug target genes were finally identified, and 13 of them had been reported to be closely associated with AD. Enrichment analyses of these identified drug target genes, based on nine pathway-related databases, revealed that the enriched terms were primarily focus on immune-relevant biological processes. Four of those identified drug target genes are involved in the classical complement pathway and process of antigen presenting. CONCLUSION: The well-reproducible results showed the good performance of the combinatorial approach, and the remaining five new targets could be a good starting point for our understanding of the pathogenesis and drug discovery of AD. Moreover, this study supported validity of the combinatorial approach integrating ontology inference with network analysis in the discovery of novel drug target for neurological diseases.

Genetic Variant rs755622 Regulates Expression of the Multiple Sclerosis Severity Modifier D-Dopachrome Tautomerase in a Sex-Specific Way.

Multiple sclerosis (MS) is a sex-specific autoimmune disease involving central nervous system. Previous studies determined that macrophage migration inhibitory factor (MIF) and its homologue D-dopachrome tautomerase (DDT) sex-specifically affect MS progression. Moreover, other studies reported that rs755622 polymorphism in promoter region of MIF gene is associated with risk of MS and affects the promoter activity to regulate MIF expression in a sex-specific way. Given that MIF and DDT share a part of promoter sequence, we surmise that rs755622 can also regulate DDT expression in a sex-specific way. However, this has not yet been studied. Here, we used five large-scale expression quantitative trait loci (eQTLs) and two RNA-seq datasets from brain and blood to assess the potential influence of rs755622 variant on expression of DDT in different genders by the linear regression and differential expression analysis. The results show that the minor allele frequency of rs755622 and expression of DDT are significantly increased in males for MS subjects and this minor allele variant can significantly upregulate DDT expression for males but not females, which suggests that the regulation of DDT expression level by rs755622 can affect MS progression in males. These findings further support and expand conclusions of previous studies and may help to better understand the mechanisms of MS.

Analyzing 74,248 Samples Confirms the Association Between CLU rs11136000 Polymorphism and Alzheimer's Disease in Caucasian But Not Chinese population.

Clusterin (CLU) is considered one of the most important roles for pathogenesis of Alzheimer's Disease (AD). The early genome-wide association studies (GWAS) identified the CLU rs11136000 polymorphism is significantly associated with AD in Caucasian. However, the subsequent studies are unable to replicate these findings in different populations. Although two independent meta-analyses show evidence to support significant association in Asian and Caucasian populations by integrating the data from 18 and 25 related GWAS studies, respectively, many of the following 18 studies also reported the inconsistent results. Moreover, there are six missed and a misclassified GWAS studies in the two meta-analyses. Therefore, we suspected that the small-scale and incompletion or heterogeneity of the samples maybe lead to different results of these studies. In this study, large-scale samples from 50 related GWAS studies (28,464 AD cases and 45,784 controls) were selected afresh from seven authoritative sources to reevaluate the effect of rs11136000 polymorphism to AD risk. Similarly, we identified that the minor allele variant of rs11136000 significantly decrease AD risk in Caucasian ethnicity using the allele, dominant and recessive model. Different from the results of the previous studies, however, the results showed a negligible or no association in Asian and Chinese populations. Collectively, our analysis suggests that, for Asian and Chinese populations, the variant of rs11136000 may be irrelevant to AD risk. We believe that these findings can help to improve the understanding of the AD's pathogenesis.

Meta-analysis of association between TCF7L2 polymorphism rs7903146 and type 2 diabetes mellitus.

BACKGROUND: Large scale association studies have found a significant association between type 2 diabetes mellitus (T2DM) and transcription factor 7-like 2 (TCF7L2) polymorphism rs7903146. However, the quality of data varies greatly, as the studies report inconsistent results in different populations. Hence, we perform this meta-analysis to give a more convincing result. METHODS: The articles, published from January 1st, 2000 to April 1st, 2017, were identified by searching in PubMed and Google Scholar. A total of 56628 participants (34232 cases and 22396 controls) were included in the meta-analysis. A total of 28 studies were divided into 4 subgroups: Caucasian (10 studies), East Asian (5 studies), South Asian (5 studies) and Others (8 studies). All the data analyses were analyzed by the R package meta. RESULTS: The significant association was observed by using the dominant model (OR = 1.41, CI = 1.36 - 1.47, p < 0.0001), recessive model (OR = 1.58, CI = 1.48 - 1.69, p < 0.0001), additive model(CT vs CC) (OR = 1.34, CI = 1.28-1.39, p < 0.0001), additive model(TT vs CC) (OR = 1.81, CI = 1.69-1.94, p < 0.0001)and allele model (OR = 1.35, CI = 1.31-1.39, p < 0.0001). CONCLUSION: The meta-analysis suggested that rs7903146 was significantly associated with T2DM in Caucasian, East Asian, South Asian and other ethnicities.

Analyzing large-scale samples confirms the association between the rs1051730 polymorphism and lung cancer susceptibility.

The early genome-wide association studies (GWAS) found a significant association between lung cancer and rs1051730 (15q25) polymorphism. However, the subsequent studies reported consistent and inconsistent results in different populations. Three meta-analysis studies were thus performed to reevaluate the association. But their results remain inconsistent. After that, some new GWAS studies reported conflicting results again. We think that the divergence of these results may be due to small-scale samples or heterogeneity among different populations. Therefore, we reevaluated the association by collecting more samples (N = 33,617 cases and 116,639 controls) from 31 studies, which incorporate 8 new studies and 23 previous studies used by one or more of the three meta-analysis studies. We observed a significant association between lung cancer and rs1051730 in pooled population by using allele (OR = 1.30, 95% CI = 1.27-1.34, P < 0.0001), dominant (OR = 1.41, 95% CI = 1.29-1.55, P < 0.0001), recessive (OR = 1.53, 95% CI = 1.42-1.65, P < 0.0001) and additive (OR = 1.75, 95% CI = 1.61-1.90, P < 0.0001) models. Through the subgroup analysis, we observed a significant heterogeneity only in East Asian population (P = 0.006, I(2) = 66.9%), and the association is significant in all subgroups (OR = 1.2976, 95% CI = 1.2622-1.3339 (European ancestry), OR = 1.5025, 95% CI = 1.2465-1.8110 (African), OR = 1.7818, 95% CI = 1.3915-2.2815 (East Asian), P < 0.0001). We believe that these results will contribute to understanding the genetic mechanism of lung cancer.

LncRNA2Target: a database for differentially expressed genes after lncRNA knockdown or overexpression.

Long non-coding RNAs (lncRNAs) have emerged as critical regulators of genes at epigenetic, transcriptional and post-transcriptional levels, yet what genes are regulated by a specific lncRNA remains to be characterized. To assess the effects of the lncRNA on gene expression, an increasing number of researchers profiled the genome-wide or individual gene expression level change after knocking down or overexpressing the lncRNA. Herein, we describe a curated database named LncRNA2Target, which stores lncRNA-to-target genes and is publicly accessible at http://www.lncrna2target.org. A gene was considered as a target of a lncRNA if it is differentially expressed after the lncRNA knockdown or overexpression. LncRNA2Target provides a web interface through which its users can search for the targets of a particular lncRNA or for the lncRNAs that target a particular gene. Both search types are performed either by browsing a provided catalog of lncRNA names or by inserting lncRNA/target gene IDs/names in a search box.