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Context: Thiazide-induced hyponatremia is one of the most common forms of hyponatremia, but its pathogenesis is incompletely understood. Recent clinical data suggest links with prostaglandin E2 (PGE2) and a single nucleotide polymorphism (SNP) in the prostaglandin transporter gene (SLCO2A1), but it is unknown if these findings also apply to the general population. Objective: To study the associations between serum sodium, thiazide diuretics, urinary excretions of PGE2, and its metabolite (PGEM), and the rs34550074 SNP in SLCO2A1 in the general population. Design: Prospective population-based cohort study (Rotterdam Study). Setting: General population. Participants: 2178 participants (65% female, age 64 +/- 8 years) Intervention(s): None. Main Outcome: Measure(s) Serum sodium levels. Results: Higher urinary PGE2 excretion was associated with lower serum sodium: difference in serum sodium for each 2-fold higher PGE2 -0.19 mmol/L [95% confidence interval (CI) -0.31 to -0.06], PGEM -0.29 mmol/L (95% CI -0.41 to -0.17). This association was stronger in thiazide users (per 2-fold higher PGE2 -0.73 vs -0.12 mmol/L and PGEM -0.6 vs -0.25 mmol/L, P for interaction <.05 for both). A propensity score matching analysis of thiazide vs non-thiazide users yielded similar results. The SNP rs34550074 was not associated with lower serum sodium or higher urinary PGE2 or PGEM excretion in thiazide or non-thiazide users. Conclusion: Serum sodium is lower in people with higher urinary PGE2 and PGEM excretion, and this association is stronger in thiazide users. This suggests that PGE2-mediated water reabsorption regulates serum sodium, which is relevant for the pathogenesis of hyponatremia in general and thiazide-induced hyponatremia specifically.

Background. Investigation of circulating metabolites associated with kidney function and chronic kidney disease (CKD) risk could enhance our understanding of underlying pathways and identify new biomarkers for kidney function. Methods. We selected participants from the population-based Rotterdam Study with data on circulating metabolites and estimated glomerular filtration rate based on serum creatinine (eGFRcreat) available at the same time point. Data on eGFR based on serum cystatin C (eGFRcys) and urine albumin-to-creatinine ratio (ACR) were also included. CKD was defined as eGFRcreat <60 ml/min per 1.73 m2. Data on circulating metabolites (ntotal = 1381) was obtained from the Nightingale and Metabolon platform. Linear regression, linear mixed, and Cox proportional-hazards regression analyses were conducted to study the associations between metabolites and kidney function. We performed bidirectional two-sample Mendelian randomization analyses to investigate causality of the identified associations. Results. We included 3337 and 1540 participants with data from Nightingale and Metabolon, respectively. A total of 1381 metabolites (243 from Nightingale and 1138 from Metabolon) were included in the analyses. A large number of metabolites were significantly associated with eGFRcreat, eGFRcys, ACR, and CKD, including 16 metabolites that were associated with all four outcomes. Among these, C-glycosyltryptophan (HR 1.50, 95%CI 1.31;1.71) and X-12026 (HR 1.46, 95%CI 1.26;1.68) were most strongly associated with CKD risk. We revealed sex differences in the associations of 11-ketoetiocholanolone glucuronide and 11-beta-glucuronide with the kidney function assessments. No causal associations between the identified metabolites and kidney function were observed. Conclusion. Our study indicates that several circulating metabolites are associated with kidney function which are likely to have potential as biomarkers, rather than as molecules involved i

BACKGROUND: Inhibition of prostaglandin synthesis by nonsteroidal anti-inflammatory drugs is associated with cardiovascular mortality and kidney disease. This study hypothesizes that urinary prostaglandin E2 (PGE2) and PGE2 metabolite (PGEM) excretions are markers of cardiovascular and kidney health, because they reflect both systemic and kidney-derived PGE2 production. METHODS AND RESULTS: PGE2 and PGEM were measured in spot urine samples from 2291 participants (≥55 years old) of the population-based Rotterdam Study. Urinary PGE2 and PGEM excretions were analyzed using linear regression analyses to identify cross-sectional associations with cardiovascular risk factors and baseline estimated glomerular filtration rate (eGFR). Longitudinal associations with cardiovascular mortality and kidney outcomes (eGFR <60 or <45 mL/min per 1.73 m 2 and the composite outcome 40% eGFR loss or kidney failure) were assessed with Cox regression. Urinary PGE2 and PGEM excretions were higher with increasing age, lower eGFR, smoking, diabetes, and albuminuria. A 2-fold higher urinary PGE2 and PGEM excretion was associated with a higher risk of cardiovascular mortality (28 825 patient-years; 160 events; PGE2 hazard ratio [HR], 1.27, [95% CI, 1.06–1.54]; PGEM HR, 1.36 [95% CI, 1.10–1.67]). Higher PGE2 excretions were also associated with a higher risk of incident eGFR <60 mL/min per 1.73 m 2 (31 530 person-years; 691 events; HR, 1.13 [95% CI, 1.02–1.25]) with similar HRs for the other kidney outcomes. CONCLUSIONS: Urinary PGE2 and PGEM excretions are novel markers for the presence and progression of cardiovascular and kidney disease. Future studies should address whether these associations are causal and can be targeted to improve cardiovascular and kidney outcomes.