Genetic correlation and Mendelian randomization analyses support causal relationships between dietary habits and age at menarche.

Dietary habits are essential in the mean age at menarche (AAM). However, the causal relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between dietary habits and AAM. Genetic summary statistics for dietary habits were obtained from the UK Biobank. GWAS summary data for AAM was obtained from the ReproGen Consortium. Linkage disequilibrium score regression was used to test genetic correlations between dietary habits and AAM. The Mendelian randomization (MR) analyses used the inverse-variance weighted method. Genetic correlations with AAM were identified for 29 candi-date dietary habits, such as milk type (skimmed, semi-skimmed, full cream; coefficient = 0.2704, Pldsc = 1.13 × 10-14). MR evaluations revealed that 19 dietary habits were associated with AAM, including bread type (white vs. any other; OR 1.71, 95% CI 1.28-2.29, Pmr = 3.20 × 10-4), tablespoons of cooked vegetables (OR 0.437, 95% CI 0.29-0.67; Pmr = 1.30 × 10-4), and cups of coffee per day (OR 0.72, 95% CI 0.57-0.92, Pmr = 8.31 × 10-3). These results were observed to be stable under the sensitivity analysis. Our study provides potential insights into the genetic mechanisms underlying AAM and evidence that dietary habits are associated with AAM.

Large-scale causal analysis of gut microbiota and six common complications of diabetes: a mendelian randomization study.

BACKGROUND: This study aimed to reveal the association between the gut microbiota (GM) and six diabetic complications: diabetic hypoglycemia; ketoacidosis; nephropathy; neuropathy; retinopathy; and Charcot's foot. METHODS: GM data were obtained from the MiBioGen consortium and Dutch Microbiome Project while data on the six diabetic complications were obtained from the FinnGen consortium. Two-sample Mendelian randomization (TSMR) was performed to explore the association between GM and the common diabetic complications. Inverse MR analysis was conducted to examine the effect of diabetic complications on the identified GM. Sensitivity tests were conducted to validate the stability of the results. Finally, multivariate MR (MVMR) was performed to determine whether GM had a direct influence on the diabetic complications. RESULTS: After multiple corrections, the inverse variance weighted (IVW) results predicted 61 suggestive markers between GM and six diabetic complications. In particular, the IVW results revealed that the Bacteroidia class and Bacteroidales order were positively associated with diabetic hypoglycemia while the Verrucomicrobiae class and Verrucomicrobiales order were positively associated with diabetic nephropathy. Based on the replication analysis, these results were identified to be stable. MVMR showed that the results remained stable after accounting for traditional risk factors. CONCLUSION: Extensive causal associations were found between GM and diabetic complications, which may provide new insights into the mechanisms of microbiome-mediated complications of diabetes.

Corrigendum: Treatment of surgical brain injury by immune tolerance induced by peripheral intravenous injection of biotargeting nanoparticles loaded with brain antigens.

[This corrects the article DOI: 10.3389/fimmu.2019.00743.].

Causal associations between common musculoskeletal disorders and dementia: a Mendelian randomization study.

Introduction: Dementia and musculoskeletal disorders (MSDs) are major public health problems. We aimed to investigate the genetic causality of common MSDs and dementia. Methods: Two-sample Mendelian randomization (MR) was used in this study. MR analysis based on gene-wide association study (GWAS) data on osteoarthritis (OA), dementia with Lewy bodies, and other MSDs and dementia types were obtained from the Genetics of Osteoarthritis consortium, IEU-open GWAS project, GWAS catalog, and FinnGen consortium. Rigorously selected single-nucleotide polymorphisms were regarded as instrumental variables for further MR analysis. Inverse-variance weighted, MR-Egger regression, weight median, simple mode, and weight mode methods were used to obtain the MR estimates. Cochran's Q test, MR-Egger and MR-Pleiotropy Residual Sum and Outlier analysis, and the leave-one-out test were applied for sensitivity testing. Results: The inverse-variance weighted method showed that hip OA was genetically associated with a lower risk of dementia, unspecified dementia, dementia in Alzheimer's disease, and vascular dementia. Kneehip OA was inversely associated with unspecified dementia and vascular dementia. Rheumatoid arthritis, juvenile idiopathic arthritis and seronegative rheumatoid arthritis were inversely associated with frontotemporal dementia, and rheumatoid arthritis was inversely associated with unspecified dementia. Simultaneously, ankylosing spondylitis was an independent risk factor for dementia, dementia with Lewy bodies, and dementia in Alzheimer's disease. Sensitivity tests showed that heterogeneity and horizontal pleiotropy did not exist in these associations. The leave-one-out test showed that these associations were stable. Conclusion: We found that some MSDs were associated with the risk of dementia and provide evidence for the early detection of dementia in patients with MSDs and for the impact of inflammation on the central nervous system.

Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis.

Epilepsy is a severe neurological condition affecting 50-65 million individuals worldwide that can lead to brain damage. Nevertheless, the etiology of epilepsy remains poorly understood. Meta-analyses of genome-wide association studies involving 15,212 epilepsy cases and 29,677 controls of the ILAE Consortium cohort were used to conduct transcriptome-wide association studies (TWAS) and protein-wide association studies (PWAS). Furthermore, a protein-protein interaction (PPI) network was generated using the STRING database, and significant epilepsy-susceptible genes were verified using chip data. Chemical-related gene set enrichment analysis (CGSEA) was performed to determine novel drug targets for epilepsy. TWAS analysis identified 21,170 genes, of which 58 were significant (TWASfdr < 0.05) in ten brain regions, and 16 differentially expressed genes were verified based on mRNA expression profiles. The PWAS identified 2249 genes, of which 2 were significant (PWASfdr < 0.05). Through chemical-gene set enrichment analysis, 287 environmental chemicals associated with epilepsy were identified. We identified five significant genes (WIPF1, IQSEC1, JAM2, ICAM3, and ZNF143) that had causal relationships with epilepsy. CGSEA identified 159 chemicals that were significantly correlated with epilepsy (Pcgsea < 0.05), such as pentobarbital, ketone bodies, and polychlorinated biphenyl. In summary, we performed TWAS, PWAS (for genetic factors), and CGSEA (for environmental factors) analyses and identified several epilepsy-associated genes and chemicals. The results of this study will contribute to our understanding of genetic and environmental factors for epilepsy and may predict novel drug targets.

No evidence of a genetic causal relationship between ankylosing spondylitis and iron homeostasis: A two-sample Mendelian randomization study.

Background: Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease that leads to bone hyperplasia and spinal ankylosis. Iron homeostasis plays a very important role in the inflammatory response and is closely related to the pathogenesis of AS. This study aimed to use large-scale genome-wide association study (GWAS) summary data to study the genetic causal relationship between AS and iron homeostasis using Mendelian randomization (MR). Methods: Genome-wide association study summary data of AS and iron homeostasis-related indicators were obtained from the FinnGen consortium and the DeCODE genetics database, respectively. We used four iron homeostasis-related indicators: ferritin, serum iron, total iron binding capacity (TIBC), and transferrin saturation (TSAT) for two-sample MR analyses to test for genetic causal association with AS using the "TwoSampleMR" package of the R software (version 4.1.2). The random-effects inverse variance weighted (IVW) method was the main analysis method used for MR. We examined the MR analysis results for heterogeneity, horizontal pleiotropy, and possible outliers. In addition, we confirmed the robustness of the MR analysis by testing whether the results were affected by a single SNP and whether they followed a normal distribution. Results: The random-effects IVW results showed that ferritin [p = 0.225, OR 95% confidence interval (CI) = 0.836 (0.627-1.116)], serum iron [p = 0.714, OR 95% CI = 0.948 (0.714-1.260)], TIBC [p = 0.380, OR 95% CI = 0.917 (0.755-1.113)], and TSAT [p = 0.674, OR 95% CI = 0.942 (0.713-1.244)] have no genetic causal relationship with AS. We detected no heterogeneity，horizontal pleiotropy and possible outliers in our MR analysis (p > 0.05). In addition, our MR analysis results were not affected by a single SNP, and were normally distributed. Conclusion: Our study did not detect a genetic causal relationship between AS and iron homeostasis. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

Identification of candidate genes and pathways associated with juvenile idiopathic arthritis by integrative transcriptome-wide association studies and mRNA expression profiles.

