Abstract While adaptive immune responses have been studied extensively in SLE (systemic lupus erythematosus), there is limited and contradictory evidence regarding the contribution of natural killer ...(NK) cells to disease pathogenesis. There is even less evidence about the role of NK cells in the more severe phenotype with juvenile-onset (J)SLE. In this study, analysis of the phenotype and function of NK cells in a large cohort of JSLE patients demonstrated that total NK cells, as well as perforin and granzyme A expressing NK cell populations, were significantly diminished in JSLE patients compared to age- and sex-matched healthy controls. The reduction in NK cell frequency was associated with increased disease activity, and transcriptomic analysis of NK populations from active and low disease activity JSLE patients versus healthy controls confirmed that disease activity was the main driver of differential NK cell gene expression. Pathway analysis of differentially expressed genes revealed an upregulation of interferon-α responses and a downregulation of exocytosis in active disease compared to healthy controls. Further gene set enrichment analysis also demonstrated an overrepresentation of the apoptosis pathway in active disease. This points to increased propensity for apoptosis as a potential factor contributing to NK cell deficiency in JSLE.
After its first detection in 1996, the highly pathogenic avian influenza A(H5Nx) virus has spread extensively worldwide. HPAIv A(H5N1) was first detected in Indonesia in 2003 and has been endemic in ...poultry in this country ever since. However, Indonesia has limited information related to the phylodynamics of HPAIv A(H5N1) in poultry. The present study aimed to increase the understanding of the evolution and temporal dynamics of HPAIv H5N1 in Indonesian poultry between 2003 and 2016. To this end, HPAIv A(H5N1) hemagglutinin sequences of viruses collected from 2003 to 2016 were analyzed using Bayesian evolutionary analysis sampling trees. Results indicated that the common ancestor of Indonesian poultry HPAIv H5N1 arose approximately five years after the common ancestor worldwide of HPAI A(H5Nx). In addition, this study indicated that only two introductions of HPAIv A(H5N1) occurred, after which these viruses continued to evolve due to extensive spread among poultry. Furthermore, this study revealed the divergence of H5N1 clade 2.3.2.1c from H5N1 clade 2.3.2.1b. Both clades 2.3.2.1c and 2.3.2.1b share a common ancestor, clade 1, suggesting that clade 2.3.2.1 originated and diverged from China and other Asian countries. Since there was limited sequence and surveillance data for the HPAIv A(H5N1) from wild birds in Indonesia, the exact role of wild birds in the spread of HPAIv in Indonesia is currently unknown. The evolutionary dynamics of the Indonesian HPAIv A(H5N1) highlight the importance of continuing and improved genomic surveillance and adequate control measures in the different regions of both the poultry and wild birds. Spatial genomic surveillance is useful to take adequate control measures. Therefore, it will help to prevent the future evolution of HPAI A(H5N1) and pandemic threats.
Influenza viruses are by nature unstable with high levels of mutations. The sequential accumulation of mutations in the surface glycoproteins allows the virus to evade the neutralizing antibodies. ...The consideration of the tropics as the influenza reservoir where viral genetic and antigenic diversity are continually generated and reintroduced into temperate countries makes the study of influenza virus evolution in Indonesia essential. A total of 100 complete coding sequences (CDS) of Hemagglutinin (HA) and Neuraminidase (NA) genes of H3N2 virus were obtained from archived samples of Influenza-Like Illness (ILI) surveillance collected from 2008 to 2010. Our evolutionary and phylogenetic analyses provide insight into the dynamic changes of Indonesian H3N2 virus from 2008 to 2010. Obvious antigenic drift with typical 'ladder-like' phylogeny was observed with multiple lineages found in each year, suggesting co-circulation of H3N2 strains at different time periods. The mutational pattern of the Indonesian H3N2 virus was not geographically related as relatively low levels of mutations with similar pattern of relative genetic diversity were observed in various geographical origins. This study reaffirms that the existence of a particular lineage is most likely the result of adaptation or competitive exclusion among different host populations and combination of stochastic ecological factors, rather than its geographical origin alone.
