Eric Green, director of the National Human Genomic Research Institute writes in Nature, “Charting a course for genetic medicine from base pairs to bedside.”[1] This research perspective comes about as close to must reading as anything in the medical literature. Not much happened in the ten years since the completion of the human genome to improve health care, but significant advances in understanding the complexities and cataloging the data, sets the stage for the next ten years during which genetic information will contribute hugely to the health care of our Nation.
As a participant, I have been away from medicine. When I sold the clinic, I came north to fly in the bush. The closest I came to medicine was the evacuation by floatplane of a fisherman with a gaff hook through his hand from a cove north of Kodiak Island. Away from medicine, however, I had time to think about the problems. I don’t think they have solved them yet, but I am fascinated by the potential for the electronic health record and medical information technology to solve problems of public health and cost as well as more accurate diagnosis and better treatment. I built a differential diagnosis based electronic patient record with Borland’s Paradox database back in the 80s. I did it more or less as a hobby, but it addressed one of the weaknesses in the present diagnostic coding system, the ICDA as it is presently used. It is a problem that still exists. I do not see it addressed adequately in present informatics literature.
The reader may be aware that the US ranks 46th out of 178 countries in infant mortality, --according to the CIA’s research 2009 -- and 37th in life expectancy. These numbers keep getting worse every time I look. There are many causes, by my opinion: access to the system, poor distribution of doctors and a significant population seeking deleterious alternative care or no care because of cost. More importantly, there may be a system problem over diagnosis caused by the requirement for a too early diagnosis in order to justify tests and reimbursement – even a reluctance to consider possibilities for fear of rendering the patient uninsurable. We have incredibly sophisticated treatment algorithms directed towards best evidence, but if the diagnosis is wrong, these guidelines are of little use. Autopsies were once the final word on diagnosis. A hospital was ranked in quality by its autopsy rate, but that is a thing of the past. Even then, there was argument over diagnosis at clinical pathological and morbidity and mortality conferences. Genomics, more than anything else, promises to offer not only a more accurate diagnosis, but also a statistically validated differential diagnosis.
Eric Green’s “course for genomic medicine,” emphasizes the cataloging of DNA: indexing genes underlying rare and common disease, the genomes of pathogens and the mutations in tumors into structured files. The National Human Genome Research Institute (NHGRI) launched a public research consortium, the Encyclopedia of DNA Elements (ENCODE) in September 2003, to carry out a project identifying all functional elements in the human genome. The relational database will need to correlate the structured files of the genome with similar structured files of all recognized medical diagnoses in order to associate, over time, all parameters of the human genome with human disease. Thus far, the Human Genome Project yields 3,000 monogenic (Mendelian) diseases and some 900 loci and complex multigenic traits. That leaves 98% or more of the remainder unknown as to its function. We are clearly at the beginning of a translational period that is at first learning the correlation between the parameters of patient symptoms, physical findings, tests and genomics to the malady in question.
Just as, the relational database requires complete genomic data, so too, the database requires an indexing of all known human illness, a large order. ICDA, the current classification of disease falls short in this requirement. CMIT until its discontinuation came close. When we have these two structured databases -- the patient and the total indexing of disease -- we will be able to identify vast amounts of unsuspected relationship between the unknown parts of the human genome and the human condition, predictive and otherwise. There will be years of data mining before valid directed diagnosis becomes a reality. Eric Green predicts 2020 before the data substantially predicts, prevents and treats based on new knowledge.
Over the past ten years, the cost of the human genome has plummeted. Massive parallel DNA sequences shorten the time required as well as cost. We have come a long way in understanding the genetic basis of disease. We recognize bio-information in non-coding DNA as well as the complexity associated with structural change and its role in disease. We recognize the role of the genome in cancer and tumor subtypes, and we do routine pharmacogenetic tests before certain drug treatments.
The NHGRI goals for 2020 include routine orders for complete genetic profiling, genomics incorporated into the electronic health record (EHR) and education of the clinicians in the use of the information.
Multiple institutions pursue these goals. I put my faith in a relational database correlating statistically the patient record with the index of all medical disease to produce a statistically validated differential diagnosis. Mine is a clinician’s viewpoint, thirty years worth. Other institutions The University of Maryland and others are working with IBM’s Watson. Watson’s ability to read and apply unstructured narrative data may mitigate the need for scrupulous indexing of both medical information and genomics. I hope it works, and look forward to reports of success. In either case, diversity is good. The more avenues pursued in solving our health care problems, the more scientific will be the outcome. Whatever the final strategy, it should stress a continuing educational flow of current medical information to the clinician. That’s where the rubber meets the road and where motivation and information is most critical.
Eric Green’s article goes on to include societal concerns and a next generation of researchers. As I said this perspective should be must reading.
http://www.nature.com/nature/journal/v470/n7333/full/nature09764.html
http://www.nature.com/nature/journal/v470/n7333/full/nature09764.html
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