In this final blog post of our 3-part series on clinical metabolomics, we summarize a recent paper that highlights how metabolomics can be used to identify novel metabolic abnormalities and potential biomarkers associated with an inherited metabolic disorder called GLUT 1 deficiency syndrome (GLUT1-DS). The study is the first to investigate metabolomics perturbation in GLUT1-DS patients, as well as treatment of the disorder with a ketogenic diet (KD), which is currently the only treatment available.

Adam Kennedy, PhD  |  Director, Scientific Discovery & Application, Metabolon

Biochemical Phenotyping & Inherited Metabolic Disorders

In this final blog post of our 3-part series on clinical metabolomics, I’d like to summarize a recent paper¹ by Cappuccio et al. that highlights how metabolomics can be used to identify novel metabolic abnormalities and potential biomarkers associated with an inherited metabolic disorder called GLUT 1 deficiency syndrome (GLUT1-DS). The study is the first to investigate metabolomics perturbation in GLUT1-DS patients, as well as treatment of the disorder with a ketogenic diet (KD), which is currently the only treatment available.

What is GLUT1-DS?

First, let me tell you a little about GLUT1-DS. It is a rare disease caused by a mutation in the SLC2A1 gene that leads to reduced function of glucose transporter type 1 (GLUT 1), whose function is to transport glucose across cell membranes into cells and tissues. GLUT1-DS is a treatable neurological disorder, but it has a broad clinical presentation that can be confused with other diseases.

According to the NIH, patients may present with following signs and symptoms², which are typical of the classic type:

• Recurrent seizures (epilepsy) beginning in the first months of life
• Microcephaly (unusually small head size) that develops after birth
• Developmental delay
• Intellectual disability
• Speech and language impairment
• Movement abnormalities (i.e. involuntary eye movements, spasticity, ataxia, dystonia)
• Behavioral problems

Other symptoms may include headaches, confusion, loss of energy and/or muscle twitches.

While there is no cure for GLUT1-DS, it can be treated with KD, a high fat, moderate protein and low carbohydrate diet that causes the body to utilize ketones for fuel in the absence of optimal levels of glucose. The energy they provide can help lessen some of the symptoms of the disorder and supply better nourishment for the developing brain.³

Treatment with a Ketogenic Diet and Carnitine for GLUT1-DS patients

Cappuccio et al. set out to understand both the biochemical perturbations in the disease pathogenesis and in treatment with KD. In patients on KD, they observed metabolomic changes that implied that a compensatory neurochemical mechanism was induced by ketone bodies to recover energy homeostasis caused by reduced glucose levels.

In patients not treated with KD, decreased levels of glucose, fructose and mannose, and indeed a decrease in most TCA cycle intermediates, were observed suggesting an impact on mitochondrial physiology. In addition, gross alterations in the lipid super-pathway of metabolism were observed for those on the KD as were changes in the metabolism of carnitine, with increased levels of acylcarnitines linked to fatty acid metabolism and reduced acylcarnitines linked to amino acid metabolism.

Carnitine modulates transport of long-chain fatty acids into mitochondria and regulates energy balance across cell membranes. Free carnitine levels were low in patients on the KD, and the overall metabolomic data was consistent with consumption of carnitine and the metabolism of fatty acids by β oxidation.

These findings resulted in the authors proposing that oral supplementation of carnitine is warranted for GLUT1-DS patients on a KD. This is in line with the idea that depletion of carnitine could impair oxidation of fatty acids and ketone production, thus reducing treatment efficacy.

Biomarkers Identified in Plasma

The authors performed metabolomic analysis of CSF and plasma on nine GLUT1-DS patients before and after KD. They identified multiple dysregulated metabolites and metabolic pathways. The researchers also identified consistent changes in the levels of 3-hydroxybutyrate, 3-hydroxybutyrylcarnitine, 3-methyladipate and N-acetylglycine as potential biomarkers of GLUT1-DS on KD. While KD is the only current treatment option, it is possible that a personalized, optimized diet may be achievable for a patient by monitoring of such plasma biomarkers.

General Takeaways

Metabolomics may provide new understanding of the mechanisms regulating GLUT1 function and may open new avenues of treatment with the collection of additional data from subjects diagnosed with GLUT1-DS or other glucose transporter deficiencies.

In this study, metabolomics revealed multiple dysregulated metabolites in several pathways in CSF, plasma and urine of patients diagnosed with GLUT1-DS. Based on this insight, the authors arrived at a suggestion for improved treatment of GLUT1-DS patients and proposed a biomarker panel to better identify the effect of the ketogenic diet.

This work is one of a growing number of studies where a global metabolomics approach, able to identify up to a thousand metabolites in plasma, could (and should) contribute to a greater knowledge of inherited metabolic disorder pathogenesis, shorten the path to diagnosis, direct therapeutic decisions, and possibly deliver new treatments.

