Schizophrenia is a common psychiatric disorder with high heritability and complex genetic architecture. Genome-wide association studies (GWAS) have identified several significant loci associated with ...schizophrenia. However, the explained heritability is still low. Growing evidence has shown schizophrenia is attributable to multiple genes with moderate effects. In-depth mining and integration of GWAS data is urgently expected to uncover disease-related gene combination patterns. Network-based analysis is a promising strategy to better interpret GWAS to identify disease-related network modules. We performed a network-based analysis on three independent schizophrenia GWASs by using a refined analysis framework, which included a more accurate gene P-value calculation, dynamic network module searching algorithm and detailed functional analysis for the obtained modules genes. The result generated 79 modules including 238 genes, which form a highly connected subnetwork with more statistical significance than expected by chance. The result validated several reported disease genes, such as MAD1L1, MCC, SDCCAG8, VAT1L, MAPK14, MYH9 and FXYD6, and also obtained several novel candidate genes and gene-gene interactions. Pathway enrichment analysis of the module genes suggested they were enriched in several neural and immune system related pathways/GO terms, such as neurotrophin signaling pathway, synaptosome, regulation of protein ubiquitination, and antigen processing and presentation. Further crosstalk analysis revealed these pathways/GO terms were cooperated with each other, and identified several important genes, which might play vital roles to connect these functions. Our network-based analysis of schizophrenia GWASs will facilitate the understanding of genetic mechanisms of schizophrenia.
Methionine has been proven to inhibit addictive behaviors of cocaine dependence. This study aimed to identify the potential mechanisms of MET relating to its inhibitory effects on cocaine induced ...cellular and behavioral changes.
MRNA and miRNA high-throughput sequencing of the prefrontal cortex in a mouse model of cocaine conditioned place preference (CPP) combined with L-methionine was performed. Differentially expressed miRNAs (DE-miRNAs) and differentially expressed genes (DEGs) regulated by cocaine and inhibited by L-methionine were identified. DEGs were mapped to STRING database to construct a protein-protein interaction (PPI) network. Then, the identified DEGs were subjected to the DAVID webserver for functional annotation. Finally, miRNA-mRNA regulatory network and miRNA-mRNA-TF regulatory networks were established to screen key DE-miRNAs and coregulation network in Cytoscape.
Sequencing data analysis showed that L-methionine reversely regulated genes and miRNAs affected by cocaine. Pathways associated with drug addiction only enriched in CS-down with MC-up genes targeted by DE-miRNAs including GABAergic synapse, Glutamatergic synapse, Circadian entrainment, Axon guidance and Calcium signaling pathway. Drug addiction associated network was formed of 22 DEGs including calcium channel (Cacna1c, Cacna1e, Cacna1g and Cacng8), ephrin receptor genes (Ephb6 and Epha8) and ryanodine receptor genes (Ryr1 and Ryr2). Calcium channel gene network were identified as a core gene network modulated by L-methionine in response to cocaine dependence. Moreover, it was predicted that Grin1 and Fosb presented in TF-miRNA-mRNA coregulation network with a high degree of interaction as hub genes and interacted calcium channels.
These identified key genes, miRNA and coregulation network demonstrated the efficacy of L-methionine in counteracting the effects of cocaine CPP. To a certain degree, it may provide some hints to better understand the underlying mechanism on L-methionine in response to cocaine abuse.
Understanding why some people establish and maintain effective control of HIV-1 and others do not is a priority in the effort to develop new treatments for HIV/AIDS. Using a whole-genome association ...strategy, we identified polymorphisms that explain nearly 15% of the variation among individuals in viral load during the asymptomatic set-point period of infection. One of these is found within an endogenous retroviral element and is associated with major histocompatibility allele human leukocyte antigen (HLA)-B*5701, whereas a second is located near the HLA-C gene. An additional analysis of the time to HIV disease progression implicated two genes, one of which encodes an RNA polymerase I subunit. These findings emphasize the importance of studying human genetic variation as a guide to combating infectious agents.
