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Abstract Atherosclerosis and its complications are major causes of cardiovascular morbidity and death. Apart from risk factors such as hypercholesterolemia and inflammation, the causal molecular mechanisms are unknown. One proposed causal mechanism involves elevated levels of reactive oxygen species (ROS). Indeed, early expression of the ROS forming NADPH oxidase type 5 (Nox5) in vascular endothelial cells correlates with atherosclerosis and aortic aneurysm. Here we test the pro-atherogenic Nox5 hypothesis using mouse models. Because Nox5 is missing from the mouse genome, a knock-in mouse model expressing human Nox5 in its physiological location of endothelial cells (eNOX5ki/ki) was tested as a possible new humanised mouse atherosclerosis model. However, whether just on a high cholesterol diet or by crossing in aortic atherosclerosis-prone ApoE −/− mice with and without induction of diabetes, Nox5 neither induced on its own nor aggravated aortic atherosclerosis. Surprisingly, however, diabetic ApoE−/− x eNOX5ki/ki mice developed aortic aneurysms more than twice as often correlating with lower vascular collagens, as assessed by trichrome staining, without changes in inflammatory gene expression, suggesting that endothelial Nox5 directly affects extracellular matrix remodelling associated with aneurysm formation in diabetes. Thus Nox5-derived reactive oxygen species are not a new independent mechanism of atherosclerosis but may enhance the frequency of abdominal aortic aneurysms in the context of diabetes. Together with similar clinical findings, our preclinical target validation opens up a first-in-class mechanism-based approach to treat or even prevent abdominal aortic aneurysms.

Abstract Differential gene expression normalised to a single housekeeping (HK) is used to identify disease mechanisms and therapeutic targets. HK gene selection is often arbitrary, potentially introducing systematic error and discordant results. Here we examine these risks in a disease model of brain hypoxia. We first identified the eight most frequently used HK genes through a systematic review. However, we observe that in both ex-vivo and in vivo, their expression levels varied considerably between conditions. When applying these genes to normalise expression levels of the validated stroke target gene, inducible Nox4, we obtained opposing results. As an alternative tool for unbiased HK gene selection, software tools exist but are limited to individual datasets lacking genome-wide search capability and user-friendly interfaces. We, therefore, developed the HouseKeepR algorithm to rapidly analyse multiple gene expression datasets in a disease-specific manner and rank HK gene candidates according to stability in an unbiased manner. Using a panel of de novo top-ranked HK genes for brain hypoxia, but not single genes, Nox4 induction was consistently reproduced. Thus, differential gene expression analysis is best normalised against a HK gene panel selected in an unbiased manner. HouseKeepR is the first user-friendly, bias-free, and broadly applicable tool to automatically propose suitable HK genes in a tissue- and disease-dependent manner.

There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. Here, the authors close this gap with NeDRex, an integrative and interactive platform.

The past decades have witnessed a paradigm shift from the traditional drug discovery shaped around the idea of “one target, one disease” to polypharmacology (multiple targets, one disease). Given the lack of clear-cut boundaries across disease (endo)phenotypes and genetic heterogeneity across patients, a natural extension to the current polypharmacology paradigm is to target common biological pathways involved in diseases via endopharmacology (multiple targets, multiple diseases). In this study, we present proximal pathway enrichment analysis (PxEA) for pinpointing drugs that target common disease pathways towards network endopharmacology. PxEA uses the topology information of the network of interactions between disease genes, pathway genes, drug targets and other proteins to rank drugs by their interactome-based proximity to pathways shared across multiple diseases, providing unprecedented drug repurposing opportunities. Using PxEA, we show that many drugs indicated for autoimmune disorders are not necessarily specific to the condition of interest, but rather target the common biological pathways across these diseases. Finally, we provide high scoring drug repurposing candidates that can target common mechanisms involved in type 2 diabetes and Alzheimer’s disease, two conditions that have recently gained attention due to the increased comorbidity among patients.

