Members 6B and 14 of the TNF receptor superfamily in multiple sclerosis predisposition

Exploring new drug treatment targets for immune related bone diseases using a multi omics joint analysis strategy

In the field of treatment and prevention of immune-related bone diseases, significant challenges persist, necessitating the urgent exploration of new and effective treatment methods. However, most existing Mendelian randomization (MR) studies are confined to a single analytical approach, which limits the comprehensive understanding of the pathogenesis and potential therapeutic targets of these diseases. In light of this, we propose the hypothesis that genetic variations in specific plasma proteins have a causal relationship with immune-related bone diseases through the MR mechanism, and that key therapeutic targets can be accurately identified using an integrated multi-omic analysis approach. This study comprehensively applied a variety of analytical methods. Firstly, the protein quantitative trait locus (pQTLs) data from two large plasma protein databases and the Genome-Wide Association Study (GWAS) data of nine immune-related bone diseases were used for Mendelian randomization (MR) analysis. At the same time, we employed the Summary-based Mendelian Randomization (SMR) method, combined with the Bayesian colocalization analysis method of coding genes, as well as the Linkage Disequilibrium Score Regression (LDSC) analysis method based on genetic correlation analysis, as methods to verify the genetic association between genes and complex diseases, thus comprehensively obtaining positive results. In addition, a Phenome-wide Association Study (PheWAS) was conducted on significantly positive genes, and their expression patterns in different tissues were also explored. Subsequently, we integrated Protein-Protein Interaction (PPI) network analysis, Gene Ontology (GO) analysis. Finally, based on the above analytical methods, drug prediction and molecular docking studies were carried out with the aim of accurately identifying key therapeutic targets. Through a comprehensive analysis using four methods, namely the Mendelian randomization (MR) analysis study, Summary-based Mendelian Randomization (SMR) analysis study, Bayesian colocalization analysis study, and Linkage Disequilibrium Score Regression (LDSC) analysis study. We found that through MR, SMR, and combined with Bayesian colocalization analysis, an association was found between rheumatoid arthritis (RA) and HDGF. Using the combination of MR and Bayesian colocalization analysis, as well as LDSC analysis, it was concluded that RA was related to CCL19 and TNFRSF14. Based on the methods of MR and Bayesian colocalization, an association was found between GPT and Crohn's disease-related arthritis, and associations were found between BTN1A1, EVI5, OGA, TNFRSF14 and multiple sclerosis (MS), and associations were found between ICAM5, CCDC50, IL17RD, UBLCP1 and psoriatic arthritis (PsA). Specifically, in the MR analysis of RA, HDGF (P_ivw = 0.0338, OR = 1.0373, 95%CI = 1.0028-1.0730), CCL19 (P_ivw = 0.0004, OR = 0.3885, 95%CI = 0.2299-0.6566), TNFRSF14 (P_ivw = 0.0007, OR = 0.6947, 95%CI = 0.5634-0.8566); in the MR analysis of MS, BTN1A1 (P_ivw = 0.0000, OR = 0.6101, 95%CI = 0.4813-0.7733), EVI5 (P_ivw = 0.0000, OR = 0.3032, 95%CI = 0.1981-0.4642), OGA (P_ivw = 0.0005, OR = 0.4599, 95%CI = 0.2966-0.7131), TNFRSF14 (P_ivw = 0.0002, OR = 0.4026, 95%CI = 0.2505-0.6471); in the MR analysis of PsA, ICAM5 (P_ivw = 0.0281, OR = 1.1742, 95%CI = 1.0174-1.3552), CCDC50 (P_ivw = 0.0092, OR = 0.7359, 95%CI = 0.5843-0.9269), IL17RD (P_ivw = 0.0006, OR = 0.7887, 95%CI = 0.6886-0.9034), UBLCP1 (P_ivw = 0.0021, OR = 0.6901, 95%CI = 0.5448-0.8741); in the MR analysis of Crohn's disease-related arthritis, GPT (P_ivw = 0.0006, OR = 0.0057, 95%CI = 0.0003-0.1111). In the Bayesian colocalization analysis of RA, HDGF (H4 = 0.8426), CCL19 (H4 = 0.9762), TNFRSF14 (H4 = 0.8016); in the Bayesian colocalization analysis of MS, BTN1A1 (H4 = 0.7660), EVI5 (H4 = 0.9800), OGA (H4 = 0.8569), TNFRSF14 (H4 = 0.8904); in the Bayesian colocalization analysis of PsA, ICAM5 (H4 = 0.9476), CCDC50 (H4 = 0.9091), IL17RD (H4 = 0.9301), UBLCP1 (H4 = 0.8862); in the Bayesian colocalization analysis of Crohn's disease-related arthritis, GPT (H4 = 0.8126). In the SMR analysis of RA, HDGF (p_SMR = 0.0338, p_HEIDI = 0.0628). In the LDSC analysis of RA, CCL19 (P = 0.0000), TNFRSF14 (P = 0.0258). By comprehensively analyzing plasma proteomic and transcriptomic data, we successfully identified key therapeutic targets for various clinical subtypes of immune-associated bone diseases. Our findings indicate that the significant positive genes associated with RA include HDGF, CCL19, and TNFRSF14; the positive gene linked to Crohn-related arthropathy is GPT; for MS, the positive genes are BTN1A1, EVI5, OGA, and TNFRSF14; and for PsA, the positive genes are ICAM5, CCDC50, IL17RD, and UBLCP1. Through this comprehensive analytical approach, we have screened potential therapeutic targets for different clinical subtypes of immune-related bone diseases. This research not only enhances our understanding of the pathogenesis of these conditions but also provides a solid theoretical foundation for subsequent drug development and clinical treatment, with the potential to yield significant advancements in the management of patients with immune-related bone diseases.

