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      Network modules as molecular disease definitions for mechanism-based endotyping anddrug repurposing



            We hardly understand any disease mechanistically and low precision drug interventions are the norm in the clinics [1,2]. Current disease definitions are also organ- and symptom-based which runs the risk that different mechanisms that cause a similar symptom are subsumed under one umbrella term. They are thus converted into one common and complex disease entity, which is impossible to untangle based on the current diagnostic tools, leading to a long-lasting classification of chronic diseases either based on symptoms or body location. The current treatment options for complex diseases are thus chronic interventions which are neither curative nor precise. Recent efforts have been made to redefine diseases by moving from symptom and organ to mechanism and cause [3]. The ultimate aim is to endotype patients and reach precision medicine. Complex diseases, contrary to rare monogenic diseases, are not caused by a single gene or protein, but several affected elements within a diseased network, a disease module. We have previously identified a disease mechanism, involving genes related to reactive oxygen species ( ROS) formation and cGMP signalling (ROCG). This disease mechanism or disease module is causal for a heterogeneous diseasome cluster of metabolic-cerebro-cardiovascular disease phenotypes [4]. Hypertension and heart failure have been validated within the ROCG endotype in biobanked patient samples (1 out of 5 and 1 out of 3 patients respectively) [5]. Stratifying patients according to both phenotype and endotype will enable high precision therapeutic interventions resulting in low number needed to treat. These data show that even for supposedly complex diseases, endotyping for precision medicine, and mechanistic disease re-definition is possible.


            Author and article information

            28 July 2022
            [1 ] Department of Pharmacology & Personalised Medicine, Maastricht University, Maastricht, The Netherlands
            [2 ] Department of Pharmacology & Personalised Medicine, Maastricht University, Maastricht, The Netherlands; Department of Neurology, University Hospital Essen, Essen, Germany
            [3 ] Department of Pharmacology & Personalised Medicine, Maastricht University, Maastricht, The Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
            [4 ] Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany; Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany
            [5 ] Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany; Computational Biomedicine Lab, Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
            Author notes
            Author information

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            Maastricht, Netherlands
            2-3 September, 2022
            : 28 July 2022

            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            endotyping,theranostics,diagnostics,biomarkers,systems medicine,network medicine,disease modules


            1. Schork Nicholas J.. Personalized medicine: Time for one-person trials. Nature. Vol. 520(7549):609–611. 2015. Springer Science and Business Media LLC. [Cross Ref]

            2. Wieseler Beate, McGauran Natalie, Kaiser Thomas. New drugs: where did we go wrong and what can we do better? BMJ. 2019. BMJ. [Cross Ref]

            3. Nogales Cristian, Mamdouh Zeinab M., List Markus, Kiel Christina, Casas Ana I., Schmidt Harald H.H.W.. Network pharmacology: curing causal mechanisms instead of treating symptoms. Trends in Pharmacological Sciences. Vol. 43(2):136–150. 2022. Elsevier BV. [Cross Ref]

            4. Langhauser Friederike, Casas Ana I., Dao Vu-Thao-Vi, Guney Emre, Menche Jörg, Geuss Eva, Kleikers Pamela W. M., López Manuela G., Barabási Albert-L., Kleinschnitz Christoph, Schmidt Harald H. H. W.. A diseasome cluster-based drug repurposing of soluble guanylate cyclase activators from smooth muscle relaxation to direct neuroprotection. npj Systems Biology and Applications. Vol. 4(1)2018. Springer Science and Business Media LLC. [Cross Ref]

            5. Elbatreek Mahmoud H., Sadegh Sepideh, Anastasi Elisa, Guney Emre, Nogales Cristian, Kacprowski Tim, Hassan Ahmed A., Teubner Andreas, Huang Po-Hsun, Hsu Chien-Yi, Schiffers Paul M. H., Janssen Ger M., Kleikers Pamela W. M., Wipat Anil, Baumbach Jan, De Mey Jo G. R., Schmidt Harald H. H. W.. NOX5-induced uncoupling of endothelial NO synthase is a causal mechanism and theragnostic target of an age-related hypertension endotype. PLOS Biology. Vol. 18(11)2020. Public Library of Science (PLoS). [Cross Ref]


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