The effect of light assisted collisions on matter wave coherence in superradiant Bose-Einstein condensates

We investigate experimentally the effects of light assisted collisions on the coherence between momentum states in Bose-Einstein condensates. The onset of superradiant Rayleigh scattering serves as a sensitive monitor for matter wave coherence. A subtle interplay of binary and collective effects leads to a profound asymmetry between the two sides of the atomic resonance and provides far bigger coherence loss rates for a condensate bathed in blue detuned light than previously estimated. We present a simplified quantitative model containing the essential physics to explain our experimental data and point at a new experimental route to study strongly coupled light matter systems.Comment: 10 pages, 4 figure

The effect of FOXA2 rs1209523 on glucose-related phenotypes and risk of type 2 diabetes in Danish individuals

<p>Abstract</p> <p>Background</p> <p>Variations within the <it>FOXA </it>family have been studied for a putative contribution to the risk of type 2 diabetes (T2D), and recently the minor T-allele of <it>FOXA2 </it>rs1209523 was reported to associate with decreased fasting plasma glucose levels in a study using a weighted false discovery rate control procedure to enhance the statistical power of genome wide association studies in detecting associations between low-frequency variants and a given trait.</p> <p>Thus, the primary aim of this study was to investigate whether the minor T-allele of rs1205923 in <it>FOXA2 </it>associated with 1) decreased fasting plasma glucose and 2) a lower risk of developing T2D. Secondly, we investigated whether rs1205923 in <it>FOXA2 </it>associated with other glucose-related phenotypes.</p> <p>Methods</p> <p>The variant was genotyped in Danish individuals from four different study populations using KASPar^®PCR SNP genotyping system. We examined for associations of the <it>FOXA2 </it>genotype with fasting plasma glucose and estimates of insulin release and insulin sensitivity following an oral glucose tolerance test in 6,162 Danish individuals from the population-based Inter99 study while association with T2D risk was assessed in 10,196 Danish individuals including four different study populations.</p> <p>Results</p> <p>The <it>FOXA2 </it>rs1209523 was not associated with fasting plasma glucose (effect size (β) = -0.03 mmol/l (95%CI: -0.07; 0.01), <it>p </it>= 0.2) in glucose-tolerant individuals from the general Danish population. Furthermore, when employing a case-control setting the variant showed no association with T2D (odds ratio (OR) = 0.82 (95%CI: 0.62-1.07), <it>p </it>= 0.1) among Danish individuals. However, when we performed the analysis in a subset of 6,022 non-obese individuals (BMI < 30 kg/m²) an association with T2D was observed (OR = 0.68 (95%CI: 0.49-0.94), <it>p </it>= 0.02). Also, several indices of insulin release and β-cell function were associated with the minor T-allele of <it>FOXA2 </it>rs1209523 in non-obese individuals.</p> <p>Conclusions</p> <p>We failed to replicate association of the minor T-allele of <it>FOXA2 </it>rs1209523 with fasting plasma glucose in a population based sample of glucose tolerant individuals. More extensive studies are needed in order to fully elucidate the potential role of <it>FOXA2 </it>in glucose homeostasis.</p

Bioinformatics-Driven Identification and Examination of Candidate Genes for Non-Alcoholic Fatty Liver Disease

ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P&lt;0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS

The minor C-allele of rs2014355 in ACADS is associated with reduced insulin release following an oral glucose load

