ReviewGeneral psychiatry2023
Deciphering the 'gut-brain axis' through microbiome diversity.
Review in General psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.Statistics in medicine · 2026Article
- MULTI-MODAL AND MULTI-REGION DISTANCE MODEL FOR NEUROIMAGING: APPLICATION TO ABCD STUDY.bioRxiv : the preprint server for biology · 2026Article
- Gut microbiome links obesity to type 2 diabetes: insights from Mendelian randomization.BMC microbiology · 2025Article
- The brain-gut axis and chronic pain: mechanisms and therapeutic opportunities.Frontiers in neuroscience · 2025Review
- Investigating bidirectional causal relationships between gut microbiota and insomnia.General psychiatry · 2025Article
- Gut microbiome and schizophrenia: insights from two-sample Mendelian randomization.Schizophrenia (Heidelberg, Germany) · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Incentivised by breakthroughs and data generated by the high-throughput sequencing technology, this paper proposes a distance-based framework to fulfil the emerging needs in elucidating insights from the high-dimensional microbiome data in psychiatric studies. By shifting focus from traditional methods that focus on the observations from each subject to the between-subject attributes that aggregate two or more subjects' entire feature vectors, the described approach revolutionises the conventional prescription for high-dimensional observations via microbiome diversity. To this end, we enrich the classical generalised linear models to articulate the multivariable regression relationship between distance-based variables. We also discuss a robust and computationally feasible semiparametric inference technique. Benefitting from the latest advances in the semiparametric efficiency theory for such attributes, the proposed estimators enjoy robustness and good asymptotic properties that guarantee sensitivity in detecting signals between clinical outcomes and microbiome diversity. It offers a readily implementable and easily interpretable solution for deciphering the gut-brain axis in mental health research.
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Registered trials
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.