We support all aspects of metabolic phenotyping, from sample to data

The metabolic phenotyping of human biological samples provides a metabolic picture which is reflective of the status of the patient at the time that the sample was collected. This information can then be used to improve our understanding of a disease and facilitate the discovery of mechanistic, prognostic and diagnostic biomarkers.

The CPC provides a collaborative and comprehensive service to handle all aspects of metabonomic research, including sample preparation, sample analysis and data pre-processingAdditionally, we are able to offer statistical analysis, data fusion and interpretation.  

To obtain meaningful results, researchers need to define the study's objective clearly and have a robust study design. If required, the CPC can help designing the study and selecting the most appropriate analytical platform to answer the research question. 

 

Please consider the following before starting your project   

Study objective

It is critical to define the purpose of the study clearly as it will determine the design and metabonomic approach for the study. For example, if you intend to have a better understanding of a disease and discover biomarkers of the disease progression, global profiling analysis will provide relevant information on affected metabolic pathways and can identify upregulated metabolites on each stage of the disease. If on the other hand, you already know the metabolic pathways affected by a disease, a targeted approach will provide the required in-depth knowledge of specific metabolites or metabolite classes.

Study design

It is necessary to have a robust study design to obtain meaningful metabolic profiles. An appropriate patient population must be selected to address the biological question and to get balanced and homogeneous groups. Each of the biological hypothesis tested, should have an adequate control group and enough samples collected to obtain statistically significant results. The biological question will also determine the analytical approach (global vs. targeted) and whether any method development will be required. It is imperative to collect a sample matrix or matrices relevant to the biological question and at a sufficient volume for the subsequent analyses. Sample collection and handling has to be consistent and degradation should be minimised throughout the investigation. Finally, it is also important to reduce the presence of confounding factors including uncontrolled dietary intake, unrecorded xenobiotic administration, ethanol contamination, inconsistent application of the protocol, etc. Too many uncontrolled confounding factors can skew the results.

Study design

Patient population

  • Appropriate control group?
  • Adequate number of patients?
  • Homogenous groups?

Confounding factors 

  • Food/drinks intake
  • Xenobiotics
  • Cleaning reagents

Study design

Sample collection

  • Sample type?
  • Consistent time-points?
  • Consistent sample collection and handling?

Sample analysis

  • Sufficient volume?
  • Global profiling or targeted assay?
  • Method development required?

 

Importance of using the correct protocol and approach

The high sensitivity of metabonomic investigations requires adherence to strict collection and handling protocols which ensure that there is minimal sample degradation and the maximum amount of information will be retrieved from each metabolic profile. Some general recommendations on sample collection and handling are summarised in the samples section.

Different analytical techniques and approaches can be employed for metabonomic analyses depending on the biological question that needs to be answered. Proton nuclear magnetic resonance (1H NMR) spectroscopy is commonly used as a first stage metabolic screening tool. To increase metabolome coverage, complementary global profiling and targeted assays are followed up using more sensitive mass spectrometry (MS)-based methods. 

Correct protocol

 

Well-powered study

As with all studies, it is essential to power the study but it is particularly pertinent in systems metabolism where hundreds or thousands of metabolic endpoints may be studied simultaneously. Therefore for longitudinal or randomised clinical studies, there should be a clear evidence of a power calculation, and around 50 patients is the minimum required to generate a meaningful analysis. For single time point studies or those with limited biofluids or samples, then much larger sample numbers are likely to be required to generate meaningful insights.