[en] Gut microbiome alterations are linked to various diseases, including neurodegeneration, but their ecological and functional impacts remain unclear. Using integrated multi-omics (metagenomics and metatranscriptomics), we analyse microbiome gene co-expression networks in Parkinson's disease (PD) and healthy controls (HC). We observe a significant depletion of hub genes in PD, including genes involved in secondary bile acid biosynthesis, bacterial microcompartments (BMCs), polysaccharides transport and flagellar assembly (FA). Blautia, Roseburia, Faecalibacterium and Anaerobutyricum genera are the main contributors to these functions, showing significantly lower expression in PD. Additionally, we identify a strong correlation between BMC and FA expression, and an apparent dysregulation in cross-feeding between commensals in PD. Finally, PD also exhibits reduced gene expression diversity compared to HC, whereby higher gene expression correlates with greater diversity. We identify disruptions in gut metabolic functions, at both taxonomic and functional level, and microbiome-wide ecological features, highlighting targets for future gut microbiome restoration efforts.
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB): Eco-Systems Biology (Wilmes Group) Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Microbiology Neurology
Author, co-author :
VILLETTE, Rémy ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Ecology
NOVIKOVA, Polina ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Systems Ecology > Team Paul WILMES
LACZNY, Cedric Christian ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Ecology
Mollenhauer, Brit; Department of Neurology, University Medical Center Göttingen, Göttingen, Germany ; Paracelsus-Elena-Klinik, Kassel, Germany
MAY, Patrick ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
WILMES, Paul ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Ecology ; Unilu - University of Luxembourg > Department of Life Sciences and Medicine
External co-authors :
yes
Language :
English
Title :
Human gut microbiome gene co-expression network reveals a loss in taxonomic and functional diversity in Parkinson's disease.
Publication date :
24 July 2025
Journal title :
Biofilms and Microbiomes
ISSN :
2055-5008
eISSN :
2055-5008
Publisher :
Springer Science and Business Media LLC, United States
H2020 - 863664 - ExpoBiome - Deciphering the impact of exposures from the gut microbiome-derived molecular complex in human health and disease
FnR Project :
FNR11333923 - MiBiPa - Non-invasive Microbiome-derived Multi-omic Biomarkers For The Early-stage Detection And Stratification Of Parkinson’S Disease, 2016 (01/09/2017-28/02/2021) - Paul Wilmes FNR10404093 - microCancer - Non-invasive Microbiome-derived Multi-omic Biomarkers For Early-stage Colorectal Cancer Detection, 2015 (01/01/2016-30/04/2019) - Paul Wilmes FNR14429377 - ProtectMove II - Reduced Penetrance In Hereditary Movement Disorders: Elucidating Mechanisms Of Endogenous Disease Protection, 2020 (01/07/2020-30/06/2023) - Anne Grünewald FNR11264123 - NCER-PD - Ncer-pd, 2015 (01/06/2015-31/05/2023) - Rejko Krüger
Name of the research project :
R-AGR-3293 - C16/BM11333923 MiBiPa - part UL - WILMES Paul
Funders :
HORIZON EUROPE European Research Council Fonds National de la Recherche Luxembourg Fulbright Research Scholarship Rotary Club Luxembourg, Espoir en tête European Union
Funding text :
This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 863664), and was further supported by the Luxembourg National Research Fund (FNR) CORE/16/BM/11333923 (MiBiPa), CORE/15/BM/10404093 (microCancer/MUST), as well as an ‘Espoîr en tête’ grant from the Rotary Club Luxembourg to P.W. This work was also supported by a Fulbright Research Scholarship from the Commission for Educational Exchange between the United States, Belgium and Luxembourg to P.W. Additional funding was provided by the FNR under INTERMOBILITY/23/17856242. The MiBiPa project was co-funded by the German Research Foundation (DFG) under grant agreement MO 2088/5-1 to B.M. Finally, P.M. was supported by the FNR National Center of Excellence in Research on Parkinson's disease (NCER-PD, 11264123), the DFG Research Unit FOR2488 (INTER/DFG/19/14429377) and FNR/DFG Core INTER (ProtectMove, FNR11250962).
