Clinical Exposomics Emerging As A Foundation For Precision Medicine

November 17, 2022

By Deborah Borfitz 

November 17, 2022 | High-resolution mass spectrometry methods are in principle “good enough” to put into clinics everywhere to measure low-abundance environmental chemicals and start cataloguing individual exposures, according to Dean Jones, Ph.D., professor of medicine and biochemistry at Emory University and director of its Clinical Biomarkers Laboratory. Jones was speaking at the Mayo Clinic’s recent Individualizing Medicine Conference focused on the “exposome"—the measure of all the exposures of an individual in a lifetime and how those exposures relate to health—and his presentation examined clinical exposomics as a foundation for precision medicine. 

As Jones sees it, clinical exposomics can be built on what is being learned in environmental epidemiology, or what he calls exposome epidemiology. New analytical capabilities can characterize individuals based on their chemical fingerprint and the information could be used in a “diagnostic and predictive way,” he says.  

“The cautionary note is we can’t do it yet,” adds Jones, highlighting the daunting task of mapping out all the different exposures given the vast number of potentially problematic chemicals. To make matters worse, people have multiple morbidities as well as multiple exposures. 

“We not only have to be able to understand the exposures, but we also have to deconvolute that from all the different disease processes that are possible,” Jones says. “We really need to have a health surveillance and forecasting system,” he continues, drawing an analogy to the decades-long approach taken by the National Weather Service to improve the accuracy of hurricane forecasting by looking at the failures of its models. 

His dream for more than a decade now is for clinical chemistry programs throughout the country to capture as much information on people’s chemical exposures as possible, Jones says. In the future, this will permit biochemical analyses of human samples to detect abnormalities and guide treatment of them—just as genomics has, against significant odds, given medicine the ability to predict risks and manage outcomes. 

Problems and Progress 

An important milestone in clinical exposomics was achieved a decade ago with the newfound ability to measure more than 20,000 chemical signatures in a single small human plasma sample, says Jones, including the detection of low-abundance metabolites (BMC Bioinformatics, DOI: 10.1186/1471-2105-14-15). “The analytical capabilities are far beyond what we can actually use, and the big problem is that we can detect these signals, but we can’t really detect them reliably, reproducibly, and in a way where we can build a cumulative database.” 

Part of the problem is that mass spectrometry analyses produce coefficients of variation, as a function of signal intensity, that are small, he explains. But most of the environmental chemicals being measured in the body are in very low abundance. The average coefficient of variation seen for these by current methods is only about 30%, far short of the goal (10% to 15%) for a clinical-grade assay. 

To capture the low abundance of environmental signals more reliably, Jones’ tactic is to do triplicate analyses of each analyte. “We have made some progress in best strategies for high abundance signals for metabolomics,” he states. “For the low abundance signals we really don’t have good strategies.” 

Traditional statistical approaches designed to produce good measurements in everybody also aren’t useful, he adds, at least for exposures relevant only to a fraction of the population. Over the past few years, efforts have focused on mapping out environmental exposures based on the metabolic products of those chemicals. 

One critical discovery was that a family of products can be measured based on their common biological precursors in lieu of measuring xenobiotics (foreign chemicals) individually, says Jones. Data scientists still need to create a practical, easy-to-use tool exploiting those known alignments. 

Jones and his colleagues have also developed gas chromatography procedures for the detection of environmental chemicals. In a paper published last year in Nature Communications (DOI: 10.1038/s41467-021-25840-9), they demonstrated its ability to measure over 1,000 environmental chemicals in a single analysis. “This is a true breakthrough if we could deliver this for a clinical chemical measurement,” he says. 

The method was used to discover a metabolite produced by the microbiome, as reported last year in Nature Metabolism (DOI: 10.1038/s42255-021-00502-8). Here, researchers showed that valerobetaine, which is produced from lysine in the diet, inhibits mitochondrial fatty acid oxygenation that would otherwise happen during sleep. Consequently, the fat gets deposited in the liver and adipose tissue. 

“We don’t have experimental studies in humans, but we have correlative data showing that in fact this chemical is associated with fatty liver and with increased BMI [body mass index] in humans,” says Jones. 

