-
PDF
- Split View
-
Views
-
Cite
Cite
Andres Rodriguez, Maria Alejandra Quintero, Hajar Hazime, Rose Killian, Gloria Michelle Ducasa, Katerina M Faust, Maria T Abreu, Risk Factors for Chronic Kidney Disease in Patients With Crohn’s Disease, Inflammatory Bowel Diseases, 2025;, izaf039, https://doi.org/10.1093/ibd/izaf039
- Share Icon Share
Abstract
Patients with inflammatory bowel diseases (IBD), including Crohn’s disease (CD), are at risk of complications, including kidney disease. It is important to identify IBD patients at higher risk of chronic kidney disease (CKD) to improve prevention and treatment. Here, we investigated the clinical and metabolomic characteristics of CD patients who develop CKD.
We identified adult CD patients with (CD + CKD, n = 87) and selected CD patients without CKD (CD controls) matched by age, race, and gender. We collected data on demographic characteristics (age, smoking status, ethnicity, gender), IBD characteristics (diagnosis, Montreal classification, medication use, IBD-related surgeries, perianal disease), and kidney-related factors (primary sclerosing cholangitis, end-stage renal disease, hypertension, diabetes, organ transplantation, and nephrolithiasis). Univariate and multivariate analyses were conducted and odds ratios were calculated to identify risk factors for CKD. Serum samples were collected for untargeted metabolomic analysis.
Chronic kidney disease was far more common in CD patients than UC patients. Crohn’s disease patients with kidney stones had a 10-fold higher risk of developing CKD than those without kidney stones. Crohn’s disease patients with more than 2 IBD-related surgeries had a 7.3-fold higher risk of developing CKD than those who had not undergone surgery. There was no relationship between the number of biologics used or mesalamine use and the risk of CKD. The serum of CD + CKD patients had elevated levels of pro-inflammatory metabolites and those linked to kidney injury.
We recommend regular kidney function monitoring and ensuring proper hydration to prevent or manage potential kidney-related complications in CD patients. Patients with resections and kidney stones are particularly vulnerable.
Lay Summary
Crohn’s disease patients are at higher risk of developing chronic kidney disease. Risk factors include kidney stones, multiple inflammatory bowel diseases–related surgeries, and previous steroid use. We recommend monitoring kidney function and ensuring proper hydration in these patients to prevent kidney-related complications.
Patients with inflammatory bowel diseases (IBD), including Crohn’s disease (CD), are at risk of complications, including kidney disease.
We matched CD patients with chronic kidney disease (CKD) to CD controls and identified risk factors for CKD, including kidney stones and multiple IBD-related surgeries.
We recommend regular monitoring of kidney function and maintaining optimal hydration in CD patients to prevent or manage potential kidney-related complications.
Introduction
Inflammatory bowel diseases (IBD) are complex and multifaceted systemic diseases characterized by inflammation of the intestine and influenced by host genetic factors, gut microbiota, and immunological responses.1,2 Management of IBD is equally intricate and requires a multidisciplinary, comprehensive approach. Proper evaluation, treatment, and management involve pharmacological,3 nutritional,4 psychosocial,5 and socioeconomic6 perspectives on care. Additionally, IBD may present with extraintestinal manifestations,7 which occur before the onset of intestinal symptoms in up to 25.8% of patients with IBD.8–10 Typical extraintestinal manifestations consist of abnormalities of the joints, skin, liver, and pancreas; the kidneys can also be affected either by the disease or as a result of medications.10
Chronic kidney disease (CKD) affects approximately 37 million adults in the United States11,12; there is currently no cure, and this disease increases the risk of cardiovascular disease.13 Patients with CKD can experience progressive worsening of kidney function.13 There are many risk factors for the development of CKD. Diabetes mellitus and hypertension are the primary contributors due to their effects on renal function.14 Age (over 60), obesity, tobacco use, cardiovascular disease, hyperlipidemia, and use of medications such as non-steroidal anti-inflammatory drugs are other factors implicated in the development of CKD.15 Race and ethnicity may also influence risk: African Americans, Hispanics, Native Americans, and Asian Americans are more susceptible to CKD.16 Additionally, patients with IBD have an increased risk of acute kidney injury and CKD,17 with up to 15.9% developing renal insufficiency.18 While recent meta-analyses have examined the relationship between CKD and IBD,17,19 the strength and specificity (eg, in IBD subtypes) of this association remains unclear.
Gastrointestinal inflammation can play a role in the development of CKD. In a retrospective cohort study, which controlled for typical risk factors for CKD (diabetes mellitus, hypertension, smoking, coronary artery disease, peripheral artery disease, stroke, healthcare utilization, and age), IBD was associated with an increased risk of CKD.20 Previous studies have attributed CKD development in IBD patients to IBD-related medication (corticosteroids,21 5-aminosalicylates,22,23 anti-TNF therapy24), interstitial nephropathies,25,26 and nephrolithiasis.27,28 However, the causes of CKD in IBD patients and associated risk factors remain unclear. Factors unique to IBD patients that may predispose them to CKD development include gut dysbiosis (excess toxins, less protective metabolites29), dyslipidemia,30 and surgery.24 Thus, patients with difficult-to-treat or more severe IBD (eg, a high number of gastrointestinal-related surgeries or a high number of biologics) may have elevated risks of developing other extraintestinal complications, such as CKD.
