Abstract
Background
Serum albumin (ALB) may be low during acute inflammation, but it is also affected by nutritional status. Therefore, we hypothesized that ALB and the C-reactive protein/ALB ratio (CRP/ALB) may be associated with disease activity in patients with Crohn’s disease (CD).
Material/Methods
Altogether, 100 patients with CD and 100 age- and sex-matched healthy volunteers were retrospectively enrolled in the current study. The patients with CD were subdivided into patients with active disease (Crohn’s Disease Activity Index >150) and those in remission. ALB levels, CRP levels, and lipid profiles were measured.
Results
ALB and CRP levels and the CRP/ALB ratio were the most useful for differentiating between active and nonactive CD. ALB levels (r=−0.50, P<0.01), CRP levels (r=0.39, P<0.01), and CRP/ALB ratio (r=0.42, P<0.01) all correlated with CD activity. These correlations were more prominent in males. Receiver Operating Characteristic (ROC) analysis indicated that the area under the curve (AUC) representing ALB (0.79) was higher than the AUC representing CRP (0.73) or CRP/ALB ratio (0.75; P>0.05). The AUCs corresponding to ALB level, CRP level, and CRP/ALB ratio were more prominent in males versus females (P<0.05). CRP level (14.55 mg/L), ALB level (34.35 g/L), and CRP/ALB ratio (0.69) had sensitivities of 67.7%, 72.6%, and 59.7%, and specificities of 73.7%, 78.9%, and 81.6%, respectively, for CD activity.
Conclusions
In the present retrospective study, we found that ALB level and CRP/ALB ratio were useful biomarkers for identifying CD activity, especially in males. These results suggest that, in addition to inflammation, assessment of patient nutritional status could also aid in identifying CD activity.
MeSH Keywords: C-Reactive Protein, Crohn Disease, Nutritional Status
Background
The biomarkers for Crohn’s disease (CD) can help in disease activity monitoring in clinical practice. The biomarkers have been useful in diagnosing inflammatory bowel disease (IBD) and assessing disease activity [1]. However, compared with the current biomarkers, endoscopy has been the gold standard for assessing CD activity. In spite of the many studies focused on discovery of new biomarkers [2–5], the search for these special biomarkers to use for diagnosis instead of endoscopy has thus far been unsuccessful. Therefore, noninvasive and cost-effective biomarkers that function as endoscopy for CD activity are still lacking for clinical practice.
Fecal calprotectin is the best clinically noninvasive biomarker of disease activity in patients with CD; however, its use in clinical practice is limited by high cost and a long time [6]. In current clinical practice, the most commonly used noninvasive serum biomarker to assess CD activity is C-reactive protein (CRP). However, CRP levels are affected not only in IBD but also in other diseases, such as rheumatoid arthritis [7].
Albumin (ALB) can maintain colloid pressure and transport free fatty acids, bilirubin, and drug metabolites. Serum ALB may be low during acute inflammation, but it is also affected by nutritional status [8]. A low ALB level is most often linked with chronic disease, frequently correlated with nutritional status [9]. Meanwhile, ALB catabolism has been directly correlated with the severity of acute infection [10]. Carbonylated albumin is a member of the family of advanced oxidation protein products that has been shown to be involved in CD [11]. However, very few studies have assessed the usefulness of ALB in determining CD activity. Meanwhile, CRP/ALB ratio, a new inflammation-based prognostic score, has been demonstrated to show prognostic value in hepatocellular carcinoma, esophageal squamous cell carcinoma, and small cell lung cancer [12–15].
Therefore, we hypothesized that ALB and CRP/ALB ratio may be associated with disease activity in patients with CD.
Material and Methods
Ethical issues
This study was reviewed and approved by the Institutional Review Board (IRB) of the Second Affiliated Hospital of Zhejiang University School of Medicine (Ethics Review Code: Research 2014-113). With the approval of the IRB, we used the patient identification numbers to collect and analyze the clinical records. The personal information was made anonymous and deidentified before analysis.
Subjects
This retrospective, case-control study was approved by the Second Affiliated Hospital, School of Medicine, Zhejiang University. A retrospective analysis of electronic medical records collected at our institution from November 2013 to July 2015, on patients aged 15 to 82 years, was performed to identify those with CD. The diagnosis of CD was established according to the participants’ clinical history and to the endoscopic, radiologic, and histopathologic findings. For the patients who were followed in the CD program at the Second Affiliated Hospital, standardized, comprehensive disease-specific information was recorded at each visit. Subjects were randomly selected using the following exclusion criteria: concomitant infection (positive stool culture, positive blood culture, infiltrates on chest x-ray examination, documented skin infection), liver cirrhosis, malignancy, chemotherapy, lymphoma, autoimmune disease, or acquired or congenital immunodeficiency. In addition, 100 sex- and age-matched healthy subjects were enrolled in the study as a control group.
