| 1. |
- Wessel, Jennifer, et al.
(author)
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Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility
- 2015
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
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Journal article (peer-reviewed)abstract
- Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF = 1.4%) with lower FG (beta = -0.09 +/- 0.01 mmol l(-1), P = 3.4 x 10(-12)), T2D risk (OR[95% CI] = 0.86[0.76-0.96], P = 0.010), early insulin secretion (beta = -0.07 +/- 0.035 pmol(insulin) mmol(glucose)(-1), P = 0.048), but higher 2-h glucose (beta = 0.16 +/- 0.05 mmol l(-1), P = 4.3 x 10(-4)). We identify a gene-based association with FG at G6PC2 (p(SKAT) = 6.8 x 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF = 20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (beta = 0.02 +/- 0.004 mmol l(-1), P = 1.3 x 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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| 2. |
- Christakoudi, Sofia, et al.
(author)
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Development and validation of the first consensus gene-expression signature of operational tolerance in kidney transplantation, incorporating adjustment for immunosuppressive drug therapy
- 2020
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In: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 58
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Journal article (peer-reviewed)abstract
- Background: Kidney transplant recipients (KTRs) with "operational tolerance" (OT) maintain a functioning graft without immunosuppressive (IS) drugs, thus avoiding treatment complications. Nevertheless, IS drugs can influence gene-expression signatures aiming to identify OT among treated KTRs. Methods: We compared five published signatures of OT in peripheral blood samples from 18 tolerant, 183 stable, and 34 chronic rejector KTRs, using gene-expression levels with and without adjustment for IS drugs and regularised logistic regression. Findings: IS drugs explained up to 50% of the variability in gene-expression and 20-30% of the variability in the probability of OT predicted by signatures without drug adjustment. We present a parsimonious consensus gene-set to identify OT, derived from joint analysis of IS-drug-adjusted expression of five published signature gene-sets. This signature, including CD40, CTLA4, HSD11B1, IGKV4-1, MZB1, NR3C2, and RAB40C genes, showed an area under the curve 0.92 (95% confidence interval 0.88-0.94) in cross-validation and 0.97 (0.93-1.00) in six months follow-up samples. Interpretation: We advocate including adjustment for IS drug therapy in the development stage of gene-expression signatures of OT to reduce the risk of capturing features of treatment, which could be lost following IS drug minimisation or withdrawal. Our signature, however, would require further validation in an independent dataset and a biomarker-led trial. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
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| 3. |
- Christakoudi, Sofia, et al.
(author)
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Steroid regulation : An overlooked aspect of tolerance and chronic rejection in kidney transplantation
- 2018
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In: Molecular and Cellular Endocrinology. - : ELSEVIER IRELAND LTD. - 0303-7207 .- 1872-8057. ; 473, s. 205-216
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Journal article (peer-reviewed)abstract
- Steroid conversion (HSD11B1, HSD11B2, H6PD) and receptor genes (NR3C1, NR3C2) were examined in kidney-transplant recipients with "operational tolerance" and chronic rejection (CR), independently and within the context of 88 tolerance-associated genes. Associations with cellular types were explored. Peripheral whole-blood gene-expression levels (RT-qPCR-based) and cell counts were adjusted for immunosuppressant drug intake. Tolerant (n = 17), stable (n = 190) and CR patients (n = 37) were compared. Healthy controls (n= 14) were used as reference. The anti-inflammatory glucocorticoid receptor (NR3C1) and the cortisol-activating HSD11B1 and H6PD genes were up-regulated in CR and were lowest in tolerant patients. The pro-inflammatory mineralocorticoid gene (NR3C2) was downregulated in stable and CR patients. NR3C1 was associated with neutrophils and NR3C2 with T-cells. Steroid conversion and receptor genes, alone, enabled classification of tolerant patients and were major contributors to gene-expression signatures of both, tolerance and CR, alongside known tolerance-associated genes, revealing a key role of steroid regulation and response in kidney transplantation.
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| 6. |
- Aad, G., et al.
