Pre-analytical Sample Handling Conditions and Their Effects on the Human Serum Metabolome
| Status: | Completed |
|---|---|
| Conditions: | Healthy Studies |
| Therapuetic Areas: | Other |
| Healthy: | No |
| Age Range: | 20 - 65 |
| Updated: | 4/21/2016 |
| Start Date: | March 2016 |
| End Date: | March 2016 |
This study evaluates how blood serum handling conditions can affect the concentrations of
~1,000 serum metabolites and attempts to quantify the degree of attenuation and/or potential
bias in epidemiologic associations that may result from less than optimal sample handling
conditions.
~1,000 serum metabolites and attempts to quantify the degree of attenuation and/or potential
bias in epidemiologic associations that may result from less than optimal sample handling
conditions.
Metabolomics, the simultaneous quantification of concentrations of hundreds or thousands of
metabolites simultaneously in a biological matrix, is a versatile analytical technique
capable of accelerating biomarker-based discoveries in nutritional science. Recently,
metabolomics has been applied to samples collected in feeding studies (1) and epidemiologic
studies (2) to identify dozens of novel potential dietary biomarkers. Several large
prospective cohort studies, many of which are collaborating in a metabolomics consortium led
by the National Cancer Institute, have recently applied metabolomics to banked samples. This
has made nutrition-related biomarkers suddenly available for tens of thousands of
participants with follow-up for disease endpoints, enabling truly large-scale nutritional
biomarkers and disease studies.
metabolites simultaneously in a biological matrix, is a versatile analytical technique
capable of accelerating biomarker-based discoveries in nutritional science. Recently,
metabolomics has been applied to samples collected in feeding studies (1) and epidemiologic
studies (2) to identify dozens of novel potential dietary biomarkers. Several large
prospective cohort studies, many of which are collaborating in a metabolomics consortium led
by the National Cancer Institute, have recently applied metabolomics to banked samples. This
has made nutrition-related biomarkers suddenly available for tens of thousands of
participants with follow-up for disease endpoints, enabling truly large-scale nutritional
biomarkers and disease studies.
Inclusion Criteria:
- Age 20 to 65 years at beginning of study.
- BMI between 18.5 and 35.0 kg/m2.
Exclusion Criteria:
- Presence of cardiovascular disease, kidney disease, liver disease, gout,
hyperthyroidism, untreated or unstable hypothyroidism, certain cancers,
gastrointestinal disease, pancreatic disease, other metabolic diseases, or
malabsorption syndromes.
- Unable or unwilling to give informed consent or communicate with study staff.
- Other medical, psychiatric, or behavioral factors that in the judgment of the
Principal Investigator may interfere with study participation or the ability to
follow the intervention protocol.
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