Genetic variants in UNC93B1 predispose to childhood-onset systemic lupus erythematosus.

Rare genetic variants in toll-like receptor 7 (TLR7) are known to cause lupus in humans and mice. UNC93B1 is a transmembrane protein that regulates TLR7 localization into endosomes. In the present study, we identify two new variants in UNC93B1 (T314A, located proximally to the TLR7 transmembrane domain, and V117L) in a cohort of east Asian patients with childhood-onset systemic lupus erythematosus. The V117L variant was associated with increased expression of type I interferons and NF-κB-dependent cytokines in patient plasma and immortalized B cells. THP-1 cells expressing the variant UNC93B1 alleles exhibited exaggerated responses to stimulation of TLR7/-8, but not TLR3 or TLR9, which could be inhibited by targeting the downstream signaling molecules, IRAK1/-4. Heterozygous mice expressing the orthologous Unc93b1V117L variant developed a spontaneous lupus-like disease that was more severe in homozygotes and again hyperresponsive to TLR7 stimulation. Together, this work formally identifies genetic variants in UNC93B1 that can predispose to childhood-onset systemic lupus erythematosus.

Palmitoylation prevents sustained inflammation by limiting NLRP3 inflammasome activation through chaperone-mediated autophagy.

As a key component of the inflammasome, NLRP3 is a critical intracellular danger sensor emerging as an important clinical target in inflammatory diseases. However, little is known about the mechanisms that determine the kinetics of NLRP3 inflammasome stability and activity to ensure effective and controllable inflammatory responses. Here, we show that S-palmitoylation acts as a brake to turn NLRP3 inflammasome off. zDHHC12 is identified as the S-acyltransferase for NLRP3 palmitoylation, which promotes its degradation through the chaperone-mediated autophagy pathway. Zdhhc12 deficiency in mice enhances inflammatory symptoms and lethality following alum-induced peritonitis and LPS-induced endotoxic shock. Notably, several disease-associated mutations in NLRP3 are associated with defective palmitoylation, resulting in overt NLRP3 inflammasome activation. Thus, our findings identify zDHHC12 as a repressor of NLRP3 inflammasome activation and uncover a previously unknown regulatory mechanism by which the inflammasome pathway is tightly controlled by the dynamic palmitoylation of NLRP3.

Leveraging trans-ethnic genetic risk scores to improve association power for complex traits in underrepresented populations.

Trans-ethnic genome-wide association studies have revealed that many loci identified in European populations can be reproducible in non-European populations, indicating widespread trans-ethnic genetic similarity. However, how to leverage such shared information more efficiently in association analysis is less investigated for traits in underrepresented populations. We here propose a statistical framework, trans-ethnic genetic risk score informed gene-based association mixed model (GAMM), by hierarchically modeling single-nucleotide polymorphism effects in the target population as a function of effects of the same trait in well-studied populations. GAMM powerfully integrates genetic similarity across distinct ancestral groups to enhance power in understudied populations, as confirmed by extensive simulations. We illustrate the usefulness of GAMM via the application to 13 blood cell traits (i.e. basophil count, eosinophil count, hematocrit, hemoglobin concentration, lymphocyte count, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular volume, monocyte count, neutrophil count, platelet count, red blood cell count and total white blood cell count) in Africans of the UK Biobank (n = 3204) while utilizing genetic overlap shared in Europeans (n = 746 667) and East Asians (n = 162 255). We discovered multiple new associated genes, which had otherwise been missed by existing methods, and revealed that the trans-ethnic information indirectly contributed much to the phenotypic variance. Overall, GAMM represents a flexible and powerful statistical framework of association analysis for complex traits in underrepresented populations by integrating trans-ethnic genetic similarity across well-studied populations, and helps attenuate health inequities in current genetics research for people of minority populations.

Pretransplant use of immune checkpoint inhibitors for hepatocellular carcinoma: A multicenter, retrospective cohort study.

