STUDY QUESTION:Do polycystic ovary syndrome (PCOS), menstrual cycle phases, and ovulatory status affect reproductive tract (RT) microbiome profiles? SUMMARY ANSWER:We identified microbial features associated with menstrual cycle phases in the upper and lower RT microbiome, but only two specific differences in the upper RT according to PCOS status. WHAT IS KNOWN ALREADY:The vaginal and uterine microbiome profiles vary throughout the menstrual cycle. Studies have reported alterations in the vaginal microbiome among women diagnosed with PCOS. STUDY DESIGN, SIZE, DURATION:This prospective case-control study included a cohort of 37 healthy control women and 52 women diagnosed with PCOS. Microbiome samples were collected from the vagina as vaginal swabs (VS) and from the uterus as endometrial flushing (EF) aspirate samples, and compared according to PCOS diagnosis, the menstrual cycle phases, and ovulatory status, at Oulu University Hospital (Oulu, Finland) from January 2017 to March 2020. PARTICIPANTS/MATERIALS, SETTING, METHODS:A total of 83 VS samples and 80 EF samples were collected. Age and body mass index (BMI) were matched between women with and without PCOS. Clinical characteristics were assessed using blood samples collected between cycle days 2 and 8, and microbial DNA was sequenced on the Ion Torrent platform. Microbial alpha diversity (i.e. the observed number of unique genera and Shannon diversity index) was analysed across sample types, PCOS diagnosis and menstrual cycle phases. Linear mixed-effects models were utilised to identify microbial features in relation to PCOS and the menstrual cycle phases. Associations between the beta diversity of the RT microbiome and PCOS- and cycle-related clinical features were calculated using PERMANOVA. MAIN RESULTS AND THE ROLE OF CHANCE:Microbial alpha diversity showed no difference with PCOS (VS: Pobserved feature = 0.836, Pshannon = 0.998; EF: Pobserved feature = 0.366, Pshannon = 0.185), but varied with menstrual cycle phases (VS: Pobserved feature = 0.001, Pshannon = 0.882; EF: Pobserved feature = 0.026, Pshannon = 0.048). No difference was observed in beta diversity based on either PCOS or the menstrual cycle phases (VS: PPCOS = 0.280, Pcycle = 0.115; EF: PPCOS = 0.234, Pcycle = 0.088). In the endometrial flushing samples, we identified two novel microbial features, characterised by the ratio of differential abundance of two genera, associated with PCOS (FDR ≤ 0.1) and 13 novel features associated with the menstrual cycle phases (FDR ≤ 0.1). LIMITATIONS, REASONS FOR CAUTION:Although this was the first study to simultaneously analyse, the lower and upper RT microbiome in women with and without PCOS, the limited sample size of anovulatory cases may hinder the detection of differences related to PCOS and ovulatory status. WIDER IMPLICATIONS OF THE FINDINGS:The main finding suggests that PCOS and the menstrual cycle phases are associated with specific microbial features in the upper RT, indicating that the analysis of the upper RT microbiome can potentially identify biomarkers for both PCOS and menstrual cycle phases. STUDY FUNDING/COMPETING INTEREST(S):This research was funded by the Research Council of Finland (grants no. 315921, 321763, 336449), the Sigrid Jusélius Foundation, Novo Nordisk Foundation (grant no. NNF21OC0070372), and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant (MATER, grant no. 813707). This research was also funded by the Estonian Research Council (grants no. PRG1076, PRG1414), the Horizon Europe grant (NESTOR, grant no. 101120075) of the European Commission, and EMBO Installation Grant (grant no. 3573). The funders did not participate in any processes of the study. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. TRIAL REGISTRATION NUMBER:N/A.

