Genetic Alleles Associated with SLE Susceptibility and Clinical Manifestations in Hispanic Patients from the Dominican Republic

The functional TNFAIP3 rs2230926T/G (Phe127Cys) variant confers risk to systemic lupus erythematosus in a Latin American population

TNFAIP3 is a classical systemic lupus erythematosus (SLE)-associated risk locus identified by genome-wide association studies (GWASs) and replicated by candidate gene association studies primarily in Caucasians and Asians. However, in Latin American populations, its role on SLE susceptibility is not known. We conducted a case-control study to evaluate whether the TNFAIP3 rs2230926T/G (Phe127Cys) variant is associated with risk of developing SLE in a cohort of Mexican patients. The TNFAIP3 rs2230926T/G variant was analyzed in 561 patients with SLE and 499 control subjects, using TaqMan probes. We found that the G allele was associated with susceptibility to SLE under the allelic (OR 2.09, p = 0.005) and genotypic (OR 2.14, p = 0.004) models. In conclusion, our results show that TNFAIP3 rs2230926T/G is a risk factor for the development of SLE in the Mexican population.

Forschung für die Praxis: Ernährung und Mikrobiom bei Autoimmunkrankheiten

Die Häufigkeit von Autoimmunerkrankungen in Industrieländern hat während der letzten Jahrzehnte ständig zugenommen. Diese Erkrankungen führen zu erhöhter Sterblichkeit sowie anhaltender Beeinträchtigung der Lebensqualität der Patienten und bedeuten eine große medizinische Belastung. Die Behandlung von Autoimmunkrankheiten beruht häufig auf unspezifischer Immunsuppression, was das Risiko von Infektionskrankheiten und Krebsmanifestationen erhöht. Die Pathogenese von Autoimmunerkrankungen ist komplex und umfasst nicht nur genetische Faktoren, sondern auch Umwelteinflüsse, die als Grund für die Zunahme von Autoimmunerkrankungen angesehen werden. Zahlreiche Umweltfaktoren wie Infektionen, Rauchen, Medikamente oder Ernährung können das Auftreten von Autoimmunität entweder fördern oder verhindern. Die Mechanismen der Beeinflussung durch Umwelteinflüsse sind jedoch komplex und derzeit noch nicht eindeutig geklärt. Die Entschlüsselung dieser Wechselwirkungen könnte unser Verständnis der Autoimmunität verbessern und neue Behandlungsmöglichkeiten für die Patienten eröffnen.

Research in practice: Diet and microbiome in autoimmune diseases

The incidence of autoimmune diseases in industrialized countries is constantly increasing over past decades. These diseases lead to increased mortality and persistent reduction in quality of life of the patients, posing a severe medical burden. Treatment of autoimmune diseases is often based on unspecific immune suppression, increasing the risk of infectious diseases as well as cancer manifestation. Pathogenesis of autoimmune conditions is complex and includes not only genetic factors, but also environmental influence, which is considered to be the reason for the rise of incidence of autoimmune diseases. Environmental factors comprise numerous elements, such as infections, smoking, medication, diet etc., which can either promote or prevent the onset of autoimmunity. However, the mechanisms of environmental influence are complex and for this moment not clearly understood. Deciphering of these interactions could enhance our comprehension of autoimmunity and provide some novel treatment options for the patients.

Regulatory Effect of Mesenchymal Stem Cells on T Cell Phenotypes in Autoimmune Diseases

Research on mesenchymal stem cells (MSCs) starts from the earliest assumption that cells derived from the bone marrow have the ability to repair tissues. Several scientists have since documented the crucial role of bone marrow-derived MSCs (BM-MSCs) in processes such as embryonic bone and cartilage formation, adult fracture and tissue repair, and immunomodulatory activities in therapeutic applications. In addition to BM-MSCs, several sources of MSCs have been reported to possess tissue repair and immunoregulatory abilities, making them potential treatment options for many diseases. Therefore, the therapeutic potential of MSCs in various diseases including autoimmune conditions has been explored. In addition to an imbalance of T cell subsets in most patients with autoimmune diseases, they also exhibit complex disease manifestations, overlapping symptoms among diseases, and difficult treatment. MSCs can regulate T cell subsets to restore their immune homeostasis toward disease resolution in autoimmune conditions. This review summarizes the role of MSCs in relieving autoimmune diseases via the regulation of T cell phenotypes.