Immune checkpoint inhibitors (ICIs) as a downstaging or bridging therapy for liver transplantation (LT) in hepatocellular carcinoma patients are rapidly increasing. However, the evidence about the feasibility and safety of pre-LT ICI therapy is limited and controversial. To this end, a multicenter, retrospective cohort study was conducted in 11 Chinese centers. The results showed that 83 recipients received pre-LT ICI therapy during the study period. The median post-LT follow-up was 8.1 (interquartile range 3.3-14.6) months. During the short follow-up, 23 (27.7%) recipients developed allograft rejection, and 7 of them (30.4%) were diagnosed by liver biopsy. Multivariate logistics regression analysis showed that the time interval between the last administration of ICI therapy and LT (TLAT) ≥ 30 days was an independent protective factor for allograft rejection (odds ratio = 0.096, 95% confidence interval 0.026-0.357; P < .001). Multivariate Cox analysis showed that allograft rejection was an independent risk factor for overall survival (hazard ratio = 9.960, 95% confidence interval 1.006-98.610; P = .043). We conclude that patients who receive a pre-LT ICI therapy with a TLAT shorter than 30 days have a much higher risk of allograft rejection than those with a TLAT longer than 30 days. The presence of rejection episodes might be associated with higher post-LT mortality.

Multi-trait transcriptome-wide association studies with probabilistic Mendelian randomization.

A transcriptome-wide association study (TWAS) integrates data from genome-wide association studies and gene expression mapping studies for investigating the gene regulatory mechanisms underlying diseases. Existing TWAS methods are primarily univariate in nature, focusing on analyzing one outcome trait at a time. However, many complex traits are correlated with each other and share a common genetic basis. Consequently, analyzing multiple traits jointly through multivariate analysis can potentially improve the power of TWASs. Here, we develop a method, moPMR-Egger (multiple outcome probabilistic Mendelian randomization with Egger assumption), for analyzing multiple outcome traits in TWAS applications. moPMR-Egger examines one gene at a time, relies on its cis-SNPs that are in potential linkage disequilibrium with each other to serve as instrumental variables, and tests its causal effects on multiple traits jointly. A key feature of moPMR-Egger is its ability to test and control for potential horizontal pleiotropic effects from instruments, thus maximizing power while minimizing false associations for TWASs. In simulations, moPMR-Egger provides calibrated type I error control for both causal effects testing and horizontal pleiotropic effects testing and is more powerful than existing univariate TWAS approaches in detecting causal associations. We apply moPMR-Egger to analyze 11 traits from 5 trait categories in the UK Biobank. In the analysis, moPMR-Egger identified 13.15% more gene associations than univariate approaches across trait categories and revealed distinct regulatory mechanisms underlying systolic and diastolic blood pressures.

Mitigation of Anti-Drug Antibody Production for Augmenting Anticancer Efficacy of Therapeutic Protein via Co-Injection of Nano-Rapamycin.

The induction of anti-drug antibody (ADA) is a formidable challenge for protein-based therapy. Trichosanthin (TCS) as a class of ribosome-inactivating proteins is widely studied in tumor treatment. However, the immunogenicity can induce the formation of ADA, which can cause hypersensitivity reactions and neutralize the efficacy of TCS, thus limiting its clinical application in cancer therapy. Here, a promising solution to this issue is presented by co-administration of the rapamycin nanoparticles and TCS. PEGylated rapamycin amphiphilic molecule is designed and synthesized as a prodrug and a delivery carrier, which can self-assemble into a nanoparticle system with encapsulation of free rapamycin, a hydrophobic drug. It is found that co-injection of the PEGylated rapamycin nanoparticles and TCS could mitigate the formation of anti-TCS antibody via inducing durable immunological tolerance. Importantly, the combination of TCS and the rapamycin nanoparticles has an enhanced effect on inhibit the growth of breast cancer. This work provides a promising approach for protein toxin-based anticancer therapy and for promoting the clinical translation.

Identifying pleiotropic genes for complex phenotypes with summary statistics from a perspective of composite null hypothesis testing.

