dbAPIS: a database of anti-prokaryotic immune system genes.

Anti-prokaryotic immune system (APIS) proteins, typically encoded by phages, prophages, and plasmids, inhibit prokaryotic immune systems (e.g. restriction modification, toxin-antitoxin, CRISPR-Cas). A growing number of APIS genes have been characterized and dispersed in the literature. Here we developed dbAPIS (https://bcb.unl.edu/dbAPIS), as the first literature curated data repository for experimentally verified APIS genes and their associated protein families. The key features of dbAPIS include: (i) experimentally verified APIS genes with their protein sequences, functional annotation, PDB or AlphaFold predicted structures, genomic context, sequence and structural homologs from different microbiome/virome databases; (ii) classification of APIS proteins into sequence-based families and construction of hidden Markov models (HMMs); (iii) user-friendly web interface for data browsing by the inhibited immune system types or by the hosts, and functions for searching and batch downloading of pre-computed data; (iv) Inclusion of all types of APIS proteins (except for anti-CRISPRs) that inhibit a variety of prokaryotic defense systems (e.g. RM, TA, CBASS, Thoeris, Gabija). The current release of dbAPIS contains 41 verified APIS proteins and ∼4400 sequence homologs of 92 families and 38 clans. dbAPIS will facilitate the discovery of novel anti-defense genes and genomic islands in phages, by providing a user-friendly data repository and a web resource for an easy homology search against known APIS proteins.

Machine learning-based prediction of diabetic patients using blood routine data.

Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked until individuals manifest noticeable symptoms of the condition. This study aimed to address this gap by collecting comprehensive datasets, including 1000 instances of blood routine data from diabetes patients and an equivalent dataset from healthy individuals. To differentiate diabetes patients from their healthy counterparts, a computational framework was established, encompassing eXtreme Gradient Boosting (XGBoost), random forest, support vector machine, and elastic net algorithms. Notably, the XGBoost model emerged as the most effective, exhibiting superior predictive results with an area under the receiver operating characteristic curve (AUC) of 99.90% in the training set and 98.51% in the testing set. Moreover, the model showcased commendable performance during external validation, achieving an overall accuracy of 81.54%. The probability generated by the model serves as a risk score for diabetes susceptibility. Further interpretability was achieved through the utilization of the Shapley additive explanations (SHAP) algorithm, identifying pivotal indicators such as mean corpuscular hemoglobin concentration (MCHC), lymphocyte ratio (LY%), standard deviation of red blood cell distribution width (RDW-SD), and mean corpuscular hemoglobin (MCH). This enhances our understanding of the predictive mechanisms underlying diabetes. To facilitate the application in clinical and real-life settings, a nomogram was created based on the logistic regression algorithm, which can provide a preliminary assessment of the likelihood of an individual having diabetes. Overall, this research contributes valuable insights into the predictive modeling of diabetes, offering potential applications in clinical practice for more effective and timely diagnoses.

dbCAN3: automated carbohydrate-active enzyme and substrate annotation.

Carbohydrate active enzymes (CAZymes) are made by various organisms for complex carbohydrate metabolism. Genome mining of CAZymes has become a routine data analysis in (meta-)genome projects, owing to the importance of CAZymes in bioenergy, microbiome, nutrition, agriculture, and global carbon recycling. In 2012, dbCAN was provided as an online web server for automated CAZyme annotation. dbCAN2 (https://bcb.unl.edu/dbCAN2) was further developed in 2018 as a meta server to combine multiple tools for improved CAZyme annotation. dbCAN2 also included CGC-Finder, a tool for identifying CAZyme gene clusters (CGCs) in (meta-)genomes. We have updated the meta server to dbCAN3 with the following new functions and components: (i) dbCAN-sub as a profile Hidden Markov Model database (HMMdb) for substrate prediction at the CAZyme subfamily level; (ii) searching against experimentally characterized polysaccharide utilization loci (PULs) with known glycan substates of the dbCAN-PUL database for substrate prediction at the CGC level; (iii) a majority voting method to consider all CAZymes with substrate predicted from dbCAN-sub for substrate prediction at the CGC level; (iv) improved data browsing and visualization of substrate prediction results on the website. In summary, dbCAN3 not only inherits all the functions of dbCAN2, but also integrates three new methods for glycan substrate prediction.

dbCAN-seq update: CAZyme gene clusters and substrates in microbiomes.

