Links between gut microbiome, metabolome, clinical variables and non-alcoholic fatty liver disease severity in bariatric patients.

BACKGROUND AND AIMS: Bacterial species and microbial pathways along with metabolites and clinical parameters may interact to contribute to non-alcoholic fatty liver disease (NAFLD) and disease severity. We used integrated machine learning models and a cross-validation approach to assess this interaction in bariatric patients. METHODS: 113 patients undergoing bariatric surgery had clinical and biochemical parameters, blood and stool metabolite measurements as well as faecal shotgun metagenome sequencing to profile the intestinal microbiome. Liver histology was classified as normal liver obese (NLO; n = 30), simple steatosis (SS; n = 41) or non-alcoholic steatohepatitis (NASH; n = 42); fibrosis was graded F0 to F4. RESULTS: We found that those with NASH versus NLO had an increase in potentially harmful E. coli, a reduction of potentially beneficial Alistipes putredinis and an increase in ALT and AST. There was higher serum glucose, faecal 3-(3-hydroxyphenyl)-3-hydroxypropionic acid and faecal cholic acid and lower serum glycerophospholipids. In NAFLD, those with severe fibrosis (F3-F4) versus F0 had lower abundance of anti-inflammatory species (Eubacterium ventriosum, Alistipes finegoldii and Bacteroides dorei) and higher AST, serum glucose, faecal acylcarnitines, serum isoleucine and homocysteine as well as lower serum glycerophospholipids. Pathways involved with amino acid biosynthesis and degradation were significantly more represented in those with NASH compared to NLO, with severe fibrosis having an overall stronger significant association with Superpathway of menaquinol-10 biosynthesis and Peptidoglycan biosynthesis IV. CONCLUSIONS: In bariatric patients, NASH and severe fibrosis were associated with specific bacterial species, metabolic pathways and metabolites that may contribute to NAFLD pathogenesis and disease severity.

Effect of faecal microbial transplant via colonoscopy in patients with severe obesity and insulin resistance: A randomized double-blind, placebo-controlled Phase 2 trial.

AIM: To assess the effects of faecal microbial transplant (FMT) from lean people to subjects with obesity via colonoscopy. MATERIAL AND METHODS: In a double-blind, randomized controlled trial, subjects with a body mass index ≥ 35 kg/m2 and insulin resistance were randomized, in a 1:1 ratio in blocks of four, to either allogenic (from healthy lean donor; n = 15) or autologous FMT (their own stool; n = 13) delivered in the caecum and were followed for 3 months. The main outcome was homeostatic model assessment of insulin resistance (HOMA-IR) and secondary outcomes were glycated haemoglobin levels, lipid profile, weight, gut hormones, endotoxin, appetite measures, intestinal microbiome (IM), metagenome, serum/faecal metabolites, quality of life, anxiety and depression scores. RESULTS: In the allogenic versus autologous groups, HOMA-IR and clinical variables did not change significantly, but IM and metabolites changed favourably (P < 0.05): at 1 month, Coprococcus, Bifidobacterium, Bacteroides and Roseburia increased, and Streptococcus decreased; at 3 months, Bacteroides and Blautia increased. Several species also changed significantly. For metabolites, at 1 month, serum kynurenine decreased and faecal indole acetic acid and butenylcarnitine increased, while at 3 months, serum isoleucine, leucine, decenoylcarnitine and faecal phenylacetic acid decreased. Metagenomic pathway representations and network analyses assessing relationships with clinical variables, metabolites and IM were significantly enhanced in the allogenic versus autologous groups. LDL and appetite measures improved in the allogenic (P < 0.05) but not in the autologous group. CONCLUSIONS: Overall, in those with obeisty, allogenic FMT via colonoscopy induced favourable changes in IM, metabolites, pathway representations and networks even though other metabolic variables did not change. LDL and appetite variables may also benefit.

New approaches and technical considerations in detecting outlier measurements and trajectories in longitudinal children growth data.

