147 research outputs found
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Platelet responses to agonists in a cohort of highly characterised platelet donors are consistent over time.
BACKGROUND AND OBJECTIVES: Platelet function shows significant inheritance that is at least partially genetically controlled. There is also evidence that the platelet response is stable over time, but there are few studies that have assessed consistency of platelet function over months and years. We aimed to measure platelet function in platelet donors over time in individuals selected from a cohort of 956 donors whose platelet function had been previously characterised. MATERIALS AND METHODS: Platelet function was assessed by flow cytometry, measuring fibrinogen binding and P-selectin expression after stimulation with either cross-linked collagen-related peptide or adenosine 5'-diphosphate. Eighty-nine donors from the Cambridge Platelet Function Cohort whose platelet responses were initially within the lower or upper decile of reactivity were retested between 4 months and five and a half years later. RESULTS: There was moderate-to-high correlation between the initial and repeat platelet function results for all assays (P ≤ 0·007, r2 0·2961-0·7625); furthermore, the range of results observed in the initial low and high responder groups remained significantly different at the time of the second test (P ≤ 0·0005). CONCLUSION: Platelet function remains consistent over time. This implies that this potential influence on quality of donated platelet concentrates will remain essentially constant for a given donor
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The effect of variation in donor platelet function on transfusion outcome: A semi-randomised controlled trial
The effect of variation in platelet function in platelet donors on patient outcome following platelet transfusion is unknown. This trial assessed the hypothesis that platelets collected from donors with highly responsive platelets to agonists in vitro assessed by flow cytometry (high-responder donors) are cleared more quickly from the circulation than those from low-responder donors, resulting in lower platelet count increments following transfusion. This parallel group, semirandomized double-blinded trial was conducted in a single center in the United Kingdom. Eligible patients were those 16 or older with thrombocytopenia secondary to bone marrow failure, requiring prophylactic platelet transfusion. Patients were randomly assigned to receive a platelet donation from a high- or low-responder donor when both were available, or when only 1 type of platelet was available, patients received that. Participants, investigators, and those assessing outcomes were masked to group assignment. The primary end point was the platelet count increment 10 to 90 minutes following transfusion. Analysis was by intention to treat. Fifty-one patients were assigned to receive platelets from low-responder donors, and 49 from high-responder donors (47 of which were randomized and 53 nonrandomized). There was no significant difference in platelet count increment 10 to 90 minutes following transfusion in patients receiving platelets from high-responder (mean, 21.0 × 109/L; 95% confidence interval [CI], 4.9-37.2) or low-responder (mean, 23.3 × 109/L; 95% CI, 7.8-38.9) donors (mean difference, 2.3; 95% CI, −1.1 to 5.7; P = .18). These results support the current policy of not selecting platelet donors on the basis of platelet function for prophylactic platelet transfusion.This work was supported in part by program grants from the NIHR (RP-PG-0310-1002), National Health Service Blood and Transplant (BS07/1R), and NIHR Cambridge BioResource
DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation
Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling. Here we present genome-wide reference maps of the associated DNA methylation dynamics. We used a meta-epigenomic approach that combines DNA methylation profiles across many small pools of cells and performed single-cell methylome sequencing to assess cell-to-cell heterogeneity. The resulting dataset identified characteristic differences between HSCs derived from fetal liver, cord blood, bone marrow, and peripheral blood. We also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors, characterized immature multi-lymphoid progenitors, and detected progressive DNA methylation differences in maturing megakaryocytes. We linked these patterns to gene expression, histone modifications, and chromatin accessibility, and we used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data. Our results contribute to a better understanding of human hematopoietic stem cell differentiation and provide a framework for studying blood-linked diseases.This work was funded by the BLUEPRINT project (European Union’s Seventh Framework Programme grant 282510), the NIHR Cambridge Biomedical Research Centre, and the Austrian Academy of Sciences. F.A.C. is supported by a Medical Research Council Clinical Training Fellowship (grant MR/K024043/1). F.H. is supported by a postdoctoral fellowship of the German Research Council (DFG; grant HA 7723/1-1). J.K. is supported by a DOC Fellowship of the Austrian Academy of Sciences. W.H.O. is supported by the NIHR, BHF (grants PG-0310-1002 and RG/09/12/28096), and NHS Blood and Transplant. E.L. is supported by a Wellcome Trust Sir Henry Dale Fellowship (grant 107630/Z/15/Z) and core support grant from the Wellcome Trust and MRC to the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute. M. Frontini is supported by the BHF Cambridge Centre of Excellence (grant RE/13/6/30180). C.B. is supported by a New Frontiers Group award of the Austrian Academy of Sciences and by a European Research Council (ERC) Starting Grant (European Union’s Horizon 2020 research and innovation program; grant 679146)