STUDY QUESTION How does the gut bacteriome differ based on mood disorders (MDs) in women with polycystic ovary syndrome (PCOS), and how can the gut bacteriome contribute to the associations between these two conditions? SUMMARY ANSWER Women with PCOS who also have MDs exhibited a distinct gut bacteriome with reduced alpha diversity and a significantly lower abundance of Butyricicoccus compared to women with PCOS but without MDs. WHAT IS KNOWN ALREADY Women with PCOS have a 4- to 5-fold higher risk of having MDs compared to women without PCOS. The gut bacteriome has been suggested to influence the pathophysiology of both PCOS and MDs. STUDY DESIGN, SIZE, DURATION This population-based cohort study was derived from the Northern Finland Birth Cohort 1966 (NFBC1966), which includes all women born in Northern Finland in 1966. Women with PCOS who donated a stool sample at age 46 years (n = 102) and two BMI-matched controls for each case (n = 205), who also responded properly to the MD criteria scales, were included. PARTICIPANTS/MATERIALS, SETTING, METHODS A total of 102 women with PCOS and 205 age- and BMI-matched women without PCOS were included. Based on the validated MD criteria, the subjects were categorized into MD or no-MD groups, resulting in the following subgroups: PCOS no-MD (n = 84), PCOS MD (n = 18), control no-MD (n = 180), and control MD (n = 25). Clinical characteristics were assessed at age 31 years and age 46 years, and stool samples were collected from the women at age 46 years, followed by the gut bacteriome analysis using 16 s rRNA sequencing. Alpha diversity was assessed using observed features and Shannon's index, with a focus on genera, and beta diversity was characterized using principal components analysis (PCA) with Bray-Curtis Dissimilarity at the genus level. Associations between the gut bacteriome and PCOS-related clinical features were explored by Spearman's correlation coefficient. A P-value for multiple testing was adjusted with the Benjamini-Hochberg false discovery rate (FDR) method. MAIN RESULTS AND THE ROLE OF CHANCE We observed changes in the gut bacteriome associated with MDs, irrespective of whether the women also had PCOS. Similarly, PCOS MD cases showed a lower alpha diversity (Observed feature, PCOS no-MD, median 272; PCOS MD, median 208, FDR = 0.01; Shannon, PCOS no-MD, median 5.95; PCOS MD, median 5.57, FDR = 0.01) but also a lower abundance of Butyricicoccus (log-fold changeAnalysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC)=-0.90, FDRANCOM-BC=0.04) compared to PCOS no-MD cases. In contrast, in the controls, the gut bacteriome did not differ based on MDs. Furthermore, in the PCOS group, Sutterella showed positive correlations with PCOS-related clinical parameters linked to obesity (BMI, r(2)=0.31, FDR = 0.01; waist circumference, r(2)=0.29, FDR = 0.02), glucose metabolism (fasting glucose, r(2)=0.46, FDR < 0.001; fasting insulin, r(2)=0.24, FDR = 0.05), and gut barrier integrity (zonulin, r(2)=0.25, FDR = 0.03). LIMITATIONS, REASONS FOR CAUTION Although this was the first study to assess the link between the gut bacteriome and MDs in PCOS and included the largest PCOS dataset for the gut microbiome analysis, the number of subjects stratified by the presence of MDs was limited when contrasted with previous studies that focused on MDs in a non-selected population. WIDER IMPLICATIONS OF THE FINDINGS The main finding is that gut bacteriome is associated with MDs irrespective of the PCOS status, but PCOS may also modulate further the connection between the gut bacteriome and MDs. STUDY FUNDING/COMPETING INTEREST(S) This research was funded by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement (MATER, No. 813707), the Academy of Finland (project grants 315921, 321763, 336449), the Sigrid Juselius Foundation, Novo Nordisk Foundation (NNF21OC0070372), grant numbers PID2021-12728OB-100 (Endo-Map) and CNS2022-135999 (ROSY) funded by MCIN/AEI/10.13039/501100011033 and ERFD A Way of Making Europe. The study was also supported by EU QLG1-CT-2000-01643 (EUROBLCS) (E51560), NorFA (731, 20056, 30167), USA/NIH 2000 G DF682 (50945), the Estonian Research Council (PRG1076, PRG1414), EMBO Installation (3573), and Horizon 2020 Innovation Grant (ERIN, No. EU952516). The funders did not participate in any process of the study. We have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER N/A.

