Biology subjects

Fugger, L.

Publications and source records attributed to Fugger, L..

7 recordsLinked to original sources

bioRxiv2026

Unconventional presentation of an immunodominant HLA-DR15-restricted nephritogenic proteinase 3 epitope implicated in vasculitis

Proteinase 3 (PR3) anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is associated with HLA-DR15, implicating HLA-DR15-restricted CD4 T cell autoimmunity in the disease. However, the PR3 epitopes presented by HLA-DR15 and the autoreactive CD4 T cell responses they elicit are undefined. Using humanized hPR3.DR15+ mice, we identified PR3216-231 as an immunodominant human PR3-derived CD4 T cell epitope presented by HLA-DR15. Immunopeptidomic profiling confirmed the natural processing and HLA-DR15-restricted presentation of PR3216-231. Structural analyses of HLA-DR15-PR3216-231 complexes revealed an unconventional mode of HLA class II antigen presentation, in which a 10 amino acid peptide core occupies the 9 amino acid binding groove, causing a central kink in the bound peptide. PR3216-231-specific CD4 T cells from both hPR3.DR15+ mice and patients with PR3-ANCA-associated vasculitis exhibited convergent T cell receptor features, and patients with active vasculitis displayed a clonally expanded, PR3216-231-specific CD4 TCR repertoire. Immunization of hPR3.DR15 mice with PR3216-231 induced cell-mediated glomerulonephritis characterized by increased renal infiltration of CD4 T cells and macrophages together with segmental glomerular necrosis. These findings identify a nephritogenic PR3-derived CD4 T cell epitope presented by HLA-DR15 in ANCA-associated vasculitis and define a new extended core binding pattern, broadening our understanding of HLA class II peptide presentation.

immunology↗

bioRxiv2023

The landscape of ancient human pathogens in Eurasia from the Stone Age to historical times

Infectious diseases have had devastating impacts on human populations throughout history, but important questions about their origins and past dynamics remain1. To create the first archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which were detected for the first time in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Intriguingly, zoonotic pathogens are only detected [~]6,500 years ago, peaking [~]5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide the first direct evidence that this lifestyle change resulted in an increased infectious disease burden. Importantly, they also suggest that the spread of these pathogens increased substantially during subsequent millenia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.

evolutionary biology↗

bioRxiv2022

Genetic risk for Multiple Sclerosis originated in Pastoralist Steppe populations

Multiple sclerosis (MS) is a modern neuro-inflammatory and -degenerative disease, which is most prevalent in Northern Europe. Whilst it is known that inherited risk to MS is located within or within close proximity to immune genes, it is unknown when, where and how this genetic risk originated 1. By using the largest ancient genome dataset from the Stone Age 2, along with new Medieval and post-Medieval genomes, we show that many of the genetic risk variants for MS rose to higher frequency among pastoralists located on the Pontic Steppe, and were brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the Steppe population, and later in Europe, likely driven by pathogenic challenges coinciding with dietary, lifestyle, and population density changes. This study highlights the critical importance of this period as a determinant of modern immune responses and its subsequent impact on the risk of developing MS in a changing environment.

evolutionary biology↗

bioRxiv2021

Parental-fetal interplay of immune genes leads to intrauterine growth restriction

Intrauterine growth restriction (IUGR) of fetuses affects 5-10% of pregnancies and is associated with perinatal morbidity, mortality and long-term health issues. Understanding genetic predisposition to IUGR is challenging, owing to extensive gene polymorphisms, linkage disequilibrium, and maternal and paternal influence. Here, we demonstrate that the inhibitory receptor, KIR2DL1, expressed on maternal uterine natural killer (uNK) cells, in interaction with the paternally-inherited HLA-C*05, an HLA-C group 2 allotype, expressed on fetal trophoblast cells, causes IUGR in a humanised mouse model. Micro-CT imaging of the uteroplacental vasculature revealed reduced uterine spiral artery diameter and increased segment length, increasing fetal blood flow resistance. Single cell RNA-Seq from the maternal-fetal interface highlighted expression programs activated by KIR2DL1-induced IUGR in several placental cell types, including degradation of extracellular matrix components, angiogenesis, and uNK cell communication, suggesting a complex response underlying IUGR. As current IUGR treatments are insufficient, our findings provide important insight for drug development.

immunology↗

bioRxiv2018

Systematic classification of shared components of genetic risk for common human diseases

Disease classification is fundamental to clinical practice, but current taxonomies do not necessarily reflect the pathophysiological processes that are common or unique to different disorders, such as those determined by genetic risk factors. Here, we use routine healthcare data from the 500,000 participants in the UK Biobank to map genome-wide associations across 19,628 diagnostic terms. We find that 3,510 independent genetic risk loci affect multiple clinical phenotypes, which we cluster into 629 distinct disease association profiles. We use multiple approaches to link clusters to different underlying biological pathways and show how these clusters define the genetic architecture of common medical conditions, including hypertension and immune-mediated diseases. Finally, we demonstrate how clusters can be utilised to re-define disease relationships and to inform therapeutic strategies.\n\nOne sentence summarySystematic classification of genetic risk factors reveals molecular connectivity of human diseases with clinical implications

genetics↗

bioRxiv2017

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body, by undertaking a Human Cell Atlas Project as an international collaborative effort. The aim would be to define all human cell types in terms of distinctive molecular profiles (e.g., gene expression) and connect this information with classical cellular descriptions (e.g., location and morphology). A comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, as well as provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas.

cell biology↗

bioRxiv2017

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data has the ability to radically transform our understanding of the human phenome, thereby accelerating progress towards precision medicine. However, a critical question when analysing high-dimensional and heterogeneous data is how to interrogate increasingly specific subphenotypes whilst retaining statistical power to detect genetic associations. Here we develop and employ a novel Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to jointly analyse genetic variants against UK Biobank healthcare phenotypes. Our method displays a more than 20% increase in power to detect genetic effects over other approaches, such that we uncover the broader burden of genetic variation: we identify associations with over 2,000 diagnostic terms. We find novel associations with common immune-mediated diseases (IMD), we reveal the extent of genetic sharing between specific IMDs, and we expose differences in disease perception or diagnosis with potential clinical implications.

genetics↗