Transcriptional characterization of human megakaryocyte polyploidization and lineage commitment
BACKGROUND: Megakaryocytes (MKs) originate from cells immuno-phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. They mature within the adult bone marrow and release platelets into the circulation. Until now, there have been no transcriptional studies of primary human bone marrow MKs. OBJECTIVES: To characterize MKs and HSCs from human bone marrow using single-cell RNA sequencing, to investigate MK lineage commitment, maturation steps, and thrombopoiesis. RESULTS: We show that MKs at different levels of polyploidization exhibit distinct transcriptional states. Although high levels of platelet-specific gene expression occur in the lower ploidy classes, as polyploidization increases, gene expression is redirected toward translation and posttranslational processing transcriptional programs, in preparation for thrombopoiesis. Our findings are in keeping with studies of MK ultrastructure and supersede evidence generated using in vitro cultured MKs. Additionally, by analyzing transcriptional signatures of a single HSC, we identify two MK-biased HSC subpopulations exhibiting unique differentiation kinetics. We show that human bone marrow MKs originate from these HSC subpopulations, supporting the notion that they display priming for MK differentiation. Finally, to investigate transcriptional changes in MKs associated with stress thrombopoiesis, we analyzed bone marrow MKs from individuals with recent myocardial infarction and found a specific gene expression signature. Our data support the modulation of MK differentiation in this thrombotic state. CONCLUSIONS: Here, we use single-cell sequencing for the first time to characterize the human bone marrow MK transcriptome at different levels of polyploidization and investigate their differentiation from the HSC
Polygenic basis and biomedical consequences of telomere length variation
Telomeres, the end fragments of chromosomes, play key roles in cellular proliferation and senescence. Here we characterize the genetic architecture of naturally occurring variation in leukocyte telomere length (LTL) and identify causal links between LTL and biomedical phenotypes in 472,174 well-characterized UK Biobank participants. We identified 197 independent sentinel variants associated with LTL at 138 genomic loci (108 new). Genetically determined differences in LTL were associated with multiple biological traits, ranging from height to bone marrow function, as well as several diseases spanning neoplastic, vascular and inflammatory pathologies. Finally, we estimated that, at the age of 40 years, people with an LTL >1 s.d. shorter than the population mean had a 2.5-year-lower life expectancy compared with the group with ≥1 s.d. longer LDL. Overall, we furnish new insights into the genetic regulation of LTL, reveal wide-ranging influences of LTL on physiological traits, diseases and longevity, and provide a powerful resource available to the global research community
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SNP in human ARHGEF3 promoter is associated with DNase hypersensitivity, transcript level and platelet function, and Arhgef3 KO mice have increased mean platelet volume
Genome-wide association studies have identified a genetic variant at 3p14.3 (SNP rs1354034) that strongly associates with platelet number and mean platelet volume in humans. While originally proposed to be intronic, analysis of mRNA expression in primary human hematopoietic subpopulations reveals that this SNP is located directly upstream of the predominantly expressed ARHGEF3 isoform in megakaryocytes (MK). We found that ARHGEF3, which encodes a Rho guanine exchange factor, is dramatically upregulated during both human and murine MK maturation. We show that the SNP (rs1354034) is located in a DNase I hypersensitive region in human MKs and is an expression quantitative locus (eQTL) associated with ARHGEF3 expression level in human platelets, suggesting that it may be the causal SNP that accounts for the variations observed in human platelet traits and ARHGEF3 expression. In vitro human platelet activation assays revealed that rs1354034 is highly correlated with human platelet activation by ADP. In order to test whether ARHGEF3 plays a role in MK development and/or platelet function, we developed an Arhgef3 KO/LacZ reporter mouse model. Reflecting changes in gene