ABSTRACT
Humans exhibit considerable variability in their immune responses to the same immune challenges. Such variation is widespread and affects individual and population-level susceptibility to infectious diseases and immune disorders. Although the factors influencing immune response diversity are partially understood, what mechanisms lead to the wide range of immune traits in healthy individuals remain largely unexplained. Here, we discuss the role that natural selection has played in driving phenotypic differences in immune responses across populations and present-day susceptibility to immune-related disorders. Further, we touch on future directions in the field of immunogenomics, highlighting the value of expanding this work to human populations globally, the utility of modeling the immune response as a dynamic process, and the importance of considering the potential polygenic nature of natural selection. Identifying loci acted upon by evolution may further pinpoint variants critically involved in disease etiology, and designing studies to capture these effects will enrich our understanding of the genetic contributions to immunity and immune dysregulation.
Subject(s)
Selection, Genetic , Humans , Animals , Genetic Predisposition to Disease , Immunity/genetics , Genetic Variation , Genetics, Population , Phenotype , Disease Susceptibility/immunologyABSTRACT
Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.
Subject(s)
Breast Neoplasms , Genetic Predisposition to Disease , Genome-Wide Association Study , RNA Splicing , Transcriptome , Humans , Breast Neoplasms/genetics , Female , RNA Splicing/genetics , Introns/genetics , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Gene Expression ProfilingABSTRACT
Single-cell RNA sequencing (scRNA-seq) technology is poised to replace bulk cell RNA sequencing for many biological and medical applications as it allows users to measure gene expression levels in a cell type-specific manner. However, data produced by scRNA-seq often exhibit batch effects that can be specific to a cell type, to a sample, or to an experiment, which prevent integration or comparisons across multiple experiments. Here, we present Dmatch, a method that leverages an external expression atlas of human primary cells and kernel density matching to align multiple scRNA-seq experiments for downstream biological analysis. Dmatch facilitates alignment of scRNA-seq data sets with cell types that may overlap only partially and thus allows integration of multiple distinct scRNA-seq experiments to extract biological insights. In simulation, Dmatch compares favorably to other alignment methods, both in terms of reducing sample-specific clustering and in terms of avoiding overcorrection. When applied to scRNA-seq data collected from clinical samples in a healthy individual and five autoimmune disease patients, Dmatch enabled cell type-specific differential gene expression comparisons across biopsy sites and disease conditions and uncovered a shared population of pro-inflammatory monocytes across biopsy sites in RA patients. We further show that Dmatch increases the number of eQTLs mapped from population scRNA-seq data. Dmatch is fast, scalable, and improves the utility of scRNA-seq for several important applications. Dmatch is freely available online.
Subject(s)
RNA-Seq/methods , Single-Cell Analysis/methods , Cluster Analysis , Gene Expression Profiling , HumansABSTRACT
Humans display remarkable interindividual variation in their immune response to identical challenges. Yet, our understanding of the genetic and epigenetic factors contributing to such variation remains limited. Here we performed in-depth genetic, epigenetic and transcriptional profiling on primary macrophages derived from individuals of European and African ancestry before and after infection with influenza A virus. We show that baseline epigenetic profiles are strongly predictive of the transcriptional response to influenza A virus across individuals. Quantitative trait locus (QTL) mapping revealed highly coordinated genetic effects on gene regulation, with many cis-acting genetic variants impacting concomitantly gene expression and multiple epigenetic marks. These data reveal that ancestry-associated differences in the epigenetic landscape can be genetically controlled, even more than gene expression. Lastly, among QTL variants that colocalized with immune-disease loci, only 7% were gene expression QTL, while the remaining genetic variants impact epigenetic marks, stressing the importance of considering molecular phenotypes beyond gene expression in disease-focused studies.
