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Cited by 34Gut microbiota and healthParkinson's Disease Mechanisms and TreatmentsGastrointestinal motility and disorders

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Difference in gut microbial dysbiotic patterns between body-first and brain-first Parkinson's disease

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Park, Don Gueu, Kang, Woorim, Shin, In-Ja, Chalita, Mauricio, Oh, Hyun-Seok, Hyun, Dong-Wook, Kim, Hyun, Chun, Jongsik, An, Young-Sil, Lee, Eun Jeong, Yoon, Jung Han·2024·Neurobiology of Disease
DOI 10.1016/j.nbd.2024.106655
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Abstract

BACKGROUND: This study aims to identify distinct microbial and functional biomarkers characteristic of body-first or brain-first subtypes of Parkinson's disease (PD). This could illuminate the unique pathogenic mechanisms within these subtypes. METHODS: In this cross-sectional study, we classified 36 well-characterized PD patients into body-first, brain-first, or undetermined subtypes based on the presence of premotor REM sleep behavior disorder (RBD) and cardiac meta-iodobenzylguanidine (MIBG) uptake. We then conducted an in-depth shotgun metagenomic analysis of the gut microbiome for each subtype and compared the results with those from age- and sex-matched healthy controls. RESULTS: Significant differences were found in the gut microbiome of body-first PD patients (n = 15) compared to both brain-first PD patients (n = 9) and healthy controls. The gut microbiome in body-first PD showed a distinct profile, characterized by an increased presence of Escherichia coli and Akkermansia muciniphila, and a decreased abundance of short-chain fatty acid-producing commensal bacteria. These shifts were accompanied by a higher abundance of microbial genes associated with curli protein biosynthesis and a lower abundance of genes involved in putrescine and spermidine biosynthesis. Furthermore, the combined use of premotor RBD and MIBG criteria was more strongly correlated with these microbiome differences than the use of each criterion independently. CONCLUSIONS: Our findings highlight the significant role of dysbiotic and pathogenic gut microbial alterations in body-first PD, supporting the body-first versus brain-first hypothesis. These insights not only reinforce the gut microbiome's potential as a therapeutic target in PD but also suggest the possibility of developing subtype-specific treatment strategies.

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  • These differences were associated with a higher abundance of microbial genes associated with curli protein biosynthesis.

    “These differences were associated with a higher abundance of microbial genes associated with curli protein biosynthesis, the significance of which is discussed in more detail below.”

    From The gut–brain axis in early Parkinson’s disease: from prodrome to prevention (2025) · cites this paper as [135]

  • In body-first PD, there was a greater abundance of E. coli and Akkermansia, and decreased abundance of SCFA-producing bacteria.

    “In body-first PD, there was a greater abundance of E. coli and Akkermansia, and decreased abundance of SCFA-producing bacteria, corroborated by other studies into the prodromal gut microbiome in PD.”

    From The gut–brain axis in early Parkinson’s disease: from prodrome to prevention (2025) · cites this paper as [135]

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Research works printed but not linked: 58