The aim of this study was to identify characteristics of IBD patients that are risk factors for CKD. By identifying IBD patients at higher risk of developing CKD, healthcare providers may be able to intercept the development of CKD, which in many cases can result in the need for dialysis or a kidney transplant.
Materials and Methods
Identification of Patients With IBD and CKD
This study was conducted at a tertiary referral center (University of Miami Health System) with approval from the University of Miami Institutional Review Board (approval numbers 20081100 and 20180765). Records from patients visiting the center from January 1, 2010, to December 31, 2022, were included in a chart review (IRB approval number 20180765). Serum samples were collected under our biorepository protocol (IRB approval number 2081100), under which patient informed consent was provided to collect blood samples at the time of clinic visit or colonoscopy from patients who visited the Crohn’s and Colitis Center.
To identify relevant patients, we first searched Epic for patients with IBD (CD or ulcerative colitis [UC]) using International Classification of Diseases, 10th revision (ICD-10) codes (K50 = Crohn’s disease, K51 = ulcerative colitis, K52 = Other, and unspecified noninfective gastroenteritis and colitis). We included only adult patients (18 years or older). Next, we identified if any of these IBD patients had CKD using the Kidney Disease: Improving Global Outcomes (KDIGO) criteria: eGFR < 60 mL/min/1.73 m2 at 2 visits separated by at least 3 months or a history of end-stage renal disease requiring renal transplant.31 IBD patients with acute kidney injury were excluded. A manual review of electric medical records was also conducted for the above criteria for IBD and CKD and to confirm IBD diagnosis (ie, a note from a gastroenterologist or a visit to the Crohn’s and Colitis Center at the University of Miami). After identifying patients with IBD and CKD, we then matched these patients to IBD controls (ie, patients without evidence of CKD). Given that age15 and race16 may influence CKD risk, we matched IBD + CKD patients to IBD controls by age, race, and gender.
Chart Review of IBD Patient Characteristics and Kidney-Related Risk Factors
After identifying IBD + CKD patients and IBD controls (matched for age, race, and gender), we performed a detailed chart review. We entered the data collected into a database maintained in Microsoft Excel (Microsoft Corporation). These data included current age, age at diagnosis, smoking status, ethnicity, medication use, gender, IBD diagnosis, and Montreal classification (for CD patients) or disease extent (for UC patients). We also noted the following categorical variables (with binary answers: yes or no): Extraintestinal manifestations of IBD (those identifiable from ICD-10 codes included only a history of primary sclerosing cholangitis and nephrolithiasis; other IBD-related skin/joint involvement could not be determined from ICD-10 codes), end-stage renal disease, hypertension, diabetes mellitus, history of organ transplantation, perianal disease, and IBD-related surgeries (eg, colectomy, small intestinal or colonic resection, or J-pouch procedure). Patients with hypertension and diabetes mellitus were identified based on ICD-10 diagnostic codes and recorded diagnosis-related medication prescriptions. Medication use included current or previous use of aminosalicylates, immunomodulators, calcineurin inhibitors, biologics, small molecules, and corticosteroids.
Given that we aimed to identify risk factors for CKD development in IBD patients, we excluded any patients who underwent a kidney transplant prior to IBD diagnosis or who underwent a kidney transplant after IBD diagnosis but for reasons unrelated to IBD (eg, due to polycystic renal disease).
Serum Metabolite Analysis Using Untargeted Metabolomics
Serum samples were available from 31 IBD controls (eGFR > 60 mL/min/1.73 m2), and 23 IBD + CKD patients (eGFR < 60 mL/min/1.73 m2). Both sets of patients (IBD controls and IBD + CKD patients) had provided informed consent to have blood collected for our biorepository. Serum samples were collected at the time of colonoscopy; therefore, they were collected from all patients in a fasting state. Samples were then spun down and stored at −80 °C prior to shipment to the Targeted Metabolomics and Proteomics Facility at the University of Alabama at Birmingham. This facility performed untargeted metabolomic profiling of the serum samples. Serum samples underwent deproteinization, and the supernatant was collected for metabolomic analysis. Untargeted metabolomics analysis was performed utilizing UPLC-MS/MS and electrospray ionization quadrupole time of flight mass spectrometry (ESI Q-TOF MS). Metabolite identification was performed based on fragmentation patterns obtained through tandem mass spectrometry (MS/MS), which were compared to known databases and libraries for structural annotation. MetaboAnalyst 5.0 (74) was used for statistical evaluations after correcting for patient medications. Normalization was performed using row-wise normalization to a constant sum, with no data transformation, followed by Pareto scaling.
