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Abstract Background Antimicrobial autoantigenic glycoprotein 2 (GP2) is an important component of the innate immune system which originates from the exocrine pancreas as well as from the small intestines. The relationship of GP2 with the intestinal microbiome as well as the systemic implications of increased fecal GP2 levels are, however, still unclear. Therefore, fecal samples from 2,812 individuals of the Study of Health in Pomerania (SHIP) were collected to determine GP2 levels (enzyme-linked immunosorbent assay) and gut microbiota profiles (16 S rRNA gene sequencing). These data were correlated and associated with highly standardised and comprehensive phenotypic data of the study participants. Results Fecal GP2 levels were increased in individuals with higher body mass index and smokers, whereas lower levels were found in case of preserved exocrine pancreatic function, female sex or a healthier diet. Moreover, higher GP2 levels were associated with increased serum levels of high-sensitivity C-reactive protein, loss of gut microbial diversity and an increase of potentially detrimental bacteria (Streptococcus, Haemophilus, Clostridium XIVa, or Collinsella). At the same time, predicted microbial pathways for the biosynthesis of beneficial short-chain fatty acids or lactic acid were depleted in individuals with high fecal GP2. Of note, GP2 exhibited a stronger association to overall microbiome variation than calprotectin. Conclusion Fecal GP2 is a biomarker of gut microbiota dysbiosis and associated with increased systemic inflammation. The intestines may be more important as origin for GP2 than pancreatic acinar cells. Future studies need to investigate the potential clinical value in disease specific patient cohorts.

Abstract Background Biomedical and lifestyle factors in Western populations have significantly shifted in recent decades, influencing public health and contributing to the increasing prevalence of non-communicable diseases (NCDs) that share inflammation as common pathology. Methods We investigated the relationship between these factors and 11 NCDs in the cross-sectional FoCus cohort (n = 1220), using logistic regression models. Associations with age-at-disease-onset were specifically analyzed for type 2 diabetes (T2D, low-grade chronic inflammation) and inflammatory bowel disease (IBD, high-grade chronic inflammation) in disease-specific cohorts (FoCus-T2D, n = 514; IBD-KC, n = 1110). Important factors for disease risk were identified using Cox-PH-regression models and time-to-event analysis. We further explored the interaction between identified risk factors and gut microbiome composition using linear models. Results Lifestyle factors were clearly linked to disease phenotypes, particularly in T2D and IBD. Still, some factors affected only the age-at-onset, but not disease prevalence. High-quality nutrition significantly delayed onset for both IBD and T2D (IBD: HR = 0.81 [0.66; 0.98]; T2D: HR = 0.45 [0.28; 0.72]). Smoking accelerated T2D onset (HR = 1.82 [1.25; 2.65]) but delayed onset in ulcerative colitis (UC: HR = 0.47 [0.28; 0.79]). Higher microbiota diversity delayed IBD onset (Shannon: HR = 0.58 [0.49; 0.71]) but had no effect on T2D. The abundance of specific microbial genera was strongly associated with various biomedical and lifestyle factors in T2D and IBD. In unaffected controls, these effects were smaller or reversed, potentially indicating a greater susceptibility of the gut microbiome to negative influences in T2D and IBD. Conclusions The dual insights into age-at-disease-onset and gut microbiota composition in disease emphasize the role of certain biomedical and lifestyle factors, e.g., nutrition quality, in disease prevention and management. Understanding these relationships provides a foundation for developing targeted strategies to mitigate the impact of metabolic and inflammatory diseases through lifestyle modifications and gut health management.

Kell is one of the most complex blood group systems, with a highly polymorphic genetic background. Extensive allelic variations in the KEL gene affect the encoded erythrocyte surface protein Kell. Genetic variants causing aberrant splicing, premature termination of protein translation, or specific amino acid exchanges lead to a variety of different phenotypes with altered Kell expression levels or changes in the antigenic properties of the Kell protein. Using an in silico structural model of the Kell protein, we analyzed the biophysical and structural context of all full-length Kell variants of known phenotype. The results provided insights regarding the 3D co-localization of antigenic Kell variants and led us to suggest several conformational epitopes on the Kell protein surface. We found a number of correlations between the properties of individual genetic variants in the Kell protein and their respective serological phenotypes, which we used as a search filter to predict potentially new immunogenic Kell variants from an in-house whole exome sequencing dataset of 19,772 exomes. Our analysis workflow and results aid blood group serologists in predicting whether a newly identified Kell genetic variant may result in a specific phenotype.

Introduction: Clara cell 16-kDa protein (CC16) is an anti-inflammatory, immunomodulatory secreted pulmonary protein with reduced serum concentrations in obesity according to recent data. Objective: Studies focused solely on bodyweight, which does not properly reflect obesity-associated implications of the metabolic and reno-cardio-vascular system. The purpose of this study was therefore to examine CC16 in a broad physiological context considering cardio-metabolic comorbidities of primary pulmonary diseases. Methods: CC16 was quantified in serum samples in a subset of the FoCus (N = 497) and two weight loss intervention cohorts (N = 99) using ELISA. Correlation and general linear regression analyses were applied to assess CC16 effects of lifestyle, gut microbiota, disease occurrence and treatment strategies. Importance and intercorrelation of determinants were validated using random forest algorithms. Results: CC16 A38G gene mutation, smoking and low microbial diversity significantly decreased CC16. Pre-menopausal female displayed lower CC16 compared to post-menopausal female and male participants. Biological age and uricosuric medications increased CC16 (all p