AIM: Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease of childhood, with genetic susceptibility and pathological processes such as autoimmunity and autoinflammation, but its pathogenesis is unclear. We conducted a transcriptome-wide association study (TWAS) using expression interpolation from a large-scale genome-wide association study (GWAS) dataset to identify genes, biological pathways, and environmental chemicals associated with JIA. METHODS: We obtained published GWAS data on JIA for TWAS and used mRNA expression profiling to validate the genes identified by TWAS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. A protein-protein interaction (PPI) network was generated, and central genes were obtained using Molecular Complex Detection (MCODE). Finally, chemical gene expression datasets were obtained from the Comparative Toxicogenomics database for chemical genome enrichment analysis. RESULTS: TWAS identified 1481 genes associated with JIA, and 154 differentially expressed genes were identified based on mRNA expression profiles. After comparing the results of TWAS and mRNA expression profiles, we obtained eight overlapping genes. GO and KEGG enrichment analyses of the genes identified by TWAS yielded 163 pathways, and PPI network analysis as well as MCODE resolution identified a total of eight clusters. Through chemical gene set enrichment analysis, 287 environmental chemicals associated with JIA were identified. CONCLUSION: By integrating TWAS and mRNA expression profiles, genes, biological pathways, and environmental chemicals associated with JIA were identified. Our findings provide new insights into the pathogenesis of JIA, including candidate genetic and environmental factors contributing to its onset and progression.

Large-Scale Genetic Correlation Analysis between Spondyloarthritis and Human Blood Metabolites.

The aim was to study the genetic correlation and causal relationship between spondyloarthritis (SpA) and blood metabolites based on the large-scale genome-wide association study (GWAS) summary data. The GWAS summary data (3966 SpA and 448,298 control cases) of SpA were from the UK Biobank, and the GWAS summary data (486 blood metabolites) of human blood metabolites were from a published study. First, the genetic correlation between SpA and blood metabolites was analyzed by linkage disequilibrium score (LDSC) regression. Next, we used Mendelian randomization (MR) analysis to perform access causal relationship between SpA and blood metabolites. Random effects inverse variance weighted (IVW) was the main analysis method, and the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The MR analysis results were dominated by the random effects IVW. The Cochran's Q statistic (MR-IVW) and Rucker's Q statistic (MR Egger) were used to check heterogeneity. MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to check horizontal pleiotropy. The MR-PRESSO was also used to check outliers. The "leave-one-out" analysis was used to assess whether the MR analysis results were affected by a single SNP and thus test the robustness of the MR results. Finally, we identified seven blood metabolites that are genetically related to SpA: X-10395 (correlation coefficient = -0.546, p = 0.025), pantothenate (correlation coefficient = -0.565, p = 0.038), caprylate (correlation coefficient = -0.333, p = 0.037), pelargonate (correlation coefficient = -0.339, p = 0.047), X-11317 (correlation coefficient = -0.350, p = 0.038), X-12510 (correlation coefficient = -0.399, p = 0.034), and X-13859 (Correlation coefficient = -0.458, p = 0.015). Among them, X-10395 had a positive genetic causal relationship with SpA (p = 0.014, OR = 1.011). The blood metabolites that have genetic correlation and causal relationship with SpA found in this study provide a new idea for the study of the pathogenesis of SpA and the determination of diagnostic indicators.

Corrigendum: Causal associations between common musculoskeletal disorders and dementia: a Mendelian randomization study.

[This corrects the article DOI: 10.3389/fnagi.2023.1253791.].

Large-scale correlation analysis of deep venous thrombosis and gut microbiota.