Multi-omic biomarkers associated with multiple sclerosis: from Mendelian randomization to drug prediction

Currently, the treatment and prevention of multiple sclerosis (MS) continue to encounter significant challenges. Mendelian randomization (MR) analysis has emerged as a crucial research method in the pursuit of new therapeutic strategies. Accordingly, we hypothesize that there exists a causal association between genetic variants of specific plasma proteins and MS through MR mechanisms, and that key therapeutic targets can be precisely identified by integrating multi-omics analytical approaches. In this study, we developed a comprehensive analytical framework aimed at identifying and validating potential therapeutic targets for MS. The framework commenced with a two-sample Mendelian randomization (MR) study utilizing two large plasma protein quantitative trait locus (pQTL) datasets. Building on this foundation, we performed Bayesian co-localization analysis of coding genes, followed by a full phenotype-wide association study (PheWAS) on the co-positive genes identified through both analytical methods. This approach allowed us to explore the functions of key genes and the mechanisms of co-morbidity associated with the disease. Subsequently, we integrated protein-protein interaction (PPI) network analysis, gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to facilitate drug prediction and molecular docking studies. This study conducted a systematic analysis between two large plasma pQTLs datasets and MS. In the MR analysis, the MR analysis of Icelandic plasma pQTLs and MS identified 88 positive plasma proteins, while the MR analysis of the UK Biobank database pQTLs and MS identified 122 positive plasma proteins. By comparison, uroporphyrinogen III synthase (UROS) and glutathione S-transferase theta 2B (GSTT2B) were found to be the positive proteins shared by the two datasets. After false discovery rate (FDR) correction, signal transducer and activator of transcription 3 (STAT3) was a significantly positive protein in the analysis of Icelandic plasma pQTLs. In the analysis of the UK Biobank database pQTLs, advanced glycosylation end product-specific receptor (AGER), allograft inflammatory factor 1 (AIF1), butyrophilin subfamily 1 member A1 (BTN1A1), cluster of differentiation 58 (CD58), desmoglein 4 (DSG4), ecotropic viral integration site 5 (EVI5), tumor necrosis factor (TNF), and tumor necrosis factor receptor superfamily member 14 (TNFRSF14) were significantly positive proteins. After Bonferroni correction, AGER, CD58, EVI5, and TNF remained significantly positive proteins in the analysis of the UK Biobank database pQTLs. In the Bayesian colocalization analysis, EVI5 (PPH4 = 0.9800), O-GlcNAcase (OGA) (PPH4 = 0.8569), and TNFRSF14 (PPH4 = 0.8904) were the common positive genes in the two analysis methods. In conclusion, EVI5, OGA, and TNFRSF14 may be potential therapeutic targets for MS. Through the comprehensive application of MR analysis and Bayesian colocalization analysis, we have successfully identified that EVI5, OGA, and TNFRSF14 may be key therapeutic targets for MS. These findings may provide a scientific basis for the development of novel immunotherapies, combination treatment regimens, or targeted intervention strategies.