Statistical Analysis
Univariate analysis of the relationships between IBD phenotype and CKD development included chi-square tests and Student’s t-tests. Analyses were performed in R version 4.4.1,32 with case–control matching performed using the package “MatchIt.”33 P-values <.05 were considered to indicate significance.
Logistic regression models were utilized for multivariate analysis. Given the absence of ESRD, PSC, organ transplantation, and tacrolimus use in CD controls, these variables were not included in the logistic regression model. Additionally, data were missing on current aminosalicylate use and current steroid use; these variables were excluded from the model. Previous biologics use and type of biologic displayed multicollinearity and were therefore not included in the model. The final model included the following variables: Race, sex, ethnicity, age, age at diagnosis, smoking status, hypertension status, diabetes status, Montreal classification, history of kidney stones, previous aminosalicylate use, previous steroid use, previous immunomodulator use, current immunomodulator use, current biologic use, number of biologics previously used, and number of GI surgeries. Variables with the highest P-values were removed one by one to investigate the contribution of each variable to the model. Using this logistic regression model, we calculated the risk of developing CKD in CD patients with a given characteristic, which we report as odds ratios (ORs) and their 95% confidence intervals (CIs) below.
Finally, we examined whether distinct clusters of metabolites emerged using partial least square-discriminant (PLS-DA) analysis followed by principal component analysis (PCA). Then, we identified the key metabolites for this observed separation using variable importance in projection (VIP) analysis.
Results
Identification of Patients With IBD and CKD
The initial search in Epic of patients who visited the University of Miami Health System yielded 40 029 IBD patients (n = 23 679 with CD and n = 16 350 with UC) (Figure 1). Of these 40 029 patients, 1022 had kidney injury. A manual chart review revealed that 795 patients had acute kidney injury, eGFR < 60 mg/mmol for less than 3 months, or age <18 years; these patients were excluded. Of the remaining 227 IBD patients with kidney injury, 91 were excluded for having insufficient IBD phenotype information for the purposes of this study, that is, lacking data on Montreal classification (CD) or disease extent (UC). Among the 136 IBD + CKD patients remaining, we found that only 36 (26.5%) had UC, while 100 (73.5%) had CD. Given the small sample size of UC patients, we ultimately decided to exclude them from further analyses. Among the remaining 100 CD + CKD patients, we were unable to identify matching controls (matched by age, gender, and race) for 5 patients. These 5 patients were subsequently excluded, along with 8 patients who received a kidney transplant prior to CD diagnosis or for unrelated reasons. Therefore, a total of 87 CD + CKD patients were identified and included in the analysis, including 8 Black patients (9%). Each CD + CKD patient was matched to at least 1 CD patient without CKD (CD control) by age, race, and gender.
Demographic and Clinical Characteristics
The CD + CKD patients were 56.3% male and 43.7% female (Table 1). Most were White (90.8%), and approximately one-third of patients identified as Hispanic (29.9%). The median age was 67 years, and the age range was 18-91. Only 6.9% of our cohort were current tobacco smokers; more than half of the patients had never smoked. Diabetes and hypertension, which are major risk factors for the development of CKD,14 were common in our case cohort (found in 16.1% and 47.1% of patients, respectively). Among the included patients, 13 had end-stage renal disease and received kidney replacement therapy in the form of hemodialysis or peritoneal dialysis, and 3 had received a renal transplant after CD diagnosis.