BACKGROUND: Growth studies rely on longitudinal measurements, typically represented as trajectories. However, anthropometry is prone to errors that can generate outliers. While various methods are available for detecting outlier measurements, a gold standard has yet to be identified, and there is no established method for outlying trajectories. Thus, outlier types and their effects on growth pattern detection still need to be investigated. This work aimed to assess the performance of six methods at detecting different types of outliers, propose two novel methods for outlier trajectory detection and evaluate how outliers affect growth pattern detection. METHODS: We included 393 healthy infants from The Applied Research Group for Kids (TARGet Kids!) cohort and 1651 children with severe malnutrition from the co-trimoxazole prophylaxis clinical trial. We injected outliers of three types and six intensities and applied four outlier detection methods for measurements (model-based and World Health Organization cut-offs-based) and two for trajectories. We also assessed growth pattern detection before and after outlier injection using time series clustering and latent class mixed models. Error type, intensity, and population affected method performance. RESULTS: Model-based outlier detection methods performed best for measurements with precision between 5.72-99.89%, especially for low and moderate error intensities. The clustering-based outlier trajectory method had high precision of 14.93-99.12%. Combining methods improved the detection rate to 21.82% in outlier measurements. Finally, when comparing growth groups with and without outliers, the outliers were shown to alter group membership by 57.9 -79.04%. CONCLUSIONS: World Health Organization cut-off-based techniques were shown to perform well in few very particular cases (extreme errors of high intensity), while model-based techniques performed well, especially for moderate errors of low intensity. Clustering-based outlier trajectory detection performed exceptionally well across all types and intensities of errors, indicating a potential strategic change in how outliers in growth data are viewed. Finally, the importance of detecting outliers was shown, given its impact on children growth studies, as demonstrated by comparing results of growth group detection.

Nordic dietary patterns and cardiometabolic outcomes: a systematic review and meta-analysis of prospective cohort studies and randomised controlled trials.

AIMS/HYPOTHESIS: Nordic dietary patterns that are high in healthy traditional Nordic foods may have a role in the prevention and management of diabetes. To inform the update of the EASD clinical practice guidelines for nutrition therapy, we conducted a systematic review and meta-analysis of Nordic dietary patterns and cardiometabolic outcomes. METHODS: We searched MEDLINE, EMBASE and The Cochrane Library from inception to 9 March 2021. We included prospective cohort studies and RCTs with a follow-up of ≥1 year and ≥3 weeks, respectively. Two independent reviewers extracted relevant data and assessed the risk of bias (Newcastle-Ottawa Scale and Cochrane risk of bias tool). The primary outcome was total CVD incidence in the prospective cohort studies and LDL-cholesterol in the RCTs. Secondary outcomes in the prospective cohort studies were CVD mortality, CHD incidence and mortality, stroke incidence and mortality, and type 2 diabetes incidence; in the RCTs, secondary outcomes were other established lipid targets (non-HDL-cholesterol, apolipoprotein B, HDL-cholesterol, triglycerides), markers of glycaemic control (HbA1c, fasting glucose, fasting insulin), adiposity (body weight, BMI, waist circumference) and inflammation (C-reactive protein), and blood pressure (systolic and diastolic blood pressure). The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach was used to assess the certainty of the evidence. RESULTS: We included 15 unique prospective cohort studies (n=1,057,176, with 41,708 cardiovascular events and 13,121 diabetes cases) of people with diabetes for the assessment of cardiovascular outcomes or people without diabetes for the assessment of diabetes incidence, and six RCTs (n=717) in people with one or more risk factor for diabetes. In the prospective cohort studies, higher adherence to Nordic dietary patterns was associated with 'small important' reductions in the primary outcome, total CVD incidence (RR for highest vs lowest adherence: 0.93 [95% CI 0.88, 0.99], p=0.01; substantial heterogeneity: I2=88%, pQ<0.001), and similar or greater reductions in the secondary outcomes of CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). Inverse dose-response gradients were seen for total CVD incidence, CVD mortality and incidence of CHD, stroke and type 2 diabetes (p<0.05). No studies assessed CHD or stroke mortality. In the RCTs, there were small important reductions in LDL-cholesterol (mean difference [MD] -0.26 mmol/l [95% CI -0.52, -0.00], pMD=0.05; substantial heterogeneity: I2=89%, pQ<0.01), and 'small important' or greater reductions in the secondary outcomes of non-HDL-cholesterol, apolipoprotein B, insulin, body weight, BMI and systolic blood pressure (p<0.05). For the other outcomes there were 'trivial' reductions or no effect. The certainty of the evidence was low for total CVD incidence and LDL-cholesterol; moderate to high for CVD mortality, established lipid targets, adiposity markers, glycaemic control, blood pressure and inflammation; and low for all other outcomes, with evidence being downgraded mainly because of imprecision and inconsistency. CONCLUSIONS/INTERPRETATION: Adherence to Nordic dietary patterns is associated with generally small important reductions in the risk of major CVD outcomes and diabetes, which are supported by similar reductions in LDL-cholesterol and other intermediate cardiometabolic risk factors. The available evidence provides a generally good indication of the likely benefits of Nordic dietary patterns in people with or at risk for diabetes. REGISTRATION: ClinicalTrials.gov NCT04094194. FUNDING: Diabetes and Nutrition Study Group of the EASD Clinical Practice.

