Högskolan i Skövde

Human hepatocytes display substantial functional inter-individual variation regarding drug metabolizing functions. In order to investigate if this diversity is mirrored in hepatocytes derived from different human pluripotent stem cell (hPSC) lines, we evaluated 25 hPSC lines originating from 24 different donors for hepatic differentiation and functionality. Homogenous hepatocyte cultures could be derived from all hPSC lines using onestandardized differentiation procedure. To the best of our knowledge this is the first report of a standardized hepatic differentiation procedure that is generally applicable across a large panel of hPSC lines without any adaptations to individual lines. Importantly, with regard to functional aspects, such as Cytochrome P450 activities, we observed that hepatocytes derived from different hPSC lines displayed inter-individual variation characteristic for primary hepatocytes obtained from different donors, while these activities were highly reproducible between repeated experiments using the same line. Taken together, these data demonstrate the emerging possibility to compile panels of hPSC-derived hepatocytes of particular phenotypes/genotypes relevant for drug metabolism and toxicity studies. Moreover, these findings are of significance for applications within the regenerative medicine field, since our stringent differentiation procedure allows the derivation of homogenous hepatocyte cultures from multiple donors which is a prerequisite for the realization of future personalized stem cell based therapies.

BACKGROUND: Dapagliflozin is a selective sodium-glucose cotransporter 2 inhibitor that improves glycemic control in patients with type II diabetes mellitus (T2DM) by reducing renal glucose reabsorption.

OBJECTIVE: The aim was to evaluate the lipid effects of dapagliflozin 10 mg or placebo in patients with T2DM with/without baseline elevated triglyceride and reduced high-density lipoprotein (HDL) cholesterol levels.

METHODS: This was a post hoc analysis of 10 phase 3, placebo-controlled studies of dapagliflozin 10 mg (N = 2237) or placebo (N = 2164) administered for 24 weeks in patients with T2DM. Patients with elevated triglyceride (>= 150 mg/dL [1.69 mmol/L]) and reduced HDL cholesterol levels (<40 mg/dL [1.04 mmol/L] in men; <50 mg/dL [1.29 mmol/L] in women) were included (group A). The reference group (group B) included patients who did not meet the defined lipid criteria.

RESULTS: The effects of dapagliflozin on fasting lipid profiles were generally similar in the 2 lipid groups (ie, groups A and B) and, compared with placebo, were associated with minor increases in non-HDL cholesterol, low-density lipoprotein, and HDL cholesterol levels. The effects on triglyceride levels were inconsistent. The incidence of adverse events (AEs)/serious AEs, and AEs of genital infection, urinary tract infection, volume reduction, renal function, and hypoglycemia were similar in the 2 lipid groups.

CONCLUSION: Patients with T2DM treated with dapagliflozin experienced minor changes in lipid levels; the changes were generally similar in the 2 lipid groups. The clinical significance of these changes in lipids is unclear, especially in view of the positive effects of dapagliflozin on other cardiovascular disease risk factors. 

Objective: After myocardial infarction (MI), the non-infarcted left ventricle (LV) ensures appropriate contractile function of the heart. Metabolic disturbance in this region greatly exacerbates post-MI heart failure (HF) pathology. This study aimed to provide a comprehensive understanding of the metabolic derangements occurring in the non-infarcted LV that could trigger cardiovascular deterioration. Methods and Results: We used a pig model that progressed into chronic HF over 3 months following MI induction. Integrated gene and metabolite signatures revealed region-specific perturbations in amino acid- and lipid metabolism, insulin signaling and, oxidative stress response. Remote LV, in particular, showed impaired glutamine and arginine metabolism, altered synthesis of lipids, glucose metabolism disorder, and increased insulin resistance. LPIN1, PPP1R3C, PTPN1, CREM, and NR0B2 were identified as the main effectors in metabolism dysregulation in the remote zone and were found differentially expressed also in the myocardium of patients with ischemic and/or dilated cardiomyopathy. In addition, a simultaneous significant decrease in arginine levels and altered PRCP, PTPN1, and ARF6 expression suggest alterations in vascular function in remote area. Conclusions: This study unravels an array of dysregulated genes and metabolites putatively involved in maladaptive metabolic and vascular remodeling in the non-infarcted myocardium and may contribute to the development of more precise therapies to mitigate progression of chronic HF post-MI.

Aims: Dapagliflozin is a selective inhibitor of sodium glucose co-transporter 2 (SGLT2). This study assessed the efficacy and safety of dapagliflozin 10 mg vs placebo in patients with type 2 diabetes (T2D) and moderate renal impairment (estimated glomerular filtration rate [eGFR], 45-59 mL/min/1.73 m(2); chronic kidney disease [CKD] stage 3A). Materials and methods: In this double-blind, parallel group, Phase 3 study (NCT02413398, ) patients with inadequately controlled T2D (HbA1c 7.0%-11.0%) were randomized (1:1) to dapagliflozin 10 mg once daily (N = 160) or matching placebo (N = 161) for 24 weeks. Randomization was stratified by pre-enrolment glucose-lowering therapy. The primary endpoint was change from baseline in HbA1c at Week 24. Results: At Week 24, compared with placebo, dapagliflozin significantly decreased HbA1c (difference [95% CI], -0.34% [-0.53, -0.15]; P < 0.001), body weight (difference [95% CI], -1.25 kg [-1.90, -0.59]; P < 0.001), fasting plasma glucose (difference [95% CI], -0.9 mmol/L [-1.5, -0.4]; P = 0.001) and systolic blood pressure (difference [95% CI], -3.1 mmHg [-6.3, 0.0]; P < 0.05). Decreases from baseline in eGFR were greater with dapagliflozin than placebo at Week 24 (-2.49 mL/min/1.73 m(2) [-4.96, -0.02]), however, eGFR returned to baseline levels at Week 27 (3 weeks post-treatment) (0.61 mL/min/1.73 m(2) [-1.59, 2.81]). No increase in adverse events (AEs; 41.9% vs 47.8%) or serious AEs (5.6% vs 8.7%) were reported with dapagliflozin versus placebo. No AEs of bone fractures, amputations or DKA were reported. Conclusions: The findings of this study (NCT02413398, ) support the positive benefit/risk profile of dapagliflozin for the treatment of patients with T2D and CKD 3A.

