Metabolite and Lipid Biomarkers Associated With Intraocular Pressure and Inner Retinal Morphology: 1H NMR Spectroscopy Results From the UK Biobank.


Journal

Investigative ophthalmology & visual science
ISSN: 1552-5783
Titre abrégé: Invest Ophthalmol Vis Sci
Pays: United States
ID NLM: 7703701

Informations de publication

Date de publication:
01 08 2023
Historique:
medline: 9 8 2023
pubmed: 8 8 2023
entrez: 8 8 2023
Statut: ppublish

Résumé

The purpose of this study was to assess metabolites associated with intraocular pressure (IOP) and inner retina structure. We cross-sectionally assessed 168 non-fasting plasma metabolites measured by nuclear magnetic resonance (NMR) spectroscopy with IOP (n = 28,195), macular retinal nerve fiber layer thickness (mRNFL; n = 10,584), and macular ganglion cell inner plexiform layer thickness (mGCIPL; n = 10,554) in the UK Biobank. We used multiple linear regression models adjusting for various covariates with probit-transformed metabolite levels as predictors for each outcome. Each estimate represents the difference in outcome variable per standard deviation increase in the probit-transformed metabolite values. We used the number of effective (NEF) tests and false discovery rate (FDR) to adjust for multiple comparisons for metabolites and metabolite classes, respectively. In individual metabolite analysis, multiple amino acids, especially branched-chain amino acids, were associated with lower IOP (-0.12 mm Hg; 95% confidence interval = -0.16 to -0.07; NEF = 2.7E-05). Albumin, 3 hydroxybutyrate, lactate, and several lipids were associated with higher IOP (range = 0.07 to 0.18 mm Hg, NEF = ≤ 0.039). In IOP-adjusted analyses, five HDL-related metabolites were associated with thinner mRNFL (-0.15 microns for all metabolites, NEF = ≤ 0.027), whereas five LDL-related metabolites were associated with thicker mGCIPL (range = 0.17 to 0.20 microns; NEF = ≤ 0.044). In metabolite class analysis, the lipid components of lipoproteins (cholesterol, triglycerides, etc.) were not associated with our outcomes (FDR > 0.2 for all); yet multiple lipoproteins were significantly (FDR < 0.05) associated with all outcomes. Branched-chain amino acids were associated with lower IOP, HDL metabolites were associated with thinner mRNFL, and LDL metabolites were associated with thicker mGCIPL.

Identifiants

pubmed: 37552033
pii: 2791380
doi: 10.1167/iovs.64.11.11
pmc: PMC10411643
doi:

Substances chimiques

Lipids 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

11

Subventions

Organisme : Medical Research Council
ID : MR/T040912/1
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA067262
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA176726
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA167552
Pays : United States
Organisme : NCI NIH HHS
ID : UM1 CA186107
Pays : United States
Organisme : NEI NIH HHS
ID : R01 EY015473
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA049449
Pays : United States
Organisme : NEI NIH HHS
ID : P30 EY003790
Pays : United States

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Auteurs

Louis R Pasquale (LR)

Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, United States.

Anthony P Khawaja (AP)

NIHR Biomedical Research Centre at Moorfields Eye Hospital & UCL Institute of Ophthalmology, London, United Kingdom.

Janey L Wiggs (JL)

Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States.

Jihye Kim (J)

Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States.

Pirro Hysi (P)

Department of Ophthalmology, King's College London, St. Thomas' Hospital, London, United Kingdom.
Department of Twin Research & Genetic Epidemiology, King's College London, St. Thomas' Hospital, London, United Kingdom.

Tobias Elze (T)

Department of Ophthalmology, Schepens Research Eye Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States.

Jessica Lasky-Su (J)

Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States.

Jae H Kang (JH)

Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States.

Oana Zeleznik (O)

Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States.

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Classifications MeSH