1,657 research outputs found

    Protocol of the adaptive study of IL-2 dose frequency on regulatory T cells in type 1 diabetes (DILfrequency): a mechanistic, non-randomised, repeat dose, open-label, response-adaptive study.

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    INTRODUCTION: Type 1 diabetes (T1D) is caused by autoimmune destruction of the insulin-producing β cells in the pancreatic islets, leading to insulinopenia and hyperglycaemia. Genetic analyses indicate that alterations of the interleukin-2 (IL-2) pathway mediating immune activation and tolerance predispose to T1D, specifically the polymorphic expression of the IL-2 receptor-α chain (CD25) on T lymphocytes. Replacement of physiological doses of IL-2 could restore self-tolerance and prevent further autoimmunity by enhancing the function of CD4(+) T regulatory cells (Tregs) to limit the activation of auto reactive T effector cells (Teffs). In this experimental medicine study, we use an adaptive trial design to determine the optimal dosing regimen for IL-2 to improve Treg function while limiting activation of Teffs in participants with T1D. METHODS AND ANALYSIS: The Adaptive study of IL-2 dose frequency on Tregs in type 1 diabetes(DILfrequency) is a mechanistic, non-randomised, repeat dose open-label, response-adaptive study of 36 participants with T1D. The objective is to establish the optimal dose and frequency of ultra-low dose IL-2: to increase Treg frequency within the physiological range, to increase CD25 expression on Tregs, without increasing CD4(+) Teffs. DILfrequency has an initial learning phase where 12 participants are allocated to six different doses and frequencies followed by an interim statistical analysis. After analysis of the learning phase, the Dose and Frequency Committee will select the optimal targets for Treg frequency, Treg CD25 expression and Teff frequency. Three groups of eight participants will be treated consecutively in the confirming phase. Each dose and frequency selected will be based on statistical analysis of all data collected from the previous groups. ETHICS: Ethical approval for DILfrequency was granted on 12 August 2014. RESULTS: The results of this study will be reported, through peer-reviewed journals, conference presentations and an internal organisational report. TRIAL REGISTRATION NUMBERS: NCT02265809, ISRCTN40319192, CRN17571.This work is funded by The Sir Jules Thorn Award for Biomedical Research 2013 (13/JTA), the JDRF (9-2011-253), the Wellcome Trust (091157) and the National Institute for Health Research Cambridge Biomedical Research Centre. The Cambridge Institute for Medical Research is in receipt of a Wellcome Trust Strategic Award (100140). AM was supported by the Medical Research Council [grant number G0800860] and the National Institute for Health Research Cambridge Biomedical Research Centre.This is the final version of the article. It was first available from BMJ via http://dx.doi.org/10.1136/bmjopen-2015-00979

    A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

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    Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available.This is the final version. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/gepi.21853/abstract

    Widespread seasonal gene expression reveals annual differences in human immunity and physiology.

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    Seasonal variations are rarely considered a contributing component to human tissue function or health, although many diseases and physiological process display annual periodicities. Here we find more than 4,000 protein-coding mRNAs in white blood cells and adipose tissue to have seasonal expression profiles, with inverted patterns observed between Europe and Oceania. We also find the cellular composition of blood to vary by season, and these changes, which differ between the United Kingdom and The Gambia, could explain the gene expression periodicity. With regards to tissue function, the immune system has a profound pro-inflammatory transcriptomic profile during European winter, with increased levels of soluble IL-6 receptor and C-reactive protein, risk biomarkers for cardiovascular, psychiatric and autoimmune diseases that have peak incidences in winter. Circannual rhythms thus require further exploration as contributors to various aspects of human physiology and disease.The Gambian study providing data for analysis was supported by core funding MC-A760-5QX00 to the International Nutrition Group by the UK Medical Research Council (MRC) and the UK Department for the International Development (DFID) under the MRC/DFID Concordat agreement. This work was supported by the JDRF UK Centre for Diabetes-Genes, Autoimmunity and Prevention (D-GAP; 4-2007-1003), the JDRF (9-2011-253), the Wellcome Trust (WT061858/091157), the National Institute for Health Research Cambridge Biomedical Research Centre (CBRC) and the Medical Research Council (MRC) Cusrow Wadia Fund. The research leading to these results has received funding from the European Union’s 7th Framework Programme (FP7/2007–2013) under grant agreement no.241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (WT100140). X.C.D. was a University of Cambridge/Wellcome Trust Infection and Immunity PhD student. R.C.F. is funded by a JDRF post-doctoral fellowship (3-2011-374). C.W. and H.G are funded by the Wellcome Trust (WT089989). The BABYDIET study was supported by grants from the Deutsche Forschungsgemeinschaft (DFG ZI-310/14-1 to-4), the JDRF (JDRF 17-2012-16 and 1-2006-665) and the German Center for Diabetes Research (DZD e.V.). E.B. is supported by the DFG Research Center and Cluster of Excellence—Center for Regenerative Therapies Dresden (FZ 111).This is the final published version. It first appeared at http://www.nature.com/ncomms/2015/150512/ncomms8000/full/ncomms8000.html

    Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes

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    Plasma levels of liver enzymes provide insights into hepatic function and related diseases. Here, the authors perform a genome-wide association study on three liver enzymes, identifying genetic variants associated with their plasma concentration as well as links to metabolic and cardiovascular diseases. Serum concentration of hepatic enzymes are linked to liver dysfunction, metabolic and cardiovascular diseases. We perform genetic analysis on serum levels of alanine transaminase (ALT), alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) using data on 437,438 UK Biobank participants. Replication in 315,572 individuals from European descent from the Million Veteran Program, Rotterdam Study and Lifeline study confirms 517 liver enzyme SNPs. Genetic risk score analysis using the identified SNPs is strongly associated with serum activity of liver enzymes in two independent European descent studies (The Airwave Health Monitoring study and the Northern Finland Birth Cohort 1966). Gene-set enrichment analysis using the identified SNPs highlights involvement in liver development and function, lipid metabolism, insulin resistance, and vascular formation. Mendelian randomization analysis shows association of liver enzyme variants with coronary heart disease and ischemic stroke. Genetic risk score for elevated serum activity of liver enzymes is associated with higher fat percentage of body, trunk, and liver and body mass index. Our study highlights the role of molecular pathways regulated by the liver in metabolic disorders and cardiovascular disease

    Higher thyrotropin leads to unfavorable lipid profile and somewhat higher cardiovascular disease risk: evidence from multi-cohort Mendelian randomization and metabolomic profiling.

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    BACKGROUND: Observational studies suggest interconnections between thyroid status, metabolism, and risk of coronary artery disease (CAD), but causality remains to be proven. The present study aimed to investigate the potential causal relationship between thyroid status and cardiovascular disease and to characterize the metabolomic profile associated with thyroid status. METHODS: Multi-cohort two-sample Mendelian randomization (MR) was performed utilizing genome-wide significant variants as instruments for standardized thyrotropin (TSH) and free thyroxine (fT4) within the reference range. Associations between TSH and fT4 and metabolic profile were investigated in a two-stage manner: associations between TSH and fT4 and the full panel of 161 metabolomic markers were first assessed hypothesis-free, then directional consistency was assessed through Mendelian randomization, another metabolic profile platform, and in individuals with biochemically defined thyroid dysfunction. RESULTS: Circulating TSH was associated with 52/161 metabolomic markers, and fT4 levels were associated with 21/161 metabolomic markers among 9432 euthyroid individuals (median age varied from 23.0 to 75.4 years, 54.5% women). Positive associations between circulating TSH levels and concentrations of very low-density lipoprotein subclasses and components, triglycerides, and triglyceride content of lipoproteins were directionally consistent across the multivariable regression, MR, metabolomic platforms, and for individuals with hypo- and hyperthyroidism. Associations with fT4 levels inversely reflected those observed with TSH. Among 91,810 CAD cases and 656,091 controls of European ancestry, per 1-SD increase of genetically determined TSH concentration risk of CAD increased slightly, but not significantly, with an OR of 1.03 (95% CI 0.99-1.07; p value 0.16), whereas higher genetically determined fT4 levels were not associated with CAD risk (OR 1.00 per SD increase of fT4; 95% CI 0.96-1.04; p value 0.59). CONCLUSIONS: Lower thyroid status leads to an unfavorable lipid profile and a somewhat increased cardiovascular disease risk

    p38 MAPK and JNK Antagonistically Control Senescence and Cytoplasmic p16INK4A Expression in Doxorubicin-Treated Endothelial Progenitor Cells

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    Patients treated with low-dose anthracyclines often show late onset cardiotoxicity. Recent studies suggest that this form of cardiotoxicity is the result of a progenitor cell disease. In this study we demonstrate that Cord Blood Endothelial Progenitor Cells (EPCs) exposed to low, sub-apoptotic doses of doxorubicin show a senescence phenotype characterized by increased SA-b-gal activity, decreased TRF2 and chromosomal abnormalities, enlarged cell shape, and disarrangement of F-actin stress fibers accompanied by impaired migratory ability. P16 INK4A localizes in the cytoplasm of doxorubicin-induced senescent EPCs and not in the nucleus as is the case in EPCs rendered senescent by different stimuli. This localization together with the presence of an arrest in G2, and not at the G1 phase boundary, which is what usually occurs in response to the cell cycle regulatory activity of p16INK4A, suggests that doxorubicin-induced p16 INK4A does not regulate the cell cycle, even though its increase is closely associated with senescence. The effects of doxorubicin are the result of the activation of MAPKs p38 and JNK which act antagonistically. JNK attenuates the senescence, p16 INK4A expression and cytoskeleton remodeling that are induced by activated p38. We also found that conditioned medium from doxorubicin-induced senescent cardiomyocytes does not attract untreated EPCs, unlike conditioned medium from apoptotic cardiomyocytes which has a strong chemoattractant capacity. In conclusion, this study provides a better understanding of the senescence of doxorubicin-treated EPCs, which may be helpful in preventing and treating late onset cardiotoxicity

    CMS physics technical design report : Addendum on high density QCD with heavy ions

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    Peer reviewe

    A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

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    Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G x E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer

    Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

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    Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation
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