Evidence map›Paper›PMID 31336807›Full record

ArticleGenes2019

MODIMA, a Method for Multivariate Omnibus Distance Mediation Analysis, Allows for Integration of Multivariate Exposure-Mediator-Response Relationships.

Bashir Hamidi, Kristin Wallace, Alexander V Alekseyenko

Abstract readEvaluation Study
In one paragraph

Article in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Microbiome mediation analysis: methods, assumptions, and practical considerations.Frontiers in cellular and infection microbiology · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Bashir HamidiProgram for Human Microbiome Research, Medical University of South Carolina, 135 Cannon Street MSC 200, Charleston, SC 29425, USA.
Kristin WallaceDepartment of Public Health Science, Medical University of South Carolina, 135 Cannon Street MSC 200, Charleston, SC 29425, USA.
Alexander V AlekseyenkoProgram for Human Microbiome Research, Medical University of South Carolina, 135 Cannon Street MSC 200, Charleston, SC 29425, USA. alekseye@musc.edu.

Funding

South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
South Carolina Cancer Disparities Research Center (SC CADRE)U54CA210962 · NCI · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ALEKSEYENKO, ALEXANDER · 2017 to 2023
$6.7M
South Carolina Cancer Disparities Research Center (SC CaDRe)U54CA210963 · NCI · SOUTH CAROLINA STATE UNIVERSITY · PI FORD, MARVELLA ELIZABETH, SALLEY, JUDITH · 2017 to 2023
$6.1M
Distance-based Panomic Analytics for Microbiome DataR01LM012517 · NLM · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ALEKSEYENKO, ALEXANDER V · 2018 to 2021
$1.3M
Increasing Access to Clinical Microbiome Specimens via a Living µbiome BankR21TR002513 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ALEKSEYENKO, ALEXANDER V · 2018 to 2019
$439k
NCATS NIH HHS R21 TR002513NCATS NIH HHS UL1 TR001450NCI NIH HHS U54 CA210962NCI NIH HHS U54 CA210963NLM NIH HHS R01 LM012517
6 · The paper itself

Abstract

Many important exposure-response relationships, such as diet and weight, can be influenced by intermediates, such as the gut microbiome. Understanding the role of these intermediates, the mediators, is important in refining cause-effect theories and discovering additional medical interventions (e.g., probiotics, prebiotics). Mediation analysis has been at the heart of behavioral health research, rapidly gaining popularity with the biomedical sciences in the last decade. A specific analytic challenge is being able to incorporate an entire 'omics assay as a mediator. To address this challenge, we propose a hypothesis testing framework for multivariate omnibus distance mediation analysis (MODIMA). We use the power of energy statistics, such as partial distance correlation, to allow for analysis of multivariate exposure-mediator-response triples. Our simulation results demonstrate the favorable statistical properties of our approach relative to the available alternatives. Finally, we demonstrate the application of the proposed methods in two previously published microbiome datasets. Our framework adds a new tool to the toolbox of approaches to the integration of 'omics big data.

Indexed as

Gastrointestinal MicrobiomeModels, StatisticalAnimalsComputational BiologyComputer SimulationDatasets as TopicHumansMiceMultivariate Analysiscausal inferencedirect effectdistance correlationindirect effectmultivariate analysismultivariate causal mediation

Identifiers

PMID31336807
PMCPMC6679421

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.