The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence

Curr Drug Targets. 2016;17(4):428-38. doi: 10.2174/1389450116666150120103329.

Abstract

Before the last decade, attempts to identify the genetic factors involved in the susceptibility to age-related complex diseases such as cardiovascular disease, diabetes and cancer had very limited success. Recently, two important advancements have provided new opportunities to improve our knowledge in this field. Firstly, it has emerged the concept of studying the molecular mechanisms underlying the age related decline of the organism (such as cellular senescence), rather than the genetics of single disorders. In addition, advances in DNA technology have uncovered an incredible number of common susceptibility variants for several complex traits. Despite these progresses, the translation of these discoveries into clinical practice has been very difficult. To date, several attempts in translating genomics to medicine are being carried out to look for the best way by which genomic discoveries may improve our understanding of fundamental issues in the prediction and prevention of some complex diseases. The successful strategy seems to be testing simultaneously multiple susceptibility variants in combination with traditional risk factors. In fact, such approach showed that genetic factors substantially improve the prediction of complex diseases especially for coronary heart disease and prostate cancer, making possible appropriate behavioural and medical interventions. In the future, the identification of new genetic variants and their inclusion into current risk profile models will probably improve the discrimination power of these models for other complex diseases such as type 2 diabetes mellitus and breast cancer. On the other hand, for traits with low heritability, this improvement will probably be negligible, and this will urge further researches on the role played by traditional and newly discovered non-genetic risk factors.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Cardiovascular Diseases / genetics
  • Cellular Senescence*
  • Diabetes Mellitus, Type 2 / genetics
  • Genetic Predisposition to Disease / genetics*
  • Genetic Variation
  • Genome-Wide Association Study
  • Genomics / methods*
  • Humans
  • Neoplasms / genetics
  • Phenotype