Human pluripotent stem cell-derived hepatocytes (hPSC-HEP) display many properties of mature hepatocytes, including expression of important genes of the drug metabolizing machinery, glycogen storage, and production of multiple serum proteins. To this date, hPSC-HEP do not, however, fully recapitulate the complete functionality of in vivo mature hepatocytes. In this study, we applied versatile bioinformatic algorithms, including functional annotation and pathway enrichment analyses, transcription factor binding-site enrichment, and similarity and correlation analyses, to datasets collected from different stages during hPSC-HEP differentiation and compared these to developmental stages and tissues from fetal and adult human liver. Our results demonstrate a high level of similarity between the in vitro differentiation of hPSC-HEP and in vivo hepatogenesis. Importantly, the transcriptional correlation of hPSC-HEP with adult liver (AL) tissues was higher than with fetal liver (FL) tissues (0.83 and 0.70, respectively). Functional data revealed mature features of hPSC-HEP including cytochrome P450 enzymes activities and albumin secretion. Moreover, hPSC-HEP showed expression of many genes involved in drug absorption, distribution, metabolism, and excretion. Despite the high similarities observed, we identified differences of specific pathways and regulatory players by analyzing the gene expression between hPSC-HEP and AL. These findings will aid future intervention and improvement of in vitro hepatocyte differentiation protocol in order to generate hepatocytes displaying the complete functionality of mature hepatocytes. Finally, on the transcriptional level, our results show stronger correlation and higher similarity of hPSC-HEP to AL than to FL. In addition, potential targets for further functional improvement of hPSC-HEP were also identified. 

Hepatocytes derived from human pluripotent stem cells (hPSC-HEP) have the potential to replace presently used hepatocyte sources applied in liver disease treatment and models of drug discovery and development. Established hepatocyte differentiation protocols are effective and generate hepatocytes, which recapitulate some key features of their in vivo counterparts. However, generating mature hPSC-HEP remains a challenge. In this study, we applied transcriptomics to investigate the progress of in vitro hepatic differentiation of hPSCs at the developmental stages, definitive endoderm, hepatoblasts, early hPSC-HEP, and mature hPSC-HEP, to identify functional targets that enhance efficient hepatocyte differentiation. Using functional annotation, pathway and protein interaction network analyses, we observed the grouping of differentially expressed genes in specific clusters representing typical developmental stages of hepatic differentiation. In addition, we identified hub proteins and modules that were involved in the cell cycle process at early differentiation stages. We also identified hub proteins that differed in expression levels between hPSC-HEP and the liver tissue controls. Moreover, we identified a module of genes that were expressed at higher levels in the liver tissue samples than in the hPSC-HEP. Considering that hub proteins and modules generally are essential and have important roles in the protein-protein interactions, further investigation of these genes and their regulators may contribute to a better understanding of the differentiation process. This may suggest novel target pathways and molecules for improvement of hPSC-HEP functionality, having the potential to finally bring this technology to a wider use.

Human pluripotent stem cells- (hPSCs-) derived hepatocytes have the potential to replace many hepatic models in drug discovery and provide a cell source for regenerative medicine applications. However, the generation of fully functional hPSC-derived hepatocytes is still a challenge. Towards gaining better understanding of the differentiation and maturation process, we employed a standardized protocol to differentiate six hPSC lines into hepatocytes and investigated the synchronicity of the hPSC lines by applying RT-qPCR to assess the expression of lineage-specific genes (OCT4, NANOG, T, SOX17, CXCR4, CER1, HHEX, TBX3, PROX1, HNF6, AFP, HNF4a, KRT18, ALB, AAT, and CYP3A4) which serve as markers for different stages during liver development. The data was evaluated using correlation and clustering analysis, demonstrating that the expression of these markers is highly synchronized and correlated well across all cell lines. The analysis also revealed a distribution of the markers in groups reflecting the developmental stages of hepatocytes. Functional analysis of the differentiated cells further confirmed their hepatic phenotype. Taken together, these results demonstrate, on the molecular level, the highly synchronized differentiation pattern across multiple hPSC lines. Moreover, this study provides additional understanding for future efforts to improve the functionality of hPSC-derived hepatocytes and thereby increase the value of related models.

The global burden of diabetes has drastically increased over the past decades and in 2017 approximately 4 million deaths were caused by diabetes and cardiovascular complications. Diabetic cardiomyopathy is a common complication of diabetes with early manifestations of diastolic dysfunction and left ventricular hypertrophy with subsequent progression to systolic dysfunction and ultimately heart failure. An in vitro model accurately recapitulating key processes of diabetic cardiomyopathy would provide a useful tool for investigations of underlying disease mechanisms to further our understanding of the disease and thereby potentially advance treatment strategies for patients. With their proliferative capacity and differentiation potential, human induced pluripotent stem cells (iPSCs) represent an appealing cell source for such a model system and cardiomyocytes derived from induced pluripotent stem cells have been used to establish other cardiovascular related disease models. Here we review recently made advances and discuss challenges still to be overcome with regard to diabetic cardiomyopathy models, with a special focus on iPSC-based systems. Recent publications as well as preliminary data presented here demonstrate the feasibility of generating cardiomyocytes with a diabetic phenotype, displaying insulin resistance, impaired calcium handling and hypertrophy. However, capturing the full metabolic- and functional phenotype of the diabetic cardiomyocyte remains to be accomplished. 

