Publications by authors named "Tim Kacprowski"

62 Publications

Network analysis methods for studying microbial communities: A mini review.

Comput Struct Biotechnol J 2021 4;19:2687-2698. Epub 2021 May 4.

Chair of Experimental Bioinformatics, Technical University of Munich, 85354 Freising, Germany.

Microorganisms including bacteria, fungi, viruses, protists and archaea live as communities in complex and contiguous environments. They engage in numerous inter- and intra- kingdom interactions which can be inferred from microbiome profiling data. In particular, network-based approaches have proven helpful in deciphering complex microbial interaction patterns. Here we give an overview of state-of-the-art methods to infer intra-kingdom interactions ranging from simple correlation- to complex conditional dependence-based methods. We highlight common biases encountered in microbial profiles and discuss mitigation strategies employed by different tools and their trade-off with increased computational complexity. Finally, we discuss current limitations that motivate further method development to infer inter-kingdom interactions and to robustly and comprehensively characterize microbial environments in the future.
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http://dx.doi.org/10.1016/j.csbj.2021.05.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131268PMC
May 2021

Carrying asymptomatic gallstones is not associated with changes in intestinal microbiota composition and diversity but cholecystectomy with significant dysbiosis.

Sci Rep 2021 03 23;11(1):6677. Epub 2021 Mar 23.

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany.

Gallstone disease affects up to twenty percent of the population in western countries and is a significant contributor to morbidity and health care expenditure. Intestinal microbiota have variously been implicated as either contributing to gallstone formation or to be affected by cholecystectomy. We conducted a large-scale investigation on 404 gallstone carriers, 580 individuals post-cholecystectomy and 984 healthy controls with similar distributions of age, sex, body mass index, smoking habits, and food-frequency-score. All 1968 subjects were recruited from the population-based Study-of-Health-in-Pomerania (SHIP), which includes transabdominal gallbladder ultrasound. Fecal microbiota profiles were determined by 16S rRNA gene sequencing. No significant differences in microbiota composition were detected between gallstone carriers and controls. Individuals post-cholecystectomy exhibited reduced microbiota diversity, a decrease in the potentially beneficial genus Faecalibacterium and an increase in the opportunistic pathogen Escherichia/Shigella. The absence of an association between the gut microbiota and the presence of gallbladder stones suggests that there is no intestinal microbial risk profile increasing the likelihood of gallstone formation. Cholecystectomy, on the other hand, is associated with distinct microbiota changes that have previously been implicated in unfavorable health effects and may not only contribute to gastrointestinal infection but also to the increased colon cancer risk of cholecystectomized patients.
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http://dx.doi.org/10.1038/s41598-021-86247-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988160PMC
March 2021

splice-aware RNA-Seq data simulation.

Bioinformatics 2021 Feb 27. Epub 2021 Feb 27.

Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.

Summary: A plethora of tools exist for RNA-Seq data analysis with a focus on alternative splicing (AS). However, appropriate data for their comparative evaluation is missing. The R package ASimulatoR simulates gold standard RNA-Seq datasets with fine-grained control over the distribution of AS events, which allow for evaluating alternative splicing tools, e.g. to study the effect of sequencing depth on the performance of AS event detection.

Availability And Implementation: ASimulatoR is freely available at https://github.com/biomedbigdata/ASimulatoR as an R package under GPL-3 license.
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http://dx.doi.org/10.1093/bioinformatics/btab142DOI Listing
February 2021

CSF proteome in multiple sclerosis subtypes related to brain lesion transcriptomes.

Sci Rep 2021 Feb 18;11(1):4132. Epub 2021 Feb 18.

Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, 5000, Odense C, Denmark.

To identify markers in the CSF of multiple sclerosis (MS) subtypes, we used a two-step proteomic approach: (i) Discovery proteomics compared 169 pooled CSF from MS subtypes and inflammatory/degenerative CNS diseases (NMO spectrum and Alzheimer disease) and healthy controls. (ii) Next, 299 proteins selected by comprehensive statistics were quantified in 170 individual CSF samples. (iii) Genes of the identified proteins were also screened among transcripts in 73 MS brain lesions compared to 25 control brains. F-test based feature selection resulted in 8 proteins differentiating the MS subtypes, and secondary progressive (SP)MS was the most different also from controls. Genes of 7 out these 8 proteins were present in MS brain lesions: GOLM was significantly differentially expressed in active, chronic active, inactive and remyelinating lesions, FRZB in active and chronic active lesions, and SELENBP1 in inactive lesions. Volcano maps of normalized proteins in the different disease groups also indicated the highest amount of altered proteins in SPMS. Apolipoprotein C-I, apolipoprotein A-II, augurin, receptor-type tyrosine-protein phosphatase gamma, and trypsin-1 were upregulated in the CSF of MS subtypes compared to controls. This CSF profile and associated brain lesion spectrum highlight non-inflammatory mechanisms in differentiating CNS diseases and MS subtypes and the uniqueness of SPMS.
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http://dx.doi.org/10.1038/s41598-021-83591-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892884PMC
February 2021

BiCoN: Network-constrained biclustering of patients and omics data.

