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 Concept Videos

Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

You might also read

Related Articles

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

Sort by
Same author

High-resolution metabolomics of maternal polybrominated diphenyl ethers (PBDE) exposure and preterm birth in the Atlanta African American Maternal-Child Cohort.

Communications medicine·2026
Same author

Differential DNA methylation in blood as potential mediator of the association between ambient PM<sub>2.5</sub> and cerebrospinal fluid biomarkers of Alzheimer's disease among a cognitively normal population-based cohort.

Molecular psychiatry·2026
Same author

Association between maternal organophosphate esters metabolite levels during pregnancy and internalizing and externalizing behaviors in children at 2-5 years.

Environmental epidemiology (Philadelphia, Pa.)·2026
Same author

Trajectories of reproductive events from menarche to menopause: identifying patterns and differences by childhood maltreatment and socioeconomic position.

American journal of epidemiology·2026
Same author

Disinfection Byproducts, Oxidative Stress, and Sleep Quality among Healthy Chinese Men.

Environment & health (Washington, D.C.)·2026
Same author

From single conventional regression to ensemble modelling: relative importance of the Healthy Eating Index-2015 components in relation to adverse pregnancy outcomes.

The British journal of nutrition·2026
Same journal

TROPOMI CO and NO<sub>2</sub> as Observational Constraints on the Sources of Air Pollution Inequalities in US Cities.

Environmental science & technology·2026
Same journal

Iron Plaque Formation in Mollisols Following Irrigation with Groundwater: Effects on Organic Matter Biotransformation and Selenium Biogeochemistry.

Environmental science & technology·2026
Same journal

Mobility and Income: Policy Insights to Support Public Electric Vehicle Charging Access.

Environmental science & technology·2026
Same journal

Soil Properties Regulate the Fate and Accumulation of Atmospherically Deposited Trace Metals in Rice across Six Major Growing Regions of China.

Environmental science & technology·2026
Same journal

NIST Polymer Pyrolysis Search: A New Pyrolysis GC-MS Search Program and Mass Spectral Reference Library.

Environmental science & technology·2026
Same journal

Targeted Acclimation Unlocks Adaptive Evolution of a Methanotrophic Consortium Enabling 3A5MI Elimination and Enhanced Sulfamethoxazole Biodegradation.

Environmental science & technology·2026
See all related articles

Related Experiment Video

Updated: May 11, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

21.6K

Evaluating Methods for High-Dimensional Mediation in Metabolomics Data.

Susan S Hoffman1, Donghai Liang1,2, Anne Dunlop3

  • 1Department of Epidemiology, Emory University, Atlanta, Georgia 30322, United States.

Environmental Science & Technology
|January 7, 2026
PubMed
Summary
This summary is machine-generated.

High-dimensional mediation analysis methods (HIMA, HDMA) and Meet-in-the-Middle (MITM) were evaluated for metabolomics data. HDMA accurately estimated total indirect effects, while HIMA showed promise, suggesting parallel approaches for robust findings.

Keywords:
HDMAHIMAhigh-dimensional mediationmeet-in-the-middlemetabolomicssimulation

More Related Videos

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.2K
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

1.0K

Related Experiment Videos

Last Updated: May 11, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

21.6K
Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.2K
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

1.0K

Area of Science:

  • Metabolomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • High-dimensional data in metabolomics presents challenges for mediation analysis.
  • Existing methods like HIMA and HDMA require evaluation for accuracy and scalability.
  • Understanding indirect effects is crucial for elucidating biological pathways.

Purpose of the Study:

  • To compare the performance of high-dimensional mediation analysis methods (HIMA, HDMA) and the Meet-in-the-Middle (MITM) approach.
  • To assess the accuracy in estimating total indirect effects (TIE) and component indirect effects (CIEs).
  • To evaluate sensitivity and specificity across various simulation scenarios.

Main Methods:

  • Simulated metabolomics data with varying sample sizes, mediator set sizes, and correlation structures.
  • Evaluation of HIMA (Zheng et al.) and HDMA (Gao et al.) for estimating TIE and CIEs.
  • Assessment of the Meet-in-the-Middle (MITM) approach and its performance metrics.

Main Results:

  • HDMA provided the most accurate TIE estimates in independent metabolite scenarios; HIMA also showed reliable CIE estimation.
  • MITM generally underestimated TIE; HIMA's TIE estimates improved with larger mediation effect sizes.
  • In correlated settings, CIE estimation was infeasible, and all methods underestimated TIE; sensitivity decreased with smaller effects and sample sizes.

Conclusions:

  • HIMA offers accurate mediation results but may reduce dimensionality, potentially excluding features.
  • Applying parallel mediation approaches (MITM, HIMA) and focusing on overlapping results is recommended.
  • There is a need for robust, scalable mediation methods specifically for untargeted metabolomics data.