| 1. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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| 2. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- Thomas, HS, et al.
(author)
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- 2019
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- 2019
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Journal article (peer-reviewed)
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| 13. |
- Romagnoni, A, et al.
(author)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Journal article (peer-reviewed)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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| 14. |
- Nagaraja, Ch., et al.
(author)
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Opening remarks
- 2016
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Conference paper (peer-reviewed)
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| 16. |
- Weinstein, John N., et al.
(author)
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The cancer genome atlas pan-cancer analysis project
- 2013
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 45:10, s. 1113-1120
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Research review (peer-reviewed)abstract
- The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. © 2013 Nature America, Inc. All rights reserved.
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| 17. |
- Momozawa, Y, et al.
(author)
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IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes
- 2018
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 2427-
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Journal article (peer-reviewed)abstract
- GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach.
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| 18. |
- Sen, P, et al.
(author)
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Vaccine hesitancy decreases in rheumatic diseases, long-term concerns remain in myositis: a comparative analysis of the COVAD surveys
- 2023
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In: Rheumatology (Oxford, England). - : Oxford University Press (OUP). - 1462-0332 .- 1462-0324. ; 62:10, s. 3291-3301
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Journal article (peer-reviewed)abstract
- ObjectiveCOVID-19 vaccines have a favorable safety profile in patients with autoimmune rheumatic diseases (AIRDs) such as idiopathic inflammatory myopathies (IIMs); however, hesitancy continues to persist among these patients. Therefore, we studied the prevalence, predictors and reasons for hesitancy in patients with IIMs, other AIRDs, non-rheumatic autoimmune diseases (nrAIDs) and healthy controls (HCs), using data from the two international COVID-19 Vaccination in Autoimmune Diseases (COVAD) e-surveys.MethodsThe first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups.ResultsWe analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, P < 0.001). However, concerns/fear over long-term safety had increased (OR: 3.6; 95% CI: 2.9, 4.6, P < 0.01). We noted with concern greater skepticism over vaccine science among patients with IIMs than AIRDs (OR: 1.8; 95% CI: 1.08, 3.2, P = 0.023) and HCs (OR: 4; 95% CI: 1.9, 8.1, P < 0.001), as well as more long-term safety concerns/fear (IIMs vs AIRDs – OR: 1.9; 95% CI: 1.2, 2.9, P = 0.001; IIMs vs HCs – OR: 5.4 95% CI: 3, 9.6, P < 0.001). Caucasians [OR 4.2 (1.7–10.3)] were likely to be more hesitant, while those with better PROMIS physical health score were less hesitant [OR 0.9 (0.8–0.97)].ConclusionVaccine hesitancy has decreased from 2021 to 2022, long-term safety concerns remain among patients with IIMs, particularly in Caucasians and those with poor physical function.
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