Pathway Analysis of Genome Wide Association Studies (GWAS) Data Associated with Male Infertility

Background: Infertility is a common condition affecting approximately 10–20% of the reproductive age population. Idiopathic infertility cases are thought to have a genetic basis, but the underlying causes are largely unknown. However, the genetic basis underlying male infertility in humans is only partially understood. The Purpose of the study is to understand the current state of research on the genetics of male infertility and its association with significant biological mechanisms. Results: We performed an Identify Candidate Causal SNPs and Pathway (ICSN Pathway) analysis using a genome-wide association study (GWAS) dataset, and NCBI-PubMed search which included 632 SNPs in GWAS and 451 SNPs from the PubMed server, respectively. The ICSN Pathway analysis produced three hypothetical biological mechanisms associated with male infertility: (1) rs8084 and rs7192→HLA-DRA→inflammatory pathways and cell adhesion; rs7550231 and rs2234167→TNFRSF14→TNF Receptor Superfamily Member 14→T lymphocyte proliferation and activation; rs1105879 and rs2070959→UGT1A6→UDP glucuronosyltransferase family 1 member A6→Metabolism of Xenobiotics, androgen, estrogen, retinol, and carbohydrates. Conclusions: We believe that our results may be helpful to study the genetic mechanisms of male infertility. Pathway-based methods have been applied to male infertility GWAS datasets to investigate the biological mechanisms and reported some novel male infertility risk pathways. This pathway analysis using GWAS dataset suggests that the biological process related to inflammation and metabolism might contribute to male infertility susceptibility. Our analysis suggests that genetic contribution to male infertility operates through multiple genes affecting common inflammatory diseases interacting in functional pathways.

Human herpesvirus 6 infection as a trigger of multiple sclerosis: an update of recent literature

BACKGROUND

This is an update on the existing evidence regarding a relationship between infection with human herpesvirus 6 (HHV-6) and multiple sclerosis (MS) in order to contribute on the attempt to define the nature and strength of that relationship.

RESULTS

Study quality was assessed using the criteria proposed by Moore and Wolfson and by the classification criteria used by the Canadian Task Force on the Periodic Health Examination. Studies were categorized both by experimental technique and by quality (high [A], intermediate [B], and low [C]) as determined by the Moore and Wolfson criteria. Overall, 27 (90%) of 30 studies, 18 (86%) of which were classified as A quality, reached a statistically significant result. According to the Canadian Task Force classification, all studies were categorized as evidence of qualityII-1. Limitations of the available experimental techniques and perspectives for future research are discussed.

CONCLUSIONS

The current review continues to emphasize the need for further, objective, evidence-based examination of the relationship between HHV-6 infection and multiple sclerosis.

Associations between CD160 polymorphisms and autoimmune thyroid disease: a case-control study

BACKGROUND

Recent researches suggest that the CD160/HVEM/LIGHT/BTLA signaling pathway may contribute to the pathogeneses of autoimmune diseases, but the relationship between CD160 polymorphisms and autoimmune thyroid disease (AITD) has not been reported yet. This study aimed to evaluate the associations between CD160 polymorphisms and AITD.

METHODS

A total of 1017 patients with AITD (634 Graves' disease and 383 Hashimoto's thyroiditis) and 856 unrelated healthy controls were recruited into our study. Odds ratios (ORs) with 95% confidence interval (95%CI) were calculated through logistic regression analyses. The CD160 SNPs were detected using Hi-SNP high-throughput genotyping.

RESULTS

There was a statistically significant difference between Graves' disease patients and the control group with respect to both the genotype distribution (P = 0.014) and allele frequency of rs744877 (P = 0.034). A significant association of CD160 rs744877 with AITD was observed before adjusted age and gender under a dominant model (OR = 0.79, 95%CI 0.66-0.95; P = 0.013) and an additive model (OR = 0.77, 95%CI 0.64-0.94, P = 0.008), and was also observed after adjusted age and gender under a dominant model (OR = 0.78, 95%CI 0.65-0.95; P = 0.011) and an additive model (OR = 0.76, 95%CI 0.63-0.93, P = 0.007). A significant association of rs744877 with Graves' disease was observed under an allele model (OR = 0.84, 95%CI 0.71-0.98, P = 0.027), a dominant model (OR = 0.74, 95%CI 0.60-0.91; P = 0.005), and an additive model (OR = 0.72, 95%CI 0.58-0.90, P = 0.004). Multivariate logistic regression analyses suggested that the association remained significant after adjustment for age and gender. However, rs744877 was not related to Hashimoto's thyroiditis. Furthermore, CD160 rs3766526 was not significantly related to either Graves' disease or Hashimoto's thyroiditis.