Background
Methionine has been proven to inhibit addictive behaviors of cocaine dependence. However, the mechanism of methionine response to cocaine CPP is unknown. Recent evidence highlights piRNAs ...to regulate genes via a miRNA‐like mechanism. Here, next‐generation sequencing is used to study mechanism on methionine response to drug‐induced behaviors though piRNA.
Methods
l‐methionine treatment cocaine CPP animal model was used to do non‐coding RNA sequencing. There were four groups to sequence: saline+saline (SS), MET+saline (MS), MET+cocaine (MC), and cocaine+saline. Combining mRNA sequencing data, the network and regulation of piRNA were analyzed with their corresponding mRNA and miRNA.
Results
Analysis of the piRNAome reveals that piRNAs inversely regulated their target mRNA genes. KEGG analysis of DE‐piRNA target mRNA genes were enriched in Morphine addiction, GABAergic synapse and Cholinergic synapse pathway. Furthermore, four significantly differential expressed genes Cacna2d3, Epha6, Nedd4l, and Vav2 were identified and regulated by piRNAs in the process of l‐methionine inhibits cocaine CPP. Thereinto, Vav2 was regulated by multiple DE piRNAs by sharing the common sequence: GTCTCTCCAGCCACCTT. Meanwhile, it was found that piRNA positively regulates miRNA and three genes Bcl3, Il20ra, and Insrr were identified and regulated by piRNA through miRNA.
Conclusion
The results showed that piRNA negatively regulated target mRNA genes and positively regulated target miRNA genes. Genes located in substance dependence, signal transduction and also nervous functions pathways were identified. When taken together, these data may explain the roles of l‐methionine in counteracting the effects of cocaine CPP via piRNAs.
our results showed piRNA negatively regulated target mRNA genes and positively regulated target miRNA genes. Genes located in substance dependence, Signal transduction and also nervous functions pathways were down‐regulated: Cacna2d3, Epha6, Nedd4l and Vav2. Thereinto, Vav2 was targeted by multiple piRNAs by sharing the common target sequence: GTCTCTCCAGCCACCTT. Taken together, these data may explain the roles of L‐methionine in counteracting the effects of cocaine CPP via piRNAs.
Primary Sjögren's syndrome (pSS) is a complex autoimmune disorder. So far, genetic research in pSS has lagged far behind and the underlying biological mechanism is unclear. Further exploring existing ...genome-wide association study (GWAS) data is urgently expected to uncover disease-related gene combination patterns. Herein, we conducted a network-based analysis by integrating pSS GWAS in Han Chinese with a protein-protein interactions network to identify pSS candidate genes. After module detection and evaluation, 8 dense modules covering 40 genes were obtained for further functional annotation. Additional 31 MHC genes with significant gene-level P-values (sigMHC-gene) were also remained. The combined module genes and sigMHC-genes, a total of 71 genes, were denoted as pSS candidate genes. Of these pSS candidates, 14 genes had been reported to be associated with any of pSS, RA, and SLE, including STAT4, GTF2I, HLA-DPB1, HLA-DRB1, PTTG1, HLA-DQB1, MBL2, TAP2, CFLAR, NFKBIE, HLA-DRA, APOM, HLA-DQA2 and NOTCH4. This is the first report of the network-assisted analysis for pSS GWAS data to explore combined gene patterns associated with pSS. Our study suggests that network-assisted analysis is a useful approach to gaining further insights into the biology of associated genes and providing important clues for future research into pSS etiology.
Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) comorbidity occurs through exposure to trauma with genetic susceptibility. Neuropeptide-Y (NPY) and dopamine are ...neurotransmitters associated with anxiety and stress-related psychiatry through receptors. We attempted to explore the genetic association between two neurotransmitter receptor systems and the PTSD-MDD comorbidity.
