• Wien. Klin. Wochenschr. · Dec 2016

    Review Meta Analysis

    P4 medicine and osteoporosis: a systematic review.

    • Klemen Kodrič, Klemen Čamernik, Darko Černe, Radko Komadina, and Janja Marc.
    • Department of Clinical Biochemistry, Faculty of Pharmacy, University of Ljubljana, Askerceva cesta 7, 1000, Ljubljana, Slovenia.
    • Wien. Klin. Wochenschr. 2016 Dec 1; 128 (Suppl 7): 480-491.

    BackgroundOsteoporosis is the most frequent bone metabolic disease. In order to improve early detection, prediction, prevention, diagnosis, and treatment of the disease, a new model of P4 medicine (personalized, predictive, preventive, and participatory medicine) could be applied. The aim of this work was to systematically review the publications of four different types of "omics" studies related to osteoporosis, in order to discover novel predictive, preventive, diagnostic, and therapeutic targets for better management of the geriatric population.MethodsTo systematically search the PubMed database, we created specific groups of criteria for four different types of "omics" information on osteoporosis: genomic, transcriptomic, proteomic, and metabolomic. We then analyzed the intersections between them in order to find correlations and common pathways or molecules with important roles in osteoporosis, and with a potential application in disease prediction, prevention, diagnosis, or treatment.ResultsAltogether, 180 publications of "omics" studies in the field of osteoporosis were found and reviewed at first selection. After introducing the inclusion and exclusion criteria (the secondary selection), 46 papers were included in the systematic review.ConclusionsThe intersection of reviewed papers identified five genes (ESR1, IBSP, CTNNB1, SOX4, and IDUA) and processes like the Wnt pathway, JAK/STAT signaling, and ERK/MAPK, which should be further validated for their predictive, diagnostic, or other clinical value in osteoporosis. Such molecular insights will enable us to fit osteoporosis into the P4 strategy and could increase the effectiveness of disease prediction and prevention, with a decrease in morbidity in the geriatric population.

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