CONCLUSION

This is the first identification of the association of CD160 rs744877 with Graves' disease. Our findings add new data to the genetic contribution to Graves' disease susceptibility and support the crucial role of the CD160/HVEM/LIGHT/BTLA pathway in the pathogenesis of Graves' disease.

Investigating the association of polymorphisms of ANKRD55 and MMEL1 with susceptibility to multiple sclerosis in Iranian population

OBJECTIVE

Multiple sclerosis (MS) is an autoimmune neurological disability in which immune cells attack the myelin sheaths that protect nerve fibers. The pathogenesis of the disease involves both complex genetic effects as well as multifaceted gene-environment interactions. In the present study, we examined the association of two Single nucleotide polymorphisms (SNPs) in ANKRD55 (rs6859219) and MMEL (rs3748816) with MS in the Iranian population. ANKRD55 is specifically expressed in human peripheral blood mononuclear cells and CD4 + T cells, while MMEL1is involved in the degradation of both neuropeptides and β-amyloid.

METHODS

In this case-control study, 110 patients with MS and 110 matched healthy controls were enrolled. The Participants were genotyped for ANKRD55 and MMEL1 SNPs using PCR-RFLP and Real-Time TaqMan SNP Genotyping respectively. The results were finally analyzed using SPSS software version 22.

RESULTS

Our results did not show significant differences in allelic frequencies of two SNPs among cases and controls (P-Value >0.05). However, for ANKRD55 (rs6859219), CA genotype was shown to have a protective effect (p = 0.035 and OR = 0.55), while CC genotype was a susceptive genotype to MS (p = 0.036 and OR = 1.8). There was no significant difference in genotypic frequencies of SNP rs3748816 in MMEL1.

CONCLUSION

We could successfully replicate the association of ANKRD55 (rs6859219) with susceptibility to MS in the Iranian population. Our result can provide an insight into better understanding the pathogenesis of MS and also improve the genetic counseling for patients affected with multiple sclerosis in Iran.

Summary-data-based Mendelian randomization prioritizes potential druggable targets for multiple sclerosis

Multiple sclerosis is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study findings into therapeutics and effective preventive strategies has been limited to date. We used summary-data-based Mendelian randomization to synthesize findings from public expression quantitative trait locus, methylation quantitative trait locus and Multiple Sclerosis Genome-Wide Association Study datasets. By correlating the effects of methylation on multiple sclerosis, methylation on expression and expression on multiple sclerosis susceptibility, we prioritize genetic loci with evidence of influencing multiple sclerosis susceptibility. We overlay these findings onto a list of 'druggable' genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and search tool for the retrieval of interacting genes/proteins to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr virus-infected B cells, lymphoblastoid cell lines. We conducted a systematic review of prioritized genes using the Open Targets platform to identify completed and planned trials targeting prioritized genes in multiple sclerosis and related disease areas. Expression of 45 genes in peripheral blood was strongly associated with multiple sclerosis susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leucocyte signalling. We refined this prioritized gene list by restricting to loci where CpG site methylation was associated with multiple sclerosis susceptibility, with gene expression and where expression was associated with multiple sclerosis susceptibility. This approach yielded a list of 15 prioritized druggable target genes for which there was evidence of a pathway linking methylation, expression and multiple sclerosis. Five of these 15 genes are targeted by existing drugs and three were replicated in a smaller expression Quantitative Trait Loci dataset (CD40, MERTK and PARP1). In lymphoblastoid cell lines, this approach prioritized 7 druggable gene targets, of which only one was prioritized by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritized genes in disorders related to multiple sclerosis. We use public datasets and summary-data-based Mendelian randomization to identify a list of prioritized druggable genetic targets in multiple sclerosis. We hope our findings could be translated into a platform for developing targeted preventive therapies.

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.

