Published online Apr 14, 2021. doi: 10.3748/wjg.v27.i14.1483
Peer-review started: September 18, 2020
First decision: November 3, 2020
Revised: November 17, 2020
Accepted: February 25, 2021
Article in press: February 25, 2021
Published online: April 14, 2021
Processing time: 202 Days and 23.7 Hours
It has been suggested that apolipoprotein E (APOE) polymorphisms are associated with the risk of developing inflammatory bowel disease (IBD) and the early age of disease onset. However, there are no reports regarding the relationship with clinical characteristics and disease severity.
To summarise that APOE polymorphisms are associated with the risk of developing IBD and the early age of disease onset.
In total, 406 patients aged 3-18 with IBD (192 had ulcerative colitis and 214 had Crohn’s disease) were genotyped using the TaqMan hydrolysis probe assay. Clinical expression was described at diagnosis and the worst flare by disease activity scales, albumin and C-reactive protein levels, localisation and behaviour (Paris classification). Systemic steroid intake with the total number of courses, immunosuppressive, biological, and surgical treatment with the time and age of the first intervention were determined. The total number of exacerbation-caused hospitalisations, the number of days spent in hospital due to exacerbation, the number of relapses, and severe relapses were also estimated.
Ulcerative colitis patients with the APOEε4 allele had lower C-reactive protein values at diagnosis (P = 0.0435) and the worst flare (P = 0.0013) compared to patients with the APOEε2 allele and genotype APOEε3/ε3. Crohn’s disease patients with the APOEε2 allele scored lower on the Pediatric Crohn’s Disease Activity Index at diagnosis (P = 0.0204). IBD patients with APOEε2 allele spent fewer days in the hospital due to relapse (P = 0.0440).
APOE polymorphisms are associated with the risk of developing IBD and the clinical expression of IBD. However, the clinical relevance of the differences identified is rather modest.
Core Tip: Apolipoprotein E polymorphisms are associated with the risk of developing inflammatory bowel disease and seem to be associated with the disease expression and treatment. However, the clinical relevance of the differences is relatively modest.
- Citation: Glapa-Nowak A, Szczepanik M, Iwańczak B, Kwiecień J, Szaflarska-Popławska AB, Grzybowska-Chlebowczyk U, Osiecki M, Dziekiewicz M, Stawarski A, Kierkuś J, Banasiewicz T, Banaszkiewicz A, Walkowiak J. Apolipoprotein E variants correlate with the clinical presentation of paediatric inflammatory bowel disease: A cross-sectional study. World J Gastroenterol 2021; 27(14): 1483-1496
- URL: https://www.wjgnet.com/1007-9327/full/v27/i14/1483.htm
- DOI: https://dx.doi.org/10.3748/wjg.v27.i14.1483
Heritability and disease risk can only be partly explained by genetic factors alone[1-4]. Inflammatory bowel disease (IBD) has a strong genetic makeup. To date, 240 risk gene loci have been associated with the disease[1]. Several genetic variations are linked to specific IBD phenotypes. For instance, NOD2, IRGM, ATG16L1, and NCF4/NCF2 are related to segmental, structuring, or early-onset disease[5-10]. Genetic testing for these and other variants may prove useful in predicting the disease course for future clinical use.
One of the well-known genetic determinants of some diseases other than IBD is apolipoprotein E (APOE), most commonly known for its role in Alzheimer’s disease[11]. Although first recognised for its role in lipoprotein metabolism, APOE is involved in several biological processes not directly related to lipid transport function[12]. Importantly, APOE is a key player in immunoregulation[13-15] and associated with autoimmune disorders such as multiple sclerosis, rheumatoid arthritis, and psoriasis[16-18]. It has been reported that APOE has several immune-related functions such as suppressing T-cell proliferation[19-21], possibly by downregulating DNA synthesis and reducing phospholipid turnover in T cells[22-24], neutrophil activation[25], and modulation of macrophage assisted[26-28] antigen presentation[14,15].