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

BackgroundDevelopment of pancreatic necroses or pseudocysts are typical complications of pancreatitis and may require endoscopic drainage therapy using metal or plastic stents. Microbial infection of these lesions poses a major challenge. So far, the composition and significance of the microbial colonization on drainage stents are largely unknown although it may impact outcomes during endoscopic drainage therapy.MethodsA total of 26 stents used for drainage of pancreatic lesions were retrieved and the stent microbiome was determined by 16S rRNA gene sequencing. Additional analysis included comparison of the stent microbiome to the intracavitary necrosis microbiome as well as scanning electron microscopy (SEM) and micro-computed tomography (μCT) imaging of selected metal or plastic stents.ResultsThe stent microbiome comprises a large proportion of opportunistic enteric pathogens such as Enterococcus (14.4%) or Escherichia (6.1%) as well as oral bacteria like Streptococcus (13.1%). Increased levels of opportunistic enteric pathogens were associated with a prolonged hospital stay (r = 0.77, p = 3e−06) and the occurrence of adverse events during drainage therapy (p = 0.011). Higher levels of oral bacteria were associated (r = −0.62, p = 8e-04) with shorter durations of inpatient treatment. SEM and μCT investigations revealed complex biofilm networks on the stent surface.ConclusionThe composition of the stent microbiome is associated with prolonged hospital stays and adverse events during endoscopic drainage therapy, highlighting the need for effective infection control to improve patient outcomes. In addition to systemic antibiotic therapy, antimicrobial stent coatings could be a conceivable option to influence the stent microbiome and possibly enhance control of the necrotic microflora.

Background/Objectives: Metered-dose inhalers (MDIs) and dry powder inhalers (DPIs) are common inhaled corticosteroid (ICS) inhaler devices. The difference in formulation and administration technique of these devices may influence oral cavity microbiota composition. We aimed to compare the saliva microbiome in children with moderate-to-severe asthma using ICS via MDIs versus DPIs. Methods: Saliva samples collected from 143 children (6–17 yrs) with moderate-to-severe asthma across four European countries (The Netherlands, Germany, Spain, and Slovenia) as part of the SysPharmPediA cohort were subjected to 16S rRNA sequencing. The microbiome was compared using global diversity (α and β) between two groups of participants based on inhaler devices (MDI (n = 77) and DPI (n = 65)), and differential abundance was compared using the Analysis of Compositions of Microbiomes with the Bias Correction (ANCOM-BC) method. Results: No significant difference was observed in α-diversity between the two groups. However, β-diversity analysis revealed significant differences between groups using both Bray–Curtis and weighted UniFrac methods (adjusted p-value = 0.015 and 0.044, respectively). Significant differential abundance between groups, with higher relative abundance in the MDI group compared to the DPI group, was detected at the family level [Carnobacteriaceae (adjusted p = 0.033)] and at the genus level [Granulicatella (adjusted p = 0.021) and Aggregatibacter (adjusted p = 0.011)]. Conclusions: Types of ICS devices are associated with different saliva microbiome compositions in moderate-to-severe pediatric asthma. The causal relation between inhaler types and changes in saliva microbiota composition needs to be further evaluated, as well as whether this leads to different potential adverse effects in terms of occurrence and level of severity.

Abstract Via 16S rRNA gene amplicon sequencing, this study explores whether the gut mucus microbiota of rainbow trout is affected by the interaction of a plant-protein-based diet and a daily handling stressor (chasing with a fishing net) across two genetic lines (A, B). Initial body weights of fish from lines A and B were 124.7 g and 147.2 g, respectively. Fish were fed 1.5% of body weight per day for 59 days either of two experimental diets, differing in their fish meal [fishmeal-based diet (F): 35%, plant-based diet (V): 7%] and plant-based protein content (diet F: 47%, diet V: 73%). No diet- or stress-related effect on fish performance was observed at the end of the trial. However, we found significantly increased observed ASVs in the intestinal mucus of fish fed diet F compared to diet V. No significant differences in Shannon diversity could be observed between treatments. The autochthonous microbiota in fish fed with diet V was dominated by representatives of the genera Mycoplasma, Cetobacterium, and Ruminococcaceae, whereas Enterobacteriaceae and Photobacterium were significantly associated with diet F. The mucus bacteria in both genetic lines were significantly separated by diet, but neither by stress nor an interaction, as obtained via PERMANOVA. However, pairwise comparisons revealed that the diet effect was only significant in stressed fish. Therefore, our findings indicate that the mucus-associated microbiota is primarily modulated by the protein source, but this modulation is mediated by the stress status of the fish.

Abstract High-throughput sequencing allowed the discovery of many disease variants, but nowadays it is becoming clear that the abundance of genomics data mostly just moved the bottleneck in Genetics and Precision Medicine from a data availability issue to a data interpretation issue. To solve this empasse it would be beneficial to apply the latest Deep Learning (DL) methods to the Genome Interpretation (GI) problem, similarly to what AlphaFold did for Structural Biology. Unfortunately DL requires large datasets to be viable, and aggregating genomics datasets poses several legal, ethical and infrastructural complications. Federated Learning (FL) is a Machine Learning (ML) paradigm designed to tackle these issues. It allows ML methods to be collaboratively trained and tested on collections of physically separate datasets, without requiring the actual centralization of sensitive data. FL could thus be key to enable DL applications to GI on sufficiently large genomics data. We propose FedCrohn, a FL GI Neural Network model for the exome-based Crohn’s Disease risk prediction, providing a proof-of-concept that FL is a viable paradigm to build novel ML GI approaches. We benchmark it in several realistic scenarios, showing that FL can indeed provide performances similar to conventional ML on centralized data, and that collaborating in FL initiatives is likely beneficial for most of the medical centers participating in them.

Periodontitis is associated with systemic chronic inflammatory diseases. There is limited evidence on the influence of anti-cytokine therapies on the periodontal condition and microbiome in the tooth pocket of such patients, so the aim of this study was to elucidate this issue. In this observational trial, the periodontal status and the gingival crevicular fluid of 13 patients with different chronic inflammatory diseases were obtained before the initiation of anti-cytokine treatment and 14 weeks after. Gingival crevicular fluid was collected for 16S rRNA gene sequencing from a clinically healthy tooth and the deepest measured pocket. The Shannon Diversity Index significantly increased in the deepest pockets of patients (p = 0.039). The data showed alterations in the diversity of the subgingival microbiome over the course of the study, implying a shift towards a healthier condition after starting anti-cytokine therapy. Additional investigations are needed to analyze whether the administration of selective biologicals can improve periodontal conditions in patients with or without chronic inflammatory diseases.

Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Abstract Gut microbiota metabolites have been mechanistically linked to inflammatory pathway activation and atherosclerosis, which are major causes of vascular stiffness (VS). Aiming to investigate if the gut microbiome might be involved in VS development, we performed a cross-sectional study (n = 3,087), nested within the population-based European Prospective Investigations into Cancer and Nutrition (EPIC) Potsdam. We investigated the correlation of the gut microbiota (alpha diversity and taxa abundance) with 3 vascular stiffness measures: carotid-femoral (PWV), aortic augmentation index (AIX) and ankle-brachial index (ABI). Shannon index was not significantly associated with VS but the number of observed Amplicon Sequence Variants (ASV) was positively associated with PWV and AIX. We found a total of 19 ASVs significantly associated with at least one VS measure in multivariable-adjusted models. One ASV (classified as Sutterella wadsworthensis) was associated with 2 VS measures, AIX (− 0.11 ± 0.04) and PWV (-0.14 ± 0.03). Other examples of ASVs associated with VS were Collinsella aerofaciens, previously reported to be affected by diet and Bacteroides uniformis, commercially available as probiotics. In conclusion, our study suggests a potential role of individual components of the gut microbiota in the aetiology of VS.

Summary: Background: Chronic inflammatory diseases (CIDs) are systems disorders that affect diverse organs including the intestine, joints and skin. The essential amino acid tryptophan (Trp) can be broken down to various bioactive derivatives important for immune regulation. Increased Trp catabolism has been observed in some CIDs, so we aimed to characterise the specificity and extent of Trp degradation as a systems phenomenon across CIDs. Methods: We used high performance liquid chromatography and targeted mass spectrometry to assess the serum and stool levels of Trp and Trp derivatives. Our retrospective study incorporates both cross-sectional and longitudinal components, as we have included a healthy population as a reference and there are also multiple observations per patient over time. Findings: We found reduced serum Trp levels across the majority of CIDs, and a prevailing negative relationship between Trp and systemic inflammatory marker C-reactive protein (CRP). Notably, serum Trp was low in several CIDs even in the absence of measurable systemic inflammation. Increases in the kynurenine-to-Trp ratio (Kyn:Trp) suggest that these changes result from increased degradation along the kynurenine pathway. Interpretation: Increases in Kyn:Trp indicate the kynurenine pathway as a major route for CID-related Trp metabolism disruption and the specificity of the network changes indicates excessive Trp degradation relative to other proteogenic amino acids. Our results suggest that increased Trp catabolism is a common metabolic occurrence in CIDs that may directly affect systemic immunity. Funding: This work was supported by the DFG Cluster of Excellence 2167 “Precision medicine in chronic inflammation” (KA, SSchr, PR, BH, SWa), the BMBF (e:Med Juniorverbund “Try-IBD” 01ZX1915A and 01ZX2215, the e:Med Network iTREAT 01ZX2202A, and GUIDE-IBD 031L0188A), EKFS (2020_EKCS.11, KA), DFG RU5042 (PR, KA), and Innovative Medicines Initiative 2 Joint Undertakings (“Taxonomy, Treatments, Targets and Remission”, 831434, “ImmUniverse”, 853995, “BIOMAP”, 821511).

ABSTRACTWhile numerous health-beneficial interactions between host and microbiota have been identified, there is still a lack of targeted approaches for modulating these interactions. Thus, we here identify precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In the first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we use metabolic modeling to identify precision prebiotics for a two-member Caenorhabditis elegans microbiome community comprising the immune-protective target species Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. We experimentally confirm four of the predicted precision prebiotics, L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid, to specifically increase the abundance of MYb11. L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.IMPORTANCEWhile various mechanisms through which the microbiome influences disease processes in the host have been identified, there are still only few approaches that allow for targeted manipulation of microbiome composition as a first step toward microbiome-based therapies. Here, we propose the concept of precision prebiotics that allow to boost the abundance of already resident health-beneficial microbial species in a microbiome. We present a constraint-based modeling pipeline to predict precision prebiotics for a minimal microbial community in the worm Caenorhabditis elegans comprising the host-beneficial Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71 with the aim to boost the growth of MYb11. Experimentally testing four of the predicted precision prebiotics, we confirm that they are specifically able to increase the abundance of MYb11 in vitro and in vivo. These results demonstrate that constraint-based modeling could be an important tool for the development of targeted microbiome-based therapies against human diseases.

Background & Aims: Genetic and microbiome studies across patients with primary sclerosing cholangitis (PSC) and ulcerative colitis (UC) have indicated that UC in PSC is a separate disease entity to primary UC, but expression studies for PSC are lacking. Methods: We conducted whole blood RNA sequencing experiments for 495 patients with UC, 220 patients with PSC (including 177 with UC), and 320 healthy controls from Germany and Norway. Differential expression analyses, gene ontology and coexpression analyses and random forest machine learning were performed to identify genes, ontologies and transcriptional features that discriminate diagnoses. Results: The blood transcriptome in UC and PSC is dominated by neutrophil activation genes (e.g. S100A12). In UC, but not in PSC (neither PSC alone nor patients with an additional diagnosis of UC [PSC/UC]), ribosomal, mitochondrial, and energy metabolism genes are upregulated in conjunction with antibody transcript expression (MZB1, IGJ). In PSC, there is an increase in modules related to apoptosis and expression of genes of interferon-I-related ontologies. Random forest analysis could poorly discriminate PSC alone from PSC/UC (AUROC 0.56), but could discriminate PSC, UC, and controls with high accuracy (AUROC UC vs. controls 0.95, PSC vs. controls 0.88, UC vs. PSC 0.986). The main coexpression modules relevant for distinguishing PSC, UC, and controls are enriched in neutrophil degranulation and antibody production genes. Conclusions: Supported by machine learning results, PSC and UC appear to be separate entities on a molecular level, while PSC/UC and PSC are indistinguishable. Impact and implications: Clinical and genetic studies suggest that the colitis-like symptoms in primary sclerosing cholangitis (PSC) represent a different disease entity from primary ulcerative colitis (UC). The present study supports this assumption with transcriptomic data from whole blood and describes notable differences in gene expression between primary UC and PSC, providing insights into the still unclear pathophysiology of both diseases. These findings are of interest to scientists seeking to decipher the molecular pathophysiology of both diseases and provide evidence that a redefinition of the PSC-UC phenotype should be considered. The study practically supports future molecular research by providing a large transcriptomic whole blood reference cohort.

