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Single-Nucleotide Variants in the AIM2 - Absent in Melanoma 2 Gene (rs1103577) Associated With Protection for Tuberculosis.

ABSTRACT: Tuberculosis (TB) remains a serious public health burden worldwide. TB is an infectious disease caused by the Mycobacterium tuberculosis Complex. Innate immune response is critical for controlling mycobacterial infection. NOD-like receptor pyrin domain containing 3/ absent in melanoma 2 (NLRP3/AIM2) inflammasomes are suggested to play an important role in TB. NLRP3/AIM2 mediate the release of pro-inflammatory cytokines IL-1β and IL-18 to control M. tuberculosis infection. Variants of genes involved in inflammasomes may contribute to elucidation of host immune responses to TB infection. The present study evaluated single-nucleotide variants (SNVs) in inflammasome genes AIM2 (rs1103577), CARD8 (rs2009373), and CTSB (rs1692816) in 401 patients with pulmonary TB (PTB), 133 patients with extrapulmonary TB (EPTB), and 366 healthy control (HC) subjects with no history of TB residing in the Amazonas state. Quantitative Real Time PCR was performed for allelic discrimination. The SNV of AIM2 (rs1103577) is associated with protection for PTB (padj: 0.033, ORadj: 0.69, 95% CI: 0.49-0.97). CTSB (rs1692816) is associated with reduced risk for EPTB when compared with PTB (padj: 0.034, ORadj: 0.50, 95% CI: 0.27-0.94). Serum IL-1β concentrations were higher in patients with PTB than those in HCs (p = 0,0003). The SNV rs1103577 of AIM2 appeared to influence IL-1β release. In a dominant model, individuals with the CC genotype (mean 3.78 ± SD 0.81) appeared to have a higher level of IL-1β compared to carriers of the T allele (mean 3.45 ± SD 0.84) among the patients with PTB (p = 0,0040). We found that SNVs of AIM2 and CTSB were associated with TB, and the mechanisms involved in this process require further study.

SUBMITTER: Figueira MBA

PROVIDER: S-EPMC8047195 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:AIM2 binds dsDNA and associates with ASC through their PYDs to form an inflammasome. RESULTS:The AIM2 PYD structure illustrates distinct charge distribution and a unique hydrophobic patch. CONCLUSION:The AIM2 PYD may bind the ASC PYD and the AIM2 HIN domain through overlapping surface. SIGNIFICANCE:These findings provide insights into the mechanisms of AIM2 autoinhibition and inflammasome assembly. Absent in melanoma 2 (AIM2) is a cytosolic double-stranded (dsDNA) sensor essential for innate immune responses against DNA viruses and bacteria such as Francisella and Listeria. Upon dsDNA engagement, the AIM2 amino-terminal pyrin domain (PYD) is responsible for downstream signaling to the adapter protein apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) through homotypic PYD-PYD interactions and the assembly of an inflammasome. Toward a better understanding of the AIM2 signaling mechanism, we determined the crystal structure of the human AIM2 PYD. The structure reveals a death domain fold with a short ?3 helix that is buttressed by a highly conserved lysine residue at the ?2 helix, which may stabilize the ?3 helix for potential interaction with partner domains. The surface of the AIM2 PYD exhibits distinct charge distribution with highly acidic ?1-?2 helices and highly basic ?5-?6 helices. A prominent solvent-exposed hydrophobic patch formed by residues Phe-27 and Phe-28 at the ?2 helix resembles a similar surface involved in the death effector domain homotypic interactions. Docking studies suggest that the AIM2 PYD may bind the AIM2 hematopoietic interferon-inducible nuclear (HIN) domain or ASC PYD using overlapping surface near the ?2 helix. This may ensure that AIM2 interacts with the downstream adapter ASC only upon release of the autoinhibition by the dsDNA ligand. Our work thus unveils novel structural features of the AIM2 PYD and provides insights into the potential mechanisms of the PYD-HIN and PYD-PYD interactions important for AIM2 autoinhibition and inflammasome assembly.

