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Dive into the research topics where Matthias Hübenthal is active.

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Featured researches published by Matthias Hübenthal.


Nature Genetics | 2016

Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota

Jun Wang; Louise B. Thingholm; Jurgita Skiecevičienė; Philipp Rausch; Martin Kummen; Johannes R. Hov; Frauke Degenhardt; Femke-Anouska Heinsen; Malte C. Rühlemann; Silke Szymczak; Kristian Holm; Tonu Esko; Jun Sun; Mihaela Pricop-Jeckstadt; Samer Al-Dury; Pavol Bohov; Jörn Bethune; Felix Sommer; David Ellinghaus; Rolf K. Berge; Matthias Hübenthal; Manja Koch; Karin Schwarz; Gerald Rimbach; Patricia Hübbe; Wei-Hung Pan; Raheleh Sheibani-Tezerji; Robert Häsler; Philipp Rosenstiel; Mauro D'Amato

Human gut microbiota is an important determinant for health and disease, and recent studies emphasize the numerous factors shaping its diversity. Here we performed a genome-wide association study (GWAS) of the gut microbiota using two cohorts from northern Germany totaling 1,812 individuals. Comprehensively controlling for diet and non-genetic parameters, we identify genome-wide significant associations for overall microbial variation and individual taxa at multiple genetic loci, including the VDR gene (encoding vitamin D receptor). We observe significant shifts in the microbiota of Vdr−/− mice relative to control mice and correlations between the microbiota and serum measurements of selected bile and fatty acids in humans, including known ligands and downstream metabolites of VDR. Genome-wide significant (P < 5 × 10−8) associations at multiple additional loci identify other important points of host–microbe intersection, notably several disease susceptibility genes and sterol metabolism pathway components. Non-genetic and genetic factors each account for approximately 10% of the variation in gut microbiota, whereby individual effects are relatively small.


Nucleic Acids Research | 2017

A comprehensive, cell specific microRNA catalogue of human peripheral blood

Simonas Juzenas; Geetha Venkatesh; Matthias Hübenthal; Marc P. Hoeppner; Zhipei Gracie Du; Maren Paulsen; Philip Rosenstiel; Philipp Senger; Martin Hofmann-Apitius; Andreas Keller; Andre Franke; Georg Hemmrich-Stanisak

Abstract With this study, we provide a comprehensive reference dataset of detailed miRNA expression profiles from seven types of human peripheral blood cells (NK cells, B lymphocytes, cytotoxic T lymphocytes, T helper cells, monocytes, neutrophils and erythrocytes), serum, exosomes and whole blood. The peripheral blood cells from buffy coats were typed and sorted using FACS/MACS. The overall dataset was generated from 450 small RNA libraries using high-throughput sequencing. By employing a comprehensive bioinformatics and statistical analysis, we show that 3′ trimming modifications as well as composition of 3′ added non-templated nucleotides are distributed in a lineage-specific manner—the closer the hematopoietic progenitors are, the higher their similarities in sequence variation of the 3′ end. Furthermore, we define the blood cell-specific miRNA and isomiR expression patterns and identify novel cell type specific miRNA candidates. The study provides the most comprehensive contribution to date towards a complete miRNA catalogue of human peripheral blood, which can be used as a reference for future studies. The dataset has been deposited in GEO and also can be explored interactively following this link: http://134.245.63.235/ikmb-tools/bloodmiRs.


Gut | 2017

Dense genotyping of immune-related loci identifies HLA variants associated with increased risk of collagenous colitis

Helga Westerlind; Marie-Rose Mellander; Francesca Bresso; Andreas Münch; Ferdinando Bonfiglio; Ghazaleh Assadi; Joseph Rafter; Matthias Hübenthal; Wolfgang Lieb; Henrik Källberg; Boel Brynedal; Leonid Padyukov; Jonas Halfvarson; Leif Törkvist; Jan Björk; Anna Andreasson; Lars Agréus; Sven Almer; Stephan Miehlke; Ahmed Madisch; Bodil Ohlsson; Robert Löfberg; Rolf Hultcrantz; Andre Franke; Mauro D'Amato

Objective Collagenous colitis (CC) is a major cause of chronic non-bloody diarrhoea, particularly in the elderly female population. The aetiology of CC is unknown, and still poor is the understanding of its pathogenesis. This possibly involves dysregulated inflammation and immune-mediated reactions in genetically predisposed individuals, but the contribution of genetic factors to CC is underinvestigated. We systematically tested immune-related genes known to impact the risk of several autoimmune diseases for their potential CC-predisposing role. Design Three independent cohorts of histologically confirmed CC cases (N=314) and controls (N=4299) from Sweden and Germany were included in a 2-step association analysis. Immunochip and targeted single nucleotide polymorphism (SNP) genotype data were produced, respectively, for discovery and replication purposes. Classical human leucocyte antigen (HLA) variants at 2-digit and 4-digit resolution were obtained via imputation from single marker genotypes. SNPs and HLA variants passing quality control filters were tested for association with CC with logistic regression adjusting for age, sex and country of origin. Results Forty-two markers gave rise to genome-wide significant association signals, all contained within the HLA region on chromosome 6 (best p=4.2×10−10 for SNP rs4143332). Among the HLA variants, most pronounced risk effects were observed for 8.1 haplotype alleles including DQ2.5, which was targeted and confirmed in the replication data set (p=2.3×10−11; OR=2.06; 95% CI (1.67 to 2.55) in the combined analysis). Conclusions HLA genotype associates with CC, thus implicating HLA-related immune mechanisms in its pathogenesis.


