Co-localization of antibiotic resistance genes is widespread in the infant gut microbiome and associates with an immature gut microbial composition.

BACKGROUND: In environmental bacteria, the selective advantage of antibiotic resistance genes (ARGs) can be increased through co-localization with genes such as other ARGs, biocide resistance genes, metal resistance genes, and virulence genes (VGs). The gut microbiome of infants has been shown to contain numerous ARGs, however, co-localization related to ARGs is unknown during early life despite frequent exposures to biocides and metals from an early age. RESULTS: We conducted a comprehensive analysis of genetic co-localization of resistance genes in a cohort of 662 Danish children and examined the association between such co-localization and environmental factors as well as gut microbial maturation. Our study showed that co-localization of ARGs with other resistance and virulence genes is common in the early gut microbiome and is associated with gut bacteria that are indicative of low maturity. Statistical models showed that co-localization occurred mainly in the phylum Proteobacteria independent of high ARG content and contig length. We evaluated the stochasticity of co-localization occurrence using enrichment scores. The most common forms of co-localization involved tetracycline and fluoroquinolone resistance genes, and, on plasmids, co-localization predominantly occurred in the form of class 1 integrons. Antibiotic use caused a short-term increase in mobile ARGs, while non-mobile ARGs showed no significant change. Finally, we found that a high abundance of VGs was associated with low gut microbial maturity and that VGs showed even higher potential for mobility than ARGs. CONCLUSIONS: We found that the phenomenon of co-localization between ARGs and other resistance and VGs was prevalent in the gut at the beginning of life. It reveals the diversity that sustains antibiotic resistance and therefore indirectly emphasizes the need to apply caution in the use of antimicrobial agents in clinical practice, animal husbandry, and daily life to mitigate the escalation of resistance. Video Abstract.

Tension band versus locking plate fixation for patella fractures - a protocol of a randomised controlled trial.

INTRODUCTION: Following surgical management of patella fractures, patients commonly report pain; difficulties with weight-bearing tasks such as walking, running and climbing stairs; and restrictions in quality of life. Recently, a locking plate system for surgical management of patella fractures has been introduced. To date, no studies have compared standard treatment with tension band wiring with locking plate fixation in a randomised study design. We aim to compare the one-year patient-reported Knee Injury and Osteoarthritis Outcome subscale scores (KOOS5-subscales) after standard care tension band fixation with locking plate fixation for patients with patella fractures. METHODS: This is a multicentre randomised and prospective clinical trial. A total of 122 patients will be included in the study, and the primary outcome will be the KOOS subscales at 12 months after surgery. CONCLUSIONS: Findings from the present study are expected to advance our understanding of outcome following surgical treatment of patella fractures. FUNDING: This study is funded, in part, by the Novo Nordisk Foundation, Denmark. CLINICALTRIALS: gov ID: NCT04891549.

Characterizing human postprandial metabolic response using multiway data analysis.

INTRODUCTION: Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time. OBJECTIVES: Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles. METHODS: We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences. RESULTS: Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state. CONCLUSION: The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Predicting Preterm Birth Using Cell-Free Ribonucleic Acid.

Spontaneous preterm birth (sPTB) is a complex and clinically heterogeneous condition that remains incompletely understood, leading to insufficient interventions to effectively prevent it from occurring. Cell-free ribonucleic acid signatures in the maternal circulation have the potential to identify biologically relevant subtypes of sPTB. These could one day be used to predict and prevent sPTB in asymptomatic individuals, and to aid in prognosis and management for individuals presenting with threatened preterm labor and preterm prelabor rupture of membranes.

Variations in the persistence of 5'-end genomic and subgenomic SARS-CoV-2 RNAs in wastewater from aircraft, airports and wastewater treatment plants.

