摘要
在过去的十年中,试图找出与年龄相关的复杂疾病如心血管疾病,糖尿病和癌症的易感性的遗传因素进展十分缓慢。最近,两个重大的进展已经给了我们提升这一领域知识的新机会。其一,在与年龄相关的有机体的衰落(如细胞衰老)而不是基因的单障碍下,产生了研究分子机制的概念。此外,DNA技术的进步,发现了一些令人难以置信的常见的敏感性复杂性状的变异。尽管有这些进步,将这些发现应用于临床实践依然很困难。到目前为止,已经尝试了一些转化基因组学到药物的方法,以寻找最好的方式—基因的发现可能会提高我们在预测和预防一些复杂疾病基础问题的理解力。成功的策略似乎是同时测试多个与传统风险因素结合的易感变异。事实上,这种方法表明遗传因素大幅度改善了对复杂疾病的预测,特别是对冠心病和前列腺癌的预测,使得正确行为和医疗干预成为可能。 在未来,新的遗传变异的识别和它们纳入目前的风险模型可能会改善这些模型对其他复杂疾病如二型糖尿病和乳腺癌的歧视力。另一方面,对于低遗传性状,这种改进很可能是可以忽略的,这将促使传统与新发现的非遗传危险因素作用的研究。
关键词: 基因组的风险概况,遗传风险评分,预防医学,衰老,基因预测,全基因组关联研究。
图形摘要
Current Drug Targets
Title:The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence
Volume: 17 Issue: 4
Author(s): Alberto Montesanto, Silvana Geracitano, Sabrina Garasto, Sergio Fusco, Fabrizia Lattanzio and Giuseppe Passarino and Andrea Corsonello
Affiliation:
关键词: 基因组的风险概况,遗传风险评分,预防医学,衰老,基因预测,全基因组关联研究。
摘要: 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.
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Alberto Montesanto, Silvana Geracitano, Sabrina Garasto, Sergio Fusco, Fabrizia Lattanzio and Giuseppe Passarino and Andrea Corsonello , The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence, Current Drug Targets 2016; 17 (4) . https://dx.doi.org/10.2174/1389450116666150120103329
DOI https://dx.doi.org/10.2174/1389450116666150120103329 |
Print ISSN 1389-4501 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-5592 |
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