Carbohydrate Active EnZymes (CAZymes) are significantly important for microbial communities to thrive in carbohydrate rich environments such as animal guts, agricultural soils, forest floors, and ocean sediments. Since 2017, microbiome sequencing and assembly have produced numerous metagenome assembled genomes (MAGs). We have updated our dbCAN-seq database (https://bcb.unl.edu/dbCAN_seq) to include the following new data and features: (i) ∼498 000 CAZymes and ∼169 000 CAZyme gene clusters (CGCs) from 9421 MAGs of four ecological (human gut, human oral, cow rumen, and marine) environments; (ii) Glycan substrates for 41 447 (24.54%) CGCs inferred by two novel approaches (dbCAN-PUL homology search and eCAMI subfamily majority voting) (the two approaches agreed on 4183 CGCs for substrate assignments); (iii) A redesigned CGC page to include the graphical display of CGC gene compositions, the alignment of query CGC and subject PUL (polysaccharide utilization loci) of dbCAN-PUL, and the eCAMI subfamily table to support the predicted substrates; (iv) A statistics page to organize all the data for easy CGC access according to substrates and taxonomic phyla; and (v) A batch download page. In summary, this updated dbCAN-seq database highlights glycan substrates predicted for CGCs from microbiomes. Future work will implement the substrate prediction function in our dbCAN2 web server.

Nanoemulsions Stable against Ostwald Ripening.

Ostwald ripening, the dominant mechanism of droplet size growth for an O/W nanoemulsion at high surfactant concentrations, depends on micelles in the water phase and high aqueous solubility of oil, especially for spontaneously formed nanoemulsions. In our study, O/W nanoemulsions were formed spontaneously by mixing a water phase with an oil phase containing fatty alcohol polyoxypropylene polyoxyethylene ether (APE). By monitoring periodically the droplet size of the nanoemulsions via dynamic light scattering, we demonstrated that the formed O/W nanoemulsions are stable against Ostwald ripening, i.e., droplet growth. In contrast, the nanoemulsion droplets grew with the addition of micelles, demonstrating the pivotal role of the presence of micelles in the water phase in the occurrence of Ostwald ripening. The influence of the initial phase of APE, the oil or water phase in which APE is present, on the micelle formation is discussed by the partition coefficient and interfacial adsorption of APE between the oil and water phase using a surface and interfacial tensiometer. In addition, the spontaneously formed O/W nanoemulsion, which is stable against Ostwald ripening, can be used as a nanocarrier for the delivery of water-insoluble pesticides. These results provide a novel approach for the preparation of stable nanoemulsions and contribute to elucidating the mechanism of instability of nanoemulsions.

Precise Control of Crystallization and Phase-Transition with Green Anti-Solvent in Wide-Bandgap Perovskite Solar Cells with Open-Circuit Voltage Exceeding 1.25 V.

Wide-bandgap perovskite solar cells (PSCs) have attracted a lot of attention due to their application in tandem solar cells. However, the open-circuit voltage (VOC ) of wide-bandgap PSCs is dramatically limited by high defect density existing at the interface and bulk of the perovskite film. Here, an anti-solvent optimized adduct to control perovskite crystallization strategy that reduces nonradiative recombination and minimizes VOC deficit is proposed. Specifically, an organic solvent with similar dipole moment, isopropanol (IPA) is added into ethyl acetate (EA) anti-solvent, which is beneficial to form PbI2 adducts with better crystalline orientation and direct formation of α-phase perovskite. As a result, EA-IPA (7-1) based 1.67 eV PSCs deliver a power conversion efficiency of 20.06% and a VOC of 1.255 V, which is one of the remarkable values for wide-bandgap around 1.67 eV. The findings provide an effective strategy for controlling crystallization to reduce defect density in PSCs.

Photopolymerized Features via Beam Pen Lithography as a Novel Tool for the Generation of Large Area Protein Micropatterns.