Wastewater sequencing has become a powerful supplement to clinical testing in monitoring SARS-CoV-2 infections in the post-COVID-19 pandemic era. While its applications in measuring the viral burden and main circulating lineages in the community have proved their efficacy, the variations in sequencing quality and coverage across the different regions of the SARS-CoV-2 genome are not well understood. Furthermore, it is unclear how different sample origins, viral extraction and concentration methods and environmental factors impact the reads sequenced from wastewater. Using high-coverage, amplicon-based, paired-end read sequencing of viral RNA extracted from wastewater collected directly from aircraft, pooled from different aircraft and airport buildings or from regular wastewater plants, we assessed the genome coverage across the sample groups with a focus on the 5'-end region covering the leader sequence and investigated whether it was possible to detect subgenomic RNA from viral material recovered from wastewater. We identified distinct patterns in the persistence of the different genomic regions across the different types of wastewaters and the existence of chimeric reads mapping to non-amplified regions. Our findings suggest that preservation of the 5'-end of the genome and the ability to detect subgenomic RNA reads, though highly susceptible to environment and sample processing conditions, may be indicative of the quality and amount of the viral RNA present in wastewater.

Randomised, Placebo-Controlled Investigation of the Impact of Probiotic Consumption on Gut Microbiota Diversity and the Faecal Metabolome in Seniors.

Aging has been associated with a changed composition and function of the gut microbiota (GM). Here, we investigate the effects of the multi-strain probiotic HOWARU® Restore on GM composition and function in seniors. Ninety-eight healthy adult volunteers aged ≥75 years were enrolled in a randomised, double-blinded intervention (NCT02207140), where they received HOWARU Restore (1010 CFU) or the placebo daily for 24 weeks, with 45 volunteers from each group completing the intervention. Questionnaires monitoring the effects on gastro-intestinal discomfort and bowel movements were collected. Faecal samples for GM characterisation (qPCR, 16S rRNA gene amplicon sequencing) and metabolomics (GC-FID, 1H NMR) were collected at the baseline and after 24 weeks. In the probiotic group, self-reported gastro-intestinal discomfort in the form of flatulence was significantly decreased during the intervention. At the baseline, 151 'core species' (present in ≥95% of samples) were identified. Most core species belonged to the Lachnospiraceae and Ruminococcaceae families. Neither alpha diversity nor beta diversity or faecal metabolites was affected by probiotic intake. On the contrary, we observed high intra-individual GM stability, with 'individual' accounting for 72-75% of variation. In conclusion, 24 weeks of HOWARU Restore intake reduced gastro-intestinal discomfort in the form of flatulence in healthy seniors without significantly influencing GM composition or activity.

An Unhealthy Dietary Pattern during Pregnancy is Associated with Neurodevelopmental Disorders in Childhood and Adolescence.

Despite the high prevalence of neurodevelopmental disorders, there are a lack of clinical studies examining the impact of pregnancy diet on child neurodevelopment. This observational clinical study examined the associations between pregnancy dietary patterns and neurodevelopmental diagnoses, as well as their symptoms, in a prospective cohort of 10-year-old children (n=508). Data-driven dietary patterns were derived from self-reported food frequency questionnaires. An Unhealthy dietary pattern in pregnancy (per SD change) was significantly associated with attention deficit hyperactivity disorder (ADHD) OR 1.66 [1.21 - 2.27], p=0.002 and autism diagnosis OR 2.22 [1.33 - 3.74], p=0.002 and associated symptoms p<0.001. Findings for ADHD were validated in two large (n=656, n=348), independent mother-child cohorts via blood metabolome modelling. Objective metabolite scores, assessed at five timepoints in mothers and children in two independent mother-child cohorts, indicated that the strongest association with ADHD was during early-to mid-pregnancy. These results provide evidence for targeted prenatal dietary interventions to prevent neurodevelopmental disorders in children.

Vertical Metabolome Transfer from Mother to Child: An Explainable Machine Learning Method for Detecting Metabolomic Heritability.

