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An Inner 'Fingerprint' For Personalizing Medical Care

Aug. 24, 2009 — Fingerprints move over. Scientists are reporting evidence that people have another defining trait that may distinguish each of the 6.7 billion humans on Earth from one another almost as surely as the arches, loops, and whorls on their fingertips. They report evidence from studies in humans for the existence of unique patterns in metabolism.


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Metabolism is a whole caboodle of chemical processes. The body uses to turn food into energy, grow, repair damage from diseases and injuries, use medicines, and carry out other functions necessary to continue living. In the new study, Ivano Bertini and colleagues cite growing evidence that each individual has a unique metabolic profile. It's a biochemical counterpart to fingerprints that can be detected by analyzing the chemical whorls and grooves that result from metabolism and can be detected in the urine.

Doctors have dreamed of using such tests for the early diagnosis of disease and personalized medical care. They could pick drugs and treatments that are best for each individual, rather than today's one-size-fits all medicine. To do so, however, doctors need evidence that the metabolic fingerprint remains stable over a period of years, with changes due to disease or medications, for instance, but not advancing age or other factors. The new study provides that evidence, based on the analysis of over 1,800 urine samples from people monitored for 2-3 years. Researchers could identify individual patients from their metabolic profiles with an accuracy of over 99 percent. The study could pave the way for using metabolic profiling to apply personalized medical care, the researchers suggest.

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The above story is reprinted from materials provided by American Chemical Society, via EurekAlert!, a service of AAAS.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.


Journal Reference:

  1. Bernini et al. Individual Human Phenotypes in Metabolic Space and Time. Journal of Proteome Research, 2009; 090625075642001 DOI: 10.1021/pr900344m
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