There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to ...address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.
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•Limited autism-microbiome associations from stool metagenomics of n = 247 children•Romboutsia timonensis was the only taxa associated with autism diagnosis•Autistic traits such as restricted interests are associated with less-diverse diet•Less-diverse diet, in turn, is associated with lower microbiome alpha-diversity
Large autism stool metagenomics study finds limited direct autism associations, in contrast to strong relationships with dietary traits, stool consistency, and age, suggestive of a model whereby genetic and phenotypic measures of the autism spectrum promote a less-diverse diet that reduces microbiome diversity.
Abstract Background/Aims Juvenile idiopathic arthritis (JIA) is the most common autoimmune rheumatic disease in children with methotrexate (MTX) as the first line treatment. However, about 50% of JIA ...patients will not respond well to MTX yet still experience drug side effects. Early prediction to MTX treatment response would be beneficial for patients and families to avoid incurring unnecessary MTX side effects and ongoing uncontrolled inflammation: such validated tools or biomarkers are currently not available. Methods Transcriptional analysis was performed on peripheral blood mononuclear cells (PBMC) from pre-MTX-treated JIA patients (n = 97) of all ILAR JIA subtypes, excluding systemic JIA. RNAseq was performed on total PBMC and sorted immune cell populations: CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD14+ monocytes. Clinical data collected at the time of sampling (baseline) and at the follow-up time (between 3-12 months) were used to define outcomes, measured as change in active joint count (AJC), change in Physician VAS (PhysVAS), and change in cJADAS10. After batch normalisation with ComBat-seq, differential gene expression (DGE) analysis was performed using limma-voom with age, sex, ethnicity, and steroid status included as covariates. Log2 fold changes were utilised to rank genes to implement gene set enrichment analysis (GSEA) by fgsea. Results DGE analysis showed minimal significant differentially expressed (DE) genes that passed 5% false discovery rate (FDR). The greatest number of significant DE genes were observed in CD14+ monocytes, where baseline expression of 13 genes were significantly associated with change in PhysVAS. As alterations of gene expression for a heterogeneous disease such as JIA can be subtle and correlated between genes, GSEA was performed to investigate expression changes at pathway level. Using MSigDb Hallmark pathways, GSEA showed interferon-related and tumor-necrosis-factor pathways as significantly associated with MTX response in all cell types (5% FDR). However, the directionality (up/down regulation) differed between cell lineages, suggesting pathways divergence between T cell and non-T cell lineages. For example, in interferon gamma pathway, up-regulation associated with poor treatment response in T-cells and down-regulation in non-T cells. Preliminary analysis of the leading edge genes of the interferon gamma pathway in the non-T cell lineages showed that many of the genes are driven by interferon alpha, whilst within CD4+ and CD8+ T cells the majority of the leading edge genes are specific to interferon gamma. Conclusion Different directionality of pathways that might be relevant to JIA response to treatment with MTX is observed in different mononuclear cell lineages. This could potentially explain the difficulties of finding biomarkers which correlate with response to treatment from whole blood or PBMC. Shared genes across different interferon-related pathways also suggest that interaction between interferon pathways might be driving the different direction of interferon pathway expression in different cell lineages. Disclosure M. Kartawinata: None. W. Lin: None. B. Jebson: None. K. O'Brien: None. E. Ralph: None. R. Restuadi: None. G.T. Hall: None. S. Castellano: None. C. Wallace: None. L.R. Wedderburn: Grants/research support; LRW Declares in kind contributions to CLUSTER by AbbVie, GSK, UCB, Sobi and Pfizer inc and non renumerated collaborations with Lilly and Novartis.
Amyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten ...risk loci to date, including the TNIP1/GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this.
The Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data (N
= 20,806, N
= 59,804) with 'omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain (N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray N
= 942, protein N
= 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO).