Variable . | CD with CKD (n = 87) . | CD without CKD (n = 148) . |
---|---|---|
Gender | ||
Male | 49 (56.3) | 80 (54.1) |
Female | 38 (43.7) | 68 (45.9) |
Race | ||
White | 79 (90.8) | 136 (91.9) |
Black | 8 (9.2) | 12 (8.1) |
Ethnicity | ||
Hispanic | 26 (29.9) | 40 (27.0) |
Non-Hispanic | 61 (70.1) | 108 (73.) |
Age, mean (IQR) | 67 (18-91) | 66 (20-88) |
Smoking status | ||
Never smoker | 45 (51.7) | 79 (53.4) |
Former smoker | 36 (41.4) | 57 (38.5) |
Current smoker | 6 (6.9) | 12 (8.1) |
Hypertension | 41 (47.1) | 40 (27.0) |
Diabetes mellitus | 14 (16.1) | 15 (10.1) |
Primary sclerosing cholangitis | 3 (3.4) | 2 (1.4) |
End-stage renal disease | 13 (14.9) | 0 |
History of kidney stones | 30 (34.5) | 8 (5.4) |
History of transplant | 8 (9.2) | 0 |
Kidney | 3 (3.4) | 0 |
Liver | 4 (4.6) | 0 |
Bowel | 1 (1.1) | 0 |
Aminosalicylate use | ||
Previous | 48 (55.2) | 105 (70.9) |
Immunomodulator use | ||
Current | 15 (17.2) | 39 (26.4) |
Previous | 56 (64.4) | 79 (53.4) |
Biologics use | ||
Current | 47 (54.0) | 85 (57.4) |
Previous | 61 (70.1) | 107 (72.3) |
# of biologics used | ||
0 | 26 (29.9) | 41 (27.7) |
1 | 29 (33.3) | 56 (39.9) |
2 | 14 (16.1) | 25 (16.9) |
3+ | 18 (20.7) | 26 (17.5) |
Steroid use | ||
Previous | 80 (92.0) | 129 (87.2) |
History of IBD-related surgery | 67 (77.0) | 74 (50.0) |
# of IBD-related surgeries | ||
1 | 19 (21.8) | 43 (29.1) |
2 | 17 (19.5) | 20 (13.5) |
3+ | 31 (35.6) | 11 (7.4) |
Variable . | CD with CKD (n = 87) . | CD without CKD (n = 148) . |
---|---|---|
Gender | ||
Male | 49 (56.3) | 80 (54.1) |
Female | 38 (43.7) | 68 (45.9) |
Race | ||
White | 79 (90.8) | 136 (91.9) |
Black | 8 (9.2) | 12 (8.1) |
Ethnicity | ||
Hispanic | 26 (29.9) | 40 (27.0) |
Non-Hispanic | 61 (70.1) | 108 (73.) |
Age, mean (IQR) | 67 (18-91) | 66 (20-88) |
Smoking status | ||
Never smoker | 45 (51.7) | 79 (53.4) |
Former smoker | 36 (41.4) | 57 (38.5) |
Current smoker | 6 (6.9) | 12 (8.1) |
Hypertension | 41 (47.1) | 40 (27.0) |
Diabetes mellitus | 14 (16.1) | 15 (10.1) |
Primary sclerosing cholangitis | 3 (3.4) | 2 (1.4) |
End-stage renal disease | 13 (14.9) | 0 |
History of kidney stones | 30 (34.5) | 8 (5.4) |
History of transplant | 8 (9.2) | 0 |
Kidney | 3 (3.4) | 0 |
Liver | 4 (4.6) | 0 |
Bowel | 1 (1.1) | 0 |
Aminosalicylate use | ||
Previous | 48 (55.2) | 105 (70.9) |
Immunomodulator use | ||
Current | 15 (17.2) | 39 (26.4) |
Previous | 56 (64.4) | 79 (53.4) |
Biologics use | ||
Current | 47 (54.0) | 85 (57.4) |
Previous | 61 (70.1) | 107 (72.3) |
# of biologics used | ||
0 | 26 (29.9) | 41 (27.7) |
1 | 29 (33.3) | 56 (39.9) |
2 | 14 (16.1) | 25 (16.9) |
3+ | 18 (20.7) | 26 (17.5) |
Steroid use | ||
Previous | 80 (92.0) | 129 (87.2) |
History of IBD-related surgery | 67 (77.0) | 74 (50.0) |
# of IBD-related surgeries | ||
1 | 19 (21.8) | 43 (29.1) |
2 | 17 (19.5) | 20 (13.5) |
3+ | 31 (35.6) | 11 (7.4) |
Abbreviations: CD, Crohn’s disease; CKD, chronic kidney disease; IBD, inflammatory bowel disease; IQR, interquartile range.
Data are presented as count (percentage) unless otherwise specified.
Variable . | CD with CKD (n = 87) . | CD without CKD (n = 148) . |
---|---|---|
Gender | ||
Male | 49 (56.3) | 80 (54.1) |
Female | 38 (43.7) | 68 (45.9) |
Race | ||
White | 79 (90.8) | 136 (91.9) |
Black | 8 (9.2) | 12 (8.1) |
Ethnicity | ||
Hispanic | 26 (29.9) | 40 (27.0) |
Non-Hispanic | 61 (70.1) | 108 (73.) |
Age, mean (IQR) | 67 (18-91) | 66 (20-88) |
Smoking status | ||
Never smoker | 45 (51.7) | 79 (53.4) |
Former smoker | 36 (41.4) | 57 (38.5) |
Current smoker | 6 (6.9) | 12 (8.1) |
Hypertension | 41 (47.1) | 40 (27.0) |
Diabetes mellitus | 14 (16.1) | 15 (10.1) |
Primary sclerosing cholangitis | 3 (3.4) | 2 (1.4) |
End-stage renal disease | 13 (14.9) | 0 |
History of kidney stones | 30 (34.5) | 8 (5.4) |
History of transplant | 8 (9.2) | 0 |
Kidney | 3 (3.4) | 0 |
Liver | 4 (4.6) | 0 |
Bowel | 1 (1.1) | 0 |
Aminosalicylate use | ||
Previous | 48 (55.2) | 105 (70.9) |