Bioinformatics 2020 Dec 26. Epub 2020 Dec 26.

Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, Munich, 80333, Germany.

Motivation: Unsupervised learning approaches are frequently employed to stratify patients into clinically relevant subgroups and to identify biomarkers such as disease-associated genes. However, clustering and biclustering techniques are oblivious to the functional relationship of genes and are thus not ideally suited to pinpoint molecular mechanisms along with patient subgroups.

Results: We developed the network-constrained biclustering approach BiCoN (Biclustering Constrained by Networks) which (i) restricts biclusters to functionally related genes connected in molecular interaction networks and (ii) maximizes the difference in gene expression between two subgroups of patients. This allows BiCoN to simultaneously pinpoint molecular mechanisms responsible for the patient grouping. Network-constrained clustering of genes makes BiCoN more robust to noise and batch effects than typical clustering and biclustering methods. BiCoN can faithfully reproduce known disease subtypes as well as novel, clinically relevant patient subgroups, as we could demonstrate using breast and lung cancer datasets. In summary, BiCoN is a novel systems medicine tool that combines several heuristic optimization strategies for robust disease mechanism extraction. BiCoN is well-documented and freely available as a python package or a web interface.

Availability And Implementation: PyPI package: https://pypi.org/project/bicon.

Web Interface: https://exbio.wzw.tum.de/bicon.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa1076DOI Listing
December 2020

A framework for modeling epistatic interaction.

Bioinformatics 2021 07;37(12):1708-1716

Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.

Motivation: Recently, various tools for detecting single nucleotide polymorphisms (SNPs) involved in epistasis have been developed. However, no studies evaluate the employed statistical epistasis models such as the χ2-test or quadratic regression independently of the tools that use them. Such an independent evaluation is crucial for developing improved epistasis detection tools, for it allows to decide if a tool's performance should be attributed to the epistasis model or to the optimization strategy run on top of it.

Results: We present a protocol for evaluating epistasis models independently of the tools they are used in and generalize existing models designed for dichotomous phenotypes to the categorical and quantitative case. In addition, we propose a new model which scores candidate SNP sets by computing maximum likelihood distributions for the observed phenotypes in the cells of their penetrance tables. Extensive experiments show that the proposed maximum likelihood model outperforms three widely used epistasis models in most cases. The experiments also provide valuable insights into the properties of existing models, for instance, that quadratic regression perform particularly well on instances with quantitative phenotypes.

Availability And Implementation: The evaluation protocol and all compared models are implemented in C++ and are supported under Linux and macOS. They are available at https://github.com/baumbachlab/genepiseeker/, along with test datasets and scripts to reproduce the experiments.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa990DOI Listing
July 2021

NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype.

PLoS Biol 2020 11 10;18(11):e3000885. Epub 2020 Nov 10.

Department of Pharmacology and Personalised Medicine, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands.

Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase (Nox) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by molecular network analysis and identify NOX5, not present in rodents, as a sole neighbor to human vasodilatory endothelial nitric oxide (NO) signaling. In hypertensive patients, endothelial microparticles indeed contained higher levels of NOX5-but not NOX1, NOX2, or NOX4-with a bimodal distribution correlating with disease severity. Mechanistically, mice expressing human Nox5 in endothelial cells developed-upon aging-severe systolic hypertension and impaired endothelium-dependent vasodilation due to uncoupled NO synthase (NOS). We conclude that NOX5-induced uncoupling of endothelial NOS is a causal mechanism and theragnostic target of an age-related hypertension endotype. Nox5 knock-in (KI) mice represent the first mechanism-based animal model of hypertension.
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http://dx.doi.org/10.1371/journal.pbio.3000885DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654809PMC
November 2020

Long-term instability of the intestinal microbiome is associated with metabolic liver disease, low microbiota diversity, diabetes mellitus and impaired exocrine pancreatic function.

Gut 2021 Mar 9;70(3):522-530. Epub 2020 Nov 9.

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany

Objective: The intestinal microbiome affects the prevalence and pathophysiology of a variety of diseases ranging from inflammation to cancer. A reduced taxonomic or functional diversity of the microbiome was often observed in association with poorer health outcomes or disease in general. Conversely, factors or manifest diseases that determine the long-term stability or instability of the microbiome are largely unknown. We aimed to identify disease-relevant phenotypes associated with faecal microbiota (in-)stability.