Vertical transmission of metabolic constituents from mother to child contributes to the manifestation of disease phenotypes in early life. This study probes the vertical transmission of metabolites from mothers to offspring by utilizing machine learning techniques to differentiate between true mother-child dyads and randomly paired non-dyads. Employing random forests (RF), light gradient boosting machine (LGBM), and logistic regression (Elasticnet) models, we analyzed metabolite concentration discrepancies in mother-child pairs, with maternal plasma sampled at 24 weeks of gestation and children's plasma at 6 months. The propensity of vertical transfer was quantified, reflecting the likelihood of accurate mother-child matching. Our findings were substantiated against an external test set and further verified through statistical tests, while the models were explained using permutation importance and SHapley Additive exPlanations (SHAP). The best model was achieved using RF, while xenobiotics were shown to be highly relevant in transfer. The study reaffirms the transmission of certain metabolites, such as perfluorooctanoic acid (PFOA), but also reveals additional insights into the maternal influence on the child's metabolome. We also discuss the multifaceted nature of vertical transfer. These machine learning-driven insights complement conventional epidemiological findings and offer a novel perspective on using machine learning as a methodology for understanding metabolic interactions.

Effect of colorectal cancer screening on colorectal cancer surgery outcomes: nationwide cohort study.

BACKGROUND: National colorectal cancer screening commenced in Denmark in 2014. Little is known about the effects of organized colorectal cancer screening on intraoperative and postoperative events. The aim of this nationwide cohort study was to evaluate the difference in intraoperative and postoperative outcomes between patients with screen-detected colorectal cancer and non-screen-detected colorectal cancer within the first 90 days after surgery. METHODS: National register data were collected for Danish residents diagnosed with colorectal cancer between January 2014 and March 2018. Outcomes for the two cohorts were reported as relative risk or weighted mean difference. Intraoperative outcomes were blood loss, blood transfusion, tumour perforation, and organ lesion. Postoperative outcomes were complications (surgical and non-surgical) and 90-day mortality. Discrete data estimates were calculated from a general linear model. Analyses were adjusted for potential healthy user bias with respect to sex, age, location of the cancer (colon/rectum), and Charlson co-morbidity index. RESULTS: In total, 10 606 patients were included. Compared with patients in the non-screen-detected colorectal cancer group (4497 patients), patients in the screen-detected colorectal cancer group (6109 patients) had reduced intraoperative blood loss (-52 mL, 95% c.i. -67 to -37, P < 0.001), a shorter duration of hospitalization (-2.3 days, 95% c.i. -2.8 to -1.8, P < 0.001), and reduced rates of intraoperative organ lesion (0.76, 95% c.i. 0.59 to 0.99, P = 0.042), surgical complications (0.79, 95% c.i. 0.73 to 0.87, P < 0.001), non-surgical complications (0.68, 95% c.i. 0.60 to 0.78, P < 0.001), and 90-day mortality (0.29, 95% c.i. 0.21 to 0.39, P < 0.001). CONCLUSION: In comparison with non-screen-detected colorectal cancer, surgery for screen-detected colorectal cancer remains associated with improvement in several intraoperative and early postoperative outcomes after considering healthy user bias.

Analyzing postprandial metabolomics data using multiway models: a simulation study.

BACKGROUND: Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data. RESULTS: We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postprandial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis of fasting-state data using principal component analysis, T0-corrected data (i.e., data corrected by subtracting fasting-state data) using a CP model and full-dynamic (i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased versus healthy groups. CONCLUSIONS: Our experiments show that it is crucial to analyze both fasting-state and T0-corrected data for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models of T0-corrected or full-dynamic data. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.

Metabolic maturation in the infant urine during the first 3 months of life.

The infant urine metabolome provides a body metabolic snapshot, and the sample collection can be done without stressing the fragile infant. 424 infant urine samples from 157 infants were sampled longitudinally at 1-, 2-, and 3 months of age. 49 metabolites were detected using proton nuclear magnetic resonance spectroscopy. Data were analyzed with multi- and univariate statistical methods to detect differences related to infant age-stage, gestational age, mother's pre-pregnancy BMI, C-section, infant birth weight, and infant sex. Significant differences were identified between age-stage (pbonferoni < 0.05) in 30% (15/49) of the detected metabolites. Urine creatinine increased significantly from 1 to 3 months. In addition, myo-inositol, taurine, methionine, and glucose seem to have conserved levels within the individual over time. We calculated a urine metabolic maturation age and found that the metabolic age at 3 months is negatively correlated to weight at 1 year. These results demonstrate that the metabolic maturation can be observed in urine metabolome with implications on infant growth and specifically suggesting that the systematic age effect on creatinine promotes caution in using this as normalization of other urine metabolites.

