Biology subjects

Ellinghaus, D.

Publications and source records attributed to Ellinghaus, D..

11 recordsLinked to original sources

bioRxiv2025

Decoding the restriction of T cell receptors to human leukocyte antigen alleles using statistical learning

Conventional T cells recognize peptides presented by the human leukocyte antigen (HLA) proteins through their T cell receptors (TCRs). Given that thousands of HLA proteins have been discovered, each presenting thousands of different peptide antigens, decoding the cognate HLA protein of a TCR experimentally is a challenging task. To address this problem, we combined statistical learning methods with a unique dataset of paired T cell repertoires and HLA allele information for 6,794 individuals. This enabled us to discover 53,870 T cell receptor alpha (TRA) and 1,095,576 beta (TRB) clonotypes that were associated with 437 unique HLA alleles. The identified clonotypes were targeting prevalent infections, e.g. influenza, cytomegalovirus and Epstein-Barr virus. Utilizing these clonotypes, we developed statistical models that impute the carriership of common HLA alleles from the TRA- or TRB-repertoire. In conclusion, the identified allele-associated clonotypes encode the HLA fingerprints and the immune exposure history of individuals and populations.

immunology↗

bioRxiv2024

Neolithic introgression of IL23R-related protection against chronic inflammatory bowel diseases in modern Europeans

BackgroundThe hypomorphic variant rs11209026-A in the IL23R gene provides significant protection against immune-related diseases in Europeans, notably inflammatory bowel disease (IBD). Today, the A-allele occurs with an average frequency of 5% in Europe. MethodsThis study comprised 251 ancient genomes from Europe spanning over 14,000 years. In these samples, the investigation focused on admixture informed analyses and selection scans of rs11209026-A and its haplotypes. Findingsrs11209026-A was found at high frequencies in Anatolian Farmers (AF, 18%) where it was likely under weak positive selection. AF later introduced the allele into the ancient European gene-pool. Subsequent admixture caused its frequency to decrease and formed the current southwest-to-northeast allele frequency cline in Europe. The geographic distribution of rs11209026-A may influence the gradient in IBD incidence rates that are highest in northern and eastern Europe. InterpretationGiven the dramatic changes from hunting and gathering to agriculture during the Neolithic, AF might have been exposed to selective pressures from a pro-inflammatory lifestyle and diet. Therefore, the protective A-allele may have increased survival by reducing intestinal inflammation and microbiome dysbiosis. The adaptively evolved function of the variant likely contributes to the high efficacy and low side-effects of modern IL-23 neutralization therapies for chronic inflammatory diseases. This study highlights how evolutionary informed research can provide promising targets for new therapeutic strategies. FundingDeutsche Forschungsgemeinschaft (DFG German Research Foundation) under Germanys Excellence Strategy - EXC 2167 390884018 and EXC 2150 390870439.

evolutionary biology↗

bioRxiv2023

Intestinal epithelial Atg16l1 influences pregnancy-induced fecal microbiota shifts in mice

Throughout gestation, the female body undergoes a series of transformations, including profound alterations in intestinal microbial communities. Changes gradually increase towards the end of pregnancy and comprise reduced -diversity of microbial communities and an increased propensity for energy harvest. Despite the importance of the intestinal microbiota for the pathophysiology of inflammatory bowel diseases, very little is known about the relationship between these microbiota shifts and pregnancy-associated complications of the disease. Here, we explored the longitudinal dynamics of gut microbiota composition and functional potential during pregnancy and after lactation in Atg16l1{Delta}IECmice carrying an intestinal epithelial deletion of the Croh[n]s disease risk gene Atg16l1. Using 16S rRNA amplicon and shotgun metagenomic sequencing, we demonstrated divergent temporal shifts in microbial composition between Atg16l1 wildtype and Atg16l1{Delta}IECpregnant mice in trimester 3, which was validated in an independent experiment. Observed differences included microbial genera implicated in IBD such as Lachnospiraceae, Roseburia, Ruminococcus, and Turicibacter. Changes partially recovered after lactation. In addition, functional inference of metagenomic data suggest a reduced potential to biosynthesize mucosal protective polyamines and reduced capacity to metabolize acidic polysaccharides (ketogluconate metabolism). On the host side, we found that the immunological response of Atg16l1{Delta}IEC mice is characterized by higher colonic mRNA levels of TNFA, and CXCL1 in trimester 3 and a lower weight of offspring at birth. Understanding pregnancy-dependent microbiome changes in the context of IBD may constitute the first step in the identification of fecal microbial biomarkers and microbiota-directed therapies that could help improving precision care for managing pregnancies in IBD patients.

microbiology↗

bioRxiv2023

GWAIS-Web: A Fast and Secure Web Service for Epistasis Detection in Genome-wide Association Interaction Studies