Design: A total of 2564 paired faecal samples from 1282 participants of the population-based Study of Health in Pomerania (SHIP) were collected at a 5-year (median) interval and microbiota profiles determined by gene sequencing. The changes in faecal microbiota over time were associated with highly standardised and comprehensive phenotypic data to determine factors related to microbiota (in-)stability.

Results: The overall microbiome landscape remained remarkably stable over time. The greatest microbiome instability was associated with factors contributing to metabolic syndrome such as fatty liver disease and diabetes mellitus. These, in turn, were associated with an increase in facultative pathogens such as or . Greatest stability of the microbiome was determined by higher initial alpha diversity, female sex, high household income and preserved exocrine pancreatic function. Participants who newly developed fatty liver disease or diabetes during the 5-year follow-up already displayed significant microbiota changes at study entry when the diseases were absent.

Conclusion: This study identifies distinct components of metabolic liver disease to be associated with instability of the intestinal microbiome, increased abundance of facultative pathogens and thus greater susceptibility toward dysbiosis-associated diseases.
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http://dx.doi.org/10.1136/gutjnl-2020-322753DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873430PMC
March 2021

The Gut Microbiome in Patients With Chronic Pancreatitis Is Characterized by Significant Dysbiosis and Overgrowth by Opportunistic Pathogens.

Clin Transl Gastroenterol 2020 09;11(9):e00232

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany.

Introduction: Exocrine pancreatic function is a critical host factor in determining the intestinal microbiota composition. Diseases affecting the exocrine pancreas could therefore influence the gut microbiome. We investigated the changes in gut microbiota of patients with chronic pancreatitis (CP).

Methods: Patients with clinical and imaging evidence of CP (n = 51) were prospectively recruited and compared with twice the number of nonpancreatic disease controls matched for distribution in age, sex, body mass index, smoking, diabetes mellitus, and exocrine pancreatic function (stool elastase). From stool samples of these 153 subjects, DNA was extracted, and intestinal microbiota composition was determined by bacterial 16S ribosomal RNA gene sequencing.

Results: Patients with CP exhibited severely reduced microbial diversity (Shannon diversity index and Simpson diversity number, P < 0.001) with an increased abundance of facultative pathogenic organisms (P < 0.001) such as Enterococcus (q < 0.001), Streptococcus (q < 0.001), and Escherichia.Shigella (q = 0.002). The CP-associated changes were independent of exocrine pancreatic insufficiency. Short-chain fatty acid producers, considered protective for epithelia such as Faecalibacterium (q < 0.001), showed reduced abundance in patients with CP. Of 4 additional patients with CP previously treated with antibiotics (ceftriaxone and metronidazole), 3 patients were characterized by distinct Enterococcus overgrowth.

Discussion: CP is associated with marked gut microbiota dysbiosis, greatly reduced diversity, and increased abundance of opportunistic pathogens, specifically those previously isolated from infected pancreatic necrosis. Taxa with a potentially beneficial role in intestinal barrier function are depleted. These changes can increase the probability of complications from pancreatitis such as infected fluid collections or small intestinal bacterial overgrowth (see Graphical Abstract, Supplementary Digital Content 1, http://links.lww.com/CTG/A383).
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http://dx.doi.org/10.14309/ctg.0000000000000232DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494146PMC
September 2020

miRNA Alterations Elicit Pathways Involved in Memory Decline and Synaptic Function in the Hippocampus of Aged Tg4-42 Mice.

Front Neurosci 2020 10;14:580524. Epub 2020 Sep 10.

Division of Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Georg-August-University, Göttingen, Germany.

The transcriptome of non-coding RNA (ncRNA) species is increasingly focused in Alzheimer's disease (AD) research. NcRNAs comprise, among others, transfer RNAs, long non-coding RNAs and microRNAs (miRs), each with their own specific biological function. We used smallRNASeq to assess miR expression in the hippocampus of young (3 month old) and aged (8 month old) Tg4-42 mice, a model system for sporadic AD, as well as age-matched wildtype controls. Tg4-42 mice express N-truncated Aβ, develop age-related neuron loss, reduced neurogenesis and behavioral deficits. Our results do not only confirm known miR-AD associations in Tg4-42 mice, but more importantly pinpoint 22 additional miRs associated to the disease. Twenty-five miRs were differentially expressed in both aged Tg4-42 and aged wildtype mice while eight miRs were differentially expressed only in aged wildtype mice, and 33 only in aged Tg4-42 mice. No significant alteration in the miRNome was detected in young mice, which indicates that the changes observed in aged mice are down-stream effects of Aβ-induced pathology in the Tg4-42 mouse model for AD. Targets of those miRs were predicted using miRWalk. For miRs that were differentially expressed only in the Tg4-42 model, 128 targets could be identified, whereas 18 genes were targeted by miRs only differentially expressed in wildtype mice and 85 genes were targeted by miRs differentially expressed in both mouse models. Genes targeted by differentially expressed miRs in the Tg4-42 model were enriched for negative regulation of long-term synaptic potentiation, learning or memory, regulation of synaptic signaling and modulation of chemical synaptic transmission obtained. This untargeted miR sequencing approach supports previous reports on the Tg4-42 mice as a valuable model for AD. Furthermore, it revealed miRs involved in AD, which can serve as biomarkers or therapeutic targets.
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http://dx.doi.org/10.3389/fnins.2020.580524DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511553PMC
September 2020