Metaorganism research contributes substantially to our understanding of the interaction between microbes and their hosts, as well as their co-evolution. Most research is currently focused on the bacterial community, while archaea often remain at the sidelines of metaorganism-related research. Here, we describe the archaeome of a total of eleven classical and emerging multicellular model organisms across the phylogenetic tree of life. To determine the microbial community composition of each host, we utilized a combination of archaea and bacteria-specific 16S rRNA gene amplicons. Members of the two prokaryotic domains were described regarding their community composition, diversity, and richness in each multicellular host. Moreover, association with specific hosts and possible interaction partners between the bacterial and archaeal communities were determined for the marine models. Our data show that the archaeome in marine hosts predominantly consists of Nitrosopumilaceae and Nanoarchaeota, which represent keystone taxa among the porifera. The presence of an archaeome in the terrestrial hosts varies substantially. With respect to abundant archaeal taxa, they harbor a higher proportion of methanoarchaea over the aquatic environment. We find that the archaeal community is much less diverse than its bacterial counterpart. Archaeal amplicon sequence variants are usually host-specific, suggesting adaptation through co-evolution with the host. While bacterial richness was higher in the aquatic than the terrestrial hosts, a significant difference in diversity and richness between these groups could not be observed in the archaeal dataset. Our data show a large proportion of unclassifiable archaeal taxa, highlighting the need for improved cultivation efforts and expanded databases.

Abstract Mutations in thyroid hormone receptor α1 (TRα1) cause Resistance to Thyroid Hormone α (RTHα), a disorder characterized by hypothyroidism in TRα1-expressing tissues including the heart. Surprisingly, we report that treatment of RTHα patients with thyroxine to overcome tissue hormone resistance does not elevate their heart rate. Cardiac telemetry in male, TRα1 mutant, mice indicates that such persistent bradycardia is caused by an intrinsic cardiac defect and not due to altered autonomic control. Transcriptomic analyses show preserved, thyroid hormone (T3)-dependent upregulation of pacemaker channels (Hcn2, Hcn4), but irreversibly reduced expression of several ion channel genes controlling heart rate. Exposure of TRα1 mutant male mice to higher maternal T3 concentrations in utero, restores altered expression and DNA methylation of ion channels, including Ryr2. Our findings indicate that target genes other than Hcn2 and Hcn4 mediate T3-induced tachycardia and suggest that treatment of RTHα patients with thyroxine in high dosage without concomitant tachycardia, is possible.

Abstract Background The aim of the present study was to characterize the effects of handling stress on the microbiota in the intestinal gut contents of rainbow trout (Oncorhynchus mykiss) fed a plant-based diet from two different breeding lines (initial body weights: A: 124.69 g, B: 147.24 g). Diets were formulated in accordance with commercial trout diets differing in their respective protein sources: fishmeal (35% in fishmeal-based diet F, 7% in plant protein-based diet V) and plant-based proteins (47% in diet F, 73% in diet V). Experimental diets were provided for 59 days to all female trout in two separate recirculating aquaculture systems (RASs; mean temperature: A: 15.17 °C ± 0.44, B: 15.42 °C ± 0.38). Half of the fish in each RAS were chased with a fishing net twice per day to induce long-term stress (Group 1), while the other half were not exposed to stress (Group 0). Results No differences in performance parameters were found between the treatment groups. By using 16S rRNA amplicon sequencing of the hypervariable region V3/V4, we examined the microbial community in the whole intestinal content of fish at the end of the trial. We discovered no significant differences in alpha diversity induced by diet or stress within either genetic trout line. However, the microbial composition was significantly driven by the interaction of stress and diet in trout line A. Otherwise, in trout line B, the main factor was stress. The communities of both breeding lines were predominantly colonized by bacteria from the phyla Fusobacteriota, Firmicutes, Proteobacteria, Actinobacteriota, and Bacteroidota. The most varying and abundant taxa were Firmicutes and Fusobacteriota, whereas at the genus level, Cetobacterium and Mycoplasma were key components in terms of adaptation. In trout line A, Cetobacterium abundance was affected by factor stress, and in trout line B, it was affected by the factor diet. Conclusion We conclude that microbial gut composition, but neither microbial diversity nor fish performance, is highly influenced by stress handling, which also interacts with dietary protein sources. This influence varies between different genetic trout lines and depends on the fish’s life history.

Abstract Background Studies on DNA methylation (DNAm) in Alzheimer’s disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression. Methods Here, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n = 337). Results We identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case–control status or Braak’s tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed “epigenetic clock” estimators we found a significant association with accelerated epigenetic aging in the brains of AD patients vs. controls. Conclusion In summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression.