Pleiotropy has important implication on genetic connection among complex phenotypes and facilitates our understanding of disease etiology. Genome-wide association studies provide an unprecedented opportunity to detect pleiotropic associations; however, efficient pleiotropy test methods are still lacking. We here consider pleiotropy identification from a methodological perspective of high-dimensional composite null hypothesis and propose a powerful gene-based method called MAIUP. MAIUP is constructed based on the traditional intersection-union test with two sets of independent P-values as input and follows a novel idea that was originally proposed under the high-dimensional mediation analysis framework. The key improvement of MAIUP is that it takes the composite null nature of pleiotropy test into account by fitting a three-component mixture null distribution, which can ultimately generate well-calibrated P-values for effective control of family-wise error rate and false discover rate. Another attractive advantage of MAIUP is its ability to effectively address the issue of overlapping subjects commonly encountered in association studies. Simulation studies demonstrate that compared with other methods, only MAIUP can maintain correct type I error control and has higher power across a wide range of scenarios. We apply MAIUP to detect shared associated genes among 14 psychiatric disorders with summary statistics and discover many new pleiotropic genes that are otherwise not identified if failing to account for the issue of composite null hypothesis testing. Functional and enrichment analyses offer additional evidence supporting the validity of these identified pleiotropic genes associated with psychiatric disorders. Overall, MAIUP represents an efficient method for pleiotropy identification.

Simultaneous test and estimation of total genetic effect in eQTL integrative analysis through mixed models.

Integration of expression quantitative trait loci (eQTL) into genome-wide association studies (GWASs) is a promising manner to reveal functional roles of associated single-nucleotide polymorphisms (SNPs) in complex phenotypes and has become an active research field in post-GWAS era. However, how to efficiently incorporate eQTL mapping study into GWAS for prioritization of causal genes remains elusive. We herein proposed a novel method termed as Mixed transcriptome-wide association studies (TWAS) and mediated Variance estimation (MTV) by modeling the effects of cis-SNPs of a gene as a function of eQTL. MTV formulates the integrative method and TWAS within a unified framework via mixed models and therefore includes many prior methods/tests as special cases. We further justified MTV from another two statistical perspectives of mediation analysis and two-stage Mendelian randomization. Relative to existing methods, MTV is superior for pronounced features including the processing of direct effects of cis-SNPs on phenotypes, the powerful likelihood ratio test for assessment of joint effects of cis-SNPs and genetically regulated gene expression (GReX), two useful quantities to measure relative genetic contributions of GReX and cis-SNPs to phenotypic variance, and the computationally efferent parameter expansion expectation maximum algorithm. With extensive simulations, we identified that MTV correctly controlled the type I error in joint evaluation of the total genetic effect and proved more powerful to discover true association signals across various scenarios compared to existing methods. We finally applied MTV to 41 complex traits/diseases available from three GWASs and discovered many new associated genes that had otherwise been missed by existing methods. We also revealed that a small but substantial fraction of phenotypic variation was mediated by GReX. Overall, MTV constructs a robust and realistic modeling foundation for integrative omics analysis and has the advantage of offering more attractive biological interpretations of GWAS results.

Incorporating genetic similarity of auxiliary samples into eGene identification under the transfer learning framework.

BACKGROUND: The term eGene has been applied to define a gene whose expression level is affected by at least one independent expression quantitative trait locus (eQTL). It is both theoretically and empirically important to identify eQTLs and eGenes in genomic studies. However, standard eGene detection methods generally focus on individual cis-variants and cannot efficiently leverage useful knowledge acquired from auxiliary samples into target studies. METHODS: We propose a multilocus-based eGene identification method called TLegene by integrating shared genetic similarity information available from auxiliary studies under the statistical framework of transfer learning. We apply TLegene to eGene identification in ten TCGA cancers which have an explicit relevant tissue in the GTEx project, and learn genetic effect of variant in TCGA from GTEx. We also adopt TLegene to the Geuvadis project to evaluate its usefulness in non-cancer studies. RESULTS: We observed substantial genetic effect correlation of cis-variants between TCGA and GTEx for a larger number of genes. Furthermore, consistent with the results of our simulations, we found that TLegene was more powerful than existing methods and thus identified 169 distinct candidate eGenes, which was much larger than the approach that did not consider knowledge transfer across target and auxiliary studies. Previous studies and functional enrichment analyses provided empirical evidence supporting the associations of discovered eGenes, and it also showed evidence of allelic heterogeneity of gene expression. Furthermore, TLegene identified more eGenes in Geuvadis and revealed that these eGenes were mainly enriched in cells EBV transformed lymphocytes tissue. CONCLUSION: Overall, TLegene represents a flexible and powerful statistical method for eGene identification through transfer learning of genetic similarity shared across auxiliary and target studies.