Immunomodulator use | ||
Current | 15 (17.2) | 39 (26.4) |
Previous | 56 (64.4) | 79 (53.4) |
Biologics use | ||
Current | 47 (54.0) | 85 (57.4) |
Previous | 61 (70.1) | 107 (72.3) |
# of biologics used | ||
0 | 26 (29.9) | 41 (27.7) |
1 | 29 (33.3) | 56 (39.9) |
2 | 14 (16.1) | 25 (16.9) |
3+ | 18 (20.7) | 26 (17.5) |
Steroid use | ||
Previous | 80 (92.0) | 129 (87.2) |
History of IBD-related surgery | 67 (77.0) | 74 (50.0) |
# of IBD-related surgeries | ||
1 | 19 (21.8) | 43 (29.1) |
2 | 17 (19.5) | 20 (13.5) |
3+ | 31 (35.6) | 11 (7.4) |
Variable . | CD with CKD (n = 87) . | CD without CKD (n = 148) . |
---|---|---|
Gender | ||
Male | 49 (56.3) | 80 (54.1) |
Female | 38 (43.7) | 68 (45.9) |
Race | ||
White | 79 (90.8) | 136 (91.9) |
Black | 8 (9.2) | 12 (8.1) |
Ethnicity | ||
Hispanic | 26 (29.9) | 40 (27.0) |
Non-Hispanic | 61 (70.1) | 108 (73.) |
Age, mean (IQR) | 67 (18-91) | 66 (20-88) |
Smoking status | ||
Never smoker | 45 (51.7) | 79 (53.4) |
Former smoker | 36 (41.4) | 57 (38.5) |
Current smoker | 6 (6.9) | 12 (8.1) |
Hypertension | 41 (47.1) | 40 (27.0) |
Diabetes mellitus | 14 (16.1) | 15 (10.1) |
Primary sclerosing cholangitis | 3 (3.4) | 2 (1.4) |
End-stage renal disease | 13 (14.9) | 0 |
History of kidney stones | 30 (34.5) | 8 (5.4) |
History of transplant | 8 (9.2) | 0 |
Kidney | 3 (3.4) | 0 |
Liver | 4 (4.6) | 0 |
Bowel | 1 (1.1) | 0 |
Aminosalicylate use | ||
Previous | 48 (55.2) | 105 (70.9) |
Immunomodulator use | ||
Current | 15 (17.2) | 39 (26.4) |
Previous | 56 (64.4) | 79 (53.4) |
Biologics use | ||
Current | 47 (54.0) | 85 (57.4) |
Previous | 61 (70.1) | 107 (72.3) |
# of biologics used | ||
0 | 26 (29.9) | 41 (27.7) |
1 | 29 (33.3) | 56 (39.9) |
2 | 14 (16.1) | 25 (16.9) |
3+ | 18 (20.7) | 26 (17.5) |
Steroid use | ||
Previous | 80 (92.0) | 129 (87.2) |
History of IBD-related surgery | 67 (77.0) | 74 (50.0) |
# of IBD-related surgeries | ||
1 | 19 (21.8) | 43 (29.1) |
2 | 17 (19.5) | 20 (13.5) |
3+ | 31 (35.6) | 11 (7.4) |
Abbreviations: CD, Crohn’s disease; CKD, chronic kidney disease; IBD, inflammatory bowel disease; IQR, interquartile range.
Data are presented as count (percentage) unless otherwise specified.
Kidney Stones Increase the Risk of CKD in CD Patients
Given that we focused on the development of CKD in IBD patients, we first examined factors directly related to IBD that may predict CKD risk. IBD patients, especially those with CD, have an increased risk of kidney stones24 due to hyperoxaluria,34 hypocitraturia,34 lower urinary pH,34,35 and low urine volume.35 In our current cohort, 34.5% of CD + CKD patients had a history of kidney stones. In contrast, only 5.4% of CD controls had a history of kidney stones. Logistic regression analysis revealed that CD patients with kidney stones had approximately a 10-fold higher risk of developing CKD than those without kidney stones (OR = 10.08, 95% CI = [3.40, 33.61]) (Figure 2).

Patient flowchart. CD, Crohn’s disease; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; IBD, inflammatory bowel disease; UC, ulcerative colitis; UM, University of Miami.
Immunomodulator and Aminosalicylate Use Is Associated With a Lower Risk of Developing CKD in CD Patients, While Steroid Use Is Associated With Higher CKD Risk
The treatment history of IBD may also influence CKD risk. A variety of medications are used to treat IBD, and patients may be switched between drug classes. In our cohort, patients with previous aminosalicylate use had a 72% lower risk of developing CKD than those without previous use of aminosalicylates (OR = 0.28, 95% CI = [0.12, 0.63]).
Crohn’s disease patients currently taking immunomodulators had a 79% lower risk of developing CKD than those not on immunomodulators (OR = 0.21, 95% CI = [0.07, 0.56]). Previous use of immunomodulators was noted in more than 53% of both case and control cohorts; however, previous immunomodulator use did not predict CKD risk. Previous steroid use did not predict CKD risk either.
