The Association of Urinary Sodium Excretion with Glaucoma and Related Traits in a Large United Kingdom Population

Abstract

Purpose: Excessive dietary sodium intake has known adverse effects on intravascular fluid volume and systemic blood pressure, which may influence intraocular pressure (IOP) and glaucoma risk. This study aimed to assess the association of urinary sodium excretion, a biomarker of dietary intake, with glaucoma and related traits, and determine whether this relationship is modified by genetic susceptibility to disease.

Design: Cross-sectional observational and gene-environment interaction analyses in the population-based UK Biobank study.

Participants: Up to 103 634 individuals (mean age: 57 years; 51% women) with complete urinary, ocular, and covariable data.

Methods: Urine sodium:creatinine ratio (UNa:Cr; mmol:mmol) was calculated from a midstream urine sample. Ocular parameters were measured as part of a comprehensive eye examination, and glaucoma case ascertainment was through a combination of self-report and linked national hospital records. Genetic susceptibility to glaucoma was calculated based on a glaucoma polygenic risk score comprising 2673 common genetic variants. Multivariable linear and logistic regression, adjusted for key sociodemographic, medical, anthropometric, and lifestyle factors, were used to model associations and gene-environment interactions.

Main outcome measures: Corneal-compensated IOP, OCT derived macular retinal nerve fiber layer and ganglion cell-inner plexiform layer (GCIPL) thickness, and prevalent glaucoma.

Results: In maximally adjusted regression models, a 1 standard deviation increase in UNa:Cr was associated with higher IOP (0.14 mmHg; 95% confidence interval [CI], 0.12-0.17; P < 0.001) and greater prevalence of glaucoma (odds ratio, 1.11; 95% CI, 1.07-1.14; P < 0.001) but not macular retinal nerve fiber layer or ganglion cell-inner plexiform layer thickness. Compared with those with UNa:Cr in the lowest quintile, those in the highest quintile had significantly higher IOP (0.45 mmHg; 95% CI, 0.36-0.53, P < 0.001) and prevalence of glaucoma (odds ratio, 1.30; 95% CI, 1.17-1.45; P < 0.001). Stronger associations with glaucoma (P interaction = 0.001) were noted in participants with a higher glaucoma polygenic risk score.

Conclusions: Urinary sodium excretion, a biomarker of dietary intake, may represent an important modifiable risk factor for glaucoma, especially in individuals at high underlying genetic risk. These findings warrant further investigation because they may have important clinical and public health implications.

Financial disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Keywords: Dietary salt; Gene-environment interaction; Glaucoma; Intraocular pressure; Urinary sodium.

Figure 1.

Flow diagram outlining the participant selection process for this study in the UK Biobank. GxE = gene-environment interaction; IOP = intraocular pressure; UNa:Cr = urine sodium:creatinine ratio.

Figure 2.

Associations of urinary sodium excretion with (A) estimated sodium intake in the past 24 hours, (B) systolic blood pressure, (C) estimated glomerular filtration rate, and (D) urine potassium concentration in UK Biobank participants. Models adjusted for: age (years), sex (women, men), Townsend deprivation index, height (cm), weight (kg), glycated hemoglobin (mmol/mol), total cholesterol (mmol/L), smoking status (never, current, former), alcohol intake (g/day), physical activity (MET-minutes/week), assessment season (Summer, Autumn, Winter, Spring), time of urine collection (morning, afternoon, evening), and urinary potassium concentration (A–C only). MET = metabolic equivalent of task; Q = quintile.

Figure 3.

Gene-environment interaction analyses illustrating the effect of the glaucoma PRS on the association of urinary sodium excretion with (A) intraocular pressure, (B) macular retinal nerve fiber layer thickness, (C) macular ganglion cell-inner plexiform layer thickness, and (D) glaucoma status in European UK Biobank participants. Models adjusted for: age (years), sex (women, men), Townsend deprivation index, height (cm), weight (kg), glycated hemoglobin (mmol/mol), total cholesterol (mmol/L), smoking status (never, current, former), alcohol intake (g/day), physical activity (MET-minutes/week), assessment season (Summer, Autumn, Winter, Spring), time of urine collection (morning, afternoon, evening), and urinary potassium concentration (mmol/L). GCIPL = ganglion cell-inner plexiform layer; PRS = polygenic risk score; Q = quartile; RNFL = retinal nerve fiber layer.