The sodium glucose co-transporter-2 inhibitor dapagliflozin has been shown to decrease urinary albumin-to-creatinine ratio (UACR). This effect, however, varies among individual patients. In this study, we assessed the baseline characteristics and concurrent changes in other cardiovascular risk markers that might be associated with UACR response to dapagliflozin. A pooled analysis of 11 phase 3 randomized, controlled clinical trials was performed. UACR change from baseline after 24 weeks treatment with dapagliflozin 10 mg/d in 531 patients with type 2 diabetes and UACR ≥30 mg/g at baseline was determined. UACR response was defined as >30% reduction from baseline at 24 weeks, whereas UACR non-response was defined as ≤30% reduction at 24 weeks. A total of 288 (54%) patients were classified as responders and 243 (46%) as non-responders. At 24 weeks, the UACR-adjusted mean change from baseline was −71.2% and 25.9% in responders and non-responders, respectively. Baseline characteristics were similar between both groups. Changes in HbA1c and body weight were comparable across groups. Responders showed a numerically larger reduction in estimated glomerular filtration rate and systolic blood pressure versus non-responders. UACR reduction to dapagliflozin is an individual characteristic that cannot be predicted by baseline clinical features or changes in metabolic variables. Whether UACR response would improve long-term renal and cardiovascular outcomes remains to be determined. 

Reference genes, often referred to as housekeeping genes (HKGs), are frequently used to normalize gene expression data based on the assumption that they are expressed at a constant level in the cells. However, several studies have shown that there may be a large variability in the gene expression levels of HKGs in various cell types. In a previous study, employing human embryonic stem cells (hESCs) subjected to spontaneous differentiation, we observed that the expression of commonly used HKG varied to a degree that rendered them inappropriate to use as reference genes under those experimental settings. Here we present a substantially extended study of the HKG signature in human pluripotent stem cells (hPSC), including nine global gene expression datasets from both hESC and human induced pluripotent stem cells (hiPSCs), obtained during directed differentiation towards endoderm-, mesoderm-, and ectoderm derivatives. Sets of stably expressed genes were compiled and a handful of genes (e.g., EID2, ZNF324B, CAPN10, and RABEP2) were identified as generally applicable reference genes in hPSCs across all cell lines and experimental conditions. The stability in gene expression profiles was confirmed by quantitative PCR (RT-qPCR) analysis. Taken together, the current results suggest that differentiating hPSCs have a distinct HKG signature, which in some aspects is different from somatic cell types, and underscore the necessity to validate the stability of reference genes under the actual experimental setup used. In addition, the novel putative HKGs identified in this study can preferentially be used for normalization of gene expression data obtained from differentiating hPSCs.

Anthracyclines, such as doxorubicin, are highly efficient chemotherapeutic agents against a variety of cancers. However, anthracyclines are also among the most cardiotoxic therapeutic drugs presently on the market. Chemotherapeutic-induced cardiomyopathy is one of the leading causes of disease and mortality in cancer survivors. The exact mechanisms responsible for doxorubicin-induced cardiomyopathy are not completely known, but the fact that the cardiotoxicity is dose-dependent and that there is a variation in time-to-onset of toxicity, and gender- and age differences suggests that several mechanisms may be involved.In the present study, we investigated doxorubicin-induced cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes using proteomics. In addition, different sources of omics data (protein, mRNA, and microRNA) from the same experimental setup were further combined and analyzed using newly developed methods to identify differential expression in data of various origin and types. Subsequently, the results were integrated in order to generate a combined visualization of the findings.In our experimental model system, we exposed cardiomyocytes derived from human pluripotent stem cells to doxorubicin for up to two days, followed by a wash-out period of additionally 12 days. Besides an effect on the cell morphology and cardiomyocyte functionality, the data show a strong effect of doxorubicin on all molecular levels investigated. Differential expression patterns that show a linkage between the proteome, transcriptome, and the regulatory microRNA network, were identified. These findings help to increase the understanding of the mechanisms behind anthracycline-induced cardiotoxicity and suggest putative biomarkers for this condition.

Human pluripotent stem cells (hPSC) have the potential to become important tools for the establishment of new models for in vitro drug testing of, for example, toxicity and pharmacological effects. Late-stage attrition in the pharmaceutical industry is to a large extent caused by selection of drug candidates using nonpredictive preclinical models that are not clinically relevant. The current hepatic in vivo and in vitro models show clear limitations, especially for studies of chronic hepatotoxicity. For these reasons, we evaluated the potential of using hPSC-derived hepatocytes for long-term exposure to toxic drugs. The differentiated hepatocytes were incubated with hepatotoxic compounds for up to 14 days, using a repeated-dose approach. The hPSC-derived hepatocytes became more sensitive to the toxic compounds after extended exposures and, in addition to conventional cytotoxicity, evidence of phospholipidosis and steatosis was also observed in the cells. This is, to the best of our knowledge, the first report of a long-term toxicity study using hPSC-derived hepatocytes, and the observations support further development and validation of hPSC-based toxicity models for evaluating novel drugs, chemicals, and cosmetics.

Anthracyclines, such as doxorubicin, are well-established, highly efficient anti-neoplastic drugs used for treatment of a variety of cancers, including solid tumors, leukemia, lymphomas, and breast cancer. The successful use of doxorubicin has, however, been hampered by severe cardiotoxic side-effects. In order to prevent or reverse negative side-effects of doxorubicin, it is important to find early biomarkers of heart injury and drug-induced cardiotoxicity. The high stability under extreme conditions, presence in various body fluids, and tissue-specificity, makes microRNAs very suitable as clinical biomarkers. The present study aimed towards evaluating the early and late effects of doxorubicin on the microRNA expression in cardiomyocytes derived from human pluripotent stem cells. We report on several microRNAs, including miR-34a, miR-34b, miR-187, miR-199a, miR-199b, miR-146a, miR-15b, miR-130a, miR-214, and miR-424, that are differentially expressed upon, and after, treatment with doxorubicin. Investigation of the biological relevance of the identified microRNAs revealed connections to cardiomyocyte function and cardiotoxicity, thus supporting the findings of these microRNAs as potential biomarkers for drug-induced cardiotoxicity.