For more information about inherited metabolic diseases and the role of metabolomics in clinical screening, see Miller et al.⁴ and Kennedy et al.⁵ or visit our Clinical Applications page.

References
1. G. Cappuccio et al. (2017) Biochemical phenotyping unravels novel metabolic abnormalities and potential biomarkers associated with treatment of GLUT 1 deficiency with ketogenic diet. PloS One 12(9): e0184022
2. https://rarediseases.info.nih.gov/diseases/9265/glut1-deficiency-syndrome
3. http://www.g1dfoundation.org/what-is-glut1-deficiency/about-the-ketogenic-diet/
4. M. Miller et al. (2015) Untargeted metabolomic analysis for the clinical screening of inborn errors of metabolism J Inherit Metabolol Dis 38(6): 1029-1039
5. AD Kennedy et al. (2016) Metabolic-profiling of human urine as a screen for multiple inborn errors of metabolism. Genet Test Mol Biomarkers 20: 485-495

In this second part of our 3-part series on clinical metabolomics and its applications, we discuss how rare diseases, namely inherited metabolic disorders, can be screened using the technology.

While rare diseases, as the name suggests, have low incidence, they are difficult to diagnose and represent a significant unmet need for both patients and clinicians alike. With approximately 7,000 different types of rare diseases and 350 million people worldwide with conditions in this category, the struggle lies in both diagnosing the patient and providing appropriate treatments (if available) in a timely manner.[i] Up to 80 percent of rare diseases are genetic, and related symptoms can be challenging to pinpoint, further delaying diagnosis.[ii]

Within the realm of rare disease are conditions considered to be inherited metabolic disorders (IMDs), which encompass about 500 rare genetic diseases that result in metabolism problems. While individually rare, they occur collectively in about 1 in 2,500 people. IMDs, also known as inborn errors of metabolism, are rare genetic disorders that often disrupt bodily processes such as the conversion of nutrients into energy and structural molecules, the breakdown and clearance of waste, or the synthesis and function of regulatory signals. The disorders are usually caused by defects in specific proteins (enzymes) that help facilitate these processes.

IMDs usually present in the neonatal period or infancy, but can occur at any time, even in adulthood. While some metabolic disorders are detected by routine newborn screening tests, others are identified only after a child or adult shows symptoms of a disorder.

Below are some examples of IMDs:

• Propionic acidemia (the body is unable to process certain parts of proteins and lipids (fats) properly, resulting in build-up of abnormal levels of toxic substances in the blood and tissues)
• Cobalamin deficiencies (a variety of disorders involving vitamin B12 deficiency)
• Citrullinemia (disorder causes ammonia and other toxic substances to accumulate in the blood)
• Medium-chain acyl-CoA dehydrogenase deficiency (disorder that prevents the body from converting certain fats to energy, particularly during periods without food [fasting])

It is critical that IMDs are diagnosed and treated quickly, as they are known to cause brain and other organ damage, developmental delay and even death.

An Available Resource

Due to the complexities associated with rare diseases, it is important for patients to feel supported. Genetic counselors specialize in providing personalized help around a patient’s genetic health and can serve as a great resource. These skilled counselors work as part of a healthcare team to guide and support patients seeking information about how inherited diseases and conditions might affect them or their families and interpret test results.

We’d like to note that the first annual Genetic Counselor Awareness Day is taking place today, November 9^th. It’s a day dedicated to recognizing the vital role these professionals play in patient care.

A Potential Solution

A relatively new, sophisticated technology called metabolomics can detect abnormal levels of metabolites associated with IMDs, thereby shortening the time to final diagnosis, potentially helping improve outcomes and saving thousands of dollars in healthcare costs. Current diagnostic procedures are based on a series of segmented genetic and biochemical tests that can take months to yield a diagnosis and corresponding treatment plan.

To address the ongoing need and solution for IMD diagnosis, Metabolon offers Meta IMD™, a test that identifies hundreds of metabolites associated with a wide range of IMDs.[iii] Meta IMD is an adjunctive, first-line clinical test that can save time to diagnosis by simultaneously surveying individual metabolites and pathways across amino acids, carbohydrates, organic acids, fatty acids, neurotransmitters, nucleotides and bile acids to detect biochemical abnormalities linked to IMDs.

Requiring just one small biological sample, Meta IMD screens for nearly 70 disorders and provides the results within 21 days. While Meta IMD is not meant to replace diagnostic testing for specific conditions, it is designed as part of the triage workflow to assist clinicians in deciding which confirmatory tests should be ordered.

Meta IMD represents a significant step toward understanding the science of IMDs and diagnosing them. Metabolon is committed to expanding clinical metabolomics testing that can help inform diagnosis and may improve patient outcomes across rare and undiagnosed diseases.

To learn more about this innovative screening tool for IMDs or to order a test, click here.