  1. Adler, 2014, Low clinical diagnostic accuracy of early vs advanced Parkinson disease: clinicopathologic study, Neurology, 83, 406, 10.1212/WNL.0000000000000641 · DOI
  2. Amorim Neto, 2022, Akkermansia muciniphila induces mitochondrial calcium overload and α -synuclein aggregation in an enteroendocrine cell line, iScience, 25, 10.1016/j.isci.2022.103908 · DOI
  3. Borghammer, 2021, The α-Synuclein origin and connectome model (SOC model) of Parkinson’s disease: explaining motor asymmetry, non-motor phenotypes, and cognitive decline, J. Parkinsons Dis., 11, 455, 10.3233/JPD-202481 · DOI · Paper page
  4. Borghammer, 2021, Neuropathological evidence of body-first vs. brain-first Lewy body disease, Neurobiol. Dis., 161, 10.1016/j.nbd.2021.105557 · DOI
  5. Braak, 2003, Staging of brain pathology related to sporadic Parkinson’s disease, Neurobiol. Aging, 24, 197, 10.1016/S0197-4580(02)00065-9 · DOI · Paper page
  6. Braak, 2003, Idiopathic Parkinson's disease: possible routes by which vulnerable neuronal types may be subject to neuroinvasion by an unknown pathogen, J. Neural Transm., 110, 517, 10.1007/s00702-002-0808-2 · DOI · Paper page
  7. Buchfink, 2015, Fast and sensitive protein alignment using DIAMOND, Nat. Methods, 12, 59, 10.1038/nmeth.3176 · DOI · Paper page
  8. Bullich, 2019, Gut vibes in Parkinson’s disease: the microbiota-gut-brain Axis, Mov. Disord. Clin. Pract., 6, 639, 10.1002/mdc3.12840 · DOI
  9. Buttner, 2014, Spermidine protects against alpha-synuclein neurotoxicity, Cell Cycle, 13, 3903, 10.4161/15384101.2014.973309 · DOI
  10. Chalita, 2020, Improved metagenomic taxonomic profiling using a curated Core gene-based bacterial database reveals unrecognized species in the genus Streptococcus, Pathogens, 9, 204, 10.3390/pathogens9030204 · DOI
  11. Chattopadhyay, 2002, Absolute requirement of spermidine for growth and cell cycle progression of fission yeast (Schizosaccharomyces pombe), Proc. Natl. Acad. Sci. USA, 99, 10330, 10.1073/pnas.162362899 · DOI
  12. Chaudhuri, 2007, The metric properties of a novel non-motor symptoms scale for Parkinson’s disease: results from an international pilot study, Mov. Disord., 22, 1901, 10.1002/mds.21596 · DOI
  13. Chung, 2015, (123)I-Metaiodobenzylguanidine myocardial scintigraphy in Lewy body-related disorders: a literature review, J. Mov. Disord., 8, 55, 10.14802/jmd.15015 · DOI
  14. Conway, 2015, Commensal and pathogenic Escherichia coli metabolism in the gut, Microbiol. Spectr., 3, 343, 10.1128/microbiolspec.MBP-0006-2014 · DOI
  15. Doty, 1996, Development of the 12-item cross-cultural smell identification test (CC-SIT), Laryngoscope, 106, 353, 10.1097/00005537-199603000-00021 · DOI
  16. Fearon, 2021, Reply to: “the logic and pitfalls of Parkinson’s as brain- versus body-first subtypes”, Mov. Disord., 36, 786, 10.1002/mds.28527 · DOI
  17. Fereshtehnejad, 2015, New clinical subtypes of Parkinson disease and their longitudinal progression: a prospective cohort comparison with other phenotypes, JAMA Neurol., 72, 863, 10.1001/jamaneurol.2015.0703 · DOI · Paper page
  18. Fusco, 2023, Short-chain fatty-acid-producing bacteria: key components of the human gut microbiota, Nutrients, 15, 2211, 10.3390/nu15092211 · DOI
  19. Gaastra, 2014, Escherichia fergusonii, Vet. Microbiol., 172, 7, 10.1016/j.vetmic.2014.04.016 · DOI
  20. Heintz-Buschart, 2018, The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder, Mov. Disord., 33, 88, 10.1002/mds.27105 · DOI · Paper page
  21. Hofer, 2022, Mechanisms of spermidine-induced autophagy and geroprotection, Nat. Aging, 2, 1112, 10.1038/s43587-022-00322-9 · DOI
  22. Horsager, 2020, Brain-first versus body-first Parkinson's disease: a multimodal imaging case-control study, Brain, 143, 3077, 10.1093/brain/awaa238 · DOI · Paper page
  23. Horsager, 2022, Clinical and imaging evidence of brain-first and body-first Parkinson's disease, Neurobiol. Dis., 164, 10.1016/j.nbd.2022.105626 · DOI
  24. Huang, 2023, Gut microbiome dysbiosis across early Parkinson's disease, REM sleep behavior disorder and their first-degree relatives, Nat. Commun., 14, 2501, 10.1038/s41467-023-38248-4 · DOI · Paper page
  25. Hughes, 1992, Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases, J. Neurol. Neurosurg. Psychiatry, 55, 181, 10.1136/jnnp.55.3.181 · DOI · Paper page
  26. Jackson, 2022, Intestinal barrier dysfunction in the absence of systemic inflammation fails to exacerbate motor dysfunction and brain pathology in a mouse model of Parkinson’s disease, Front. Neurol., 13, 10.3389/fneur.2022.882628 · DOI
  27. Jankovic, 1990, Variable expression of Parkinson's disease: a base-line analysis of the DATATOP cohort. The Parkinson Study Group, Neurology, 40, 1529, 10.1212/WNL.40.10.1529 · DOI
  28. Kanehisa, 2017, KEGG: new perspectives on genomes, pathways, diseases and drugs, Nucleic Acids Res., 45, D353, 10.1093/nar/gkw1092 · DOI · Paper page
