Evidence map›Paper›PMID 37212075›Full record

ArticleJournal of Parkinson's disease2023

IgA-Biome Profiles Correlate with Clinical Parkinson's Disease Subtypes.

Eric L Brown, Heather T Essigmann, Kristi L Hoffman, Ashley S Alexander, Michael Newmark, Zhi-Dong Jiang, Jessika Suescun, Mya C Schiess, Craig L Hanis, Herbert L DuPont

Open access · diamondAbstract read
In one paragraph

Article in Journal of Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% of its field
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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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

10 authors at 3 institutions in 1 country.

Eric L BrownCenter for Infectious Diseases, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
Heather T EssigmannCenter for Infectious Diseases, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
Kristi L HoffmanAlkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
Ashley S AlexanderKelsey Research Foundation, Houston, TX, USA.
Michael NewmarkKelsey Research Foundation, Houston, TX, USA.
Zhi-Dong JiangCenter for Infectious Diseases, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
Jessika SuescunDepartment of Neurology/UTMOVE University of Texas McGovern Medical School, Houston, TX, USA.
Mya C SchiessDepartment of Neurology/UTMOVE University of Texas McGovern Medical School, Houston, TX, USA.
Craig L HanisHuman Genetics Center, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
Herbert L DuPontCenter for Infectious Diseases, Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
The University of Texas Health Science Center at Houston · USKelsey Research Foundation · USBaylor College of Medicine · US

Funding

Tissue Analysis & Molecular Imaging CoreP30DK056338 · NIDDK · BAYLOR COLLEGE OF MEDICINE · PI Hashem B El-Serag · 2001 to 2026
$28.3M
Translational Research Support CoreP30ES030285 · NIEHS · BAYLOR COLLEGE OF MEDICINE · PI Cheryl L. Walker · 2019 to 2026
$14.7M
NIDDK NIH HHS P30 DK056338
6 · The paper itself

Abstract

backgroundParkinson's disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity.

objectiveBecause secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson's disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes.

methodsFlow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina).

resultsIgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson's disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples.

conclusionIgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches.

Indexed as

Gastrointestinal MicrobiomeParkinson DiseaseDisease ProgressionHumansImmunoglobulin ATremorImmunoglobulin A16S RNA gene sequencingIgA-BiomemicrobiomeParkinson’s diseaseParkinson’s disease clinical subtypessecretory IgA

Identifiers

PMID37212075
PMCPMC10357173
OpenAlexW4377091577

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.