Microbiota medicine: towards clinical revolution.

The human gastrointestinal tract is inhabited by the largest microbial community within the human body consisting of trillions of microbes called gut microbiota. The normal flora is the site of many physiological functions such as enhancing the host immunity, participating in the nutrient absorption and protecting the body against pathogenic microorganisms. Numerous investigations showed a bidirectional interplay between gut microbiota and many organs within the human body such as the intestines, the lungs, the brain, and the skin. Large body of evidence demonstrated, more than a decade ago, that the gut microbial alteration is a key factor in the pathogenesis of many local and systemic disorders. In this regard, a deep understanding of the mechanisms involved in the gut microbial symbiosis/dysbiosis is crucial for the clinical and health field. We review the most recent studies on the involvement of gut microbiota in the pathogenesis of many diseases. We also elaborate the different strategies used to manipulate the gut microbiota in the prevention and treatment of disorders. The future of medicine is strongly related to the quality of our microbiota. Targeting microbiota dysbiosis will be a huge challenge.

MicroRNAs: A Link between Mammary Gland Development and Breast Cancer.

Breast cancer is among the most common cancers in women, second to skin cancer. Mammary gland development can influence breast cancer development in later life. Processes such as proliferation, invasion, and migration during mammary gland development can often mirror processes found in breast cancer. MicroRNAs (miRNAs), small, non-coding RNAs, can repress post-transcriptional RNA expression and can regulate up to 80% of all genes. Expression of miRNAs play a key role in mammary gland development, and aberrant expression can initiate or promote breast cancer. Here, we review the role of miRNAs in mammary development and breast cancer, and potential parallel roles. A total of 32 miRNAs were found to be expressed in both mammary gland development and breast cancer. These miRNAs are involved in proliferation, metastasis, invasion, and apoptosis in both processes. Some miRNAs were found to have contradictory roles, possibly due to their ability to target many genes at once. Investigation of miRNAs and their role in mammary gland development may inform about their role in breast cancer. In particular, by studying miRNA in development, mechanisms and potential targets for breast cancer treatment may be elucidated.

Citrobacter rodentium alters the mouse colonic miRNome.

Citrobacter rodentium is a murine pathogen causing transmissible colonic hyperplasia and colitis with a pathogenic mechanism similar to foodborne enterohaemorrhagic Escherichia coli in humans. Mechanisms underlying intestinal responses to C. rodentium infection are incompletely understood. We identified 24 colonic microRNAs (miRNAs) as significantly deregulated in response to C. rodentium, including miR-7a, -17, -19a, -20a, -20b, -92a, -106a, -132, -200a, and -2137; most of these miRNAs belong to the oncogenic miR-17-92 clusters. Pathways involved in cell cycle, cancers, and immune responses were enriched among the predicted targets of these miRNAs. We further demonstrated that an apoptosis facilitator, Bim, is a candidate gene target of miRNA-mediated host response to the infection. These findings suggest that host miRNAs participate in C. rodentium pathogenesis and may represent novel treatment targets.