APOE is a polymorphic protein present in three major isoforms that differ only by two single amino acid substitutions, APOEε4 (arg112, arg158), APOEε3 (cys112, arg158), and APOEε2 (cys112, cys158). The amino acid replacement causes profound functional changes at the cellular and molecular level as well as in the immune system. APOE suppresses the production of proinflammatory cytokines such as tumour necrosis factor-α in microglia in an isoform-dependent manner (ε2 > ε3 > ε4)[29]. In turn, inflammatory cytokines can promote APOE synthesis and release or downregulate the production of APOE in different tissues[30,31]. However, interactions between APOE and cytokines are occasionally conflicting, highlighting the complex roles of APOE and cytokines in various disorders[15].
In IBD, inflammation alters lipid, apolipoprotein, and lipoprotein profiles in subjects with active disease[32,33] and patients with limited response to infliximab[34]. A previous study from Saudi Arabia showed that the genetic distribution of APOE polymorphisms in IBD seems to be altered compared to healthy subjects[35]. The study also suggested that the ε4 allele increased the risk of IBD and was associated with an early onset of the disease. Similarly, APOEε4 has been associated with severity in another immunologic disorder: rheumatoid arthritis[16]. For these reasons, this study aimed to investigate the relationship between APOE variants with disease severity in IBD.
Patients recruited to the study belonged to the Polish Paediatric Crohn’s and Colitis cohort and involved 406 paediatric IBD patients: 214 with Crohn’s disease (CD; 86 females, 128 males) and 192 with ulcerative colitis (UC; 87 females, 105 males) (Table 1). Patients were recruited in the course of hospital treatment or during scheduled visits at outpatient clinics (Department of Pediatric Gastroenterology and Metabolic Diseases, Poznań University of Medical Sciences; The Department of Gastroenterology, Hepatology, Feeding Disorders and Paediatrics; The Children’s Memorial Health Institute, Warsaw; Department of Pediatric Gastroenterology and Nutrition, Medical University of Warsaw; Department and Clinic of Pediatrics, Gastroenterology and Nutrition, Wroclaw Medical University; Department of Pediatrics, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Katowice; Department of Pediatrics, Faculty of Medical Sciences, Medical University of Silesia in Katowice and Department of Pediatric Endoscopy and Gastrointestinal Function Testing, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Bydgoszcz, Poland). The diagnosis of IBD was confirmed by experienced gastroenterologists using standard diagnostic criteria[36,37]. The inclusion criteria were a diagnosis of CD or UC and aged 3-18. Patients in life-threatening, severe general condition were excluded from the study. The study obtained the approval of the Bioethical Committee at Poznań University of Medical Sciences (960/15 with the associated amendments).
Variables median (IQR) or n (%) | n | Crohn’s disease | Ulcerative colitis | P value |
Age in yr | ||||
At inclusion | 397 | 15.18 (13.32-17.05) | 15.11 (11.70-16.75) | 0.044 |
At diagnosis | 404 | 12.58 (10.02-14.32) | 12.14 (7.89-14.94) | 0.365 |
At worst flare | 355 | 13.63 (11.54-15.85) | 13.76 (10.13-15.84) | 0.244 |
Duration of the disease (yr) | 390 | 2.23 (0.82-4.25) | 1.88 (0.36-3.77) | 0.239 |
Female | 173 | 86 (40.2) | 87 (45.3) | 0.297 |
Nutritional status | ||||
Weight at diagnosis in kg | 387 | 38.0 (27.0-49.8) | 40.0 (27.8-53.9) | 0.490 |
Weight at diagnosis, z score | 383 | -0.82 [(-1.39)-(-0.04)] | -0.51 [(-1.12)-0.22] | 0.003 |
Height at diagnosis in cm | 382 | 151.0 (137.0-164.5) | 152.0 (130.5-168.3) | 0.718 |