A. Elbaz L. Carcaillon S. Kab F. Moisan Epidemiology of Parkinson’s disease Rev. Neurol. 172 14 26 1:STN:280:DC%2BC28rmtVKhtA%3D%3D 26718594
M.J. Howell C.H. Schenck Rapid eye movement sleep behavior disorder and neurodegenerative disease JAMA Neurol. 72 707 712 25867792
A. Fasano N.P. Visanji L.W.C. Liu A.E. Lang R.F. Pfeiffer Gastrointestinal dysfunction in Parkinson’s disease Lancet Neurol. 14 625 639 1:CAS:528:DC%2BC2MXosVGjtbo%3D 25987282
H. Braak U. Rüb W.P. Gai K. Del Tredici Idiopathic Parkinson’s disease: possible routes by which vulnerable neuronal types may be subject to neuroinvasion by an unknown pathogen J. Neural Transm. 110 517 536 1:STN:280:DC%2BD3s3gt1GltQ%3D%3D 12721813
J.F. Cryan K.J. O’Riordan K. Sandhu V. Peterson T.G. Dinan The gut microbiome in neurological disorders Lancet Neurol. 19 179 194 1:CAS:528:DC%2BC1MXitF2mu73E 31753762
A. Keshavarzian et al. Colonic bacterial composition in Parkinson’s disease Mov. Disord. 30 1351 1360 1:CAS:528:DC%2BC2MXhsVOqsbvL 26179554
F. Scheperjans et al. Gut microbiota are related to Parkinson’s disease and clinical phenotype Mov. Disord. 30 350 358 25476529
Bhattarai, Y. et al. Role of gut microbiota in regulating gastrointestinal dysfunction and motor symptoms in a mouse model of Parkinson’s disease. Gut Microbes13, 1866974 (2021).
M. Hirayama K. Ohno Parkinson’s disease and gut microbiota Ann. Nutr. Metab. 77 28 35 1:CAS:528:DC%2BB3MXit1Oit7jL 34500451
Y. Qian et al. Alteration of the fecal microbiota in Chinese patients with Parkinson’s disease Brain Behav. Immun. 70 194 202 29501802
G.A. Weiss T. Hennet Mechanisms and consequences of intestinal dysbiosis Cell. Mol. Life Sci. 74 2959 2977 1:CAS:528:DC%2BC2sXlt1Srs7s%3D 28352996 11107543 2017 74:16
Stolfi, C., Maresca, C., Monteleone, G. & Laudisi, F. Implication of intestinal barrier dysfunction in gut dysbiosis and diseases. Biomedicines10, 289 (2022).
Romano, S. et al. Meta-analysis of the Parkinson’s disease gut microbiome suggests alterations linked to intestinal inflammation. npj Parkinsons Dis.7, 27 (2021).
J.M. Boertien P.A.B. Pereira V.T.E. Aho F. Scheperjans Increasing comparability and utility of gut microbiome studies in Parkinson’s disease: a systematic review J. Parkinsons Dis. 9 S297 S312 31498131 6839453
T.S. Toh et al. Gut microbiome in Parkinson’s disease: new insights from meta-analysis Parkinsonism Relat. Disord. 94 1 9 34844021
Mao, J. et al. Gut microbiome is associated with the clinical response to anti-PD-1 based immunotherapy in hepatobiliary cancers. J. Immunother. Cancer9, e003334 (2021).
J.C. Boktor et al. Integrated multi-cohort analysis of the Parkinson’s disease gut metagenome Mov. Disord. 38 399 409 1:CAS:528:DC%2BB3sXhvVyjsro%3D 36691982
Wallen, Z. D. et al. Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms. Nat. Commun.13, 6958 (2022).
Villette, R. et al. Integrated multi-omics highlights alterations of gut microbiome functions in prodromal and idiopathic Parkinson’s disease. bioRxiv 2024.12.13.628341. https://doi.org/10.1101/2024.12.13.628341 (2024).