Sodium, potassium intake, and all-cause mortality: confusion and new findings.

BACKGROUND: The World Health Organization (WHO) has established recommended daily intakes for sodium and potassium. However, there is currently some controversy regarding the association between sodium intake, potassium intake, the sodium-to-potassium ratio, and overall mortality. To assess the correlations between sodium intake, potassium intake, the sodium-to-potassium ratio, and overall mortality, as well as the potential differences in sodium and potassium intake thresholds among different population groups, we analyzed data from NHANES 2003-2018. METHODS: NHANES is an observational cohort study that estimates sodium and potassium intake through one or two 24-h dietary recalls. Hazard ratios (HR) for overall mortality were calculated using multivariable adjusted Cox models accounting for sampling design. A total of 13855 out of 26288 participants were included in the final analysis. Restricted cubic spline analyses were used to examine the relationship between sodium intake, potassium intake, and overall mortality. If non-linearity was detected, we employed a recursive algorithm to calculate inflection points. RESULTS: Based on one or two 24-h dietary recalls, the sample consisted of 13,855 participants, representing a non-institutionalized population aged 40-80 years, totaling 11,348,771 person-months of mean follow-up 99.395 months. Daily sodium intake and daily potassium intake were inversely associated with all-cause mortality. Restrictive cubic spline analysis showed non-linear relationships between daily sodium intake, potassium intake, sodium-potassium ratio, and total mortality. The inflection point for daily sodium intake was 3133 mg/d, and the inflection point for daily potassium intake was 3501 mg/d, and the inflection point for daily sodium-potassium ratio intake was 1.203 mg/mg/d. In subgroup analyses, a significant interaction was found between age and high sodium intake, which was further confirmed by the smooth curves that showed a U-shaped relationship between sodium intake and all-cause mortality in the elderly population, with a inflection point of 3634 mg/d. CONCLUSION: Nonlinear associations of daily sodium intake, daily potassium intake and daily sodium-potassium ratio intake with all-cause mortality were observed in American individuals. The inflection point for daily sodium intake was 3133 mg/d. And the inflection point for daily sodium intake was 3634 mg/d in elderly population. The inflection point for daily potassium intake was 3501 mg/d. The inflection point for daily sodium-potassium ratio intake was 1.203 mg/mg/d, respectively, A healthy diet should be based on reasonable sodium intake and include an appropriate sodium-to-potassium ratio.

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations.

BACKGROUND: Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently. RESULTS: By leveraging summary statistics of 37 traits from East Asian (Nmax=254,373) or European (Nmax=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρg) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with [Formula: see text] ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs. CONCLUSIONS: Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes.

BACKGROUND: Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. RESULTS: By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. CONCLUSIONS: Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Aggregating multiple expression prediction models improves the power of transcriptome-wide association studies.