DIGGER: exploring the functional role of alternative splicing in protein interactions.

Nucleic Acids Res 2021 01;49(D1):D309-D318

Chair of Experimental Bioinformatics, TUM School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany.

Alternative splicing plays a major role in regulating the functional repertoire of the proteome. However, isoform-specific effects to protein-protein interactions (PPIs) are usually overlooked, making it impossible to judge the functional role of individual exons on a systems biology level. We overcome this barrier by integrating protein-protein interactions, domain-domain interactions and residue-level interactions information to lift exon expression analysis to a network level. Our user-friendly database DIGGER is available at https://exbio.wzw.tum.de/digger and allows users to seamlessly switch between isoform and exon-centric views of the interactome and to extract sub-networks of relevant isoforms, making it an essential resource for studying mechanistic consequences of alternative splicing.
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http://dx.doi.org/10.1093/nar/gkaa768DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778957PMC
January 2021

Multiple Sclerosis Atlas: A Molecular Map of Brain Lesion Stages in Progressive Multiple Sclerosis.

Netw Syst Med 2020 27;3(1):122-129. Epub 2020 Aug 27.

Neurology Research Unit, Department of Neurology, Odense University Hopsital, Odense, Denmark.

Multiple sclerosis (MS) is a chronic disorder of the central nervous system with an untreatable late progressive phase. Molecular maps of different stages of brain lesion evolution in patients with progressive multiple sclerosis (PMS) are missing but critical for understanding disease development and to identify novel targets to halt progression. The MS Atlas database comprises comprehensive high-quality transcriptomic profiles of 98 white matter (WM) brain samples of different lesion types (normal-appearing WM [NAWM], active, chronic active, inactive, remyelinating) from ten progressive MS patients and 25 WM areas from five non-neurological diseased cases. We introduce the first MS brain lesion atlas (msatlas.dk), developed to address the current challenges of understanding mechanisms driving the fate on a lesion basis. The MS Atlas gives means for testing research hypotheses, validating biomarkers and drug targets. It comes with a user-friendly web interface, and it fosters bioinformatic methods for network enrichment to extract mechanistic markers for specific lesion types and pathway-based lesion type comparison. We describe examples of how the MS Atlas can be used to extract systems medicine signatures and demonstrate the interface of MS Atlas. This compendium of mechanistic PMS WM lesion profiles is an invaluable resource to fuel future MS research and a new basis for treatment development.
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http://dx.doi.org/10.1089/nsm.2020.0006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500075PMC
August 2020

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity.

Diabetes 2020 12 11;69(12):2806-2818. Epub 2020 Sep 11.

Department of Biostatistics, Boston University School of Public Health, Boston, MA.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , , , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry ( = 2 × 10, = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
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http://dx.doi.org/10.2337/db20-0070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679778PMC
December 2020

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Cell 2020 09;182(5):1214-1231.e11

Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD, 21224, USA.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.
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http://dx.doi.org/10.1016/j.cell.2020.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482360PMC
September 2020

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Cell 2020 09;182(5):1198-1213.e14

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Division on Aging, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
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http://dx.doi.org/10.1016/j.cell.2020.06.045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480402PMC
September 2020

Exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing.

Nat Commun 2020 07 14;11(1):3518. Epub 2020 Jul 14.

Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, München, Germany.

