Metabolic syndrome (MetS) is a clustering of five conditions that includes abdominal obesity, diabetes, and high blood pressure. One quarter of the developed world population is estimated to have the condition (1). It is associated with the risk of coronary heart disease, stroke, and other conditions that affect the blood vessels (2). Diagnosis of MetS can be challenging as there is a lack of consensus about a definition of the condition. It is often associated with lifestyle factors such as poor diet and physical inactivity, but there are also genetic factors that put some people at higher risk.
As principal investigator at the CIC bioGUNE in Bilbao, Spain, I have been researching MetS for many years, with research supporting a future personalized medicine approach to its prevention and treatment. My team is using nuclear magnetic resonance (NMR) spectroscopy to characterize biomarkers of the disease at different stages of its progression, with the aim of identifying a person’s risk of the disease prior to symptoms developing. As MetS is both preventable and reversible, this information could eventually lead to lower instances of the disease, and the resulting benefits to individuals and healthcare systems could be significant (3).
Research has shown that, in 2020, an estimated 2.5 million children and 35.5 million adolescents were living with MetS (4). In addition to affecting quality of life for patients, this places a substantial burden on healthcare systems, and has serious socioeconomic implications that have been described as a medical challenge for the whole research community (5).
Diagnosis of MetS is usually determined by the presentation of at least three of the following four factors: abdominal obesity (a waist measurement of 40+ inches for men and 35 inches for women), high blood sugar (100mg/dL or more), high serum triglycerides (150mg/dL or more), and low high-density lipoprotein (less than 40mg/dL for men, 50mg/dL or less for women). A joint statement by several bodies, including the International Diabetes Federation and the American Heart Association, recognized that, although waist circumference is an important signifier of MetS, this does not account for differences in sex and across ethnic groups (6).
Hernandez-Baixauli and collaborators highlighted that traditional molecular markers are not precise enough to detect the disease at earlier stages: “At present, the lack of robust health status biomarkers for the principal clusters of MetS and obesity is a bottleneck that slows down the personalized nutrition in metabolomics. The exposure of each risk factor can be detected by traditional molecular markers, but the current biomarkers have not been enough precise to detect the primary stages of disease. Thus, there is a need to obtain novel molecular markers of pre-disease stages” (7).
NMR can be applied in the characterization of disease biomarkers and in the evaluation of the prognosis of the disease by analyzing different samples throughout disease progression. For many analytical scientists, NMR is a go-to technique. It is robust, reliable, and non-destructive, and its quantitative capabilities offer high coverage and low detection limits. In the analysis of biofluids, the metabolism you can measure is statistically significant, so, the data is very high quality.
One of the major advantages of using NMR spectroscopy is its reproducibility. NMR is both intra- and inter-reproducible and allows the quantification of metabolites in a single acquisition. These measurements are the same in a lab in Germany, for example, or a collaborator’s lab in Australia.
NMR spectroscopy has proven to be an important analytical technique in the field of metabolomics. Its reproducibility, quantitative measurements, and ability to identify metabolites in complex mixtures make it a key driver in the advances of metabolomics and other scientific areas (8).
NMR has also been used by my team to research rare diseases, such as the early-onset disease Friedreich’s ataxia (FA), caused by an insufficiency of the iron binding protein, human frataxin (9).Using NMR spectroscopy (Bruker, Billerica, MA), molecular dynamics and docking approaches, the research demonstrated new roles of frataxin. The findings expanded the relevant molecular targets for frataxin and may help identify the different roles this protein plays in iron regulation and metabolism.
My team has also conducted extensive research within the field of metabolomics. Through its work, the team has built up a cohort of 15,000 people and collected more than 90,000 samples in the local biobank. The research into MetS involves collecting serum and urine samples from people at different stages of the disease and comparing them to the available medical data. Using an NMR-based in vitro diagnostics regulation (IVDr) platform, the team has developed a predictive model for MetS, (10) which, when fully validated and translated into the clinic, could have a positive impact on patient outcomes.
Large-scale studies such as this allow biomarkers to be identified that are relevant to subgroups of people. Madhusoodanan highlighted how traditional biomarkers are not accurate predictors of MetS in women, nor in people of color globally—meaning research at the population scale will help identify more relevant biomarkers (11).
For example, I was part of a global research network initiated by Bruker under the guidance of the Australian National Phenome Center (ANPC) in 2020: the NMR International COVID-19 Research Network (12).NMR was used to produce spectral data that were exchangeable and integratable across the network. The network found biochemical abnormalities in patient blood samples, identified by a quantitative, label-free assay platform integrating NMR spectroscopy and mass spectrometry (MS), that relate to long COVID-19 symptoms, which persist post-acute SARS-CoV-2 infection. This insight proves useful for further research into Long COVID, which remains a major healthcare challenge today.
NMR spectroscopy has a role to play in the move towards the personalized precision medicine paradigm. Being able to analyze a large sample cohort is important when validating complex biological samples. The versatility and ability of NMR to handle large data sets is an asset in the metabolomic research needed to support this move. NMR is playing a key role in today’s research that will help advance our understanding of the human metabolome.
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