A cantilever-free scanning probe lithography (CF-SPL)-based method for the rapid polymerization of nanoscale features on a surface via crosslinking and thiol-acrylate photoreactions is described, wherein the nanoscale position, height, and diameter of each feature can be finely and independently tuned. With precise spatiotemporal control over the illumination pattern, beam pen lithography (BPL) allows for the photo-crosslinking of polymers into ultrahigh resolution features over centimeter-scale areas using massively parallel >160 000 pen arrays of individually addressable pens that guide and focus light onto the surface with sub-diffraction resolution. The photoinduced crosslinking reaction of the ink material, which is composed of photoinitiator, diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide, poly(ethylene glycol) diacrylate, and thiol-modified functional binding molecules (i.e., thiol-PEG-biotin or 16-mercaptohexanoic acid), proceeds to ≈80% conversion with UV exposure (72 mW cm-2 ) for short time periods (0.5 s). Such polymer patterns are further reacted with proteins (streptavidin and fibronectin) to yield protein arrays with feature arrangements at high resolution and densities controlled by local UV exposure. This platform, which combines polymer photochemistry and massive arrays of scanning probes, constitutes a new approach to making biomolecular microarrays in a high-throughput and high-yielding manner, opening new routes for biochip synthesis, bioscreening, and cell biology research.

AIE-YOLO: Auxiliary Information Enhanced YOLO for Small Object Detection.

Small object detection is one of the key challenges in the current computer vision field due to the low amount of information carried and the information loss caused by feature extraction. You Only Look Once v5 (YOLOv5) adopts the Path Aggregation Network to alleviate the problem of information loss, but it cannot restore the information that has been lost. To this end, an auxiliary information-enhanced YOLO is proposed to improve the sensitivity and detection performance of YOLOv5 to small objects. Firstly, a context enhancement module containing a receptive field size of 21×21 is proposed, which captures the global and local information of the image by fusing multi-scale receptive fields, and introduces an attention branch to enhance the expressive ability of key features and suppress background noise. To further enhance the feature expression ability of small objects, we introduce the high- and low-frequency information decomposed by wavelet transform into PANet to participate in multi-scale feature fusion, so as to solve the problem that the features of small objects gradually disappear after multiple downsampling and pooling operations. Experiments on the challenging dataset Tsinghua-Tencent 100 K show that the mean average precision of the proposed model is 9.5% higher than that of the original YOLOv5 while maintaining the real-time speed, which is better than the mainstream object detection models.

Cetrimonium bromide promotes the clearance of lipids by activating the TFEB-mediated autophagosome-lysosome pathway in hepatic cells.

Autophagy plays a key role in the metabolism of macromolecules via the degradative abilities of the lysosome. Transcription factor EB (TFEB) regulates autophagosome biogenesis and lysosome function, and promoting TFEB activity has emerged as a potential strategy for the treatment of metabolic disorders. Herein, we report that cetrimonium bromide (CTAB; a quaternary ammonium compound) promotes autophagy and lysosomal biogenesis by inducing the nuclear translocation of TFEB in hepatic cells. Knockdown of TFEB mediated by short hairpin RNA inhibits CTAB-induced autophagy and lysosomal biogenesis. Mechanistically, CTAB treatment inhibits the Akt-mTORC1 signaling pathway. Moreover, CTAB treatment significantly increases lipid metabolism in both palmitate- and oleate-treated HepG2 cells, and this increase was attenuated by knockdown of TFEB. Collectively, our results indicate that CTAB activates the autophagosome-lysosome pathway via inducing the nuclear translocation of TFEB by inhibiting the mTORC1 signaling pathway. These results add to the collective understanding of TFEB function and provide new insights into CTAB-mediated lipid metabolism.

Electrochemical Tri- and Difluoromethylation-Triggered Cyclization Accompanied by the Oxidative Cleavage of Indole Derivatives.