Project description:Absent in Melanoma 2 (AIM2) is a member of the HIN-200 family of hematopoietic, IFN-inducible, nuclear proteins, associated with both, infection defense and tumor pathology. Recently, AIM2 was found to act as a DNA sensor in innate immunity. In addition, we and others have previously demonstrated a high frequency of AIM2-alterations in microsatellite unstable (MSI-H) tumors. To further elucidate AIM2 function in colorectal tumors, we here addressed AIM2-responsive target genes by microarray based gene expression profiling of 22 244 human genes. A total of 111 transcripts were significantly upregulated, whereas 80 transcripts turned out to be significantly downregulated in HCT116 cells, constitutively expressing AIM2, compared with AIM2-negative cells. Among the upregulated genes that were validated by quantitative PCR and western blotting we recognized several interferon-stimulated genes (ISGs: IFIT1, IFIT2, IFIT3, IFI6, IRF7, ISG15, HLA-DRA, HLA-DRB, TLR3 and CIITA), as well as genes involved in intercellular adhesion and matrix remodeling. Expression of ISGs correlated with expression of AIM2 in 10 different IFN-γ treated colorectal cancer cell lines. Moreover, small interfering RNA-mediated knock-down of AIM2 resulted in reduced expression of HLA-DRA, HLA-DRB and CIITA in IFN-γ-treated cells. IFN-γ independent induction of HLA-DR genes and their encoded proteins was also demonstrated upon doxycyclin-regulated transient induction of AIM2. Luciferase reporter assays revealed induction of the HLA-DR promoter upon AIM2 transfection in different cell lines. STAT-signaling was not involved in IFN-γ independent induction of ISGs, arguing against participation of cytokines released in an autostimulating manner. Our data indicate that AIM2 mediates both IFN-γ dependent and independent induction of several ISGs, including genes encoding the major histocompatibility complex (MHC) class II antigens HLA-DR-α and -β. This suggests a novel role of the IFN/AIM2/ISG cascade likewise in cancer cells.

Project description:BackgroundIn recent years the number of human genetic variants deposited into the publicly available databases has been increasing exponentially. The latest version of dbSNP, for example, contains ~50 million validated Single Nucleotide Variants (SNVs). SNVs make up most of human variation and are often the primary causes of disease. The non-synonymous SNVs (nsSNVs) result in single amino acid substitutions and may affect protein function, often causing disease. Although several methods for the detection of nsSNV effects have already been developed, the consistent increase in annotated data is offering the opportunity to improve prediction accuracy.ResultsHere we present a new approach for the detection of disease-associated nsSNVs (Meta-SNP) that integrates four existing methods: PANTHER, PhD-SNP, SIFT and SNAP. We first tested the accuracy of each method using a dataset of 35,766 disease-annotated mutations from 8,667 proteins extracted from the SwissVar database. The four methods reached overall accuracies of 64%-76% with a Matthew's correlation coefficient (MCC) of 0.38-0.53. We then used the outputs of these methods to develop a machine learning based approach that discriminates between disease-associated and polymorphic variants (Meta-SNP). In testing, the combined method reached 79% overall accuracy and 0.59 MCC, ~3% higher accuracy and ~0.05 higher correlation with respect to the best-performing method. Moreover, for the hardest-to-define subset of nsSNVs, i.e. variants for which half of the predictors disagreed with the other half, Meta-SNP attained 8% higher accuracy than the best predictor.ConclusionsHere we find that the Meta-SNP algorithm achieves better performance than the best single predictor. This result suggests that the methods used for the prediction of variant-disease associations are orthogonal, encoding different biologically relevant relationships. Careful combination of predictions from various resources is therefore a good strategy for the selection of high reliability predictions. Indeed, for the subset of nsSNVs where all predictors were in agreement (46% of all nsSNVs in the set), our method reached 87% overall accuracy and 0.73 MCC. Meta-SNP server is freely accessible at http://snps.biofold.org/meta-snp.

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Single-Nucleotide Variants in the AIM2 - Absent in Melanoma 2 Gene (rs1103577) Associated With Protection for Tuberculosis.

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