Transcriptome-wide association study (TWAS) is an important integrative method for identifying genes that are causally associated with phenotypes. A key step of TWAS involves the construction of expression prediction models for every gene in turn using its cis-SNPs as predictors. Different TWAS methods rely on different models for gene expression prediction, and each such model makes a distinct modeling assumption that is often suitable for a particular genetic architecture underlying expression. However, the genetic architectures underlying gene expression vary across genes throughout the transcriptome. Consequently, different TWAS methods may be beneficial in detecting genes with distinct genetic architectures. Here, we develop a new method, HMAT, which aggregates TWAS association evidence obtained across multiple gene expression prediction models by leveraging the harmonic mean P-value combination strategy. Because each expression prediction model is suited to capture a particular genetic architecture, aggregating TWAS associations across prediction models as in HMAT improves accurate expression prediction and enables subsequent powerful TWAS analysis across the transcriptome. A key feature of HMAT is its ability to accommodate the correlations among different TWAS test statistics and produce calibrated P-values after aggregation. Through numerical simulations, we illustrated the advantage of HMAT over commonly used TWAS methods as well as ad hoc P-value combination rules such as Fisher's method. We also applied HMAT to analyze summary statistics of nine common diseases. In the real data applications, HMAT was on average 30.6% more powerful compared to the next best method, detecting many new disease-associated genes that were otherwise not identified by existing TWAS approaches. In conclusion, HMAT represents a flexible and powerful TWAS method that enjoys robust performance across a range of genetic architectures underlying gene expression.

A randomized-controlled trial of ischemia-free liver transplantation for end-stage liver disease.

BACKGROUND & AIMS: Ischemia-reperfusion injury (IRI) has thus far been considered as an inevitable component of organ transplantation, compromising outcomes, and limiting organ availability. Ischemia-free organ transplantation is a novel approach designed to avoid IRI, with the potential to improve outcomes. METHODS: In this randomized-controlled clinical trial, recipients of livers from donors after brain death were randomly assigned to receive either an ischemia-free or a 'conventional' transplant. The primary endpoint was the incidence of early allograft dysfunction. Secondary endpoints included complications related to graft IRI. RESULTS: Out of 68 randomized patients, 65 underwent transplants and were included in the analysis. 32 patients received ischemia-free liver transplantation (IFLT), and 33 received conventional liver transplantation (CLT). Early allograft dysfunction occurred in two recipients (6%) randomized to IFLT and in eight (24%) randomized to CLT (difference -18%; 95% CI -35% to -1%; p = 0.044). Post-reperfusion syndrome occurred in three recipients (9%) randomized to IFLT and in 21 (64%) randomized to CLT (difference -54%; 95% CI -74% to -35%; p <0.001). Non-anastomotic biliary strictures diagnosed with protocol magnetic resonance cholangiopancreatography at 12 months were observed in two recipients (8%) randomized to IFLT and in nine (36%) randomized to CLT (difference, -28%; 95% CI -50% to -7%; p = 0.014). The comprehensive complication index at 1 year after transplantation was 30.48 (95% CI 23.25-37.71) in the IFLT group vs. 42.14 (95% CI 35.01-49.26) in the CLT group (difference -11.66; 95% CI -21.81 to -1.51; p = 0.025). CONCLUSIONS: Among patients with end-stage liver disease, IFLT significantly reduced complications related to IRI compared to a conventional approach. CLINICAL TRIAL REGISTRATION: chictr.org. ChiCTR1900021158. IMPACT AND IMPLICATIONS: Ischemia-reperfusion injury has thus far been considered as an inevitable event in organ transplantation, compromising outcomes and limiting organ availability. Ischemia-free liver transplantation is a novel approach of transplanting donor livers without interruption of blood supply. We showed that in patients with end-stage liver disease, ischemia-free liver transplantation, compared with a conventional approach, led to reduced complications related to ischemia-reperfusion injury in this randomized trial. This new approach is expected to change the current practice in organ transplantation, improving transplant outcomes, increasing organ utilization, while providing a clinical model to delineate the impact of organ injury on alloimmunity.

N-Doping Coupled with Co-Vacancies Activating Sulfur Atoms and Narrowing Bandgap for CoS Toward Synergistically Accelerating Hydrogen Evolution.

The combination of hetero-elemental doping and vacancy engineering will be developed as one of the most efficient strategies to design excellent electrocatalysts for hydrogen evolution reaction (HER). Herein, a novel strategy for N-doping coupled with Co-vacancies is demonstrated to precisely activate inert S atoms adjacent to Co-vacancies and significantly improve charge transfer for CoS toward accelerating HER. In this strategy, N-doping favors the presence of Co-vacancies, due to greatly decreasing their formation energy. The as-developed strategy realizes the upshift of S 3p orbitals followed by more overlapping between S 3py and H 1s orbitals, which results in the favorable hydrogen atom adsorption free energy change (ΔGH ) to activate inert S atoms as newborn catalytical sites. Besides, this strategy synergistically decreases the bandgap of CoS, thereby achieving satisfactory electrical conductivity and low charge-transfer resistance for the as-obtained electrocatalysts. With an excellent HER activity of -89.0 mV at 10.0 mA cm-2 in alkaline environments, this work provides a new approach to unlocking inert sites and significantly improving charge transfer toward cobalt-based materials for highly efficient HER.