(author)
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Readiness of the ATLAS Tile Calorimeter for LHC collisions
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:4, s. 1193-1236
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Journal article (peer-reviewed)abstract
- The Tile hadronic calorimeter of the ATLAS detector has undergone extensive testing in the experimental hall since its installation in late 2005. The readout, control and calibration systems have been fully operational since 2007 and the detector has successfully collected data from the LHC single beams in 2008 and first collisions in 2009. This paper gives an overview of the Tile Calorimeter performance as measured using random triggers, calibration data, data from cosmic ray muons and single beam data. The detector operation status, noise characteristics and performance of the calibration systems are presented, as well as the validation of the timing and energy calibration carried out with minimum ionising cosmic ray muons data. The calibration systems' precision is well below the design value of 1%. The determination of the global energy scale was performed with an uncertainty of 4%.
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| 7. |
- Aad, G., et al.
(author)
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Studies of the performance of the ATLAS detector using cosmic-ray muons
- 2011
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 71:3
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Journal article (peer-reviewed)abstract
- Muons from cosmic-ray interactions in the atmosphere provide a high-statistics source of particles that can be used to study the performance and calibration of the ATLAS detector. Cosmic-ray muons can penetrate to the cavern and deposit energy in all detector subsystems. Such events have played an important role in the commissioning of the detector since the start of the installation phase in 2005 and were particularly important for understanding the detector performance in the time prior to the arrival of the first LHC beams. Global cosmic-ray runs were undertaken in both 2008 and 2009 and these data have been used through to the early phases of collision data-taking as a tool for calibration, alignment and detector monitoring. These large datasets have also been used for detector performance studies, including investigations that rely on the combined performance of different subsystems. This paper presents the results of performance studies related to combined tracking, lepton identification and the reconstruction of jets and missing transverse energy. Results are compared to expectations based on a cosmic-ray event generator and a full simulation of the detector response.
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| 8. |
- Aad, G., et al.
(author)
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The ATLAS Simulation Infrastructure
- 2010
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In: European Physical Journal C. Particles and Fields. - : Springer Science and Business Media LLC. - 1434-6044 .- 1434-6052. ; 70:3, s. 823-874
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Journal article (peer-reviewed)abstract
- The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.
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| 10. |
- Fusar-Poli, Paolo, et al.
(author)
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The Science of Prognosis in Psychiatry : A Review
- 2018
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In: JAMA psychiatry. - : American Medical Association (AMA). - 2168-6238 .- 2168-622X. ; 75:12, s. 1289-1297
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Research review (peer-reviewed)abstract
- IMPORTANCE Prognosis is a venerable component of medical knowledge introduced by Hippocrates (460-377 BC). This educational review presents a contemporary evidence-based approach for how to incorporate clinical risk prediction models in modern psychiatry. The article is organized around key methodological themes most relevant for the science of prognosis in psychiatry. Within each theme, the article highlights key challenges and makes pragmatic recommendations to improve scientific understanding of prognosis in psychiatry.OBSERVATIONS The initial step to building clinical risk prediction models that can affect psychiatric care involves designing the model: preparation of the protocol and definition of the outcomes and of the statistical methods (theme 1). Further initial steps involve carefully selecting the predictors, preparing the data, and developing the model in these data. A subsequent step is the validation of the model to accurately test its generalizability (theme 2). The next consideration is that the accuracy of the clinical prediction model is affected by the incidence of the psychiatric condition under investigation (theme 3). Eventually, clinical prediction models need to be implemented in real-world clinical routine, and this is usually the most challenging step (theme 4). Advanced methods such as machine learning approaches can overcome some problems that undermine the previous steps (theme 5). The relevance of each of these themes to current clinical risk prediction modeling in psychiatry is discussed and recommendations are given.CONCLUSIONS AND RELEVANCE Together, these perspectives intend to contribute to an integrative, evidence-based science of prognosis in psychiatry. By focusing on the outcome of the individuals, rather than on the disease, clinical risk prediction modeling can become the cornerstone for a scientific and personalized psychiatry.
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