Biologic use was also common. We posited that more aggressive CD that resulted in CKD may be linked to more biologic use. Over 54% of CD + CKD cases and CD controls were currently using biologics, and previous use of biologics was recorded in more than 70% of both case and control cohorts. Current use of biologics, previous use of biologics, and the number of biologics previously received did not influence the risk of CKD.
Multiple IBD-Related Surgeries Increases the Risk of CKD
In addition to medication use, we asked whether IBD-related surgeries (eg, bowel resection) increased the risk of CKD. Among CD + CKD patients, 77% had undergone at least 1 IBD-related surgery, whereas 50% of CD controls had at least 1 IBD-related surgery. CD + CKD patients were also more likely to have undergone multiple surgeries. CD patients with 3 or more IBD-related surgeries had an approximately 7-fold higher risk of developing CKD than those who had not undergone such surgery (OR = 7.3, 95% CI = [1.89, 31.24]).
Metabolomic Profile of CD + CKD Patients
Given that both CKD and IBD are associated with specific changes in the gut microbiota and circulating metabolites,36,37 we asked whether CD + CKD patients have a distinct metabolomic profile in the sera compared to CD controls. Univariate analysis (using an FDR-adjusted P-value threshold of 0.1) revealed 7 metabolites that differed significantly between IBD patients with and without CKD (Figure 3A). PLS-DA followed by PCA showed that serum metabolites of CD + CKD patients clustered separately from the serum metabolites of CD patients without CKD (Figure 3B).

Risk of CKD in CD patients according to each characteristic. Red (darker) lines indicate significant associations of a variable with the presence or absence of CKD. CD, Crohn’s disease; CKD, chronic kidney disease;GI, gastrointestinal.
Variable importance in projection analysis was performed to reveal the key metabolites that contributed the most to the observed separation. Overall, metabolites associated with CKD and reduced eGFR suggested alterations in several pathways, such as amino acid metabolism and nucleotide metabolism, in CD + CKD patients. Among these metabolites, L-kynurenine, kynurenic acid, propionylcarnitine (PLC), N2,N2-dimethylguanosine, and 1-methyladenosine were markedly elevated in the sera of CD patients with CKD compared to those without CKD (Figure 3C). Interestingly, L-kynurenine and kynurenic acid are associated with the kynurenine pathway, which is the primary route for tryptophan catabolism in the liver.38 Propionylcarnitine is an acylcarnitine that is elevated in the blood of individuals with obesity and type 2 diabetes39; it has been recently linked to CKD.40 N2,N2-dimethylguanosine is a metabolite produced during RNA turnover and DNA damage.41 Alterations in its serum levels are associated with CKD.41 Finally, 1-methyladenosine is a uremic toxin and is associated with the progression of kidney disease and worsening renal function.42
Pathway analysis revealed significant enrichment in pathways such as tryptophan metabolism, branched-chain fatty acid oxidation, and beta-oxidation of very long-chain fatty acids in IBD + CKD patients compared to IBD controls (Figure 3D). These findings suggest that CKD exacerbates mitochondrial dysfunction,43 lipid dysregulation, and oxidative stress,44 compounding the inflammatory and metabolic burden already present in IBD. In contrast, pathways such as caffeine metabolism, homocysteine degradation, selenoamino acid metabolism, and glycine and serine metabolism were enriched in IBD controls compared to IBD + CKD patients (Figure 3E). This suggests that the absence of CKD allows for more efficient detoxification processes, amino acid metabolism, and oxidative stress regulation; these pathways are likely impaired in IBD + CKD patients due to kidney dysfunction and systemic metabolic disruption.
Disease signature analysis further underscored the distinct metabolic profile of IBD + CKD patients, with overlaps observed in conditions like colorectal cancer, celiac disease, mitochondrial disorders, and leukemia (Figure 3F). These enriched disease signatures point to heightened nucleotide turnover, oxidative stress, and systemic inflammation in IBD + CKD patients, revealing unique pathogenetic pathways. Taken together, these data suggest that the metabolic alterations in IBD + CKD patients not only reflect kidney dysfunction but also exacerbate systemic inflammation and potentially accelerate disease complications, distinguishing these patients from IBD patients without CKD.
Discussion
Renal complications in IBD are well documented. Most studies, however, have not provided the granularity to understand which specific IBD patients are at risk for this complication. We believe it is important for practitioners to identify the IBD patient phenotypes at heightened risk of developing CKD to inform prevention and treatment. In the present study, we found that patients with CD have a higher risk of developing CKD than patients with UC, similar to previous reports.45 Traditional risk factors for CKD, such as age >60, obesity, smoking, cardiovascular disease, hyperlipidemia, use of medications (eg, NSAIDs), race (eg, Black), and ethnicity (Hispanic),15,16 were more commonly observed in CD patients with CKD than in those without CKD. Moreover, we identified new risk factors for CKD development in CD patients: A history of kidney stones, multiple IBD-related surgeries, and the use of specific medications.