Height at diagnosis, z score | 378 | -0.37 [(-1.29)-0.47] | 0.06 [(-0.67)-0.81] | 0.001 |
Body mass index at diagnosis in kg/m2 | 382 | 16.6 (14.5-18.4) | 17.4 (15.5-19.3) | 0.019 |
Body mass index at diagnosis, z score | 378 | -0.79 [(-1.47)-(-0.04)] | -0.49 [(-1.00)-0.16] | 0.006 |
Albumin level at diagnosis in g/dL | 345 | 3.90 (3.51-4.25) | 4.10 (3.70-4.40) | < 0.003 |
Parameter of inflammation | ||||
CRP at diagnosis in mg/L1 | 386 | 12.94 (2.10-29.25) | 2.24 (0.50-10.80) | < 0.001 |
CRP at worst flare in mg/L | 347 | 13.95 (3.03-32.43) | 2.70 (0.63-13.44) | < 0.001 |
Disease activity scales | ||||
PCDAI/PUCAI at diagnosis | 190/166 | 32 (23-48) | 45 (28-60) | |
PCDAI/PUCAI at worst flare | 170/155 | 40 (30-53) | 50 (35-65) | |
Treatment | ||||
Systemic steroids2 | 406 | 115 (53.7) | 138 (71.9) | < 0.001 |
Immunosuppressive treatment3 | 405 | 168 (78.5) | 112 (58.6) | < 0.001 |
Biological therapy4 | 406 | 107 (50.0) | 49 (25.5) | < 0.001 |
Operative treatment5 | 406 | 29 (13.6) | 4 (2.1) | < 0.001 |
Disease activity was assessed using appropriate scales at diagnosis and the worst flare [Pediatric Ulcerative Colitis Activity Index and Pediatric Crohn’s Disease Activity Index (PCDAI)][38], which was defined by the highest Pediatric Ulcerative Colitis Activity Index and PCDAI scales in their medical history. Albumin (g/dL) and C-reactive protein (CRP; mg/L) concentrations at diagnosis and the worst flare were obtained from medical records (CRP reference range 0-5 mg/L). The treatment domain included data regarding systemic steroid intake with the total number of courses, immunosuppressive treatment with the time and age of the first intake, biological therapy with time and age of first admission, and operative treatment with time and age of first surgery. The localisation and behaviour of the disease were defined by the Paris Classification at the diagnosis and worst flare[39]. Most CD patients presented with an ileocolonic location and nonstricturing behaviour of the disease (Supplementary Table 1), while most UC patients presented with pancolitis and were never severe (S0: > 65 on the Pediatric Ulcerative Colitis Activity Index scale; Supplementary Table 2). Based on medical records, the total number of exacerbation hospitalisations, the number of days spent in hospital due to exacerbation, the number of relapses, and severe relapses from diagnosis were estimated and calculated per year of the disease duration. The associated extraintestinal symptoms and concomitant diseases were collected from the medical history.
DNA was isolated from whole blood using the Blood Mini (A and A Biotechnology). A hydrolysis probe assay (TaqMan assay) was used with the following probes, C_904973_10 and C_3084793_20, to genotype patients (Life Technologies Corp. Carlsbad. California, United States). The genotyping was performed on the CFX-96 thermocycler system with allele discrimination plots provided by CFX Manager Software (Bio-Rad, Hercules, CA, United States).
Differences in categorical variables were compared with two-tailed Fisher’s exact test. Differences in continuous variables were evaluated by the Mann Whitney U test and Kruskal-Wallis test. Post hoc comparisons were performed with Dunn’s test, and the significance level for the time-to-treatment analysis was evaluated by Gehan’s test. The explanatory factor analysis was used to analyse the underlying factors in the questionnaire. The significance level was set at P < 0.05, and statistical analyses were performed using Statistica 13.1 software (StatSoft Inc, Tulsa, OK, United States), JASP 0.10.2 (University of Amsterdam, Amsterdam, the Netherlands), and G*Power (Dusseldorf University, Germany). Comparisons between groups with less than ten patients were not included.
