Combining metabolomics and DNA sequencing could be the key to discovering new inborn errors of metabolism in children.
Jonathan James |
Although individually exceedingly rare, together inborn errors of metabolism (IEM) make up a sizeable portion of the broader spectrum of genetic disorders. Nevertheless, they remain underdiagnosed and undertreated (1). A multidisciplinary group based at the University of Texas Southwestern Medical Center in Dallas are working to improve our understanding of these diverse conditions. In a recent study, they combined genomic and metabolomic data to diagnose lipoyltransferase-1 deficiency (LIPT1D), an IEM characterized by abnormal brain development, seizures, and lactic acidosis (2). The team are optimistic that the new approach could provide the basis for more routine identification and treatment of IEMs.
“We’ve long known you can treat many IEMs if you pick up the underlying metabolic disturbance quickly,” says Ralph DeBerardinis, Professor of Pediatric Genetics and Metabolism at UT Southwestern and a co-author of the paper. Phenylketonuria (PKU), a well-known IEM, is characterized by a failure to metabolize phenylalanine, resulting in the accumulation of phenylalanine and related metabolites in blood and urine – abnormalities easily detected by laboratory testing (3). But many other diseases remain poorly characterized and much more difficult to pinpoint – something that DeBerardinis hopes to address with advanced techniques. “It has become apparent that applying broad profiling technology will allow us to understand metabolic disturbances at a more granular level, helping us to uncover these conditions and ultimately to develop new therapies,” he says (4).
Part of the problem is that current diagnostic approaches are narrow in scope. DeBerardinis certainly believes so; after all, even the most sophisticated clinical tests can only pick up a small fraction of potential markers. “You might be able to detect 50 biomarkers or so in a high-end laboratory,” says DeBerardinis. “But there are potentially thousands of detectable metabolites in the blood – each of which could be associated with a novel IEM.”
There certainly seems to be plenty of reason for optimism, but DeBerardinis is keen to stress caution, at least for now. “We really need to know more about metabolic variability in the normal population first,” he says. To get that data, the team are looking further afield. “We have established collaborations with medical geneticists in Pakistan, where the frequency of undiagnosed IEMs is high. Because that population has remained relatively understudied, there’s opportunity for discoveries that will help us better understand and treat IEMs,” says DeBerardinis. And although that project only began a few months ago, progress is already being made. “We have around 150 samples so far – we’re very excited to see where the work takes us.”
- D Waters et al., “Global birth prevalence and mortality from inborn errors of metabolism: a systematic analysis of the evidence”, J Glob Health, 8, 021102 (2018). DOI: 10.7189/ jogh.08.021102.
- M Ni et al., “Functional assessment of Lipoyltransferase-1 deficiency in cells, mice, and humans”, Cell Rep, 27, 1376 (2019). DOI: 10.1016/j.celrep.2019.04.005.
- NA Hafid, J Christodoulou, “Phenylketonuria: a review of current and future treatments”, 4, 304 (2018). DOI: 10.3978/j.issn.2224- 4336.2015.10.07.
- A Tebani et al., “Clinical Metabolomics: The new metabolic window for inborn errors of metabolism investigation in the post-genomic era”, Int J Mol Sci, 17, 1167 (2016). DOI: 10.3390/ijms17071167.