Omega-3 Polyunsaturated Fatty Acids Time-Dependently Reduce Cell Viability and Oncogenic MicroRNA-21 Expression in Estrogen Receptor-Positive Breast Cancer Cells (MCF-7).

The omega-3 polyunsaturated fatty acid (n-3 PUFA), α-linolenic acid (ALA), and its metabolites, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), independently reduce the growth of breast cancer cells in vitro, but the mechanisms, which may involve microRNA (miRNA), are still unclear. The expression of the oncomiR, miR-21, is reduced by DHA treatment, but the effects of ALA on miR-21, alone or combined with EPA and DHA under physiologically relevant concentrations, have not been investigated. The effects of ALA alone and +/-EPA and DHA at the blood molar ratios seen in either humans (1.0:1.0:2.5, ALA:EPA:DHA) or mice (1.0:0.4:3.1, ALA:EPA:DHA) post flaxseed oil consumption (containing ALA) were assessed in vitro in MCF-7 breast cancer cells. Cell viability and the expression of miR-21 and its molecular target, phosphatase and tension homolog (PTEN, gene and protein), at different time points, were examined. At 1, 3, 48 and 96 h ALA alone and 24 h animal ratio treatments significantly reduced MCF-7 cell viability, while 1 and 3 h ALA alone and human and animal ratio treatments all significantly reduced miR-21 expression, and 24 h animal ratio treatment reduced miR-21 expression; these effects were not associated with changes in PTEN gene or protein expressions. We showed for the first time that ALA alone or combined with EPA and DHA at levels seen in human and animal blood post-ALA consumption can significantly reduce cell viability and modulate miR-21 expression in a time- and concentration-dependent manner, with the animal ratio containing higher DHA having a greater effect. The time dependency of miR-21 effects suggests the significance of considering time as a variable in miRNA studies, particularly of miR-21.

Gut microbiota-bone axis.

The gut microbiota (GM) is an important regulator of body homeostasis, including intestinal and extra-intestinal effects. This review focuses on the GM-bone axis, which we define as the effect of the gut-associated microbial community or the molecules they synthesize, on bone health. While research in this field is limited, findings from preclinical studies support that gut microbes positively impact bone mineral density and strength parameters. Moreover, administration of beneficial bacteria (probiotics) in preclinical models has demonstrated higher bone mineralization and greater bone strength. The preferential bacterial genus that has shown these beneficial effects in bone is Lactobacillus and thus lactobacilli are among the best candidates for future clinical intervention trials. However, their effectiveness is dependent on stage of development, as early life constitutes an important time for impacting bone health, perhaps via modulation of the GM. In addition, sex-specific difference also impacts the efficacy of the probiotics. Although auspicious, many questions regarding the GM-bone axis require consideration of potential mechanisms; sex-specific efficacy; effective dose of probiotics; and timing and duration of treatment.

Altered hepatic gene expression in nonalcoholic fatty liver disease is associated with lower hepatic n-3 and n-6 polyunsaturated fatty acids.

UNLABELLED: In nonalcoholic fatty liver disease, hepatic gene expression and fatty acid (FA) composition have been reported independently, but a comprehensive gene expression profiling in relation to FA composition is lacking. The aim was to assess this relationship. In a cross-sectional study, hepatic gene expression (Illumina Microarray) was first compared among 20 patients with simple steatosis (SS), 19 with nonalcoholic steatohepatitis (NASH), and 24 healthy controls. The FA composition in hepatic total lipids was compared between SS and NASH, and associations between gene expression and FAs were examined. Gene expression differed mainly between healthy controls and patients (SS and NASH), including genes related to unsaturated FA metabolism. Twenty-two genes were differentially expressed between NASH and SS; most of them correlated with disease severity and related more to cancer progression than to lipid metabolism. Biologically active long-chain polyunsaturated FAs (PUFAs; eicosapentaenoic acid + docosahexaenoic acid, arachidonic acid) in hepatic total lipids were lower in NASH than in SS. This may be related to overexpression of FADS1, FADS2, and PNPLA3. The degree and direction of correlations between PUFAs and gene expression were different among SS and NASH, which may suggest that low PUFA content in NASH modulates gene expression in a different way compared with SS or, alternatively, that gene expression influences PUFA content differently depending on disease severity (SS versus NASH). CONCLUSION: Well-defined subjects with either healthy liver, SS, or NASH showed distinct hepatic gene expression profiles including genes involved in unsaturated FA metabolism. In patients with NASH, hepatic PUFAs were lower and associations with gene expression were different compared to SS.