Subject(s)
Influenza, Human , Humans , Influenza, Human/genetics , Individuality , Quantitative Trait Loci/genetics , Chromosome Mapping , Epigenesis, GeneticABSTRACT
INTRODUCTION: The relationship between progesterone (P) and diabetic nephropathy (DKD) is unclear. Herein, we investigated the relationship between progesterone and DKD in men and postmenopausal women with type 2 diabetes mellitus. MATERIALS AND METHODS: We recruited 3,556 male and postmenopausal female patients and obtained the dominance ratio (OR) and corresponding 95% confidence intervals (CIs) associated with progesterone by logistic regression analysis after adjusting for potentially confounding variants. RESULTS: We found that progesterone levels were significantly lower in the massive proteinuria and microproteinuria groups compared with the non-DKD group for male patients. Also, microproteinuria and massive proteinuria prevalence were higher in the first (lowest) progesterone quartile than in the second to fourth quartiles. After adjusting for confounders, compared with the first (lowest) progesterone quartile group, the OR for the second to fourth quartiles in the male microproteinuria subgroup, were: Q2: 0.846 (95% CI: 0.581-1.233, P = 0.385); Q3: 0.667 (95% CI: 0.45-0988, P = 0.044); Q4: 0.597 (95% CI: 0.393-0.907, P = 0.016). In the male massive proteinuria subgroup, the OR for the third quartile group was 0.418 (95% CI: 0.201-0.867, P = 0.019). In contrast, no significant association was detected between progesterone and DKD prevalence in the female group. CONCLUSIONS: Progesterone levels were negatively associated with DKD incidence in hospitalized male patients with type 2 diabetes mellitus.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetic Nephropathies , Humans , Male , Female , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/epidemiology , Retrospective Studies , Progesterone , Cross-Sectional Studies , Diabetic Nephropathies/etiology , Proteinuria/complicationsABSTRACT
Metabolic reprogramming in malignant cells is a hallmark of cancer that relies on augmented glycolytic metabolism to support their growth, invasion, and metastasis. However, the impact of global adipose metabolism on tumor growth and the drug development by targeting adipose metabolism remain largely unexplored. Here we show that a therapeutic paradigm of drugs is effective for treating various cancer types by browning adipose tissues. Mirabegron, a clinically available drug for overactive bladders, displays potent anticancer effects in various animal cancer models, including untreatable cancers such as pancreatic ductal adenocarcinoma and hepatocellular carcinoma, via the browning of adipose tissues. Genetic deletion of the uncoupling protein 1, a key thermogenic protein in adipose tissues, ablates the anticancer effect. Similarly, the removal of brown adipose tissue, which is responsible for non-shivering thermogenesis, attenuates the anticancer activity of mirabegron. These findings demonstrate that mirabegron represents a paradigm of anticancer drugs with a distinct mechanism for the effective treatment of multiple cancers.
Subject(s)
Adipose Tissue, White , Neoplasms , Animals , Adipose Tissue, White/metabolism , Adipose Tissue, Brown/metabolism , Acetanilides/pharmacology , Acetanilides/metabolism , Energy Metabolism , Thermogenesis , Neoplasms/metabolism , Uncoupling Protein 1/genetics , Uncoupling Protein 1/metabolismABSTRACT
Circular RNA (circRNA) is implicated in many types of cancer; however, the expression and role of circRNAs in colorectal cancer (CRC) remains poorly understood. In this study, a circRNA microarray assay was performed to detect abnormally expressed circRNAs in CRC, and tissue arrays were used to determine the prognosis for CRC patients. Cell counting kit-8, clone formation, wound healing, and transwell assays were used to evaluate cell functions in vitro, and a mouse subcutaneous tumor model was designed for in vivo analysis. Autophagy was observed using confocal laser scanning and transmission electron microscopy. The expression of circRNA, miRNA, and mRNA was detected using qPCR; western blot, RNA pull-down assay, RNA immunoprecipitation, and dual luciferase assessment were applied for mechanistic studies. We found that circRNA_103948 expression is upregulated in CRC tissues, compared with adjacent normal tissues, and associated with poor prognosis. Knockdown of circRNA_103948 suppressed CRC both in vitro and in vivo. Mechanistically, circRNA_103948 could directly bind to miR-1236-3p and relieve suppression of the target TPT1. Furthermore, circRNA_103948 inhibited autophagy of CRC cells. Taken together, circRNA_103948 knockdown inhibited CRC cell growth by targeting miR-1236-3p/TPT1 axis-mediated autophagy. Thus, the circRNA_103948/miR-1236-3p/TPT1 axis affects CRC progression via modulation of autophagy.
