Toward Precision Medicine Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease (2011) / Chapter Skim
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3 What Would a Knowledge Network and New Taxonomy Look Like?
3 What Would a Knowledge Network and New Taxonomy Look Like?
Pages 41-58
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From page 41... ...
But what would these resources look like and what implications would they have for disease classification, basic research, clinical care, and the health-care system? This chapter describes the Committee's vision of a comprehensive Knowledge Network of Disease and New Taxonomy that would unite the biomedical-research, public-health, and health-care-delivery communities around the related goals of advancing our understanding of disease pathogene sis and improving health.
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From page 42... ...
As a consequence, diagnosis based on traditional "signs and symptoms" alone carries the risk of missing opportunities for prevention, or early intervention can readily misdiagnose patients altogether. Even when histological analysis is performed, typically on tissue obtained after diseases become clinically evident, obtaining optimal diagnostic results can depend on supplementing standard histology with ancillary genetic or immunohistochemical testing to identify specific mutations or marker proteins.
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From page 43... ...
. Despite the focus on the individual patient in the creation of the Information Commons, the Committee expects that the inclusion of patients from diverse populations coupled with the incorporation of various types of infor 1 As with all patient-related data in electronic medical records and contributed to the Informa tion Commons, information in the exposome layer requires that attention be paid to data sharing, informed consent, and privacy issues; see discussion Chapter 4.
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From page 44... ...
By incorporating data derived from multi-level assessments, a Knowl edge Network of Disease could lead to better understanding of the variables and mechanisms underlying disease and health disparities, thereby helping to reveal a truer picture of the ecology of human health and facilitating a more holistic ap proach to health promotion and disease prevention. mation contained in the exposome will result in a Knowledge Network that could also inform the identification of population-level interventions and the improvement of population health.
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From page 45... ...
While molecular variables are often more easily measured and more directly tied to disease outcomes, if the modifiable factors that have contributed to the signature are known, we will be better able to prevent disease and to phenotype, genotype, and treat patients. Asthma illustrates the interplay of social, behavioral, environmental, and genetic factors in disease classification.
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From page 46... ...
THE PROPOSED KNOWLEDGE NETWORK OF DISEASE WOULD GO BEYOND DESCRIPTION A Knowledge Network of Disease would aspire to go far beyond disease description. It would seek to provide a unifying framework within which basic biology, clinical research, and patient care could co-evolve.
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From page 47... ...
of a disease with an unknown pathogenic mechanism to the information avail able for better understood diseases. Similarities between the molecular profiles of diseases with known and unknown pathogenic mechanisms might point directly to shared disease mechanisms, or at least serve as a starting point for directed molecular interrogation of cellular pathways likely to be involved in the pathogenesis of both diseases.
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From page 48... ...
In other cases, the identification of links between environmental factors or lifestyle choices and disease incidence may make it possible to reduce disease incidence by lifestyle interventions. Importantly, as discussed below, the Committee believes the Knowledge Network and its underlying Information Commons would enable the discovery of improved treatments by providing a powerful new research resource that would bring together researchers with diverse skills and integrate knowledge about disease processes in an unprecedented way.
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From page 49... ...
Such data would allow more rational recom mendations regarding risk-reduction strategies, thereby creating enormous value for individual patients, health-care providers, and payers, by making it possible to avoid unnecessary screening and treatment while reducing cancer incidence and promoting early detection. of researchers would ultimately prove to be a Knowledge Network of Disease's greatest legacy for biomedical research.
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From page 50... ...
However, the Committee regards the Information Commons and Knowledge Network of Disease, as potentially powerful tools for understand ing and addressing health disparities because they would be informed by data on the environmental and social factors that influence the health of individual patients. For the first time, these resources would bring together, in the same place, molecular profiles, health histories, and data on the many determinants of health and disease, thereby optimizing the ability to decipher the mechanisms through which exogenous factors give rise to endogenous, biological inputs, directly affecting health.
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From page 51... ...
The Knowledge Network of Disease, created by integrating data in the Information Commons with fundamental biological knowledge, drawn from the biomedical literature and existing community databases such as GenBank, would be the centerpiece of the informational resources underlying the New Taxonomy. The Committee envisions this network as: Highly inter-connected.
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From page 52... ...
The data in the Information Commons and Knowledge Network serve three purposes: (1) they provide the basis to generate a dynamic, adaptive system that informs taxonomic classification of disease; (2)
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From page 53... ...
Furthermore, the available information would need to be mineable in ways that are custom-tailored to the needs of different users, possibly by implementation of purpose-specific user interfaces. While the Committee agreed upon the generalities listed above and illustrated in Figure 3-1 about the Information Commons and Knowledge Network -- and their relationship to a New Taxonomy -- specifics of implementation such as the detailed design of the Information Commons, the information technology platforms used to create it, questions about where key infrastructure should be physically housed, who would oversee it, and how the Information Commons would be financed, were considered beyond the scope of the Committee's charge in a framework study.
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From page 54... ...
So, what is the difference between the Committee's vision of the Information Commons and Knowledge Network of Disease and reasonable extrapolations of what the NCBI has already accomplished? The key difference is that the Information Commons, which would underlie the other databases, would be "individual-centric." The various databanks curated by NCBI generally only contain a single disease parameter and even if multiple pieces of information from an individual make it into multiple data banks -- say a breast cancer patient's transcriptome stored in the GeneOmnibus database of published microarray data and information about her chromosome translocations in the Cancer Chromosome databank -- they are not linked be tween databases.
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From page 55... ...
and dramatic improvements in database technology in many ways analogous to the driving forces current advances in data generation and handling in biomedicine, it became apparent to many users of geographically indexed information that a surprisingly high portion of the world's information could be organized around GPS coordinates. Like the proposed Information Commons, GISs are layered data structures that inter-connect vast amounts of information and can be mined for information that is not readily apparent in the primary GPS of an object.
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From page 56... ...
The individual-centric nature of an Information Commons is an important means of ensuring that the data underlying the Knowledge Network, and its derived taxonomy, would be constantly updated. As participating patients undergo new tests and treatments, associated information would enter the Information Commons and, on the basis of these data, the taxonomies, such as the ICD, could be updated continuously.
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From page 57... ...
Inevitably, the Knowledge Network initially would be devised primarily through data acquired, placed in the Information Commons, and analyzed by researchers and medical institutions in developed countries. However, a comprehensive and fully developed Knowledge Network of Disease must in clude the many diseases, including infectious diseases and disorders linked to geographically limited environmental exposures that are endemic in low- and middle-income settings throughout the world.
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From page 58... ...
Indeed, the individual-centric character of the Information Commons -- and the inclusion of available data about contributing individuals, including information about where and in what circumstances they live -- offers an unprecedented path toward a Knowledge Network of Disease that can meet global needs for health care and disease prevention.
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