The aim of this study was to characterize the ophthalmic and genetic features of Bardet Biedl (BBS) syndrome in a cohort of patients from a German specialized ophthalmic care center. Sixty-one patients, aged 5–56 years, underwent a detailed ophthalmic examination including visual acuity and color vision testing, electroretinography (ERG), visually evoked potential recording (VEP), fundus examination, and spectral domain optical coherence tomography (SD-OCT). Adaptive optics flood illumination ophthalmoscopy was performed in five patients. All patients had received diagnostic genetic testing and were selected upon the presence of apparent biallelic variants in known BBSassociated genes. All patients had retinal dystrophy with morphologic changes of the retina. Visual acuity decreased from ~0.2 (decimal) at age 5 to blindness 0 at 50 years. Visual field examination could be performed in only half of the patients and showed a concentric constriction with remaining islands of function in the periphery. ERG recordings were mostly extinguished whereas VEP recordings were reduced in about half of the patients. The cohort of patients showed 51 different likely biallelic mutations—of which 11 are novel—in 12 different BBS-associated genes. The most common associated genes were BBS10 (32.8%) and BBS1 (24.6%), and by far the most commonly observed variants were BBS10 c.271dup;p.C91Lfs*5 (21 alleles) and BBS1 c.1169T>G;p.M390R (18 alleles). The phenotype associated with the different BBS-associated genes and genotypes in our cohort is heterogeneous, with diverse features without genotype–phenotype correlation. The results confirm and expand our knowledge of this rare disease.

Inflammation is a crucial physiological defense mechanism of the human body to injury or infection. However, dysregulation of the magnitude or duration of inflammation response underlies multiple disease pathologies and may cause organ damage. Sepsis is a severe inflammatory disease now known as a clinical syndrome defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis patients often die of organ failure and the endothelium and neutrophil-endothelial cell (EC) interactions play an active role in the regulation of the systemic inflammatory response. Systemic inflammatory disease often results in alterations in vascular endothelium barrier function, increased permeability, excessive leukocyte trafficking, and reactive oxygen species production, leading to organ damage. While neutrophils are critical to host defense, neutrophil dysregulation has a critical role in organ damage through release of proteases, neutrophil extracellular traps (NETs), and reactive oxygen species (ROS), which can damage host tissue leading to organ failure. To date therapeutic approaches are largely supportive and therapeutics targeting endothelium inflammation and immune cell dysregulation are urgently needed. However, strong concerns regarding the level of phenotypic heterogeneity of microvascular ECs between different organs have been expressed. Microvascular EC heterogeneity in different organs and organ-specific variations in EC structure and function are regulated by intrinsic signals that are differentially expressed across organs and species, as a result of which neutrophil recruitment to discrete organs may be regulated differently. In addition, therapeutic development is hindered due to the heterogeneous nature of sepsis and the presence of multiple distinct immune phenotypes that can impact function and response to infection. In fact, clinically sepsis is a heterogeneous syndrome and diagnosis is complicated due to the broad spectrum of non-specific clinical features. Patients with similar clinical symptoms can be associated with distinct immune cell phenotypes ranging from excessive immune activation to immunosuppression, which means different therapeutics are required. In this work, the morphological and functional variations of differently originated microvascular endothelium are discussed and how these variances affect systemic function in response to inflammation. Emerging in vivo and in vitro models and techniques including microphysiological devices, proteomics, and RNA-Sequencing used to study the cellular and molecular heterogeneity of endothelium from different organs will also be discussed. Our group have developed a novel Organ-on-Chip, the biomimetic microfluidic assay (bMFA) that mimics physiological conditions, allowing us to observe real-time neutrophil-endothelial interactions, including rolling, adhesion, and migration, and to study endothelial barrier function under physiologically relevant conditions including the effect of shear forces and vascular geometry. The bMFA enables the quantification of leukocyte-EC interactions, including rolling velocity, number of adhered leukocytes in response to different shear rates, number of migrated leukocytes, EC permeability, adhesion molecule expression and other important variables. Furthermore, by using human related samples, such as human ECs and leukocytes, bMFA provides a tool for rapid screening of potential therapeutics to increase their clinical translatability. In this work, a protocol was developed to study endothelium function and neutrophil-endothelial interactions during inflammation in the bMFA. Lastly, to develop targeted therapeutics, immunophenotyping is needed to identify distinct immune cell functional phenotypes. We have developed a methodology to classify ICU sepsis patients into three phenotypes using patient data, Organ-on-Chip-based neutrophil functional analysis and proteomics. The findings of the study will help identify different sepsis patient immune-phenotypes and personalize treatment accordingly. / Mechanical Engineering