Subject(s)
Autophagy/genetics , Colorectal Neoplasms/genetics , Gene Expression Regulation, Neoplastic , RNA, Circular , Apoptosis/genetics , Biomarkers, Tumor , Cell Line, Tumor , Cell Movement/genetics , Colorectal Neoplasms/metabolism , Colorectal Neoplasms/pathology , Genes, Reporter , Humans , MicroRNAs/genetics , RNA Interference , RNA, Messenger/genetics , Up-RegulationABSTRACT
BACKGROUND: The vast majority of trait-associated variants identified using genome-wide association studies (GWAS) are noncoding, and therefore assumed to impact gene regulation. However, the majority of trait-associated loci are unexplained by regulatory quantitative trait loci (QTLs). RESULTS: We perform a comprehensive characterization of the putative mechanisms by which GWAS loci impact human immune traits. By harmonizing four major immune QTL studies, we identify 26,271 expression QTLs (eQTLs) and 23,121 splicing QTLs (sQTLs) spanning 18 immune cell types. Our colocalization analyses between QTLs and trait-associated loci from 72 GWAS reveals that genetic effects on RNA expression and splicing in immune cells colocalize with 40.4% of GWAS loci for immune-related traits, in many cases increasing the fraction of colocalized loci by two fold compared to previous studies. Notably, we find that the largest contributors of this increase are splicing QTLs, which colocalize on average with 14% of all GWAS loci that do not colocalize with eQTLs. By contrast, we find that cell type-specific eQTLs, and eQTLs with small effect sizes contribute very few new colocalizations. To investigate the 60% of GWAS loci that remain unexplained, we collect H3K27ac CUT&Tag data from rheumatoid arthritis and healthy controls, and find large-scale differences between immune cells from the different disease contexts, including at regions overlapping unexplained GWAS loci. CONCLUSION: Altogether, our work supports RNA splicing as an important mediator of genetic effects on immune traits, and suggests that we must expand our study of regulatory processes in disease contexts to improve functional interpretation of as yet unexplained GWAS loci.
Subject(s)
Gene Expression Regulation , Genetic Association Studies , Genetic Variation , Immunity/genetics , Quantitative Trait Loci , Quantitative Trait, Heritable , Arthritis, Rheumatoid/etiology , Arthritis, Rheumatoid/metabolism , Arthritis, Rheumatoid/pathology , Chromosome Mapping , Databases, Nucleic Acid , Disease Susceptibility , Gene Expression Profiling , Genetic Association Studies/methods , Genetic Predisposition to Disease , Genome-Wide Association Study/methods , Histones/metabolism , Humans , Immunomodulation/genetics , Organ Specificity , TranscriptomeABSTRACT
Little is known about co-transcriptional or post-transcriptional regulatory mechanisms linking noncoding variation to variation in organismal traits. To begin addressing this gap, we used 3' Seq to study the impact of genetic variation on alternative polyadenylation (APA) in the nuclear and total mRNA fractions of 52 HapMap Yoruba human lymphoblastoid cell lines. We mapped 602 APA quantitative trait loci (apaQTLs) at 10% FDR, of which 152 were nuclear specific. Effect sizes at intronic apaQTLs are negatively correlated with eQTL effect sizes. These observations suggest genetic variants can decrease mRNA expression levels by increasing usage of intronic PAS. We also identified 24 apaQTLs associated with protein levels, but not mRNA expression. Finally, we found that 19% of apaQTLs can be associated with disease. Thus, our work demonstrates that APA links genetic variation to variation in gene expression, protein expression, and disease risk, and reveals uncharted modes of genetic regulation.
Subject(s)
Gene Expression Regulation , Polyadenylation/genetics , Cell Line , HumansABSTRACT
AIM: The aim of this study was to investigate whether there are blood glucose fluctuations in gout patients with hyperuricemia and normal glucose tolerance, and the effect of urate-lowering therapy on blood glucose fluctuations. METHODS: Thirty patients with newly diagnosed gout, hyperuricemia and normal glucose tolerance were enrolled in our study. Continuous glucose monitoring system (CGMS) was used to detect the blood glucose fluctuations of these gout patients. Changes in blood glucose fluctuations after allopurinol therapy were also evaluated. RESULTS: Compared with the reference values of blood glucose fluctuation parameters in China, gout patients had greater glycemic fluctuations including higher mean amplitude of glucose excursions (MAGE) (4.65 vs 1.94 mmol/L, P < .001), higher largest amplitude of blood glucose excursions (LAGE) (4.99 vs 3.72 mmol/L, P < .001) and higher standard deviations of blood glucose (SDBG) (1.36 vs 0.79 mmol/L, P < .001). MAGE was significantly correlated with uric acid (ß = .007, P = .024) and HOMA-insulin resistance (IR) (ß = .508, P = .03). Allopurinol treatment significantly reduced MAGE (4.16 vs 4.65 mmol/L, P < .001), SDBG (0.99 vs 1.36 mmol/L, P < .001) and HOMA-IR (2.26 vs 3.01, P < .001) in gout patients. CONCLUSION: Blood glucose fluctuation increased even in the stage of normal glucose tolerance among gout patients. Blood glucose fluctuations in gout patients were associated with the level of serum uric acid and allopurinol could decrease blood glucose fluctuation as well as IR.