Evaluation of belimumab in treatment of Chinese childhood-onset systemic lupus erythematosus: a prospective analysis from multicenter study.

OBJECTIVE: The aim of this study is to identify whether low lupus disease activity status (LLDAS) and clinical remission (CR) of belimumab plus standard of care (SoC) therapy are achievable goals in childhood-onset SLE (cSLE). METHODS: This multicentre, one arm pre-post intervention study was conducted at 15 centers in China. The primary end point was to describe the proportion of patients who achieved LLDAS and CR after 3, 6, and 12 months after treatment with belimumab plus SoC therapy. A multiple regression model was used to impute missing data. A Poisson regression model was used to calculate the effect of belimumab treatment on the reduced risk of serious diseases and the incidence of new damage. RESULT: 193 (92.2% female) with active cSLE from 15 centers were included. At 3, 6 and 12 months, the proportion of LLDAS (CR) was 12.4% (1.0%), 25.6% (4.5%) and 70.3% (29.7%), respectively. The mean SELENA-SLEDAI score decreased from 11.0 at baseline to 3.7, 2.9 and 1.7 at 3, 6, and 12 months. At baseline, all patients received steroids at a mean (SD) prednisone equivalent dose of 31.0 (18.2) mg/day, which decreased to 19.4 (10.8) mg/day at month 3, 12.6 (7.2) mg/day at month 6 and 6.7 (5.3) mg/day at month 12. The symptoms and immunological indicators were also significantly improved. CONCLUSION: This is the first and largest sample size prospective clinical intervention study of cSLE patients treated with belimumab in China. LLDAS and CR were attainable treat-to-target of belimumab plus SoC therapy in cSLE.

Lamina propria interleukin 17 A aggravates natural killer T-cell activation in autoimmune hepatitis.

Autoimmune hepatitis is an interface hepatitis characterized by the progressive destruction of the liver parenchyma, the cause of which is still obscure. Interleukin (IL)-17A is a major driver of autoimmunity, which can be produced by innate immune cells against several intracellular pathogens. Here, we investigated the involvement of IL-17A in a mice model of immune-mediated hepatitis with the intestine exposed to Salmonella typhimurium. Our results showed more severe Concanavalin (Con) A-induced liver injury and gut microbiome dysbiosis when the mice were treated with a gavage of S. typhimurium. Then, the natural killer (NK) T cells were overactivated by the accumulated IL-17A in the liver in the Con A and S. typhimurium administration group. IL-17A could activate NKT cells by inducing CD178 expression via IL-4/STAT6 signaling. Furthermore, via the portal tract, the laminae propria mucosal-associated invariant T (MAIT)-cell-derived IL-17A could be the original driver of NKT cell overactivation in intragastric administration of S. typhimurium and Con A injection. In IL-17A-deficient mice, Con A-induced liver injury and NKT cell activation were alleviated. However, when AAV-sh-mIL-17a was used to specifically knock down IL-17A in liver, it seemed that hepatic IL-17a knock down did not significantly influence the liver injury. Our results suggested that, under Con A-induction, laminae propria MAIT-derived IL-17A activated hepatic NKT, and this axis could be a therapeutic target in autoimmune liver disease.

Association of aspirin with all-cause and cardiocerebrovascular mortality in patients with metabolic associated fatty liver disease.