Considering their unique roles in organic synthesis, and pharmaceutical and agrochemical applications, the development of fluoroalkylation, cyclization, and indole oxidative cleavage are important topics. Herein, an unprecedented electrochemical tri- and difluoromethylation/cyclization/indole oxidative cleavage process occurring in an undivided cell is presented. The protocol employs a readily prepared Langlois reagent as the fluoroalkyl source, affording a series of tri- or difluoromethylated 2-(2-acetylphenyl)isoquinoline-1,3-diones in good yields with excellent stereoselectivity. It is worth noting that this new methodology merges the fluoroalkylation/cyclization of N-substituted acrylamide alkenes with the oxidative cleavage of an indole C(2)=C(3) bond under external oxidant-free conditions.

Altered expression of serum miR-106a, miR-19b, miR-17, and PTEN in patients with idiopathic membranous nephropathy.

BACKGROUND: To find new diagnostic markers for idiopathic membranous nephropathy (IMN) and also conduct preliminary explorations into the possible pathogenesis of IMN by comparing the expression of microRNA-451a (miR-451a), miR-106a, miR-19b, miR-17, and phosphatase and tensin homolog (PTEN) protein in the serum of patients with IMN and healthy controls. METHODS: The expression levels of miR-451a, miR-106a, miR-19b, and miR-17 in the serum of patients in the IMN group (n = 55, age: 50.2 ± 12.1 years) and the control group (n = 58, age 47.4 ± 13.1 years) were measured by quantitative real-time polymerase chain reaction (qRT-PCR), and the concentration of serum PTEN protein was determined by enzyme-linked immunosorbent assay (ELISA). RESULTS: Compared with the control group, the expression of miR-106a, miR-19b, and miR-17 was decreased significantly in the IMN group, whereas PTEN protein concentration was increased significantly in the IMN group. The areas under the receiver operating characteristic curve (AUC) of serum miR-106a, miR-19b, miR-17, and PTEN were 0.66 (95% confidence interval [CI], 0.56-0.76), 0.81 (95% CI, 0.73-0.89), 0.69 (95% CI, 0.59-0.79), and 0.86 (95% CI, 0.79-0.93), respectively. The level of serum PTEN protein was negatively correlated with the expression of miR-106a and miR-19b. PTEN concentration was positively correlated with serum urea (Urea), creatinine (Crea), cystatin C (Cysc), 24 h urine total protein (24 h-UP) and negatively correlated with albumin (Alb) and estimated glomerular filtration rate (eGFR). CONCLUSIONS: MiR-106a, miR-19b, miR-17, and PTEN are involved in the pathogenesis of IMN and may become new biomarkers for the diagnosis of IMN.

Comprehensive Analyses of the Immunoglobulin Proteome for the Classification of Glomerular Diseases.

Glomerular diseases, which are currently diagnosed using an invasive renal biopsy, encompass numerous disease subtypes that often display similar clinical manifestations even though they have different therapeutic regimes. Therefore, a noninvasive assay is needed to classify and guide the treatment of glomerular diseases. Here, we develop and apply a high-throughput and quantitative microarray platform to characterize the immunoglobulin proteome in the serum from 419 healthy and diseased patients. The immunoglobulin proteome-clinical variable correlation network revealed novel pathological mechanisms of glomerular diseases. Furthermore, an immunoglobulin proteome-multivariate normal distribution (IP-MiND) mathematical model based on the correlation network classified healthy volunteers and patients with idiopathic membranous nephropathy with an average recall of 48% (23-80%) in the discovery cohort and 64% (63-65%) in an independent validation cohort. Our results demonstrate the translational utility of our microarray platform to glomerular diseases as well as its clinical potential in characterizing other human diseases.

Phospholipase-A2 receptor antibody, 24 hours proteinuria, and serum albumin as indicators of cyclophosphamide efficacy in idiopathic membranous nephropathy.