Objective: Although previous studies have shown that gut microbiota may be involved in the occurrence of deep venous thrombosis (DVT), the specific link between the two remains unclear. The present study aimed to explore this question from a genetic perspective. Materials and methods: Genome-wide association study (GWAS) summary data of DVT were obtained from the UK Biobank (N = 9,059). GWAS summary data of the gut microbiota were obtained from the Flemish Gut Flora Project (N = 2,223) and two German cohorts (FoCus, N = 950; PopGen, N = 717). All the participants were of European ancestry. Linkage disequilibrium score (LDSC) regression has great potential for analyzing the heritability of disease or character traits. LDSC regression was used to analyze the genetic correlation between DVT and the gut microbiota based on the GWAS summary data obtained from previous studies. Mendelian randomization (MR) was used to analyze the genetic causal relationship between DVT and the gut microbiota. We used the random effects inverse variance weighted, MR Egger, weighted median, simple mode, and weighted mode to perform MR analysis. We performed a sensitivity analysis of the MR analysis results by examining heterogeneity and horizontal pleiotropy. Results: Linkage disequilibrium score analysis showed that Streptococcaceae (correlation coefficient = -0.542, SE = 0.237, P = 0.022), Dialister (correlation coefficient = -0.623, SE = 0.316, P = 0.049), Streptococcus (correlation coefficient = -0.576, SE = 0.264, P = 0.029), and Lactobacillales (correlation coefficient = -0.484, SE = 0.237, P = 0.042) had suggestive genetic correlation with DVT. In addition, the MR analysis showed that Streptococcaceae had a positive genetic causal relationship with DVT (P = 0.027, OR = 1.005). There was no heterogeneity or horizontal pleiotropy in the MR analysis (P > 0.05). Conclusion: In this study, four gut microbes (Streptococcaceae, Dialister Streptococcus, Lactobacillales) had suggestive genetic correlations with DVT, and Streptococcaceae had a positive causal relationship with DVT. Our findings provide a new research direction for the further study of and prevention of DVT.

Identifying celiac disease-related chemicals by transcriptome-wide association study and chemical-gene interaction analyses.

Celiac disease (CeD) is one of the most common intestinal inflammatory diseases, and its incidence and prevalence have increased over time. CeD affects multiple organs and systems in the body, and environmental factors play a key role in its complex pathogenesis. Although gluten exposure is known to be the causative agent, many unknown environmental factors can trigger or exacerbate CeD. In this study, we investigated the influence of genetic and environmental factors on CeD. Data from a CeD genome-wide association study that included 12,041 CeD cases and 12,228 controls were used to conduct a transcriptome-wide association study (TWAS) using FUSION software. Gene expression reference data were obtained for the small intestine, whole blood, peripheral blood, and lymphocytes. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significant genes identified by the TWAS and conducted a protein-protein interaction network analysis based on the STRING database to detect the function of TWAS-identified genes for CeD. We also performed a chemical-related gene set enrichment analysis (CGSEA) using the TWAS-identified genes to test the relationships between chemicals and CeD. The TWAS identified 8,692 genes, including 101 significant genes (p adjusted < 0.05). The CGSEA identified 2,559 chemicals, including 178 chemicals that were significantly correlated with CeD. This study performed a TWAS (for genetic factors) and CGSEA (for environmental factors) and identified several CeD-associated genes and chemicals. The findings expand our understanding of the genetic and environmental factors related to immune-mediated diseases.

Pulmonary embolism and 529 human blood metabolites: genetic correlation and two-sample Mendelian randomization study.

