Urinary stone disease represents a significant clinical challenge worldwide, affecting up to 14.8% of the global population with substantial healthcare burden and recurrence rates (1). Stone composition analysis provides crucial insights into underlying metabolic abnormalities and guides management strategies, with calcium oxalate being the most prevalent stone type in the general population (2,3). Recent large-scale studies have revealed complex patterns in stone composition related to demographics, comorbidities, and seasonal variations (4). However, renal transplant recipients represent a unique population with fundamentally altered physiology. The metabolic milieu of these patients-characterized by chronic immunosuppressive therapy, perturbed calcium-phosphate homeostasis, vitamin D dysregulation, and frequent urological complications-suggests distinct stone pathogenesis (5,6). Post-transplant metabolic bone disease, altered parathyroid function, and medications such as calcineurin inhibitors and corticosteroids further complicate the picture (7). Despite growing recognition of stone disease as a significant post-transplant complication affecting 1-4% of recipients, with contemporary registry data confirming a 3-year incidence of approximately 1.7% (5), large-scale studies systematically comparing stone composition patterns between transplant recipients and matched controls using rigorous propensity score matching methods remain scarce (8,9).Given the distinct physiological, pharmacological, and anatomical profiles of renal transplant recipients, we hypothesized that among patients who form urinary stones, the composition profile would differ substantially from that in non-transplant patients. The interplay between immunosuppressive medications, metabolic alterations including hypercalciuria and hyperuricosuria, structural changes such as ureteral strictures, and recurrent urinary tract infections may shift stone formation patterns in ways not yet fully elucidated (10). Previous small-scale studies have suggested increased infection stone prevalence in transplant recipients, but comprehensive analyses with adequate control groups and adjustment for confounding factors are lacking (11). Understanding these compositional differences is essential for developing targeted evaluation, treatment, and recurrence prevention strategies in this vulnerable population, where stone disease can threaten graft function and patient outcomes. Therefore, we conducted this large-scale retrospective observational study analyzing 33,616 urinary stone samples collected over a decade (2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023)(2024) to comprehensively characterize stone composition patterns in renal transplant recipients who developed nephrolithiasis with those in matched non-transplant stone formers. Using propensity score matching to minimize selection bias and rigorous statistical methods including progressive adjustment models and comprehensive subgroup analyses, we aimed to: (1) identify specific stone composition profiles associated with renal transplantation among stone-forming patients; (2) quantify the magnitude of these associations while controlling for potential confounders; (3) explore demographic and clinical factors that may modify these relationships; and (4) elucidate potential mechanistic pathways linking transplantation to these distinct stone composition patterns, thereby providing evidencebased guidance for the clinical evaluation, treatment, and prevention of stones in transplant patients (4,12).This retrospective observational study analyzed urinary stone composition data from 33,616 samples collected at the First Affiliated Hospital of Guangzhou Medical University and Yuebei People's Hospital of Shaoguan in Southern China between April 2014 and December 2024. The study population comprised exclusively patients who underwent surgical or spontaneous passage of urinary stones and subsequent compositional analysis. For each specimen, primary, secondary, and tertiary components were documented, along with patient demographics (age and sex) and detailed comorbidities. Patients were categorized into two groups: the renal transplantation group (patients with a history of kidney transplantation who subsequently developed urinary stones) and the control group (stone-forming patients without transplantation history) (Figure 1). Inclusion criteria were: (1) availability of complete stone composition analysis data, and (2) complete demographic and clinical information. Exclusion criteria included: (1) incomplete stone composition analysis, (2) missing critical baseline data, and (3) stones analyzed by methods other than infrared spectroscopy. Due to the retrospective nature of the study and the use of anonymized data, the requirement for informed consent was waived (ES-2025-K062). The data collection protocol adhered to the principles outlined in the Declaration of Helsinki.In our laboratory, stone composition was examined using Fourier Transform-Infrared Spectrometry (Thermo). As per the European Association of Urology guidelines, stones were first