The most prevalent genotype in UC and CD was APOEε3/ε3 (Table 2). No differences in the distribution of alleles and genotypes between UC and CD were documented.
Genotype/allele | UC, n = 192 | CD, n = 214 | P value, two-tailed Fisher exact | Odds ratio (95%CI) |
ε3/ε3 | 118 | 135 | 0.7590 | 0.93 (0.62-1.40) |
ε3/ε4 | 47 | 41 | 0.2278 | 1.37 (0.85-2.20) |
ε2/ε3 | 18 | 35 | 0.0397 | 0.53 (0.29-0.97) |
ε3+ | 183 | 211 | 0.0757 | 0.29 (0.08-1.08) |
ε4+ | 54 | 43 | 0.0629 | 1.56 (0.98-2.46) |
ε2+ | 24 | 37 | 0.2108 | 0.68 (0.39-1.19) |
The distribution of the APOE genotypes was compared to previous studies in the Polish population (Supplementary Table 3). Pooling available data[40-42] to obtain a similar sample size (n = 425) showed a significantly lower frequency of APOEε3/ε3 genotype in IBD patients compared to controls (62.3% vs 71.5%; P = 0.0051; odds ratio = 0.66; 95% confidence interval: 0.49-0.88) and simultaneously higher frequency of APOEε3/ε4 genotype (21.7% vs 15.1%; P = 0.0153; odds ratio = 1.56; 95% confidence interval: 1.09-2.23) with no difference in other genotypes or for the APOEε3 allele (P = 0.8625). However, in the study of Bojar et al[43] (postmenopausal women; n = 402), the distribution of APOEε3/ε3 genotype was similar to the present study (62.9% vs 62.3%; P = 0.8555; odds ratio = 0.97; 95% confidence interval: 0.73-1.30).
UC patients with APOEε3ε3 had higher CRP values, and the APOEε2/ε3 genotype were predisposed to left-sided colitis (E2) at diagnosis (Table 3). Concomitant diseases in CD patients occurred at different frequencies in major APOE genotypes, and children with APOEε2ε3 genotype had significantly lower PCDAI scores at diagnosis than patients with the remaining genotypes (Table 4). UC patients with the APOEε4 allele had significantly lower CRP levels than the patients with APOEε3ε3 genotype and APOEε2-positive, both at diagnosis and at the worst flare (Table 5). There were also differences in age at first biological treatment. Additionally, APOEε2-positive patients with IBD spent significantly fewer days in the hospital due to relapse per year of disease duration than APOEε4-positive patients and with the APOEε3/ε3 genotype (Table 5). Patients with CD and APOEε3ε3 genotype had lower values of standardised body height at diagnosis (Table 5). No difference was observed in the frequency of systemic steroids, immunosuppressive, and biological treatment between APOE genotypes in UC and CD patients. Supplementary Table 4 shows the results for the whole group of IBD patients.