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Various studies exist about the molecular mechanisms of viral infection. However, such information is spread across many publications and it is very time-consuming to integrate, and exploit. We develop CoVex, an interactive online platform for SARS-CoV-2 host interactome exploration and drug (target) identification. CoVex integrates virus-human protein interactions, human protein-protein interactions, and drug-target interactions. It allows visual exploration of the virus-host interactome and implements systems medicine algorithms for network-based prediction of drug candidates. Thus, CoVex is a resource to understand molecular mechanisms of pathogenicity and to prioritize candidate therapeutics. We investigate recent hypotheses on a systems biology level to explore mechanistic virus life cycle drivers, and to extract drug repurposing candidates. CoVex renders COVID-19 drug research systems-medicine-ready by giving the scientific community direct access to network medicine algorithms. It is available at https://exbio.wzw.tum.de/covex/.
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http://dx.doi.org/10.1038/s41467-020-17189-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7360763PMC
July 2020

EpiGEN: an epistasis simulation pipeline.

Bioinformatics 2020 12;36(19):4957-4959

Technical University of Munich, School of Life Sciences Weihenstephan, Chair of Experimental Bioinformatics, 85354 Freising, Germany.

Summary: Simulated data are crucial for evaluating epistasis detection tools in genome-wide association studies. Existing simulators are limited, as they do not account for linkage disequilibrium (LD), support limited interaction models of single nucleotide polymorphisms (SNPs) and only dichotomous phenotypes or depend on proprietary software. In contrast, EpiGEN supports SNP interactions of arbitrary order, produces realistic LD patterns and generates both categorical and quantitative phenotypes.

Availability And Implementation: EpiGEN is implemented in Python 3 and is freely available at https://github.com/baumbachlab/epigen.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa245DOI Listing
December 2020

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

PLoS Comput Biol 2020 02 3;16(2):e1007616. Epub 2020 Feb 3.

Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.
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http://dx.doi.org/10.1371/journal.pcbi.1007616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043350PMC
February 2020

Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans.

Nat Genet 2020 02 20;52(2):167-176. Epub 2020 Jan 20.

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.

The kidneys integrate information from continuous systemic processes related to the absorption, distribution, metabolism and excretion (ADME) of metabolites. To identify underlying molecular mechanisms, we performed genome-wide association studies of the urinary concentrations of 1,172 metabolites among 1,627 patients with reduced kidney function. The 240 unique metabolite-locus associations (metabolite quantitative trait loci, mQTLs) that were identified and replicated highlight novel candidate substrates for transport proteins. The identified genes are enriched in ADME-relevant tissues and cell types, and they reveal novel candidates for biotransformation and detoxification reactions. Fine mapping of mQTLs and integration with single-cell gene expression permitted the prioritization of causal genes, functional variants and target cell types. The combination of mQTLs with genetic and health information from 450,000 UK Biobank participants illuminated metabolic mediators, and hence, novel urinary biomarkers of disease risk. This comprehensive resource of genetic targets and their substrates is informative for ADME processes in humans and is relevant to basic science, clinical medicine and pharmaceutical research.
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http://dx.doi.org/10.1038/s41588-019-0567-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484970PMC
February 2020

Association of proteome and metabolome signatures with severity in patients with community-acquired pneumonia.

J Proteomics 2020 03 30;214:103627. Epub 2019 Dec 30.

Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Felix-Hausdorff-Str. 8, 17475 Greifswald, Germany. Electronic address:

A combined OMICS screening approach of human plasma and serum was used to characterize protein and metabolome signatures displaying association to severity of Community-acquired pneumonia (CAP). 240 serum and BD P100 EDTA plasma samples from patients diagnosed with CAP, collected during the day of enrolment to the hospital, were analyzed by a metabolomic and proteomic approach, respectively. Disease severity of CAP patients was stratified using the Sequential Organ Failure Assessment (SOFA) score. Quantitative proteome and metabolome data, derived by LC-MS/MS, were associated to SOFA and specific parameters of SOFA using linear regression models adjusted for age, BMI, sex, smoking and technical variables. Both proteome and metabolome profiling revealed remarkable strong changes in plasma and serum composition in relation to severity of CAP. Proteins and metabolites displaying SOFA associated levels are involved in immune response, particularly in processes of lipid metabolism. Proteins, which show an association to SOFA score, are involved in acute phase response, coagulation, complement activation and inflammation. Many of these metabolites and proteins displayed not only associations to SOFA, but also to parameters of SOFA score, which likely reflect the strong influence of lung-, liver-, kidney- and heart-dysfunction on the metabolome and proteome patterns. SIGNIFICANCE: Community-acquired pneumonia is the most frequent infection disease with high morbidity and mortality. So far, only few studies focused on the identification of proteins or metabolites associated to severity of CAP, often based on smaller sample sets. A screening for new diagnostic markers requires extensive sample collections in combination with high quality clinical data. To characterize the proteomic and metabolomics pattern associated to severity of CAP we performed a combined metabolomics and proteomic approach of serum and plasma sample from a multi-center clinical study focused on patients with CAP, requiring hospitalization. The results of this association study of omics data to the SOFA score enable not only an interpretation of changes in molecular patterns with severity of CAP but also an assignment of altered molecules to dysfunctions of respiratory, renal, coagulation, cardiovascular systems as well as liver.
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http://dx.doi.org/10.1016/j.jprot.2019.103627DOI Listing
March 2020

Helicobacter pylori infection associates with fecal microbiota composition and diversity.

