Primary vertex reconstruction using GPUs for the upgrade of the Inner Tracking System of the ALICE experiment at LHC

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Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Primary vertex reconstruction using GPUs for the upgrade of the Inner Tracking System of the ALICE experiment at LHC

In 2021 the Large Hadron Collider at CERN will start its third data taking period, the so- called Run 3, which will last until 2023. During the Long Shutdown 2, the pause between Run 2 and Run 3, the four major experiments at the accelerator (ALICE, ATLAS, CMS, LHCb), are undergoing through major upgrades and working on the apparatus mainte- nance. In particular, the ALICE (A Large Hadron Collider Experiment) experiment is performing a huge upgrade of some detectors at the hardware level and a big effort is ded- icated to the online and offline processes to improve the data acquisition and processing. The ALICE experiment aims at studying the Quark-Gluon Plasma, a state of matter where quarks and gluons are not confined into hadrons and that can be inspected and charac- terised using high-energy ion collisions. Plans for ALICE in Run 3 include the collection of 10 nb−1 of Pb–Pb collisions, with an instantaneous luminosity up to 6 ×1027 cm−2s−1 and a collision rate of 50 kHz at 5.5 TeV, corresponding to a total of 1011 interactions recorded. This is the minimum rate required to address the proposed physics programme that focuses on rare probes both at low and high momentum. For the proton collisions programme, the experimental apparatus will acquire data with a rate up to 400 kHz of interactions at 13 TeV, to obtain a a meaningful data reference, instrumental for the heavy-ion physics programme. ALICE will also move to a brand new paradigm for what concern the data acquisition of many sub-detectors, the so-called continuous readout. This approach fore- sees a trigger-less mode to acquire data continuously; furthermore, data are processed and reconstructed as a stream of data in an on-line mode during the data taking. Such condi- tions impose stringent constraints to the detector performance in terms of acquisition rate and challenges for what concerns the output data bandwidth, forcing a general upgrade of the hardware and the software of the experiment. To comply with this ambitious scenario, many interventions are being operated on sub- detectors of the ALICE apparatus, mostly dedicated to the readout electronics and to sensor readout capabilities, to provide a faster acquisition rate compared to the Run 2 working conditions. Two brand new detectors have also be designed and constructed to improve the precision of physics measurements: a Muon Forward Tracker (MFT) and a completely renovated Inner Tracking System (ITS), the sub-detector dedicated to the re- construction of the interaction vertex, placed within the innermost section of the detector, in the central barrel volume of the ALICE apparatus. The latter is a cylindrical detector built up with seven concentric layers of silicon pixels chips adopting a Monolithic Active Pixels Sensors (MAPS) layout, a new technology for faster and more precise measurements. The upgraded layout is characterised by finer pixel granularity, inner barrel closer to the beam pipe with respect to the ITS used during the LHC Run2 and counts one additional layer for a total of 7 layers. These hardware features translate in a better spatial resolu- tion of the interaction point (tridimensional space point where beams collide) and better resolution for low momentum particles and tracks parameters useful at the data analysis level. The continuous readout set also critical challenges in terms of online data reduction, compression and reconstruction. It is estimated that the whole online reconstruction work- flow will be able to cope with a 3.5 TB/s bandwidth of data in input and will write ∼ 100 GB/s of data on persistent storage. To enable the processing of continuous readout data stream it has been developed a completely renewed software stack which includes parts to be run both online and offline on reconstructed data. The new framework is called Online-Offline (O2). Such a new platform is thought to be deployed both on large comput- ing clusters like the Event Processing Node farm (EPN), the main computing centre used for online reconstruction, located on-site close to the ALICE experimental apparatus, but also on smaller computing resources, down to the single workstation of a scientist. The O2 framework presents a new operational design, compared with former software used in ALICE. It is based on workflows operated by generic logical "devices": computing processes that aims at continuously execute some routine depending on the designed roles. Devices are then plugged each others to create actual pipelines or topologies, where they can com- municate and cooperate to execute more complex tasks. The O2 embodies a multi-process paradigm where each device is represented by a process on a computing resource and the workflows are described by topologies connecting devices following a data-flow models. More in details, each device is responsible to perform a piece of a large routine and the output data are exchanged across devices by mean of messages that can be implemented using different technologies, depending on the underlying computing infrastructure. Every type of workflow in the O2 is described and implemented using this design, from Monte Carlo simulation to online data reconstruction and even the analysis framework is being developed using the same core approach. The schema is flexible and scalable, each en- tity can be, if required, replicated to cope with specific demands and the deployment of a workflow can be done on a laptop as well as on a High-Performance Computing cluster, in some cases. These features are completely transparent to the final user, which will be able to agilely work with both resources with minimal techincal effort. Ultimately, the framework does support heterogeneous architectures, allowing devices to offload payloads on computing accelerators like Graphic Processing Units (GPUs) and Fully Programmable Field Arrays (FPGAs), to obtain high-throughput computations with a fully integrated data model to support them. The work in this thesis will present the design, development and implementation of a primary vertex reconstruction algorithm with ITS-only data that will be used by ALICE in the online reconstruction phase during the Run 3. The estimation of the primary vertex po- sition is instrumental for calibrating detectors because it provides useful information on the beam position. More importantly, it is a critical information for some online reconstruction processes such as the ITS tracking, the process that reconstruct the trajectories of charged particles, as a critical starting point for the process. The work presented is integrated in the O2 framework, and provides both a CPU and a GPU-accelerated parallel version of the algorithm. The algorithm is able to identify also the so-called pile up of events, when data related to more than one collision vertex are present in the same input dataset, and provide their position with a resolution compliant with the physics programme requests. Concern- ing the GPU version, two implementations are presented: on using Nvidia GPUs and one using Advanced Micro Devices (AMD) GPUs. Two versions are coded using the two corre- sponding development frameworks, the Computing Unified Device Architecture (CUDA) for Nvidia and Heterogeneous-Computing Interface for Portability (HIP) from AMD. Con- sistency checks among three implementations are performed, together with performance benchmarks. Time measurements are also reported for comparison the 3 implementations. The primary vertex reconstruction is proven to be compliant with the O2 requirements in terms of resolution and time performance. Knowledge acquired in working on this will be used in future also to further extend the dominion of the GPU-accelerated workflows in the O2 context