Data extraction
Data relating to patient age, sex, age at disease onset, age at diagnosis, disease course, smoking history, family history, signs and symptoms, appearance of fistulas, endoscopic and radiologic findings, medical treatment, and history of intestinal surgery were collected from the medical records. The prescription of immunomodulators (such as 6-mercaptopurine or azathioprine), steroids, and biologics such as infliximab was also recorded. Patient disease activity was determined based on Crohn’s Disease Activity Index (CDAI). Laboratory examinations of the CD group and control group included measurements of ALB, lipid profiles and CRP levels. CD group members with CDAI scores >150 were considered to have active disease [16].
Statistical analysis
All statistical analyses were performed using SPSS 20 software. Data were expressed either as the mean plus or minus standard deviation (±SD) or as geometrical means (95% CI) for continuous variables and as percentages for categorical variables. CRP and lipid levels were analyzed after log-transformation due to a skewed distribution. General characteristics were compared separately among participants with and without CD using the t test. Categorical variables were analyzed via the chi-square test. Spearman correlation coefficients were used to study the relationships among CRP levels, ALB levels, CRP/ALB ratio, and CD activity. To assess the utility of CRP levels, ALB levels, and CRP/ALB ratio as biomarkers for discriminating active versus remitted patients with CD, as well as patients with CD from non-CD controls, we constructed sex-specific Receiver Operating Characteristic (ROC) curves and compared the areas under the ROC curves (AUCs) using the Z-statistic. P<0.05 was considered statistically significant.
Results
Clinical and laboratory characteristics of the CD and control groups
During November 2013 to July 2015, a total of 109 patients with CD were identified, of whom 9 patients did not meet the inclusion criteria. A total of 100 patients with CD were enrolled in the study, including 57 males and 43 females. There were 62 patients with active CD and 38 patients in remission. There were no significant differences in sex or age between the CD group and the control group (P>0.05). In comparing the CD group with the control group, significant differences were found in CRP/ALB ratio and CRP, total protein, ALB, and lipid levels, as shown in Table 1. In comparing patients with active CD with patients in remission, significant differences were found in CRP and ALB levels, CRP/ALB ratio, and body mass index (BMI) as shown in Table 2.
Table 1.
Clinical and biochemical characteristics in CD group and control group.
| CD group (n=100) | Control group (n=100) | P value | |
|---|---|---|---|
| Age (years) | 33.06±12.87 | 35.43±9.75 | 0.144 |
| Smoking (Yes/No) | 21/79 | 28/72 | 0.25 |
| BMI kg/m2 | 18.65±3.02 | 22.62±4.59 | <0.001 |
| FPG mmol/L | 4.43±0.57 | 5.11±0.81 | <0.001 |
| TC mmol/L | 3.56±0.91 | 4.65±0.72 | <0.001 |
| TG mmol/L | 1.11±0.44 | 1.32±0.53 | <0.001 |
| ApoAI g/L | 1.02±0.18 | 1.42±0.18 | <0.001 |
| ApoB g/L | 0.74±0.21 | 0.95±0.21 | <0.001 |
| HDL-C mmol/L | 0.96±0.23 | 1.49±0.32 | <0.001 |
| LDL-c mmol/L | 1.99±0.66 | 2.80±0.57 | <0.001 |
| CR μmol/L | 57.35±16.72 | 66.46±14.19 | <0.001 |
| BUN mmol/L | 3.98±1.73 | 5.07±1.20 | <0.001 |
| CRP mg/L | 24.50±25.92 | 4.91±3.21 | <0.001 |
| ALB g/L | 34.29±5.90 | 47.76±3.25 | <0.001 |
| TP g/L | 61.90±8.57 | 73.60±4.31 | <0.001 |
| ALT U/L | 13.40±10.66 | 21.57±13.77 | <0.001 |
| AST U/L | 17.68±6.98 | 21.90±9.51 | <0.001 |
| CRP/ALB | 0.79±0.88 | 0.10±0.07 | <0.001 |
BMI – body mass index; FPG – fasting plasma glucose; TC – total cholesterol; TG – triglycerides; ApoAI – apolipoprotein AI; ApoB – apolipoprotein B; HDL-C – high density lipoprotein cholesterol; LDL-C – low density lipoprotein cholesterol; CR – creatinine; BUN – blood urea nitrogen; CRP – C-reactive protein; ALB – albumin; TP – total protein; ALT – alanine aminotransferase; AST – aspartate aminotransferase.
