Cargando…

Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in...

Descripción completa

Detalles Bibliográficos
Autores principales: Talavera Andújar, Begoña, Aurich, Dagny, Aho, Velma T. E., Singh, Randolph R., Cheng, Tiejun, Zaslavsky, Leonid, Bolton, Evan E., Mollenhauer, Brit, Wilmes, Paul, Schymanski, Emma L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9482909/
https://www.ncbi.nlm.nih.gov/pubmed/35829770
http://dx.doi.org/10.1007/s00216-022-04207-z
_version_ 1784791557165023232
author Talavera Andújar, Begoña
Aurich, Dagny
Aho, Velma T. E.
Singh, Randolph R.
Cheng, Tiejun
Zaslavsky, Leonid
Bolton, Evan E.
Mollenhauer, Brit
Wilmes, Paul
Schymanski, Emma L.
author_facet Talavera Andújar, Begoña
Aurich, Dagny
Aho, Velma T. E.
Singh, Randolph R.
Cheng, Tiejun
Zaslavsky, Leonid
Bolton, Evan E.
Mollenhauer, Brit
Wilmes, Paul
Schymanski, Emma L.
author_sort Talavera Andújar, Begoña
collection PubMed
description Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-022-04207-z.
format Online
Article
Text
id pubmed-9482909
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-94829092022-09-20 Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study Talavera Andújar, Begoña Aurich, Dagny Aho, Velma T. E. Singh, Randolph R. Cheng, Tiejun Zaslavsky, Leonid Bolton, Evan E. Mollenhauer, Brit Wilmes, Paul Schymanski, Emma L. Anal Bioanal Chem Research Paper Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00216-022-04207-z. Springer Berlin Heidelberg 2022-07-13 2022 /pmc/articles/PMC9482909/ /pubmed/35829770 http://dx.doi.org/10.1007/s00216-022-04207-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Paper
Talavera Andújar, Begoña
Aurich, Dagny
Aho, Velma T. E.
Singh, Randolph R.
Cheng, Tiejun
Zaslavsky, Leonid
Bolton, Evan E.
Mollenhauer, Brit
Wilmes, Paul
Schymanski, Emma L.
Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title_full Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title_fullStr Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title_full_unstemmed Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title_short Studying the Parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
title_sort studying the parkinson’s disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9482909/
https://www.ncbi.nlm.nih.gov/pubmed/35829770
http://dx.doi.org/10.1007/s00216-022-04207-z
work_keys_str_mv AT talaveraandujarbegona studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT aurichdagny studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT ahovelmate studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT singhrandolphr studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT chengtiejun studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT zaslavskyleonid studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT boltonevane studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT mollenhauerbrit studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT wilmespaul studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy
AT schymanskiemmal studyingtheparkinsonsdiseasemetabolomeandexposomeinbiologicalsamplesthroughdifferentanalyticalandcheminformaticsapproachesapilotstudy