In one paragraphArticle in Metabolites, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
10 authors.
Akiko HanyudaDepartment of Ophthalmology, Keio University School of Medicine, Tokyo 160-8582, Japan.ORCID 0000-0002-2342-9550 Oana A ZeleznikChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0002-8705-1163 Yoshihiko RaitaDepartment of Nephrology, Okinawa Prefectural Chubu Hospital, Naha 904-2293, Japan.
Danielle E HaslamChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0003-0144-3287 Qi SunChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Kazuno NegishiDepartment of Ophthalmology, Keio University School of Medicine, Tokyo 160-8582, Japan.ORCID 0000-0002-2892-9810 Louis R PasqualeDepartment of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0002-5835-3496 Jessica Lasky-SuChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Janey L WiggsDepartment of Ophthalmology, Harvard Medical School, Massachusetts Eye and Ear Infirmary, Boston, MA 02114, USA.
Jae H KangChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0003-4812-0557 Funding
Life Course Cancer Epidemiology Cohort in WomenU01CA176726 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI ELIASSEN, A. HEATHER, WILLETT, WALTER C. · 2018 to 2025
$22.4MLong Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3MCancer Epidemiology Cohort in Male Health ProfessionalsU01CA167552 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Lorelei Mucci, Walter C. Willett · 2017 to 2026
$17.0MGene-Environment Interactions in GlaucomaR01EY015473 · NEI · MASSACHUSETTS EYE AND EAR INFIRMARY · PI PASQUALE, LOUIS ROBERT · 2005 to 2021
$8.3MGenetic and Environmental Risk Factors for Exfoliation Syndrome and GlaucomaR01EY020928 · NEI · MASSACHUSETTS EYE AND EAR INFIRMARY · PI KANG, JAE H, WIGGS, JANEY L · 2011 to 2025
$7.3MPROSPECTIVE STUDY OF RISK FACTORS FOR EYE DISEASER01EY009611 · NEI · BRIGHAM AND WOMEN'S HOSPITAL · PI HANKINSON, SUSAN E. · 1995 to 2004
$2.2MProteomic and integrative omic profiles of sugar- and artificially sweetened beverage consumption and changes in type 2 diabetes risk factorsK01DK136968 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI Danielle Haslam · 2023 to 2026
$634kNCI NIH HHS U01 CA167552NCI NIH HHS U01 CA176726NCI NIH HHS UM1 CA186107NEI NIH HHS R01 EY009611NEI NIH HHS R01 EY015473NEI NIH HHS R01 EY020928NIDDK NIH HHS K01 DK136968NIH HHS NEI R01 EY020928, R01 EY015473 (LRP), NCI UM1 CA186107, U01 CA167552, and an unrestricted challenge grant to Icahn School of Medicine at Mount Sinai, Department of Ophthalmology from Research to Prevent Blindness (LRP).
6 · The paper itselfAbstract
backgroundExfoliation glaucoma (XFG) represents a form of deleterious ocular aging of unclear etiology. We evaluated prediagnostic nuclear magnetic resonance (NMR)-based metabolites in relation to XFG risk, expanding on our prior findings of XFG-related metabotypes using liquid chromatography-mass spectrometry (LC-MS).
methodsWe identified 217 XFG cases and 217 matched controls nested within three prospective health professional cohorts with plasma collected a mean 11.8 years before case identification. Plasma metabolites were analyzed using the targeted NMR Nightingale platform. Conditional logistic models and Metabolite Set Enrichment Analysis were performed. Multiple comparison issues were addressed using the number of effective tests (NEF) and false discovery rate (FDR).
resultsAmong 235 profiled metabolites, higher glucose was significantly associated with a lower risk of XFG (odds ratio (95%CI) = 0.42 (0.26, 0.7); NEF = 0.03). Among metabolite classes, lipoprotein subclasses and branched-chain amino acids were inversely associated, while relative lipoprotein lipid concentrations were adversely associated (FDR < 0.05).
conclusionNMR profiling revealed that glucose, branched-chain amino acids, lipoprotein subclasses, and relative lipoprotein lipid concentrations may play important roles in XFG etiology.
Indexed as
exfoliation glaucomametabolomicsnuclear magnetic resonance spectrometryomics
Identifiers
PMID40710569
PMCPMC12299095
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