Högskolan i Skövde

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) constitute an appealing tool for drug discovery, disease modeling, and cardiotoxicity screening. However, their physiological immaturity, resembling CMs in the late fetal stage, limits their utility. Herein, we have developed a novel, scalable cell culture medium designed to enhance the maturation of hPSC-CMs. This medium facilitates a metabolic shift towards fatty acid utilization and augments mitochondrial function by targeting Acetyl-CoA carboxylase 2 (ACC2) with a specific small molecule inhibitor. Our findings demonstrate that this maturation protocol significantly advances the metabolic, structural, molecular and functional maturity of hPSC-CMs at various stages of differentiation. Furthermore, it enables the creation of cardiac microtissues with superior structural integrity and contractile properties. Notably, hPSC-CMs cultured in this optimized maturation medium display increased accuracy in modeling a hypertrophic cardiac phenotype following acute endothelin-1 induction and show a strong correlation between in vitro and in vivo target engagement in drug screening efforts. This approach holds promise for improving the utility and translatability of hPSC-CMs in cardiac disease modeling and drug discovery. 

Background: Diabetic foot ulcers (DFU) pose a significant health risk in diabetic patients, with insufficient revascularization during wound healing being the primary cause. This study aimed to assess microvessel sprouting and wound healing capabilities using vascular endothelial growth factor (VEGF-A) and a modified fibroblast growth factor (FGF1). Methods: An ex vivo aortic ring rodent model and an in vivo wound healing model in diabetic mice were employed to evaluate the microvessel sprouting and wound healing capabilities of VEGF-A and a modified FGF1 both as monotherapies and in combination. Results: The combination of VEGF-A and FGF1 demonstrated increased vascular sprouting in the ex vivo mouse aortic ring model, and topical administration of a combination of VEGF-A and FGF1 mRNAs formulated in lipid nanoparticles (LNPs) in mouse skin wounds promoted faster wound closure and increased neovascularization seven days post-surgical wound creation. RNA-sequencing analysis of skin samples at day three post-wound creation revealed a strong transcriptional response of the wound healing process, with the combined treatment showing significant enrichment of genes linked to skin growth. Conclusion: f-LNPs encapsulating VEGF-A and FGF1 mRNAs present a promising approach to improving the scarring process in DFU.

Transcriptional studies of the human heart provide insight into physiological and pathophysiological mechanisms, essential for understanding the fundamental mechanisms of normal cardiac function and how they are altered by disease. To improve the understanding of why men and women may respond differently to the same therapeutic treatment it is crucial to learn more about sex-specific transcriptional differences. In this study the transcriptome of right atrium and left ventricle was compared across sex and regional location. Paired biopsies from five male and five female patients undergoing aortic valve replacement or coronary artery bypass grafting were included. Gene expression analysis identified 620 differentially expressed transcripts in atrial and ventricular tissue in men and 471 differentially expressed transcripts in women. In total 339 of these transcripts overlapped across sex but notably, 281 were unique in the male tissue and 162 in the female tissue, displaying marked sex differences in the transcriptional machinery. The transcriptional activity was significantly higher in atrias than in ventricles as 70% of the differentially expressed genes were upregulated in the atrial tissue. Furthermore, pathway- and functional annotation analyses performed on the differentially expressed genes showed enrichment for a more heterogeneous composition of biological processes in atrial compared with the ventricular tissue, and a dominance of differentially expressed genes associated with infection disease was observed. The results reported here provide increased insights about transcriptional differences between the cardiac atrium and ventricle but also reveal transcriptional differences in the human heart that can be attributed to sex.

Two validated assays, a bridging ELISA and a luciferase-based bioassay, were compared for detection of anti-drug antibodies (ADA) against interferon-beta (IFN-β) in patients with multiple sclerosis. Serum samples were tested from patients enrolled in a prospective study of 18 months. In contrast to the ELISA, when IFN-β-specific rabbit polyclonal and human monoclonal antibodies were tested, the bioassay was the more sensitive to detect IFN-β ADA in patients' sera. For clinical samples, selection of method of ELISA should be evaluated prior to the use of a multi-tiered approach. A titer threshold value is reported that may be used as a predictor for persistently positive neutralizing ADA.