MotivationGenome-wide association interaction studies (GWAIS) are becoming increasingly important as estimates of genetic interactions at the genome-wide level using genome-wide data from hundreds of thousands of individuals from large biobanks showed that non-additive genetic variance plays a role in complex human traits in addition to additive genetic effects identified in genome-wide association studies (GWAS). However, a comprehensive genome-wide search for all combinations of second-order (SNPxSNP) or third-order (SNPxSNPxSNP) associations using millions of SNP markers is a very computationally intensive task, especially when hundreds of thousands or, in the near future, even millions of individuals can be studied with GWAS datasets. The runtime so far exceeds years, even if the search is performed on a multicore CPU server system. ResultsWe developed GWAIS-Web, a web service for fast analysis of genome-wide interactions with case-control GWAS datasets. By using a hybrid combination of graphics-processing units (GPUs) and field-programmable gate arrays (FPGAs), GWAIS-Web speeds up epistasis detection methods for binary traits by a factor of more than 2000, allowing an exhaustive SNP-SNP GWAIS with a GWAS data set of one million SNPs and 500,000 individuals to complete within one day, which would take more than five years on a regular CPU server system. The user can choose between different methods for epistasis detection, such as logistic regression, BOOST, mutual information (MI) and others, with calculations in double precision and including on-the-fly filtering of correlated results based on linkage disequilibrium (LD). Due to the underlying common data structure of GWAIS-Web, all methods can be combined and processed together on-the-fly without increasing the runtime. The user can choose between 2nd order (pairwise) and 3rd order tests and can also limit the search to selected chromosomal regions. GWAIS-Web offers a high level of security through optional 2-factor authentication, encrypted connections and the protection of GWAS/user account data in accordance with the European General Data Protection Regulation (GDPR). AvailabilityGWAIS-Web is freely available at https://hybridcomputing.ikmb.uni-kiel.de. The stand-alone software HybridGWAIS can be downloaded at https://github.com/ikmb/hybridgwais. Supplementary informationSupplementary data are available online.

genetics↗

bioRxiv2022

Predicting Peptide HLA-II Presentation Using Immunopeptidomics, Transcriptomics and Deep Multimodal Learning

The human leukocyte antigen (HLA) class II proteins present peptides to CD4+ T cells through an interaction with T cell receptors (TCRs). Thus, HLA proteins are key players in shaping immunogenicity and immunodominance. Nevertheless, factors governing peptide presentation by HLA-II proteins are still poorly understood. To address this problem, we profiled the blood transcriptome and immunopeptidome of 20 healthy individuals and integrated the profiles with publicly available immunopeptidomics datasets. In depth multi-omics analysis identified expression levels and subcellular locations as import sequence-independent features governing presentation. Levering this knowledge, we developed the Peptide Immune Annotator Multimodal (PIA-M) tool, as a novel pan multimodal transformer-based framework that utilises sequence-dependent along with sequence-independent features to model presentation by HLA-II proteins. PIA-M illustrated a consistently superior performance relative to existing tools across two independent test datasets (area under the curve: 0.93 vs. 0.84 and 0.95 vs. 0.86), respectively. Besides achieving a higher predictive accuracy, PIA-M with its Rust-based pre-processing engine, had significantly shorter runtimes. PIA-M is freely available with a permissive licence as a standalone pipeline and as a webserver (https://hybridcomputing.ikmb.uni-kiel.de/pia). In conclusion, PIA-M enables a new state-of-the-art accuracy in predicting peptide presentation by HLA-II proteins in vivo.

bioinformatics↗

bioRxiv2022

MAGScoT - a fast, lightweight, and accurate bin-refinement software

We introduce MAGScoT, a fast, lightweight and accurate implementation for the reconstruction of highest-quality metagenome-assembled genomes (MAGs) from the output of multiple genome-binning softwares. MAGScoT outperforms popular bin-refinement solutions in terms of quality and quantity of MAGs as well as computation time and resource consumption. MAGScoT is available via GitHub (https://github.com/ikmb/MAGScoT) and as an easy-to-use Docker container (https://hub.docker.com/repository/docker/ikmb/magscot).

bioinformatics↗

bioRxiv2022

EagleImp-Web: A Fast and Secure Genotype Phasing and Imputation Web Service using Field-Programmable Gate Arrays