Table 2.
The difference between active and remission.
| Active (n=62) | Remission (n=38) | t/χ2 | P value | |
|---|---|---|---|---|
| Age (years) | 33.01±12.43 | 33.13±13.73 | 0.04 | 0.966 |
| Smoking (Yes/No) | 13/49 | 8/30 | 0.01 | 0.992 |
| BMI kg/m2 | 17.63±2.42 | 20.32±3.17 | 4.78 | <0.001 |
| FPG mmol/L | 4.36±0.57 | 4.53±0.57 | 1.49 | 0.138 |
| TC mmol/L | 3.40±0.78 | 3.83±1.05 | 2.37 | 0.019 |
| TG mmol/L | 1.06±0.35 | 1.21±0.55 | 1.55 | 0.125 |
| ApoAI g/L | 0.99±0.17 | 1.09±0.19 | 2.75 | 0.007 |
| ApoB g/L | 0.74±0.22 | 0.75±0.21 | 0.26 | 0.797 |
| HDL-C mmol/L | 0.93±0.22 | 1.01±0.23 | 1.77 | 0.080 |
| LDL-c mmol/L | 1.87±0.54 | 2.19±0.78 | 2.48 | 0.015 |
| CR μmol/L | 54.64±18.26 | 61.76±12.87 | 2.1 | 0.038 |
| BUN mmol/L | 3.75±1.90 | 4.36±1.33 | 1.73 | 0.086 |
| CRP mg/L | 31.58±28.26 | 12.96±16.14 | 4.19 | <0.001 |
| ALB g/L | 32.00±4.94 | 38.02±5.46 | 5.67 | <0.001 |
| TP g/L | 60.76±8.58 | 63.76±8.32 | 1.72 | 0.089 |
| ALT U/L | 12.42±10.89 | 15.00±10.20 | 1.18 | 0.242 |
| AST U/L | 17.23±7.94 | 18.42±5.05 | 0.83 | 0.409 |
| CRP/ALB | 1.03±0.98 | 0.38±0.49 | 4.42 | <0.001 |
BMI – body mass index; FPG – fasting plasma glucose; TC – total cholesterol; TG – triglycerides; ApoAI – apolipoprotein AI; ApoB – apolipoprotein B; HDL-C – high density lipoprotein cholesterol; LDL-C – low density lipoprotein cholesterol; CR – creatinine; BUN – blood urea nitrogen; CRP – C-reactive protein; ALB – albumin; TP – total protein; ALT – alanine aminotransferase; AST – aspartate aminotransferase.
Association between serum biomarkers and CD activity
Spearman correlations between serum biomarkers and CD activity are shown in Table 3. ALB levels (r=−0.50, P<0.01), CRP levels (r=0.39, P<0.01), and CRP/ALB ratio (r=0.42, P<0.01) all correlated with CD activity. Additionally, CRP/ALB ratio and CRP and ALB levels had higher correlations to CD activity in males versus females. The same results were found after adjusting for age and BMI, as shown in Table 3.
Table 3.
Spearman correlations between risk factors and CD activity.
