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  • American Association for the Advancement of Science (AAAS)  (3)
  • 1
    Online Resource
    Online Resource
    American Association for the Advancement of Science (AAAS) ; 2009
    In:  Science Translational Medicine Vol. 1, No. 1 ( 2009-10-07)
    In: Science Translational Medicine, American Association for the Advancement of Science (AAAS), Vol. 1, No. 1 ( 2009-10-07)
    Abstract: Thanks to the revolutions in information technology, human “-omics” research, and intricate medical device development, academic health centers (AHCs) now have an unparalleled potential to become translational engines that both generate basic science advances and then translate them into human studies and, ultimately, into improved health care. However, AHC infrastructures have traditionally been optimized to foster basic research. Now modifications must be made to meet these expanded roles of AHCs, from providing fundamental biomedical insights to first-in-human interventions and, if warranted, to larger randomized clinical trials. Eventually, AHCs must integrate these improved treatments into patient care. Challenges to this process have been defined by the Institute of Medicine. Building the appropriate infrastructures for human investigation and stabilizing the careers of young physicians essential to these translational events have become critical needs that will require systemic investments if AHCs are to respond to these biological revolutions and fulfill their promise.
    Type of Medium: Online Resource
    ISSN: 1946-6234 , 1946-6242
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2009
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  • 2
    Online Resource
    Online Resource
    American Association for the Advancement of Science (AAAS) ; 2010
    In:  Science Translational Medicine Vol. 2, No. 32 ( 2010-05-19)
    In: Science Translational Medicine, American Association for the Advancement of Science (AAAS), Vol. 2, No. 32 ( 2010-05-19)
    Abstract: Isolated gonadotropin-releasing hormone (GnRH) deficiency is a treatable albeit rare form of reproductive failure that has revealed physiological mechanisms controlling human reproduction, but despite substantial progress in discovering pathogenic single-gene defects, most of the genetic basis of GnRH deficiency remains uncharted. Although unbiased genetic investigations of affected families have identified mutations in previously unsuspected genes as causes of this disease in some cases, their application has been severely limited because of the negative effect of GnRH deficiency on fertility; moreover, relatively few of the many candidate genes nominated because of biological plausibility from in vitro or animal model experiments were subsequently validated in patients. With the advent of exciting technological platforms for sequencing, homozygosity mapping, and detection of structural variation at the whole-genome level, human investigations are again assuming the leading role for gene discovery. Using human GnRH deficiency as a paradigm and presenting original data from the screening of numerous candidate genes, we discuss the emerging model of patient-focused clinical genetic research and its complementarities with basic approaches in the near future.
    Type of Medium: Online Resource
    ISSN: 1946-6234 , 1946-6242
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2010
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  • 3
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 360, No. 6395 ( 2018-06-22)
    Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    RVK:
    RVK:
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2018
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
    SSG: 11
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