97 research outputs found
Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.
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. [Abstract copyright: © 2023. The Author(s).
Author Correction:Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models
In the version of this article initially published, Cristina Leal Rodríguez (Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark) was omitted from the author list. The error has been corrected in the HTML and PDF versions of the article</p
Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study
Introduction: The use of anti-retroviral therapy (ART) has dramatically reduced HIV-1 associated morbidity and mortality. However, HIV-1 infected individuals have increased rates of morbidity and mortality compared to the non-HIV-1 infected population and this appears to be related to end-organ diseases collectively referred to as Serious Non-AIDS Events (SNAEs). Circulating miRNAs are reported as promising biomarkers for a number of human disease conditions including those that constitute SNAEs. Our study sought to investigate the potential of selected miRNAs in predicting mortality in HIV-1 infected ART treated individuals. Materials and Methods: A set of miRNAs was chosen based on published associations with human disease conditions that constitute SNAEs. This case: control study compared 126 cases (individuals who died whilst on therapy), and 247 matched controls (individuals who remained alive). Cases and controls were ART treated participants of two pivotal HIV-1 trials. The relative abundance of each miRNA in serum was measured, by RTqPCR. Associations with mortality (all-cause, cardiovascular and malignancy) were assessed by logistic regression analysis. Correlations between miRNAs and CD4+ T cell count, hs-CRP, IL-6 and D-dimer were also assessed. Results: None of the selected miRNAs was associated with all-cause, cardiovascular or malignancy mortality. The levels of three miRNAs (miRs -21, -122 and -200a) correlated with IL-6 while miR-21 also correlated with D-dimer. Additionally, the abundance of miRs -31, -150 and -223, correlated with baseline CD4+ T cell count while the same three miRNAs plus miR- 145 correlated with nadir CD4+ T cell count. Discussion: No associations with mortality were found with any circulating miRNA studied. These results cast doubt onto the effectiveness of circulating miRNA as early predictors of mortality or the major underlying diseases that contribute to mortality in participants treated for HIV-1 infection
A Field Guide to Pandemic, Epidemic and Sporadic Clones of Methicillin-Resistant Staphylococcus aureus
In recent years, methicillin-resistant Staphylococcus aureus
(MRSA) have become a truly global challenge. In addition to the long-known
healthcare-associated clones, novel strains have also emerged outside of the
hospital settings, in the community as well as in livestock. The emergence and
spread of virulent clones expressing Panton-Valentine leukocidin (PVL) is an
additional cause for concern. In order to provide an overview of pandemic,
epidemic and sporadic strains, more than 3,000 clinical and veterinary isolates
of MRSA mainly from Germany, the United Kingdom, Ireland, France, Malta, Abu
Dhabi, Hong Kong, Australia, Trinidad & Tobago as well as some reference
strains from the United States have been genotyped by DNA microarray analysis.
This technique allowed the assignment of the MRSA isolates to 34 distinct
lineages which can be clearly defined based on non-mobile genes. The results
were in accordance with data from multilocus sequence typing. More than 100
different strains were distinguished based on affiliation to these lineages,
SCCmec type and the presence or absence of PVL. These
strains are described here mainly with regard to clinically relevant
antimicrobial resistance- and virulence-associated markers, but also in relation
to epidemiology and geographic distribution. The findings of the study show a
high level of biodiversity among MRSA, especially among strains harbouring
SCCmec IV and V elements. The data also indicate a high
rate of genetic recombination in MRSA involving SCC elements, bacteriophages or
other mobile genetic elements and large-scale chromosomal replacements
A Field Guide to Pandemic, Epidemic and Sporadic Clones of Methicillin-Resistant Staphylococcus aureus
In recent years, methicillin-resistant Staphylococcus aureus
(MRSA) have become a truly global challenge. In addition to the long-known
healthcare-associated clones, novel strains have also emerged outside of the
hospital settings, in the community as well as in livestock. The emergence and
spread of virulent clones expressing Panton-Valentine leukocidin (PVL) is an
additional cause for concern. In order to provide an overview of pandemic,
epidemic and sporadic strains, more than 3,000 clinical and veterinary isolates
of MRSA mainly from Germany, the United Kingdom, Ireland, France, Malta, Abu
Dhabi, Hong Kong, Australia, Trinidad & Tobago as well as some reference
strains from the United States have been genotyped by DNA microarray analysis.
This technique allowed the assignment of the MRSA isolates to 34 distinct
lineages which can be clearly defined based on non-mobile genes. The results
were in accordance with data from multilocus sequence typing. More than 100
different strains were distinguished based on affiliation to these lineages,
SCCmec type and the presence or absence of PVL. These
strains are described here mainly with regard to clinically relevant
antimicrobial resistance- and virulence-associated markers, but also in relation
to epidemiology and geographic distribution. The findings of the study show a
high level of biodiversity among MRSA, especially among strains harbouring
SCCmec IV and V elements. The data also indicate a high
rate of genetic recombination in MRSA involving SCC elements, bacteriophages or
other mobile genetic elements and large-scale chromosomal replacements
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk
Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis
Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe
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