Variables median (IQR) or n (%) | n | ε2/ε3 | ε3/ε3 | ε3/ε4 | P value |
Age in yr | |||||
At inclusion | 184 | 15.7 (12.5-16.9) | 15.3 (11.9-16.9) | 14.3 (11.5-16.3) | 0.2464 |
At diagnosis | 191 | 11.4 (7.9-14.6) | 12.4 (7.9-15.0) | 12.4 (8.2-14.9) | 0.9070 |
At worst flare | 171 | 14.6 (9.9-16.4) | 13.7 (10.4-16.0) | 13.7 (10.0-15.7) | 0.7255 |
Duration of the disease in yr | 179 | 3.0 (1.4-6.2) | 1.9 (0.4-3.5) | 1.2 (0.0-3.5) | 0.0868 |
Nutritional status | |||||
Weight at diagnosis in kg | 180 | 40.0 (28.8-59.5) | 39.0 (27.8-54.0) | 43.8 (29.5-53.4) | 0.9704 |
Weight at diagnosis, z score | 179 | -0.20 [(-0.86)-0.43] | -0.5 [(-1.1)-0.1] | -0.24 [(-0.95)-0.63] | 0.3037 |
Height at diagnosis in cm | 175 | 146.5 (129.0-169.0) | 153.0 (131.0-168.5) | 156.0 (131.5-169.0) | 0.9175 |
Height at diagnosis, z score | 174 | 0.12 [(-0.62)-0.75] | 0.09 [(-0.69)-0.79] | 0.22 [(-0.44)-1.06] | 0.5823 |
Body mass index at diagnosis in kg/m2 | 175 | 17.61 (16.02-19.74) | 17.0 (15.4-19.1) | 17.9 (15.4-20.3) | 0.5121 |
Body mass index at diagnosis, z score | 174 | -0.11 [(-0.70)-0.29)] | -0.56 [(-0.99)-0.11] | -0.30 [(-1.12)-0.56] | 0.2293 |
Weight at worst flare in kg | 164 | 46.1 (31.6-62.0) | 46.2 (31.9-55.6) | 50.0 (28.0-61.0) | 0.9600 |
Weight at worst flare, z score | 161 | -0.33 [(-1.00)-0.56] | -0.58 [(-0.95)-0.16] | -0.52 [(-0.90)-0.40] | 0.6559 |
Height at worst flare in cm | 162 | 162.5 (138.5-173.5) | 159.0 (140.9-171.0) | 160.0 (135.0-172.0) | 0.9688 |
Height at worst flare, z score | 161 | 0.11 [(-0.72)-1.16] | -0.09 [(-0.62)-0.78] | 0.06 [(-0.62)-0.89] | 0.8376 |
Body mass index at worst flare in kg/m2 | 160 | 18.20 (16.47-19.74) | 17.36 (15.75-19.71) | 17.93 (15.89-20.96) | 0.6013 |
Body mass index at worst flare, z score | 159 | -0.22 [(-1.16)-0.14] | -0.68 [(-1.10)-0.16] | -0.43 [(-1.12)-0.63] | 0.6789 |
Albumin level | |||||
At diagnosis in g/dL | 159 | 4.2 (4.0-4.6) | 4.1 (3.7-4.4) | 4.1 (3.6-4.4) | 0.2569 |
At worst flare in g/ dL | 148 | 4.3 (4.0-4.7) | 4.1 (3.6-4.4) | 4.2 (4.0-4.4) | 0.3488 |
Parameter of inflammation | |||||
CRP at diagnosis in mg/L | 178 | 3.8 (0.7-6.6) | 2.5 (0.7-12.2) | 1.1 (0.2-8.0) | 0.0515 |
CRP at worst flare in mg/L | 162 | 2.1 (1.1-23.3) | 3.7 (1.1-19.0) | 0.8 (0.3-2.9) | 0.0012 |
Disease activity scales | |||||
PUCAI at diagnosis | 166 | 40 (18-55) | 45 (30-60) | 50 (25-60) | 0.5144 |
PUCAI at worst flare | 155 | 48 (20-65) | 55 (40-65) | 50 (30-65) | 0.3766 |
Disease localisation and behaviour | |||||
E1 at diagnosis | 19/192 | 3 (16.7) | 10 (8.5) | 6 (12.8) | 0.4694 |
E2 at diagnosis | 33/192 | 8 (44.4) | 16 (13.6) | 9 (19.1) | 0.0063 |
E3 at diagnosis | 28/192 | 1 (5.6) | 18 (15.3) | 9 (19.1) | 0.3953 |