Trying to understand the genetics of atopic dermatitis

Atopic dermatitis (AD) is a common and complex skin disease associated with both genetic and environmental factors. Loss-of-function mutations in the filaggrin gene, encoding a structural protein with an important role in epidermal barrier function, constitutes a well recognised susceptibility locus for AD. Further, genome-wide association studies (GWAS), including large meta-analyses, have discovered 38 additional susceptibility loci with genome-wide significance. However, the reported variations only explain a fraction of the overall heritability of AD. Here, we summarize the current knowledge of the role of filaggrin and the epidermal differentiation complex as well as the results of GWAS, with an emphasis on novel findings and observations made in the past two years. Additionally, we present first results of exome sequencing for AD and discuss novel therapeutic strategies.

DcR3 gene polymorphisms are associated with sporadic breast infiltrating ductal carcinoma in Northeast Chinese women

Decoy Receptor 3 (DcR3), also called TNFRSF6β, is a member of the tumor necrosis factor receptor superfamily and is a soluble receptor for FasL. DcR3 is overexpressed in cancers and contributes to tumorigenesis through immune suppression and promotion of angiogenesis. We found that DcR3 is overexpressed in breast infiltrating ductal carcinoma (IDC) cells as compared with normal controls. We also conducted a case-control study analyzing associations of DcR3 polymorphisms with breast IDC risk. Subjects included 531 females with breast IDC and 592 age-matched healthy controls. Four DcR3 single nucleotide polymorphism loci with minor frequencies of more than 5% (rs3208008, rs41309931, rs2297441 and rs1291207) were genotyped using polymerase chain reaction restriction fragment length polymorphism and sequencing. Our results revealed significant differences in rs41309931genotypes and alleles (P < 0.01). Based on Haploview software analysis, the haplotype block A_rs3208008 G_rs41309931 G_rs2297441 A_rs1291207 exhibited the highest frequency, but, haplotype blocks A_rs3208008 T_rs41309931 G_rs2297441 A_rs1291207 and C_rs3208008 G_rs41309931 G_rs2297441 A_rs1291207 were associated with breast IDC risk. This study also detected associations between DcR3 gene polymorphisms and the clinicopathological features of breast IDC, including lymph node metastasis and C-erbB2, P53, estrogen receptor and progesterone receptor status. These data indicate that DcR3 gene polymorphisms are associated with sporadic breast IDC risk in Northeast Chinese females.

Tumor necrosis factor superfamily in innate immunity and inflammation

The tumor necrosis factor superfamily (TNFSF) and its corresponding receptor superfamily (TNFRSF) form communication pathways required for developmental, homeostatic, and stimulus-responsive processes in vivo. Although this receptor-ligand system operates between many different cell types and organ systems, many of these proteins play specific roles in immune system function. The TNFSF and TNFRSF proteins lymphotoxins, LIGHT (homologous to lymphotoxins, exhibits inducible expression, and competes with HSV glycoprotein D for herpes virus entry mediator [HVEM], a receptor expressed by T lymphocytes), lymphotoxin-β receptor (LT-βR), and HVEM are used by embryonic and adult innate lymphocytes to promote the development and homeostasis of lymphoid organs. Lymphotoxin-expressing innate-acting B cells construct microenvironments in lymphoid organs that restrict pathogen spread and initiate interferon defenses. Recent results illustrate how the communication networks formed among these cytokines and the coreceptors B and T lymphocyte attenuator (BTLA) and CD160 both inhibit and activate innate lymphoid cells (ILCs), innate γδ T cells, and natural killer (NK) cells. Understanding the role of TNFSF/TNFRSF and interacting proteins in innate cells will likely reveal avenues for future therapeutics for human disease.

Classification of HHV-6A and HHV-6B as distinct viruses

Shortly after the discovery of human herpesvirus 6 (HHV-6), two distinct variants, HHV-6A and HHV-6B, were identified. In 2012, the International Committee on Taxonomy of Viruses (ICTV) classified HHV-6A and HHV-6B as separate viruses. This review outlines several of the documented epidemiological, biological, and immunological distinctions between HHV-6A and HHV-6B, which support the ICTV classification. The utilization of virus-specific clinical and laboratory assays for distinguishing HHV-6A and HHV-6B is now required for further classification. For clarity in biological and clinical distinctions between HHV-6A and HHV-6B, scientists and physicians are herein urged, where possible, to differentiate carefully between HHV-6A and HHV-6B in all future publications.