Doxorubicin is a chemotherapeutic agent indicated for the treatment of a variety of cancer types, including leukaemia, lymphomas, and many solid tumours. The use of doxorubicin is, however, associated with severe cardiotoxicity, often resulting in early discontinuation of the treatment. Importantly, the toxic symptoms can occur several years after the termination of the doxorubicin administration. In this study, the toxic effects of doxorubicin exposure have been investigated in cardiomyocytes derived from human embryonic stem cells (hESC). The cells were exposed to different concentrations of doxorubicin for up to 2 days, followed by a 12 day recovery period. Notably, the cell morphology was altered during drug treatment and the cells showed a reduced contractile ability, most prominent at the highest concentration of doxorubicin at the later time points. A general cytotoxic response measured as Lactate dehydrogenase leakage was observed after 2 days' exposure compared to the vehicle control, but this response was absent during the recovery period. A similar dose-dependant pattern was observed for the release of cardiac specific troponin T (cTnT) after 1 day and 2 days of treatment with doxorubicin. Global transcriptional profiles in the cells revealed clusters of genes that were differentially expressed during doxorubicin exposure, a pattern that in some cases was sustained even throughout the recovery period, suggesting that these genes could be used as sensitive biomarkers for doxorubicin-induced toxicity in human cardiomyocytes. The results from this study show that cTnT release can be used as a measurement of acute cardiotoxicity due to doxorubicin. However, for the late onset of doxorubicin-induced cardiomyopathy, cTnT release might not be the most optimal biomarker. As an alternative, some of the genes that we identified as differentially expressed after doxorubicin exposure could serve as more relevant biomarkers, and may also help to explain the cellular mechanisms behind the late onset apoptosis associated with doxorubicin-induced cardiomyopathy.

Cardiac hypertrophy is a condition that may contribute to the development of heart failure. In this study, we compare the gene-expression patterns of our in vitro stem-cell-based cardiac hypertrophy model with the gene expression of biopsies collected from hypertrophic human hearts. Twenty-five differentially expressed genes (DEGs) from both groups were identified and the expression of selected corresponding secreted proteins were validated using ELISA and Western blot. Several biomarkers, including CCN2, THBS1, NPPA, and NPPB, were identified, which showed significant overexpressions in the hypertrophic samples in both the cardiac biopsies and in the endothelin-1-treated cells, both at gene and protein levels. The protein-interaction network analysis revealed CCN2 as a central node among the 25 overlapping DEGs, suggesting that this gene might play an important role in the development of cardiac hypertrophy. GO-enrichment analysis of the 25 DEGs revealed many biological processes associated with cardiac function and the development of cardiac hypertrophy. In conclusion, we identified important similarities between ET-1-stimulated human-stem-cell-derived cardiomyocytes and human hypertrophic cardiac tissue. Novel putative cardiac hypertrophy biomarkers were identified and validated on the protein level, lending support for further investigations to assess their potential for future clinical applications. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Cardiac hypertrophy is an important and independent risk factor for the development of heart failure. To better understand the mechanisms and regulatory pathways involved in cardiac hypertrophy, there is a need for improved in vitro models. In this study, we investigated how hypertrophic stimulation affected human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CMs). The cells were stimulated with endothelin-1 (ET-1) for 8, 24, 48, 72, or 96 h. Parameters including cell size, ANP-, proBNP-, and lactate concentration were analyzed. Moreover, transcriptional profiling using RNA-sequencing was performed to identify differentially expressed genes following ET-1 stimulation. The results show that the CMs increase in size by approximately 13% when exposed to ET-1 in parallel to increases in ANP and proBNP protein and mRNA levels. Furthermore, the lactate concentration in the media was increased indicating that the CMs consume more glucose, a hallmark of cardiac hypertrophy. Using RNA-seq, a hypertrophic gene expression pattern was also observed in the stimulated CMs. Taken together, these results show that hiPSC-derived CMs stimulated with ET-1 display a hypertrophic response. The results from this study also provide new molecular insights about the underlying mechanisms of cardiac hypertrophy and may help accelerate the development of new drugs against this condition.

Cardiac hypertrophy is an important and independent risk factor for the development of cardiac myopathy that may lead to heart failure. The mechanisms underlying the development of cardiac hypertrophy are yet not well understood. To increase the knowledge about mechanisms and regulatory pathways involved in the progression of cardiac hypertrophy, we have developed a human induced pluripotent stem cell (hiPSC)-based in vitro model of cardiac hypertrophy and performed extensive characterization using a multi-omics approach. In a series of experiments, hiPSC-derived cardiomyocytes were stimulated with Endothelin-1 for 8, 24, 48, and 72 h, and their transcriptome and secreted proteome were analyzed. The transcriptomic data show many enriched canonical pathways related to cardiac hypertrophy already at the earliest time point, e.g., cardiac hypertrophy signaling. An integrated transcriptome–secretome analysis enabled the identification of multimodal biomarkers that may prove highly relevant for monitoring early cardiac hypertrophy progression. Taken together, the results from this study demonstrate that our in vitro model displays a hypertrophic response on both transcriptomic- and secreted-proteomic levels. The results also shed novel insights into the underlying mechanisms of cardiac hypertrophy, and novel putative early cardiac hypertrophy biomarkers have been identified that warrant further investigation to assess their potential clinical relevance.

There is an urgent need for improved models for cardiotoxicity testing. Here we propose acoustic sensing applied to beating human cardiomyocyte clusters for non-invasive, surrogate measuring of the QT interval and other characteristics of the contractile machinery. In experiments with the acoustic method quartz crystal microbalance with dissipation monitoring (QCM-D), the shape of the recorded signals was very similar to the extracellular field potential detected in electrochemical experiments, and the expected changes of the QT interval in response to addition of conventional drugs (E-4031 or nifedipine) were observed. Additionally, changes in the dissipation signal upon addition of cytochalasin D were in good agreement with the known, corresponding shortening of the contraction-relaxation time. These findings suggest that QCM-D has great potential as a tool for cardiotoxicological screening, where effects of compounds on the cardiomyocyte contractile machinery can be detected independently of whether the extracellular field potential is altered or not.