BACKGROUND: We aimed to evaluate cyclophosphamide efficacy in the treatment of idiopathic membranous nephropathy (IMN) and explore the efficacy of phospholipase-A2 receptor antibody (PLA2R-Ab), 24 hours proteinuria, and serum albumin in predicting 6- and 12-month treatment effects. METHODS: A retrospective analysis was performed on 135 patients with IMN who followed up after treatment. The observation points were before, and after 3, 6, and 12 months of treatment. We collected clinical indicator data at each observation point and measured PLA2R-Ab levels before and after 3-month treatment. RESULTS: The remission rates at 3, 6, and 12 months of cyclophosphamide therapy for patients with IMN were 41.4, 74.8, and 76.1%, respectively. Patients in whom PLA2R-Ab turned negative within 3 months had high remission rates at 3, 6, and 12 months after treatment (P < .05). PLA2R-Ab change at 3 months had a strong correlation with 24 hours proteinuria change at 6 months. The change in albumin concentration before and after 3-month treatment was an independent variable related to remission rate at 6 months, and 24 hours proteinuria change before and after 6-month treatment was an independent variable related to remission rate at 12 months after treatment. CONCLUSION: Cyclophosphamide showed good efficacy at 3, 6, and 12 months for patients with IMN. Serum albumin change and PLA2R-Ab change at 3 months can be used as indicators to predict remission at 6 months, respectively. Moreover, 24 hours proteinuria change at 6 months can predict remission at 12 months.

Identification of Two Novel R2R3-MYB Transcription factors, PsMYB114L and PsMYB12L, Related to Anthocyanin Biosynthesis in Paeonia suffruticosa.

Flower color is a charming phenotype with very important ornamental and commercial values. Anthocyanins play a critical role in determining flower color pattern formation, and their biosynthesis is typically regulated by R2R3-MYB transcription factors (TFs). Paeonia suffruticosa is a famous ornamental plant with colorful flowers. However, little is known about the R2R3-MYB TFs that regulate anthocyanin accumulation in P. suffruticosa. In the present study, two R2R3-MYB TFs, namely, PsMYB114L and PsMYB12L, were isolated from the petals of P. suffruticosa 'Shima Nishiki' and functionally characterized. Sequence analysis suggested that PsMYB114L contained a bHLH-interaction motif, whereas PsMYB12L contained two flavonol-specific motifs (SG7 and SG7-2). Subsequently, the in vivo function of PsMYB114L and PsMYB12L was investigated by their heterologous expression in Arabidopsis thaliana and apple calli. In transgenic Arabidopsis plants, overexpression of PsMYB114L and of PsMYB12L caused a significantly higher accumulation of anthocyanins, resulting in purple-red leaves. Transgenic apple calli overexpressing PsMYB114L and PsMYB12L also significantly enhanced the anthocyanins content and resulted in a change in the callus color to red. Meanwhile, gene expression analysis in A. thaliana and apple calli suggested that the expression levels of the flavonol synthase (MdFLS) and anthocyanidin reductase (MdANR) genes were significantly downregulated and the dihydroflavonol 4-reductase (AtDFR) and anthocyanin synthase (AtANS) genes were significantly upregulated in transgenic lines of PsMYB114L. Moreover, the expression level of the FLS gene (MdFLS) was significantly downregulated and the DFR (AtDFR/MdDFR) and ANS (AtANS/MdANS) genes were all significantly upregulated in transgenic lines plants of PsMYB12L. These results indicate that PsMYB114L and PsMYB12L both enhance anthocyanin accumulation by specifically regulating the expression of some anthocyanin biosynthesis-related genes in different plant species. Together, these results provide a valuable resource with which to further study the regulatory mechanism of anthocyanin biosynthesis in P. suffruticosa and for the breeding of tree peony cultivars with novel and charming flower colors.

New Generation of Clickable Nucleic Acids: Synthesis and Active Hybridization with DNA.

Due to the ability to generate oligomers of precise sequence, sequential and stepwise solid-phase synthesis has been the dominant method of producing DNA and other oligonucleotide analogues. The requirement for a solid support, however, and the physical restrictions of limited surface area thereon significantly diminish the efficiency and scalability of these syntheses, thus, negatively affecting the practical applications of synthetic polynucleotides and other similarly created molecules. By employing the robust photoinitiated thiol-ene click reaction, we developed a new generation of clickable nucleic acids (CNAs) with a polythioether backbone containing repeat units of six atoms, matching the spacing of the phosphodiester backbone of natural DNA. A simple, inexpensive, and scalable route was utilized to produce CNA monomers in gram-scale, which indicates the potential to dramatically lower the cost of these DNA mimics and thereby expand the scope of these materials. The efficiency of this approach was demonstrated by the completion of CNA polymerization in 30 seconds, as characterized by size-exclusive chromatography (SEC) and infrared (IR) spectroscopy. CNA/DNA hybridization was demonstrated by gel electrophoresis and used in CdS nanoparticle assembly.