References

[i] Global Genes. RARE Diseases: Facts and Statistics. Available at https://globalgenes.org/rare-diseases-facts-statistics/. Accessed 08-27-2017.

[ii] Ibid.

[iii] Metabolon. “Metabolon Launches Meta IMD™ Test to Speed Diagnosis of Inherited Metabolic Disorders.” Published 09-28-2016. Available at https://www.metabolon.com/who-we-are/news-events/news/metabolon-launches-meta-imdtm-test-speed-diagnosis-inherited-metabolic-disorders. Accessed 11-1-2017.

We’re kicking off a 3-part series of blog posts to help explain what clinical metabolomics is, why it’s important and how it’s being applied in rare diseases, especially inherited metabolic disorders.

Kirk Pappan, PhD – Associate Director, Scientific Discovery and Application, Precision Medicine, Metabolon

To get started, let’s tackle a very important question. Isn’t clinical metabolomics just like basic research metabolomics?

Umm, well…
Maybe I’ll answer that with an analogy.

Are you familiar with the Piano Guys? They just play the piano – right? Well, I guess, if you consider airlifting a grand piano to the top of a tall desert mesa to record their cover of Coldplay’s Paradise, “just playing the piano.” Go ahead, invest five minutes to watch the video, then you can read the rest of this post followed by a really, really productive day of work without any goofing off. I won’t tell anyone.

When I joined the Precision Medicine group of Metabolon a little over a year ago, I learned first-hand about the features that distinguish metabolomics for clinical applications – or clinical metabolomics – from metabolomics used for basic research. Having analyzed and interpreted hundreds of datasets as a study director on the basic research services side of the company, I am well aware of the comprehensive UHPLC-tandem mass spectrometry profiling technology and iterative improvements that have expanded its coverage across all areas of metabolism while reducing variance (reported as median standard deviation) to less than 5%. I also know that a large reference standard library, which includes information about retention time on a chromatography column, accurate mass of the parent ion and preferred adducts, as well as accurate mass fragmentation data from tandem mass spectrometry, enables the unambiguous identification of approximately 1,000 named metabolites in plasma.

It is important to point out that metabolomics studies involve groups of subjects, while the clinical use is to evaluate an “n of 1.” The question has been “what are the biomarkers that separate the groups?” In the clinic, however, the question is “what are the molecules that are outside the expected range?” Then, more importantly, “what does all this tell us about disease or the health status of an individual?”

While a robust biochemical profiling platform is a necessary element, it is not sufficient to meet all the criteria needed to define clinical metabolomics. Clinical significance is about more than analytical precision. From my perspective, there are two additional elements, which when combined with the core platform technology, complete the definition of clinical metabolomics.

Specifically, clinical metabolomics involves the application of clinical laboratory standards, protocols and oversight to a global biochemical profiling technology whose results are interpreted relative to a reference cohort. While there are many other aspects of a clinical test, I’m going to focus on those mentioned above.

All clinical laboratory testing adheres to standard practices, protocols, training, oversight and record-keeping standards. You’d find no less in our clinical metabolomics laboratory which follows SOPs, personnel training, an alphabet soup of standards such as CAP, CLIA, CAPA and HIPAA, analytical validation of the technology, clinical validation of observed disorders, continuous quality and performance analysis, and project management to meet delivery timelines. In other words, clinical metabolomics adheres to the same long-established practices that define all clinical tests that have the potential to lead to life-altering decisions by families, doctors and other medical professionals.

In retrospect, the comparison of biochemical levels to expected ranges defined by a reference cohort is obvious for clinical laboratory results. Nonetheless, this final distinguishing element of clinical laboratory testing tripped me up initially.

On the basic metabolomics research side of the company, we use sample powering to drive the statistical results at the end of a study. For example, a common study design for analysis of samples collected from humans might involve 50 healthy controls and 50 disease cases to look for biomarkers or mechanisms of disease. For basic research studies, the most common data analysis approach involves comparing the means of two groups by a method such as the Welch’s t-test to calculate a p-value.

However, clinical laboratory testing doesn’t look at group averages – it focuses on how the individual  differs compared to a reference population. This is a bedrock principle of clinical laboratory test result reporting and is likewise a required standard needed to adapt metabolomics to precision medicine.

Thus, the final step of moving metabolomics into the clinical testing laboratory involves the acquisition of biochemical profiles from hundreds of individuals to comprise a reference population. From this population, the mean and standard deviation can be determined for each biochemical detected and can be used to define cut-offs for the expected reference range. Calculating a z-score for every biochemical detected in a patient sample then allows the biochemical to be understood in terms of where it lies in relation to the reference population.

