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Finding New Genetic Mutations Amid Healthy Cells

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Po-Ruh Loh
Po-Ru Loh Courtesy of Loh Lab

You might recall learning in biology class that the cells constantly replicating and dividing in our bodies all carry the same DNA, inherited in equal parts from each parent. But it’s become increasingly clear in recent years that even seemingly healthy tissues contain neighborhoods of cells bearing their own acquired genetic mutations. The question is: What do all those altered cells mean for our health?

With support from a 2018 NIH Director’s New Innovator Award, Po-Ru Loh, Harvard Medical School, Boston, is on a quest to find out, though without the need for sequencing lots of DNA in his own lab. Loh will instead develop ultrasensitive computational tools to pick up on those often-subtle alterations within the vast troves of genomic data already stored in databases around the world.

How is that possible? The math behind it might be complex, but the underlying idea is surprisingly simple. His algorithms look for spots in the genome where a slight imbalance exists in the quantity of DNA inherited from mom versus dad.

Actually, Loh can’t tell from the data which parent provided any snippet of chromosomal DNA. But looking at DNA sequenced from a mixture of many cells, he can infer which stretches of DNA were most likely inherited together from a single parent.

Any slight skew in those quantities point the way to genomic territory where a tiny portion of chromosomal DNA either went missing or became duplicated in some cells. This common occurrence, especially in older adults, leads to a condition called genetic mosaicism, meaning that, contrary to most biology textbooks, all cells aren’t exactly the same.

By detecting those subtle imbalances in the data, Loh can pinpoint small DNA alterations, even when they occur in 1 in 1,000 cells collected from a person’s bloodstream, saliva, or tissues. That’s the kind of sensitivity that most scientists would not have thought possible.

Loh has already begun putting his new computational approach to work, as reported in Nature last year [1]. In DNA data from blood samples of more than 150,000 participants in the United Kingdom Biobank, his method uncovered well over 8,000 mosaic chromosomal alterations.

The study showed that some of those alterations were associated with an increased risk of developing blood cancers. However, it’s important to note that most people with evidence of mosaicism won’t go on to develop cancer. The researchers also made the unexpected discovery that some individuals carried genetic variants that made them more prone than others to pick up new mutations in their blood cells.

What’s especially exciting is Loh’s computational tools now make it possible to search for signs of mosaicism within all the genetic data that’s ever been generated. Even more importantly, these tools will allow Loh and other researchers to ask and answer important questions about the consequences of mosaicism for a wide range of diseases.


[1] Insights into clonal haematopoiesis from 8,342 mosaic chromosomal alterations. Loh PR, Genovese G, Handsaker RE, Finucane HK, Reshef YA, Palamara PF, Birmann BM, Talkowski ME, Bakhoum SF, McCarroll SA, Price AL. Nature. 2018 Jul;559(7714):350-355.


Loh Lab (Harvard Medical School, Boston)

Loh Project Information (NIH RePORTER)

NIH Director’s New Innovator Award (Common Fund)

NIH Support: Common Fund; National Institute of Environmental Health Sciences