Formation of lipid vesicles in situ utilizing the thiol-Michael reaction.

Synthetic unilamellar liposomes, functionalized to enable novel characteristics and behavior, are of great utility to fields such as drug delivery and artificial cell membranes. However, the generation of these liposomes is frequently highly labor-intensive and time consuming whereas in situ liposome formation presents a potential solution to this problem. A novel method for in situ lipid formation is developed here through the covalent addition of a thiol-functionalized lysolipid to an acrylate-functionalized tail via the thiol-Michael addition reaction with potential for inclusion of additional functionality via the tail. Dilute, stoichiometric mixtures of a thiol lysolipid and an acrylate tail reacted in an aqueous media at ambient conditions for 48 hours reached nearly 90% conversion, forming the desired thioether-containing phospholipid product. These lipids assemble into a high density of liposomes with sizes ranging from 20 nm to several microns in diameter and include various structures ranging from spheres to tubular vesicles with structure and lamellarity dependent upon the catalyst concentration used. To demonstrate lipid functionalization, an acrylate tail possessing a terminal alkyne was coupled into the lipid structure. These functionalized liposomes enable photo-induced polymerization of the terminal alkyne upon irradiation.

Implementation of two distinct wavelengths to induce multistage polymerization in shape memory materials and nanoimprint lithography.

Here, a process is introduced for forming dual stage thiol-Michael/acrylate hybrid networks photocured by two different wavelengths, demonstrating its use in nanoimprint lithography (NIL) and shape memory materials. Initiated with a visible light sensitive photobase and a UV-sensitive radical initiator, thiol-Michael-acrylate hybrid polymerizations were programmed to proceed sequentially and orthogonally, with base-catalyzed thiol-Michael photopolymerization as the first stage and radical mediated acrylate photopolymerization as the second stage. By regulating the photopolymerization formulations, i.e. thiol-to-acrylate ratios, initiator loadings and irradiation conditions, a series of materials with highly tunable mechanical performance was achieved, with ultimate Tg values ranging from 23 to 70 °C. With a photopatternable first stage and a readily reconfigurable second stage, its implementation in nanoimprint lithography (NIL) enabled surface features on the scale of 10 nm to be formed on a photopatterned substrate. Additionally, the dual stage polymer results in a relatively homogenous polymer network with a narrow glass transition temperature (Tg), which enables rapid response in applications as shape memory materials, with shape-fixity values above 95% and shaperecovery values above 99%. With its unique photocuring process and programmable mechanical properties, the two color light controlled photopolymerization can be exploited as a useful tool in a wide range of materials science applications.

Automatic non-proliferative diabetic retinopathy screening system based on color fundus image.

BACKGROUND: Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients. METHODS: This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images. Firstly, the fundus structures, including blood vessels, optic disc and macula, are extracted and located, respectively. In particular, a new optic disc localization method using parabolic fitting is proposed based on the physiological structure characteristics of optic disc and blood vessels. Then, early lesions, such as microaneurysms, hemorrhages and hard exudates, are detected based on their respective characteristics. An equivalent optical model simulating human eyes is designed based on the anatomical structure of retina. Main structures and early lesions are reconstructed in the 3D space for better visualization. Finally, the severity of each image is evaluated based on the international criteria of diabetic retinopathy. RESULTS: The system has been tested on public databases and images from hospitals. Experimental results demonstrate that the proposed system achieves high accuracy for main structures and early lesions detection. The results of severity classification for non-proliferative diabetic retinopathy are also accurate and suitable. CONCLUSIONS: Our system can assist ophthalmologists for clinical diagnosis, automatic screening and course progression of patients.

Single nucleotide polymorphisms in TNFAIP3 were associated with the risks of rheumatoid arthritis in northern Chinese Han population.

