Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation.

Sabina Bijlsma1, Ivana Bobeldijk, Elwin R Verheij

  • 1Business Unit Analytical Sciences and Business Unit Physiological Sciences, TNO Quality of Life, P.O. Box 360, 3700 AJ Zeist, The Netherlands. bijlsma@voeding.tno.nl

Analytical Chemistry
|January 18, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Extracting host-specific developmental signatures from longitudinal microbiome data.

PLoS computational biology·2026
Same author

Cashew Reaction Thresholds, Its Predictors, and Very Low Validated Safe Doses, in a Large Allergic Population (Nut CRACKER Study).

Allergy·2026
Same author

Novel OGTT metrics do not provide incremental predictive value beyond conventional glycemic criteria for remission of prediabetes in individuals with impaired fasting glucose: results from the PREVIEW trial.

Cardiovascular diabetology·2026
Same author

Disparities in GLP-1 and GIP responses to small intestinal glucose infusion in individuals with well- and poorly-controlled type 2 diabetes.

Diabetes research and clinical practice·2026
Same author

Analysis of microbiome high-dimensional experimental design data using generalized linear models and ANOVA simultaneous component analysis.

Frontiers in microbiomes·2026
Same author

Enduring improvements in hepatic insulin sensitivity predict sustained remission of prediabetes during a 3-year lifestyle intervention: results from the PREVIEW multinational diabetes prevention trial.

Metabolism: clinical and experimental·2026
Same journal

Modeling the Effects of Short-Range Randomness in Packed Sphere Beds.

Analytical chemistry·2026
Same journal

Mitochondrial Redox Cascade-Directed Covalent NIR Fluorogenic Imaging of Therapy-Induced Senescence Integrates Tumor and Host Responses.

Analytical chemistry·2026
Same journal

Proteomic Profiling of RHD-Related Mitral Annulus Calcification Enabled by Magnetic Carbon Nanomaterial-Supported Quasi-Immobilized Enzyme Digestion.

Analytical chemistry·2026
Same journal

Spatial-Photonic Encoding on a Single Fiber: Breaking the Bottleneck in Photoelectrochemical Biosensing for Precision Diagnostics.

Analytical chemistry·2026
Same journal

Spreadable Biosensing Pregel for Analyte Visualization in Peeled Plant Tissues.

Analytical chemistry·2026
Same journal

DARibo-Q: RNA Allosteric Transduction for Fluorescence Imaging of Dopamine Modulation in Living Systems.

Analytical chemistry·2026
See all related articles

This study developed a robust statistical strategy for analyzing large-scale human metabolomics data, successfully identifying metabolic profile differences between obese and lean individuals after a high-fat meal.

Area of Science:

  • Metabolomics
  • Lipidomics
  • Human Physiology

Background:

  • Metabolomics studies generate large datasets with significant biological variation.
  • Analyzing these datasets requires sophisticated analytical and statistical protocols.
  • Understanding metabolic profiles in obesity requires advanced data processing techniques.

Purpose of the Study:

  • To develop and validate a pragmatic statistical approach for large-scale human metabolomics studies.
  • To detect subtle differences in metabolic profiles between obese and lean subjects.
  • To identify potential biomarkers associated with metabolic responses to a high-fat meal.

Main Methods:

  • Analysis of 600 plasma samples using liquid chromatography-mass spectrometry (LC-MS) lipidomics.

Related Experiment Videos

  • Development of a multi-step strategy including data preprocessing, statistical analysis, and model validation.
  • Application of partial least-squares discriminant analysis (PLS-DA) for biomarker discovery.
  • Validation of PLS-DA models using permutation tests and noninformative models.

    • Main Results:

    • A robust statistical strategy was successfully applied to a large human metabolomics dataset.
    • The approach effectively handled substantial biological variation to detect small metabolic differences.
    • Potential biomarkers were identified and validated, providing insights into metabolic regulation.

    Conclusions:

    • The proposed strategy is effective for processing and analyzing large-scale human metabolomics data.
    • This methodology enables the detection of subtle metabolic changes in complex biological systems.
    • The findings contribute to a better understanding of metabolic profiling in obesity research.