ITGAM is a risk factor to systemic lupus erythematosus and possibly a protection factor to rheumatoid arthritis in patients from Mexico

Longevity-associated BPIFB4 gene counteracts the inflammatory signaling

BACKGROUND

Increased levels of pro-inflammatory proteins in plasma can be detected in older individuals and associate with the so called chronic low-grade inflammation, which contributes to a faster progression of aged-related cardiovascular (CV) diseases, including frailty, neurodegeneration, gastro-intestinal diseases and disorders reflected by alterations in the composition of gut microbiota. However, successful genetic programme of long-living individuals alters the trajectory of the ageing process, by promoting an efficient immune response that can counterbalance deleterious effects of inflammation and the CV complications. This is the case of BPIFB4 gene in which, homozygosity for a four single-nucleotide polymorphism (SNP) haplotype, the Longevity-Associated Variant (LAV) correlates with prolonged health span and reduced risk of CV complications and inflammation. The relation between LAV-BPIFB4 and inflammation has been proven in different experimental models, here we hypothesized that also human homozygous carriers of LAV-BPIFB4 gene may experience a lower inflammatory burden as detected by plasma proteomics that could explain their favourable CV risk trajectory over time. Moreover, we explored the therapeutic effects of LAV-BPIFB4 in inflammatory disease and monolayer model of intestinal barrier.

RESULTS

We used high-throughput proteomic approach to explore the profiles of circulating proteins from 591 baseline participants selected from the PLIC cohort according to the BPIFB4 genotype to identify the signatures and differences of BPIFB4 genotypes useful for health and disease management. The observational analysis identified a panel of differentially expressed circulating proteins between the homozygous LAV-BPIFB4 carriers and the other alternative BPIFB4 genotypes highlighting in the latter ones a higher grade of immune-inflammatory markers. Moreover, in vitro studies performed on intestinal epithelial organs from inflammatory bowel disease (IBD) patients and monolayer model of intestinal barrier demonstrated the benefit of LAV-BPIFB4 treatment.

CONCLUSIONS

Homozygosity for LAV-BPIFB4 results in the attenuation of inflammation in PLIC cohort and IBD patients providing preliminary evidences for its therapeutic use in inflammatory disorders that need to be further characterized and confirmed by independent studies.

NFIL3 aggravates human coronary artery endothelial cell injury by promoting ITGAM transcription in Kawasaki disease

OBJECTIVE

High expression of nuclear factor interleukin-3 (NFIL3) and integrin Alpha M (ITGAM) was found in serum samples from Kawasaki disease (KD) patients through bioinformatics analysis. Hence, this study aimed to explore the biological functions of NFIL3 and ITGAM in KD serum-stimulated human coronary artery endothelial cells (HCAECs).

METHODS

The differentially-expressed genes in KD were analyzed through bioinformatics analysis. Serum samples were obtained from 18 KD patients and 18 healthy volunteers, followed by detection of NFIL3 and ITGAM levels in KD serum. After HCAECs were transfected with sh-NFIL3, sh-ITGAM, or sh-NFIL3 + oe-ITGAM and underwent 24-h KD serum stimulation, cell viability and apoptosis and the levels of inflammation-related factors were measured. The binding between NFIL3 and ITGAM was validated by dual-luciferase and chromatin immunoprecipitation (ChIP) assays.

RESULTS

NFIL3 and ITGAM were up-regulated in serum from KD patients and KD serum-stimulated HCAECs. Down-regulation of NFIL3 or ITGAM inhibited KD serum-induced cell apoptosis and inflammatory response of HCAECs and promoted cell viability. Mechanistically, NFIL3 promoted ITGAM transcription level. Up-regulation of ITGAM reversed the improvement of NFIL3 down-regulation on KD serum-induced HCAEC injury.

CONCLUSION

NFIL3 aggravated KD serum-induced HCAEC injury by promoting ITGAM transcription, which provided new insights into the treatment of KD.

Identifying Aging-Related Biomarkers and Immune Infiltration Features in Diabetic Nephropathy Using Integrative Bioinformatics Approaches and Machine-Learning Strategies

BACKGROUND

Aging plays an essential role in the development of diabetic nephropathy (DN). This study aimed to identify and verify potential aging-related genes associated with DN using bioinformatics analysis.