Mucin-Microbiota Interaction During Postnatal Maturation of the Intestinal Ecosystem: Clinical Implications.

The mucus layer and gut microbiota interplay contributes to host homeostasis. The mucus layer serves as a scaffold and a carbon source for gut microorganisms; conversely, gut microorganisms, including mucin degraders, influence mucin gene expression, glycosylation, and secretion. Conjointly they shield the epithelium from luminal pathogens, antigens, and toxins. Importantly, the mucus layer and gut microbiota are established in parallel during early postnatal life. During this period, the development of gut microbiota and mucus layer is coupled with that of the immune system. Developmental changes of different mucin types can impact the age-dependent patterns of intestinal infection in terms of incidence and severity. Altered mucus layer, dysbiotic microbiota, and abnormal mucus-gut microbiota interaction have the potential for inducing systemic effects, and accompany several intestinal diseases such as inflammatory bowel disease, colorectal cancer, and radiation-induced mucositis. Early life provides a pivotal window of opportunity to favorably modulate the mucus-microbiota interaction. The support of a health-compatible mucin-microbiota maturation in early life is paramount for long-term health and serves as an important opportunity for clinical intervention.

Intestinal microbiota in patients with nonalcoholic fatty liver disease.

UNLABELLED: Despite evidence that the intestinal microbiota (IM) is involved in the pathogenesis of obesity, the IM composition of patients with nonalcoholic fatty liver disease (NAFLD) has not been well characterized. This prospective, cross-sectional study was aimed at identifying differences in IM between adults with biopsy-proven NAFLD (simple steatosis [SS] or nonalcoholic steatohepatitis [NASH]) and living liver donors as healthy controls (HC). Fifty subjects were included: 11 SS, 22 NASH, and 17 HC. One stool sample was collected from each participant. Quantitative real-time polymerase chain reaction was used to measure total bacterial counts, Bacteroides/Prevotella (herein referred to as Bacteroidetes), Clostridium leptum, C. coccoides, bifidobacteria, Escherichia coli and Archaea in stool. Clinical and laboratory data, food records, and activity logs were collected. Patients with NASH had a lower percentage of Bacteroidetes (Bacteroidetes to total bacteria counts) compared to both SS and HC (P = 0.006) and higher fecal C. coccoides compared to those with SS (P = 0.04). There were no differences in the remaining microorganisms. As body mass index (BMI) and dietary fat intake differed between the groups (P < 0.05), we performed linear regression adjusting for these variables. The difference in C. coccoides was no longer significant after adjusting for BMI and fat intake. However, there continued to be a significant association between the presence of NASH and lower percentage Bacteroidetes even after adjusting for these variables (P = 0.002; 95% confidence interval = -0.06 to -0.02). CONCLUSION: There is an inverse and diet-/BMI-independent association between the presence of NASH and percentage Bacteroidetes in the stool, suggesting that the IM may play a role in the development of NAFLD.

Cecal microbiota and mammary gland microRNA signatures are related and modifiable by dietary flaxseed with implications for breast cancer risk.

IMPORTANCE: Breast cancer is a leading cause of cancer mortality worldwide. There is a growing interest in using dietary approaches, including flaxseed (FS) and its oil and lignan components, to mitigate breast cancer risk. Importantly, there is recognition that pubertal processes and lifestyle, including diet, are important for breast health throughout life. Mechanisms remain incompletely understood. Our research uncovers a link between mammary gland miRNA expression and the gut microbiota in young female mice. We found that this relationship is modifiable via a dietary intervention. Using data from The Cancer Genome Atlas, we also show that the expression of miRNAs involved in these relationships is altered in breast cancer in humans. These findings highlight a role for the gut microbiome as a modulator, and thus a target, of interventions aiming at reducing breast cancer risk. They also provide foundational knowledge to explore the effects of early life interventions and mechanisms programming breast health.