Research Paradigm 

The metabolic effects of substances in the body can be quite dramatic, Jones notes, pointing to the results of a clinical study conducted 12 years ago suggesting challenge tests could be applied to individuals using high-resolution methods to “very exquisitely detect changes in metabolism with different exposures.” As described in a paper published in The Analyst (DOI: 10.1039/c0an00333f), the chemical metabolic profiles of individuals fed a diet deficient in an essential amino acid (methionine) differed from those given a nutritionally replete diet. One young, thin woman on the methionine-deficient diet who showed no outward symptoms nonetheless experienced a profound metabolic change.  

Studies in nematodes and rodents have allowed exposome researchers to measure cause-effect relationships between environmental exposures and health outcomes, he says. In a mouse study published in 2019 (American Journal of Pathology, DOI: 10.1016/j.ajpath.2019.04.013), researchers showed a dietary level of cadmium (a toxic metal) potentiates the severity of respiratory syncytial virus (RSV) as measured by lung RSV titer and increased inflammation. The difference between the control and cadmium treatment groups, in human terms, was like “eating sunflower seeds from sunflowers that were grown in North Dakota versus those grown in the southern part of Oklahoma,” says Jones. 

The same exposome research paradigm has been seen in human research, as first evidenced by a study that published in 2016 (International Journal of Epidemiology, DOI: 10.1093/ije/dyw218) where high-resolution metabolomic exposomic analysis was used to measure occupational exposures to trichloroethylene.  

Exposome researchers have measured metabolomics for most of the top 40 causes of chronic health conditions in humans, says Jones. “We now have that foundation where we can extend this to understanding the... forecasting of disease.” 

Bidirectional Response 

Many types of exposome frameworks are emerging, notably for newborns in terms of pregnancy outcomes and childhood development, he continues. The European Human Exposome Network, for example, is funding an international project (ATHLETE) measuring various environmental exposures to better understand their impact from pregnancy to adolescence.    

Dozens of studies are now available mapping out the metabolic functional responses to different exposures, notably air pollution, says Jones. “The development of this research is really much further along than we have been able to assimilate.” 

Metabolomics-based studies find remarkably similar patterns for many different types of lung diseases, he adds. This suggests the utility of a “meet-in-the-middle approach” where an exposure and disease outcome can be examined simultaneously based on their metabolic relationship. “What we’re realizing now is that it is more complicated than that because there is a functional reprogramming from the exposures,” akin to the reported epigenomic effects associated with exposures. 

“We just don’t know what that full spectrum of reprogramming really entails, but what we know from our epidemiology research is that disease changes behavior and behavior changes exposures, so we have this complication in terms of being able to map out the sequence of events because it’s not just a one-directional response structure,” says Jones. “It’s bidirectional.” 

‘Tremendous Potential’ 

In a 2018 metabolome-wide association study of anti-epileptic drug treatment during pregnancy (Toxicology and Applied Pharmacology, DOI: 10.1016/j.taap.2018.12.001), it was observed that different drugs were associated with different metabolic pathways. “What this means is if we could map out a woman’s response to the drug, and if that were linked to adverse outcomes, we may be able to simply switch the medication, and this could be done on a personalized basis ... to minimize the risks to the mom and to the baby,” says Jones. 

But to date, the closest science has come to translating exposome epidemiology data into clinical exposomics approaches for improving individualized medicine is related to alcohol consumption and smoking during pregnancy, he quickly adds. 

Clinical exposomics nonetheless has “tremendous potential” in managing disease trajectories, says Jones, in some cases by modifying exposures. “We just need the clinical platforms to be able to do high-throughput accurate quantitative measures of exposures and we are not quite there [yet].” 

But real-world precision medicine applications are suggested by what has already been learned from clinical exposomic measures—including the fact that air pollution causes a decline in arginine, which in turn causes a potentiation of inflammation, he says. Theoretically, precursors to arginine could be introduced via a dietary or therapeutic intervention to change the body’s metabolism of the amino acid in a way that protects sensitive individuals against adverse outcomes.