Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations.

The microbiota in individual habitats differ in both relative composition and absolute abundance. While sequencing approaches determine the relative abundances of taxa and genes, they do not provide information on their absolute abundances. Here, we developed a machine-learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data.

Comorbidities confound metabolomics studies of human disease.

The co-occurrence of multiple chronic conditions, termed multimorbidity, presents an expanding global health challenge, demanding effective diagnostics and treatment strategies. Chronic ailments such as obesity, diabetes, and cardiovascular diseases have been linked to metabolites interacting between the host and microbiota. In this study, we investigated the impact of co-existing conditions on risk estimations for 1375 plasma metabolites in 919 individuals from population-based Estonian Biobank cohort using liquid chromatography mass spectrometry (LC-MS) method.

A history of repeated antibiotic usage leads to microbiota-dependent mucus defects.

Recent evidence indicates that repeated antibiotic usage lowers microbial diversity and ultimately changes the gut microbiota community. However, the physiological effects of repeated - but not recent - antibiotic usage on microbiota-mediated mucosal barrier function are largely unknown. By selecting human individuals from the deeply phenotyped Estonian Microbiome Cohort (EstMB), we here utilized human-to-mouse fecal microbiota transplantation to explore long-term impacts of repeated antibiotic use on intestinal mucus function.

Gut microbiome in endometriosis: a cohort study on 1000 individuals.

Background: Endometriosis, defined as the presence of endometrial-like tissue outside of the uterus, is one of the most prevalent gynecological disorders. Although different theories 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, their dysbiosis, and the development of endometriosis is understudied.

Association of Accelerometer-Determined Physical Activity and Sedentary Behavior With the Gut Microbiome in Middle-Aged Women: A Compositional Data Approach.

The beneficial effects of physical activity (PA) on gut microbiome have been reported, nevertheless the findings are inconsistent, with the main limitation of subjective methods for assessing PA. It is well accepted that using an objective assessment of PA reduces the measurement error and also allows objective assessment of sedentary behavior (SB). We aimed to study the associations between accelerometer-assessed behaviors (i.

Cell-Free Microbial DNA Analysis: Effects of Blood Plasma and Serum Quantity, Biobanking Protocols, and Isolation Kits.

Recent studies highlight the presence of bacterial sequences in the human blood, suggesting potential clinical significance for circulating microbial signatures. These sequences could presumably serve in the diagnosis, prediction, or monitoring of various health conditions. Ensuring the similarity of samples before bacterial analysis is crucial, especially when combining samples from different biobanks prepared under varying conditions (such as different DNA extraction kits, centrifugation conditions, blood collection tubes, etc.

Uterine Microbiome: Does the Sampling Technique Matter?

Studies have proven the significance of microbial communities in various parts of the human body for health. In recent years it has been discovered that the uterine cavity is not sterile, and endometrium has its own microbiome which appears to have an impact on female fertility and gynecological pathologies. has shown to dominate the microbial profile in the uterus and is considered an indicator of a healthy uterine environment.

Evaluating the clinical relevance of the enterotypes in the Estonian microbiome cohort.

Human gut microbiome is subject to high inter-individual and temporal variability, which complicates building microbiome-based applications, including applications that can be used to improve public health. Categorizing the microbiome profiles into a small number of distinct clusters, such as enterotyping, has been proposed as a solution that can ameliorate these shortcomings. However, the clinical relevance of the enterotypes is poorly characterized despite a few studies marking the potential for using the enterotypes for disease diagnostics and personalized nutrition.

Gut metagenome associations with extensive digital health data in a volunteer-based Estonian microbiome cohort.

Microbiome research is starting to move beyond the exploratory phase towards interventional trials and therefore well-characterized cohorts will be instrumental for generating hypotheses and providing new knowledge. As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. Here we analyze stool data from deep metagenomic sequencing together with rich phenotyping, including 71 diseases, 136 medications, 21 dietary questions, 5 medical procedures, and 19 other factors.