G. Meng H. Mei Transcriptional dysregulation study reveals a core network involving the progression of Alzheimer’s disease Front. Aging Neurosci. 11 101 1:CAS:528:DC%2BB3cXhslGhtLo%3D 31133844 6513962
L. Cai S. Tang Y. Liu Y. Zhang Q. Yang The application of weighted gene co-expression network analysis and support vector machine learning in the screening of Parkinson’s disease biomarkers and construction of diagnostic models Front Mol. Neurosci. 16 1274268 1:CAS:528:DC%2BB2cXntVyksLg%3D 37908486 10614158
H. Roume et al. Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks npj Biofilms Microbiomes 1 1:CAS:528:DC%2BB3cXhsVWiu78%3D 28721231 5515219 15007
P. Langfelder S. Horvath WGCNA: an R package for weighted correlation network analysis BMC Bioinforma. 9 1 13
C.E. Shannon A mathematical theory of communication Bell Syst. Tech. J. 27 379 423
S. Horvath et al. Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target Proc. Natl. Acad. Sci. USA 103 17402 17407 1:CAS:528:DC%2BD28Xht1KqtL%2FM 17090670 1635024
B. Zhang S. Horvath A general framework for weighted gene co-expression network analysis Stat. Appl. Genet. Mol. Biol. 4 1 1:CAS:528:DC%2BD28XmsVGgurY%3D
P. Langfelder P.S. Mischel S. Horvath When is hub gene selection better than standard meta-analysis? PLoS ONE 8 e61505 1:CAS:528:DC%2BC3sXmvVGjtLs%3D 23613865 3629234
G. Calabrese et al. Systems genetic analysis of osteoblast-lineage cells PLoS Genet. 8 1003150
M.S. Cirstea et al. Microbiota composition and metabolism are associated with gut function in Parkinson’s disease Mov. Disord. 35 1208 1217 1:CAS:528:DC%2BB3cXhsVektrbE 32357258
B. Huang et al. Gut microbiome dysbiosis across early Parkinson’s disease, REM sleep behavior disorder and their first-degree relatives Nat. Commun. 14 1:CAS:528:DC%2BB3sXptlSjtLg%3D 37130861 10154387 2501
A. Ruaud et al. Syntrophy via interspecies H2 transfer between Christensenella and Methanobrevibacter underlies their global cooccurrence in the human gut mBio 11 e03235 19 1:CAS:528:DC%2BB3cXhvFalurbJ 32019803 7002349
D.A. Ravcheev I. Thiele Systematic genomic analysis reveals the complementary aerobic and anaerobic respiration capacities of the human gut microbiota Front. Microbiol. 5 674 25538694 4257093
O. Tsoy D. Ravcheev A. Mushegian Comparative genomics of ethanolamine utilization J. Bacteriol. 191 7157 7164 1:CAS:528:DC%2BD1MXhsVyrtrjI 19783625 2786565
J.E. Vance Historical perspective: phosphatidylserine and phosphatidylethanolamine from the 1800s to the present J. Lipid Res. 59 923 944 1:CAS:528:DC%2BC1cXhtVKjtLnJ 29661786 5983396
Dank, A. et al. Bacterial microcompartment-dependent 1,2-propanediol utilization of Propionibacterium freudenreichii.Front. Microbiol.12, 679827 (2021).
Q. Li et al. Trait-based study predicts glycerol/diol dehydratases as a key function of the gut microbiota of hindgut-fermenting carnivores Microbiome 12 39300575 11414229 178
K. Asija M. Sutter C.A. Kerfeld A survey of bacterial microcompartment distribution in the human microbiome Front. Microbiol. 12 669024 34054778 8156839
D. Jallet et al. Integrative in vivo analysis of the ethanolamine utilization bacterial microcompartment in Escherichia coli mSystems 9 e0075024 39023255
N. Reichardt et al. Phylogenetic distribution of three pathways for propionate production within the human gut microbiota ISME J. 8 1323 1335 1:CAS:528:DC%2BC2cXosVyqt74%3D 24553467 4030238
Yüksel, E, Voragen, A. G. J. & Kort, R. The pectin metabolizing capacity of the human gut microbiota. Crit. Rev. Food Sci. Nutr. https://doi.org/10.1080/10408398.2024.2400235 (2024)
L.J. Lindstad et al. Human gut faecalibacterium prausnitzii deploys a highly efficient conserved system to cross-feed on β-mannan-derived oligosaccharides mBio 12 e0362820 34061597
K. Machiels et al. A decrease of the butyrate-producing species Roseburia hominis and Faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis Gut 63 1275 1283 1:CAS:528:DC%2BC2cXhsFGhur3E 24021287