Sci Rep 2019 12 27;9(1):20100. Epub 2019 Dec 27.

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany.

Helicobacter (H.) pylori is the most important cause for peptic ulcer disease and a risk factor for gastric carcinoma. How colonization with H. pylori affects the intestinal microbiota composition in humans is unknown. We investigated the association of H. pylori infection with intestinal microbiota composition in the population-based cohort Study-of-Health-in-Pomerania (SHIP)-TREND. Anti-H. pylori serology and H. pylori stool antigen tests were used to determine the H. pylori infection status. The fecal microbiota composition of 212 H. pylori positive subjects and 212 matched negative control individuals was assessed using 16S rRNA gene sequencing. H. pylori infection was found to be significantly associated with fecal microbiota alterations and a general increase in fecal microbial diversity. In infected individuals, the H. pylori stool antigen load determined a larger portion of the microbial variation than age or sex. The highest H. pylori stool antigen loads were associated with a putatively harmful microbiota composition. This study demonstrates profound alterations in human fecal microbiota of H. pylori infected individuals. While the increased microbiota diversity associated with H. pylori infection as well as changes in abundance of specific genera could be considered to be beneficial, others may be associated with adverse health effects, reflecting the complex relationship between H. pylori and its human host.
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http://dx.doi.org/10.1038/s41598-019-56631-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934578PMC
December 2019

Molecular signature of different lesion types in the brain white matter of patients with progressive multiple sclerosis.

Acta Neuropathol Commun 2019 12 11;7(1):205. Epub 2019 Dec 11.

Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, DK-5000, Odense C, Denmark.

To identify pathogenetic markers and potential drivers of different lesion types in the white matter (WM) of patients with progressive multiple sclerosis (PMS), we sequenced RNA from 73 different WM areas. Compared to 25 WM controls, 6713 out of 18,609 genes were significantly differentially expressed in MS tissues (FDR < 0.05). A computational systems medicine analysis was performed to describe the MS lesion endophenotypes. The cellular source of specific molecules was examined by RNAscope, immunohistochemistry, and immunofluorescence. To examine common lesion specific mechanisms, we performed de novo network enrichment based on shared differentially expressed genes (DEGs), and found TGFβ-R2 as a central hub. RNAscope revealed astrocytes as the cellular source of TGFβ-R2 in remyelinating lesions. Since lesion-specific unique DEGs were more common than shared signatures, we examined lesion-specific pathways and de novo networks enriched with unique DEGs. Such network analysis indicated classic inflammatory responses in active lesions; catabolic and heat shock protein responses in inactive lesions; neuronal/axonal specific processes in chronic active lesions. In remyelinating lesions, de novo analyses identified axonal transport responses and adaptive immune markers, which was also supported by the most heterogeneous immunoglobulin gene expression. The signature of the normal-appearing white matter (NAWM) was more similar to control WM than to lesions: only 465 DEGs differentiated NAWM from controls, and 16 were unique. The upregulated marker CD26/DPP4 was expressed by microglia in the NAWM but by mononuclear cells in active lesions, which may indicate a special subset of microglia before the lesion develops, but also emphasizes that omics related to MS lesions should be interpreted in the context of different lesions types. While chronic active lesions were the most distinct from control WM based on the highest number of unique DEGs (n = 2213), remyelinating lesions had the highest gene expression levels, and the most different molecular map from chronic active lesions. This may suggest that these two lesion types represent two ends of the spectrum of lesion evolution in PMS. The profound changes in chronic active lesions, the predominance of synaptic/neural/axonal signatures coupled with minor inflammation may indicate end-stage irreversible molecular events responsible for this less treatable phase.
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http://dx.doi.org/10.1186/s40478-019-0855-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6907342PMC
December 2019

Associations of autozygosity with a broad range of human phenotypes.

Nat Commun 2019 10 31;10(1):4957. Epub 2019 Oct 31.

Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.
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http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019

Retraction Note: Unique RNA signature of different lesion types in the brain white matter in progressive multiple sclerosis.

Acta Neuropathol Commun 2019 08 21;7(1):136. Epub 2019 Aug 21.

Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, DK-5000, Odense, Denmark.

The authors have retracted this article [1] because a line was omitted from the data sheet; this was due to a bug in the analysis scripts.
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http://dx.doi.org/10.1186/s40478-019-0790-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6704544PMC
August 2019

Obese Individuals with and without Type 2 Diabetes Show Different Gut Microbial Functional Capacity and Composition.

