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- López-Isac, Elena, et al.
(författare)
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Brief Report : IRF4 Newly Identified as a Common Susceptibility Locus for Systemic Sclerosis and Rheumatoid Arthritis in a Cross-Disease Meta-Analysis of Genome-Wide Association Studies
- 2016
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Ingår i: Arthritis & Rheumatology. - : Wiley. - 2326-5191 .- 2326-5205. ; 68:9, s. 2338-2344
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that have similar clinical and immunologic characteristics. To date, several shared SSc–RA genetic loci have been identified independently. The aim of the current study was to systematically search for new common SSc–RA loci through an interdisease meta–genome-wide association (meta-GWAS) strategy. Methods: The study was designed as a meta-analysis combining GWAS data sets of patients with SSc and patients with RA, using a strategy that allowed identification of loci with both same-direction and opposite-direction allelic effects. The top single-nucleotide polymorphisms were followed up in independent SSc and RA case–control cohorts. This allowed an increase in the sample size to a total of 8,830 patients with SSc, 16,870 patients with RA, and 43,393 healthy controls. Results: This cross-disease meta-analysis of the GWAS data sets identified several loci with nominal association signals (P < 5 × 10−6) that also showed evidence of association in the disease-specific GWAS scans. These loci included several genomic regions not previously reported as shared loci, as well as several risk factors that were previously found to be associated with both diseases. Follow-up analyses of the putatively new SSc–RA loci identified IRF4 as a shared risk factor for these 2 diseases (Pcombined = 3.29 × 10−12). Analysis of the biologic relevance of the known SSc–RA shared loci identified the type I interferon and interleukin-12 signaling pathways as the main common etiologic factors. Conclusion: This study identified a novel shared locus, IRF4, for the risk of SSc and RA, and highlighted the usefulness of a cross-disease GWAS meta-analysis strategy in the identification of common risk loci.
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| 2. |
- Vande Vyvere, Thijs, et al.
(författare)
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Prognostic Validation of the NINDS Common Data Elements for the Radiologic Reporting of Acute Traumatic Brain Injuries : A CENTER-TBI Study.
- 2020
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 37:11, s. 1269-1282
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study is to investigate the prognostic value of using the National Institute of Neurological Disorders and Stroke (NINDS) standardized imaging-based pathoanatomic descriptors for the evaluation and reporting of acute traumatic brain injury (TBI) lesions. For a total of 3392 patients (2244 males and 1148 females, median age = 51 years) enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we extracted 96 Common Data Elements (CDEs) from the structured reports, spanning all three levels of pathoanatomic information (i.e., 20 "basic," 60 "descriptive," and 16 "advanced" CDE variables per patient). Six-month clinical outcome scores were dichotomized into favorable (Glasgow Outcome Scale Extended [GOS-E] = 5-8) versus unfavorable (GOS-E = 1-4). Regularized logistic regression models were constructed and compared using the optimism-corrected area under the curve (AUC). An abnormality was reported for the majority of patients (64.51%). In 79.11% of those patients, there was at least one coexisting pathoanatomic lesion or associated finding. An increase in lesion severity, laterality, and volume was associated with more unfavorable outcomes. Compared with the full set of pathoanatomic descriptors (i.e., all three categories of information), reporting "basic" CDE information provides at least equal discrimination between patients with favorable versus unfavorable outcome (AUC = 0.8121 vs. 0.8155, respectively). Addition of a selected subset of "descriptive" detail to the basic CDEs could improve outcome prediction (AUC = 0.8248). Addition of "advanced" or "emerging/exploratory" information had minimal prognostic value. Our results show that the NINDS standardized-imaging based pathoanatomic descriptors can be used in large-scale studies and provide important insights into acute TBI lesion patterns. When used in clinical predictive models, they can provide excellent discrimination between patients with favorable and unfavorable 6-month outcomes. If further validated, our findings could support the development of structured and itemized templates in routine clinical radiology.
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| 3. |
- Vande Vyvere, Thijs, et al.
(författare)
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Prognostic Validation of the NINDS Standardized Pathoanatomic Terms and Definitions for the Reporting of Acute Traumatic Brain Injuries : A CENTER-TBI study
- 2020
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 37:11, s. 1269-1282
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To aim of this study is to investigate the prognostic value of using the NINDS standardized imaging-based pathoanatomic descriptors for the evaluation and reporting of acute TBI lesions.METHODS: For a total of 3,392 patients (2,244 males and 1,148 females, Median = 51 years) enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we extracted 96 CDEs from the structured reports, spanning all three levels of pathoanatomic information (i.e. 20 "basic", 60 "descriptive" and 16 "advanced" CDE variables per patient). 6-month clinical outcome scores were dichotomized into favorable (GOS-E = 5-8) versus unfavorable (GOS-E = 1-4). Regularized logistic regression models were constructed and compared using the optimism-corrected AUC.RESULTS: An abnormality was reported for the majority of patients (64.51%). In 79.11% of those patients, there was at least one coexisting pathoanatomic lesion or associated finding. An increase in lesion severity, laterality and volume was associated with more unfavorable outcomes. Compared to the full set of pathoanatomic descriptors (i.e. all three categories of information), reporting "basic" CDE information provides at least equal discrimination between patients with favorable versus unfavorable outcome (AUC = 0.8121 vs. 0.8155, respectively). Addition of a selected subset of "descriptive" detail (i.e. location and volume) to specific basic CDEs could improve outcome prediction (AUC = 0.8248). Addition of "advanced" or "emerging" information had minimal prognostic value.CONCLUSION: Our results show that the NINDS standardized-imaging based pathoanatomic descriptors can be used in large-scale studies and provide important insights into acute TBI lesion patterns. When used in clinical predictive models, they can provide excellent discrimination between patients with favorable and unfavorable 6-month outcomes. If further validated, our findings could support the development of structured and itemized templates in routine clinical radiology. Key words: Traumatic Brain Injury, Computed Tomography, Common Data Elements, Structured Reporting.
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