Comment

Filter By:

Article Type
  • The clinical application of genomic technologies is driving new discoveries that may be relevant to individuals who have previously undergone genetic testing. This Comment highlights the need for a framework to decide whether to recontact patients and inform them of new genetic findings.

    • Noor A. A. Giesbertz
    • Wim H. van Harten
    • Annelien L. Bredenoord
    Comment
  • A genomics-informed response to infectious disease has great potential to improve individual patient treatment as well as public health. This Comment discusses the ethical, legal and social challenges that will need to be overcome if clinical pathogen genomics is to be implemented successfully.

    • Stephanie B. Johnson
    • Michael Parker
    Comment
  • Variants of unknown significance (VUS) are genetic variants whose association with disease risk is unknown. The authors posit that VUS should not inform clinical decision-making as the benefits of returning this genetic information to patients undergoing genetic testing are outweighed by the potential for harm.

    • Samantha Pollard
    • Sophie Sun
    • Dean A. Regier
    Comment
  • This Comment discusses how data from smartphones or wearables could be used for behavioural phenotyping, knowledge that may help to reveal the genetic and environmental contributions to disease-related behavioural variation.

    • Nelson B. Freimer
    • David C. Mohr
    Comment
  • The lack of family health history experienced by most adopted persons can represent a marked disadvantage for these individuals. Genetic testing has the potential to reliably and usefully fill informational gaps, but considerable challenges need to be addressed to assemble an economic case for affordability.

    • Thomas May
    Comment
  • In personalized medicine, a major aim is to provide the right treatment to the right patient. In this Comment article, Gibson discusses how a more overt and genomics-informed focus on those individuals who are unlikely to benefit from treatment could reduce prescription rates and provide financial and health-care benefits.

    • Greg Gibson
    Comment
  • Genome-wide sequencing (GWS) is the most sensitive test available for detecting pathogenic genetic variants but it generates complex results. It is important, therefore, that individuals undergoing GWS are offered both pre-test and post-test genetic counselling.

    • Alison M. Elliott
    • Jan M. Friedman
    Comment
  • Current approaches for diagnosing mitochondrial disorders involve specialist clinical assessment, biochemical analyses and targeted molecular genetic testing. There is now a strong rationale for undertaking first-line genome-wide sequencing, accelerating the speed of diagnosis and avoiding the need for expensive and invasive investigations.

    • F. Lucy Raymond
    • Rita Horvath
    • Patrick F. Chinnery
    Comment
  • A recent patent granted for methods for diagnosing autism spectrum disorder (ASD) raises several ethical concerns beyond the fundamental question of whether genomic sequences are patentable, as it suggests that genetic testing can provide a diagnosis of ASD even before behavioural symptoms present.

    • Kristien Hens
    • Ilse Noens
    • Jean Steyaert
    Comment
  • Researchers should embrace differences in genetic background to build richer disease models that more accurately reflect the level of variation in the human population, posits Clement Chow.

    • Clement Y. Chow
    Comment
  • Caroline Wright, Matthew Hurles and Helen Firth propose that a principle of proportionality be applied to genomic data that weighs the depth of data (what is shared) against the breadth of sharing (with whom) to find a proportionate approach that balances beneficence and non-maleficence.

    • Caroline F. Wright
    • Matthew E. Hurles
    • Helen V. Firth
    Comment
  • Jesse Boehm and Todd Golub call for an international effort to establish >10,000 cancer cell line models as a community resource. Cancer cell line factories will facilitate the creation of a cancer dependency map, connecting cancer genomics to therapeutic dependencies.

    • Jesse S. Boehm
    • Todd R. Golub
    Comment