L. Ye et al. Repressed Blautia-acetate immunological axis underlies breast cancer progression promoted by chronic stress Nat. Commun. 14 1:CAS:528:DC%2BB3sXitVygurvE 37789028 10547687 6160
Y. Yi et al. Gut microbiome components predict response to neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: a prospective, longitudinal study Clin. Cancer Res. 27 1329 1340 1:CAS:528:DC%2BB3MXpsVegs7w%3D 33298472
D. Yu et al. Gut Roseburia is a protective marker for peritoneal metastasis of gastric cancer Cancer Med 13 e70037 1:CAS:528:DC%2BB2cXhslahs7nL 39109683 11304227
J. Wirbel et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer Nat. Med. 25 679 689 1:CAS:528:DC%2BC1MXosFGqur0%3D 30936547 7984229
Q. Guo et al. Multiomics analyses with stool-type stratification in patient cohorts and blautia identification as a potential bacterial modulator in type 2 Diabetes Mellit. Diabetes 73 511 527 1:CAS:528:DC%2BB2cXlvFKrs78%3D
A.R. Ives S.R. Carpenter Stability and diversity of ecosystems Science 317 58 62 1:CAS:528:DC%2BD2sXnt1Sjtbg%3D 17615333
M. Loreau N. Behera Phenotypic diversity and stability of ecosystem processes Theor. Popul Biol. 56 29 47 1:STN:280:DyaK1MzntValug%3D%3D 10438667
B. Mollenhauer et al. Nonmotor and diagnostic findings in subjects with de novo Parkinson disease of the DeNoPa cohort Neurology 81 1226 1234 23997153
B. Mollenhauer et al. Monitoring of 30 marker candidates in early Parkinson disease as progression markers Neurology 87 168 27164658 4940068
A.J. Hughes S.E. Daniel L. Kilford A.J. Lees Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases J. Neurol. Neurosurg. Psychiatry 55 181 184 1:STN:280:DyaK383is1Omsg%3D%3D 1564476 1014720
A. Heintz-Buschart et al. The nasal and gut microbiome in Parkinson’s disease and idiopathic rapid eye movement sleep behavior disorder Mov. Disord. 33 88 98 1:CAS:528:DC%2BC1cXhtlKnu7k%3D 28843021
H. Roume et al. A biomolecular isolation framework for eco-systems biology ISME J. 7 110 121 22763648 3526178
S. Narayanasamy et al. IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses Genome Biol. 17 1 21
C. Quast et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools Nucleic Acids Res. 41 D590 1:CAS:528:DC%2BC38XhvV2ksb%2FN 23193283
D. Li C.M. Liu R. Luo K. Sadakane T.W. Lam MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph Bioinformatics 31 1674 1676 1:CAS:528:DC%2BC28XhtFyltL3N 25609793
P. Queirós F. Delogu O. Hickl P. May P. Wilmes Mantis: flexible and consensus-driven genome annotation Gigascience 10 1 14
Y. Liao G.K. Smyth W. Shi featureCounts: an efficient general purpose program for assigning sequence reads to genomic features Bioinformatics 30 923 930 1:CAS:528:DC%2BC2cXltFGqu7c%3D 24227677
D.E. Wood J. Lu B. Langmead Improved metagenomic analysis with Kraken 2 Genome Biol. 20 1 13
H. Cho et al. Comprehensive evaluation of methods for differential expression analysis of metatranscriptomics data Brief. Bioinform. 24 1 16 1:CAS:528:DC%2BB2cXntF2htg%3D%3D
Rezaie, N, Reese, F. & Mortazavi, A. PyWGCNA: a Python package for weighted gene co-expression network analysis. Bioinformatics 39 (2023).
Hagberg A, Schult D. & Swart P. Network analysis in Python. https://github.com/networkx/networkx, https://networkx.org/ (2004).
Oksanen, O, Blanchet, F. G. & Kindt, R. Community ecology package [R package vegan version 2.6-8]. https://doi.org/10.32614/CRAN.PACKAGE.VEGAN (2016).
V.J. Debastiani V.D. Pillar SYNCSA—R tool for analysis of metacommunities based on functional traits and phylogeny of the community components Bioinformatics 28 2067 2068 1:CAS:528:DC%2BC38XhtFSlsbzI 22668789
Varrette, S. et al. Management of an academic HPC & research computing facility: the ULHPC experience 2.0. in Proc. ACM International Conference Proceeding Series, 14–24. https://doi.org/10.1145/3560442.3560445 (ACM, 2022).
