Image courtesy of Dr. Phil Bradley
You remember the last time you were laid up with the flu. The aches, the chills. Well, your immune system remembers, too — and it recorded that memory in your genes.
A study published this week by scientists at Fred Hutchinson Cancer Research Center suggests that, with enough work, we can decipher the hidden messages that our immune systems have recorded. That’s important because, if we could learn to decode this concealed knowledge, it could have enormous potential for diagnosing or treating disease, the researchers said.
In the study, published Aug. 28 in the journal eLife, the team examined genes in immune cells called T cells. The researchers showed that they could detect clear patterns among different individuals, and these patterns appeared to hint at previous viral exposures and shared genetic traits.
“I think it does paint an optimistic picture of the utility of T-cell repertoires as diagnostics,” said Dr. Phil Bradley, a Fred Hutch structural biologist and the study’s senior author.
Do we record our disease history in a shared language?
Though your disease history may be written in your DNA, it isn’t easy to translate. And whether the history of shared immune exposures is written in a shared immune “language” has been an open question for scientists in this field, Bradley said.
Their concern: “We all have some kind of immune memory, [but] maybe each person’s is written in some kind of idiosyncratic language that we’re never going to figure out,” he said. The worry still isn’t totally laid to rest, but his work supports the notion that our immune records do share a language that can be decrypted.
Fred Hutch file
The challenge: nearly infinite variation
To begin seeking this shared language, Bradley’s team focused on T cells, which use specialized molecules called T-cell receptors, or TCRs, to recognize when other cells are unhealthy, such as if the cells are infected by a virus.
But your immune system has no idea what life is going to throw at you. Maybe you’ll get the flu, or maybe you’ll get chicken pox. Maybe it will be cancer. Your immune system has come up with a way of churning out an almost limitless variety of TCRs to meet the potential pathogenic demand. As each T cell develops, it shuffles and rearranges the genes that make up its unique TCR. Tweaked and tailored, each new TCR is slightly different than the last.
TCRs assess your health by taking stock of bits and pieces of proteins that your cells display on their surface. Sometimes these come from your own proteins, and sometimes they come from a pathogen. These bits and pieces are called peptides. Peptides on display are cradled in molecules dubbed HLA, for human leukocyte antigen.
If a T cell’s TCR recognizes a specific peptide cradled in a particular HLA, this triggers the T cell to respond. The T cell multiplies itself and acquires the ability to persist in your body for decades. And its TCR genes become part of the permanent chronicle of your health.
Unfortunately for Bradley’s goals, HLA genes also differ quite a bit among people. This added twist makes it even more complicated to understand how a particular TCR gets etched in our immune history: If two people have different HLA variants, the same pathogen could be recognized by a separate TCR in each person. Thus, matching TCR to pathogen, or even TCR to HLA variant, is no easy task.
TCRs, peptides and HLA molecules come together in a complex 3D interaction. Ultimately, the language that Bradley is trying to translate is 3D as well. “It’s really the language of protein structure — the way they’re shaped and interact. That’s still really hard to model and predict,” he said.
Picking out shared patterns
How similar are the diverse collections of TCRs in different people’s immune systems? And do these similarities actually mean anything? To begin answering these questions, Bradley’s group started with only two dimensions. They turned to a publicly available database of TCR genes drawn from 666 healthy volunteers.
The 80 million unique TCR genes contained in the database had already been used by the Hutch’s Dr. Harlan Robins to link TCR patterns to known exposure to cytomegalovirus, a common and usually symptom-free childhood infection.
But Bradley wanted to ask the question in a slightly different way. What if the data held patterns that could be connected to infections whose identities weren’t known to the researchers?
In addition to the TCR gene sequences, they also had data on the volunteers’ HLA sequences and CMV exposure. The scientists also had information about how a TCR’s final 3D structure is influenced by the sequence of the DNA that codes for it, and the 2D sequence of the TCR proteins before they fold up to make their final 3D shape. They combined all this with information others had published that linked specific TCR sequences to specific pathogens.
His team developed methods to see whether different TCRs tended to be found together in some people but not others, and whether these clusters were associated with specific HLA variants or seemed to suggest a particular infection.
Indeed, the team was able to detect distinct TCR clusters — and often link them to certain HLA types or possible exposure to disease.
“One things of the things that was most striking was that you do see these clusters of T-cell receptors,” said Bradley. A number of different HLA backgrounds appeared to produce their own clusters. Information from the field also allowed the scientists to note that certain TCRs were likely triggered by distinct viruses.
In some cases, the fact that the same TCR popped up in different people seemed mostly likely due to the fact that they also shared HLA variants. In others, information from previously published studies strongly suggested that a TCR cluster was created in response to a specific, unknown infection. But because his data set didn’t include information about infection history beyond CMV, Bradley wasn’t able to nail this down.
“I think we’re safe in saying that we saw statistically significant patterns,” Bradley said. “What we can’t say for sure is that they correlate with an immune exposure versus, say, a genetic factor that causes a subset of the cohort [group of volunteers] to respond in a way that generates these TCR clusters. We couldn’t rule that out.”
The researchers are working to accumulate more information about immune exposures from the volunteers in the database to see if they can more strongly link pathogens to TCR clusters. Bradley is also excited to see if stronger associations with pathogen or with HLA type are lurking in TCRs' 3D structures.
Though there’s still much to learn, Bradley is enthusiastic about the possibilities if researchers can become fluent in the language of T-cell memory.
Perhaps TCR patterns could be used to detect whether a cancer patient is a good candidate for an anti-tumor immunotherapy. Or perhaps people prone to autoimmune diseases carry notable TCR patterns that might predict disease before symptoms begin.
Right now, these potential applications are far in the future. In the meantime, Bradley is cautiously optimistic.
“Our study certainly wasn’t the first to show that you have shared receptors among people, but it adds weight to the notion that even though there’s this vast potential for diversity [within each person’s T-cell collection], there are still interpretable patterns,” he said.
The memories of our immune systems do carry important messages, Bradley thinks — and we can learn to read them.
The National Institutes of Health funded this work.
Sabrina Richards, a staff writer at Fred Hutchinson Cancer Research Center, has written about scientific research and the environment for The Scientist and OnEarth Magazine. She has a Ph.D. in immunology from the University of Washington, an M.A. in journalism and an advanced certificate from the Science, Health and Environmental Reporting Program at New York University. Reach her at email@example.com.
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