METHODS

To begin with, we combined the datasets from GEO microarrays (GSE104954 and GSE30528) to find the genes that were differentially expressed (DEGs) across samples from DN and healthy patient populations. By overlapping DEGs, weighted co-expression network analysis (WGCNA), and 1357 aging-related genes (ARGs), differentially expressed ARGs (DEARGs) were discovered. We next performed functional analysis to determine DEARGs' possible roles. Moreover, protein-protein interactions were examined using STRING. The hub DEARGs were identified using the CytoHubba, MCODE, and LASSO algorithms. We next used two validation datasets and Receiver Operating Characteristic (ROC) curves to determine the diagnostic significance of the hub DEARGs. RT-qPCR, meanwhile, was used to confirm the hub DEARGs' expression levels in vitro. In addition, we investigated the relationships between immune cells and hub DEARGs. Next, Gene Set Enrichment Analysis (GSEA) was used to identify each biomarker's biological role. The hub DEARGs' subcellular location and cell subpopulations were both identified and predicted using the HPA and COMPARTMENTS databases, respectively. Finally, drug-protein interactions were predicted and validated using STITCH and AutoDock Vina.

RESULTS

A total of 57 DEARGs were identified, and functional analysis reveals that they play a major role in inflammatory processes and immunomodulation in DN. In particular, aging and the AGE-RAGE signaling pathway in diabetic complications are significantly enriched. Four hub DEARGs (CCR2, VCAM1, CSF1R, and ITGAM) were further screened using the interaction network, CytoHubba, MCODE, and LASSO algorithms. The results above were further supported by validation sets, ROC curves, and RT-qPCR. According to an evaluation of immune infiltration, DN had significantly more resting mast cells and delta gamma T cells but fewer regulatory T cells and active mast cells. Four DEARGs have statistical correlations with them as well. Further investigation revealed that four DEARGs were implicated in immune cell abnormalities and regulated a wide range of immunological and inflammatory responses. Furthermore, the drug-protein interactions included four possible therapeutic medicines that target four DEARGs, and molecular docking could make this association practical.

CONCLUSIONS

This study identified four DEARGs (CCR2, VCAM1, CSF1R, and ITGAM) associated with DN, which might play a key role in the development of DN and could be potential biomarkers in DN.

Proteomic analysis identifies subgroups of patients with active systemic lupus erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients.

METHOD

Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile.

RESULTS

In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617).

CONCLUSIONS

Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE.

A gene-level test for directional selection on gene expression

Most variants identified in human genome-wide association studies and scans for selection are noncoding. Interpretation of their effects and the way in which they contribute to phenotypic variation and adaptation in human populations is therefore limited by our understanding of gene regulation and the difficulty of confidently linking noncoding variants to genes. To overcome this, we developed a gene-wise test for population-specific selection based on combinations of regulatory variants. Specifically, we use the QX statistic to test for polygenic selection on cis-regulatory variants based on whether the variance across populations in the predicted expression of a particular gene is higher than expected under neutrality. We then applied this approach to human data, testing for selection on 17,388 protein-coding genes in 26 populations from the Thousand Genomes Project. We identified 45 genes with significant evidence (FDR<0.1) for selection, including FADS1, KHK, SULT1A2, ITGAM, and several genes in the HLA region. We further confirm that these signals correspond to plausible population-level differences in predicted expression. While the small number of significant genes (0.2%) is consistent with most cis-regulatory variation evolving under genetic drift or stabilizing selection, it remains possible that there are effects not captured in this study. Our gene-level QX score is independent of standard genomic tests for selection, and may therefore be useful in combination with traditional selection scans to specifically identify selection on regulatory variation. Overall, our results demonstrate the utility of combining population-level genomic data with functional data to understand the evolution of gene expression.

ITGAM rs1143679 Variant in Systemic Lupus Erythematosus Is Associated with Increased Serum Calcification Propensity

OBJECTIVES

CD11B/ITGAM (Integrin Subunit α M) mediates the adhesion of monocytes, macrophages, and granulocytes and promotes the phagocytosis of complement-coated particles. Variants of the ITGAM gene are candidates for genetic susceptibility to systemic lupus erythematosus (SLE). SNP rs1143679 (R77H) of CD11B particularly increases the risk of developing SLE. Deficiency of CD11B is linked to premature extra-osseous calcification, as seen in the cartilage of animals with osteoarthritis. Serum calcification propensity measured by the T50 test is a surrogate marker for systemic calcification and reflects increased cardiovascular (CV) risk. We aimed to assess whether the CD11B R77H gene variant is associated with a higher serum calcification propensity (i.e., a lower T50 value) in SLE patients compared to the wild-type allele (WT).