BACKGROUND: The incidence of pulmonary embolism complications in the literature ranges from 10 to 50%, with a 0.5-10% risk of fatal pulmonary embolism. However, the biological cause of pulmonary embolism is unknown. METHODS: This study used data from the Genome-Wide Association Study (GWAS) of Pulmonary Embolism and Human Blood Metabolites from the UK Biobank, and the data from subjects of European ancestry were analyzed. We explored the relationship between pulmonary embolism and blood metabolites in three ways. We first analyzed the genetic correlation between pulmonary embolism and human blood metabolites using the linkage disequilibrium score regression (LDSC) and then analyzed the causal relationship between pulmonary embolism and meaningful blood metabolites obtained from the LDSC, a procedure for which we used Mendelian randomization analysis. Finally, we obtained transcriptome sequencing data for patients with a pulmonary embolism from the GEO database, analyzed differentially expressed genes (DEGs) in patients with pulmonary embolism versus healthy populations, and compared the DEGs with the resulting blood metabolite genes to further validate the relationship between pulmonary embolism and blood metabolites. RESULT: We found six human blood metabolites genetically associated with pulmonary embolism, stearic acid glycerol phosphate ethanolamine (correlation coefficient = 0.2582, P = 0.0493), hydroxytryptophan (correlation coefficient = 0.2894, P = 0.0435), and N1-methyladenosine (correlation coefficient = 0.0439, P = 0.3728), and a significant causal relationship was discovered between hydroxytryptophan and pulmonary embolism. After screening microarray data from the GEO database, we performed differential gene analysis on the GSE19151 dataset and screened a total of 22,216 genes with P values less than 0.05, including 17,361 upregulated genes and 4854 downregulated genes. By comparing the resulting differentially expressed genes with six genes encoding blood metabolites, LIPC and NAT2 were found to be differentially expressed in association with pulmonary embolism.

Genome- and transcriptome-wide association studies show that pulmonary embolism is associated with bone-forming proteins.

BACKGROUND: Pulmonary embolism (PE) is a leading cause of death in stroke patients and a severe health burden worldwide. There is a pressing need to understand the mechanisms by which it occurs and to identify at-risk patients efficiently and accurately. METHODS: First, based on data from GWAS in European populations, we performed a linkage disequilibrium score regression (LDSC) analysis of plasma proteins and PE in 3,283 individuals and additionally analyzed the genetic association between PE and fracture. Then, we performed a TWAS on PE GWAS data using skeletal muscle and blood for gene expression references. Finally, we validated the genetic correlation between PE and human plasma proteins by co-matching the genes encoding the identified proteins and those identified using TWAS with the differentially expressed genes obtained from mRNA expression profiling of PE. RESULTS: We identified five plasma proteins associated with PE, including hydroxycarboxylic acid receptor 2, defensin 118, and bone morphogenetic protein (BMP) 7, as well as a relationship between PE and fracture. Comparison of genes encoding these proteins with genes obtained from TWAS and then with differentially expressed genes obtained from PE mRNA expression profiling revealed that PE was highly correlated with the BMP family of genes.

Transcriptome-Wide Association Studies and Integration Analysis of mRNA Expression Profiles Identify Candidate Genes and Pathways Associated With Ankylosing Spondylitis.

This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data. AS genome-wide association study (GWAS) summary data from the large GWAS database were used. This included data of 1265 AS patients and 452264 controls. A TWAS of AS was conducted using these data. The analysis software used was FUSION, and Epstein-Barr virus-transformed lymphocytes, transformed fibroblasts, peripheral blood, and whole blood were used as gene expression references. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the important genes identified via TWAS. Protein-protein interaction (PPI) network analysis based on the STRING database was also performed to detect genes shared by TWAS and mRNA expression profiles in AS. TWAS identified 920 genes (P <0.05) and analyzed mRNA expression profiles to obtain 1183 differential genes. Following comparison of the TWAS results and mRNA expression characteristics, we obtained 70 overlapping genes and performed GO and KEGG enrichment analyses of these genes to obtain 16 pathways. Via PPI network analysis, we obtained the protein interaction network and performed MCODE analysis to acquire the HUB genes. Similarly, we performed GO and KEGG analyses on the genes identified by TWAS, obtained 98 pathways after screening, and analyzed protein interactions via the PPI network. Through the integration of TWAS and mRNA expression analysis, genes related to AS and GO and KEGG terms were determined, providing new evidence and revealing the pathogenesis of AS. Our AS TWAS work identified novel genes associated with AS, as well as suggested potential tissues and pathways of action for these TWAS AS genes, providing a new direction for research into the pathogenesis of AS.