SMR analyses implicated both TNIP1 and GPX3 (p < 1.15 × 10
), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1. In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10
, adjusted R
= 0.042, B
= 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all < 0.0001), which were rescued with gpx3 expression, with no phenotype identified with tnip1 KD or gpx3 overexpression.
These results support GPX3 as a lead ALS risk gene in this locus, with more data needed to confirm/reject a role for TNIP1. This has implications for understanding disease mechanisms (GPX3 acts in the same pathway as SOD1, a well-established ALS-associated gene) and identifying new therapeutic approaches. Few previous examples of in-depth investigations of risk loci in ALS exist and a similar approach could be applied to investigate future expected GWAS findings.
Although neurological manifestations associated with dengue viruses (DENV) infection have been reported, there is very limited information on the genetic characteristics of neurotropic DENV. Here we ...describe the isolation and complete genome analysis of DENV serotype 3 (DENV-3) from cerebrospinal fluid of an encephalitis paediatric patient in Jakarta, Indonesia. Next-generation sequencing was employed to deduce the complete genome of the neurotropic DENV-3 isolate. Based on complete genome analysis, two unique and nine uncommon amino acid changes in the protein coding region were observed in the virus. A phylogenetic tree and molecular clock analysis revealed that the neurotropic virus was a member of Sumatran-Javan clade of DENV-3 genotype I and shared a common ancestor with other isolates from Jakarta around 1998. This is the first report of neurotropic DENV-3 complete genome analysis, providing detailed information on the genetic characteristics of this virus.
Along with improvement of modern electronic games, necessity of an intelligent agent that easily build is needed. One of electronic games that need good intelligent agent is real-time tactics. In ...this game type, good action planning is necessary to provide best experience to the player.On this paper, we try to find out whether if Goal-Oriented Action Planning (GOAP) is robust enough to be used at tactical game. By using GOAP, tactic dynamism still can be provided withreasonable amount of runtime.
Major challenges in understanding the functional consequences of genetic risk factors for human disease are which tissues and cell types are affected and the limited availability of suitable tissue. ...The aim of this study was to evaluate tissue-specific genotype-epigenetic characteristics in DNA samples from both endometrium and blood collected from women at different stages of the menstrual cycle and relate results to genetic risk factors for reproductive traits and diseases.
We analysed DNA methylation (DNAm) data from endometrium and blood samples from 66 European women. Methylation profiles were compared between stages of the menstrual cycle, and changes in methylation overlaid with changes in transcription and genotypes. We observed large changes in methylation (27,262 DNAm probes) across the menstrual cycle in endometrium that were not observed in blood. Individual genotype data was tested for association with methylation at 443,016 and 443,101 DNAm probes in endometrium and blood respectively to identify methylation quantitative trait loci (mQTLs). A total of 4546 sentinel cis-mQTLs (P < 1.13 × 10
) and 434 sentinel trans-mQTLs (P < 2.29 × 10
) were detected in endometrium and 6615 sentinel cis-mQTLs (P < 1.13 × 10
) and 590 sentinel trans-mQTLs (P < 2.29 × 10
) were detected in blood. Following secondary analyses, conducted to test for overlap between mQTLs in the two tissues, we found that 62% of endometrial cis-mQTLs were also observed in blood and the genetic effects between tissues were highly correlated. A number of mQTL SNPs were associated with reproductive traits and diseases, including one mQTL located in a known risk region for endometriosis (near GREB1).
We report novel findings characterising genetic regulation of methylation in endometrium and the association of endometrial mQTLs with endometriosis risk and other reproductive traits and diseases. The high correlation of genetic effects between tissues highlights the potential to exploit the power of large mQTL datasets in endometrial research and identify target genes for functional studies. However, tissue-specific methylation profiles and genetic effects also highlight the importance of also using disease-relevant tissues when investigating molecular mechanisms of disease risk.
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