METHODS

Cross-sectional study incorporating adults with SLE genotyped for the CD11B variant R77H and assessed for serum calcification propensity with the T50 method. Participants were included in a multicenter trans-disciplinary cohort and fulfilled the 1997 revised American College of Rheumatology (ACR) criteria for SLE. We used descriptive statistics for comparing baseline characteristics and sequential T50 measurements in subjects with the R77H variant vs. WT CD11B.

RESULTS

Of the 167 patients, 108 (65%) were G/G (WT), 53 (32%) were G/A heterozygous, and 6 (3%) were A/A homozygous for the R77H variant. A/A patients cumulated more ACR criteria upon inclusion (7 ± 2 vs. 5 ± 1 in G/G and G/A; p = 0.02). There were no differences between the groups in terms of global disease activity, kidney involvement, and chronic renal failure. Complement C3 levels were lower in A/A individuals compared to others (0.6 ± 0.08 vs. 0.9 ± 0.25 g/L; p = 0.02). Baseline T50 did not differ between the groups (A/A 278 ± 42' vs. 297 ± 50' in G/G and G/A; p = 0.28). Considering all sequential T50 test results, serum calcification propensity was significantly increased in A/A individuals compared to others (253 ± 50 vs. 290 ± 54; p = 0.008).

CONCLUSIONS

SLE patients with homozygosity for the R77H variant and repeated T50 assessment displayed an increased serum calcification propensity (i.e., a lower T50) and lower C3 levels compared to heterozygous and WT CD11B, without differing with respect to global disease activity and kidney involvement. This suggests an increased CV risk in SLE patients homozygous for the R77H variant of CD11B.

An Integrative Bioinformatics Analysis of the Potential Mechanisms Involved in Propofol Affecting Hippocampal Neuronal Cells

The aim of this study is to probe the possible molecular mechanisms underlying the effects of propofol on HT22 cells. HT22 cells treated with different concentrations were sequenced, and then the results of the sequencing were analyzed for dynamic trends. Expression pattern clustering analysis was performed to demonstrate the expression of genes in the significant trend modules in each group of samples. We first chose the genes related to the trend module for WGCNA analysis, then constructed the PPI network of module genes related to propofol treatment group, and screened the key genes. Finally, GSEA analysis was performed on the key genes. Overall, 2,506 genes showed a decreasing trend with increasing propofol concentration, and 1,871 genes showed an increasing trend with increasing propofol concentration. WGCNA analysis showed that among them, turquoise panel genes were negatively correlated with propofol treatment, and genes with Cor R >0.9 in the turquoise panel were selected for PPI network construction. The MCC algorithm screened a total of five key genes (CD86, IL10RA, PTPRC, SPI1, and ITGAM). GSEA analysis showed that CD86, IL10RA, PTPRC, SPI1, and ITGAM are involved in the PRION_DISEASES pathway. Our study showed that propofol sedation can affect mRNA expression in the hippocampus, providing new ideas to identify treatment of nerve injury induced by propofol anesthesia.

Identification and validation of inferior prognostic genes associated with immune signatures and chemotherapy outcome in acute myeloid leukemia

Acute myeloid leukemia (AML) is a group of heterogeneous hematological malignancies. We identified key genes as ITGAM and lncRNA ITGB2-AS1 through different bioinformatics tools. Furthermore, qPCR was performed to verify the expression level of essential genes in clinical samples. Retrospective research on 179 AML cases was used to investigate the relationship between the expression of ITGAM and the characteristics of AML. The critical gene relationship with immune infiltration in AML was estimated. The clinical validation and prognostic investigation showed that ITGAM, PPBP, and ITGB2-AS1 are highly expressed in AML (P < 0.001) and significantly associated with the overall survival in AML. Moreover, the retrospective research on 179 clinical cases showed that positive expression of ITGAM is substantially related to AML classification (P < 0.001), higher count of white blood cells (P < 0.01), and poor chemotherapy outcome (P < 0.05). Furthermore, based on grouping ITGAM as the high and low expression in TCGA-LAML profile, we found that genes in the highly expressed ITGAM group are mainly involved in immune infiltration and inflammation-related signaling pathways. Finally, we discovered that the expression level of ITGAM and lncRNA ITGB2-AS1 are not just closely related to the immune score and stromal score (P < 0.001) but also significantly positively correlated with various Immune signatures in AML (P < 0.001), indicating the association of these genes with immunosuppression in AML. The prediction of candidate drugs indicated that certain immunosuppressive drugs have potential therapeutic effects for AML. The critical genes could be used as potential biomarkers to evaluate the survival and prognosis of AML.

