Milestone for Personalized Medicine
A detailed study predicts the onset of diabetes and shows that treatment works
Source: “Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes”
Michael Snyder et al.
Cell 148: 1293–1307
RESULTS: After sequencing his own genes, Stanford University geneticist Michael Snyder discovered that he had a high risk of developing type 2 diabetes. He and colleagues measured changes to 40,000 of his biological variables that could be associated with diabetes, such as gene and metabolite activity. After he developed the disease, the data they’d collected revealed the precise time of onset: his diabetes seems to have been triggered by a cold. They observed how the disease changed the variables they were monitoring. Treatment, including diet and exercise, returned the molecular markers that reflected diabetes to their normal state.
WHY IT MATTERS: The case study is one of the most extensive biological profiles of an individual to date and the first to closely monitor molecular changes as a disease progresses. The results show that genomics can be combined with dynamic molecular and physiological data to identify the beginning of a disease sooner than is possible with conventional measures, and to closely track the effect of treatment. This might lead to personalized treatments that improve patient health.
METHODS: Researchers sequenced Snyder’s DNA and transcription RNA, which copies DNA, and generated profiles of his protein, metabolite, and antibody levels. They monitored changes over the course of 14 months, taking 20 blood samples and analyzing a total of three billion data points.
NEXT STEPS: The researchers plan to use the new approach to study more patients, with the goal of identifying the most useful biological markers for diabetes and gaining new insight into its triggers. This could help them reduce the number of biological markers that need to be studied, which is essential to making personalized medicine affordable. Collecting the data for the study cost $2,500 per blood sample, a figure that doesn’t include the cost of analyzing the data. Eventually, the researchers plan to apply the approach to understanding and treating other diseases.
Forecasting Heart Attacks
A new test could tell doctors when danger is imminent
Source: “Characterization of Circulating Endothelial Cells in Acute Myocardial Infarction”
Eric J. Topol et al.
Science Translational Medicine 126: 1–9
RESULTS: An automated procedure typically used in cancer care and research was used to measure and characterize a type of cells called circulating endothelial cells, which are associated with heart attacks. The test showed that levels of the cells in heart attack victims were four times higher than in healthy people. The cells were also larger and abnormally shaped, and they had multiple nuclei.
WHY IT MATTERS: Although stress tests and other procedures can detect problems that could lead to heart attacks, they don’t predict when a heart attack will occur. In some cases, people who appear healthy according to these tests have heart attacks just a few days later. Researchers have known that circulating endothelial cells are connected to heart attacks, but doctors lacked a good way to test for them. Because the test the researchers used can detect elevated levels of the cells and can recognize cellular abnormalities that are closely associated with heart attacks, it might help doctors identify people who are at imminent risk and take preventive measures, such as putting them on medication to prevent a blood clot or monitoring them in the hospital.
METHODS: Using a commercially available type of fluorescence microscopy, the researchers isolated and imaged circulating endothelial cells from blood samples of 50 emergency-room patients who had had heart attacks. They compared the results with tests on a group of 44 healthy people.
NEXT STEPS: Before the test can be used clinically, the results must be replicated. Researchers hope to develop a commercial blood test within two years.
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