| 1. |
- Gehlen, J., et al.
(författare)
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First genome-wide association study of esophageal atresia identifies three genetic risk loci at CTNNA3, FOXF1/FOXC2/FOXL1, and HNF1B
- 2022
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Ingår i: Human Genetics and Genomics Advances. - : Elsevier BV. - 2666-2477. ; 3:2
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Tidskriftsartikel (refereegranskat)abstract
- Esophageal atresia with or without tracheoesophageal fistula (EA/TEF) is the most common congenital malformation of the upper digestive tract. This study represents the first genome-wide association study (GWAS) to identify risk loci for EA/TEF. We used a European case-control sample comprising 764 EA/TEF patients and 5,778 controls and observed genome-wide significant associations at three loci. On chromosome 10q21 within the gene CTNNA3 (p = 2.11 × 10−8; odds ratio [OR] = 3.94; 95% confidence interval [CI], 3.10–5.00), on chromosome 16q24 next to the FOX gene cluster (p = 2.25 × 10−10; OR = 1.47; 95% CI, 1.38–1.55) and on chromosome 17q12 next to the gene HNF1B (p = 3.35 × 10−16; OR = 1.75; 95% CI, 1.64–1.87). We next carried out an esophageal/tracheal transcriptome profiling in rat embryos at four selected embryonic time points. Based on these data and on already published data, the implicated genes at all three GWAS loci are promising candidates for EA/TEF development. We also analyzed the genetic EA/TEF architecture beyond the single marker level, which revealed an estimated single-nucleotide polymorphism (SNP)-based heritability of around 37% ± 14% standard deviation. In addition, we examined the polygenicity of EA/TEF and found that EA/TEF is less polygenic than other complex genetic diseases. In conclusion, the results of our study contribute to a better understanding on the underlying genetic architecture of ET/TEF with the identification of three risk loci and candidate genes. © 2022 The Authors
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| 2. |
- Pennells, Lisa, et al.
(författare)
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Equalization of four cardiovascular risk algorithms after systematic recalibration : individual-participant meta-analysis of 86 prospective studies
- 2019
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 40:7, s. 621-
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Tidskriftsartikel (refereegranskat)abstract
- Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
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| 3. |
- Mingardo, E, et al.
(författare)
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A genome-wide association study with tissue transcriptomics identifies genetic drivers for classic bladder exstrophy
- 2022
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Ingår i: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 5:1, s. 1203-
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Tidskriftsartikel (refereegranskat)abstract
- Classic bladder exstrophy represents the most severe end of all human congenital anomalies of the kidney and urinary tract and is associated with bladder cancer susceptibility. Previous genetic studies identified one locus to be involved in classic bladder exstrophy, but were limited to a restrict number of cohort. Here we show the largest classic bladder exstrophy genome-wide association analysis to date where we identify eight genome-wide significant loci, seven of which are novel. In these regions reside ten coding and four non-coding genes. Among the coding genes is EFNA1, strongly expressed in mouse embryonic genital tubercle, urethra, and primitive bladder. Re-sequence of EFNA1 in the investigated classic bladder exstrophy cohort of our study displays an enrichment of rare protein altering variants. We show that all coding genes are expressed and/or significantly regulated in both mouse and human embryonic developmental bladder stages. Furthermore, nine of the coding genes residing in the regions of genome-wide significance are differentially expressed in bladder cancers. Our data suggest genetic drivers for classic bladder exstrophy, as well as a possible role for these drivers to relevant bladder cancer susceptibility.
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| 4. |
- Allesøe, Rosa Lundbye, et al.
(författare)
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Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models
- 2023
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Ingår i: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 41:3, s. 399-408
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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.
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| 5. |
- Giel, KE, et al.
(författare)
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Binge eating disorder
- 2022
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Ingår i: Nature reviews. Disease primers. - : Springer Science and Business Media LLC. - 2056-676X. ; 8:1, s. 16-
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Tidskriftsartikel (refereegranskat)
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| 6. |
- Karlsson, Hanna L., et al.
(författare)
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Mechanism-based genotoxicity screening of metal oxide nanoparticles using the ToxTracker panel of reporter cell lines
- 2014
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Ingår i: Particle and Fibre Toxicology. - : Springer Science and Business Media LLC. - 1743-8977. ; 11, s. 41-
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Tidskriftsartikel (refereegranskat)abstract
- Background: The rapid expansion of manufacturing and use of nano-sized materials fuels the demand for fast and reliable assays to identify their potential hazardous properties and underlying mechanisms. The ToxTracker assay is a recently developed mechanism-based reporter assay based on mouse embryonic stem (mES) cells that uses GFP-tagged biomarkers for detection of DNA damage, oxidative stress and general cellular stress upon exposure. Here, we evaluated the ability of the ToxTracker assay to identify the hazardous properties and underlying mechanisms of a panel of metal oxide-and silver nanoparticles (NPs) as well as additional non-metallic materials (diesel, carbon nanotubes and quartz). Methods: The metal oxide-and silver nanoparticles were characterized in terms of agglomeration and ion release in cell medium (using photon cross correlation spectroscopy and inductively coupled plasma with optical emission spectroscopy, respectively) as well as acellular ROS production (DCFH-DA assay). Cellular uptake was investigated by means of transmission electron microscopy. GFP reporter induction and cytotoxicity of the NPs was simultaneously determined using flow cytometry, and genotoxicity was further tested using conventional assays (comet assay, gamma-H(2)AX and RAD51 foci formation). Results: We show that the reporter cells were able to take up nanoparticles and, furthermore, that exposure to CuO, NiO and ZnO nanoparticles as well as to quartz resulted in activation of the oxidative stress reporter, although only at high cytotoxicity for ZnO. NiO NPs activated additionally a p53-associated cellular stress response, indicating additional reactive properties. Conventional assays for genotoxicity assessment confirmed the response observed in the ToxTracker assay. We show for CuO NPs that the induction of oxidative stress is likely the consequence of released Cu ions whereas the effect by NiO was related to the particles per se. The DNA replication stress-induced reporter, which is most strongly associated with carcinogenicity, was not activated by any of the tested nanoparticles. Conclusions: We conclude that the ToxTracker reporter system can be used as a rapid mechanism-based tool for the identification of hazardous properties of metal oxide NPs. Furthermore, genotoxicity of metal oxide NPs seems to occur mainly via oxidative stress rather than direct DNA binding with subsequent replication stress.
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