Genetic association analysis of ATG16L1 rs2241880, rs6758317 and ATG16L2 rs11235604 polymorphisms with rheumatoid arthritis in a Chinese population

Analysis of TLR10 gene polymorphisms in patients with rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a chronic systemic disease characterized by inflammatory synovitis, and genetic factors play the greatest role in RA. This study aimed to investigate the relationship between Toll-like receptor 10(TLR10) gene polymorphisms and susceptibility to RA.

METHODS

A total of 271 patients with RA and an equal number of healthy controls were included, and the TLR10 rs2101521, rs10004195 and rs11725309 loci were genotyped by time-of-flight mass spectrometry.

RESULTS

Compared with healthy controls, Individuals carrying the rs2101521 G allele had an increased risk of developing RA (P = 0.01; odds ratio (OR) = 1.367; 95 % confidence interval (CI): 1.076-1.736). Individuals with the rs2101521 GG genotype had a greater risk of RA (P = 0.01; OR = 1.816; 95 % CI: 1.161-2.984). Stratified analysis demonstrated a greater prevalence of positive anti-cyclic citrullinated peptide (CCP)antibody in patients carrying the rs2101521 G allele (P = 0.03). Additionally, patients with the rs11725309 CT genotype had elevated levels of C-reactive protein (CRP)(P = 0.007).

CONCLUSION

In conclusion, TLR10 gene polymorphisms are associated with RA susceptibility.

Atg16l2 augments Nlrc4 inflammasome activation by facilitating NAIPs-NLRC4 association

As cytoplasmic protein complexes that are pivotal for innate immunity, inflammasomes act primarily through the detection of pathogen- or danger-associated molecular patterns. Nucleotide oligomerisation domain-like receptor family and caspase activation recruitment domain-containing protein 4 (NLRC4) inflammasomes identify and eliminate intracellular pathogens, a process contingent on the ligand-recognition capabilities of neuronal apoptosis inhibitory proteins (NAIPs). Upon detection of specific molecules indicative of intracellular infection, NAIPs discern distinct pathogenic components and subsequently transmit signals to NLRC4, thus initiating their activation and triggering an inflammatory response. However, the mechanisms underlying NLRC4 inflammasome remain unclear. In this study, we elucidated the critical role of ATG16L2 in activating the NLRC4 inflammasome. ATG16L2-deficient macrophages exhibited reduced NLRC4 inflammasome activation, characterised by decreased oligomerisation of apoptosis-associated speck-like protein containing a CARD and attenuated cleavage of Pro-caspase-1, Pro-IL-1β and gasdermin D. Co-immunoprecipitation assays revealed an interaction between ATG16L2 and NAIPs. Furthermore, ATG16L2 enhanced the association between NAIPs and NLRC4 by binding to NAIPs. For ATG16L2-knockout mice infected with Salmonella typhimurium, pathogen clearance and survival rates markedly decreased. Collectively, our findings suggest that ATG16L2 is a significant modulator of the innate immune system, influencing the activity of the NLRC4 inflammasome and the host's defensive response to intracellular pathogens.

Modulation of the immunity and inflammation by autophagy

Autophagy, a highly conserved cellular self-degradation pathway, has emerged with novel roles in the realms of immunity and inflammation. Genome-wide association studies have unveiled a correlation between genetic variations in autophagy-related genes and heightened susceptibility to autoimmune and inflammatory diseases. Subsequently, substantial progress has been made in unraveling the intricate involvement of autophagy in immunity and inflammation through functional studies. The autophagy pathway plays a crucial role in both innate and adaptive immunity, encompassing various key functions such as pathogen clearance, antigen processing and presentation, cytokine production, and lymphocyte differentiation and survival. Recent research has identified novel approaches in which the autophagy pathway and its associated proteins modulate the immune response, including noncanonical autophagy. This review provides an overview of the latest advancements in understanding the regulation of immunity and inflammation through autophagy. It summarizes the genetic associations between variants in autophagy-related genes and a range of autoimmune and inflammatory diseases, while also examining studies utilizing transgenic animal models to uncover the in vivo functions of autophagy. Furthermore, the review delves into the mechanisms by which autophagy dysregulation contributes to the development of three common autoimmune and inflammatory diseases and highlights the potential for autophagy-targeted therapies.