High-dose vitamin D3 supplementation in pregnancy and risk of neurodevelopmental disorders in the children at age 10: A randomized clinical trial.

BACKGROUND: Vitamin D deficiency in pregnancy may increase the risk of autism and attention deficit hyperactivity disorder (ADHD). OBJECTIVE: The objective of this study was to estimate the effect of vitamin D3 supplementation in pregnancy on risk of autism and ADHD. DESIGN: This randomized clinical trial was part of the COpenhagen Prospective Study on Neuro-PSYCHiatric Development (COPYCH) project nested within the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) cohort comprising a population-based sample of 700 healthy mother-child pairs enrolled at week 24 of pregnancy. Maternal 25-hydroxy-vitamin D (25(OH)D) was measured at inclusion and 623 mothers were randomized 1:1 to either high-dose (2800 IU/d) or standard dose (400 IU/d) vitamin D3 until 1 wk postpartum (315 received high-dose, 308 standard dose). At age 10, diagnoses and symptom load of autism and ADHD, respectively, were established using the Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version. RESULTS: The psychopathologic evaluation was completed by 591 children aged 10 y, and 16 children (2.7%) were diagnosed with autism and 65 (11.0%) with ADHD. Hereof, 496 children participated in the vitamin D3 trial (246 received high-dose, 250 standard dose). Of these, 12 children (2.4%) were diagnosed with autism and 58 (11.7%) with ADHD. Higher maternal preintervention 25(OH)D levels were associated with a decreased risk of autism [odd ratio (OR) per 10 nmol/L: 0.76 (0.59,0.97); P = 0.034], lower autistic symptom load [ß per 10 nmol/L: -0.03 (-0.05,0.00); P = 0.024), and decreased risk of ADHD diagnosis (OR per 10 nmol/L: 0.88 (0.78,0.99); P = 0.033]. High-dose vitamin D3 supplementation was not associated with risk of autism or ADHD. CONCLUSIONS: Higher maternal preintervention 25(OH)D was associated with a decreased risk of autism, lower autistic symptom load, and decreased risk of ADHD diagnosis, but high-dose vitamin D3 supplementation in pregnancy had no effect on risk of autism and ADHD. This trial was registered at clinicaltrials.gov as NCT00856947.

Dimensional profiling of psychopathology in children and adolescents based on the K-SADS-PL and an analysis of the construct validity of two ADHD symptom dimensions.

OBJECTIVES: The traditional view on psychiatric disorders as categorical and distinct is being challenged by perspectives emphasizing the relevance of dimensional and transdiagnostic assessment. However, most diagnostic instruments are based on a categorical view with a threshold-approach to disease classification. METHODS: We here describe algorithms for dimensionalizing the psychopathological ratings of the widely used diagnostic interview for children and adolescents, the Kiddie-Schedule for Affective Disorders and Schizophrenia - Present and Lifetime Version (K-SADS-PL). We further evaluate the criterion-related construct validity of the dimensionalized attention-deficit/hyperactivity disorder (ADHD) scales using Rasch models in a sample of 590 children (mean age 10.29 (.36), 49% girls). RESULTS: The algorithms generate scores of current symptom load, i.e., the sum of clinician-rated symptoms within each disorder assessed with the interview. We found support for counting symptoms of inattention and hyperactivity/impulsivity, respectively, but not for a single combined ADHD scale. CONCLUSIONS: The algorithms constitute an initial step in creating a framework for clinician-rated dimensional analyses of symptoms derived from the K-SADS-PL, but future studies are needed to further evaluate the construct validity of the remaining scales and the reliability and clinical utility of the method. We believe that our proposed algorithms offer a novel method of dimensional psychopathological assessment, which can be applied in multiple branches of child and adolescent psychiatry.

The infant gut virome is associated with preschool asthma risk independently of bacteria.