Subject(s)
Allopurinol/therapeutic use , Blood Glucose Self-Monitoring , Blood Glucose/drug effects , Gout Suppressants/therapeutic use , Gout/drug therapy , Hyperuricemia/drug therapy , Uric Acid/blood , Adult , Aged , Allopurinol/adverse effects , Biomarkers/blood , Blood Glucose/metabolism , Down-Regulation , Female , Gout/blood , Gout/diagnosis , Gout Suppressants/adverse effects , Humans , Hyperuricemia/blood , Hyperuricemia/diagnosis , Insulin Resistance , Male , Middle Aged , Predictive Value of Tests , Time Factors , Treatment Outcome , Young AdultABSTRACT
INTRODUCTION: Clinical guidelines have recommended a target of serum uric acid (SUA) level below 6.0 mg/dL for the urate-lowering therapy (ULT) of gout patients, but there are still a high proportion of patients failing to achieve the therapeutic target above. This study aimed to identify possible predictors of poor response to ULT in gout patients. METHODS: We performed a post-hoc analysis of a multicenter randomized double-blind trial which assessed the efficacy of febuxostat in patients with hyperuricemia (serum urate level ≥ 8.0 mg/dL) and gout. Demographic characters and baseline data including SUA levels were collected. Poor response to ULT was defined as average SUA after ULT was more than 6.0 mg/dL. Factors associated with poor response to ULT in gout patients were analyzed, and multivariate logistic regression analysis was also carried out to find out those independent predictors. RESULTS: A total of 370 patients were enrolled in this post-hoc analysis. Compared with those with good response to ULT, patients with poor response to ULT had younger age (P < 0.001), higher proportion of obesity (P = 0.003), higher proportion of statins use (P = 0.019), higher body mass index (BMI) (P < 0.001), higher baseline SUA (P < 0.001), higher proportion of males (P = 0.001), higher alanine transaminase (P < 0.001), higher aspartate transaminase (P = 0.017), higher total cholesterol (P = 0.005), higher triglyceride (P = 0.042), and higher low density lipoprotein (P = 0.037). Multivariate logistic regression analysis showed that younger age (odds ratio (OR) = 0.965, 95% CI 0.943-0.987, P = 0.002), higher BMI (OR = 1.133, 95% CI 1.049-1.224, P = 0.001), higher baseline SUA (OR = 1.006, 95% CI 1.002-1.009, P = 0.001), and no application of febuxostat therapy (OR = 0.41, 95% CI 0.25-0.68, P < 0.001) were independent predictors of poor response to ULT in patients with gout. CONCLUSION: In patients with gout and hyperuricemia, younger age, higher BMI, and higher baseline SUA are predictors of poor response to ULT. These findings could help physicians better identify patients who may fail in ULT and give individualized treatment precisely. TRIAL REGISTRATION: The trial was registered at chinadrugtrials.org.cn in 2012 (CTR20130172).Key Points⢠A post-hoc analysis of a multicenter randomized double-blind trial which assessed the efficacy of febuxostat in patients with hyperuricemia and gout was performed.⢠Multivariate logistic regression analysis showed that younger age, higher BMI, and higher baseline SUA are predictors of poor response to urate-lowering therapy.
Subject(s)
Gout Suppressants/therapeutic use , Gout/drug therapy , Hyperuricemia/drug therapy , Adult , Female , Gout/complications , Humans , Hyperuricemia/complications , Male , Middle Aged , Treatment FailureSubject(s)
Carcinoma, Hepatocellular , Fatty Liver , Liver Neoplasms , Humans , Fatty Liver/pathology , Liver CirrhosisABSTRACT
PURPOSE: Serum platinum is measurable for years after completion of cisplatin-based chemotherapy (CBC). We report the largest investigation of serum platinum levels to date of 1,010 testicular cancer survivors (TCS) assessed 1-35 years after CBC and evaluate genetic contributions to these levels. EXPERIMENTAL DESIGN: Eligible TCS given 300 or 400 (±15) mg/m2 cisplatin underwent extensive audiometric testing, clinical examination, completed questionnaires, and had crude serum platinum levels measured. Associations between serum platinum and various risk factors and toxicities were assessed after fitting a biexponential model adjusted for follow-up time and cumulative cisplatin dose. A genome-wide association study (GWAS) was performed using the serum platinum residuals of the dose and time-adjusted model. RESULTS: Serum platinum levels exceeded the reference range for approximately 31 years, with a strong inverse relationship with creatinine clearance at follow-up (age-adjusted P = 2.13 × 10-3). We observed a significant, positive association between residual platinum values and luteinizing hormone (age-adjusted P = 6.58 × 10-3). Patients with high residual platinum levels experienced greater Raynaud phenomenon than those with medium or low levels (age-adjusted ORhigh/low = 1.46; P = 0.04), as well as a higher likelihood of developing tinnitus (age-adjusted ORhigh/low = 1.68, P = 0.07). GWAS identified one single-nucleotide polymorphism (SNP) meeting genome-wide significance, rs1377817 (P = 4.6 × 10-8, a SNP intronic to MYH14). CONCLUSIONS: This study indicates that residual platinum values are correlated with several cisplatin-related toxicities. One genetic variant is associated with these levels.