Data on microRNA expression, predicted gene targets and pathway analysis in response to different concentrations of a cranberry proanthocyanidin-rich extract and its metabolite 3-(4-hydroxyphenyl)-propionic acid in intestinal Caco-2BBe1 cells.

Cranberry-derived proanthocyanidin (PAC) is processed by the gut microbiota to produce 3-(4-hydroxyphenyl)-propionic acid (HPPA), among other metabolites. These data are in support of the article entitled, "Cranberry proanthocyanidin and its microbial metabolite 3,4-dihydroxyphenylacetic acid, but not 3-(4-hydroxyphenyl)-propionic acid, partially reverse pro-inflammatory microRNA responses in human intestinal epithelial cells," published in Molecular Nutrition and Food Research [1]. Here we describe data generated by nCounterⓇ Human v3 miRNA Expression Panel of RNA obtained from Caco-2BBe1 cells exposed to two different concentrations of cranberry extract rich in PAC (50 µg/ml or 100 µg/ml) or 3-(4-hydroxyphenyl)-propionic acid (5 µg/ml or 10 µg/ml) for 24 h, then stimulated with 1 ng/ml of IL-1ß or not (mock) for three hours. The raw data are publicly available at the NCBI GEO database GSE237078. This work also includes descriptive methodological procedures, treatment-responsive microRNA (miRNA) expression profiles in Caco-2BBe1 cells, and in silico mRNA gene target and pathway enrichment analyses of significantly differentially expressed miRNAs (q < 0.001). Cranberry and its components have recognized health benefits, particularly in relation to combatting inflammation and pathogenic bacterial adhesion. These data will be valuable as a reference to study the response of intestinal cells to other polyphenol-rich food sources, analyze gut microbial responses to cranberry and its metabolites in different cell lines and mammalian hosts to elucidate individualized effects, and to delineate the role of the gut microbiota in facilitating the benefits of cranberry. Moreover, these data will aid in expanding our knowledge on the mechanisms underlying the benefits of cranberry and its components.

Accelerometer-based sleep metrics and gut microbiota during adolescence: Association findings from a Brazilian population-based birth cohort.

BACKGROUND: Sleep and gut microbiota are emerging putative risk factors for several physical, mental, and cognitive conditions. Sleep deprivation has been shown to be linked with unhealthy microbiome environments in animal studies. However, in humans, the results are mixed. Epidemiological studies evaluating the effect of accelerometer-based sleep measures on gut microbiome are scarce. This study aims to explore the relationship between sleep duration and efficiency with the gut microbiota in adolescence. METHODS: A subsample of 352 participants from the 2004 Pelotas (Brazil) Birth Cohort Study with sleep and fecal microbiota data available were included in the study. Sleep duration and sleep efficiency were obtained from actigraphy information at 11 years old whereas microbiota information from fecal samples was collected at 12 years. The fecal microbiota was analyzed via Illumina MiSeq (16S rRNA V3-V4 region) and the UNOISE pipeline. Alpha was assessed in QIIME2. Association measures for sleep variables and microbial α-diversity, and bacterial relative abundance were assessed through generalized models (linear and logistic regression), adjusting for maternal and child variables confounders. RESULTS: Adjusted models showed that sleep duration was positively associated with Simpson index of α-diversity (ß = 0.003; CI95 %: 0.00004; 0.01). Both sleep duration (OR = 0.43; CI95 % 0.25; 0.74) and efficiency (OR = 0.55; CI95 % 0.38; 0.78) were associated with lower Bacteroidetes abundance. CONCLUSION: Our results suggest that sleep duration and efficiency are linked to gut microbiota diversity and composition even with 1-2 years gap from exposure to outcome. The findings support the role of sleep in the gut-brain axis as well as provide insights on how to improve microbiota health.

Age, dietary fiber, breath methane, and fecal short chain fatty acids are interrelated in Archaea-positive humans.