Identifying Environmental Endocrine Disruptors Associated With the Age at Menarche by Integrating a Transcriptome-Wide Association Study With Chemical-Gene-Interaction Analysis.

Menarche is the first occurrence of menstrual bleeding and one of the most important events of female puberty. Alarmingly, over the last several decades, the mean age at menarche (AAM) has decreased. Environmental endocrine disruptors (EEDs) are chemicals that may interfere with the endocrine system, resulting in adverse developmental, immunological, neurological, and reproductive effects in humans. Thus, the effects of EEDs on fertility and reproduction are growing concerns in modern societies. In this study, we aimed to determine the influence of genetic and environmental factors on AAM. We used data from an AAM genome-wide association study of 329,345 women to conduct a transcriptome-wide association study (TWAS) with FUSION software. As references, we determined the gene-expression levels in the hypothalamus, pituitary gland, ovaries, uterus, and whole blood. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significantly dysregulated genes identified by the TWAS. Using the STRING database, we also generated a protein-protein-interaction network to analyze common AAM-specific genes identified by the TWAS with different tissues. We performed chemical-related gene set enrichment analysis (CGSEA) and identified significant TWAS genes to uncover relationships between different chemicals and AAM. The TWAS identified 9,848 genes; among these, 1580 genes were significant (P < 0.05), and 11 genes were significant among the hypothalamus, pituitary, ovary, uterus, and whole blood. CGSEA identified 1,634 chemicals, including 120 chemicals significantly correlated with AAM. In summary, we performed a TWAS (for genetic factors) and CGSEA (for environmental factors) focusing on AAM and identified several AAM-associated genes and EEDs. The results of this study expand our understanding of genetic and environmental factors related to the onset of female puberty.

A large-scale genetic correlation scan between rheumatoid arthritis and human plasma protein.

AIMS: The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA). METHODS: Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls. RESULTS: We found that seven kinds of plasma proteins had genetic correlations with RA, such as Soluble Receptor for Advanced Glycation End Products (sRAGE) (correlation coefficient = 0.2582, p = 0.049), vesicle transport protein USE1 (correlation coefficient = 0.1337, p = 0.018), and spermatogenesis-associated protein 20 (correlation coefficient = 0.3706, p = 0.018). There was a significant causal relationship between sRAGE and RA. By comparing the genes encoding seven plasma proteins, we found that only USE1 was a DEG associated with RA. CONCLUSION: Our study identified a set of candidate plasma proteins that showed signals correlated with RA. Since the results of this study need further experimental verification, they should be interpreted with caution. However, we hope that this paper will provide new insights for the discovery of pathogenic genes and RA pathogenesis in the future. Cite this article: Bone Joint Res 2022;11(2):134-142.

An ultrasensitive and point-of-care sensor for the telomerase activity detection.

Telomerase owns great application potential in diagnosis, therapy, prognosis, and drug screening of cancers. Thus, the ultrasensitive and point-of-care detection of telomerase activity meets the clinical demands extremely. Here, a sensor based on telomerase extends activators to unlock the ssDNase activity of CRISPR/Cas12a was created for the first time to detect the telomerase activity. Based on the fluorescence or CRISPR/Cas12a-based lateral flow assay, we achieve the ultrasensitive and point-of-care detection of telomerase activity in MCF-7 cells low to 57 cells·mL-1 and 5.7 × 102 cells·mL-1 in about 1 h, respectively. Besides, the detection of telomerase activity in different subtype breast cancer cells indicates that the proposed sensor possesses potential in the classification of breast cancer cell subtypes.

Treatment of Surgical Brain Injury by Immune Tolerance Induced by Peripheral Intravenous Injection of Biotargeting Nanoparticles Loaded With Brain Antigens.

