Insight into the biological make-up of complex disorders can improve their diagnosis, lead to the discovery of new targets for therapy, increase awareness of genome-environment interactions in health and disease, and open the door to predictive medicine. More than 1 600 genome-wide association studies (GWASs) have been published, and have identified hundreds of polymorphisms associated with more than 250 common diseases or traits. However, for most of the genomic variants identified so far only inconclusive associations with complex diseases have been reported and for many of them their predictive value reaches the same level as the traditional risk. The limited value of these results is probably due to regulatory elements in 2-3% of the encoding genome, whose function has only recently been partially decrypted. Nevertheless, genomic sequencing is an attractive tool for personalized medicine. During the last few years several commercial ventures have begun marketing GWASs directly to consumers for medical, genealogic, and even recreational purposes. Although these tests show promise for the future, consumers should be aware of the unreliability of most of their results at the present time. The development of methods integrating clinical and genetic data together with a better understanding of the heritability of complex diseases will be necessary in the endeavour to progress towards a personalized medicine. In order to achieve maximum benefits from GWASs while keeping the disadvantages to a minimum, guidelines will be necessary to manage the technical advances and to meet the challenges involved in the clinical application of whole genomic sequencing.

Dallapiccola, B., Mingarelli, R., Boccia, S., Genetic prediction of common complex disorders assessed by next generation sequencing and genome wide analysis, <<ITALIAN JOURNAL OF PUBLIC HEALTH>>, 2012; 9 (4): e8691.8-e8691-8. [doi:10.2427/8691] [http://hdl.handle.net/10807/39949]

Genetic prediction of common complex disorders assessed by next generation sequencing and genome wide analysis

Boccia, Stefania
2012

Abstract

Insight into the biological make-up of complex disorders can improve their diagnosis, lead to the discovery of new targets for therapy, increase awareness of genome-environment interactions in health and disease, and open the door to predictive medicine. More than 1 600 genome-wide association studies (GWASs) have been published, and have identified hundreds of polymorphisms associated with more than 250 common diseases or traits. However, for most of the genomic variants identified so far only inconclusive associations with complex diseases have been reported and for many of them their predictive value reaches the same level as the traditional risk. The limited value of these results is probably due to regulatory elements in 2-3% of the encoding genome, whose function has only recently been partially decrypted. Nevertheless, genomic sequencing is an attractive tool for personalized medicine. During the last few years several commercial ventures have begun marketing GWASs directly to consumers for medical, genealogic, and even recreational purposes. Although these tests show promise for the future, consumers should be aware of the unreliability of most of their results at the present time. The development of methods integrating clinical and genetic data together with a better understanding of the heritability of complex diseases will be necessary in the endeavour to progress towards a personalized medicine. In order to achieve maximum benefits from GWASs while keeping the disadvantages to a minimum, guidelines will be necessary to manage the technical advances and to meet the challenges involved in the clinical application of whole genomic sequencing.
2012
Inglese
Dallapiccola, B., Mingarelli, R., Boccia, S., Genetic prediction of common complex disorders assessed by next generation sequencing and genome wide analysis, <<ITALIAN JOURNAL OF PUBLIC HEALTH>>, 2012; 9 (4): e8691.8-e8691-8. [doi:10.2427/8691] [http://hdl.handle.net/10807/39949]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/39949
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