Hepatotoxicity is one of the most cited reasons for withdrawal of approved drugs from the market. The use of nonclinically relevant in vitro and in vivo testing systems contributes to the high attrition rates. Recent advances in differentiating human induced pluripotent stem cells (hiPSCs) into pure cultures of hepatocyte-like cells expressing functional drug metabolizing enzymes open up possibilities for novel, more relevant human cell based toxicity models. The present study aimed to investigate the use of hiPSC derived hepatocytes for conducting mechanistic toxicity testing by image based high content analysis (HCA). The hiPSC derived hepatocytes were exposed to drugs known to cause hepatotoxicity through steatosis and phospholipidosis, measuring several endpoints representing different mechanisms involved in drug induced hepatotoxicity. The hiPSC derived hepatocytes were benchmarked to the HepG2 cell line and generated robust HCA data with low imprecision between plates and batches. The different parameters measured were detected at subcytotoxic concentrations and the order of which the compounds were categorized (as severe, moderate, mild, or nontoxic) based on the degree of injury at isomolar concentration corresponded to previously published data. Taken together, the present study shows how hiPSC derived hepatocytes can be used as a platform for screening drug induced hepatotoxicity by HCA.

In this article, we present an interactive prototype that aids the interpretation of large-scale gene expression data, showing how visualization techniques can be applied to support knowledge extraction from large datasets. The developed prototype was evaluated on a dataset of human embryonic stem cell-derived cardiomyocytes. The visualization approach presented here supports the analyst in finding genes with high similarity or dissimilarity across different experimental groups. By using an external overview in combination with filter windows, and various color scales for showing the degree of similarity, our interactive visual prototype is able to intuitively guide the exploration processes over the large amount of gene expression data.

Using human pluripotent stem cells as a source to generate differentiated progenies for regenerative medicine applications has attracted substantial interest during recent years. Having the capability to produce large quantities of human cells that can replace damaged tissue due to disease or injury opens novel avenues for relieving symptoms and also potentially offers cures for many severe human diseases. Although tremendous advancements have been made, there is still much research and development left before human pluripotent stem cell derived products can be made available for cell therapy applications. In order to speed up the development processes, we argue strongly in favor of cross-disciplinary collaborative efforts which have many advantages, especially in a relatively new field such as regenerative medicine based on human pluripotent stem cells. In this review, we aim to illustrate how some of the hurdles for bringing human pluripotent stem cell derivatives from bench-to-bed can be effectively addressed through the establishment of collaborative programs involving academic institutions, biotech industries, and pharmaceutical companies. By taking advantage of the strengths from each organization, innovation and productivity can be maximized from a resource perspective and thus, the chances of successfully bringing novel regenerative medicine treatment options to patients increase.

Aims: Use and dosing of guideline-directed medical therapy (GDMT) in patients with heart failure (HF) have been shown to be suboptimal. Among new users of GDMT in HF, we followed the real-life patterns of dose titration and discontinuation of angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), beta-blockers, mineralocorticoid receptor antagonists (MRA) and angiotensin receptor-neprilysin inhibitors (ARNI).

Methods and results: New users were identified in health care databases in Sweden, UK and US between 2016–2019. Inclusion criterion was a recent HF hospitalization (HHF) triggering the initiation of GDMT. Patients were grouped by GDMT, i.e. ACEi, ARB, beta-blocker, MRA and ARNI, and stratified by initial dose. Follow-up was 12 months, until death or study end. Outcomes were dose titration within each drug class, discontinuation and first HHF or death. Dose/discontinuation follow-up was assessed daily based on the coverage length of a filled prescription and reported on day 365. New users of ACEi (n = 8426), ARB (n = 2303), beta-blockers (n = 10 476), MRA (n = 17 421), and ARNI (n = 29 546) were identified. Over 12 months, target dose achievement was 15%, 10%, 12%, 30%, and discontinuation was 55%, 33%, 24% and 27% for ACEi, ARB, beta-blockers and ARNI, respectively. MRA was rarely titrated and discontinuation rates were high (40%). Event rates for HHF or death ranged from 40.0–86.9 per 100 patient-years across the treatment groups.

Conclusion: Despite high risk of clinical events following HHF, new initiation of GDMT was followed by consistent patterns of low up-titration and early GDMT discontinuation in three countries with different health care and economies. Our data highlight the urgent need for moving away from long sequential approach when initiating HF treatment and for improving just-in-time decision support for patients and health care providers.

Aims: Renin-angiotensin system inhibitors (RASi) are the most effective treatments for diabetic kidney disease but significant residual renal risk remains, possibly because of other mechanisms of kidney disease progression unrelated to RAS that may be present. Sodium-glucose co-transporter-2 inhibitors reduce albuminuria and may complement RASi by offering additional renal protection. This post hoc analysis investigated the effects of dapagliflozin on cardio-renal risk factors in patients with type 2 diabetes (T2D) with increased albuminuria treated with or without RASi at baseline. Materials and methods: We evaluated the effects of dapagliflozin 10 mg/day over 12–24 weeks across 13 placebo-controlled studies in patients with T2D with a urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g at baseline. Patients were divided into two subgroups based on treatment with or without RASi at baseline. Results: Compared with patients with RASi at baseline (n = 957), patients without RASi (n = 302) were younger, had a shorter duration of diabetes (7 vs. 12 years), higher estimated glomerular filtration rate (eGFR) and lower UACR, serum uric acid (sUA), body weight and systolic blood pressure. Placebo-adjusted treatment effects of dapagliflozin on UACR, eGFR, glycated haemoglobin and haematocrit over 24 weeks were similar across groups. Mean reductions in body weight and sUA were more distinct in patients without RASi treatment at baseline. Conclusions: Treatment with dapagliflozin over 24 weeks provides similar clinically relevant improvements in metabolic and haemodynamic parameters, and similar reductions in UACR, in patients with T2D with elevated albuminuria treated with or without RASi at baseline. © 2019 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.