| Correlation coefficient | Correlation coefficient after adjusting for age and BMI | |||||
|---|---|---|---|---|---|---|
| Total | Male | Female | Total | Male | Female | |
| Age (years) | 0.02 | 0.08 | −0.14 | / | / | / |
| Sex | 0.18 | / | / | 0.12 | / | / |
| BMI kg/m2 | 0.41* | −0.4* | −0.42* | / | / | / |
| Smoking (Yes/No) | −0.01 | 0.12 | / | 0.09 | 0.15 | / |
| FPS mmol/L | −0.13 | −0.16 | −0.13 | −0.09 | −0.18 | 0.11 |
| TC mmol/L | −0.22* | −0.4* | −0.02 | −0.17 | −0.29* | 0.01 |
| TG mmol/L | −0.08 | −0.19 | 0.03 | −0.07 | −0.15 | 0.06 |
| ApoA g/L | −0.24* | −0.32* | −0.18 | −0.22* | −0.25 | −0.24 |
| ApoB g/L | −0.04 | −0.12 | −0.03 | 0.05 | 0.03 | 0.05 |
| HDL-C mmol/L | −0.20* | −0.28* | −0.13 | −0.16 | −0.19 | −0.11 |
| LDL-c mmol/L | −0.26* | −0.44* | −0.09 | −0.15 | −0.26 | −0.01 |
| CR μmol/L | 0.29* | −0.21 | −0.33* | −0.11 | −0.08 | −0.05 |
| BUN mmol/L | −0.27* | −0.22 | −0.27 | −0.11 | −0.15 | −0.30 |
| CRP mg/L | 0.39* | 0.53* | 0.22 | 0.29* | 0.32* | 0.25 |
| ALB g/L | −0.50* | −0.64* | −0.23* | −0.39* | −0.52* | −0.19 |
| TP g/L | −0.15* | −0.31* | 0.07 | −0.14 | −0.30* | −0.02 |
| ALT U/L | −0.27* | −0.20 | −0.25 | 0.02 | 0.05 | 0.02 |
| AST U/L | −0.22* | −0.15 | −0.24 | 0.01 | 0.01 | 0.04 |
| CRP/ALB | 0.42* | 0.55* | 0.23 | 0.29* | 0.34* | 0.23 |
BMI – body mass index; FPG – fasting plasma glucose; TC – total cholesterol; TG – triglycerides; ApoAI – apolipoprotein AI; ApoB – apolipoprotein B; HDL-C – high density lipoprotein cholesterol; LDL-C – low density lipoprotein cholesterol; CR – creatinine; BUN – blood urea nitrogen; CRP – C-reactive protein; ALB – albumin; TP – total protein; ALT – alanine aminotransferase; AST – aspartate aminotransferase;
P<0.05.
Diagnostic values of the biomarkers in CD activity
To compare the predictive values of CRP and ALB levels, as well as the CRP/ALB ratio, for CD activity, we analyzed ROC curves. The AUCs corresponding to the serum biomarkers are shown in Table 4. Figures 1–3 depict the discriminatory values of CRP and ALB levels and the CRP/ALB ratio relative to CD activity. ROC analysis using the Z-statistic indicated that the AUC of ALB (0.79) was higher than that of CRP (0.73) and the CRP/ALB ratio (0.75) in CD (P>0.05). Based on the Z-statistic, the AUC of ALB was higher than that of CRP and CRP/ALB in both males and females (P>0.05). Based on the Z-statistic, we also found that the AUC of ALB was higher in males (0.87) than in females (0.65; P<0.05), the AUC of CRP was higher in males (0.81) than in females (0.64; P<0.05), and the AUC of CRP/ALB was higher in males (0.82) than in females (0.65; P<0.05). The cutoff values, sensitivities, and specificities of ALB and CRP levels and the CRP/ALB ratio for detecting CD activity are shown in Table 5.
Table 4.
Discriminatory power of CRP, BMI and ALB for CD activity by Receiver Operating Characteristic (ROC) curves in CD group, male and female.
| Total (AUC) | Male (AUC) | Female (AUC) | |
|---|---|---|---|
| Smoking (Yes/No) | 0.50 | 0.56 | 0.50 |
| BMI kg/m2 | 0.74* | 0.73* | 0.77* |
| GLU mmol/L | 0.58 | 0.59 | 0.58 |
| TC mmol/L | 0.63* | 0.73* | 0.51 |
| TG mmol/L | 0.55 | 0.61 | 0.52 |
| ApoA g/L | 0.64 | 0.68 | 0.62 |
| ApoB g/L | 0.52 | 0.57 | 0.52 |
| HDL-C mmol/L | 0.62* | 0.66* | 0.58 |
| LDL-c mmol/L | 0.65* | 0.76* | 0.56 |
| CR μmol/L | 0.67* | 0.62 | 0.71* |
| BUN mmol/L | 0.66* | 0.63 | 0.67 |
| CRP mg/L | 0.73* | 0.81* | 0.64 |
| ALB g/L | 0.79* | 0.87* | 0.65 |
| TP g/L | 0.59 | 0.68* | 0.54 |
| CRP/ALB | 0.75* | 0.82* | 0.65 |
AUC – area under the curve; BMI – body mass index; FPG – fasting plasma glucose; TC – total cholesterol; TG – triglycerides; ApoAI – apolipoprotein AI; ApoB – apolipoprotein B; HDL-C – high density lipoprotein cholesterol; LDL-C – low density lipoprotein cholesterol; CR – creatinine; BUN – blood urea nitrogen; CRP – C-reactive protein; ALB – albumin; TP – total protein;
P<0.05.
Figure 1.
Discriminatory power of ALB, CRP, and CRP/ALB for CD activity by ROC curves in patients with CD. ALB – albumin; CD – Crohn’s disease; CRP – C-reactive protein; ROC – Receiver Operating Characteristic.
Figure 2.