Four groups were identified using latent profile analysis (LPA) to examine the patterns of PTSD and MDD comorbidity among survivors exposed to earthquake-related trauma: low symptoms, predominantly depression, predominantly PTSD, and PTSD-MDD comorbidity.
(rs4425326),
(rs11724320),
(rs1079597), and
(rs6280) were genotyped from 1,140 Chinese participants exposed to earthquake-related trauma. Main, gene-environment interaction (G × E), and gene-gene interaction (G × G) effects for low symptoms, predominantly depression, and predominantly PTSD were tested using a multinomial logistic model with PTSD-MDD comorbidity as a reference.
The results demonstrated that compared to PTSD-MDD comorbidity, epistasis (G × G)
-
(rs4425326 × rs1079597) affects low symptoms (
= -0.66,
= 0.52 95% CI: 0.32-0.84,
= 0.008,
= 0.008) and predominantly PTSD (
= -0.56,
= 0.57 95% CI: 0.34-0.97,
= 0.037,
= 0.039), while
-
(rs4425326 × rs6280) impacts low symptoms (
= 0.82,
= 2.27 95% CI: 1.26-4.10,
= 0.006,
= 0.005) and predominantly depression (
= 1.08,
= 2.95 95% CI: 1.55-5.62,
= 0.001,
= 0.001). The two G × G effects are independent.
NPY and dopamine receptor genes are related to the genetic etiology of PTSD-MDD comorbidity, whose specific mechanisms can be studied at multiple levels.
Primary Sjögren's syndrome (pSS) is a systematic autoimmune disease with evidence of genetic predisposition. The IKZF1 (IKAROS family zinc finger 1 (Ikaros)) gene is located at 7p12.2, encodes a ...transcription factor related to chromatin remodeling, regulates lymphocyte differentiation, and has been reported to be associated with some autoimmune diseases. However, there have been no reports of an association between IKZF1 and pSS. To investigate the possibility of an association between the IKZF1 locus and pSS, we selected two single nucleotide polymorphisms (SNPs) in the IKZF1 locus, rs4917129 and rs4917014, based on a detailed analysis of genome-wide association study (GWAS) data and performed genotyping in 665 Han Chinese pSS patients and 863 healthy controls. The results of an association test showed significant association signals (rs4917129: P-value = 5.5e-4, OR (odds ratio) = 0.72, 95% CI (confidence interval) = 0.60-0.87; rs4917014: P-value = 1.2e-3, OR = 0.76, 95% CI = 0.64-0.89). A meta-analysis that combined the above results with data from previous GWAS, further confirmed these associations (rs4917129: Pmeta = 4.24e-8, ORmeta = 0.70, 95% CI = 0.61-0.79; rs4917014: Pmeta = 6.0e-8, ORmeta = 0.72, 95% CI = 0.64-0.81). A bioinformatics analysis indicated that both SNPs were located in a putative enhancer area in immune-related cell lines and tissues. A protein-protein interaction analysis found that IKZF1, together with GTF2I (an SS susceptibility gene newly identified through GWAS), could interact with histone deacetylase family proteins. In summary, this is the first study to report an association between IKZF1 and SS in Han Chinese.
Post-traumatic stress disorder (PTSD) is a trauma- and stress-related psychiatric syndrome that occurs after exposure to extraordinary stressors. The neurotransmitter dopamine (DA) plays important ...roles in neurobiological processes like reward and stress, and a link between PTSD and the dopaminergic system has been reported. Thus, the investigation of an association between PTSD and gene-gene interaction (epistasis) within dopaminergic genes could uncover the genetic basis of dopamine-related PTSD symptomatology and contribute to precision medicine.
We genotyped seven single nucleotide polymorphisms (SNPs) of three dopaminergic genes
(rs1800497 and rs1801028),
(rs6269, rs4633, rs4818 and rs4680) and
(rs1611115), in a Chinese predominantly adult cohort that had been exposed to an earthquake (156 PTSD cases and 978 controls).