  29. Kernbach, 2022, Foundations of machine learning-based clinical prediction modeling: part II-generalization and overfitting, Acta Neurochir. Suppl., 134, 15, 10.1007/978-3-030-85292-4_3 · DOI
  30. Langmead, 2012, Fast gapped-read alignment with bowtie 2, Nat. Methods, 9, 357, 10.1038/nmeth.1923 · DOI · Paper page
  31. Lei, 2023, Akkermansia muciniphila in neuropsychiatric disorders: friend or foe?, Front. Cell. Infect. Microbiol., 13, 10.3389/fcimb.2023.1224155 · DOI
  32. Li, 2011, Widespread RNA and DNA sequence differences in the human transcriptome, Science, 333, 53, 10.1126/science.1207018 · DOI
  33. Li, 2017, Diagnostic accuracy of REM sleep behaviour disorder screening questionnaire: a meta-analysis, Neurol. Sci., 38, 1039, 10.1007/s10072-017-2886-9 · DOI
  34. Lin, 2020, Analysis of compositions of microbiomes with bias correction, Nat. Commun., 11, 3514, 10.1038/s41467-020-17041-7 · DOI
  35. Makletsova, 2019, Polyamines in Parkinson’s disease: their role in oxidative stress induction and protein aggregation, J. Neurol. Res., 9, 1, 10.14740/jnr509 · DOI
  36. Na, 2018, UBCG: up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction, J. Microbiol., 56, 280, 10.1007/s12275-018-8014-6 · DOI
  37. Nasreddine, 2005, The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment, J. Am. Geriatr. Soc., 53, 695, 10.1111/j.1532-5415.2005.53221.x · DOI · Paper page
  38. Nomura, 2011, Utility of the REM sleep behavior disorder screening questionnaire (RBDSQ) in Parkinson’s disease patients, Sleep Med., 12, 711, 10.1016/j.sleep.2011.01.015 · DOI
  39. Oh, 2022, Proposal of a health gut microbiome index based on a meta-analysis of Korean and global population datasets, J. Microbiol., 60, 533, 10.1007/s12275-022-1526-0 · DOI
  40. Oppong, 2015, Biofilm-associated bacterial amyloids dampen inflammation in the gut: oral treatment with curli fibres reduces the severity of hapten-induced colitis in mice, NPJ Biofilms Microbiomes, 1, 10.1038/npjbiofilms.2015.19 · DOI
  41. Park, 2023, Neurofilament light chain and cardiac MIBG uptake as predictors for phenoconversion in isolated REM sleep behavior disorder, J. Neurol., 270, 4393, 10.1007/s00415-023-11785-0 · DOI
  42. Patterson, 2017, Human gut symbiont Roseburia hominis promotes and regulates innate immunity, Front. Immunol., 8, 1166, 10.3389/fimmu.2017.01166 · DOI · Paper page
  43. Qu, 2023, Excessive consumption of mucin by over-colonized Akkermansia muciniphila promotes intestinal barrier damage during malignant intestinal environment, Front. Microbiol., 14, 1111911, 10.3389/fmicb.2023.1111911 · DOI
  44. Quinlan, 2010, BEDTools: a flexible suite of utilities for comparing genomic features, Bioinformatics, 26, 841, 10.1093/bioinformatics/btq033 · DOI · Paper page
  45. Rigottier-Gois, 2013, Dysbiosis in inflammatory bowel diseases: the oxygen hypothesis, ISME J., 7, 1256, 10.1038/ismej.2013.80 · DOI
  46. Rivera-Chávez, 2017, Oxygen as a driver of gut dysbiosis, Free Radic. Biol. Med., 105, 93, 10.1016/j.freeradbiomed.2016.09.022 · DOI
  47. Salazar, 2019, Age-associated changes in gut microbiota and dietary components related with the immune system in adulthood and old age: a cross-sectional study, Nutrients, 11, 1765, 10.3390/nu11081765 · DOI
  48. Salimiyan Rizi, 2020, Clinical and pathogenesis overview of Enterobacter infections, Rev. Clin. Med., 6, 146
  49. Shin, 2015, Proteobacteria: microbial signature of dysbiosis in gut microbiota, Trends Biotechnol., 33, 496, 10.1016/j.tibtech.2015.06.011 · DOI · Paper page
  50. Stiasny-Kolster, 2007, The REM sleep behavior disorder screening questionnaire--a new diagnostic instrument, Mov. Disord., 22, 2386, 10.1002/mds.21740 · DOI
  51. Vongsavath, 2023, The potential role of fecal microbiota transplantation in Parkinson’s disease: a systematic literature review, Appl. Microbiol., 3, 993, 10.3390/applmicrobiol3030067 · DOI
  52. Wan, 2020, Older patients with IBD might have higher risk of Parkinson's disease, Gut, 69, 193, 10.1136/gutjnl-2018-317103 · DOI
  53. Weersma, 2020, Interaction between drugs and the gut microbiome, Gut, 69, 1510, 10.1136/gutjnl-2019-320204 · DOI
  54. Wood, 2019, Improved metagenomic analysis with kraken 2, Genome Biol., 20, 257, 10.1186/s13059-019-1891-0 · DOI
  55. Xaio, 2001, Effect of LPS on the permeability of the blood-brain barrier to insulin, Brain Res., 896, 36, 10.1016/S0006-8993(00)03247-9 · DOI
  56. Ye, 2009, A parsimony approach to biological pathway reconstruction/inference for genomes and metagenomes, PLoS Comput. Biol., 5, 10.1371/journal.pcbi.1000465 · DOI
  57. Yoon, 2017, Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies, Int. J. Syst. Evol. Microbiol., 67, 1613, 10.1099/ijsem.0.001755 · DOI
  58. Zhang, 2019, Akkermansia muciniphila is a promising probiotic, Microb. Biotechnol., 12, 1109, 10.1111/1751-7915.13410 · DOI · Paper page

