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- Lopez-Isac, E, et al.
(författare)
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GWAS for systemic sclerosis identifies multiple risk loci and highlights fibrotic and vasculopathy pathways
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 4955-
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Tidskriftsartikel (refereegranskat)abstract
- Systemic sclerosis (SSc) is an autoimmune disease that shows one of the highest mortality rates among rheumatic diseases. We perform a large genome-wide association study (GWAS), and meta-analysis with previous GWASs, in 26,679 individuals and identify 27 independent genome-wide associated signals, including 13 new risk loci. The novel associations nearly double the number of genome-wide hits reported for SSc thus far. We define 95% credible sets of less than 5 likely causal variants in 12 loci. Additionally, we identify specific SSc subtype-associated signals. Functional analysis of high-priority variants shows the potential function of SSc signals, with the identification of 43 robust target genes through HiChIP. Our results point towards molecular pathways potentially involved in vasculopathy and fibrosis, two main hallmarks in SSc, and highlight the spectrum of critical cell types for the disease. This work supports a better understanding of the genetic basis of SSc and provides directions for future functional experiments.
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| 3. |
- Lourido, L., et al.
(författare)
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A clinical model including protein biomarkers predicts radiographic knee osteoarthritis : a prospective study using data from the Osteoarthritis Initiative
- 2021
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Ingår i: Osteoarthritis and Cartilage. - : Elsevier BV. - 1063-4584 .- 1522-9653. ; 29:8, s. 1147-1154
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Tidskriftsartikel (refereegranskat)abstract
- Objective: We aimed to provide a model to predict the prospective development of radiographic KOA (rKOA). Method: Baseline sera from 333 non-radiographic KOA subjects belonging to OA Initiative (OAI) who developed or not, rKOA during a follow-up period of 96 months were used in this study. The exploratory cohort included 200 subjects, whereas the replication cohort included 133. The levels of inter-alpha trypsin inhibitor heavy chain 1 (ITIH1), complement C3 (C3) and calcyclin (S100A6), identified in pre-vious large proteomic analysis, were analyzed by using sandwich immunoassays on suspension bead arrays. The association of protein levels and clinical covariates with rKOA incidence was assessed by combining logistic regression analysis, Receiver Operating Characteristic (ROC) analysis, Integrated Discrimination Improvement (IDI) analysis and Kaplan-Meier curves. Results: Levels of ITIH1, C3 and S100A6 were significantly associated with the prospective development of rKOA, showing an area under the curve (AUC) of 0.713 (0.624-0.802), 0.708 (0.618-0.799) and 0.654 (0.559-0.749), respectively to predict rKOA in the replication cohort. The inclusion of ITIH1 in the clinical model (age, gender, BMI, previous knee injury and WOMAC pain) improved the predictive capacity of the clinical covariates (AUC = 0.754 [0.670-0.838]) producing the model with the highest AUC (0.786 [0.705-0.867]) and the highest IDI index (9%). High levels of ITIH1 were also associated with an earlier onset of the disease. Conclusion: A clinical model including protein biomarkers that predicts incident rKOA has been devel-oped. Among the tested biomarkers, ITIH1 showed potential to improve the capacity to predict rKOA incidence in clinical practice. (C) 2021 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
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