Differences in microbial profile of endometrial fluid and tissue samples in women with in vitro fertilization failure are driven by Lactobacillus abundance.

Introduction: The endometrial microbiota has been linked to several gynecological disorders, including infertility. It has been shown that the microbial profile of endometrium could have a role in fertilization and pregnancy outcomes. In this study we aim to assess the microbial community of endometrial tissue (ET) and endometrial fluid (EF) samples in women receiving in vitro fertilization (IVF) treatment.

The Nutritional Supplement -Alpha Glycerylphosphorylcholine Promotes Atherosclerosis.

-alpha glycerylphosphorylcholine (GPC), a nutritional supplement, has been demonstrated to improve neurological function. However, a new study suggests that GPC supplementation increases incident stroke risk thus its potential adverse effects warrant further investigation. Here we show that GPC promotes atherosclerosis in hyperlipidemic mice.

Using fecal immunochemical tubes for the analysis of the gut microbiome has the potential to improve colorectal cancer screening.

Colorectal cancer (CRC) is a challenging public health problem which successful treatment depends on the stage at diagnosis. Recently, CRC-specific microbiome signatures have been proposed as a marker for CRC detection. Since many countries have initiated CRC screening programs, it would be useful to analyze the microbiome in the samples collected in fecal immunochemical test (FIT) tubes for fecal occult blood testing.

Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment.

The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations and their relation to the development and progression of various complex diseases. Improved data-analytical tools are needed to exploit all information from these biological datasets, taking into account the peculiarities of microbiome data, i.

Machine Learning Reveals Time-Varying Microbial Predictors with Complex Effects on Glucose Regulation.

The incidence of type 2 diabetes (T2D) has been increasing globally, and a growing body of evidence links type 2 diabetes with altered microbiota composition. Type 2 diabetes is preceded by a long prediabetic state characterized by changes in various metabolic parameters. We tested whether the gut microbiome could have predictive potential for T2D development during the healthy and prediabetic disease stages.

Large-scale association analyses identify host factors influencing human gut microbiome composition.

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10) threshold.

The Gut Microbiome in Polycystic Ovary Syndrome and Its Association with Metabolic Traits.

Context: Despite the gut microbiome being widely studied in metabolic diseases, its role in polycystic ovary syndrome (PCOS) has been scarcely investigated.

Objective: Compare the gut microbiome in late fertile age women with and without PCOS and investigate whether changes in the gut microbiome correlate with PCOS-related metabolic parameters.

Design: Prospective, case-control study using the Northern Finland Birth Cohort 1966.

IL-22 Paucity in APECED Is Associated With Mucosal and Microbial Alterations in Oral Cavity.

Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APECED) is caused by recessive mutations in the gene. The hallmark of the disease is the production of highly neutralizing autoantibodies against type I interferons and IL-22. Considering the importance of IL-22 in maintaining mucosal barrier integrity and shaping its microbial community, we sought to study potential changes in the oral cavity in this model of human IL-22 paucity.

Publisher Correction: Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.

In the version of this article originally published, the name of author Martin H. de Borst was coded incorrectly in the XML. The error has now been corrected in the HTML version of the paper.

Using the natural variation of mouse populations to understand host-gut microbiome interactions.

One approach to understanding gut microbiome-host interactions, described in this review, is to examine how natural variation in a model organism, where environmental factors can be controlled, affects the microbiome and, in turn, how the microbiome is associated with physiological or clinical traits. A variation of this approach, termed "systems genetics" is to characterize both the microbiome and the host using various high throughput technologies, such as metabolomics or gene expression of the microbiome and the host. By relating variation in the microbiome and host functions to such "molecular phenotypes", hypotheses can be generated and then experimentally tested.

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals.

Efficient and Accurate Multiple-Phenotype Regression Method for High Dimensional Data Considering Population Structure.

A typical genome-wide association study tests correlation between a single phenotype and each genotype one at a time. However, single-phenotype analysis might miss unmeasured aspects of complex biological networks. Analyzing many phenotypes simultaneously may increase the power to capture these unmeasured aspects and detect more variants.