Discriminatory power of ALB, CRP, and CRP/ALB for CD activity by ROC curves in males. ALB – albumin; CD – Crohn’s disease; CRP – C-reactive protein; ROC – Receiver Operating Characteristic.
Figure 3.
Discriminatory power of ALB, CRP, and CRP/ALB for CD activity by ROC curves in females. ALB – albumin; CD – Crohn’s disease; CRP – C-reactive protein; ROC – Receiver Operating Characteristic.
Table 5.
The sensitivty and specifity for detecting CD activity.
| Cutoff-value | Sensitivity | Specificity | |
|---|---|---|---|
| CRP mg/L | 14.55 | 67.7% | 73.7% |
| ALB g/L | 34.35 | 72.6% | 78.9% |
| CRP/ALB | 0.69 | 59.7% | 81.6% |
CRP – C-reactive protein; ALB – albumin.
Discussion
In the current study, we found that CRP levels and the CRP/ALB ratio increased and ALB levels significantly decreased in subjects with active versus remitted CD. ALB had a higher correlation with active CD (r=−0.50) than either CRP (r=0.39) or CRP/ALB (r=0.42), especially in males. ROC analysis indicated that the AUC of ALB (0.79) was higher than the AUCs of CRP (0.73) and of CRP/ALB (0.75; P>0.05). Decreased ALB values were more indicative of active CD than the other evaluated biomarkers.
In this study, we found that sex-based differences existed in protein metabolism in active CD. ALB, CRP, and CRP/ALB all had a higher correlation with CD activity in males. Meanwhile, they were also more prominent in estimating CD activity in males versus females. Previous epidemiologic studies have showed that differences exist between the sexes about the incidence and severity of IBD and the mortality of patients with IBD [17]. One study showed that estradiol in ovariectomized mice could ameliorate the severity of colitis [17]. Sankaran-Walters showed that women had higher levels of immune activation and inflammation-associated gene expression in gut mucosal samples, which indicated that women were vulnerable to CD [18]. We think that estrogens may play an important role in sex-based differences. However, several studies have reported no sex-based differences with respect to patient symptoms or extraintestinal manifestations [19], risk of intestinal resection surgery [20], or medication use [21].
ALB is involved in metabolism in patients with CD. In the current study, we found that ALB was more helpful in detecting CD activity than CRP, especially in males. Previous research shows that inflammatory response had an effect on ALB synthesis [22]. Nutrition-related factors have emerged as environmental triggers for the development and modification of lifestyle-related chronic diseases, including IBD [23]. Therefore, assessment of CD patient nutritional status could also help in the identification of CD activity.
The CRP/ALB ratio was first reported to identify patients with serious illness on an acute medical ward [24]. More recently, the CRP/ALB ratio had been demonstrated to show outstanding prognostic value in cancers [12,13]. In our study, we found the extent of ALB decline to be inversely correlated to the degree of CRP increase, and the CRP/ALB ratio had a an AUC (0.75) higher than that of CRP (P>0.05). The results indicated that the CRP/ALB ratio, integrating the effects of both inflammation and malnutrition, was a novel and promising inflammation-based biomarker for CD activity.
There were several important limitations in the current study. The number of enrolled CD subjects was small; therefore, the observed effects may not be applicable to the general population. As this was a retrospective study, medication history, disease history, surgical history, diabetes duration, and possible medication intolerances may be additional limiting factors when extrapolating the present findings to the general population. Given the retrospective nature of our study, some of the enrolled patients did not undergo small bowel endoscopy. The simple endoscopic score for Crohn’s disease (SES-CD) has proven more useful than CDAI. Therefore, we hope to assess the value of ALB level and CRP/ALB ratio in comparison with SES-CD in the future. Despite these limitations, ALB level and the CRP/ALB ratio could be useful in predicting CD activity.
Conclusions
In the current retrospective study, we found that ALB level and the CRP/ALB ratio were useful biomarkers for identifying CD activity, especially in males. These results suggest that, in addition to inflammation, assessment of patient nutritional status could also aid in identifying CD activity.
Footnotes
Disclosures: The authors have no conflicts of interest to declare regarding the publication of this manuscript.
Source of support: This research project was supported by grants from the National Health Key Special Fund (No. 200802112), Health Department Fund (Nos. 2007A093, 201343550), Traditional Chinese Medicine Bureau Fund (No. 2007ZA019), Natural Science Fund of Zhejiang Province (Nos.Y2080001, Y12H160121, LY13H200001), Key Project of Zhejiang Province (Nos. 2009C03012-5, 2013C03044-5), and National Natural Science Foundation of China (general project No. 81372302)
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