BackgroundThe gut microbiome plays a crucial role in the pathogenesis and progression of inflammatory bowel disease (IBD). Understanding the dynamics of the gut microbiome in relation to treatment can provide valuable insights into disease management and therapy strategies. The aim of this study is to investigate if diversity and composition of the gut microbiome correlate with time since treatment and disease activity during maintenance infliximab (IFX) therapy among children with IBD.MethodsData was collected from IBD patients aged 10-17 participating in an IFX-eHealth study. IFX infusions were administered in 4-12-week intervals based on weekly faecal calprotectin (FC) combined with symptom scores. Excess stool samples underwent microbiome profiling using 16S rRNA gene sequencing. Microbiome features, including alpha diversity and single taxa, were analysed for three key variables: 1) weeks-since-treatment, 2) FC, and 3) symptom score.ResultsFrom 25 patients (median age 14.4 years) diagnosed with Crohn´s Disease (n = 16) or ulcerative colitis (n = 9), microbiota were analysed in 671 faecal samples collected across 15 treatment intervals. A significant decrease over time in Shannon diversity, following the initial increase within four weeks of treatment, was found across patients. FC levels showed no association with alpha diversity (p>0.1), while symptom scores showed a negative association with Shannon and observed diversity in patients with UC. At the genus level, a lower abundance of the genera Anaerostipes and Fusicatenibacter (Firmicutes), and a greater abundance of the genus Parasutterella (Proteobacteria), were associated (p.adjConclusionsWe found a recurring reduction over time in alpha diversity following the initial increase in diversity after an IFX infusion. Changes in an individual's microbiome may be an early sign of increasing disease activity that precedes clinical symptoms and increased FC.

The genetic basis of primary sclerosing cholangitis has only been partially uncovered. Here, the authors perform a multitrait genome-wide association study to provide insight into the genetic etiology of primary sclerosing cholangitis risk and possible therapeutic drug targets.

Abstract Background Bacterial and viral infections may cause or exacerbate various human diseases and to detect microbes in tissue, one method of choice is RNA sequencing. The detection of specific microbes using RNA sequencing offers good sensitivity and specificity, but untargeted approaches suffer from high false positive rates and a lack of sensitivity for lowly abundant organisms. Results We introduce Pathonoia, an algorithm that detects viruses and bacteria in RNA sequencing data with high precision and recall. Pathonoia first applies an established k-mer based method for species identification and then aggregates this evidence over all reads in a sample. In addition, we provide an easy-to-use analysis framework that highlights potential microbe-host interactions by correlating the microbial to the host gene expression. Pathonoia outperforms state-of-the-art methods in microbial detection specificity, both on in silico and real datasets. Conclusion Two case studies in human liver and brain show how Pathonoia can support novel hypotheses on microbial infection exacerbating disease. The Python package for Pathonoia sample analysis and a guided analysis Jupyter notebook for bulk RNAseq datasets are available on GitHub.

Abstract Background Characterization of clinical phenotypes in context with tumor and host genomic information can aid in the development of more effective and less toxic risk-adapted and targeted treatment strategies. To analyze the impact of therapy-related hyperbilirubinemia on treatment outcome and to identify contributing genetic risk factors of this well-recognized adverse effect we evaluated serum bilirubin levels in 1547 pediatric patients with acute lymphoblastic leukemia (ALL) and conducted a genome-wide association study (GWAS). Patients and methods Patients were treated in multicenter trial AIEOP-BFM ALL 2000 for pediatric ALL. Bilirubin toxicity was graded 0 to 4 according to the Common Toxicity Criteria (CTC) of the National Cancer Institute. In the GWAS discovery cohort, including 650 of the 1547 individuals, genotype frequencies of 745,895 single nucleotide variants were compared between 435 patients with hyperbilirubinemia (CTC grades 1-4) during induction/consolidation treatment and 215 patients without it (grade 0). Replication analyses included 224 patients from the same trial. Results Compared to patients with no (grade 0) or moderate hyperbilirubinemia (grades 1-2) during induction/consolidation, patients with grades 3-4 had a poorer 5-year event free survival (76.6 ± 3% versus 87.7 ± 1% for grades 1-2, P = 0.003; 85.2 ± 2% for grade 0, P

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

DNA methyltransferase 3 A (DNMT3A) is involved in DNA methylation, and genetic variants in the DNMT3 locus have been associated with inflammatory bowel disease. Here the authors report that DNMT3A controls intestinal epithelial barrier function and restoration of the gut barrier function after intestinal epithelial perturbation.

Microbiome composition is influenced by genetics, although the specific host genetic factors responsible are not well known. Here, the authors performed a genome-wide meta-analysis to discover host genetic effects on skin microbiota and finding potential causal effects of microbiota composition on skin diseases.

This study presents a large-scale analysis of microbial diversity in deep-sea sponges. They show that sponge microbial abundance status, geographic distance, sponge phylogeny and the physical-biogeochemical environment drive microbiome composition, in descending order of relevance. The uniqueness of each deep-sea sponge ground stresses the need for their strategic preservation.

Inflammatory Bowel Disease (IBD) affects approximately 0.3% of the global population, with incidence rates rising dramatically worldwide. Emerging evidence points to an interplay between exposome factors such as diet and gut microbiota, host genetics, and the immune system as crucial elements in IBD development. ATP-binding cassette (ABC) transporters, including human p-glycoprotein encoded by the Abcb1 gene, influence intestinal inflammation, and their expression may interact with environmental factors such as diet and gut microbes. Our study aimed to examine the impact of protein sources on a genetic colitis mouse model.MethodsAbcb1a-deficient colitis mice were fed either casein or red meat-supplemented diets to investigate potential colitis-aggravating components in red meat and their effects on host-microbiota interactions. We conducted deep label free quantitative proteomic inflammation profiling of gastrointestinal tissue (colon, ileum) and urine, and determined the overall microbiome in feces using 16S rRNA gene sequencing. Microbiota shifts by diet and protein transporter impairment were addressed by multivariate statistical analysis. Colon and systemic gut inflammation were validated through histology and immune assays, respectively.ResultsA quantitative discovery based proteomic analysis of intestinal tissue and urine revealed associations between ileum and urine proteomes in relation to Abcb1a deficiency. The absence of Abcb1a efflux pump function and diet-induced intestinal inflammation impacted multiple systemic immune processes, including extensive neutrophil extracellular trap (NET) components observed in relation to neutrophil degranulation throughout the gastrointestinal tract. The colitis model’s microbiome differed significantly from that of wild-type mice, indicating the substantial influence of efflux transporter deficiency on microbiota.ConclusionThe proteomic and microbiota analyzes of a well-established murine model enabled the correlation of gastrointestinal interactions not readily identifiable in human cohorts. Insights into dysregulated biological pathways in this disease model might offer translational biomarkers based on NETs and improved understanding of IBD pathogenesis in human patients. Our findings demonstrate that drug transporter deficiency induces substantial changes in the microbiota, leading to increased levels of IBD-associated strains and resulting in intestinal inflammation.GRAPHICAL ABSTRACT