Aims: Anemia is common in type 2 diabetes (T2D), particularly in patients with kidney impairment, and often goes unrecognized. Dapagliflozin treatment increases hemoglobin and serum erythropoietin levels. We investigated the effect of dapagliflozin 10-mg/day on hemoglobin in T2D patients with and without anemia. Methods: Data from 5325 patients from 14 placebo-controlled, dapagliflozin-treatment studies of at least 24-weeks duration were pooled. Dapagliflozin's effects (vs. placebo) on hemoglobin, serum albumin, estimated glomerular filtration rate (eGFR), systolic blood pressure, body weight, and safety in patients with and without anemia were evaluated. Results: At baseline, 13% of all T2D patients and 28% of those with chronic kidney disease (eGFR &lt;60 mL/min/1.73 m2) had anemia. Hemoglobin increased continuously to at least week 8 and was sustained throughout 24-weeks follow-up in dapagliflozin-treated patients. Serum albumin increased in dapagliflozin-treated patients at week 4 and remained stable thereafter. Dapagliflozin was well tolerated and corrected anemia in 52% of patients with anemia at baseline (placebo: 26%). Incidences of new-onset anemia were lower in dapagliflozin-treated (2.3%) versus placebo-treated (6.5%) patients. Conclusions: Treatment with dapagliflozin can correct and prevent anemia in T2D patients. A gradual increase in hemoglobin beyond week 4 may indicate an erythropoiesis-stimulating effect of sodium-glucose cotransporter 2 inhibition. 

Dapagliflozin is a highly selective sodium-glucose cotransporter 2 inhibitor associated with stabilization of estimated glomerular filtration rate (eGFR); reductions in glycated hemoglobin (HbA1c), systolic blood pressure, body weight, and albuminuria; and a small and consistent increase in hematocrit [1–4]. This data set is based on the associated article [5] analyzing data from 5325 patients with type 2 diabetes from 14 placebo-controlled, phase 3 (one phase 2/3), double-blind dapagliflozin treatment studies of 24–104 weeks’ duration. Data on dapagliflozin's effects (vs. placebo) on hemoglobin (Hb), hematocrit, serum albumin, serum total protein concentrations, urine albumin/creatinine ratio, eGFR, heart rate, blood pressure, body weight, and safety in patients with type 2 diabetes with and without anemia were pooled and analyzed. Patients were divided into two groups according to baseline Hb levels: anemia (Hb <13 g/dL in men and <12 g/dL in women) and no anemia. Some biomarkers associated with erythropoiesis and the presence of anemia, such as iron, transferrin, ferritin, reticulocytes, and hepcidin, were not included in the original studies and therefore data for these biomarkers were not available. Descriptive statistics were used for baseline characteristics and safety data and a longitudinal repeated-measures mixed model for efficacy data. Changes in Hb concentrations were evaluated, and the proportion of patients with baseline anemia who were no longer anemic at week 24 was determined, as was the occurrence of polycythemia (Hb >16.5 g/dL in men and >16.0 g/dL in women). Because anemia commonly occurs in patients with diabetes and chronic kidney disease [6], the data can be of value to further analyze trends in relevant physiological and pathophysiological parameters.

Human embryonic stem cells (hESCs) can differentiate into a variety of specialized cell types. Thus, they provide a model system for embryonic development to investigate the molecular processes of cell differentiation and lineage commitment. The development of the cardiac lineage is easily detected in mixed cultures by the appearance of spontaneously contracting areas of cells. We performed gene expression profiling of undifferentiated and differentiating hESCs and monitored 468 genes expressed during cardiac development and/or in cardiac tissue. Their transcription during early differentiation of hESCs through embryoid bodies (EBs) was investigated and compared with spontaneously differentiating hESCs maintained on feeders in culture without passaging (high-density (HD) protocol). We observed a larger variation in the gene expression between cells from a single cell line that were differentiated using two different protocols than in cells from different cell lines that were cultured according to the same protocol. Notably, the EB protocol resulted in more reproducible transcription profiles than the HD protocol. The results presented here provide new information about gene regulation during early differentiation of hESCs with emphasis on the cardiomyogenic program. In addition, we also identified regulatory elements that could prove critical for the development of the cardiomyocyte lineage.

It is now well documented that human embryonic stem cells (hESCs) can differentiate into functional cardiomyocytes. These cells constitute a promising source of material for use in drug development, toxicity testing, and regenerative medicine. To assess their utility as replacement or complement to existing models, extensive phenotypic characterization of the cells is required. In the present study, we used microarrays and analyzed the global transcription of hESC-derived cardiomyocyte clusters (CMCs) and determined similarities as well as differences compared with reference samples from fetal and adult heart tissue. In addition, we performed a focused analysis of the expression of cardiac ion channels and genes involved in the Ca2+-handling machinery, which in previous studies have been shown to be immature in stem cell-derived cardiomyocytes. Our results show that hESC-derived CMCs, on a global level, have a highly similar gene expression profile compared with human heart tissue, and their transcriptional phenotype was more similar to fetal than to adult heart. Despite the high similarity to heart tissue, a number of significantly differentially expressed genes were identified, providing some clues toward understanding the molecular difference between in vivo sourced tissue and stem cell derivatives generated in vitro. Interestingly, some of the cardiacrelated ion channels and Ca2+-handling genes showed differential expression between the CMCs and heart tissues. These genes may represent candidates for future genetic engineering to create hESC-derived CMCs that better mimic the phenotype of the cardiomyocytes present in the adult human heart.

Recent studies have shown that microRNAs (miRNAs) act as posttranscriptional regulators and that they play important roles during heart development and in cardiac function. Thus, they may provide new means of altering stem cell fate and differentiation processes. However, information about the correlation between global miRNA and mRNA expression in cardiomyocyte clusters (CMCs) derived from human embryonic stem cells (hESC) and in fetal and adult heart tissue is lacking. In the present study the global miRNA and mRNA expression in hESC-derived CMCs and in fetal and adult heart tissue was investigated in parallel using microarrays. Target genes for the differentially expressed miRNAs were predicted using computational methods, and the concordance in miRNA expression and mRNA levels of potential target genes was determined across the experimental samples. The biology of the predicted target genes was further explored regarding their molecular functions and involvement in known regulatory pathways. A clear correlation between the global miRNA expression and corresponding target mRNA expression was observed. Using three different sources of cardiac tissue-like samples, we defined the similarities between in vitro hESC-derived CMCs and their in vivo counterparts. The results are in line with previously reported observations that miRNAs repress mRNA expression and additionally identify a number of novel miRNAs with potential important roles in human cardiac tissue. The concordant miRNA expression pattern observed among all the cardiac tissue-like samples analyzed here provide a starting point for future ambitious studies aiming towards assessment of the functional roles of specific miRNAs during cardiomyocyte differentiation.