Role of Systemic Lupus Erythematosus Risk Variants With Opposing Functional Effects as a Driver of Hypomorphic Expression of TNIP1 and Other Genes Within a Three-Dimensional Chromatin Network

OBJECTIVE

Genetic variants in the region of tumor necrosis factor-induced protein 3-interacting protein 1 (TNIP1) are associated with autoimmune disease and reduced TNIP1 gene expression. The aim of this study was to define the functional genetic mechanisms driving TNIP1 hypomorphic expression imparted by the systemic lupus erythematosus-associated TNIP1 H1 risk haplotype.

METHODS

Dual luciferase expression and electrophoretic mobility shift assays were used to evaluate the allelic effects of 11 risk variants on enhancer function and nuclear protein binding in immune cell line models (Epstein-Barr virus [EBV]-transformed human B cells, Jurkat cells, and THP-1 cells), left in a resting state or stimulated with phorbol 12-myristate 13-acetate/ionomycin. HiChIP was used to define the regulatory 3-dimensional (3-D) chromatin network of the TNIP1 haplotype by detecting in situ long-range DNA contacts associated with H3K27ac-marked chromatin in EBV B cells. Then, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to determine the expression of genes within the 3-D chromatin network.

RESULTS

Bioinformatics analyses of 50 single-nucleotide polymorphisms on the TNIP1 H1 risk haplotype identified 11 non-protein-coding variants with a high likelihood of influencing TNIP1 gene expression. Eight variants in EBV B cells, 5 in THP-1 cells, and 2 in Jurkat cells exhibited various allelic effects on enhancer activation, resulting in a cumulative suppressive effect on TNIP1 expression (net effect of risk variants -7.14 fold, -6.80 fold, and -2.44 fold, respectively; n > 3). Specifically, in EBV B cells, only 2 variants (rs10057690 and rs13180950) exhibited allele-specific loss of both enhancer activity and nuclear protein binding (each P < 0.01 relative to nonrisk alleles). In contrast, the rs10036748 risk allele reduced binding affinities of the transcriptional repressors basic helix-loop-helix family member 40/differentially expressed in chondrocytes 1 (bHLHe40/DEC1) (P < 0.05 relative to nonrisk alleles) and CREB-1 (P not significant) in EBV B cells, resulting in a gain of enhancer activity (P < 0.05). HiChIP and qRT-PCR analyses revealed that overall transcriptional repression of the TNIP1 haplotype extended to the neighboring genes DCTN4 and GMA2, both of which also showed decreased expression in the presence of the TNIP1 risk haplotype (P < 0.001 and P < 0.01, respectively, relative to the nonrisk haplotype); notably, it was found that these genes share a 3-D chromatin network.

CONCLUSION

Hypomorphic TNIP1 expression results from the combined concordant and opposing effects of multiple risk variants carried on the TNIP1 risk haplotype, with the strongest regulatory effect in B lymphoid lineage cells. Furthermore, the TNIP1 risk haplotype effect extends to neighboring genes within a shared chromatin network.

Correlations of Expression Levels of a Panel of Genes (IRF5, STAT4, TNFSF4, MECP2, and TLR7) and Cytokine Levels (IL-2, IL-6, IL-10, IL-12, IFN-γ, and TNF-α) with Systemic Lupus Erythematosus Outcomes in Jordanian Patients

Systemic lupus erythematosus (SLE) is characterized by systemic end-organ damage. We investigated the involvement of IRF5, TLR-7, MECP2, STAT4, and TNFSF4 genes and TNF-α, IFN-γ, IL-2, IL-12, IL-6, and IL-10 cytokines in SLE pathogenesis and in organ damage in Jordanian patients. Blood was collected from 51 patients and 50 controls. Expression levels of SLE genes in PBMCs and cytokine levels were determined using RT-PCR and ELISA, respectively. Expression levels of all genes and levels of TNF-α, IL-12, IL-6, and IL-10 were higher in SLE patients than those in controls (p < 0.05), whereas IL-2 level was lower. High STAT4 (α), TNFSF4, and IL-10 levels correlated with cardiovascular damage, and high MECP2 (α) and TNF-α correlated with renal damage. Pulmonary and musculoskeletal damages correlated with high levels of TNFSF4. We concluded that STAT4 and TNFSF4 genes with TNF-α and IL-10 cytokines could be used as biomarkers to assess SLE activity and manage treatment.

Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

BACKGROUND

Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN.

RESULTS

Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features.

CONCLUSIONS

This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.