Metabolomic profiling in small vessel disease identifies multiple associations with disease severity.
Sands, Caroline J
Tuladhar, Anil M
de Leeuw, Frank Erik
Lewis, Matthew R
Markus, Hugh S
Oxford University Press (OUP)
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Harshfield, E. L., Sands, C. J., Tuladhar, A. M., de Leeuw, F. E., Lewis, M. R., & Markus, H. S. (2022). Metabolomic profiling in small vessel disease identifies multiple associations with disease severity.. Brain https://doi.org/10.1093/brain/awac041
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.
This study was supported by the Cambridge British Heart Foundation Centre of Research Excellence (RE/18/1/34212) and the Medical Research Council and National Institute for Health Research (NIHR) (grant MC-PC-12025). Additional support was provided by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 667375 (CoSTREAM). This research was also supported by the Cambridge University Hospitals NIHR Biomedical Research Centre (BRC-1215-20014) and the NIHR Imperial Biomedical Research Centre. AMT is supported by the Dutch Heart Foundation (Hartstichting) (grant 2016 T044). HSM is supported by a NIHR Senior Investigator Award. Data collection in the SCANS cohort was funded by the Wellcome Trust. The views expressed in this publication are those of the authors and not necessarily those of the NIHR, NHS, or UK Department of Health and Social Care.
European Commission Horizon 2020 (H2020) Societal Challenges (667375)
National Institute for Health Research (IS-BRC-1215-20014)
British Heart Foundation (RE/18/1/34212)
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External DOI: https://doi.org/10.1093/brain/awac041
This record's URL: https://www.repository.cam.ac.uk/handle/1810/333583
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