PLOS ONE | 2015

Sparse Modeling Reveals miRNA Signatures for Diagnostics of Inflammatory Bowel Disease

Matthias Hübenthal; Georg Hemmrich-Stanisak; Frauke Degenhardt; Silke Szymczak; Zhipei Du; Abdou ElSharawy; Andreas Keller; Stefan Schreiber; Andre Franke

The diagnosis of inflammatory bowel disease (IBD) still remains a clinical challenge and the most accurate diagnostic procedure is a combination of clinical tests including invasive endoscopy. In this study we evaluated whether systematic miRNA expression profiling, in conjunction with machine learning techniques, is suitable as a non-invasive test for the major IBD phenotypes (Crohns disease (CD) and ulcerative colitis (UC)). Based on microarray technology, expression levels of 863 miRNAs were determined for whole blood samples from 40 CD and 36 UC patients and compared to data from 38 healthy controls (HC). To further discriminate between disease-specific and general inflammation we included miRNA expression data from other inflammatory diseases (inflammation controls (IC): 24 chronic obstructive pulmonary disease (COPD), 23 multiple sclerosis, 38 pancreatitis and 45 sarcoidosis cases) as well as 70 healthy controls from previous studies. Classification problems considering 2, 3 or 4 groups were solved using different types of penalized support vector machines (SVMs). The resulting models were assessed regarding sparsity and performance and a subset was selected for further investigation. Measured by the area under the ROC curve (AUC) the corresponding median holdout-validated accuracy was estimated as ranging from 0.75 to 1.00 (including IC) and 0.89 to 0.98 (excluding IC), respectively. In combination, the corresponding models provide tools for the distinction of CD and UC as well as CD, UC and HC with expected classification error rates of 3.1 and 3.3%, respectively. These results were obtained by incorporating not more than 16 distinct miRNAs. Validated target genes of these miRNAs have been previously described as being related to IBD. For others we observed significant enrichment for IBD susceptibility loci identified in earlier GWAS. These results suggest that the proposed miRNA signature is of relevance for the etiology of IBD. Its diagnostic value, however, should be further evaluated in large, independent, clinically well characterized cohorts.


Oncotarget | 2017

MiRNA profiling of gastrointestinal stromal tumors by next-generation sequencing

Ugne Gyvyte; Simonas Juzenas; Violeta Salteniene; Juozas Kupcinskas; Lina Poskiene; Laimutis Kucinskas; Sonata Jarmalaite; Kristina Stuopelyte; Ruta Steponaitiene; Georg Hemmrich-Stanisak; Matthias Hübenthal; Alexander Link; Sabine Franke; Andre Franke; Dalia Pangonyte; Vaiva Lesauskaite; Jurgita Skieceviciene

Deregulation of miRNAs has been observed virtually in all major types of cancer, whereas the miRNA signature in GIST is not well characterized yet. In this study the first high-throughput miRNA profiling of 15 paired GIST and adjacent normal tissue samples was performed using small RNA-seq approach and differentially expressed miRNAs as well as isomiRNAs were defined. Highly significantly deregulated miRNAs were selected for validation by Taq-Man low-density array in replication group of 40 paired samples. Validated miRNAs were further subjected to enrichment analysis, which revealed significantly enriched KEGG pathways in the main GIST associated pathways. Further, we used an integrated analysis of miRNA-mRNA correlations for KIT and PDGFRA target genes and found a significant correlation between all of the enriched miRNAs and their target gene KIT. Results of the phenotype analysis showed miR-509-3p to be up-regulated in epithelioid and mixed cell types compared to spindle type, whereas miR-215-5p showed negative correlation with risk grade of GIST. These data reveal a detailed miRNA profile of GIST and highlight new candidates that may be important in the development of malignant disease.


