Multiomics implicate gut microbiota in altered lipid and energy metabolism in Parkinson’s disease

Pereira, Pedro; Dk, Trivedi; Silverman, Justin D.; Ic, Duru; Paulín, Lars; Auvinen, Petri; Scheperjans, Filip

doi:10.1101/2021.05.29.21258035

Cited by 4 publications

(8 citation statements)

References 57 publications

(106 reference statements)

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Section: Discussionmentioning

confidence: 99%

“…Several studies have found alterations in microbial composition and metabolites in PD, but the mechanisms linking these changes to PD and its symptoms are not well understood. 8,9,11 The bacterial metabolite butyrate is a strong HDAC inhibitor, with known epigenetic effects. 62 Several studies have shown the ability of butyrate to affect the innate and adaptive immune system as well as to alter the blood-brain barrier permeability.…”

Section: Discussionmentioning

confidence: 99%

“…These same mice displayed increased motor deficits after receiving a fecal transplant from a PD patient compared to receiving transplant from a healthy donor. Moreover, the composition and function of the gut microbiome in PD patients have been shown to be significantly different from healthy controls in multiple studies 7‐10 …”

Section: Figurementioning

confidence: 99%

“…Moreover, the composition and function of the gut microbiome in PD patients have been shown to be significantly different from healthy controls in multiple studies. [7][8][9][10] Recent meta-analyses suggest that a reduced abundance of short-chain fatty acid (SCFA) producing bacteria is one of the most consistent findings in the PD microbiome composition across studies. 11,12 SCFAs are saturated fatty acids produced via the fermentation of dietary fiber by certain colonic bacteria.…”

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confidence: 99%

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Bacterial Butyrate in Parkinson's Disease Is Linked to Epigenetic Changes and Depressive Symptoms

Xie

Ensink

et al. 2022

Movement Disorders

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A BS TRACT: Background: The gut microbiome and its metabolites can impact brain health and are altered in Parkinson's disease (PD) patients. It has been recently demonstrated that PD patients have reduced fecal levels of the potent epigenetic modulator butyrate and its bacterial producers.Objectives: Here, we investigate whether the changes in the gut microbiome and associated metabolites are related to PD symptoms and epigenetic markers in leucocytes and neurons. Methods: Stool, whole blood samples, and clinical data were collected from 55 PD patients and 55 controls. We performed DNA methylation analysis on whole blood samples and analyzed the results in relation to fecal shortchain fatty acid concentrations and microbiota composition. In another cohort, prefrontal cortex neurons were isolated from control and PD brains. We identified genome-wide DNA methylation by targeted bisulfite sequencing. Results: We show that lower fecal butyrate and reduced counts of genera Roseburia, Romboutsia, and Prevotella are related to depressive symptoms in PD patients. Genes containing butyrate-associated methylation sites include PD risk genes and significantly overlap with sites epigenetically altered in PD blood leucocytes, predominantly neutrophils, and in brain neurons, relative to controls. Moreover, butyrate-associated methylated-DNA regions in PD overlap with those altered in gastrointestinal (GI), autoimmune, and psychiatric diseases. Conclusions: Decreased levels of bacterially produced butyrate are related to epigenetic changes in leucocytes and neurons from PD patients and to the severity of their depressive symptoms. PD shares common butyratedependent epigenetic changes with certain GI and psychiatric disorders, which could be relevant for their epidemiological relation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

mentioning

confidence: 99%

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Bacterial Butyrate in Parkinson's Disease Is Linked to Epigenetic Changes and Depressive Symptoms

Xie

Ensink

et al. 2022

Movement Disorders

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“…Trivedi used gas chromatography–mass spectrometry (GC–MS) to prove that there were different VOCs in the sebum of PD and healthy people . These VOCs such as perillic aldehyde and eicosane may change with the increase of sebum secretion, and the interaction between sebum and the yeast of the microbiome can make human skin smelly. − Besides, Tsuda used GC–MS to analyze the smell of sebum and found that the types and concentrations of VOCs such as dodecane, acetone, and ethyl acetate released in the sebum of PD patients were related to UPDRS part 3, representing the severity of motor in PD. These studies indicated that sebum gas could be used for the detection of PD.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligent Olfactory System for the Diagnosis of Parkinson’s Disease

et al. 2022

ACS Omega

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Background: Currently, Parkinson’s disease (PD) diagnosis is mainly based on medical history and physical examination, and there is no objective and consistent basis. By the time of diagnosis, the disease would have progressed to the middle and late stages. Pilot studies have shown that a unique smell was present in the skin sebum of PD patients. This increases the possibility of a noninvasive diagnosis of PD using an odor profile. Methods: Fast gas chromatography (GC) combined with a surface acoustic wave sensor with embedded machine learning (ML) algorithms was proposed to establish an artificial intelligent olfactory (AIO) system for the diagnosis of Parkinson’s through smell. Sebum samples of 43 PD patients and 44 healthy controls (HCs) from Fourth Affiliated Hospital of Zhejiang University School of Medicine, China, were smelled by the AIO system. Univariate and multivariate methods were used to identify the significant volatile organic compound (VOC) features in the chromatograms. ML algorithms, including support vector machine, random forest (RF), k nearest neighbor (KNN), AdaBoost (AB), and Naive Bayes (NB), were used to distinguish PD patients from HC based on the VOC peaks in the chromatograms of sebum samples. Results: VOC peaks with average retention times of 5.7, 6.0, and 10.6 s, respectively, corresponding to octanal, hexyl acetate, and perillic aldehyde, were significantly different in PD and HC. The accuracy of the classification based on the significant features was 70.8%. Based on the odor profile, the classification had the highest accuracy and F1 of the five models with 0.855 from NB and 0.846 from AB, respectively, in the process of model establishing. The highest specificity and sensitivity of the five classifiers were 91.6% from NB and 91.7% from RF and KNN, respectively, in the evaluating set. Conclusions: The proposed AIO system can be used to diagnose PD through the odor profile of sebum. Using the AIO system is helpful for the screening and diagnosis of PD and is conducive to further tracking and frequent monitoring of the PD treatment process.

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Interpretable machine learning on metabolomics data reveals biomarkers for Parkinson’s disease

Zhang

Xue

Kolachalama

et al. 2022

Preprint

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The use of machine learning (ML) with metabolomics provides opportunities for the early diagnosis of disease. However, the accuracy and extent of information obtained from ML and metabolomics can be limited owing to challenges associated with interpreting disease prediction models and analysing many chemical features with abundances that are correlated and ‘noisy’. Here, we report an interpretable neural network (NN) framework to accurately predict disease and identify significant biomarkers using whole metabolomics datasets without feature selection. The performance of the NN approach for predicting Parkinson’s disease (PD) from blood plasma metabolomics data was significantly higher than classical ML methods with a mean area under the curve of > 0.995. PD-specific markers that contribute significantly to early disease prediction were identified including an exogenous polyfluoroalkyl substance. It is anticipated that this accurate and interpretable NN-based approach can improve diagnostic performance for many other diseases using metabolomics and other untargeted ‘omics methods.

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Multiomics implicate gut microbiota in altered lipid and energy metabolism in Parkinson’s disease

Cited by 4 publications

References 57 publications

Bacterial Butyrate in Parkinson's Disease Is Linked to Epigenetic Changes and Depressive Symptoms

Bacterial Butyrate in Parkinson's Disease Is Linked to Epigenetic Changes and Depressive Symptoms

Artificial Intelligent Olfactory System for the Diagnosis of Parkinson’s Disease

Interpretable machine learning on metabolomics data reveals biomarkers for Parkinson’s disease

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