Inflammatory bowel disease patients may develop CKD due to dehydration, kidney stone formation, or bowel resections (especially of the small intestine). Urolithiasis is well documented in patients with IBD, especially CD. Inflammatory bowel disease patients with bowel resections are at an even higher risk of urolithiasis.46 Crohn’s disease patients, especially after an ileal resection, exhibit hyperoxaluria and low levels of calcium excretion, which predisposes them to urolithiasis formation.47 Beyond recommending adequate hydration in patients with IBD, practitioners should actively look for nephrolithiasis and attempt to mitigate its risk. In our initial Epic database search, we identified over 1000 patients with IBD and kidney disease. Even though most of these patients did not meet our strict criteria for CKD, this finding highlights potential opportunities to identify patients with acute kidney injury that may benefit from increased hydration. Moreover, urolithiasis due to calcium oxalate stones can be mitigated with a low-oxalate diet and daily calcium intake.48
Inflammatory bowel disease patients are also known to develop electrolyte imbalances and acute kidney injuries because of vomiting, diarrhea, or severe dehydration, especially in times of active flares. While Montreal classification and 1 bowel resection did not significantly predict subsequent CKD in our study, we found that CD patients who had undergone 3 or more surgeries had over 7 times higher odds of developing CKD than those who had not undergone surgery. This aligns with previous findings that the risks of acute kidney injury or kidney failure are elevated in IBD patients who undergo colectomy.49 Similar to the link between bowel resection and risk of urolithiasis, we suspect that the underlying pathophysiological factor leading from refractory CD to CKD is severe dehydration, poor ileal absorption, electrolyte imbalances, and frequent acute renal injury.50 Our metabolomic data support this possibility, as CD + CKD patients exhibited higher serum levels of metabolites associated with kidney injury and oxidative cell damage than CD patients without CKD.
The medications used to treat IBD and reduce inflammation represent potential mitigators of risk for CKD development in IBD patients. Of the commonly used IBD medications, we observed a 0.28-fold lower risk of CKD in patients with previous 5-aminosalicylic acid use, and no significant change in CKD risk in patients with biologic, immunomodulator, or steroid use. 5-aminosalicylic acid medications have the possibility—though rare—of inducing interstitial nephritis.26 We found a slight protective effect of these medications; however, most patients with CD should not be on 5-aminosalicylates given their lack of efficacy. This leads us to speculate that mesalamine use was likely associated with patients who had milder disease. While we did not find significant associations between biologic use and CKD risk, we believe that studies with larger sample sizes may find that patients on 2 or more biologics may be at higher risk of CKD since such medication use may indicate that these patients have refractory disease.
Among the CD patients with CKD, 8 patients had received organ transplants: liver (n = 4), kidney (n = 3), or bowel transplant (n = 1). Notably, we excluded any patients with renal transplants prior to their CD diagnosis or who received a renal transplant for reasons unrelated to CD (eg, polycystic renal disease). Thus, the remaining renal transplant patients required a kidney transplant secondary to complications of CD. The 1 patient who received a small bowel transplant had undergone multiple small bowel resections, a proctocolectomy, and multiple failures of biologics from different classes. The severity of this CD case and risk of chronic dehydration likely increased the patient’s risk of CKD. In liver transplant patients, the medical complications leading to a liver transplant and the use of calcineurin inhibitors may have contributed to renal insufficiency. Although this group is too small to permit subgroup analyses, this observation highlights that CD patients who have had liver transplants are also at risk of CKD.
Overall, we suggest that physicians should actively monitor CD patients with multiple gastrointestinal surgeries for subtle decreases in kidney function (reflected by a 25% decrease in the eGFR from baseline levels, according to the Risk, Injury, Failure, Loss, and End-Stage Kidney Disease [RIFLE] criteria51,52) as well as dehydration to index the risk of CKD. We highlight the recommendations of the Kidney Function Monitoring in Inflammatory Bowel Disease (MONITORED) initiative, which suggests that kidney function be monitored at IBD diagnosis and annually thereafter, with additional monitoring prior to starting a new medication.53 Kidney function thresholds of concern include a 30% change in serum creatine, albuminuria or proteinuria, specific eGFR thresholds according to age,53 an albumin-to-creatine ratio (ACR) = 30 mg/g, or persistent hematuria.17 Further decreases in kidney function (≥50% drop in the eGFR) during a flare or period of dehydration would constitute acute kidney injury; providers should monitor these patients to make sure that kidney function returns to baseline. Finally, we recommend more aggressive use of methods to mitigate the risk of kidney stones (changes in diet, dietary supplementations) in severe CD cases, as applicable, to prevent the development of CKD.