Abstract Study question Do gut microbial composition and functionality differ between women with and without endometriosis? Summary answer Gut microbiome diversity and composition (species and microbial pathways) were not significantly different between women with and without endometriosis. What is known already Endometriosis, defined as the presence of endometrial-like tissue outside of the uterus, is one of the most common female reproductive disorders. Although different theories of the possible causes of endometriosis have been proposed, its pathogenesis is not clear. Novel studies indicate that the gut microbiome may be involved in the etiology of endometriosis, nevertheless, the connection between microbes, its dysbiosis and the development of endometriosis remains unexplored. This study aims to analyze and compare the gut microbiome profile in women with and without endometriosis in a large cohort to identify microbial targets potentially involved in the development of the disease. Study design, size, duration This case-control study included a subsample of 1000 women (age = 45.61±10.36 years; BMI = 25.67±5.59) of the Estonian Microbiome (EstMB) cohort, a volunteer-based sub-cohort of the Estonian Biobank created in 2017. 136 women with endometriosis and 864 control women who have not been diagnosed with endometriosis or any of its most prevalent comorbidities (systemic lupus erythematosus, rheumatoid arthritis, autoimmune thyroiditis, celiac disease, multiple sclerosis and irritable bowel syndrome) were included in this study. Participants/materials, setting, methods Microbial DNA from fecal samples was extracted and sequenced by paired-end metagenomic shotgun sequencing (Illumina Novaseq 6000 platform). Microbial functional pathways were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.genome.jp/kegg/). Partitioning around medoids (PAM) algorithm was performed to cluster the microbial profile of the Estonian population. The alpha- and beta-diversity and differential abundance analyses were performed to assess the gut microbiome (species and KEGG orthologies [KO]) in both groups. Main results and the role of chance After metagenomics analysis, 17180 microbes and 7869 KO were detected. Those bacteria and KO with a relative abundance > 1 % were used for the diversity and differential abundance analyses, resulting in 2442 species and 1974 KO. PAM clustering analysis stratified the study population into two enterotypes: one characterized by a high abundance of Prevotella copri and the second presented a high abundance of Bacteroides genus (PERMANOVA, p = 0.001). However, the enterotypes were not associated with the presence/absence of endometriosis. Microbial alpha-diversity (observed richness and Shannon’s index) was not significantly different between women with and without endometriosis (all p-value > 0.05). Beta-diversity analyses on the microbial and functional profile (species and KO profile) indicated no significant dissimilarity between groups (PERMANOVA, all p > 0.05). No differential species nor KO were detected after multiple testing adjustment (all FDR p > 0.05). Limitations, reasons for caution This case-control study did not identify a distinct gut microbial profile in women with endometriosis. A deeper analysis considering potential confounders (specifically hormonal treatment in patients) is needed to further confirm our results. Wider implications of the findings Endometriosis is a widespread disorder affecting ∼10% of reproductive-age women. To the best of our knowledge, this is the biggest metagenome study performed in women with endometriosis. Our findings do not find enough evidence to support the existence of a gut microbiome-dependent mechanism implicated in the pathogenesis of endometriosis. Trial registration number Not applicable

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed whole-genome genotypes and 16S fecal microbiome data from 18,473 individuals (25 cohorts). Microbial composition showed high variability across cohorts: we detected only 9 out of 410 genera in more than 95% of the samples. A genome-wide association study (GWAS) of host genetic variation in relation to microbial taxa identified 30 loci affecting microbome taxa at a genome-wide significant (P<5×10-8) threshold. Just one locus, the lactase (LCT) gene region, reached study-wide significance (GWAS signal P=8.6×10−21); it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.94×10−10<P<5×10−8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization analyses identified enrichment of microbiome trait loci SNPs in the metabolic, nutrition and environment domains and indicated food preferences and diseases as mediators of genetic effects.

Background Gut microbes play a critical role in the production of trimethylamine N-oxide (TMAO), an atherogenic metabolite that impacts platelet responsiveness and thrombosis potential. Involving both microbe and host enzymatic machinery, TMAO generation utilizes a metaorganismal pathway, beginning with ingestion of trimethylamine (TMA)-containing dietary nutrients such as choline, phosphatidylcholine and carnitine, which are abundant in a Western diet. Gut microbial TMA lyases use these nutrients as substrates to produce TMA, which upon delivery to the liver via the portal circulation, is converted into TMAO by host hepatic flavin monooxygenases (FMOs). Gut microbial production of TMA is rate limiting in the metaorganismal TMAO pathway because hepatic FMO activity is typically in excess. Objectives FMO3 is the major FMO responsible for host generation of TMAO; however, a role for FMO3 in altering platelet responsiveness and thrombosis potential invivo has not yet been explored. Methods The impact of FMO3 suppression (antisense oligonucleotide-targeting) and overexpression (as transgene) on plasma TMAO levels, platelet responsiveness and thrombosis potential was examined using a murine FeCl3-induced carotid artery injury model. Cecal microbial composition was examined using 16S analyses. Results Modulation of FMO3 directly impacts systemic TMAO levels, platelet responsiveness and rate of thrombus formation invivo. Microbial composition analyses reveal taxa whose proportions are associated with both plasma TMAO levels and invivo thrombosis potential. Conclusions The present studies demonstrate that host hepatic FMO3, the terminal step in the metaorganismal TMAO pathway, participates in diet-dependent and gut microbiota-dependent changes in both platelet responsiveness and thrombosis potential invivo.

We have carried out taxonomic profiling of gut microbiota in a population of about 100 commercially available inbred strains of mice termed the Hybrid Mouse Diversity Panel (HMDP). This panel has been developed as a systems genetics resource and can be used for high resolution association mapping of complex traits. When maintained under controlled environmental conditions, the gut microbiota composition exhibits high heritability in the HMDP as calculated using a linear mixed model assuming additive genetic effects. Genome‐wide association analysis with informative SNPs identified significant loci in the mouse genome associated with relative abundances of specific taxa. The HMDP mice have been typed for a number of cardiovascular, metabolic, and other clinical traits, allowing correlation analysis of gut microbiota composition with clinical traits. Some of these associations, such as the association between Akkermansia muciniphila levels and high fat diet response, have subsequently been confirmed in published experimental studies. A number of novel associations are presently being tested using co‐fostering of different inbred strains or experimental introduction of cultured bacterial species. A variety of diets have been studied across the HMDP. In conclusion, studies of natural variations in gut microbiota composition in mice may help identify regulatory host factors as well as providing a global view of the relationships between microbiota and clinically relevant traits.