categorized into seven primary types, including calcium oxalate (CaOx), calcium phosphate (CaP), uric acid (UA), magnesium ammonium phosphate (MAP, struvite), carbonate apatite (CA), ammonium urate (AU), and cystine (CYS) (13). Stones with MAP, CA, or AU were classified as infection stones. To conduct a more detailed analysis, we reorganized these elements into five primary categories: calcium-containing stones (including various forms of calcium oxalate monohydrate COM, calcium oxalate dihydrate COD, calcium phosphate CaP, and calcium carbonate CC), infection stones (comprising magnesium ammonium phosphate MAP, carbonate apatite CA, and ammonium urate AU), uric acid stones (including uric acid UA and its derivatives), cystine stones (CYS), and other rare compositions. Every stone sample was examined for its primary, secondary, and tertiary components. For the primary statistical analysis comparing composition prevalence between groups, stones were classified based on their dominant (primary) component.The documentation and classification of comorbidities included urological conditions (urinary tract infection UTI, hydronephrosis and To reduce confounding by indication and selection bias, we performed 1:2 propensity score matching using nearest-neighbor matching with a caliper width of 0.2 standard deviations. The propensity score was calculated using a logistic regression model that included age and sex as covariates. Balance diagnostics were assessed using standardized mean differences (SMD), with SMD <0.1 considered indicative of adequate balance. After matching, we verified that baseline characteristics were well-balanced between the transplant and control groups.All statistical analyses were performed using R and IBM SPSS Statistics (Version 25.0). Continuous variables were presented as Study profile and baseline characteristics of kidney transplant recipients with urinary stones. The flowchart depicts the identification of kidney transplant recipients from a 10-year urinary stone disease database. Stone formers in this cohort were categorized into five groups based on their primary stone composition: calcium-containing stones, infectious stones, uric acid stones, cystine stones, and other stones.mean ± standard deviation or median (interquartile range) depending on distribution normality, and compared using Student's t-test or Mann-Whitney U test. Categorical variables were expressed as frequencies and percentages, and compared using chi-square test or Fisher's exact test when appropriate. Univariate logistic regression analysis was performed to identify associations between renal transplantation and specific stone compositions, with results presented as odds ratios (OR) and 95% confidence intervals (CI). To assess the robustness of associations, we conducted sensitivity analyses using progressively adjusted models: Model 1 (unadjusted), Model 2 (adjusted for age and sex), and Model 3 (further adjusted for urinary tract stricture and renal atrophy for carbonate apatite stones). Subgroup analyses were performed stratified by age (<65 vs. ≥65 years), sex, comorbidities, and urological conditions, with interaction tests conducted using likelihood ratio tests. Forest plots were generated to visualize effect estimates across subgroups. All statistical tests were two-sided, and P<0.05 was considered statistically significant. Graphical visualization was performed using the 'ggplot2' package in R, with subsequent color and layout refinements made in Adobe Illustrator, as previously described (14)(15)(16).We further evaluated the age and sex distribution of the study cohorts (Figure 2). Among the 33,616 stone-forming patients from two hospitals, 69 underwent renal transplantation and subsequently developed nephrolithiasiswhile 33,547 stone-forming patients did not have a transplant history. Before matching, the control group demonstrated a substantially larger sample size with a broad age distribution centered around 50 years (mean age 51.59 ± 13.59 years), whereas the renal transplantation group showed a younger mean age of 48.12 ± 12.64 years (p=0.034) (Figures 2A,B). The renal transplantation group exhibited a male predominance (72.5% vs. 59.2%, p=0.034). After 1:2 propensity score matching, 139 nontransplant stone-forming patients were selected as controls, achieving excellent balance in age (48.13 ± 12.55 vs. 48.12 ± 12.64 years, p=0.994) and sex distribution (72.7% vs. 72.5% male, p=1.000), as demonstrated by the overlapping age distributions in the right panel of Figure 2C.Table 1 presents the pre-matching comparison, revealing significant differences in the distribution of stone composition between groups (p<0.001). The renal transplantation group showed a markedly higher proportion of carbonate apatite stones (37.7% vs. 16.4%) and calcium phosphate stones (8.7% vs. 2.7%), while calcium oxalate monohydrate stones were less prevalent (39.1% vs. 63.7%). Notably, ammonium urate and cystine stones were absent in the transplant cohort. Regarding comorbidities and urological conditions, the transplant group demonstrated significantly higher rates of urinary tract