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Metadata

Authors
Park, D. G., Kang, W., Shin, I.-J., Chalita, M., Oh, H.-S., Hyun, D.-W., Kim, H., Chun, J., An, Y.-S., Lee, E. J., & Yoon, J. H.
Affiliations
Ajou University (KR)
Corresponding author
  • Lee, Eun Jeong
  • Yoon, Jung Han
ORCID
Venue
Neurobiology of Disease
Publisher
Elsevier BV
Published
2024-10
Volume
201
Pages
106655
ISSN
0969-9961 (ISSN-L)
DOI
10.1016/j.nbd.2024.106655
OpenAlex
W4402042810
Cited by
34
References
8
Citations by year
2026: 17 · 2025: 14 · 2024: 3
FWCI
4.63
Type
journal article
Language
en
Open access
Licence
Locations
  • Neurobiology of Disease (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • AJOU Open Repository (Ajou University) (submittedVersion, cc-by-nc-nd)
  • Seoul National University Open Repository (Seoul National University) (submittedVersion)
Funders
  • Ministry of Science, ICT and Future Planning
  • National Research Foundation of Korea
  • Korea Ministry of Science and ICT (2022R1C1C1005741, RS-2023-00217595)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Clinical Neurology › Parkinson's Disease Mechanisms and Treatments
  • Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
Keywords
Parkinson's disease, gut microbiota, gut dysbiosis, REM sleep behavior disorder, MIBG uptake, Escherichia coli, Akkermansia muciniphila, short-chain fatty acids, microbial biomarkers, disease subtypes
MeSH terms
Gastrointestinal Microbiome, Aged, Brain, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Parkinson Disease, REM Sleep Behavior Disorder, Dysbiosis

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