Subject(s)
Antineoplastic Agents/blood , Cisplatin/blood , Testicular Neoplasms/blood , Testicular Neoplasms/genetics , Adolescent , Adult , Aged , Antineoplastic Agents/therapeutic use , Cancer Survivors , Cisplatin/therapeutic use , Follow-Up Studies , Genome-Wide Association Study/methods , Humans , Male , Middle Aged , Myosin Heavy Chains/genetics , Myosin Type II/genetics , Polymorphism, Single Nucleotide , Risk Factors , Testicular Neoplasms/drug therapy , Testicular Neoplasms/pathology , Young AdultABSTRACT
Due to the abuse of antibiotics, antibiotic residues can be detected in both natural environment and various industrial products, posing threat to the environment and human health. Here we describe the design and implementation of an engineered Escherichia coli capable of degrading tetracycline (Tc)-one of the commonly used antibiotics once on humans and now on poultry, cattle and fisheries. A Tc-degrading enzyme, TetX, from the obligate anaerobe Bacteroides fragilis was cloned and recombinantly expressed in E. coli and fully characterized, including its K m and k cat value. We quantitatively evaluated its activity both in vitro and in vivo by UV-Vis spectrometer and LC-MS. Moreover, we used a tetracycline inducible amplification circuit including T7 RNA polymerase and its specific promoter PT7 to enhance the expression level of TetX, and studied the dose-response of TetX under different inducer concentrations. Since the deployment of genetically modified organisms (GMOs) outside laboratory brings about safety concerns, it is necessary to explore the possibility of integrating a kill-switch. Toxin-Antitoxin (TA) systems were used to construct a mutually dependent host-plasmid platform and biocontainment systems in various academic and industrious situations. We selected nine TA systems from various bacteria strains and measured the toxicity of toxins (T) and the detoxifying activity of cognate antitoxins (A) to validate their potential to be used to build a kill-switch. These results prove the possibility of using engineered microorganisms to tackle antibiotic residues in environment efficiently and safely.
ABSTRACT
Tumor necrosis factor-α (TNF-α) is a cell signaling protein involved in systemic inflammation, and is also an important cytokine in the acute phase reaction. Several studies suggested a possible association between TNF-α and diabetic peripheral neuropathy (DPN) in type 2 diabetic patients, but no accurate conclusion was available. A systematic review and meta-analysis of observational studies was performed to comprehensively assess the association between serum TNF-α levels and DPN in type 2 diabetic patients. We searched Pubmed, Web of Science, Embase, and China Biology Medicine (CMB) databases for eligible studies. Study-specific data were combined using meta-analysis. Fourteen studies were finally included into the meta-analysis, which involved a total of 2650 participants. Meta-analysis showed that there were obviously increased serum TNF-α levels in DPN patients compared with type 2 diabetic patients without DPN (standard mean difference [SMD] = 1.203, 95 % CI 0.795-1.611, P < 0.001). There were also obviously increased levels of serum TNF-α in diabetic patients with DPN when compared with healthy controls (SMD = 2.364, 95 % CI 1.333-3.394, P < 0.001). In addition, there were increased serum TNF-α levels in painful DPN patients compared with painless DPN patients (SMD = 0.964, 95 % CI 0.237-1.690, P = 0.009). High level of serum TNF-α was significantly associated with increased risk of DPN in patients with type 2 diabetes (odds ratio [OR] = 2.594, 95 % CI 1.182-5.500, P = 0.017). Increased serum levels of TNF-α was not associated with increased risk of painful DPN in patients with type 2 diabetes (OR = 2.486, 95 % CI 0.672-9.193, P = 0.172). Sensitivity analysis showed that there was no obvious change in the pooled estimates when omitting single study by turns. Type 2 diabetic patients with peripheral neuropathy have obviously increased serum TNF-α levels than type 2 diabetic patients without peripheral neuropathy and healthy controls, and high level of serum TNF-α may be associated with increased risk of peripheral neuropathy independently. Further prospective cohort studies are needed to assess the association between TNF-α and DPN.