Novel linkage disequilibrium clustering algorithm identifies new lupus genes on meta-analysis of GWAS datasets

Type I interferon associated epistasis may contribute to early disease-onset and high disease activity in juvenile-onset lupus

Pathologic type I interferon (T1IFN) expression is a key feature in systemic lupus erythematosus (SLE) that associates with disease activity. When compared to adult-onset disease, juvenile-onset (j)SLE is characterized by increased disease activity and damage, which likely relates to increased genetic burden. To identify T1IFN-associated gene polymorphisms (TLR7, IRAK1, miR-3142/miR-146a, IRF5, IRF7, IFIH1, IRF8, TYK2, STAT4), identify long-range linkage disequilibrium and gene:gene interrelations, 319 jSLE patients were genotyped using panel sequencing. Coupling phenotypic quantitative trait loci (QTL) analysis identified 10 jSLE QTL that associated with young age at onset (<12 years; IRAK1 [rs1059702], TLR7 [rs3853839], IFIH1 [rs11891191, rs1990760, rs3747517], STAT4 [rs3021866], TYK2 [rs280501], IRF8 [rs1568391, rs6638]), global disease activity (SLEDAI-2 K >10; IFIH1 [rs1990760], STAT4 [rs3021866], IRF8 [rs903202, rs1568391, rs6638]), and mucocutaneous involvement (TLR7 [rs3853839], IFIH1 [rs11891191, rs1990760]). This study suggests T1IFN-associated polymorphisms and gene:gene interrelations in jSLE. Genotyping of jSLE patients may allow for individualized treatment and care.

Interaction between Long Noncoding RNAs and Syncytin-1/Syncytin-2 Genes and Transcripts: How Noncoding RNAs May Affect Pregnancy in Patients with Systemic Lupus Erythematosus

BACKGROUND

Patients with systemic lupus erythematosus (SLE) often suffer from obstetric complications not necessarily associated with the antiphospholipid syndrome. These events may potentially result from the reduced placental synthesis of the fusogenic proteins syncytin-1 and syncytin-2, observed in women with pregnancy-related disorders. SLE patients have an aberrant noncoding (nc)RNA signature that may in turn dysregulate the expression of syncytin-1 and syncytin-2 during placentation. The aim of this research is to computationally evaluate and characterize the interaction between syncytin-1 and syncytin-2 genes and human ncRNAs and to discuss the potential implications for SLE pregnancy adverse outcomes.

METHODS

The FASTA sequences of the syncytin-1 and syncytin-2 genes were used as inputs to the Ensembl.org library to find any alignments with human ncRNA genes and their transcripts, which were characterized for their tissue expression, regulatory activity on adjacent genes, biological pathways, and potential association with human disease.

RESULTS

BLASTN analysis revealed a total of 100 hits with human long ncRNAs (lncRNAs) for the syncytin-1 and syncytin-2 genes, with median alignment scores of 151 and 66.7, respectively. Only lncRNAs TP53TG1, TTTY14, and ENSG00000273328 were reported to be expressed in placental tissue. Dysregulated expression of lncRNAs TP53TG1, LINC01239, and LINC01320 found in this analysis has previously been described in SLE patients as well as in women with a high-risk pregnancy. In addition, some of the genes adjacent to lncRNAs aligned with syncytin-1 or syncytin-2 in a regulatory region might increase the risk of pregnancy complications or SLE.

CONCLUSIONS

This is the first computational study showing alignments between syncytin-1 and syncytin-2 genes and human lncRNAs. Whether this mechanism affects syncytiotrophoblast morphogenesis in SLE females is unknown and requires further investigation.

E-Commerce Precision Marketing and Consumer Behavior Models Based on IoT Clustering Algorithm

This article aims to study e-commerce precision models and consumer behavior models based on clustering algorithms, and at the same time conduct detailed research on the Gaussian mixture distribution algorithm, consumer behavior and model construction, and precision marketing strategies in the clustering algorithm. First, a lot of analysis and demonstration of precision marketing strategies and the construction of consumer behavior models are carried out, and then the clustering algorithm-based electronic some experiments were carried out on the application of commercial precision marketing methods and consumer behavior models. The experimental results show that the precision marketing method using the clustering algorithm is more in line with the development of modern e-commerce. The application of the algorithm in the precision marketing methods of enterprises and consumer behavior models has promoted the vigorous development of enterprises, making the sales volume of enterprises reach 9.8 %.

