Exploring the association between osteoporosis and kidney stones: a clinical to mechanistic translational study based on big data and bioinformatics.

ABSTRACT:

Background

Osteoporosis and kidney stones share several common pathophysiological risk factors, and their association is well-established. However, previous studies have primarily focused on environmental mediators, such as diet, and the precise mechanism linking these two conditions remains unclear.

Methods

The relationship between osteoporosis and kidney stones was analyzed using weighted multivariate logistic regression, employing data from five cycles of the National Health and Nutrition Examination Survey (NHANES) from 2007-2010, 2013-2014, and 2017-2020. Gene expression data from the Gene Expression Omnibus (GEO) microarray database were integrated with machine learning techniques to identify key genes involved in both osteoporosis and kidney stones. Common targets wer

SUBMITTER: Luo D 

PROVIDER: S-EPMC11956445 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature