sábado, 9 de junio de 2018

Tracking the Translation of Genomic Discoveries to Population Health Benefits: Connecting the Dots from Investment to Population Health Information | | Blogs | CDC

Tracking the Translation of Genomic Discoveries to Population Health Benefits: Connecting the Dots from Investment to Population Health Information | | Blogs | CDC

Centers for Disease Control and Prevention. CDC twenty four seven. Saving Lives, Protecting People

Tracking the Translation of Genomic Discoveries to Population Health Benefits: Connecting the Dots from Investment to Population Health Information

Posted on  by Wei Yu and Muin J. Khoury, Office of Public Health Genomics, Centers for Disease Control and Prevention

a file folder labeled Grants with DNA



In March 2018, the CDC Office of Public Health Genomics launched the Grant Database (GDB), an extension of the Public Health Genomics Knowledge Base (PHGKB). GDB “connects the dots” between funding investment and publications on translation, implementation, and evaluation of population health impact of genomics and precision medicine.
We launched PHGKB in 2016, as an open-access, web-based, searchable information system. PHGKB systematically curates and updates information that bridges population-based research on genomics with clinical and public health applications. Details on PHGKB have been published in a scientific article and in a recent blog post. The main objective of PHGKB is to provide practitioners, consumers, and policy makers with an up-to-date view of the translational landscape of genomic medicine and related fields. The information includes guidelines and recommendations and systematic reviews as well as translation and implementation studies of genomic applications in the real world. Another rationale for PHGKB is to stimulate clinical and population research in promising applications to accelerate implementation and health impact. This rationale resulted from our observations that very little research is conducted to evaluate and implement promising genomic tests and applications. In fact, less than 2% of published genomics research falls in the category, “beyond bench to bedside” but is nevertheless essential in fulfilling the promise of genomics and precision medicine. We labeled this phenomenon as “the road less traveled.” Most funding for studies is geared towards discovery research or early translation (or bench to bedside), which might account for the lack of genomics publications. See our papers hereand here.
Now GDB, as one of the searchable databases, displays grant related information from the published literature deposited in Genomics & Health Impact Weekly Scan Database and the HuGE Literature Finder Database extracted from NCBI PubMed. A backend automatic script was created to retrieve four basic information (Grant ID, Acronym, Agency and Country) from the PubMed records when the information is available via NCBI E-utilities. Other reference information, such as the full funding agency names, were populated in the database based on the information on the NCBI website. The same search strategy used in other applications/databases in PHGKB was applied where users can perform a free text search. As of March 8, 2018, GDB contains grant information from eight countries and 479 agencies on more than 116, 000 records in PHGKB.
We illustrate the use of GDB in the context of genomic translation for our three top Tier 1 genomic applications: familial hypercholesterolemia (FH), hereditary breast and ovarian cancer (HBOC) due to BRCA mutations, and Lynch syndrome. Collectively, these conditions affect around 2 million people in the United States, most do not know they are affected. Existing but incompletely applied guidelines can save lives and prevent cancer and heart disease. Table 1 shows the total number of grants funded for each conditions, number of countries, funding agencies, and the contribution of the National Institute of Health (NIH). Grants are also connected to the type of publication (epidemiology, evidence synthesis, and translation/implementation studies). Most funded grants are in HBOC (796 grants), followed by Lynch syndrome (421) and lastly FH (239). Reported grant support comes from 42 funders (HBOC), 32 funders (Lynch) and 24 funders (FH). Most reported funding comes from the United States and the United Kingdom. Within the United States, NIH funded most grants (NCI for the two cancers and NHLBI for FH).
For now, GDB is a work-in-progress and it is important to acknowledge some limitations.
  • The database relies on PubMed information. The completeness of reported information is variable, mostly the grants from U.S. federal government agencies, especially NIH. As a result, the many papers in PHGKB contain grant information.
  • In addition, GDB lacks detailed grant information because of the technical inability to link directly with the NIH central grant database, due to non-standardized Grant IDs from PubMed. We provide a link to a third party web-based tool for NIH funding detail information whenever data are available.
In searching for information, we encourage users to experiment with GDB as a new feature of PHGKB. It may help them to “connect the dots” between funding investment and information and publications in genomic translation in the “road less traveled” to population health impact of genomics and precision medicine. We are eager to get input and feedback on how to continue to improve GDB and PHGKB in general.
An overview of grant information associated with 3 CDC tier 1 genomic applications, by country, agency and associated publications (analysis conducted using grants database on March 6, 2018
ConditionFamilial Hyper-
Cholesterolemia
No (%)
BRCA
(HBOC)
No (%)
Lynch
Syndrome
No (%)
Number of Grants239796421
Number of Funders244232
Country
USA115 (48%)591 (74%)322 (76%)
UK94 (39%)179 (23%)89 (22%)
Other30 (13%)26 (3%)10 (2%)
Funding
NHLBI or NCI73 (NHLBI)472 (NCI)239 (NCI)
Other NIH298548
Total NIH102 (43%)557 (70%)287 (57%)
Non-NIH137 (57%)239 (30%)134 (43%)
Associated Publications
Total55 (100%)226 (100%)161(100%)
Epidemiology28 (48%)140 (62%)58 (36%)
Translation/ Implementation14 (26%)74 (33%)69 (43%)
Evidence Synthesis/ Guidelines7 (13%)6 (2.5%)13 (8%)
Other5 (9%)6 (2.5%)20 (13%)
Please submit your comments here.
Posted on  by Wei Yu and Muin J. Khoury, Office of Public Health Genomics, Centers for Disease Control and Prevention

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