Expression of DDX11 and DNM1L at the 12p11 Locus Modulates Systemic Lupus Erythematosus Susceptibility

Objectives: This study employed genetic and functional analyses using OASIS meta-analysis of multiple existing GWAS and gene-expression datasets to identify novel SLE genes. Methods: Four hundred and ten genes were mapped using SNIPPER to 30 SLE GWAS loci and investigated for expression in three SLE GEO-datasets and the Cordoba GSE50395-dataset. Blood eQTL for significant SNPs in SLE loci and STRING for functional pathways of differentially expressed genes were used. Confirmatory qPCR on SLE monocytes was performed. The entire 12p11 locus was investigated for genetic association using two additional GWAS. Expression of 150 genes at this locus was assessed. Based on this significance, qPCRs for DNM1L and KRAS were performed. Results: Fifty genes were differentially expressed in at least two SLE GEO-datasets, with all probes directionally aligned. DDX11, an RNA helicase involved in genome stability, was downregulated in both GEO and Cordoba datasets. The most significant SNP, rs3741869 in OASIS locus 12p11.21, containing DDX11, was a cis-eQTL regulating DDX11 expression. DDX11 was found repressed. The entire 12p11 locus showed three association peaks. Gene expression in GEO datasets identified DNM1L and KRAS, besides DDX11. Confirmatory qPCR validated DNM1L as an SLE susceptibility gene. DDX11, DNM1L and KRAS interact with each other and multiple known SLE genes including STAT1/STAT4 and major components of IFN-dependent gene expression, and are responsible for signal transduction of cytokines, hormones, and growth-factors, deregulation of which is involved in SLE-development. Conclusion: A genomic convergence approach with OASIS analysis of multiple GWAS and expression datasets identified DDX11 and DNM1L as novel SLE-genes, the expression of which is altered in monocytes from SLE patients. This study lays the foundation for understanding the pathogenic involvement of DDX11 and DNM1L in SLE by identifying them using a systems-biology approach, while the 12p11 locus harboring these genes was previously missed by four independent GWAS.

mRNA expression analysis confirms CD44 splicing impairment in systemic lupus erythematosus patients

BACKGROUND

Systemic Lupus Erythematosus (SLE) is a complex chronic autoimmune disease characterized by several immunological alterations. T cells have a peculiar role in SLE pathogenesis, moving from the bloodstream to the peripheral tissues, causing organ damage. This process is possible for their increased adherence and migration capacity mediated by adhesion molecules, such as CD44. Ten different variant isoforms of this molecule have been described, and two of them, CD44v3 and CD44v6 have been found to be increased on SLE T cells compared to healthy controls, being proposed as biomarkers of disease and disease activity. The process of alternative splicing of CD44 transcripts is not fully understood. We investigated the mRNA expression of CD44v3 and CD44v6 and also analyzed possible CD44 splicing regulators (ESRP1 molecule and rs9666607 CD44 polymorphism) in a cohort of SLE patients compared to healthy controls.

METHODS

This study involved 18 SLE patients and 18 healthy controls. Total RNA and DNA were extracted by peripheral blood mononuclear cells. The expression study was conducted by quantitative RT-polymerase chain reaction, using SYBR Green protocol. Genotyping of rs9666607 SNP was performed by direct sequencing.

RESULTS

CD44v6 mRNA expression was higher in SLE patients compared to healthy controls (p = 0.028). CD44v3/v6 mRNA ratio in healthy controls was strongly unbalanced towards isoform v3 compared to SLE patients (p = 0.002) and decreased progressively from healthy controls to the SLE patients in remission and those with active disease (p = 0.015). The expression levels of CD44v3 and CD44v6 mRNA correlated with the disease duration (p = 0.038, Pearson r = 0.493 and p = 0.038, Pearson r = 0.495, respectively). Splicing regulator ESRP1 expression positively correlated with CD44v6 expression in healthy controls (p = 0.02, Pearson r = 0.532) but not in SLE patients. The variant A allele of rs9666607 of CD44 was associated with higher level of global CD44 mRNA (p = 0.04) but not with the variant isoforms.

CONCLUSIONS

In SLE patients, the increase in CD44v6 protein correlates with a higher transcript level of this isoform, confirming an impairment of CD44 splicing in the disease, whose regulatory mechanisms require further investigation.

Variants of genes encoding TNF receptors and ligands and proteins regulating TNF activation in familial multiple sclerosis

INTRODUCTION

Numerous genetic variants have been associated with susceptibility to multiple sclerosis (MS). Variants located in genes involved in specific pathways, such as those affecting TNF-α, can contribute to the risk of MS. The purpose of this study was to determine whether variants of these genes are associated with greater risk of MS.

METHODS

We used whole-exome sequencing to study genes coding for TNF-α receptors and ligands, and proteins promoting TNF-α expression in 116 individuals from 19 families including at least two MS patients. We compared patients with MS, patients with other autoimmune diseases, and healthy individuals.

RESULTS

Greater polymorphism was observed in several genes in families with familial MS compared to the general population; this may reflect greater susceptibility to autoimmune diseases. Pedigree analysis also revealed that LT-α variants rs1041981 and rs2229094 and LT-β variant rs4647197 were associated with MS and that LT-β variant rs4647183 was associated with other autoimmune diseases. The association between autoimmune disease and TNFAIP2 variant rs1132339 is particularly noteworthy, as is the fact that TNFAIP6 variant rs1046668 appears to follow a recessive inheritance pattern.

