2022
DOI: 10.1101/2022.06.08.495316
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Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms

Abstract: Parkinson's disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association. Thirty-percent of species and pathways tested had altered abundances in PD, depicting a widespread dysbiosis. Network analysis showed PD-associated species form po… Show more

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Cited by 2 publications
(2 citation statements)
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“…This is a crucial question that needs to be addressed, since most current therapies are aimed at targeting FUS in the central nervous system, without considering the systemic alterations caused by FUS mutation. Of note, investigation of pleiotropic phenotypes in Parkinson's disease has proven illuminating, with a role for the gut-brain axis proposed as a major early pathomechanism (Wallen et al 2022).…”
Section: Discussionmentioning
confidence: 99%
“…This is a crucial question that needs to be addressed, since most current therapies are aimed at targeting FUS in the central nervous system, without considering the systemic alterations caused by FUS mutation. Of note, investigation of pleiotropic phenotypes in Parkinson's disease has proven illuminating, with a role for the gut-brain axis proposed as a major early pathomechanism (Wallen et al 2022).…”
Section: Discussionmentioning
confidence: 99%
“…To test the effect of medication usage we applied two independent strategies. First, we selected all metadata related to medication usage available from Wallen et al 15,103 We then retained only medications used in at least 20% of the participants (11 medications in total) and used them to perform a variable selection using the regsubsets function in the leaps v_3.1 R package 104 . This was done for the regressions modelling the abundance of the features as a function of medications and disease status, allowing models with a maximum of 12 variables (including all medications and the disease status).…”
Section: Methodsmentioning
confidence: 99%