Once excessive, neurological disorders associated with inflammatory conditions will inevitably cause secondary inflammatory damage to brain tissue. Immunosuppressive therapy can reduce the inflammatory state, but resulting infections can expose the patient to greater risk. Using specific immune tolerance organs or tissues from the body, brain antigen immune tolerance treatment can create a minimal immune response to the brain antigens that does not excessively affect the body's immunity. However, commonly used immune tolerance treatment approaches, such as those involving the nasal, gastrointestinal mucosa, thymus or liver portal vein injections, affect the clinical conversion of the therapy due to uncertain drug absorption, or inconvenient routes of administration. If hepatic portal intravenous injections of brain antigens could be replaced by normal peripheral venous infusion, the convenience of immune tolerance treatment could certainly be greatly increased. We attempted to encapsulate brain antigens with minimally immunogenic nanomaterials, to control the sizes of nanoparticles within the range of liver Kupffer cell phagocytosis and to coat the antigens with a coating material that had an affinity for liver cells. We injected these liver drug-loaded nanomaterials via peripheral intravenous injection. With the use of microparticles with liver characteristics, the brain antigens were transported into the liver out of the detection of immune armies in the blood. This approach has been demonstrated in rat models of surgical brain injury. It has been proven that the immune tolerance of brain antigens can be accomplished by peripheral intravenous infusion to achieve the effect of treating brain trauma after operations, which simplifies the clinical operation and could elicit substantial improvements in the future.

Nanoparticles based on disulfide-containing poly(ß-amino ester) and zwitterionic fluorocarbon surfactant as a redox-responsive drug carrier for brain tumor treatment.

Malignant brain tumors are often characterized by rapid growth, high invasiveness and poor prognosis. Current methods for brain tumor treatment are dramatically limited because of their inability to cross the blood-brain barrier (BBB) and enter the tumor cells. In this study, we prepared redox-responsive nanoparticles based on disulfide-containing poly(ß-amino ester) (ssPBAE) and a zwitterionic fluorocarbon surfactant (Intechem-02) that has a carboxybetaine moiety in molecular structure, and preliminarily evaluated their potential as a drug carrier for brain tumor treatment. These nanoparticles, named as ssPBAEI, had a regular spherical shape and a small size below 50 nm with a relative narrow distribution. Doxorubicin (DOX), as a model chemotherapeutic drug, was efficiently encapsulated into ssPBAEI nanoparticles with a loading content of 25.4%. DOX-loaded ssPBAEI nanoparticles (ssPBAEI/DOX) showed significant redox-responsive in vitro release property and successfully carried DOX across a BBB model, monolayer of human brain capillary endothelial hCMEC/D3 cells. In human glioma LN229 cells, ssPBAEI/DOX nanoparticles were efficiently internalized and DOX was successfully released afterwards, thus significantly inhibited cell growth and induced cell apoptosis. In summary, this nanoparticle system based on ssPBAE and Intechem-02 showed a great potential as a drug carrier for brain tumor treatment.

Immune Tolerance Therapy: A New Method for Treatment of Traumatic Brain Injury.

OBJECTIVE: Due to the special anatomical structure and pathophysiological mechanism of the central nervous system (CNS), there is a big difference between the repair of brain injury and other systems of the body. More and more evidence shows that targetedly reducing the autoimmune response of brain tissue without affecting the immune function in other parts of the body will be the best optimized treatment for brain injury. DATA SOURCES: This review was based on data in articles published in PubMed up to June 5, 2017, with the following keywords: "immune tolerance", "traumatic brain injury", and "central nervous system". STUDY SELECTION: Original articles and critical reviews on immune tolerance and brain damage were selected for this review. References of the retrieved articles were also screened to search for potentially relevant papers. RESULTS: The CNS is isolated from the immune system through the blood-brain barrier. After brain injury, brain antigens are released into the systemic circulation to induce damaging immune responses. Immune tolerance can effectively reduce the brain edema and neurological inflammatory response after brain injury, which is beneficial to the recovery of neurological function. The clinical application prospect and theoretical research value of the treatment of immune tolerance on traumatic brain injury (TBI) is worth attention. CONCLUSIONS: The establishment of immune tolerance mechanism has a high clinical value in the treatment of TBI. It opens up new opportunities for the treatment of brain damage.