CONCLUSIONS

Our findings support the idea that the risk of familial MS is associated with variants of signaling pathways, including those involving TNF-α.

The TRPC6 intronic polymorphism, associated with the risk of neurological disorders in systemic lupus erythematous, influences immune cell function

Patients with systemic lupus erythematosus (SLE) carrying a TT genotype for the rs7925662 single nucleotide polymorphism (SNP) in the transient receptor potential canonical channel 6 (TRPC6) gene are more likely to develop neuropsychiatric manifestations (NPSLE). We functionally characterised the effects of TRPC6 on peripheral blood mononuclear cells from 18 patients with SLE and 8 healthy controls with a known genotype. TRPC6 influenced calcium currents, apoptosis rates and cytokine secretion in a disease- and genotype-dependent manner. Cells from TT patients with NPSLE were more dependent on TRPC6 for the generation of calcium currents.

Genomic convergence of locus-based GWAS meta-analysis identifies AXIN1 as a novel Parkinson's gene

Parkinson's disease (PD) is a common, disabling neurodegenerative disorder with significant genetic underpinnings. Multiple genome-wide association studies (GWAS) have been conducted with identification of several PD loci. However, these only explain about 25% of PD genetic risk indicating that additional loci of modest effect remain to be discovered. Association clustering methods such as gene-based tests are more powerful than single-variant analysis for identifying modest genetic effects. Combined with the locus-based algorithm, OASIS, the most significant association signals can be homed in. Here, two dbGAP GWAS datasets (7415 subjects (2750 PD and 4845 controls) genotyped for 0.78 million SNPs) were analyzed using combined clustering algorithms to identify 88 PD candidate genes in 24 loci. These were further investigated for gene expression in substantia nigra (SN) of PD and control subjects on GEO datasets. Expression differences were also assessed in normal brains SN versus white matter on BRAINEAC datasets. This genetic and functional analysis identified AXIN1, a key regulator of Wnt/β-catenin signaling, as a novel PD gene. This finding links PD with inflammation. Other significantly associated genes were CSMD1, CLDN1, ZNF141, ZNF721, RHOT2, RICTOR, KANSL1, and ARHGAP27. Novel PD genes were identified using genomic convergence of gene-wide and locus-based tests and expression studies on archived datasets.

Locus and gene-based GWAS meta-analysis identifies new diabetic nephropathy genes

Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes.

Aberrant T Cell Signaling and Subsets in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a chronic multi-organ debilitating autoimmune disease, which mainly afflicts women in the reproductive years. A complex interaction of genetics, environmental factors and hormones result in the breakdown of immune tolerance to "self" leading to damage and destruction of multiple organs, such as the skin, joints, kidneys, heart and brain. Both innate and adaptive immune systems are critically involved in the misguided immune response against self-antigens. Dendritic cells, neutrophils, and innate lymphoid cells are important in initiating antigen presentation and propagating inflammation at lymphoid and peripheral tissue sites. Autoantibodies produced by B lymphocytes and immune complex deposition in vital organs contribute to tissue damage. T lymphocytes are increasingly being recognized as key contributors to disease pathogenesis. CD4 T follicular helper cells enable autoantibody production, inflammatory Th17 subsets promote inflammation, while defects in regulatory T cells lead to unchecked immune responses. A better understanding of the molecular defects including signaling events and gene regulation underlying the dysfunctional T cells in SLE is necessary to pave the path for better management, therapy, and perhaps prevention of this complex disease. In this review, we focus on the aberrations in T cell signaling in SLE and highlight therapeutic advances in this field.

Locus and gene-based GWAS meta-analysis identifies new diabetic nephropathy genes

Objective Assimilation of SNPs Interacting in Synchrony (OASIS) is a locus-based clustering algorithm recently described that can potentially address false positives and negatives in genome-wide association studies (GWAS) of complex disorders. Diabetic nephropathy (DN) is incompletely understood due to a paucity of genes identified despite several GWAS. OASIS was applied to three DN dbGAP GWAS datasets (4725 subjects; 1.06 million SNPs). OASIS identified 19 DN genes which were verified using single variant replication in a standard association study and gene-based analysis using GATES. CARS and FRMD3 were confirmed as DN genes, and five known diabetes-associated genes, viz. NLRP3, INPPL1, PIK3C2G, NRXN3, and TBC1D4, not previously identified using these datasets were discovered. Furthermore, three additional novel DN genes were found which replicated in two sets of analysis, viz. NTN1, EBF2, and DNAH11. Hence, composite analysis with OASIS, gene-based, and single variant association testing can be universally applied to existing GWAS datasets for the identification of new genes.