Imputation web servers have been developed that allow phasing and imputation of genome-wide data without the need for own computing resources. However, their terms of use, data sharing with third parties, the security architecture of the web service, and the algorithms and parameter settings used are only partially disclosed. We developed EagleImp-Web, a fast, secure and convenient web service for phasing and imputation of genome-wide data. The web service uses technical improvements in phasing and imputation algorithms and a field-programmable gate array (FPGA) accelerator design to reduce computation time without loss of phasing and imputation quality. Other key features include no exposure of user information and input/output data to third parties, high data security and fast secure download, user authentication through 2-factor authentication, full control in managing user accounts, and full transparency of algorithms and their settings. EagleImp-Web provides simple and convenient functionalities for monitoring running jobs and selecting parameter settings and output information. Due to the speed advantage over a purely CPU-based implementation, EagleImp-Web offers the user the ability to choose a more resource-intensive parameter setting in exchange for computation time to further improve phasing and imputation quality. EagleImp-Web is freely availabe at https://hybridcomputing.ikmb.uni-kiel.de.

bioinformatics↗

bioRxiv2022

EagleImp: Fast and Accurate Genome-wide Phasing and Imputation in a Single Tool

BackgroundReference-based phasing and genotype imputation algorithms have been developed with sublinear theoretical runtime behaviour, but runtimes are still high in practice when large genome-wide reference datasets are used. MethodsWe developed EagleImp, a software with algorithmic and technical improvements and new features for accurate and accelerated phasing and imputation in a single tool. ResultsWe compared accuracy and runtime of EagleImp with Eagle2, PBWT and prominent imputation servers using whole-genome sequencing data from the 1000 Genomes Project, the Haplotype Reference Consortium and simulated data with more than 1 million reference genomes. EagleImp is 2 to 10 times faster (depending on the single or multiprocessor configuration selected) than Eagle2/PBWT, with the same or better phasing and imputation quality in all tested scenarios. For common variants investigated in typical GWAS studies, EagleImp provides same or higher imputation accuracy than the Sanger Imputation Service, Michigan Imputation Server and the newly developed TOPMed Imputation Server, despite larger (not publicly available) reference panels. It has many new features, including automated chromosome splitting and memory management at runtime to avoid job aborts, fast reading and writing of large files, and various user-configurable algorithm and output options. ConclusionsDue to the technical optimisations, EagleImp can perform fast and accurate reference-based phasing and imputation for future very large reference panels with more than 1 million genomes. EagleImp is freely available for download from https://github.com/ikmb/eagleimp.

bioinformatics↗

bioRxiv2019

Neolithic genomes reveal a distinct ancient HLA allele pool and population transformation in Europe

The Wartberg culture (WBC, 3,500-2,800 BCE) dates to the Late Neolithic period, a time of important demographic and cultural transformations in western Europe. We perform a genome-wide analysis of 42 individuals who were interred in a WBC collective burial in Niedertiefenbach, Germany (3,300-3,200 cal. BCE). Our results highlight that the Niedertiefenbach population indeed emerged at the beginning of the WBC. This farming community was genetically heterogeneous and carried a surprisingly large hunter-gatherer ancestry component (40%). We detect considerable differences in the human leukocyte antigen gene pool between contemporary Europeans and the Niedertiefenbach individuals whose immune response was primarily geared towards defending viral infections.

evolutionary biology↗

bioRxiv2019

A genome-wide genetic pleiotropy approach identified shared loci between multiple system atrophy and inflammatory bowel disease

We aimed to identify shared genetic background between multiple system atrophy (MSA) and autoimmune diseases by using the conjFDR approach. Our study showed significant genetic overlap between MSA and inflammatory bowel disease and identified DENND1B, C7, and RSP04 loci, which are linked to significant changes in methylation or expression levels of adjacent genes. We obtained evidence of enriched heritability involving immune/digestive categories. Finally, an MSA mouse model showed dysregulation of the C7 gene in the degenerating midbrain compared to wildtype mice. The results identify novel molecular mechanisms and implicate immune and gut dysfunction in MSA pathophysiology.

genetics↗

bioRxiv2018

Whole Genome Sequencing of Primary Immunodeficiency reveals a role for common and rare variants in coding and non-coding sequences

Primary immunodeficiency (PID) is characterised by recurrent and often life-threatening infections, autoimmunity and cancer, and it presents major diagnostic and therapeutic challenges. Although the most severe forms present in early childhood, the majority of patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent, and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic PID genetic diagnosis is difficult and the role of genetics is not well defined. We addressed these challenges by performing whole genome sequencing (WGS) of a large PID cohort of 1,318 participants. Analysis of coding regions of 886 index cases found disease-causing mutations in known monogenic PID genes in 10.3%, while a Bayesian approach (BeviMed4) identified multiple potential new candidate genes, including IVNS1ABP. Exploration of the non-coding genome revealed deletions in regulatory regions which contribute to disease causation. Finally, a genome-wide association study (GWAS) identified PID-associated loci and uncovered evidence for co-localisation of, and interplay between, novel high penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to variable penetrance and phenotypic complexity in PID. Thus, a cohort-based WGS approach to PID diagnosis can increase diagnostic yield while deepening our understanding of the key pathways influencing human immune responsiveness.

immunology↗