| 1. |
- Mishra, A., et al.
(författare)
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Stroke genetics informs drug discovery and risk prediction across ancestries
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611
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Tidskriftsartikel (refereegranskat)abstract
- Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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| 2. |
- Williams, R. D., et al.
(författare)
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Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network
- 2022
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. Methods: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. Results: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. Conclusions: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use. © 2022, The Author(s).
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| 3. |
- Reps, J. M., et al.
(författare)
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Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study
- 2021
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Ingår i: JMIR Medical Informatics. - : JMIR Publications Inc.. - 2291-9694. ; 9:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the "prediction model risk of bias assessment" criteria, and it has not been externally validated. Objective: The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases. Methods: We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia. Results: The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68. Conclusions: Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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| 4. |
- Zetterström, P., et al.
(författare)
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Nanoscale defect clusters in metallic glasses
- 2007
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Ingår i: Journal of Physics. - : IOP Publishing. - 0953-8984 .- 1361-648X. ; 19:37, s. 376217-
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Tidskriftsartikel (refereegranskat)abstract
- The reverse Monte Carlo method was used to obtain three-dimensional discrete distributions of constitutional atoms in melt-spun CuZr and CuZrTi metallic glasses from neutron and x-ray diffraction data. It was found that the icosahedral short-range order is less stable in the CuZr binary alloy than in the Ti-doped ternary alloy. The present investigation also provides evidence on the medium-range order, characterized by some nanoscale clusters of defects, in the metallic-glassy state.
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| 5. |
- Cong, D Y, et al.
(författare)
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Crystal structures and textures in the hot-forged Ni-Mn-Ga shape memory alloys
- 2006
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Ingår i: Metallurgical and Materials Transactions. A. - 1073-5623 .- 1543-1940. ; 37A:5, s. 1397-1403
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Tidskriftsartikel (refereegranskat)abstract
- Three ferromagnetic shape-memory alloys with the chemical compositions of Ni53Mn25Ga22, Ni48Mn30Ga22, and Ni48Mn25Ga22Co5 were prepared by the induction-melting and hot-forging process. The crystal structures were investigated by the neutron powder diffraction technique, showing that Ni53Mn25Ga22 and Ni48Mn25Ga22Co5 have a tetragonal, I4/mmm martensitic structure at room temperature, while Ni48Mn30Ga22 has a cubic, L2(1) austenitic structure at room temperature. The development of textures in the hot-forged samples shows the in-plane plastic flow anisotropy from the measured pole figures by means of the neutron diffraction technique. Significant texture changes were observed for the Ni48Mn25Ga22Co5 alloy after room temperature deformation, which is due to the deformation-induced rearrangements of martensitic variants. An excellent shape-memory effect (SME) with a recovery ratio of 74 pct was reported in this Ni48Mn25Ga22Co5 polycrystalline alloy after annealing above the martensitic transformation temperature, and the "shape-memory" influence also occurs in the distributions of grain orientations.
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| 6. |
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| 7. |
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| 8. |
- Jia, N, et al.
(författare)
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Micromechanical behavior and texture evolution of duplex stainless steel studied by neutron diffraction and self-consistent modeling
- 2008
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Ingår i: Acta Materialia. - : Elsevier BV. - 1359-6454 .- 1873-2453. ; 56:4, s. 782-793
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Tidskriftsartikel (refereegranskat)abstract
- Microscopic incompatibility-induced stresses in a duplex stainless steel undergoing plastic deformation are elucidated using a visco-plastic self-consistent model. The model considers not only the grain-orientation-dependent stresses and phase-to-phase interactions, but also texture evolution during deformation. The parameters used for describing the micromechanical behavior of the two-phase polycrystalline material are directly derived from the neutron diffraction data. A reliable prediction of the evolution of grain orientation distributions for both phases at small deformations is achieved after considering various micromechanical interactions of the studied material. © 2007 Acta Materialia Inc.
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| 9. |
- Li, N, et al.
(författare)
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Localized amorphism after high-strain-rate deformation in TWIP steel
- 2011
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Ingår i: Acta Materialia. - : Elsevier. - 1359-6454 .- 1873-2453. ; 59:16, s. 6369-6377
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Tidskriftsartikel (refereegranskat)abstract
- The microstructural features of shear localization, generated by a high-strain-rate deformation (similar to 10(5) s(-1)), of a twinning-induced plasticity (TWIP) steel containing about 17.5 wt.% Mn were well characterized by means of optical microscopy, transmission electron microscopy and electron backscatter diffraction. The high deformation rate was obtained by a ballistic impact penetration test on the TWIP steel sheet. In addition to the deformation twins observed as the main microstructural characterization in the matrix, some shear bands consisting of complex microstructures were also evidenced in the highly deformed area. Inside the shear band, there exist a large region of amorphous phase and a smooth transition zone that also contains nanocrystalline phases. The grain size decreases gradually in the transition zone, changing from a coarse scale (andgt;100 nm) to a fine scale (andlt;10 nm) adjacent to the amorphous region. The coexistence of the amorphous state and the fine-scaled nanocrystalline phase clearly suggests that melting inside the shear bands occurred, which is corroborated by calculations showing a very high rise in temperature due to localized plastic deformation and extremely rapid cooling by heat dissipation into the specimen.
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| 10. |
- Peng, Ru, 1960-, et al.
(författare)
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Interactions between the phase stress and the grain-orientation-dependent stress in duplex stainless steel during deformation
- 2006
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Ingår i: Acta Materialia. - : Elsevier BV. - 1359-6454 .- 1873-2453. ; 54:15, s. 3907-3916
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Tidskriftsartikel (refereegranskat)abstract
- The development of phase stress and grain-orientation-dependent stress under uniaxial compression was investigated in a duplex stainless steel consisting of austenite and ferrite. Using in situ neutron diffraction measurements, the strain response of several h k l planes to the applied compressive stress was mapped as a function of applied stress and sample direction. Analysis based on the experimental results and elastoplastic self-consistent simulations shows that phase stresses of thermal origin further increase during elastic loading but decrease with increased plastic deformation. Grain-orientation-dependent stresses become significant in both austenite and ferrite after loading into the plastic region. After unloading from the plastic regime, a considerable intergranular stress remains in the austenitic phase and dominates over the phase stress. This study provides fundamental experimental inputs for future micromechanical modeling aiming at the evaluation and prediction of the mechanical performance of multiphase materials. © 2006 Acta Materialia Inc.
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