Recent attention has focused on the significance of colonic Archaea in human health and energy metabolism. The main objectives of this study were to determine the associations among the number of fecal Archaea, body mass index (BMI), fecal short chain fatty acid (SCFA) concentrations, and dietary intakes of healthy humans. We collected demographic information, 3-d diet records, and breath and fecal samples from 95 healthy participants who were divided into 2 groups: detectable Archaea (>10(6) copies/g; Arch+ve) and undetectable Archaea. Dietary intakes, BMI, and fecal SCFAs were similar in both groups. The mean number of Archaea 16S rRNA gene copies detected in Arch+ve participants' feces was 8.9 ± 0.2 log/g wet weight. In Arch+ve participants, there were positive correlations between breath methane and age (r = 0.52; P = 0.001), total dietary fiber (TDF) intake (r = 0.57; P = 0.0003), and log number of fecal Archaea 16S rRNA gene copies (r = 0.35; P = 0.03). In the Arch+ve group, negative correlations were observed between TDF/1000 kcal and fecal total SCFA (r = -0.46; P ≤ 0.01) and between breath methane and fecal total SCFA (r = -0.42; P = 0.01). Principal component analysis identified a distinct Archaea factor with positive loadings of age, breath methane, TDF, TDF/1000 kcal, and number of log Archaea 16S rRNA gene copies. The results suggest that colonic Archaea is not associated with obesity in healthy humans. The presence of Archaea in humans may influence colonic fermentation by altering SCFA metabolism and fecal SCFA profile.

Lipopolysaccharide-Induced Bone Loss in Rodent Models: A Systematic Review and Meta-Analysis.

Osteoporosis has traditionally been characterized by underlying endocrine mechanisms, though evidence indicates a role of inflammation in its pathophysiology. Lipopolysaccharide (LPS), a component of gram-negative bacteria that reside in the intestines, can be released into circulation and stimulate the immune system, upregulating bone resorption. Exogenous LPS is used in rodent models to study the effect of systemic inflammation on bone, and to date a variety of different doses, routes, and durations of LPS administration have been used. The study objective was to determine whether systemic administration of LPS induced inflammatory bone loss in rodent models. A systematic search of Medline and four other databases resulted in a total of 110 studies that met the inclusion criteria. Pooled standardized mean differences (SMDs) and corresponding 95% confidence intervals (CI) with a random-effects meta-analyses were used for bone volume fraction (BV/TV) and volumetric bone mineral density (vBMD). Heterogeneity was quantified using the I2 statistic. Shorter-term (<2 weeks) and longer-term (>2 weeks) LPS interventions were analyzed separately because of intractable study design differences. BV/TV was significantly reduced in both shorter-term (SMD = -3.79%, 95% CI [-4.20, -3.38], I2 62%; p < 0.01) and longer-term (SMD = -1.50%, 95% CI [-2.00, -1.00], I2 78%; p < 0.01) studies. vBMD was also reduced in both shorter-term (SMD = -3.11%, 95% CI [-3.78, -2.44]; I2 72%; p < 0.01) and longer-term (SMD = -3.49%, 95% CI [-4.94, -2.04], I2 82%; p < 0.01) studies. In both groups, regardless of duration, LPS negatively impacted trabecular bone structure but not cortical bone structure, and an upregulation in bone resorption demonstrated by bone cell staining and serum biomarkers was reported. This suggests systemically delivered exogenous LPS in rodents is a viable model for studying inflammatory bone loss, particularly in trabecular bone. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

A novel systematic pipeline for increased predictability and explainability of growth patterns in children using trajectory features.