Cell Host Microbe 2019 08 6;26(2):252-264.e10. Epub 2019 Aug 6.

Biostatistics Department, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; The Broad Institute of MIT and Harvard, Cambridge, MA 02115, USA.

Obesity and type 2 diabetes (T2D) are metabolic disorders that are linked to microbiome alterations. However, their co-occurrence poses challenges in disentangling microbial features unique to each condition. We analyzed gut microbiomes of lean non-diabetic (n = 633), obese non-diabetic (n = 494), and obese individuals with T2D (n = 153) from German population and metabolic disease cohorts. Microbial taxonomic and functional profiles were analyzed along with medical histories, serum metabolomics, biometrics, and dietary data. Obesity was associated with alterations in microbiome composition, individual taxa, and functions with notable changes in Akkermansia, Faecalibacterium, Oscillibacter, and Alistipes, as well as in serum metabolites that correlated with gut microbial patterns. However, microbiome associations were modest for T2D, with nominal increases in Escherichia/Shigella. Medications, including antihypertensives and antidiabetics, along with dietary supplements including iron, were significantly associated with microbiome variation. These results differentiate microbial components of these interrelated metabolic diseases and identify dietary and medication exposures to consider in future studies.
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http://dx.doi.org/10.1016/j.chom.2019.07.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720933PMC
August 2019

A structured weight loss program increases gut microbiota phylogenetic diversity and reduces levels of Collinsella in obese type 2 diabetics: A pilot study.

PLoS One 2019 18;14(7):e0219489. Epub 2019 Jul 18.

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany.

The global obesity epidemic constitutes a major cause of morbidity and mortality challenging public health care systems worldwide. Thus, a better understanding of its pathophysiology and the development of novel therapeutic options are urgently needed. Recently, alterations of the intestinal microbiome in the obese have been discussed as a promoting factor in the pathophysiology of obesity and as a contributing factor to related diseases such as type 2 diabetes and metabolic syndrome. The present pilot study investigated the effect of a structured weight loss program on fecal microbiota in obese type 2 diabetics. Twelve study subjects received a low-calorie formula diet for six weeks, followed by a nine week food reintroduction and stabilization period. Fecal microbiota were determined by 16S rRNA gene sequencing of stool samples at baseline, after six weeks and at the end of the study after fifteen weeks. All study subjects lost weight continuously throughout the program. Changes in fecal microbiota were most pronounced after six weeks of low-calorie formula diet, but reverted partially until the end of the study. However, the gut microbiota phylogenetic diversity increased persistently. The abundance of Collinsella, which has previously been associated with atherosclerosis, decreased significantly during the weight loss program. This study underlines the impact of dietary changes on the intestinal microbiome and further demonstrates the beneficial effects of weight loss on gut microbiota. Trial registration: ClinicalTrials.gov NCT02970838.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219489PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6638920PMC
March 2020

Mendelian randomization evaluation of causal effects of fibrinogen on incident coronary heart disease.

PLoS One 2019 10;14(5):e0216222. Epub 2019 May 10.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.

Background: Fibrinogen is an essential hemostatic factor and cardiovascular disease risk factor. Early attempts at evaluating the causal effect of fibrinogen on coronary heart disease (CHD) and myocardial infraction (MI) using Mendelian randomization (MR) used single variant approaches, and did not take advantage of recent genome-wide association studies (GWAS) or multi-variant, pleiotropy robust MR methodologies.

Methods And Findings: We evaluated evidence for a causal effect of fibrinogen on both CHD and MI using MR. We used both an allele score approach and pleiotropy robust MR models. The allele score was composed of 38 fibrinogen-associated variants from recent GWAS. Initial analyses using the allele score used a meta-analysis of 11 European-ancestry prospective cohorts, free of CHD and MI at baseline, to examine incidence CHD and MI. We also applied 2 sample MR methods with data from a prevalent CHD and MI GWAS. Results are given in terms of the hazard ratio (HR) or odds ratio (OR), depending on the study design, and associated 95% confidence interval (CI). In single variant analyses no causal effect of fibrinogen on CHD or MI was observed. In multi-variant analyses using incidence CHD cases and the allele score approach, the estimated causal effect (HR) of a 1 g/L higher fibrinogen concentration was 1.62 (CI = 1.12, 2.36) when using incident cases and the allele score approach. In 2 sample MR analyses that accounted for pleiotropy, the causal estimate (OR) was reduced to 1.18 (CI = 0.98, 1.42) and 1.09 (CI = 0.89, 1.33) in the 2 most precise (smallest CI) models, out of 4 models evaluated. In the 2 sample MR analyses for MI, there was only very weak evidence of a causal effect in only 1 out of 4 models.

