ArticleEuropean urology open science2024
Evaluation of Genetic Associations with Clinical Phenotypes of Kidney Stone Disease.
Article in European urology open science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Deep biochemical phenotyping reveals prognostic value of rare genetic variants in adult kidney stone disease.The Journal of clinical investigation · 2026Observational
- Personalised prevention and management of kidney stones: a narrative review on the importance of integrating environmental, social and genetic factors.Public health reviews · 2026Review
- Multi-habitat microbiome profiling identifies habitat-dependent alterations and complementary discriminatory information in urolithiasis.Frontiers in cellular and infection microbiology · 2026Article
- The Application of Nanomaterials in Kidney Stone Disease: Emerging Strategies for Early Diagnosis, Targeted Therapy, and Prevention.International journal of nanomedicine · 2026Review
- Large language models improve the identification of emergency department visits for symptomatic kidney stones.Scientific reports · 2025Article
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6 authors.
Funding
Abstract
Background and objective: Previous studies have reported a strong genetic contribution to kidney stone risk. This study aims to identify genetic associations of kidney stone disease within a large-scale electronic health record system. Methods: We performed genome-wide association studies (GWASs) for nephrolithiasis from genotyped samples of 5571 cases and 83 692 controls. This analysis included a primary GWAS focused on nephrolithiasis and subsequent subgroup GWASs stratified by stone composition types. For significant risk variants, we performed association analyses with stone composition and first-time 24-h urine parameters. To assess disease severity, we investigated the associations with age at first stone diagnosis, age at first stone-related procedure, and time between first and second stone-related procedures. Key findings and limitations: The primary GWAS analysis identified ten significant loci, all located on chromosome 16 within coding regions of the Conclusions and clinical implications: We replicated germline variants associated with kidney stone disease risk at Patient summary: We identify genetic variants linked to kidney stone disease within an electronic health record (EHR) system. These findings suggest a role for the EHR to enable a precision-medicine approach for stone disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.