Summary: Background: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. Methods: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. Findings: Genetically elevated PUFA desaturase activity was associated (P

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.

Pemphigus foliaceus (PF) is an autoimmune skin blistering disease characterized by antidesmoglein-1 IgG production, with an endemic form (EPF) in Brazil. Genetic and epigenetic factors have been associated with EPF, but its etiology is still not fully understood. To evaluate the genetic association of histone (de)acetylation-related genes with EPF susceptibility, we evaluated 785 polymorphisms from 144 genes, for 227 EPF patients and 194 controls. Carriers of HDAC4_rs4852054*A were more susceptible (OR = 1.79, p = 0.0038), whereas those with GSE1_rs13339618*A (OR = 0.57, p = 0.0011) and homozygotes for PHF21A_rs4756055*A (OR = 0.39, p = 0.0006) were less susceptible to EPF. These variants were not associated with sporadic PF (SPF) in German samples of 75 SPF patients and 150 controls, possibly reflecting differences in SPF and EPF pathophysiology. We further evaluated the expression of histone (de)acetylation-related genes in CD4+ T lymphocytes, using RNAseq. In these cells, we found a higher expression of KAT2B, PHF20, and ZEB2 and lower expression of KAT14 and JAD1 in patients with active EPF without treatment compared to controls from endemic regions. The encoded proteins cause epigenetic modifications related to immune cell differentiation and cell death, possibly affecting the immune response in patients with PF.

Abstract Inflammatory bowel disease (IBD) is characterised by chronic inflammation of the gastrointestinal tract. Although its aetiology remains unknown, environmental and genetic factors are involved in its development. Regarding genetics, more than 200 loci have been associated with IBD but the transferability of those signals to the Basque population living in Northern Spain, a population with distinctive genetic background, remains unknown. We have analysed 5,411,568 SNPs in 498 IBD cases and 935 controls from the Basque population. We found 33 suggestive loci (p 0.68. In conclusion, we report on the genetic architecture of IBD in the Basque population, and explore the performance of European-descent genetic risk scores in this population.

Abstract To elucidate cross-sectional patterns and longitudinal changes of oral and stool microbiota in multiple sclerosis (MS) patients and the effect of B-cell depletion. We conducted an observational, longitudinal clinical cohort study analysing four timepoints over 12 months in 36 MS patients, of whom 22 initiated B-cell depleting therapy with ocrelizumab and a healthy control group. For microbiota analysis of the oral cavity and the gut, provided stool and oral swab samples underwent 16S rDNA sequencing and subsequent bioinformatic analyses. Oral microbiota-patterns exhibited a reduced alpha-diversity and unique differential microbiota changes compared to stool such as increased levels of Proteobacteria and decreased abundance of Actinobacteria. Following B-cell depletion, we observed increased alpha-diversity in the gut and the oral cavity as well as a long-term sustained reduction of pro-inflammatory Gram-negative bacteria (e.g., Escherichia/Shigella). MS patients have altered stool and oral microbiota diversity patterns compared to healthy controls, which are most pronounced in patients with higher disease activity and disability. Therapeutic B-cell depletion is associated with persisting regression of these changes. Whether these microbial changes are unspecific side-effects of B-cell depletion or indirectly modulate MS disease activity and progression is currently unknown and necessitates further investigations.

The human leukocyte antigen (HLA) proteins are an indispensable component of adaptive immunity because of their role in presenting self and foreign peptides to T cells. Further, many complex diseases are associated with genetic variation in the HLA region, implying an important role for specific HLA-presented peptides in the etiology of these diseases. Identifying the specific set of peptides presented by an individual’s HLA proteins in vivo, as a whole being referred to as the immunopeptidome, has therefore gathered increasing attention for different reasons. For example, identifying neoepitopes for cancer immunotherapy, vaccine development against infectious pathogens, or elucidating the role of HLA in autoimmunity. Despite the tremendous progress made during the last decade in these areas, several questions remain unanswered. In this perspective, we highlight five remaining key challenges in the analysis of peptide presentation and T cell immunogenicity and discuss potential solutions to these problems. We believe that addressing these questions would not only improve our understanding of disease etiology but will also have a direct translational impact in terms of engineering better vaccines and in developing more potent immunotherapies.

Florian Uellendahl-Werth et al. conduct cross-tissue transcriptome-wide association studies to explore genetic mechanisms shared across immune-related and psychiatric traits. Their results identify several genes (including PPP3CA) that could mediate the interplay between psychiatric and inflammatory disease.

Genetic studies of eczema to date have mostly explored common genetic variation. Here, the authors perform a large meta-analysis for common and rare variants and discover 8 loci associated with eczema. Over 20% of the heritability of the condition is attributable to rare variants.

