The "Omics" Era: New Biomarkers Of Metabolic Disease Risk?

11/3/2014

by Wei Perng, PhD

Recent technological advances have landed us in a new age of research known as “the omics” era. While the number of omics categories is rapidly increasing, the core four involve the large-scale evaluation of gene expression (genomics), mRNA expression (transcriptomics), protein structure and function (proteomics), and metabolite patterns (metabolomics) - all in hopes to gain knowledge on disease development. Scientists have recently taken a keen interest in metabolomics; specifically, on how low-molecular-weight compounds (e.g. amino acids, carbohydrates, fatty acids, hormones) in tissue can provide information on disease progression and prognosis. Metabolomics could provide a snapshot of the good, the bad, and everything in between.

The concept of using metabolite composition to evaluate disease status is not new. Back in 1500 B.C., traditional Chinese doctors used ants to determine whether a patient’s urine contained high glucose levels characteristic of diabetes. Modern-day doctors have more complex tools to assess diabetes risk, but the same concept of quantifying glucose concentrations in biofluids is applied in the fasting blood sugar test and oral glucose tolerance test. Other examples of metabolomics in clinical practice include the quantification of blood urea, glutamine, and arginine to evaluate liver function, and measuring serum urea nitrogen and creatinine levels to gauge kidney function. Metabolomics has even blazed a path in the field of toxicology as a comprehensive way to assess physiological changes caused by chemical exposures.

Some new evidence suggests that certain metabolite patterns in blood may actually signal future risk of disease. In 2009, Newgard et al. reported that a metabolite profile characterized by high circulating levels of branched-chain amino acids (BCAA) and related metabolites corresponds with obesity status and contributed to the development of insulin resistance in adult humans and rodents. Following this work, Wang et al. conducted a prospective cohort study in healthy middle-aged adults and discovered that the BCAA metabolite pattern preceded development of type 2 diabetes by over a decade – independently of weight status - suggesting that aberrances in BCAA metabolism may serve as an early marker of diabetes risk. This finding is especially exciting because metabolic diseases are often present years before becoming clinically apparent, but by the time they are detected considerable damage has already occurred. Taking the example of diabetes, by the time hyperglycemia manifests, substantial pancreatic cell damage has transpired, highlighting the need to identify more downstream biomarkers.

So what are the next steps? First and foremost, additional longitudinal studies examining the link between metabolite patterns and disease incidence are necessary to confirm the findings of Wang et al. There is also a need to examine these associations in pediatric populations, as most metabolic risk factors begin early in life and track into adulthood. Our research group at OPP recently conducted a cross-sectional study of 262 mother-child pairs in Project Viva, and found that obese children had higher blood BCAA than their lean counterparts. Furthermore, the BCAA metabolite pattern was directly associated with other indicators of adiposity, such as fat mass and skin-fold thicknesses, as well as with biomarkers of metabolic risk, including insulin resistance, inflammation, and altered satiety hormones. As the children get older, we hope to examine whether this metabolite pattern is associated with development of adiposity and worsening of the biomarkers.

Taken together, current evidence hints at the utility of metabolomics in metabolic risk assessment. However, whether metabolic profiling can be used regularly in the clinic depends on the strength of future study findings, and improvements in technology to lower the cost of running metabolic panels.

2 Comments

Gautham Sridharan

11/3/2014 05:51:49 am

Nice article! Metabolomics analysis does indeed have promise to characterize several disease states!

Wei Perng

11/4/2014 06:53:08 am

Thanks, Gautham! We deal predominantly with obesity-related disease at OPP, but I know you do interesting work with liver tissue. I would love to hear more about it sometime!

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