Replacement therapy in severe hemophilia A leads to factor VIII (FVIII) inhibitors in 30% of patients. Factor VIII gene (F8) mutation type, a family history of inhibitors, ethnicity and intensity of treatment are established risk factors, and were included in two published prediction tools based on regression models. Recently investigated immune regulatory genes could also play a part in immunogenicity. Our objective is to identify bio-clinical and genetic markers for FVIII inhibitor development, taking into account potential genetic high order interactions. The study population consisted of 593 and 79 patients with hemophilia A from centers in Bonn and Frankfurt respectively. Data was collected in the European ABIRISK tranSMART database. A subset of 125 severely affected patients from Bonn with reliable information on first treatment was selected as eligible for risk stratification using a hybrid tree-based regression model (GPLTR). In the eligible subset, 58 (46%) patients developed FVIII inhibitors. Among them, 49 (84%) were "high risk" F8 mutation type. 19 (33%) had a family history of inhibitors. The GPLTR model, taking into account F8 mutation risk, family history of inhibitors and product type, distinguishes two groups of patients: a high-risk group for immunogenicity, including patients with positive HLA-DRB1*15 and genotype G/A and A/A for IL-10 rs1800896, and a low-risk group of patients with negative HLA-DRB1*15 / HLA-DQB1*02 and T/T or G/T for CD86 rs2681401. We show associations between genetic factors and the occurrence of FVIII inhibitor development in severe hemophilia A patients taking into account for high-order interactions using a generalized partially linear tree-based approach.

Cell-based models of the blood-brain barrier (BBB) are important for increasing the knowledge of BBB formation, degradation and brain exposure of drug substances. Human models are preferred over animal models because of inter-species differences in BBB structure and function. However, access to human primary BBB tissue is limited and has shown degeneration of BBB functions in vitro. Human induced pluripotent stem cells (iPSCs) can be used to generate relevant cell types to model the BBB with human tissue. We generated a human iPSC-derived model of the BBB that includes endothelial cells in co-culture with pericytes, astrocytes and neurons. Evaluation of barrier properties showed that the endothelial cells in our co-culture model have high transendothelial electrical resistance, functional efflux and ability to discriminate between CNS permeable and non-permeable substances. Whole genome expression profiling revealed transcriptional changes that occur in co-culture, including upregulation of tight junction proteins such as claudins and neurotransmitter transporters. Pathway analysis implicated changes in the WNT, TNF and PI3K-Akt pathways upon co-culture. Our data suggests that co-culture of iPSC-derived endothelial cells promotes barrier formation on a functional and transcriptional level. The information about gene expression changes in co-culture can be used to further improve iPSC-derived BBB models through selective pathway manipulation.

 Efficiency in dealing with batch effects will be the next frontier in large-scale biological data analysis, particularly when involving the integration of different types of datasets. Large-scale omics techniques have quickly developed during the last decade and huge amounts of data are now generated, which has started to revolutionize the area of medical research. With the increase in the volume of data across the whole spectrum of biology, problems related to data analytics are continuously increasing as analysis and interpretation of these large volumes of molecular data has become a real challenge. Tremendous efforts have been made to obtain data from various molecular levels and the most recent trends show that more and more researchers now are trying to integrate data of various molecular types to inform hypotheses and biological questions. Tightly connected to this work are the batch-related biases that commonly are apparent between different datasets, but these problems are often not tackled. In present study the ComBat algorithm was applied and evaluated on two different data integration problems. Results show that the batch effects present in the integrated datasets efficiently could be removed by applying the ComBat algorithm.

Allogenic stem cell transplantation has shown considerable success in a number of hematological malignancies, in particular in leukemia. The beneficial effect is mediated by donor T cells recognizing patient-specific HLA-binding peptides. These peptides are called minor histocompatibility antigens (miHAs) and are typically caused by single nucleotide polymorphisms. Tissue-specific miHAs have successfully been used in anti-tumor therapy without causing unspecific graft-versus-host reactions. However, only a small number of miHAs have been identified to date, limiting the clinical use.

Here we present an immunoinformatics pipeline for the identification of miHAs. The pipeline can be applied to large-scale miHA screening, for example, in the development of diagnostic tests. Another interesting application is the design of personalized miHA-based cancer therapies based on patient-donor pair-specific miHAs detected by this pipeline. The suggested method covers various aspects of genetic variant detection, effects of alternative transcripts, and HLA-peptide binding. A comparison of our computational pipeline and experimentally derived datasets shows excellent agreement and coverage of the computationally predicted miHAs.