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      Mechanistic endotyping of the ROS/cGMP disease cluster in the Estonian Biobank

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            Abstract

            We hardly comprehend any disease mechanistically, meaning most disease definitions are organ- and symptom-based and fail to represent the underlying mechanism of the disease. Current therapies can thus only treat symptoms chronically yielding unprecise and low patient-relevant outcomes ( 1, 2). Symptom-based disease definitions also have the risk of agglutinating different molecular mechanisms that cause similar symptoms under umbrella disease terms. As a result, they are combined into a single common and complex disease entity that is impossible to untangle with present diagnostic methods. Contrarily, apparently unrelated disease phenotypes co-occur in the same patient beyond chance, which may indicate shared causal mechanisms ( 3). Thus, in order to reach precision medicine and to achieve treatment accuracy, we must first determine the underlying disease mechanism and endotype patients based on the cause of the disease. This approach will redefine diseases, shifting the focus from symptoms and affected organs to the underlying mechanisms and causes ( 4). Here, we investigate one of the best studied diseasome clusters of fourteen heterogeneous cardiovascular, neuro-psychiatric, metabolic and pulmonary comorbid disease phenotypes of unmet medical need, defined - at least in part - by reactive oxygen species ( ROS)-induced dysfunction of and cGMP signaling (ROCG) ( 5, 6). Previously, we have shown that NADPH oxidase 5 (NOX5) levels in endothelial microparticles were able to identify the ROCG endotype in hypertensive patients ( 7). Here, we used a high-throughput screening plasma antibody assay to measure NOX5 plasma levels and analyze over 1,000 human samples of the ROCG cluster in collaboration with the Estonian biobank to identify the prevalence of the ROCG endotype. Stratifying patients according to both phenotype and endotype will allow for high precision, i.e., low number needed to treat therapeutic interventions. These data show that even for supposedly complex diseases, endotyping for precision medicine and mechanistic disease re-definition is possible.

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            Author and article information

            Conference
            RExPO23 Conference
            REPO4EU
            19 October 2023
            Affiliations
            [1 ] Maastricht University, Department of Pharmacology and Personalised Medicine, Maastricht (The Netherlands) ( https://ror.org/02jz4aj89)
            [2 ] Institute of Genomics, University of Tartu, Tartu, Estonia;
            [3 ] Institute of Genomics, University of Tartu, Tartu, Estonia ( https://ror.org/03z77qz90)
            [4 ] Maastricht University, Department of Pharmacology and Personalised Medicine, Maastricht (The Netherlands);
            Author notes
            Author information
            https://orcid.org/0000-0001-7535-0417
            https://orcid.org/0000-0003-2362-656X
            https://orcid.org/0000-0002-1667-0266
            https://orcid.org/0000-0002-1332-8713
            https://orcid.org/0000-0001-9748-1020
            https://orcid.org/0000-0002-5323-3102
            https://orcid.org/0000-0003-1982-6569
            https://orcid.org/0000-0002-3718-796X
            https://orcid.org/0000-0002-2964-6011
            https://orcid.org/0000-0003-0419-5549
            Article
            10.58647/REXPO.23000033.v1
            d8c26bcd-0dad-494a-a253-896aaa762a58

            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 .

            RExPO23
            2
            Stockholm, Sweden
            25-26 October 2023
            History
            : 19 October 2023
            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/501100007601, Horizon 2020;
            Award ID: 777111
            Funded by: funder-id http://dx.doi.org/10.13039/100018696, HORIZON EUROPE Health;
            Award ID: 101057619
            Categories

            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Bioinformatics & Computational biology
            diagnostics,precision biomarkers,disease endotyping,precision medicine,systems medicine,network pharmacology

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