stricture (21.7% vs. 7.2%, p<0.001), renal insufficiency (15.9% vs. 8.4%, p=0.042), renal atrophy (14.5% vs. 5.5%, p=0.003), and hypertension (46.4% vs. 20.2%, p<0.001).After propensity score matching (Table 2), the stone composition differences persisted and became even more pronounced (p=0.001), with the transplant group maintaining significantly higher proportions of carbonate apatite (37.7% vs. 15.8%) and calcium phosphate stones (8.7% vs. 2.9%), and lower calcium oxalate monohydrate prevalence (39.1% vs. 66.9%). The matched cohorts showed improved balance in most baseline characteristics, though significant differences remained in several variables. The transplant group continued to exhibit higher prevalence of urinary tract stricture (21.7% vs. 9.4%, p=0.025), renal atrophy (14.5% vs. 3.6%, p=0.01), diabetes mellitus (14.5% vs. 5.0%, p=0.038), and hypertension (46.4% vs. 15.8%, p<0.001). Additionally, stone location distribution differed significantly (p=0.011), with the transplant group showing a higher proportion of single-site stones (88.4% vs. 69.8%). Interestingly, the control group had a higher prevalence of staghorn calculi (8.6% vs. 0%, p=0.028), while the transplant group demonstrated a significantly Analysis of the 69 kidney transplant recipients with urinary stones revealed distinctive patterns. The cohort showed consistent male predominance (72.5%) across the study period, with most cases occurring in patients aged 40-49 (n=22) (Figure 3G). The cohort showed consistent male predominance throughout the study period, with case numbers increasing notably after 2019 (Figure 3A). Stone presentation exhibited seasonal variation, with higher frequency in summer (n=24) and autumn (n=19) compared to spring (n=14) and winter (n=14) (Figure 3B). This pattern was particularly evident in patients aged 40-69 years (Figure 3C).Compositionally, infection-related stones were prominent, with carbonate apatite (CA) representing the most frequent infectious component across seasons (Figure 3D). CA stones were most prevalent in younger transplant recipients, peaking in the 30-39 year age group (n=7) (Figure 3H). Calcium-containing stones, particularly calcium oxalate monohydrate (COM), showed higher counts in summer (n=9) and were most common in patients aged 40-49 (n=7) and 50-59 (n=5) years (Figures 3F,I). Uric acid stones demonstrated seasonal variation with highest frequency in autumn (n=3) (Figure 3E).Univariate logistic regression analysis revealed that renal transplantation was significantly associated with specific stone types (Figure 4). Specifically, renal transplantation demonstrated a strong inverse association with calcium oxalate stone formation (OR 0.32, 95% CI: 0.17-0.57, p<0.001), indicating that among stoneforming patients, transplant recipients had approximately 68% lower odds of having a stone dominated by calcium oxalate compared to matched non-transplant stone formers. Conversely, renal transplantation was significantly associated with a higher odds of of carbonate apatite stone formation (OR 3.22, 95% CI: 1.66-6.32, p<0.001), representing more than a three-fold higher odds of having a carbonate apatite-dominant stone in the transplant group. These findings remained consistent with the compositional differences observed in the baseline comparison, reinforcing the distinct stone composition profiles in renal transplant stone formers. For carbonate apatite stones, additional clinical factors associated with carbonate apatite stones emerged beyond transplantation status. Renal atrophy showed the strongest association (OR 4.37, 95% CI: 1.49-13.17, p=0.007), followed by urinary tract stricture (OR 2.50, 95% CI: 1.06-5.75, p=0.032), both suggesting that structural and anatomical abnormalities of the urinary system contribute to carbonate apatite stone formation in patients who develop stones. Interestingly, younger age was also inversely associated with carbonate apatite stones (OR 0.96 per year, 95% CI: 0.94-0.99, p=0.006). Other variables including sex, diabetes mellitus, hypertension, renal insufficiency, and stone location showed no significant associations with either stone type in the univariate analysis.To explore whether the inverse association between renal transplantation and calcium oxalate stones varied across different patient subgroups, we conducted comprehensive subgroup analyses stratified by demographic characteristics, comorbidities, and urological conditions (Figure 4). This inverse association of renal transplantation with calcium oxalate stones was consistently observed across most subgroups, though the magnitude of the association varied. In patients younger than 65 years, renal transplantation demonstrated a particularly strong inverse association (OR 0.26, 95% CI: 0.14-0.50), whereas this association was attenuated and lost statistical significance in older patients (≥65 years: OR 1.30, 95% CI: 0.23-7.38), though the interaction was not statistically significant (p=0.304). Similarly, the inverse association appeared more pronounced in male patients (OR 0.25, 95% CI: 0.12-0.50) compared to female patients (OR 0.59, 95% CI: 