The role of ATG16L2 in autophagy and disease

Macroautophagy/autophagy, a fundamental cell process for nutrient recycling and defense against pathogens (termed xenophagy), is crucial to human health. ATG16L2 (autophagy related 16 like 2) is an autophagic protein and a paralog of ATG16L1. Both proteins are implicated in similar diseases such as cancer and other chronic diseases; however, most autophagy studies to date have primarily focused on the function of ATG16L1, with ATG16L2 remaining uncharacterized and understudied. Overexpression of ATG16L2 has been reported in various cancers including colorectal, gastric, and prostate carcinomas, whereas altered methylation of ATG16L2 has been associated with lung cancer formation and poorer response to therapy in leukemia. In addition, ATG16L2 polymorphisms have been implicated in a range of other diseases including inflammatory bowel diseases and neurodegenerative disorders. Despite this likely role in human health, the function of this enigmatic protein in autophagy remains unknown. Here, we review current studies on ATG16L2 and collate evidence that suggests that this protein is a potential modulator of autophagy as well as the implications this has on pathogenesis.Abbreviations: ATG5: autophagy related 5; ATG12: autophagy related 12; ATG16L1: autophagy related 16 like 1; ATG16L2: autophagy related 16 like 2; CD: Crohn disease; IBD: inflammatory bowel diseases; IRGM: immunity related GTPase M; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; PE: phosphatidylethanolamine; RB1CC1: RB1 inducible coiled-coil 1; SLE: systemic lupus erythematosus; WIPI2B: WD repeat domain, phosphoinositide interacting 2B.

Associations between ATG16L1 gene polymorphism and antineutrophil cytoplasmic antibody‐associated vasculitis in the Chinese Guangxi population: A case–control study

Background

Antineutrophil cytoplasmic antibody (ANCA)‐associated vasculitis (AAV) is an autoimmune disease often accompanied by rapidly progressive renal failure, and the genetic background is still unknown. Our study was performed to test whether autophagy‐related 16 like 1 (ATG16L1) rs4663402 and rs4663396 single nucleotide polymorphisms (SNPs) were associated with AAV in the Chinese Guangxi population.

Methods

One hundred seventy seven unrelated AAV patients and 216 healthy controls were included in this case–control study. Multiplex polymerase chain reaction combined with high‐throughput sequencing was used for typing, and SNPStats and SHEsis were used for association analysis, pairwise linkage disequilibrium, and haplotype analysis.

Results

rs4663402 and rs4663396 were in Hardy–Weinberg equilibrium in AAV and control groups. The frequencies of rs4663402 AA, AT, and TT genotypes were 82.5%, 16.9%, and 0.6%, respectively, in patients with AAV, and 83.5%, 16.2%, and 0.5%, respectively, in controls. The frequencies of rs4663396 CC, CT, and TT genotypes were 63.8%, 33.9%, and 2.3%, respectively, in patients with AAV, and 69.2%, 26.6%, and 4.2%, respectively, in controls. Haplotype analysis revealed two SNPs in a single haplotype block (D′ = 1.0). Our logistic regression adjusted for sex and age showed no association between rs4663402 and rs4663396 and the risk for AAV in genetic models (p > 0.05). However, ATG16L1 rs4663396 CC and CT + TT genotypes exhibited statistically significant differences in the incidence of arthralgia (p = 0.03).

Conclusions

Our results indicated that ATG16L1 rs4663402 and rs4663396 polymorphisms were not associated with AAV in the Chinese Guangxi population. ATG16L1 rs4663396 CT + TT genotype may be associated with arthralgia.

Transcriptome profile of spleen tissues from locally-adapted Kenyan pigs (Sus scrofa) experimentally infected with three varying doses of a highly virulent African swine fever virus genotype IX isolate: Ken12/busia.1 (ken-1033)

Background

African swine fever (ASF) is a lethal hemorrhagic disease affecting domestic pigs resulting in up to 100% mortality rates caused by the ASF virus (ASFV). The locally-adapted pigs in South-western Kenya have been reported to be resilient to disease and harsh climatic conditions and tolerate ASF; however, the mechanisms by which this tolerance is sustained remain largely unknown. We evaluated the gene expression patterns in spleen tissues of these locally-adapted pigs in response to varying infective doses of ASFV to elucidate the virus-host interaction dynamics.