Single Cell Transcriptomics Implicate Novel Monocyte and T Cell Immune Dysregulation in Sarcoidosis

Sarcoidosis is a systemic inflammatory disease characterized by infiltration of immune cells into granulomas. Previous gene expression studies using heterogeneous cell mixtures lack insight into cell-type-specific immune dysregulation. We performed the first single-cell RNA-sequencing study of sarcoidosis in peripheral immune cells in 48 patients and controls. Following unbiased clustering, differentially expressed genes were identified for 18 cell types and bioinformatically assessed for function and pathway enrichment. Our results reveal persistent activation of circulating classical monocytes with subsequent upregulation of trafficking molecules. Specifically, classical monocytes upregulated distinct markers of activation including adhesion molecules, pattern recognition receptors, and chemokine receptors, as well as enrichment of immunoregulatory pathways HMGB1, mTOR, and ephrin receptor signaling. Predictive modeling implicated TGFβ and mTOR signaling as drivers of persistent monocyte activation. Additionally, sarcoidosis T cell subsets displayed patterns of dysregulation. CD4 naïve T cells were enriched for markers of apoptosis and Th17/T_reg differentiation, while effector T cells showed enrichment of anergy-related pathways. Differentially expressed genes in regulatory T cells suggested dysfunctional p53, cell death, and TNFR2 signaling. Using more sensitive technology and more precise units of measure, we identify cell-type specific, novel inflammatory and regulatory pathways. Based on our findings, we suggest a novel model involving four convergent arms of dysregulation: persistent hyperactivation of innate and adaptive immunity via classical monocytes and CD4 naïve T cells, regulatory T cell dysfunction, and effector T cell anergy. We further our understanding of the immunopathology of sarcoidosis and point to novel therapeutic targets.

Microenvironment-related prognostic genes in esophageal cancer

Background

Esophageal cancer is one of the most common malignant tumors. The role of tumor microenvironment in esophageal cancer is unclear.

Methods

The gene expression profiles and clinical data of 158 patients with esophageal cancer were extracted from The Cancer Genome Atlas database. Immune scores and stromal scores were calculated based on ESTIMATE algorithm. According to different immune/stromal scores, differentially expressed genes (DEGs) were identified. The function enrichment, protein interactions of shared DEGs and their associations with overall survival were analyzed.

Results

In regard to the association of the immune/stromal scores and disease stage, pathological type and overall survival, only the stromal scores among the different stages were significantly different (P=0.015). In the high immune and stromal score groups, 603 shared up-regulated genes were found. The related function and pathways included regulation of lymphocyte activation, cytokine binding and chemokine signaling pathway. Protein-protein interaction analysis showed that ITGAM had the most connections, followed by CXCL10 and CCR2. High expression of 11 genes, including MS4A7, TMIGD3, MS4A4A, EVI2A, MS4A6A, FCER1G, AIF1, GNGT2, LCP2, DNAJC5B and RNASE6, were found to be associated with shorter overall survival.

Conclusions

Microenvironment-associated functions and pathways were analyzed in esophageal cancer, and 11 microenvironment-associated genes were correlated to poor prognoses. Further studies on these genes may be helpful to understand the tumor microenvironment and provide new therapies for esophageal cancer.

Association between polymorphisms of FKBP5 gene and suicide attempt in a Mexican population: A case-control study

Five polymorphisms (rs4713916, rs4713902, rs1360780, rs9296158 and rs3800373) of FKBP5 gene were analyzed in a case-control study comprising 423 Mexican individuals (146 individuals with suicide attempt and 277 controls). The SNP's were genotyped using the TaqMan-allelic assay. Genotype and allele frequencies were compared between the two groups, then the association between FKBP5 gene polymorphisms and suicide attempt was analyzed. We found a significant association of rs1360780 T minor allele (All, OR = 1.80, 95 % CI = 1.35-2.41, P = 0.0005; Males, OR = 2.25, 95 % CI = 1.44-3.50, P = 0.0002) as a suicide behavior risk factor. Conversely, rs3800373 C minor allele (All, OR = 0.61, 95 % CI = 0.46-0.83; P = 0.0013; Females, OR = 0.33, 95 % CI = 0.22-0.50; P = 0.0001) and the A-C-T-A-C haplotype (OR = 0.06, 95 % CI = 0.01-0.36; P = 0.002) were significantly associated as protective factors. No association was observed with the other SNP's. Our study suggests that SNP's in FKBP5 gene contribute to suicide behavior pathogenesis.