Apolipoprotein E (apoE) occurs on the majority of plasma lipoproteins and plays a major role in the lipid metabolism in the periphery and in the central nervous system. ApoE is a polymorphic protein with three common isoforms, apoE2, apoE3 and apoE4, derived from respective alleles '2, '3 and '4. The aim of this study was to develop a sample pretreatment protocol combined with rapid mass spectrometry (MS)-based assay for simultaneous apolipoprotein profiling and apoE phenotype identification. This assay was validated in 481 samples from patients with stable atherosclerotic cardiovascular disease (ASCVD) and applied to study association with mild cognitive impairment (MCI) in the LIFE Adult study, including overall 690 study subjects. Simultaneous quantification of 8–12 major apolipoproteins including apoA-I, apoB-100 and apoE could be performed within 6.5 min. Phenotyping determined with the developed MS assay had good agreement with the genotyping by real-time fluorescence PCR (97.5%). ApoE2 isoform was associated with the highest total apoE concentration compared to apoE3 and apoE4 (p < 0.001). In the subgroup of diabetic atherosclerotic cardiovascular disease (ASCVD) patients, apoE2 isoform was related to higher apoC-I levels (apoE2 vs. apoE3, p < 0.05), while in the subgroup of ASCVD patients under statin therapy apoE2 was related to lower apoB-100 levels (apoE2 vs. apoE3/apoE4, p < 0.05). A significant difference in apoE concentration observed between mild cognitive impairment (MCI) subjects and controls was confirmed for each apoE phenotype. In conclusion, this study provides evidence for the successful implementation of an MS-based apoE phenotyping assay, which can be used to assess phenotype effects on plasma lipid and apolipoprotein levels.

Ontologies are widely used in various domains, including biomedical research, to structure information, represent knowledge, and analyze data. The combination of ontologies from different domains is crucial for systematic data analysis and comparison of similar domains. This process requires ontology composition, integration, and alignment, which involve creating new classes by reusing classes from different domains, aggregating types of ontologies within the same domain, and finding correspondences between ontologies within the same or similar domain. This thesis presents use cases where we applied ontology composition, integration, and alignment of phenotype ontologies, and evaluated the resulting ontologies and alignment. First, we analyzed a large aging dataset of inbred laboratory mice, using Mouse Anatomy and Mouse Pathology ontologies. Second, we integrated phenotype ontologies for human and model organism phenotypes to enable comparisons of phenotypes between and within individual species. We developed Pheno-e, an extension of PhenomeNet. We identified novel abnormal anatomical classes for fly phenotypes, allowing the annotation of fly genes that were not annotated before. We demonstrate the distinct contributions of each species' phenotypic data to detecting human diseases using Pheno-e, and show that mouse phenotypic data contributes the most to the discovery of gene--disease associations. This work could guide the selection of model organisms when building methods to find gene-disease associations. Additionally, we refined class definitions in phenotypic ontologies, specifically targeting cell cardinality phenotypes. This representation resolved incorrect inferences in the utilized ontologies, enabling accurate interpretation of phenotypic descriptions. Our findings reveal that this correction enhances gene-disease prediction for diseases associated with cardinality phenotypes. Third, we introduce a novel neural-symbolic method that combines logic fundamentals with machine learning for ontology alignment. This method begins with symbolic representation, followed by iterative neural learning for alignment and symbolic representation consistency checking and reasoning, and back to neural learning. We demonstrate that our system generates noncontroversial alignments first and these alignments are coherent with respect to OWL EL. This novel method can pave the way for more accurate and efficient ontology-based methods, which can have significant implications for various semantic web applications.

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