<p>Abstract</p> <p>Background</p> <p>A genome-wide association study (GWAS) using metabolite concentrations as proxies for enzymatic activity, suggested that two variants: rs2014355 in the gene encoding short-chain acyl-coenzyme A dehydrogenase (<it>ACADS</it>) and rs11161510 in the gene encoding medium-chain acyl-coenzyme A dehydrogenase (<it>ACADM</it>) impair fatty acid β-oxidation. Chronic exposure to fatty acids due to an impaired β-oxidation may down-regulate the glucose-stimulated insulin release and result in an increased risk of type 2 diabetes (T2D). We aimed to investigate whether the two variants associate with altered insulin release following an oral glucose load or with T2D.</p> <p>Methods</p> <p>The variants were genotyped using KASPar^®PCR SNP genotyping system and investigated for associations with estimates of insulin release and insulin sensitivity following an oral glucose tolerance test (OGTT) in a random sample of middle-aged Danish individuals (<it>n</it>_{<it>ACADS </it>}= 4,324; <it>n</it>_{<it>ACADM </it>}= 4,337). The T2D-case-control study involved a total of ~8,300 Danish individuals (<it>n</it>_{<it>ACADS </it>}= 8,313; <it>n</it>_{<it>ACADM </it>}= 8,344).</p> <p>Results</p> <p>In glucose-tolerant individuals the minor C-allele of rs2014355 of <it>ACADS </it>associated with reduced measures of serum insulin at 30 min following an oral glucose load (per allele effect (β) = -3.8% (-6.3%;-1.3%), <it>P </it>= 0.003), reduced incremental area under the insulin curve (β = -3.6% (-6.3%;-0.9%), <it>P </it>= 0.009), reduced acute insulin response (β = -2.2% (-4.2%;0.2%), <it>P </it>= 0.03), and with increased insulin sensitivity ISI_Matsuda(β = 2.9% (0.5%;5.2%), <it>P </it>= 0.02). The C-allele did not associate with two other measures of insulin sensitivity or with a derived disposition index. The C-allele was not associated with T2D in the case-control analysis (OR 1.07, 95% CI 0.96-1.18, <it>P </it>= 0.21). rs11161510 of <it>ACADM </it>did not associate with any indices of glucose-stimulated insulin release or with T2D.</p> <p>Conclusions</p> <p>In glucose-tolerant individuals the minor C-allele of rs2014355 of <it>ACADS </it>was associated with reduced measures of glucose-stimulated insulin release during an OGTT, a finding which in part may be mediated through an impaired β-oxidation of fatty acids.</p

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk

Combinatorial, additive and dose-dependent drug–microbiome associations

Data availability: The source data for the figures are provided at Zenodo (https://doi.org/10.5281/zenodo.4728981). Raw shotgun sequencing data that support the findings of this study have been deposited at the ENA under accession codes PRJEB41311, PRJEB38742 and PRJEB37249 with public access. Raw spectra for metabolomics have been deposited in the MassIVE database under the accession codes MSV000088043 (UPLC–MS/MS) and MSV000088042 (GC–MS). The metadata on disease groups and drug intake are provided in Supplementary Tables 1–3. The demographic, clinical and phenotype metadata, and processed microbiome and metabolome data for French, German and Danish participants are available at Zenodo (https://doi.org/10.5281/zenodo.4674360).Code availability: The new drug-aware univariate biomarker testing pipeline is available as an R package (metadeconfoundR; Birkner et al., manuscript in preparation) at Github (https://github.com/TillBirkner/metadeconfoundR) and at Zenodo (https://doi.org/10.5281/zenodo.4721078). The latest version (0.1.8) of this package was used to generate the data shown in this publication. The code used for multivariate analysis based on the VpThemAll package is available at Zenodo (https://doi.org/10.5281/zenodo.4719526). The phenotype and drug intake metadata, processed microbiome, and metabolome data and code resources are available for download at Zenodo (https://doi.org/10.5281/zenodo.4674360). The code for reproducing the figures is provided at Zenodo (https://doi.org/10.5281/zenodo.4728981).During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1,2,3,4,5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease.This work was supported by the European Union’s Seventh Framework Program for research, technological development and demonstration under grant agreement HEALTH-F4-2012-305312 (METACARDIS). Part of this work was also supported by the EMBL, by the Metagenopolis grant ANR-11-DPBS-0001, by the H2020 European Research Council (ERC-AdG-669830) (to P.B.), and by grants from the Deutsche Forschungsgemeinschaft (SFB1365 to S.K.F. and L.M.; and SFB1052/3 A1 MS to M.S. (209933838)). Assistance Publique-Hôpitaux de Paris is the promoter of the clinical investigation (MetaCardis). M.-E.D. is supported by the NIHR Imperial Biomedical Research Centre and by grants from the French National Research Agency (ANR-10-LABX-46 (European Genomics Institute for Diabetes)), from the National Center for Precision Diabetic Medicine – PreciDIAB, which is jointly supported by the French National Agency for Research (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional Council (Agreement 20001891/NP0025517) and by the European Metropolis of Lille (MEL, Agreement 2019_ESR_11) and by Isite ULNE (R-002-20-TALENT-DUMAS), also jointly funded by ANR (ANR-16-IDEX-0004-ULNE), the Hauts-de-France Regional Council (20002845) and by the European Metropolis of Lille (MEL). R.J.A. is a member of the Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Bioscience. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research institution at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation

Combinatorial, additive and dose-dependent drug–microbiome associations

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease