A new study shows that the microbial communities we carry in and on our
bodies -- known as the human microbiome -- have the potential to uniquely
identify individuals, much like a fingerprint. Harvard T.H. Chan School of
Public Health researchers and colleagues demonstrated that personal microbiomes
contain enough distinguishing features to identify an individual over time from
among a research study population of hundreds of people. The study, the first to
rigorously show that identifying people from microbiome data is feasible,
suggests that we have surprisingly unique microbial inhabitants, but could raise
potential privacy concerns for subjects enrolled in human microbiome research
projects.
The study appears online May 11, 2015 in the journal PNAS.
"Linking a human DNA sample to a database of human DNA 'fingerprints' is the
basis for forensic genetics, which is now a decades-old field. We've shown that
the same sort of linking is possible using DNA sequences from microbes
inhabiting the human body -- no human DNA required. This opens the door to
connecting human microbiome samples between databases, which has the potential
to expose sensitive subject information -- for example, a sexually-transmitted
infection, detectable from the microbiome sample itself," said lead author Eric
Franzosa, research fellow in the Department of Biostatistics at Harvard Chan.
Franzosa and colleagues used publicly available microbiome data produced through
the Human Microbiome Project (HMP), which surveyed microbes in the stool,
saliva, skin, and other body sites from up to 242 individuals over a months-long
period. The authors adapted a classical computer science algorithm to combine
stable and distinguishing sequence features from individuals' initial microbiome
samples into individual-specific "codes." They then compared the codes to
microbiome samples collected from the same individuals' at follow-up visits and
to samples from independent groups of individuals.
The results showed that the codes were unique among hundreds of individuals, and
that a large fraction of individuals' microbial "fingerprints" remained stable
over a one-year sampling period. The codes constructed from gut samples were
particularly stable, with more than 80% of individuals identifiable up to a year
after the sampling period.
"Although the potential for any data privacy concerns from purely microbial DNA
is very low, it's important for researchers to know that such issues are
theoretically possible," said senior author Curtis Huttenhower, associate
professor of computational biology and bioinformatics at Harvard Chan School.
"Perhaps even more exciting are the implications of the study for microbial
ecology, since it suggests our unique microbial residents are tuned to the
environment of our body -- our genetics, diet, and developmental history -- in
such a way that they stick with us and help to fend off less-friendly microbial
invaders over time."
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