BackgroundMachine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distributed machine learning models without sharing sensitive data. In addition, the implementation is time-consuming and requires advanced programming skills and complex technical infrastructures. ObjectiveVarious tools and frameworks have been developed to simplify the development of FL algorithms and provide the necessary technical infrastructure. Although there are many high-quality frameworks, most focus only on a single application case or method. To our knowledge, there are no generic frameworks, meaning that the existing solutions are restricted to a particular type of algorithm or application field. Furthermore, most of these frameworks provide an application programming interface that needs programming knowledge. There is no collection of ready-to-use FL algorithms that are extendable and allow users (eg, researchers) without programming knowledge to apply FL. A central FL platform for both FL algorithm developers and users does not exist. This study aimed to address this gap and make FL available to everyone by developing FeatureCloud, an all-in-one platform for FL in biomedicine and beyond. MethodsThe FeatureCloud platform consists of 3 main components: a global frontend, a global backend, and a local controller. Our platform uses a Docker to separate the local acting components of the platform from the sensitive data systems. We evaluated our platform using 4 different algorithms on 5 data sets for both accuracy and runtime. ResultsFeatureCloud removes the complexity of distributed systems for developers and end users by providing a comprehensive platform for executing multi-institutional FL analyses and implementing FL algorithms. Through its integrated artificial intelligence store, federated algorithms can easily be published and reused by the community. To secure sensitive raw data, FeatureCloud supports privacy-enhancing technologies to secure the shared local models and assures high standards in data privacy to comply with the strict General Data Protection Regulation. Our evaluation shows that applications developed in FeatureCloud can produce highly similar results compared with centralized approaches and scale well for an increasing number of participating sites. ConclusionsFeatureCloud provides a ready-to-use platform that integrates the development and execution of FL algorithms while reducing the complexity to a minimum and removing the hurdles of federated infrastructure. Thus, we believe that it has the potential to greatly increase the accessibility of privacy-preserving and distributed data analyses in biomedicine and beyond.

Hypertension is the most important cause of death and disability in the elderly. In 9 out of 10 cases, the molecular cause, however, is unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase (Nox) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by molecular network analysis and identify NOX5, not present in rodents, as a sole neighbor to human vasodilatory endothelial nitric oxide (NO) signaling. In hypertensive patients, endothelial microparticles indeed contained higher levels of NOX5-but not NOX1, NOX2, or NOX4-with a bimodal distribution correlating with disease severity. Mechanistically, mice expressing human Nox5 in endothelial cells developed-upon aging-severe systolic hypertension and impaired endothelium-dependent vasodilation due to uncoupled NO synthase (NOS). We conclude that NOX5-induced uncoupling of endothelial NOS is a causal mechanism and theragnostic target of an age-related hypertension endotype. Nox5 knock-in (KI) mice represent the first mechanism-based animal model of hypertension.

In cardiovascular disease, the protective NO/sGC/cGMP signalling-pathway is impaired due to a decreased pool of NO-sensitive haem-containing sGC accompanied by a reciprocal increase in NO-insensitive haem-free sGC. However, no direct method to detect cellular haem-free sGC other than its activation by the new therapeutic class of haem mimetics, such as BAY 58-2667, is available. Here we show that fluorescence dequenching, based on the interaction of the optical active prosthetic haem group and the attached biarsenical fluorophor FlAsH can be used to detect changes in cellular sGC haem status. The partly overlap of the emission spectrum of haem and FlAsH allows energy transfer from the fluorophore to the haem which reduces the intensity of FlAsH fluorescence. Loss of the prosthetic group, e.g. by oxidative stress or by replacement with the haem mimetic BAY 58-2667, prevented the energy transfer resulting in increased fluorescence. Haem loss was corroborated by an observed decrease in NO-induced sGC activity, reduced sGC protein levels, and an increased effect of BAY 58-2667. The use of a haem-free sGC mutant and a biarsenical dye that was not quenched by haem as controls further validated that the increase in fluorescence was due to the loss of the prosthetic haem group. The present approach is based on the cellular expression of an engineered sGC variant limiting is applicability to recombinant expression systems. Nevertheless, it allows to monitor sGC's redox regulation in living cells and future enhancements might be able to extend this approach to in vivo conditions.

Ischemic stroke is the second leading cause of death worldwide. Only one moderately effective therapy exists, albeit with contraindications that exclude 90% of the patients. This medical need contrasts with a high failure rate of more than 1,000 pre-clinical drug candidates for stroke therapies. Thus, there is a need for translatable mechanisms of neuroprotection and more rigid thresholds of relevance in pre-clinical stroke models. One such candidate mechanism is oxidative stress. However, antioxidant approaches have failed in clinical trials, and the significant sources of oxidative stress in stroke are unknown. We here identify NADPH oxidase type 4 (NOX4) as a major source of oxidative stress and an effective therapeutic target in acute stroke. Upon ischemia, NOX4 was induced in human and mouse brain. Mice deficient in NOX4 (Nox4(-/-)) of either sex, but not those deficient for NOX1 or NOX2, were largely protected from oxidative stress, blood-brain-barrier leakage, and neuronal apoptosis, after both transient and permanent cerebral ischemia. This effect was independent of age, as elderly mice were equally protected. Restoration of oxidative stress reversed the stroke-protective phenotype in Nox4(-/-) mice. Application of the only validated low-molecular-weight pharmacological NADPH oxidase inhibitor, VAS2870, several hours after ischemia was as protective as deleting NOX4. The extent of neuroprotection was exceptional, resulting in significantly improved long-term neurological functions and reduced mortality. NOX4 therefore represents a major source of oxidative stress and novel class of drug target for stroke therapy.