A typical GWAS tests correlation between a single phenotype and each genotype one at a time. However, it is often very useful to analyze many phenotypes simultaneously. For example, this may increase the power to detect variants by capturing unmeasured aspects of complex biological networks that a single phenotype might miss. There are several multivariate approaches that try to detect variants related to many phenotypes, but none of them consider population structure and each may result in a significant number of false positive identifications. Here, we introduce a new methodology, referred to as GAMMA, that could both simultaneously analyze many phenotypes as well as correct for population structure. In a simulated study, GAMMA accurately identifies true genetic effects without false positive identifications, while other methods either fail to detect true effects or result in many false positive identifications. We further apply our method to genetic studies of yeast and gut microbiome from mouse and show that GAMMA identifies several variants that are likely to have a true biological mechanism.

Chronic respiratory diseases are the 3rd leading cause of death, and individuals suffering from respiratory distress are at risk for cardiovascular complications. Changes in the commensal bacteria in the lung have been associated with the development of chronic lung conditions including asthma, cystic fibrosis, chronic obstructive pulmonary disease (COPD), and pulmonary fibrosis. The lung is a dynamic environment, constantly subject to influx of debris and microbes. The clearance of pathogens and adaptation to changes in commensal flora are mediated by innate and acquired immune responses that minimize inflammation and maintain pulmonary homeostasis. Surfactant proteins are essential for the structure and function of pulmonary surfactant, produced solely by pulmonary type 2 cells, and have their own intrinsic innate immune properties. The ATP Binding Cassette Transporter G1 (ABCG1) is highly expressed in pulmonary type 2 cells, alveolar macrophages and immune cells. We have recently demonstrated that ABCG1 regulates pulmonary B cell and natural antibody homeostasis. Here we show that mice lacking ABCG1 specifically in pulmonary type 2 cells have altered lamellar body and surfactant homeostasis. Additionally, we show that mice lacking ABCG1 have disturbances in the commensal bacteria that populate the lungs. Abcg1-/- mice may represent a novel model in which to study the interaction between pulmonary surfactant metabolism, pulmonary innate immune responses and the lung microbiome.

Department of Cellular & Molecular Medicine, Center for Cardiovascular Diagnostics and Prevention, and Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio 44195, USA. Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles 90095, USA. Department of Mathematics, Cleveland State University, Cleveland, Ohio 44115, USA. Department of Microbiology, Center for Clinical Epidemiology and Biostatistics, Division of Gastroenterology, and 8 Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA. Department of Pathology, Section on Lipid Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA. 10 Children's Hospital Oakland Research Institute, Oakland, CA 94609, USA.

Objective: Essential hypertension with its concurrent risk to other cardiovascular diseases affects approximately 25% of population in industrialized societies. Determining the genetic component of the disease is crucial for better understanding of the molecular basis of the phenotype and for developing more effective treatment of the disease. I present the data on a novel, so far non-described human polymorphic intronic AluYb8 element located in hypertension candidate gene WNK1 [With No K (lysine)]. WNK1 plays an important role in salt homeostasis through different mechanisms and thereby has functional importance in blood pressure regulation. Design and Methods: We have screened primates for the presence of WNK1 AluYb8 and genotyped 22 populations from Europe, Asia and Africa (854 individuals) to the distribution of this Alu-insertion. The carrier-status of the WNK1 AluYb8 insertion was explored for the association with cardiovascular traits (HYPEST and CADCZ sample collections) and the effect on gene expression profile in leucocytes. Results and Conclusions: The comparative sequencing showed that the surrounding genomic region of the human-specific WNK1 AluYb8 insertion is highly conserved between human and chimpanzee. Population genetic study indicated an expansion of the Alu-bearing chromosomes in Europe and Asia. The allele frequency of this Alu-insertion in Sub-Saharan Africa was ∼3.3 times lower than in other studied populations (4.8% versus 15.8%). Statistically significant association was detected between the carrier status of the WNK1 AluYb8 and systolic as well as diastolic blood pressure (linear regression testing, p = 0.01 and p = 0.03, respectively, HYPEST study, n = 1211). Subjects with the Alu insertion had higher blood pressure readings. In both, essential hypertension (17.7%) and coronary artery disease(17.23%) patients the allele frequency of the AluYb8 insertion was higher compared to controls (14.51% and 15.32%, respectively). Real-time PCR analysis showed that AluYb8 insertion affects the profile of alternative WNK1 transcripts in leucocytes. In conclusion this study suggests a possible involvement of WNK1 intronic polymorphic AluYb8 in increasing the susceptibility to essential hypertension.