Metabolomic analysis revealed marked differences in the serum profiles of IBD + CKD patients compared to IBD patients without CKD, providing important insights into the metabolic interplay of these conditions. Elevated metabolites such as L-kynurenine and kynurenic acid highlight disruptions in tryptophan metabolism, potentially exacerbating oxidative stress and inflammation44—which are common drivers of both CKD and IBD.54,55 Similarly, elevated propionylcarnitine levels reflect altered fatty acid metabolism,56 linking systemic energy dysregulation to kidney dysfunction. Differences in metabolites such as N2,N2-dimethylguanosine and 1-methyladenosine, which are associated with nucleotide turnover and uremic toxin accumulation,57 suggest that CKD amplifies systemic metabolic disturbances already present in IBD. These findings point to key areas for further investigation, including the role of mitochondrial function and uremic toxin pathways in driving disease severity.
Pathway analysis reinforced these observations, with enrichment in pathways such as tryptophan metabolism, branched-chain fatty acid oxidation, and beta-oxidation of very long-chain fatty acids underscoring the presence of mitochondrial dysfunction and systemic inflammation.43,58 The clustering of IBD + CKD patients in multivariate analyses highlights the distinct metabolic phenotype associated with CKD comorbidity. Disease signature analysis further connects these metabolic disruptions to broader clinical implications, including overlaps with conditions such as colorectal cancer, celiac disease, and mitochondrial disorders. These parallels suggest that CKD exacerbates inflammatory and metabolic pathways in a way that may contribute to long-term complications in IBD patients. Taken together, these findings highlight a future in which monitoring specific metabolites in IBD patients can identify patients at risk of CKD development as well as potential therapeutic targets for prevention.
Our study has several limitations. First, although we matched cases (CD + CKD patients) and controls (CD controls) according to age and gender, IBD is a heterogeneous disease with highly variable manifestations. Future studies with stricter matching of cases to controls according to IBD phenotype (location, severity, etc.) may provide further insight into the causes underlying the development of CKD in this at-risk population. Second, it is unclear whether our findings regarding IBD-related medication use and CKD risk are due to the direct effect of these medications or represent underlying differences in IBD severity. Further research is needed to disentangle these effects. Regardless, healthcare providers may use these medications as a proxy when evaluating CKD risk. Third, not all patients provided urine samples. We did not include the availability of urine samples in our inclusion/exclusion criteria because it would have markedly reduced the sample size of our study. Therefore, we did not compare the urinary ACR of patients. Future studies should include urinalysis data to better characterize kidney function. Fourth, we lacked data on body mass index; higher BMI is a risk factor for CKD.15
Conclusions
Renal complications in IBD are well documented; however, stratification for CKD risk in IBD patients has yet to be achieved. We found that CD patients with kidney stones had a 10-fold higher risk of developing CKD than those without kidney stones. Additionally, CD patients with more than 2 IBD-related surgeries (eg, bowel resection) had a 7.3-fold higher risk of developing CKD than those who had not undergone surgery. Physicians may use these newly identified risk factors to predict the risk of CKD in CD patients, improving treatment and prevention efforts.
Serum metabolites are altered in IBD patients with CKD compared to those without CKD. (A) Univariate analysis of untargeted serum metabolomics data comparing IBD patients with CKD (n = 23) to IBD patients without CKD (n = 31). (B) Principal component analysis (PCA) of untargeted metabolites from the sera of IBD patients with CKD (n = 23) compared to those from the sera of IBD patients without CKD (n = 31). (C) Variable importance in projection (VIP) analysis of untargeted serum metabolites from IBD patients with CKD (n = 23) compared to those from IBD patients without CKD (n = 31). (D) Pathway enrichment analysis of untargeted serum metabolites showing enriched pathways in the sera of IBD patients with CKD (n = 23) compared to those without CKD (n = 31). (E) Pathway enrichment analysis of untargeted serum metabolites showing enriched pathways in the sera of IBD patients without CKD (n = 31) compared to IBD patients with CKD (n = 23). (F) Disease signature enrichment analysis of untargeted serum metabolites showing enriched disease signatures in the sera of IBD patients with CKD (n = 23) compared to those without CKD (n = 31). CD, Crohn’s disease; CKD, chronic kidney disease; IBD, inflammatory bowel disease.
Funding
No funding was received to support this research.
Conflicts of Interest
M.T.A. has received research funding from the National Institute of Health Research, DOD, and charities including The Leona M. and Harry B. Helmsley Charitable Trust and the Crohn’s and Colitis Foundation. She has served as a consultant or on the advisory board of the following companies: AbbVie Inc., Amgen Inc., Bristol Myers Squibb, Celsius Therapeutics, Eli Lilly and Company, Gilead Sciences Inc., Janssen Pharmaceuticals, and Pfizer Pharmaceutical. She has been a teacher, lecturer, or speaker at the following companies: Janssen Pharmaceuticals, and Takeda Pharmaceuticals. All other authors declare that they have no conflicts of interest.
Ethics Approval
This study was conducted at a tertiary referral center (University of Miami Health System) with approval from the University of Miami Institutional Review Board (approval numbers 20081100 and 20180765).