BACKGROUND: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic destructive inflammation in synovial joints. It is well known that genetic and environmental risk factors and their interaction contribute to RA pathogenesis. This study aimed to investigate the association between the critical polymorphisms in the tumor necrosis factor α (TNFα)-induced protein 3(TNFAIP3) gene and the risk of RA in a large northern Chinese Han population. METHODS: A case-control study of 1280 RA patients and 1280 matched healthy controls was conducted. RESULTS: This study showed that carriers of the rs2230926 TG genotype or rs10499194 CT genotype had an increased risk for RA compared with those carrying the wild genotype (rs2230926: OR = 1.48, 95% CI = 1.17-1.86, p = 0.001; rs10499194: OR = 2.00, 95% CI = 1.46-2.74, p < 0.001). The combined rs2230926TG/GG or rs10499194 CT/TT were associated with an increased risk of RA (ORs were 1.50 and 2.01, 95% CIs were 1.19-1.88 and 1.47-2.74, respectively, both p < 0.001). There was not significant association between rs13207033 polymorphism and RA risk. Subset analysis stratified to gender showed that the increased risks were significant among the genotypes TG, TG/GG of rs2230926 and CT, CT/TT of rs10499194 and the corresponding ORs were 1.42 (95% CI = 1.10-1.83, p = 0.006), 1.44(95% CI = 1.12-1.85, p = 0.004), 1.52(95% CI = 1.05-2.20, p = 0.026) and 1.52(95% CI = 1.06-2.19, p = 0.023) in the female population. Stratified analyses by age found that rs2230926(TG, TG/GG) and rs10499194(CT, CT/TT) polymorphisms were associated with RA risks in population ≤53 years old and among >53 years old only rs10499194(CT, TT, CT/TT) polymorphism had significant results. The interaction analysis suggested that individuals with both risk genotypes of the two SNPs have a higher elevated risk of RA than those with only one of them (ORs were 3.44 compared to 1.74 and 1.35). The haplotype results showed that individuals with the rs2230926G-rs13207033G-rs10499194C haplotype were associated with increased risks of RA (OR = 1.37, 95% CI = 1.08-1.74, p = 0.010). CONCLUSIONS: Rs10499194 and rs2230926 polymorphisms in the TNFAIP3 gene region may be susceptibility factors for rheumatoid arthritis in the northern Chinese Han population.

Association between polymorphism in TRAF1/C5 gene and risk of rheumatoid arthritis: a meta-analysis.

Rheumatoid arthritis (RA) is a common chronic inflammatory autoimmune disease. Single nucleotide polymorphisms of tumor necrosis factor-receptor associated factor 1/complement component 5 (TRAF1/C5) gene are suspected to be associated with the risk of RA. This meta-analysis was performed to study the relationship between the polymorphism rs10818488 in TRAF1/C5 gene with RA. We retrieved the relevant articles from PubMed, EMBASE and the China National Knowledge Infrastructure databases. Odd ratios were calculated to assess the association between TRAF1/C5 rs10818488 polymorphism and RA risk. Meta-analyses were performed on the total data set and separately for the major ethnic groups and RF and ACAP status. All analyses were performed using the Stata software. Eight articles were included in the present analysis. Meta-analysis showed a weak association between TRAF1/C5 rs10818488 polymorphism and RA in all subjects (OR = 1.13, 95 % CI = 1.01­1.27, P heterogeneity < 0.001). Stratified analyses indicated that the TRAF1/C5 rs10818488 A allele was significantly associated with RA in Caucasians (OR = 1.29, 95 %CI = 1.14­1.47, P heterogeneity = 0.026), Asians (OR = 0.92, 95 %CI = 0.86­0.99, P heterogeneity = 0.378) and Africans (OR = 1.56, 95 %CI = 1.23­1.98, P heterogeneity = 0.876), also significantly in positive ACPA and positive RF patients versus controls (ORs were 1.20 and 1.25, 95 %CIs were 1.08­1.33 and 1.14­1.37, P values for heterogeneity were 0.215 and 0.133, respectively). Genetic polymorphism rs10818488 in TRAF1/C5 gene might be associated with RA susceptibility.