Introduction: Inflammatory bowel disease (IBD) is characterized by a dysbiosis of the gut microbiome that results from the interaction of the constituting taxa with one another, and with the host. At the same time, host genetic variation is associated with both IBD risk and microbiome composition.Methods: In the present study, we defined quantitative traits (QTs) from modules identified in microbial co-occurrence networks to measure the inter-individual consistency of microbial abundance and subjected these QTs to a genome-wide quantitative trait locus (QTL) linkage analysis.Results: Four microbial network modules were consistently identified in two cohorts of healthy individuals, but three of the corresponding QTs differed significantly between IBD patients and unaffected individuals. The QTL linkage analysis was performed in a sub-sample of the Kiel IBD family cohort (IBD-KC), an ongoing study of 256 German families comprising 455 IBD patients and 575 first- and second-degree, non-affected relatives. The analysis revealed five chromosomal regions linked to one of three microbial module QTs, namely on chromosomes 3 (spanning 10.79 cM) and 11 (6.69 cM) for the first module, chr9 (0.13 cM) and chr16 (1.20 cM) for the second module, and chr13 (19.98 cM) for the third module. None of these loci have been implicated in a microbial phenotype before.Discussion: Our study illustrates the benefit of combining network and family-based linkage analysis to identify novel genetic drivers of microbiome composition in a specific disease context.

Portal hypertension (PH) in liver cirrhosis leads to increased gut permeability and the translocation of bacteria across the gut–liver axis. Microbial DNA has recently been detected in different blood compartments; however, this phenomenon has not been thoroughly analyzed in PH. This study aimed to explore circulating bacterial DNA signatures, inflammatory cytokines, and gut permeability markers in different blood compartments (peripheral and hepatic veins) of patients with cirrhosis and PH. The 16S rRNA blood microbiome profiles were determined in 58 patients with liver cirrhosis and 46 control patients. Taxonomic differences were analyzed in relation to PH, liver function, inflammatory cytokines, and gut permeability markers. Circulating plasma microbiome profiles in patients with cirrhosis were distinct from those of the controls and were characterized by enrichment of Comamonas, Cnuella, Dialister, Escherichia/Shigella, and Prevotella and the depletion of Bradyrhizobium, Curvibacter, Diaphorobacter, Pseudarcicella, and Pseudomonas. Comparison of peripheral and hepatic vein blood compartments of patients with cirrhosis did not reveal differentially abundant taxa. Enrichment of the genera Bacteroides, Escherichia/Shigella, and Prevotella was associated with severe PH (SPH) in both blood compartments; however, circulating microbiome profiles could not predict PH severity. Escherichia/Shigella and Prevotella abundance was correlated with IL-8 levels in the hepatic vein. In conclusion, we demonstrated a distinct circulating blood microbiome profile in patients with cirrhosis, showing that specific bacterial genera in blood are marginally associated with SPH, Model for End-Stage Liver Disease score, and inflammation biomarkers; however, circulating microbial composition failed to predict PH severity.

Dysbiosis of the gut microbiome is a hallmark of inflammatory bowel disease (IBD) and both, IBD risk and microbiome composition, have been found to be associated with genetic variation. Using data from families of IBD patients, we examined the association between genetic and microbiome similarity in a specific IBD context, followed by a genome-wide quantitative trait locus (QTL) linkage analysis of various microbiome traits using the same data. SNP genotypes as well as gut microbiome and phenotype data were obtained from the Kiel IBD family cohort (IBD-KC). The IBD-KC is an ongoing prospective study in Germany currently comprising 256 families with 455 IBD patients and 575 first- and second-degree relatives. Initially focusing upon known IBD risk loci, we noted a statistically significant (FDR

Recent rodent microbiome experiments suggest that besides Akkermansia, Parasutterella sp. are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize Parasutterella in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438). In addition, we examined Parasutterella abundance in response to a weight loss intervention (n = 55). Parasutterella was positively associated with BMI and type 2 diabetes independently of the reduced microbiome α/β diversity and low-grade inflammation commonly found in obesity. Nutritional analysis revealed a positive association with the dietary intake of carbohydrates but not with fat or protein consumption. Out of 126 serum metabolites differentially detectable by untargeted HPLC-based MS-metabolomics, L-cysteine showed the strongest reduction in subjects with high Parasutterella abundance. This is of interest, since Parasutterella is a known high L-cysteine consumer and L-cysteine is known to improve blood glucose levels in rodents. Furthermore, metabolic network enrichment analysis identified an association of high Parasutterella abundance with the activation of the human fatty acid biosynthesis pathway suggesting a mechanism for body weight gain. This is supported by a significant reduction of the Parasutterella abundance during our weight loss intervention. Together, these data indicate a role for Parasutterella in human type 2 diabetes and obesity, whereby the link to L-cysteine might be relevant in type 2 diabetes development and the link to the fatty acid biosynthesis pathway for body weight gain in response to a carbohydrate-rich diet in obesity development.

Abstract Background Clinical interpretation of genetic variants in the context of the patient’s phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. Methods We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. Results GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. Conclusions GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

Abstract Compared to the huge microbial diversity in most mammals, human gut microbiomes have lost diversity while becoming specialized for animal-based diets – especially compared to chimps, their genetically closest ancestors. The lowered microbial diversity within the gut of westernized populations has also been associated with different kinds of chronic inflammatory diseases in humans. To further deepen our knowledge on phylogenetic and ecologic impacts on human health and fitness, we established the herein presented biobank as well as its comprehensive microbiota analysis. In total, 368 stool samples from 38 different animal species, including Homo sapiens, belonging to four diverse mammalian orders were collected at seven different locations and analyzed by 16S rRNA gene amplicon sequencing. Comprehensive data analysis was performed to (i) determine the overall impact of host phylogeny vs. diet, location, and ecology and to (ii) examine the general pattern of fecal bacterial diversity across captive mammals and humans. By using a controlled study design with captive mammals we could verify that host phylogeny is the most dominant driver of mammalian gut microbiota composition. However, the effect of ecology appears to be able to overcome host phylogeny and should therefore be studied in more detail in future studies. Most importantly, our study could observe a remarkable decrease of Spirochaetes and Prevotella in westernized humans and platyrrhines, which is probably not only due to diet, but also to the social behavior and structure in these communities. Our study highlights the importance of phylogenetic relationship and ecology within the evolution of mammalian fecal microbiota composition. Particularly, the observed decrease of Spirochaetes and Prevotella in westernized communities might be associated to lifestyle dependent rapid evolutionary changes, potentially involved in the establishment of dysbiotic microbiomes, which promote the etiology of chronic diseases.