Metabolomics is only beginning to penetrate the world of clinical laboratory testing, but its future in the space is bright. While the technology will continue to advance, it will also be interesting to watch how the application of clinical laboratory standards, protocols and oversight, as well as the use of reference populations, advances and adapts as clinical metabolomics gains its footing. A good first step in this evolution will be to remember that it takes more than a robust platform technology to conduct clinical testing.

To learn more about our clinical products and services or to order a Meta IMD test, please click here.

We asked David Allaway, PhD, Senior Research Scientist in Nutrition & Metabolism, to tell us about his recently published study and what he learned by working with Metabolon.

Mars Petcare is one of the world’s leading pet care providers and features 41 well-known brands, including PEDIGREE®, IAMS®, WHISKAS®, ROYAL CANIN® and BANFIELD®. The company’s WALTHAM Centre for Pet Nutrition is using cutting-edge technology in its research to better understand pet metabolism and create healthier foods and supplements. We asked David Allaway, PhD, Senior Research Scientist in Nutrition & Metabolism, to tell us about his recently published study and what he learned by working with Metabolon.

Why did you decide to run this study?

As with humans, excess weight is an increasingly common health issue for both cats and dogs. In cats, neutering is known to be a significant risk factor for obesity. However, the mechanisms that promote this neuter-associated weight gain are not well understood. For instance, there can be an acute increase in body weight in the weeks following neutering. Researchers have speculated whether this is due to an increased drive to eat more food, or reduced energy requirements, or a combination of both. Whilst it has been shown that providing neutered female kittens with estrogen can mitigate weight gain, the issues are less well understood in males. Without a clear hypothesis to test, we chose metabolomics. This allows us to obtain data to develop the “best hypothesis” to test in future studies.

The aim of this study was to find out whether:
i.    cats need less food after neutering to maintain their healthy body weight, and
ii.    sexual development prior to neutering would lead to a different energy requirements needs.

What did you find out?

The metabolomics analysis indicated that neutering did not cause a detectable shift in energy metabolism that would explain any reduction in dietary intake. We also found that the age at which neutering took place had little impact on the fasted plasma metabolome beyond 12 weeks after the procedure.

This study also provided us with a wealth of information related to age, sexual development and neutering. This is one of the major benefits of using metabolomics in a non-hypothesis-driven study. We were able to analyse many metabolites across a range of metabolic pathways to establish which were most important.

In the paper, we reported a number of interpretations of the data that are fascinating. In particular, we saw the potential physiological costs of using a valuable commodity, such as a S-amino acid derivative, as a signalling device for conspecifics. We also potentially identified a transition in liver function/maturation that occurs around 20 weeks of age.

Why does neutering matter to pet nutrition?

At WALTHAM, we want to understand more about the impact of neutering, a known risk factor for obesity. Of particular interest are any potential changes in the nutritional requirements for neutered kittens. With this information, Mars Petcare can make the appropriate changes to products or feeding guidelines, if required. In addition, knowledge and best practices can be shared with regulatory authorities, vets and owners. Our research is revealing the range of energy requirements needed to support healthy kitten growth and how neutering might impact this.

How is metabolomics useful in aiding a fundamental understanding of pet health and nutrition?

We’ve used metabolomics in various studies, and though the purposes may be very different, the theme is consistent: it generates insights that can guide future hypothesis-led studies. Metabolomics provides a vast range of metabolite data from accessible biofluids. This reflects systemic changes in metabolism that help us understand what metabolic differences exist between groups (such as breed, gender or neuter group). The appropriate interpretation of these data can improve understanding of the influence of diet on metabolism in healthy animals.

Robust, data-led analysis is especially useful for cats as they are obligate carnivores and don’t conform to the classical paradigm of mammalian energy metabolism. Instead, numerous adaptations support increased protein oxidation and manage reduced carbohydrate intake. Metabolomics has already helped us reveal how such adaptations may influence how cats respond to diets differently to dogs. The approach has also identified confounding factors that may affect data interpretation collected in hypothesis-driven nutrition studies. This is incredibly important for our research, which is always conducted in accordance with the 3Rs principle to replace, reduce and refine the number of individuals required in a study. Of course, there are challenges, too. As we undertake more metabolomics studies, we continually improve our study designs to support better interpretation of these data we collect.

How did Metabolon’s technology help?

The various analytical platforms allowed many different, chemically diverse metabolites to be measured. This was important for non-hypothesis driven experimental design. It allowed changes of lipids associated with age to be identified, as well as amino acid derivatives associated with sexual development and neutering. Without a broad panel of metabolites, especially the feline-specific felinine derivatives, we would not have been able to contextualize the data to make the interpretations we made.

What are the implications for your findings?

I would like to think that the study may have provided food for thought to others interested in cat health, metabolism, sexual development and weight management, as well as the physiological costs associated with conspecific signalling. It would be nice to think that future studies from other labs could incorporate evidence from the robust analysis and interpretation that we have provided here.

To learn more about metabolomics or request information about a study, please contact us.