Nucleic Acids Research | 2017

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs

Tobias Fehlmann; Christina Backes; Mustafa Kahraman; Jan Haas; Nicole Ludwig; Andreas E. Posch; Maximilian Würstle; Matthias Hübenthal; Andre Franke; Benjamin Meder; Eckart Meese; Andreas Keller

Abstract The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.


international conference on conceptual structures | 2017

Fast Genome-Wide Third-order SNP Interaction Tests with Information Gain on a Low-cost Heterogeneous Parallel FPGA-GPU Computing Architecture

Lars Wienbrandt; Jan Christian Kässens; Matthias Hübenthal; David Ellinghaus

Abstract Complex diseases may result from many genetic variants interacting with each other. For this reason, genome-wide interaction studies (GWIS) are currently performed to detect pairwise SNP interactions. While the computations required here can be completed within reasonable time, it has been inconvenient yet to detect third-order SNP interactions for large-scale datasets due to the cubic complexity of the problem. In this paper we introduce a feasible method for third-order GWIS analysis of genotyping data on a low-cost heterogeneous computing system that combines a Virtex-7 FPGA and a GeForce GTX 780 Ti GPU, with speedups between 70 and 90 against a CPU-only approach and a speedup of approx. 5 against a GPU-only approach. To estimate effect sizes of third-order interactions we employed information gain (IG), a measure that has been applied on a genome-wide scale only for pairwise interactions in the literature yet.


Gut | 2018

Sucrase-isomaltase 15Phe IBS risk variant in relation to dietary carbohydrates and faecal microbiota composition

Louise B. Thingholm; Malte C. Rühlemann; Jun Wang; Matthias Hübenthal; Wolfgang Lieb; Matthias Laudes; Andre Franke; Mauro D’Amato

Recently in Gut , a coding sucrase-isomaltase ( SI ) variant (15Phe at single nucleotide polymorphism rs9290264) with 35% reduced disaccharidase activity was reported to increase IBS risk and to correlate with more frequent stools. These observations were not assessed in relation to key dietary factors including carbohydrate (ie, SI substrates) consumption.1 Here, we studied two large German population-based cross-sectional cohorts, namely PopGen (n=639; average age 61.4; 44.8% female) and FoCus (n=759; average age 53.0; 58.5% female), with available genotype (genome-wide arrays), dietary (12-month food frequency questionnaire, FFQ), faecal microbiota (16S sequencing) and IBS status (self-reported from questionnaire) data, as previously described in detail.2–4 In a combined age/sex/body mass index (BMI)-adjusted logistic regression analysis of the two data sets, carriers of the 15Phe variant (52.86%) reported IBS significantly more often than non-carriers (3.69% vs 1.84%, respectively; P=0.044, OR=2.04), thus replicating and extending previous findings.1 When taking into account the consumption of SI substrate carbohydrates (polysaccharides and disaccharides; g/day) estimated from FFQ, this association appeared strongest for individuals with lowest intake (not shown). In particular, as illustrated in figure 1, starch was the individual carbohydrate component where the largest difference in IBS prevalence …


Bioinformatics | 2018

A high-resolution map of the human small non-coding transcriptome

Tobias Fehlmann; Christina Backes; Julia Alles; Ulrike Fischer; Martin Hart; Fabian Kern; Hilde Langseth; Trine B. Rounge; Sinan Uğur Umu; Mustafa Kahraman; Thomas Laufer; Jan Haas; Cord F Staehler; Nicole Ludwig; Matthias Hübenthal; Benjamin Meder; Andre Franke; Hans Peter Lenhof; Eckart Meese; Andreas Keller

Motivation: Although the amount of small non‐coding RNA‐sequencing data is continuously increasing, it is still unclear to which extent small RNAs are represented in the human genome. Results: In this study we analyzed 303 billion sequencing reads from nearly 25 000 datasets to answer this question. We determined that 0.8% of the human genome are reliably covered by 874 123 regions with an average length of 31 nt. On the basis of these regions, we found that among the known small non‐coding RNA classes, microRNAs were the most prevalent. In subsequent steps, we characterized variations of miRNAs and performed a staged validation of 11 877 candidate miRNAs. Of these, many were actually expressed and significantly dysregulated in lung cancer. Selected candidates were finally validated by northern blots. Although isolated miRNAs could still be present in the human genome, our presented set likely contains the largest fraction of human miRNAs. Contact: [email protected]‐saarland.de or [email protected]‐saarland.de Supplementary information: Supplementary data are available at Bioinformatics online.


Gastroenterology | 2018

Female-Specific Association Between Variants on Chromosome 9 and Self-Reported Diagnosis of Irritable Bowel Syndrome

Ferdinando Bonfiglio; Tenghao Zheng; Koldo Garcia-Etxebarria; Fatemeh Hadizadeh; Luis Bujanda; Francesca Bresso; Lars Agréus; Anna Andreasson; Aldona Dlugosz; Greger Lindberg; Peter T. Schmidt; Pontus Karling; Bodil Ohlsson; Magnus Simren; Susanna Walter; Gerardo Nardone; Rosario Cuomo; Paolo Usai-Satta; Francesca Galeazzi; Matteo Neri; Piero Portincasa; M. Bellini; Giovanni Barbara; Anna Latiano; Matthias Hübenthal; Vincent Thijs; M.G. Netea; Daisy Jonkers; Lin Chang; Emeran A. Mayer

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