Methods

Locally adapted pigs (n = 14) were experimentally infected with a high dose (1x10⁶HAD₅₀), medium dose (1x10⁴HAD₅₀), and low dose (1x10²HAD₅₀) of the highly virulent genotype IX ASFV Ken12/busia.1 (Ken-1033) isolate diluted in PBS and followed through the course of infection for 29 days. The in vivo pig host and ASFV pathogen gene expression in spleen tissues from 10 pigs (including three from each infective group and one uninfected control) were analyzed in a dual-RNASeq fashion. We compared gene expression between three varying doses in the host and pathogen by contrasting experiment groups against the naïve control.

Results

A total of 4954 differentially expressed genes (DEGs) were detected after ASFV Ken12/1 infection, including 3055, 1771, and 128 DEGs in the high, medium, and low doses, respectively. Gene ontology and KEGG pathway analysis showed that the DEGs were enriched for genes involved in the innate immune response, inflammatory response, autophagy, and apoptosis in lethal dose groups. The surviving low dose group suppressed genes in pathways of physiopathological importance. We found a strong association between severe ASF pathogenesis in the high and medium dose groups with upregulation of proinflammatory cytokines and immunomodulation of cytokine expression possibly induced by overproduction of prostaglandin E synthase (4-fold; p < 0.05) or through downregulation of expression of M1-activating receptors, signal transductors, and transcription factors. The host-pathogen interaction resulted in induction of expression of immune-suppressive cytokines (IL-27), inactivation of autophagy and apoptosis through up-regulation of NUPR1 [5.7-fold (high dose) and 5.1-fold (medium dose) [p < 0.05] and IL7R expression. We detected repression of genes involved in MHC class II antigen processing and presentation, such as cathepsins, SLA-DQB1, SLA-DOB, SLA-DMB, SLA-DRA, and SLA-DQA in the medium and high dose groups. Additionally, the host-pathogen interaction activated the CD8⁺ cytotoxicity and neutrophil machinery by increasing the expression of neutrophils/CD8⁺ T effector cell-recruiting chemokines (CCL2, CXCL2, CXCL10, CCL23, CCL4, CXCL8, and CXCL13) in the lethal high and medium dose groups. The recovered pigs infected with ASFV at a low dose significantly repressed the expression of CXCL10, averting induction of T lymphocyte apoptosis and FUNDC1 that suppressed neutrophilia.

Conclusions

We provide the first in vivo gene expression profile data from locally-adapted pigs from south-western Kenya following experimental infection with a highly virulent ASFV genotype IX isolate at varying doses that mimic acute and mild disease. Our study showed that the locally-adapted pigs induced the expression of genes associated with tolerance to infection and repression of genes involved in inflammation at varying levels depending upon the ASFV dose administered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08754-8.

Machine Learning-Based Models for Detection of Biomarkers of Autoimmune Diseases by Fragmentation and Analysis of miRNA Sequences

Thanks to high-throughput data technology, microRNA analysis studies have evolved in early disease detection. This work introduces two complete models to detect the biomarkers of two autoimmune diseases, multiple sclerosis and rheumatoid arthritis, via miRNA analysis. Based on work the authors published previously, both introduced models involve complete pipelines of text mining methods, integrated with traditional machine learning methods, and LSTM deep learning. This work also studies the fragmentation of miRNA sequences to reduce the needed processing time and computational power. Moreover, this work studies the impact of obtaining two different library preparation kits (NEBNEXT and NEXTFLEX) on the detection accuracy for rheumatoid arthritis. Additional experiments are applied to the proposed models based on three different transcriptomic datasets. The results denote that the transcriptomic fragmentation model reported a biomarker detection accuracy of 96.45% on a sequence fragment size of 0.2, indicating a significant reduction in execution power while retaining biomarker detection accuracy. On the other hand, the LSTM model obtained a promising detection accuracy of 72%, implying savings in feature engineering processing. Additionally, the fragmentation model and the LSTM model reported 22.4% and 87.5% less execution time than work in the literature, respectively, denoting a considerable execution power reduction.