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10.3390/ijms18061248

http://scihub22266oqcxt.onion/10.3390/ijms18061248
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C5486071!5486071!28604601
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suck abstract from ncbi


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pmid28604601      Int+J+Mol+Sci 2017 ; 18 (6): ä
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  • Personalized Medicine: New Perspectives for the Diagnosis and the Treatment of Renal Diseases #MMPMID28604601
  • Gluba-Brzózka A; Franczyk B; Olszewski R; Banach M; Rysz J
  • Int J Mol Sci 2017[Jun]; 18 (6): ä PMID28604601show ga
  • The prevalence of renal diseases is rising and reaching 5?15% of the adult population. Renal damage is associated with disturbances of body homeostasis and the loss of equilibrium between exogenous and endogenous elements including drugs and metabolites. Studies indicate that renal diseases are influenced not only by environmental but also by genetic factors. In some cases the disease is caused by mutation in a single gene and at that time severity depends on the presence of one or two mutated alleles. In other cases, renal disease is associated with the presence of alteration within a gene or genes, but environmental factors are also necessary for the development of disease. Therefore, it seems that the analysis of genetic aspects should be a natural component of clinical and experimental studies. The goal of personalized medicine is to determine the right drug, for the right patient, at the right time. Whole-genome examinations may help to change the approach to the disease and the patient resulting in the creation of ?personalized medicine? with new diagnostic and treatment strategies designed on the basis of genetic background of each individual. The identification of high-risk patients in pharmacogenomics analyses will help to avoid many unwarranted side effects while optimizing treatment efficacy for individual patients. Personalized therapies for kidney diseases are still at the preliminary stage mainly due to high costs of such analyses and the complex nature of human genome. This review will focus on several areas of interest: renal disease pathogenesis, diagnosis, treatment, rate of progression and the prediction of prognosis.
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