Comparative transcriptomic analysis identifies genes differentially expressed in human epicardial progenitor cells and hiPSC-derived cardiac progenitor cells: effects of hypoxic vs normoxic culture conditions.

Housekeeping genes (HKGs) are involved in basic functions needed for the sustenance of the cell and are assumed to be constitutively expressed at a constant level. Based on these features, HKGs are frequently used for normalization of gene expression data. In the present study, we used the CodeLink Gene Expression Bioarray system to interrogate changes in gene expression occurring during differentiation of human ESCs (hESCs). Notably, in the three hESC lines used for the study, we observed that the RNA levels of 56 frequently used HKGs varied to a degree that rendered them inappropriate as reference genes. Therefore, we defined a novel set of HKGs specifically for hESCs. Here we present a comprehensive list of 292 genes that are stably expressed (coefficient of variation <20%) in differentiating hESCs. These genes were further grouped into high-, medium-, and low-expressed genes. The expression patterns of these novel HKGs show very little overlap with results obtained from somatic cells and tissues. We further explored the stability of this novel set of HKGs in independent, publicly available gene expression data from hESCs and observed substantial similarities with our results. Gene expression was confirmed by real-time quantitative polymerase chain reaction analysis. Taken together, these results suggest that differentiating hESCs have a unique HKG signature and underscore the necessity to validate the expression profiles of putative HKGs. In addition, this novel set of HKGs can preferentially be used as controls in gene expression analyses of differentiating hESCs.

Human embryonic stem cells (hESCs) represent populations of pluripotent undifferentiated cells with unlimited replication capacity which can be coaxed to differentiate into a variety of specialized cells. As a result, there is great hope that hESCs will be extremely useful by providing platforms for various in vitro applications (e.g. in drug discovery) as well as for future use of hESCs and their differentiated progeny in cell replacement therapies. In order to realize the potential of hESCs, it is necessary to gain much deeper knowledge about the processes that govern differentiation of these cells.

In recent years, significant progress towards understanding cellular differentiation has been fuelled, in part, by studying gene expression using microarrays. In this large scale studies, statistical methods are used to normalize the gene expression data and render comparisons between different samples. In lower throughput analyses, RNA levels in hESCs are also measured using RT-PCR requiring normalization of the gene expression data to adequately correct for inter-sample variation. In general, investigators have used the traditional housekeeping genes (HKGs) (e.g. GAPDH, b-tubulin, b-actin) in studies of hESCs. HKGs are involved in basic functions needed for the sustenance of the cell and are assumed to be constitutively expressed at a constant level. Based on these features, HKGs are frequently used for normalization of gene expression data. However, it is well known that the expression of several of these genes vary considerably in adult tissues and their suitability as HKGs in hESCs remains to be proven. In this regard, the RNA levels of HPRT and b-tubulin were shown to vary substantially in differentiating mouse ESCs.

In the present study, we used the CodeLinkTM Gene Expression Bioarray system to interrogate changes in gene expression occurring during differentiation of hESCs. Notably, in the three hESC lines used for the study, we observed that the RNA levels of 56 frequently used HKGs varied to a degree that rendered them inappropriate as reference genes. Therefore, we defined a novel set of HKGs specifically for hESCs. Here we present a comprehensive list of 292 genes that are stably expressed (coefficient of variation<20%) in differentiating hESCs. These genes were further grouped into high, medium, and low expressed genes. The expression patterns of these novel HKGs show very little overlap with results obtained from somatic cells and tissues. We further explored the stability of this novel set of HKGs in independent, publicly available gene expression data from hESCs and observed substantial similarities in terms of stably expressed genes. Taken together, these results suggest that hESCs have a unique HKG signature and underscore the necessity to validate the expression profiles of putative HKGs. In addition, the novel set of identified HKGs can preferentially be used as controls in gene expression analyses of differentiating hESCs.

Human embryonic stem cells (hESC) can differentiate into a variety of specialized cell types, and they constitute a useful model system to study embryonic development in vitro. In order to fully utilize the potential of these cells, the mechanisms that regulate the developmental processes of specific lineage differentiation need to be better defined. The aim of this study was to explore the molecular program involved in the differentiation of hESC towards definitive endoderm (DE) and further into the hepatic lineage, and to compare that to primitive endoderm (PrE) differentiation. To that end, we applied two protocols, a specific DE differentiation protocol and an intrinsic differentiation protocol that mainly mediates PrE formation. We collected hESC, hESC-derived DE, DE-derived hepatocyte-progenitors (DE-Prog), DE-derived hepatocyte-like cells (DE-Hep), and the corresponding PrE-derivatives. The samples were analyzed using microarrays, and we identified sets of genes which were exclusively up-regulated in DE-derivatives (compared to PrE-derivatives) at discrete developmental stages. We also investigated known protein interactions among the set of up-regulated genes in DE-Hep. The results demonstrate important differences between DE- and PrE-differentiation on the transcriptional level. In particular, our results identify a unique molecular program, exclusively activated during development of DE and the subsequent differentiation of DE towards the hepatic lineage. We identified key-genes and pathways of potential importance for future efforts to improve hepatic differentiation from hESC. These results reveal new opportunities for rational design of specific interventions with the purpose of generating enriched populations of DE derivatives, including functional hepatocytes.

