Placenta accreta:adherent placenta due to Asherman syndrome

It is important to be aware of the risk of abnormally invasive placenta in patients with a history of Asherman syndrome and uterine scarring. A prenatal diagnosis by ultrasonography is useful when planning of mode of delivery

Homozygous carriers of the TCF7L2 rs7903146 T-allele show altered postprandial response in triglycerides and triglyceride-rich lipoproteins

The TCF7L2 rs7903146 T-allele shows the strongest association with type 2 diabetes (T2D) among common gene variants. The aim of this study was to assess circulating levels of metabolites following a meal test in individuals carrying the high risk rs790346 TT genotype (cases) and low-risk CC genotype (controls). Sixty-two men were recruited based on TCF7L2 genotype, 31 were TT carriers and 31 were age- and BMI-matched CC carriers. All participants consumed a test meal after 12 hours of fasting. Metabolites were measured using proton nuclear magnetic resonance (NMR) spectroscopy. Metabolomic profiling of TCF7L2 carriers were performed for 141 lipid estimates. TT carriers had lower fasting levels of L-VLDL-L (total lipids in large very low density lipoproteins, p = 0.045), L-VLDL-CE (cholesterol esters in large VLDL, p = 0.03), and L-VLDL-C (total cholesterol in large VLDL, p = 0.045) compared to CC carriers. Additionally, TT carriers had lower postprandial levels of total triglycerides (TG) (q = 0.03), VLDL-TG (q = 0.05, including medium, small and extra small, q = 0.048, q = 0.0009, q = 0.04, respectively), HDL-TG (triglycerides in high density lipoproteins q = 0.037) and S-HDL-TG (q = 0.00003). In conclusion, TT carriers show altered postprandial triglyceride response, mainly influencing VLDL and HDL subclasses suggesting a genotype-mediated effect on hepatic lipid regulation

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

Background: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. Methods: In this genome-wide analysis we included adults (aged ≥18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. Findings: 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G→A (Gly168Ser) in the GLP1R (0·08% [95% CI 0·04–0·12] or 0·9 mmol/mol lower reduction in HbA1c per serine, p=6·0 × 10−5) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6·7 × 10−8), largely driven by rs140226575G→A (Thr370Met; 0·25% [SE 0·06] or 2·7 mmol/mol [SE 0·7] greater HbA1c reduction per methionine, p=5·2 × 10−6). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6–11%) than in White European populations. Combining these two genes identified 4% of the population who had a 30% greater reduction in HbA1c than the 9% of the population with the worse response. Interpretation: This genome-wide pharmacogenomic study of GLP-1 receptor agonists provides novel biological and clinical insights. Clinically, when genotype is routinely available at the point of prescribing, individuals with ARRB1 variants might benefit from earlier initiation of GLP-1 receptor agonists. Funding: Innovative Medicines Initiative and the Wellcome Trus

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

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth

This is the final version. Available on open access from Nature Research via the DOI in this record. Data availability: Individual cohorts contributing to the meta-analysis should be contacted directly as each cohort has different data access policies. GWAS summary statistics from this study are available via the EGG website (https://egg-consortium.org/placental-weight-2023.html, https://www.ebi.ac.uk/gwas/), as well as the GWAS catalog (https://www.ebi.ac.uk/gwas/, accession numbers GCST90275189, GCST90275190, GCST90275191, GCST90275192, GCST90275193, GCST90275194, GCST90275195, GCST90275196, GCST90275197, GCST90275198, GCST90275199). Access to personal-level information from Gen3G (including methylation array data) is subject to controlled access according to participants’ consent concerning sharing of personal data. Request for conditions of access and for data access should be addressed to Center Hospitalier Universitaire de Sherbrooke institutional ethics committee: [email protected] availability: Analysis code is available from https://github.com/EarlyGrowthGenetics/placental_weight_codeA well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.Wellcome Trus

Metabolites related to purine catabolism and risk of type 2 diabetes incidence; modifying effects of the TCF7L2-rs7903146 polymorphism

Studies examining associations between purine metabolites and type 2 diabetes (T2D) are limited. We prospectively examined associations between plasma levels of purine metabolites with T2D risk and the modifying effects of transcription factor-7-like-2 (TCF7L2) rs7903146 polymorphism on these associations. This is a case-cohort design study within the PREDIMED study, with 251 incident T2D cases and a random sample of 694 participants (641 non-cases and 53 overlapping cases) without T2D at baseline (median follow-up: 3.8 years). Metabolites were semi-quantitatively profiled with LC-MS/MS. Cox regression analysis revealed that high plasma allantoin levels, including allantoin-to-uric acid ratio and high xanthine-to-hypoxanthine ratio were inversely and positively associated with T2D risk, respectively, independently of classical risk factors. Elevated plasma xanthine and inosine levels were associated with a higher T2D risk in homozygous carriers of the TCF7L2-rs7903146 T-allele. The potential mechanisms linking the aforementioned purine metabolites and T2D risk must be also further investigated.This study was supported by research grant R01-DK-102896 from the National Institutes of Health. The Prevención con DietaMediterránea (PREDIMED) trial was supported by the official funding agency for biomedical research of the Spanish government, the Instituto de Salud Carlos III, through grants provided to research networks specifically developed for the trial [grant RTIC G03/140 (to Ramón Estruch); grant RTIC RD 06/0045 (to Miguel A. Martínez-González)] and through the Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición and by grants from Centro Nacional de Investigaciones Cardiovasculares (grant CNIC 06/2007), the Fondo de Investigación Sanitaria Fondo Europeo de Desarrollo Regional (grants PI04–2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, and PI13/00462), the Ministerio de Ciencia e Innovación (grants AGL-2009–13906-C02 and AGL2010–22319-C03), the Fundación Mapfre 2010, Consejería de Salud de la Junta de Andalucía (grant PI0105/2007), the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (grants ACOMP06109, GVA-COMP2010–181, GVACOMP2011–151, CS2010-AP-111, and CS2011-AP-042), and the Regional Government of Navarra (grant P27/2011). Genotyping of the TCF7L2-rs7903146 polymorphism was supported by PROMETEO17/2017 from the Generalitat Valenciana, and 538/U/2016 from Fundacio la Marato-TV3. Dr. Christopher Papandreou was supported by a postdoctoral fellowship granted by the Autonomous Government of Catalonia (PERIS 2016-2020 INCORPORACIÓ DE CIENTÍFICAS I TECNÒLEGS, SLT002/0016/00428). Dr Marta Guasch-Ferré was supported by a postdoctoral fellowship granted by the Lilly Foundation European Association of Diabetes (EASD) through the Institut d’Investigacions Sanitàries Pere i Virgili (IISPV), Tarragona, Spain. The authors are indebted to George A. Fragkiadakis (Department of Nutrition & Dietetics, Technological Education Institute of Crete, Greece) for his intellectual contributions to this manuscript