1. |
- Allesøe, Rosa Lundbye, et al.
(författare)
-
Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
- 2023
-
Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 41:3, s. 399-408
-
Tidskriftsartikel (refereegranskat)abstract
- The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.
|
|
2. |
|
|
3. |
|
|
4. |
|
|
5. |
|
|
6. |
|
|
7. |
|
|
8. |
|
|
9. |
|
|
10. |
|
|
11. |
- Gudmundsdottir, Valborg, et al.
(författare)
-
Whole blood co-expression modules associate with metabolic traits and type 2 diabetes : an IMI-DIRECT study
- 2020
-
Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 12:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.Conclusions: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.
|
|
12. |
- Munch Roager, Henrik, et al.
(författare)
-
Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: A randomised cross-over trial
- 2019
-
Ingår i: Gut. - : BMJ. - 1468-3288 .- 0017-5749. ; 68:1, s. 83-93
-
Tidskriftsartikel (refereegranskat)abstract
- Objective T o investigate whether a whole grain diet alters the gut microbiome and insulin sensitivity, as well as biomarkers of metabolic health and gut functionality. Design 60 Danish adults at risk of developing metabolic syndrome were included in a randomised cross-over trial with two 8-week dietary intervention periods comprising whole grain diet and refined grain diet, separated by a washout period of =6 weeks. The response to the interventions on the gut microbiome composition and insulin sensitivity as well on measures of glucose and lipid metabolism, gut functionality, inflammatory markers, anthropometry and urine metabolomics were assessed. Results 50 participants completed both periods with a whole grain intake of 179±50 g/day and 13±10 g/day in the whole grain and refined grain period, respectively. Compliance was confirmed by a difference in plasma alkylresorcinols (p<0.0001). Compared with refined grain, whole grain did not significantly alter glucose homeostasis and did not induce major changes in the faecal microbiome. Also, breath hydrogen levels, plasma short-chain fatty acids, intestinal integrity and intestinal transit time were not affected. The whole grain diet did, however, compared with the refined grain diet, decrease body weight (p<0.0001), serum inflammatory markers, interleukin (IL)-6 (p=0.009) and C-reactive protein (p=0.003). The reduction in body weight was consistent with a reduction in energy intake, and IL-6 reduction was associated with the amount of whole grain consumed, in particular with intake of rye. Conclusion C ompared with refined grain diet, whole grain diet did not alter insulin sensitivity and gut microbiome but reduced body weight and systemic lowgrade inflammation.
|
|
13. |
- Pedersen, Henrik AE., et al.
(författare)
-
Phylogenetics of Dendrochilum (Orchidaceae) : Evidence of pronounced morphological homoplasy and predominantly centric endemism
- 2019
-
Ingår i: Taxon. - : John Wiley & Sons. - 0040-0262 .- 1996-8175. ; 68:6, s. 1173-1188
-
Tidskriftsartikel (refereegranskat)abstract
- A phylogenetic hypothesis for the genus Dendrochilum s.l. (including Bracisepalum) is based on nucleotide sequences of the nuclear ribosomal ITS and two plastid regions (matK, ycf1). The trees based on parsimony analysis of the nrITS and plastid partitions, respectively, are largely congruent, the only strongly supported conflict being the exact position of D. arachnites. Maximum likelihood analysis of the combined molecular matrix resulted in a tree with very high topological congruence to the parsimony consensus tree and to a fossil-calibrated Bayesian inference tree that was used for dating. Our results confirm that monophyly of Dendrochilum is only supported if Bracisepalum is included in the former. They also suggest that only two subgenera (Dendrochilum, Platyclinis) should be recognized, whereas all other subgenera and sections previously proposed on a morphological basis should be treated as synonyms of subg. Platyclinis. Indeed, mapping of five vegetative and nine floral characters of alleged systematic value, using DELTRAN and ACCTRAN optimization, demonstrates pronounced morphological homoplasy. Molecular time calibration dates the origin of the genus to the Miocene and contradicts the hypothesis that most extant Dendrochilum species did not evolve until the Holocene. Inferred phylogenetic relationships between extant species, in combination with previously identified hotspots of narrow endemism, suggest that species endemism in Dendrochilum is predominantly centric.
|
|
14. |
- Aad, G., et al.
(författare)
-
- 2015
-
Ingår i: Journal of High Energy Physics. - 1029-8479 .- 1126-6708. ; :8
-
Tidskriftsartikel (refereegranskat)
|
|
15. |
|
|
16. |
|
|
17. |
|
|
18. |
|
|
19. |
|
|
20. |
|
|
21. |
|
|
22. |
|
|
23. |
|
|
24. |
|
|
25. |
|
|