expression, LacZ expression increases during MK maturation in these mice. Although Arhgef3 KO mice have significantly larger platelets, loss of Arhgef3 does not affect baseline MK or platelets nor does it affect platelet function or platelet recovery in response to antibody-mediated platelet depletion compared to littermate controls. In summary, our data suggest that modulation of ARHGEF3 gene expression in humans with a promoter-localized SNP plays a role in human MKs and human platelet function-a finding resulting from the biological follow-up of human genetic studies. Arhgef3 KO mice partially recapitulate the human phenotype.Financial support was provided by NIH grants DK094934, DK086267, and DK0724429 to DSK, HL102482 to PB, the Cardeza Foundation for Hematologic Research (PB), and American Heart Association Fellowship 14PRE20480196 to LMS. MF is supported by the BHF Cambridge Centre of Excellence RE/13/6/30180. PvdH is supported by the Landsteiner Foundation for Blood Transfusion Research grant LSBR1133. LAT was supported by Leukaemia & Lymphoma Research Fellowship 09018. Research in the Ouwehand laboratory is supported by EU-FP7 project BLUEPRINT (282510) and by program grants from the National Institute for Health Research (NIHR); and the British Heart Foundation under numbers RP-PG- 0310-1002 and RG/09/12/28096. The laboratory receives funding from NHS Blood and Transplant for facilities
Meta-Analysis of Genome-Wide Scans for Human Adult Stature Identifies Novel Loci and Associations with Measures of Skeletal Frame Size
Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1×10−8 and rs910316 in TMED10, P-value = 1.4×10−7) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3×10−7 and rs849141 in JAZF1, P-value = 3.2×10−11). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4×10−5 and rs6817306 in LCORL, P-value = 4×10−4), hip axis length (including rs6830062 at LCORL, P-value = 4.8×10−4 and rs4911494 at UQCC, P-value = 1.9×10−4), and femur length (including rs710841 at PRKG2, P-value = 2.4×10−5 and rs10946808 at HIST1H1D, P-value = 6.4×10−6). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height
Population-scale proteome variation in human induced pluripotent stem cells
Human disease phenotypes are driven primarily by alterations in protein expression and/or function. To date, relatively little is known about the variability of the human proteome in populations and how this relates to variability in mRNA expression and to disease loci. Here, we present the first comprehensive proteomic analysis of human induced pluripotent stem cells (iPSC), a key cell type for disease modelling, analysing 202 iPSC lines derived from 151 donors, with integrated transcriptome and genomic sequence data from the same lines. We characterised the major genetic and non-genetic determinants of proteome variation across iPSC lines and assessed key regulatory mechanisms affecting variation in protein abundance. We identified 654 protein quantitative trait loci (pQTLs) in iPSCs, including disease-linked variants in protein-coding sequences and variants with trans regulatory effects. These include pQTL linked to GWAS variants that cannot be detected at the mRNA level, highlighting the utility of dissecting pQTL at peptide level resolution
Increased DNA methylation variability in type 1 diabetes across three immune effector cell types
The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D.This work was funded by the EU-FP7 project BLUEPRINT (282510) and the Wellcome Trust (99148). We thank all twins for taking part in this study; Kerra Pearce and Mark Kristiansen (UCL Genomics) for processing the Illumina Infinium HumanMethylation450 BeadChips; Rasmus Bennet for technical assistance; and Laura Phipps for proofreading the manuscript. The BMBF Pediatric Diabetes Biobank recruits patients from the National Diabetes Patient Documentation System (DPV), and is financed by the German Ministry of Education and Research within the German Competence Net Diabetes Mellitus (01GI1106 and 01GI1109B). It was integrated into the German Center for Diabetes Research in January 2015. We thank the Swedish Research Council and SUS Funds for support. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers, and thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the NIHR Cambridge Biomedical Research Centre for funding. The Cardiovascular Epidemiology Unit is supported by the UK Medical Research Council (G0800270), BHF (SP/09/002), and NIHR Cambridge Biomedical Research Centre. Research in the Ouwehand laboratory is supported by the NIHR, BHF (PG-0310-1002 and RG/09/12/28096) and NHS Blood and Transplant. K.D. is funded as a HSST trainee by NHS Health Education England. M.F. is supported by the BHF Cambridge Centre of Excellence (RE/13/6/30180). A.D., E.L., L.C. and P.F. receive additional support from the European Molecular Biology Laboratory. A.K.S. is supported by an ADA Career Development Award (1-14-CD-17). B.O.B. and R.D.L. acknowledge support from the Deutsche Forschungsgemeinschaft (DFG) and European Federation for the Study of Diabetes, respectively
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