Microbiota signatures in type-2 diabetic patients with chronic kidney disease - A Pilot Study

The human microbiota is paramount for normal host physiology. Altered host-microbiome interactions are part of the pathogenesis of numerous common ailments. Currently, much emphasis is placed on the involvement of the microbiome in the pathogenesis of type-2 diabetes mellitus (T2DM), impaired glucose tolerance, and other metabolic disorders (i.e. obesity). Several studies found highly significant correlations of specific intestinal bacteria with T2DM. A better understanding of the role of the microbiome in diabetes and its complications might provide new insights in the development of new therapeutic principles. Our pilot study investigates the microbiota patterns in Romanian type-2 diabetic patients with diabetic kidney disease. Fecal samples were collected from type 2-diabetic patients and healthy controls and further used for bacterial DNA isolation. Using 16 rDNA qRT-PCR, we analyzed phyla abundance (Bacteroidetes, Firmicutes) as well as the relative abundance of specific bacterial groups (Lactobacillus sp., Enterobacteriaceae, Ruminococus sp., Prevotella sp., Faecalibacterium sp., Clostridium coccoides, Clostridium leptum). Our study also investigates the diabetic fungal microbiome for the first time. Furthermore, we report significant correlations between the treatment regimen and microbiota composition in diabetic nephropathy

New HARPS and FEROS observations of GJ1046

In this paper we present new precise Doppler data of GJ1046 taken between November 2005 and July 2018 with the HARPS and the FEROS high-resolution spectographs. In addition, we provide a new stellar mass estimate of GJ1046 and we update the orbital parameters of the GJ1046 system. These new data and analysis could be used together with the GAIA epoch astrometry, when available, for braking the $\sin i$ degeneracy and revealing the true mass of the GJ1046 system.Comment: 2 pages, 1 figure, 1 table with RV data (available only in the Astro-PH version of the paper), Accepted by RNAA

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5–40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8

The microaerophilic microbiota of de-novo paediatric inflammatory bowel disease: the BISCUIT study

<p>Introduction: Children presenting for the first time with inflammatory bowel disease (IBD) offer a unique opportunity to study aetiological agents before the confounders of treatment. Microaerophilic bacteria can exploit the ecological niche of the intestinal epithelium; Helicobacter and Campylobacter are previously implicated in IBD pathogenesis. We set out to study these and other microaerophilic bacteria in de-novo paediatric IBD.</p> <p>Patients and Methods: 100 children undergoing colonoscopy were recruited including 44 treatment naïve de-novo IBD patients and 42 with normal colons. Colonic biopsies were subjected to microaerophilic culture with Gram-negative isolates then identified by sequencing. Biopsies were also PCR screened for the specific microaerophilic bacterial groups: Helicobacteraceae, Campylobacteraceae and Sutterella wadsworthensis.</p> <p>Results: 129 Gram-negative microaerophilic bacterial isolates were identified from 10 genera. The most frequently cultured was S. wadsworthensis (32 distinct isolates). Unusual Campylobacter were isolated from 8 subjects (including 3 C. concisus, 1 C. curvus, 1 C. lari, 1 C. rectus, 3 C. showae). No Helicobacter were cultured. When comparing IBD vs. normal colon control by PCR the prevalence figures were not significantly different (Helicobacter 11% vs. 12%, p = 1.00; Campylobacter 75% vs. 76%, p = 1.00; S. wadsworthensis 82% vs. 71%, p = 0.312).</p> <p>Conclusions: This study offers a comprehensive overview of the microaerophilic microbiota of the paediatric colon including at IBD onset. Campylobacter appear to be surprisingly common, are not more strongly associated with IBD and can be isolated from around 8% of paediatric colonic biopsies. S. wadsworthensis appears to be a common commensal. Helicobacter species are relatively rare in the paediatric colon.</p&gt

Cell-free DNA mutations as biomarkers in breast cancer patients receiving tamoxifen

The aim was to identify mutations in serum cell-free DNA (cfDNA) associated with disease progression on tamoxifen treatment in metastatic breast cancer (MBC). Sera available at start of therapy, during therapy and at disease progression were selected from 10 estrogen receptor (ER)-positive breast cancer patients. DNA from primary tumor and normal tissue and cfDNA from minute amounts of sera were analyzed by targeted next generation sequencing (NGS) of 45 genes (1,242 exons). At disease progression, stop-gain single nucleotide variants (SNVs) for CREBBP (1 patient) and SMAD4 (1 patient) and non-synonymous SNVs for AKAP9 (1 patient), PIK3CA (2 patients) and TP53 (2 patients) were found. Mutations in CREBBP and SMAD4 have only been occasionally reported in breast cancer. All mutations, except for AKAP9, were also present in the primary tumor but not detected in all blood specimens preceding progression. More sensitive detection by deeper re-sequencing and digital PCR confirmed the occurrence of circulating tumor DNA (ctDNA) and these biomarkers in blood specimens

Reply to: New Meta- and Mega-analyses of Magnetic Resonance Imaging Findings in Schizophrenia: Do They Really Increase Our Knowledge About the Nature of the Disease Process?

This work was supported by National Institute of Biomedical Imaging and Bioengineering Grant No. U54EB020403 (to the ENIGMA consortium)