Abstract:: Objectives: To examine the relationship between antibody status and cycle threshold (Ct) values, the prognostic value of the latter for COVID-19 patients, and the inter-assay comparability of SARS-CoV-2 Ct values. Methods: In 347 COVID-19 inpatients, SARS-CoV-2 Ct values (via reverse transcription-quantitative polymerase chain reaction) on admission were compared between 2 assays and correlated with the antibody response (in the course of the disease), the clinical course and the time since onset of symptoms. Results: Ct values for 2 of 3 target genes showed significant differences between the 2 assays used (P=0.012 and P

Abstract Background The human leukocyte antigen (HLA) proteins play a fundamental role in the adaptive immune system as they present peptides to T cells. Mass-spectrometry-based immunopeptidomics is a promising and powerful tool for characterizing the immunopeptidomic landscape of HLA proteins, that is the peptides presented on HLA proteins. Despite the growing interest in the technology, and the recent rise of immunopeptidomics-specific identification pipelines, there is still a gap in data-analysis and software tools that are specialized in analyzing and visualizing immunopeptidomics data. Results We present the IPTK library which is an open-source Python-based library for analyzing, visualizing, comparing, and integrating different omics layers with the identified peptides for an in-depth characterization of the immunopeptidome. Using different datasets, we illustrate the ability of the library to enrich the result of the identified peptidomes. Also, we demonstrate the utility of the library in developing other software and tools by developing an easy-to-use dashboard that can be used for the interactive analysis of the results. Conclusion IPTK provides a modular and extendable framework for analyzing and integrating immunopeptidomes with different omics layers. The library is deployed into PyPI at https://pypi.org/project/IPTKL/ and into Bioconda at https://anaconda.org/bioconda/iptkl , while the source code of the library and the dashboard, along with the online tutorials are available at https://github.com/ikmb/iptoolkit .

BackgroundClara cell 16 kDa protein (CC16) is a secretory protein primarily expressed in epithelial cells in the lungs. Previous studies show that CC16 exerts anti-inflammatory and immune-modulatory properties in both acute and chronic pulmonary diseases. However, despite the evidence of CC16’s high biomarker potential, evaluation of its role in infectious diseases is yet very limited.MethodsSerum CC16 concentrations were measured by ELISA and assessed in two different types of severe infections. Using a case-control study design, patients treated for either severe SARS-CoV-2 or severe non-pulmonary sepsis infection were compared to age- and sex-matched healthy human subjects.ResultsSerum CC16 was significantly increased in both types of infection (SARS-CoV-2: 96.22 ± 129.01 ng/ml vs. healthy controls: 14.05 ± 7.48 ng/ml, p = 0.022; sepsis: 35.37 ± 28.10 ng/ml vs. healthy controls: 15.25 ± 7.51 ng/ml, p = 0.032) but there were no distinct differences between infections with and without pulmonary focus (p = 0.089). Furthermore, CC16 serum levels were positively correlated to disease duration and inversely to the platelet count in severe SARS-CoV-2 infection.ConclusionsIncreased CC16 serum levels in both SARS-CoV-2 and sepsis reinforce the high potential as a biomarker for epithelial cell damage and bronchoalveolar−blood barrier leakage in pulmonary as well as non-pulmonary infectious diseases.

Abstract Background Human well-being has been linked to the composition and functional capacity of the intestinal microbiota. As regular exercise is known to improve human health, it is not surprising that exercise was previously described to positively modulate the gut microbiota, too. However, most previous studies mainly focused on either elite athletes or animal models. Thus, we conducted a randomised intervention study that focused on the effects of different types of training (endurance and strength) in previously physically inactive, healthy adults in comparison to controls that did not perform regular exercise. Overall study duration was ten weeks including six weeks of intervention period. In addition to 16S rRNA gene amplicon sequencing of longitudinally sampled faecal material of participants (six time points), detailed body composition measurements and analysis of blood samples (at baseline and after the intervention) were performed to obtain overall physiological changes within the intervention period. Activity tracker devices (wrist-band wearables) provided activity status and sleeping patterns of participants as well as exercise intensity and heart measurements. Results Different biometric responses between endurance and strength activities were identified, such as a significant increase of lymphocytes and decrease of mean corpuscular haemoglobin concentration (MCHC) only within the strength intervention group. In the endurance group, we observed a significant reduction in hip circumference and an increase in physical working capacity (PWC). Though a large variation of microbiota changes were observed between individuals of the same group, we did not find specific collective alterations in the endurance nor the strength groups, arguing for microbiome variations specific to individuals, and therefore, were not captured in our analysis. Conclusions We could show that different types of exercise have distinct but moderate effects on the overall physiology of humans and very distinct microbial changes in the gut. The observed overall changes during the intervention highlight the importance of physical activity on well-being. Future studies should investigate the effect of exercise on a longer timescale, investigate different training intensities and consider high-resolution shotgun metagenomics technology. Trial registration DRKS, DRKS00015873 . Registered 12 December 2018; Retrospectively registered.

Age at onset of X-linked dystonia-parkinsonism is 50% explained by the length of a repeat in an SVA insert. The authors perform a GWAS for genetic modifiers and discover three more loci, accounting for another 13% of variability in age at onset with the protective alleles delaying onset by seven years.