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Metabolomic profiling in small vessel disease identifies multiple associations with disease severity

Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict...

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Autores principales: Harshfield, Eric L, Sands, Caroline J, Tuladhar, Anil M, de Leeuw, Frank Erik, Lewis, Matthew R, Markus, Hugh S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337813/
https://www.ncbi.nlm.nih.gov/pubmed/35254405
http://dx.doi.org/10.1093/brain/awac041
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author Harshfield, Eric L
Sands, Caroline J
Tuladhar, Anil M
de Leeuw, Frank Erik
Lewis, Matthew R
Markus, Hugh S
author_facet Harshfield, Eric L
Sands, Caroline J
Tuladhar, Anil M
de Leeuw, Frank Erik
Lewis, Matthew R
Markus, Hugh S
author_sort Harshfield, Eric L
collection PubMed
description Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches.
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spelling pubmed-93378132022-08-01 Metabolomic profiling in small vessel disease identifies multiple associations with disease severity Harshfield, Eric L Sands, Caroline J Tuladhar, Anil M de Leeuw, Frank Erik Lewis, Matthew R Markus, Hugh S Brain Original Article Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches. Oxford University Press 2022-02-08 /pmc/articles/PMC9337813/ /pubmed/35254405 http://dx.doi.org/10.1093/brain/awac041 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Harshfield, Eric L
Sands, Caroline J
Tuladhar, Anil M
de Leeuw, Frank Erik
Lewis, Matthew R
Markus, Hugh S
Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title_full Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title_fullStr Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title_full_unstemmed Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title_short Metabolomic profiling in small vessel disease identifies multiple associations with disease severity
title_sort metabolomic profiling in small vessel disease identifies multiple associations with disease severity
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9337813/
https://www.ncbi.nlm.nih.gov/pubmed/35254405
http://dx.doi.org/10.1093/brain/awac041
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