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Human humoral immune responses to SARS-CoV-2 vaccines exhibit substantial inter-individual variability and have been linked to vaccine efficacy. To elucidate the underlying mechanism behind this variability, we conducted a genome-wide association study (GWAS) on the anti-spike IgG serostatus of UK Biobank participants who were previously uninfected by SARS-CoV-2 and had received either the first dose (n = 54,066) or the second dose (n = 46,232) of COVID-19 vaccines. Our analysis revealed significant genome-wide associations between the IgG antibody serostatus following the initial vaccine and human leukocyte antigen (HLA) class II alleles. Specifically, the HLA-DRB1∗13:02 allele (MAF = 4.0%, OR = 0.75, p = 2.34e-16) demonstrated the most statistically significant protective effect against IgG seronegativity. This protective effect was driven by an alteration from arginine (Arg) to glutamic acid (Glu) at position 71 on HLA-DRβ1 (p = 1.88e-25), leading to a change in the electrostatic potential of pocket 4 of the peptide binding groove. Notably, the impact of HLA alleles on IgG responses was cell type specific, and we observed a shared genetic predisposition between IgG status and susceptibility/severity of COVID-19. These results were replicated within independent cohorts where IgG serostatus was assayed by two different antibody serology tests. Our findings provide insights into the biological mechanism underlying individual variation in responses to COVID-19 vaccines and highlight the need to consider the influence of constitutive genetics when designing vaccination strategies for optimizing protection and control of infectious disease across diverse populations.

Amplitude error of each antenna in three-element array is an important factor affecting the angle simulation precision, which is a key index in radio frequency simulation system (RFSS). Analyzing the relationship between angle simulation error and amplitude error is of great significance. Firstly, under the maximum amplitude error limitation of three-element array, the problem of maximum angle simulation error at a fixed incoming wave direction is modeled. This optimization problem is a non-convex optimization problem, and by analyzing its structural characteristics, six possible values for the optimal solution are obtained. Secondly, the problem of maximum angle simulation error at any incoming wave direction within the three-element array is modeled. Based on the optimization results for the fixed incoming wave direction and structural properties of the problem, a closed-form expression for the maximum angle simulation error is obtained, and the apparent radiation centers corresponding to the maximum angle simulation error are revealed. Then, when the amplitude errors approach zero, the asymptotic characteristics of the maximum angle simulation error of the three-element array are analyzed, revealing that the asymptotic angle simulation error increases linearly with the amplitude error. Finally, the accuracy of the analysis results is proved via numerical simulations.

Plumage color, a pivotal attribute delineating diverse Muscovy duck strains, assumes considerable significance within the field of Muscovy duck breeding research. This study extends the existing research by delving into the hereditary aspects of genes associated with plumage coloration in Muscovy ducks. The principal objective is to discern marker genes conducive to targeted breeding strategies based on plumage color, thereby furnishing indispensable technical foundations for the development of novel Muscovy duck varieties. Our investigation focused on scrutinizing the impact of MYOT and MB genes on the genetic expression of plumage color at both the RNA and protein levels in Muscovy ducks. The results elucidate that black Muscovy ducks manifest markedly elevated mRNA and protein expression levels of MYOT and MB genes in comparison to their white counterparts, indicating that both genes may play a constructive regulatory role in the context of plumage coloration in Muscovy ducks. The outcomes of this study delineate a discernible correlation between MYOT and MB genes and the plumage coloration in Muscovy ducks. Employing gene expression analysis, we successfully identified candidate genes that may be intricately linked to the determination of plumage color in these ducks.

Abstract Background There is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment. Methods To identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models. Results Through MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation. Conclusions Our MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

Abstract Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Background and objectiveAcute ischemic stroke (AIS) is a leading cause of mortality, severe neurological and long-term disability world-wide. Blood-based indicators may provide valuable information on identified prognostic factors. However, currently, there is still a lack of peripheral blood indicators for the prognosis of AIS. We aimed to identify the most promising prognostic indicators and establish prognostic models for AIS.Methods484 subjects enrolled from four centers were analyzed immunophenotypic indicators of peripheral blood by flow cytometry. Least absolute shrinkage and selection operator (LASSO) regression was applied to minimize the potential collinearity and over-fitting of variables measured from the same subject and over-fitting of variables. Univariate and multivariable Cox survival analysis of differences between and within cohorts was performed by log-rank test. The areas under the receiving operating characteristic (ROC) curves were used to evaluate the selection accuracy of immunophenotypic indicators in identifying AIS subjects with survival risk. The prognostic model was constructed using a multivariate Cox model, consisting of 402 subjects as a training cohort and 82 subjects as a testing cohort.ResultsIn the prospective study, 7 immunophenotypic indicators of distinct significance were screened out of 72 peripheral blood immunophenotypic indicators by LASSO. In multivariate cox regression, CTL (%) [HR: 1.18, 95% CI: 1.03–1.33], monocytes/μl [HR: 1.13, 95% CI: 1.05–1.21], non-classical monocytes/μl [HR: 1.09, 95% CI: 1.02–1.16] and CD56high NK cells/μl [HR: 1.13, 95% CI: 1.05–1.21] were detected to decrease the survival probability of AIS, while Tregs/μl [HR:0.97, 95% CI: 0.95–0.99, p=0.004], BM/μl [HR:0.90, 95% CI: 0.85–0.95, p=0.023] and CD16+NK cells/μl [HR:0.93, 95% CI: 0.88–0.98, p=0.034] may have the protective effect. As for indicators’ discriminative ability, the AUC for CD56highNK cells/μl attained the highest of 0.912. In stratification analysis, the survival probability for AIS subjects with a higher level of Tregs/μl, BM/μl, CD16+NK cells/μl, or lower levels of CD56highNK cells/μl, CTL (%), non-classical monocytes/μl, Monocytes/μl were more likely to survive after AIS. The multivariate Cox model showed an area under the curve (AUC) of 0.805, 0.781 and 0.819 and 0.961, 0.924 and 0.982 in the training and testing cohort, respectively.ConclusionOur study identified 7 immunophenotypic indicators in peripheral blood may have great clinical significance in monitoring the prognosis of AIS and provide a convenient and valuable predictive model for AIS.

Abstract Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson’s disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins’ interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.

The Righi–Leduc heat flux generated by the self-generated magnetic field in the ablative Rayleigh–Taylor instability driven by a laser irradiating thin targets is studied through two-dimensional extended-magnetohydrodynamic simulations. The perturbation structure gets into a low magnetization state though the peak strength of the self-generated magnetic field could reach hundreds of teslas. The Righi–Leduc effect plays an essential impact both in the linear and nonlinear stages, and it deflects the total heat flux towards the spike base. Compared to the case without the self-generated magnetic field included, less heat flux is concentrated at the spike tip, finally mitigating the ablative stabilization and leading to an increase in the velocity of the spike tip. It is shown that the linear growth rate is increased by about 10% and the amplitude during the nonlinear stage is increased by even more than 10% due to the feedback of the magnetic field, respectively. Our results reveal the importance of Righi–Leduc heat flux to the growth of the instability and promote deep understanding of the instability evolution together with the self-generated magnetic field, especially during the acceleration stage in inertial confinement fusion.