Statistical genetics analysis identified a
-
interaction (rs1800497 × rs6269), which is associated with PTSD diagnosis (
= 0.0008055 and
= 0.0169155). Single-variant and haplotype-based subset analyses showed that rs1800497 modulates the association directions of both the rs6269 G allele and the rs6269-rs4633-rs4818-rs4680 haplotype G-C-G-G. The interaction (rs1800497 × rs6269) was replicated in a Chinese young female cohort (32 cases and 581 controls,
= 0.01329).
Rs1800497 is related to the DA receptor D2 density and rs6269-rs4633-rs4818-rs4680 haplotypes affect the catechol O-methyltransferase level and enzyme activity. Thus, the interaction was inferred to be at protein-protein and DA activity level. The genotype combinations of the two SNPs indicate a potential origin of DA homeostasis abnormalities in PTSD development.
Safety is the most important aspect of railway transportation. To ensure the safety of high-speed trains, various train components are equipped with sensor devices for real-time monitoring. Sensor ...monitoring data can be used for fast intelligent diagnosis and accurate positioning of train faults. However, existing train fault diagnosis technology based on cloud computing has disadvantages of long processing times and high consumption of computing resources, which conflict with the real-time response requirements of fault diagnosis. Aiming at the problems of train fault diagnosis in the cloud environment, this paper proposes a train fault diagnosis model based on edge and cloud collaboration. The model first utilizes a SAES-DNN (stacked auto-encoders deep neural network) fault recognition method, which can integrate automatic feature extraction and type recognition and complete fault classification over deep hidden features in high-dimensional data, so as to quickly locate faults. Next, to adapt to the characteristics of edge computing, the model applies a SAES-DNN model trained in the cloud and deployed in the edge via the transfer learning strategy and carries out real-time fault diagnosis on the vehicle sensor monitoring data. Using a motor fault as an example, when compared with a similar intelligent learning model, the proposed intelligent fault diagnosis model can greatly improve diagnosis accuracy and significantly reduce training time. Through the transfer learning approach, adaptability of the fault diagnosis algorithm for personalized applications and real-time performance of the fault diagnosis is enhanced. This paper also proposes a visual analysis method of train fault data based on knowledge graphs, which can effectively analyze fault causes and fault correlation.
Background:
Post-traumatic stress disorder (PTSD) and depression are common mental disorders in individuals experiencing traumatic events. To date, few studies have studied the relationship between ...genetic basis and phenotypic heterogeneity of traumatized individuals. The present study examined the effects of four FKBP5 SNPs (rs1360780, rs3800373, rs9296158, and rs9470080) in four postdisaster groups (low symptom, predominantly depressive, predominantly PTSD, and combined PTSD-depression symptom groups) as identified by latent profile analysis.
Methods:
A total of 1,140 adults who experienced the 2008 Wenchuan earthquake participated in our study. Earthquake-related trauma, PTSD, and depressive symptoms were measured using standard psychometric instruments. The four FKBP5 SNPs were genotyped using a custom-by-design 2 × 48-Plex SNP scan™ Kit.
Results:
After adjusting for covariates, the main and gene–environment interaction effects of rs9470080 were all significant when the combined PTSD-depression group was compared with the low symptoms, predominantly depression and predominantly PTSD groups. rs9470080 TT genotype carriers had a higher risk of developing high co-occurring PTSD and depression symptoms than the C allele carriers. However, when trauma exposure was severe, the TT genotype carriers and C allele carriers did not differ in the risk of developing high co-occurring PTSD and depressive symptoms. The other three SNPs demonstrated no significant effects. Moreover, the rs3800373-rs9296158-rs1360780-rs9470080 haplotype A-G-C-T was found significantly associated with combined PTSD-depression symptoms.
Conclusion:
Our findings support the genetic basis of phenotypic heterogeneity in people exposed to trauma. Furthermore, the results reveal the possibility that the variants of FKBP5 gene may be associated with depression-PTSD comorbidity.
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