Abstract: SA-OR39
The Plasma Metabolome and Risk of Incident Kidney Stones
Session Information
- Fluid, Electrolyte, and Acid-Base Disorders: Clinical Research
November 04, 2023 | Location: Room 111, Pennsylvania Convention Center
Abstract Time: 04:39 PM - 04:48 PM
Category: Fluid, Electrolytes, and Acid-Base Disorders
- 1102 Fluid, Electrolyte, and Acid-Base Disorders: Clinical
Authors
- Ferraro, Pietro Manuel, Universita Cattolica del Sacro Cuore Facolta di Medicina e Chirurgia, Roma, Lazio, Italy
- Li, Yukun, University of Massachusetts Amherst, Amherst, Massachusetts, United States
- Curhan, Gary C., Brigham and Women's Hospital Channing Division of Network Medicine, Boston, Massachusetts, United States
- Taylor, Eric N., Brigham and Women's Hospital Channing Division of Network Medicine, Boston, Massachusetts, United States
Background
The pathogenesis of kidney stone disease is not completely understood. Information on metabolomic profiles in kidney stone formers is limited, with most studies focusing on urine metabolomics or on pediatric populations using cross-sectional designs. To examine independent associations between plasma metabolomic profiles and the risk of incident, symptomatic kidney stones in adults, we conducted prospective nested case-control studies in two large cohorts.
Methods
We performed plasma metabolomics on 1,758 participants, including 879 stone formers (346 from the Health Professionals Follow-up [HPFS] cohort, 533 from the Nurses’ Health Study [NHS] II cohort) and 879 non-stone formers (346 from HPFS, 533 from NHS II) matched for age, race, time of blood collection, fasting status and (for NHS II) menopausal status and luteal day of menstrual cycle for premenopausal participants. Conditional logistic regression models were used to estimate the odds ratio of kidney stones corresponding to a one standard deviation increase in metabolite levels, adjusted for confounders. A plasma metabolite based score reflecting risk of incident kidney stones was developed in each cohort in a conditional logistic regression model with a lasso penalty. The scores derived in the HPFS (‘KMS_HPFS’) and the NHS II (‘KMS_NHS’) were each tested for its association with kidney stone risk in the other cohort.
Results
In each cohort, a variety of individual metabolites were associated with incident kidney stone formation at prespecified levels of metabolome-wide statistical significance. We identified three novel metabolites associated with kidney stones in both HPFS and NHS II, all with inverse associations with kidney stones risk: beta-cryptoxanthin, sphingomyelin (d18:2/24:1, d18:1/24:2), and sphingomyelin (d18:2/24:2). The standardized KMS_HPFS yielded an OR for stones in the NHS II cohort of 1.23 (95% CI 1.05, 1.44; p-value = 0.008). The standardized KMS_NHS was in the expected direction but did not reach statistical significance in HPFS (OR 1.16, 95% CI 0.97, 1.39; p-value = 0.10).
Conclusion
The findings of specific metabolites associated with kidney stone status in two cohorts as well as a plasma metabolomic signature in stone formers offers a novel approach to characterize stone formers and to elucidate the pathogenesis of stone formation with the future potential to personalize therapeutic approaches.
Funding
- NIDDK Support