0.19-1.79), but again without significant interaction (p=0.201).The inverse association remained robust across subgroups defined by comorbidities and urological conditions, with no significant effect modification detected. Among patients without diabetes mellitus (OR 0.30, 95% CI: 0.16-0.56), hypertension (OR 0.27, 95% CI: 0.12-0.59), renal atrophy (OR 0.34, 95% CI: 0.18-0.63), urinary tract stricture (OR 0.37, 95% CI: 0.19-0.71), or renal insufficiency (OR 0.31, 95% CI: 0.16-0.58), renal transplantation consistently showed inverse associations with calcium oxalate stones. Notably, the inverse association was even more pronounced in patients with urinary tract stricture (OR 0.16, 95% CI: 0.03-0.84), though the interaction test was not significant (p=0.348). Stone location also did not significantly modify the transplantation association (p=0.599), with inverse associations observed in both kidney stones (OR 0.35, 95% CI: 0.18-0.68) and ureteral stones (OR 0.17, 95% CI: 0.03-1.07). The consistency of these findings across diverse patient subgroups strengthens the evidence that renal transplantation fundamentally alters the stone composition profile, specifically characterized by a lower representation of calcium oxalate stones, in patients who develop nephrolithiasis.To assess the robustness of the observed associations and examine potential confounding effects, we performed sensitivity analyses using progressively adjusted logistic regression models (Figure 5). For the lower proportion of calcium oxalate stones among stone formers, the inverse association with renal transplantation remained consistent across different modeling strategies. In the unadjusted model, renal transplantation showed a strong inverse association with calcium oxalate stones (OR 0.32, 95% CI: 0.17-0.57), which persisted after adjusting for age and sex (OR 0.31, 95% CI: 0.17-0.56), demonstrating minimal confounding by these demographic factors. The consistency of effect estimates across models suggests that the inverse association between renal transplantation and calcium oxalate stone formation is robust and unlikely to be explained by age or sex differences between groups.In contrast, the positive association between renal transplantation and carbonate apatite stones showed more notable changes with progressive adjustment. The unadjusted model revealed a strong association (OR 3.22, 95% CI: 1.66-6.32), which remained significant after adjusting for age and sex (OR 3.41, 95% CI: 1.72-6.88). When further adjusted for urinary tract stricture and renal atrophy-two factors independently associated with carbonate apatite formation-the association was attenuated but remained statistically significant (OR 2.82, 95% CI: 1.37-5.82). This attenuation suggests that structural and anatomical abnormalities of the urinary tract may partially mediate the relationship between renal transplantation and carbonate apatite stone formation. Nevertheless, the persistence of a significant association even after accounting for these factors indicates that renal transplantation is linked to additional effects on carbonate apatite stone occurrence beyond its association with urological complications.This comprehensive analysis of 33,616 urinary stone cases represents of the studies stone composition patterns in renal transplant recipients matched findings that the stone composition profile fundamentally in transplant recipients, who exhibit a higher odds of carbonate apatite stones (OR 3.22, 95% CI: 1.66-6.32, and 68% lower odds of calcium oxalate stones (OR 0.32, 95% CI: 0.17-0.57, compared to propensity non-transplant stone formers. These associations remained robust across sensitivity analyses and diverse patient subgroups. Additionally, transplant recipients demonstrated significantly higher proportions of stone composition vs. urinary tract stricture (21.7% vs. 9.4%, p=0.025), and renal atrophy (14.5% vs. 3.6%, These findings challenge the that calcium oxalate stones across patient and the unique metabolic and anatomical by transplantation in this stone-forming higher proportion of carbonate apatite stones in our transplant cohort (37.7% vs. in with logistic regression analysis for calcium oxalate stones and carbonate apatite stones. of models showing adjusted odds ratios (OR) with 95% confidence intervals for factors associated with Stones and evidence that post-transplant metabolic bone disease and altered calcium-phosphate a for stone formation. Recent studies have that chronic immunosuppressive therapy, particularly calcineurin inhibitors and bone and urinary phosphate that kidney stone of transplant recipients years with infection-related stones being The immunosuppressive in calcineurin and a complex metabolic milieu that beyond their For such as in both and transplantation effects on calcium-phosphate including increased renal calcium calcium and effects on and function findings by the magnitude of this association and structural urological urinary tract stricture (OR 2.50, and renal atrophy (OR 4.37, factors associated with carbonate apatite stones. 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