MicroRNAs (miRNAs) are small non-coding molecules that have been shown to play key roles in regulating cellular development and to be involved in various diseases. By interfering with their target mRNAs, these molecules inhibit the expression of proteins, either by de-stabilizing the messenger RNA (mRNA) molecule or by preventing its translation. Each miRNA can target hundreds of mRNAs, and one mRNA can be targeted by several miRNAs.This makes it extremely complex to determine the regulatory functions of specific miRNAs in the transcription and translation processes. However, important advancements in microarray technology have made large scale monitoring of miRNA expression possible. This opens the possibility to move from studies of single molecules to studies of complex molecular processes, pathways, and biological systems. Recent studies have indicated important roles for miRNAs in stem cell differentiation in general and in cardiac development in particular. This paper presents a global transcriptional study where putativecorrelation between miRNA and mRNA expression in fetal- and adult heart tissues samples and in clusters of cardiomyocytes derived from human embryonic stem cells (hESCs) were investigated. Target genes of miRNAs expressed in cardiac tissue have been predicted and their transcriptional profiles investigated in tissue specimen. By using a statistical algorithm, up- and down-regulated miRNAs and mRNAs have been identified in four different cardiac related samples. In total, 17 cardiac related miRNAs have been analyzed and for each of these, clusters of negatively correlated target genes were identified. This supports the hypothesis that sets of miRNAs play an important role in modulating the expression of genes, which are important for cardiac development. Interestingly, the results from this study also indicate a global negative correlation between miRNA expression and mRNA expression, which previously has not been reported.

Human embryonic stem cells (hESCs) can differentiate in vitro into spontaneously contracting cardiomyocytes (CMs). These cells may prove extremely useful for various applications in basic research, drug discovery, and regenerative medicine. To fully use the potential of the cells, they need to be extensively characterized, and the regulatory mechanisms that control hESC differentiation toward the cardiac lineage need to be better defined. In this study, we used microarrays to analyze, for the first time, the global gene expression profile of isolated hESC-derived CM clusters. By comparing the clusters with undifferentiated hESCs and using stringent selection criteria, we identified 530 upregulated and 40 downregulated genes in the contracting clusters. To further characterize the family of upregulated genes in the hESC-derived CM clusters, the genes were classified according to their Gene Ontology annotation. The results indicate that the hESC-derived CM clusters display high similarities, on a molecular level, to human heart tissue. Moreover, using the family of upregulated genes, we created protein interaction maps that revealed topological characteristics. We also searched for cellular pathways among the upregulated genes in the hESC-derived CM clusters and identified eight significantly upregulated pathways. Real-time quantitative polymerase chain reaction and immunohistochemical analysis confirmed the expression of a subset of the genes identified by the microarrays. Taken together, the results presented here provide a molecular signature of hESC-derived CM clusters and further our understanding of the biological processes that are active in these cells.

MicroRNAs (miRNAs) are small non-coding molecules that have been shown to play key roles in regulating cellular development and to be involved in various diseases. By interfering with their target mRNAs, these molecules inhibit the expression of proteins, either by destabilizing the mRNA molecule or by preventing its translation. It has been suggested that each miRNA can target hundreds of mRNAs, and that one mRNA can be targeted by several miRNAs. This makes it extremely complex to determine the roles of specific miRNAs in the regulation of translation of mRNA. Recent advancements in microarray technology have made large-scale monitoring of miRNA expression possible. However, the size and complexity of these data sets make them challenging to analyze, and improved algorithms are therefore required to facilitate the analysis. In this paper, we present a novel clustering algorithm that uses an Information Fusion (IF) approach to cluster miRNA data, allowing for multiple types of input data to guide the clustering. For evaluation of the algorithm, we used miRNA expression data from human embryonic stem cells and cardiomyocyte-like cells derived thereof. Clusters obtained when using the multiple input data approach were compared to those generated when using only the expression data. Our results show that it is beneficial to include various types of genomic data as input to the clustering process, since it results in clusters of increased biological relevance.

Aims: Hypomagnesemia (serum magnesium [Mg] <0.74 mmol/L [<1.8 mg/dL]) is commonly observed in patients with type 2 diabetes (T2D). This study investigated the effect of treatment with dapagliflozin 10 mg on Mg concentrations in patients with T2D. Methods: In this post hoc analysis, we used pooled data from 10 placebo-controlled studies of dapagliflozin over 24 weeks of treatment in patients with T2D. We evaluated the change in Mg in patients receiving dapagliflozin vs. placebo overall, and in subgroups with baseline hypomagnesemia and normal/hypermagnesemia (≥0.74 mmol/L [≥1.8 mg/dL]). We determined the proportion of patients with baseline hypomagnesemia who achieved Mg ≥0.74 mmol/L (≥1.8 mg/dL). Results: A total of 4398 patients with T2D were included. The mean change from baseline to week 24 in Mg was significantly larger with dapagliflozin vs. placebo; difference, 0.06 mmol/L (95% confidence interval [CI]: 0.05, 0.06). The proportion of patients with Mg within the population reference range after 24 weeks of treatment was significantly higher with dapagliflozin vs. placebo; difference, 47.8% (95% CI: 41.4, 53.9). The proportion of patients displaying hypermagnesemia did not increase with dapagliflozin treatment. Conclusions: Treatment with dapagliflozin 10 mg resulted in correction of Mg concentrations in patients with T2D and hypomagnesemia. 

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic-and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

A common approach for analyzing large-scale molecular data is to cluster objects sharing similar characteristics. This assumes that genes with highly similar expression profiles are likely participating in a common molecular process. Biological systems are extremely complex and challenging to understand, with proteins having multiple functions that sometimes need to be activated or expressed in a time-dependent manner. Thus, the strategies applied for clustering of these molecules into groups are of key importance for translation of data to biologically interpretable findings. Here we implemented a multi-assignment clustering (MAsC) approach that allows molecules to be assigned to multiple clusters, rather than single ones as in commonly used clustering techniques. When applied to high-throughput transcriptomics data, MAsC increased power of the downstream pathway analysis and allowed identification of pathways with high biological relevance to the experimental setting and the biological systems studied. Multi-assignment clustering also reduced noise in the clustering partition by excluding genes with a low correlation to all of the resulting clusters. Together, these findings suggest that our methodology facilitates translation of large-scale molecular data into biological knowledge. The method is made available as an R package on GitLab (https://gitlab.com/wolftower/masc).