Bacteriophage (also known as phage) communities that inhabit the gut have a major effect on the structure and functioning of bacterial populations, but their roles and association with health and disease in early life remain unknown. Here, we analyze the gut virome of 647 children aged 1 year from the Copenhagen Prospective Studies on Asthma in Childhood2010 (COPSAC2010) mother-child cohort, all deeply phenotyped from birth and with longitudinally assessed asthma diagnoses. Specific temperate gut phage taxa were found to be associated with later development of asthma. In particular, the joint abundances of 19 caudoviral families were found to significantly contribute to this association. Combining the asthma-associated virome and bacteriome signatures had additive effects on asthma risk, implying an independent virome-asthma association. Moreover, the virome-associated asthma risk was modulated by the host TLR9 rs187084 gene variant, suggesting a direct interaction between phages and the host immune system. Further studies will elucidate whether phages, alongside bacteria and host genetics, can be used as preclinical biomarkers for asthma.

Differential responses of the gut microbiome and resistome to antibiotic exposures in infants and adults.

Despite their crucial importance for human health, there is still relatively limited knowledge on how the gut resistome changes or responds to antibiotic treatment across ages, especially in the latter case. Here, we use fecal metagenomic data from 662 Danish infants and 217 young adults to fill this gap. The gut resistomes are characterized by a bimodal distribution driven by E. coli composition. The typical profile of the gut resistome differs significantly between adults and infants, with the latter distinguished by higher gene and plasmid abundances. However, the predominant antibiotic resistance genes (ARGs) are the same. Antibiotic treatment reduces bacterial diversity and increased ARG and plasmid abundances in both cohorts, especially core ARGs. The effects of antibiotic treatments on the gut microbiome last longer in adults than in infants, and different antibiotics are associated with distinct impacts. Overall, this study broadens our current understanding of gut resistome dynamics and the impact of antibiotic treatment across age groups.

A chemical structure and machine learning approach to assess the potential bioactivity of endogenous metabolites and their association with early-childhood hs-CRP levels.

Metabolomics has gained much attraction due to its potential to reveal molecular disease mechanisms and present viable biomarkers. In this work we used a panel of untargeted serum metabolomes in 602 childhood patients of the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 493 chemical compounds curated using automated procedures. Using predicted quantitative-structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines, we created a filtering method for the vast number of quantified metabolites. The metabolites measured in children's serums used here have predicted potential against the chosen target modelled targets. The targets from Tox21 have been used with quantitative structure-activity relationships (QSARs) and were trained for ~7000 structures, saved as models, and then applied to 493 metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation. The significant metabolites were reported.

Fungi and bacteria in the beds of rural and urban infants correlate with later risk of atopic diseases.

INTRODUCTION: Rural children have a lower risk of asthma and atopic diseases than urban children. However, whether indoor microbiota in non-farming rural homes provides protection is unclear. METHODS: Here, we examine if microbes in the beds of rural and urban infants are associated with later development of atopic diseases. We studied fungi and bacteria in the beds of 6-month-old infants (n = 514) in association with the risk of asthma, allergic rhinitis, eczema and aeroallergen sensitization at 6 years of age in the prospective COPSAC2010 cohort. RESULTS: Both fungal and bacterial diversity were lower in the beds of children, who later developed allergic rhinitis (-0.22 [-0.43,-0.01], padj = .04 and -.24 [-0.42,-0.05], padj = .01 respectively) and lower bacterial richness was discovered in beds of children later developing asthma (-41.34 [-76.95,-5.73], padj = .02) or allergic rhinitis (-45.65 [-81.19,-10.10], padj = .01). Interestingly, higher fungal diversity and richness were discovered in the beds of children developing eczema (0.23 [0.02,0.43], padj = .03 and 29.21 [1.59,56.83], padj = .04 respectively). We defined a limited set of fungal and bacterial genera that predicted rural/urban environment. Some rural-associated bacterial genera such as Romboutsia and Bacillus and fungal genera Spegazzinia and Physcia were also associated with reduced risk of diseases, including eczema. These fungal and bacterial fingerprints predicting the living environment were associated with asthma and allergic rhinitis, but not eczema, with rural compositions being protective. The bed dust bacteria mediated 27% of the protective association of a rural living environment for allergic rhinitis (p = .04). CONCLUSIONS: Bed dust microbes can be differentially associated with airway- and skin-related diseases. The differing bed dust microbiota between rural and urban infants may influence their later risk of asthma and allergic rhinitis.