Conclusions: A small causal effect of fibrinogen on CHD is observed using multi-variant MR approaches which account for pleiotropy, but not single variant MR approaches. Taken together, results indicate that even with large sample sizes and multi-variant approaches MR analyses still cannot exclude the null when estimating the causal effect of fibrinogen on CHD, but that any potential causal effect is likely to be much smaller than observed in epidemiological studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216222PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510421PMC
January 2020

Unique RNA signature of different lesion types in the brain white matter in progressive multiple sclerosis.

Acta Neuropathol Commun 2019 04 25;7(1):58. Epub 2019 Apr 25.

Department of Neurology, Odense University Hospital, J.B. Winslowsvej 4, DK-5000, Odense, Denmark.

The heterogeneity of multiple sclerosis is reflected by dynamic changes of different lesion types in the brain white matter (WM). To identify potential drivers of this process, we RNA-sequenced 73 WM areas from patients with progressive MS (PMS) and 25 control WM. Lesion endophenotypes were described by a computational systems medicine analysis combined with RNAscope, immunohistochemistry, and immunofluorescence. The signature of the normal-appearing WM (NAWM) was more similar to control WM than to lesions: one of the six upregulated genes in NAWM was CD26/DPP4 expressed by microglia. Chronic active lesions that become prominent in PMS had a signature that were different from all other lesion types, and were differentiated from them by two clusters of 62 differentially expressed genes (DEGs). An upcoming MS biomarker, CHI3L1 was among the top ten upregulated genes in chronic active lesions expressed by astrocytes in the rim. TGFβ-R2 was the central hub in a remyelination-related protein interaction network, and was expressed there by astrocytes. We used de novo networks enriched by unique DEGs to determine lesion-specific pathway regulation, i.e. cellular trafficking and activation in active lesions; healing and immune responses in remyelinating lesions characterized by the most heterogeneous immunoglobulin gene expression; coagulation and ion balance in inactive lesions; and metabolic changes in chronic active lesions. Because we found inverse differential regulation of particular genes among different lesion types, our data emphasize that omics related to MS lesions should be interpreted in the context of lesion pathology. Our data indicate that the impact of molecular pathways is substantially changing as different lesions develop. This was also reflected by the high number of unique DEGs that were more common than shared signatures. A special microglia subset characterized by CD26 may play a role in early lesion development, while astrocyte-derived TGFβ-R2 and TGFβ pathways may be drivers of repair in contrast to chronic tissue damage. The highly specific mechanistic signature of chronic active lesions indicates that as these lesions develop in PMS, the molecular changes are substantially skewed: the unique mitochondrial/metabolic changes and specific downregulation of molecules involved in tissue repair may reflect a stage of exhaustion.
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http://dx.doi.org/10.1186/s40478-019-0709-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482546PMC
April 2019

Impaired Exocrine Pancreatic Function Associates With Changes in Intestinal Microbiota Composition and Diversity.

Gastroenterology 2019 03 2;156(4):1010-1015. Epub 2018 Nov 2.

Department of Medicine A, University Medicine Greifswald, Greifswald, Germany. Electronic address:

Background & Aims: Changes in intestinal microbiome composition are associated with inflammatory, metabolic, and malignant disorders. We studied how exocrine pancreatic function affects intestinal microbiota.

Methods: We performed 16S ribosomal RNA gene sequencing analysis of stool samples from 1795 volunteers from the population-based Study of Health in Pomerania who had no history of pancreatic disease. We also measured fecal pancreatic elastase by enzyme-linked immunosorbent assay and performed quantitative imaging of secretin-stimulated pancreatic fluid secretion. Associations of exocrine pancreatic function with microbial diversity or individual genera were calculated by permutational analysis of variance or linear regression, respectively.

Results: Differences in pancreatic elastase levels associated with significantly (P < .0001) greater changes in microbiota diversity than with participant age, body mass index, sex, smoking, alcohol consumption, or dietary factors. Significant changes in the abundance of 30 taxa, such as an increase in Prevotella (q < .0001) and a decrease of Bacteroides (q < .0001), indicated a shift from a type-1 to a type-2 enterotype. Changes in pancreatic fluid secretion alone were also associated with changes in microbial diversity (P = .0002), although to a lesser degree.

Conclusions: In an analysis of fecal samples from 1795 volunteers, pancreatic acinar cell, rather than duct cell, function is presently the single most significant host factor to be associated with changes in intestinal microbiota composition.
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http://dx.doi.org/10.1053/j.gastro.2018.10.047DOI Listing
March 2019
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