| 1. |
- Momozawa, Y, et al.
(författare)
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IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes
- 2018
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1, s. 2427-
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Falkén, Y., et al.
(författare)
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Actions of prolonged ghrelin infusion on gastrointestinal transit and glucose homeostasis in humans
- 2010
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Ingår i: Neurogastroenterology and Motility. - : Wiley. - 1350-1925 .- 1365-2982. ; 22:6, s. e192-e200
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Tidskriftsartikel (refereegranskat)abstract
- Background Ghrelin is produced by enteroendocrine cells in the gastric mucosa and stimulates gastric emptying in healthy volunteers and patients with gastroparesis in short-term studies. The aim of this study was to evaluate effects of intravenous ghrelin on gastrointestinal motility and glucose homeostasis during a 6-h infusion in humans. Methods Ghrelin (15 pmol kg−1 min−1) or saline was infused intravenously for 360 min after intake of radio-opaque markers, acetaminophen, and lactulose after a standardized breakfast in 12 male volunteers. Gastric emptying, orocecal transit, colonic transit, postprandial plasma concentrations of glucose, insulin, glucagon-like peptide-1 (GLP-1), and peptide YY were assessed. In vitro studies of gastrointestinal muscle contractility were performed. Key Results The gastric emptying rate was faster for ghrelin compared to saline (P = 0.002) with a shorter half-emptying time (50.3 ± 3.9 vs 59.9 ± 4.4 min, P = 0.004). There was no effect of ghrelin on orocecal or colonic transit. Postprandial elevations of plasma glucose, insulin, and GLP-1 occurred 15 min earlier and were higher with ghrelin. The insulinogenic index did not change during ghrelin infusion. Basal in vitro contractility was unaffected by ghrelin. Conclusions & Inferences The effect of a 6-h ghrelin infusion on gastrointestinal motility is limited to the stomach without affecting orocecal or colonic transit. Plasma glucose, insulin, and GLP-1 are elevated postprandially, probably as a result of the hastened gastric emptying. Changes in glucose homeostasis as a consequence of stimulated gastric emptying and hormone release, need to be taken into account in the use of pharmacological stimulants for the treatment of motility disorders.
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| 3. |
- Romagnoni, A, et al.
(författare)
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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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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)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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