OBJECTIVE: Longitudinal patterns of growth in early childhood are associated with health conditions throughout life. Knowledge of such patterns and the ability to predict them can lead to better prevention and improved health promotion in adulthood. However, growth analyses are characterized by significant variability, and pattern detection is affected by the method applied. Moreover, pattern labelling is typically performed based on ad hoc methods, such as visualizations or clinical experience. Here, we propose a novel pipeline using features extracted from growth trajectories using mathematical, statistical and machine-learning approaches to predict growth patterns and label them in a systematic and unequivocal manner. METHODS: We extracted mathematical and clinical features from 9577 children growth trajectories embedded with machine-learning predictions of the growth patterns. We experimented with two sets of features (CAnonical Time-series Characteristics and trajectory features specific to growth), developmental periods and six machine-learning classifiers. Clinical experts provided labels for the detected patterns and decision rules were created to associate the features with the labelled patterns. The predictive capacity of the extracted features was validated on two heterogenous populations (The Applied Research Group for Kids and the 2004 Pelotas Birth Cohort, based in Canada and Brazil, respectively). RESULTS: Features predictive ability measured by accuracy and F1 score was ≥ 80% and ≥ 0.76 respectively in both cohorts. A small number of features (n = 74) was sufficient to distinguish between growth patterns in both cohorts. Slope, intercept of the trajectory, age at peak value, start value and change of the growth measure were among the top identified features. CONCLUSION: Growth features can be reliably used as predictors of growth patterns and provide an unbiased understanding of growth patterns. They can be used as tool to reduce the effort to repeat analysis and variability concerning anthropometric measures, time points and analytical methods, in the context of the same or similar populations.

Intestinal microRNAs and bacterial taxa in juvenile mice are associated, modifiable by allochthonous lactobacilli, and affect postnatal maturation.

The interplay between the intestinal microbiota and host is critical to intestinal ontogeny and homeostasis. MicroRNAs (miRNAs) may be an underlying link. Intestinal miRNAs are microbiota-dependent and, when shed in the lumen, affect resident microorganisms. Yet, longitudinal relationships between intestinal tissue miRNAs, luminal miRNAs, and luminal microorganisms have not been elucidated, especially in early life. Here, we investigated the postnatal cecal miRNA and microbiota populations, their relationship, and their impact on intestinal maturation in specific pathogen-free mice; we also assessed if they can be modified by intervention with allochthonous probiotic lactobacilli. We report that cecal and cecal content miRNA and microbiota signatures are temporally regulated, correlated, and modifiable by probiotics with implications for intestinal maturation. These findings help understand causal relationships within the gut ecosystem and provide a basis for preventing and managing their alterations in diseases throughout life. IMPORTANCE The gut microbiota affects intestinal microRNA (miRNA) signatures and is modified by host-derived luminal miRNA. This suggests the existence of close miRNA-microbiota relationships that are critical to intestinal homeostasis. However, an integrative analysis of these relationships and their evolution during intestinal postnatal maturation is lacking. We provide a system-level longitudinal analysis of miRNA-microbiota networks in the intestine of mice at the weaning transition, including tissue and luminal miRNA and luminal microbiota. To address causality and move toward translational applications, we used allochthonous probiotic lactobacilli to modify these longitudinal relationships and showed that they are critical for intestinal maturation in early life. These findings contribute to understand mechanisms that underlie the maturation of the intestinal ecosystem and suggest that interventions aiming at maintaining, or restoring, homeostasis cannot prescind from considering relationships among its components.

A novel shape-based approach to identify gestational age-adjusted growth patterns from birth to 11 years of age.

Child growth patterns assessment is critical to design public health interventions. However, current analytical approaches may overlook population heterogeneity. To overcome this limitation, we developed a growth trajectories clustering pipeline that incorporates a shape-respecting distance, baseline centering (i.e., birth-size normalized trajectories) and Gestational Age (GA)-correction to characterize shape-based child growth patterns. We used data from 3945 children (461 preterm) in the 2004 Pelotas Birth Cohort with at least 3 measurements between birth (included) and 11 years of age. Sex-adjusted weight-, length/height- and body mass index-for-age z-scores were derived at birth, 3 months, and at 1, 2, 4, 6 and 11 years of age (INTERGROWTH-21st and WHO growth standards). Growth trajectories clustering was conducted for each anthropometric index using k-means and a shape-respecting distance, accounting or not for birth size and/or GA-correction. We identified 3 trajectory patterns for each anthropometric index: increasing (High), stable (Middle) and decreasing (Low). Baseline centering resulted in pattern classification that considered early life growth traits. GA-correction increased the intercepts of preterm-born children trajectories, impacting their pattern classification. Incorporating shape-based clustering, baseline centering and GA-correction in growth patterns analysis improves the identification of subgroups meaningful for public health interventions.