BACKGROUND: Studies on aspirin's effects on metabolic-associated fatty liver disease (MAFLD) are limited. The aim of this study was to assess the association between aspirin and all-cause and cardiovascular disease (CVD) mortality in individuals with MAFLD. METHODS: Data were acquired from the National Health And Nutrition Examination Survey (NHANES) III. MAFLD diagnosis was consistent with that of international expert consensus. The independent association between aspirin and all-cause and CVD mortality in participants with MAFLD was evaluated by multiple Cox regression. Stratified analyses and interaction tests were performed to investigate whether covariates modified the association between aspirin and MAFLD mortality. RESULTS: Of 4594 eligible participants, 3,162 (68.83%) never took aspirin (0 times/month), 962 (20.94%) took it occasionally (1-14 times/month) and 470 (10.23%) took it regularly (≥15 times/month). Multiple cox regression showed that aspirin was not associated with overall mortality for MAFLD individuals. Stratified analysis revealed that in middle-aged (45-59 years) participants with MAFLD, occasional aspirin use was associated with low all-cause mortality risk (HR = 0.61, 95% CI = 0.43-0.86), while there was no significant association between aspirin and all-cause mortality among the young or the elderly. CONCLUSIONS: We found that the association between aspirin and all-cause MAFLD mortality varies by both age and frequency of administration. More prospective studies are needed to explore aspirin's influence on MALFD mortality.

C-terminal modification of a de novo designed antimicrobial peptide via capping of macrolactam rings.

In this work, by capping a macrolactam ring at the C-terminus of a de novo-designed peptide, namely zp80, we have constructed a small peptide library via the solid phase peptide synthesis for screening. Eight peptides bearing different aspartic acid-rich macrolactam rings but the same linear (IIRR)4 unit exhibited improved antibacterial activities, hemolytic activity, and selectivity index. Mechanistic studies revealed that they could destroy the integrity of bacterial envelope, leading to cytoplasm leakage and rapid dissipation of membrane potential. One of these peptides, zp90 with a macrolactam ring of (KaDGD), demonstrated preferential interaction with calcium ions at a stoichiometric ratio of 1:1, promoting the affinity of designed peptides to bacterial membrane. Overall, this work provides a feasible strategy for medicinal chemists to further develop potent, selective, and multifunctional de novo-designed antimicrobial peptides.

FGF10 mitigates doxorubicin-induced myocardial toxicity in mice via activation of FGFR2b/PHLDA1/AKT axis.

Doxorubicin is a common chemotherapeutic agent in clinic, but myocardial toxicity limits its use. Fibroblast growth factor (FGF) 10, a multifunctional paracrine growth factor, plays diverse roles in embryonic and postnatal heart development as well as in cardiac regeneration and repair. In this study we investigated the role of FGF10 as a potential modulator of doxorubicin-induced cardiac cytotoxicity and the underlying molecular mechanisms. Fgf10+/- mice and an inducible dominant negative FGFR2b transgenic mouse model (Rosa26rtTA; tet(O)sFgfr2b) were used to determine the effect of Fgf10 hypomorph or blocking of endogenous FGFR2b ligands activity on doxorubicin-induced myocardial injury. Acute myocardial injury was induced by a single injection of doxorubicin (25 mg/kg, i.p.). Then cardiac function was evaluated using echocardiography, and DNA damage, oxidative stress and apoptosis in cardiac tissue were assessed. We showed that doxorubicin treatment markedly decreased the expression of FGFR2b ligands including FGF10 in cardiac tissue of wild type mice, whereas Fgf10+/- mice exhibited a greater degree of oxidative stress, DNA damage and apoptosis as compared with the Fgf10+/+ control. Pre-treatment with recombinant FGF10 protein significantly attenuated doxorubicin-induced oxidative stress, DNA damage and apoptosis both in doxorubicin-treated mice and in doxorubicin-treated HL-1 cells and NRCMs. We demonstrated that FGF10 protected against doxorubicin-induced myocardial toxicity via activation of FGFR2/Pleckstrin homology-like domain family A member 1 (PHLDA1)/Akt axis. Overall, our results unveil a potent protective effect of FGF10 against doxorubicin-induced myocardial injury and identify FGFR2b/PHLDA1/Akt axis as a potential therapeutic target for patients receiving doxorubicin treatment.