E4 at diagnosis | 83/192 | 5 (27.8) | 60 (50.8) | 18 (38.3) | 0.0990 |
S0 at diagnosis | 110/192 | 13 (72.2) | 69 (58.5) | 28 (59.6) | 0.5383 |
S1 at diagnosis | 37/192 | 3 (16.7) | 23 (19.5) | 11 (23.4) | 0.7885 |
E1 at worst flare | 9/192 | 1 (5.6) | 4 (3.4) | 4 (8.5) | 0.3863 |
E2 at worst flare | 27/192 | 3 (16.7) | 18 (15.3) | 6 (12.8) | 0.8943 |
E3 at worst flare | 23/192 | 3 (16.7) | 16 (13.6) | 4 (8.5) | 0.5814 |
E4 at worst flare | 75/192 | 7 (38.9) | 50 (42.4) | 18 (38.3) | 0.8750 |
S0 at worst flare | 83/192 | 9 (50.0) | 52 (44.1) | 22 (46.8) | 0.8713 |
S1 at worst flare | 49/192 | 5 (27.8) | 34 (28.8) | 10 (21.3) | 0.6114 |
Treatment | |||||
Systemic steroids1 | 192 | 11 (61.1) | 92 (78.0) | 29 (61.7) | 0.0599 |
Number of courses of steroid treatment | 190 | 1 (0-2) | 1 (1-2) | 1 (0-2) | 0.0672 |
Immunosuppressive treatment2 | 191 | 9 (50.0) | 74 (63.2) | 25 (53.2) | 0.3451 |
Number of immunosuppressants | 191 | 1 (0-1) | 1 (0-1) | 1 (0-1) | 0.2572 |
Time-to-first dose of immunosuppressive treatment in mo | 109 | 3.0 (2.0-17.0) | 4.0 (0.0-10.0) | 2.8 (0.0-8.0) | 0.4356 |
Age at first intake of immunosuppressive treatment in yr | 109 | 14.7 (10.4-16.1) | 12.3 (7.8-14.1) | 11.0 (7.3-15.5) | 0.2381 |
Biological therapy3 | 192 | 4 (22.2) | 29 (24.8) | 13 (27.7) | 0.8781 |
Total number of biologics | 192 | 0 (0-0) | 0 (0-0) | 0 (0-1) | 0.8164 |
Time-to-first dose of biological treatment in mo | 48 | 19.9 (12.8-50.3) | 16.4 (9.1-28.1) | 10.8 (4.0-27.7) | 0.3152 |
Age at first biological treatment | 49 | 15.7 (14.7-15.9) | 11.5 (7.9-14.6) | 10.7 (4.5-15.5) | 0.0852 |
Operative treatment4 | 192 | 0 (0.0) | 3 (2.5) | 1 (2.1) | 0.7893 |
Age at first surgery in yr | 6 | 7.7 (5.9-9.6) | 14.8 (6.8-17.1) | 13.0 (10.4-15.6) | 0.2969 |
Time-to-first surgery in mo | 4 | 16.7 (5.0-28.7) | 19.1 (0.9-37.4) | 1.0000 | |
Hospitalisations, if duration ≥ 1 yr | |||||
Hospitalisations for relapse, per 1 yr of the disease | 98 | 0.3 (0.3-0.8) | 0.6 (0.3-1.6) | 0.9 (0.5-1.3) | 0.2518 |
Days of hospitalisation for relapse, per 1 yr of the disease | 98 | 2.5 (0.6-4.5) | 4.8 (1.8-9.3) | 7.3 (3.8-8.7) | 0.1362 |
Relapses from diagnosis, per 1 yr of the disease | 98 | 0.3 (0.1-0.8) | 0.6 (0.3-1.2) | 0.8 (0.3-1.3) | 0.3491 |
Severe relapses from diagnosis, per 1 yr of the disease | 100 | 0.0 (0.0-0.3) | 0.1 (0.0-0.6) | 0.2 (0.0-0.4) | 0.7150 |
Concomitant diseases5 | 192 | 9 (50.0) | 41 (34.7) | 15 (31.9) | 0.3781 |
Extraintestinal manifestations | 192 | 3 (16.7) | 23 (19.5) | 10 (21.3) | 0.9131 |
Variables median (IQR) or n (%) | n | ε2/ε3 | ε3/ε3 | ε3/ε4 | P value |
Age in yr | |||||
At inclusion | 213 | 15.5 (13.2-16.8) | 15.2 (13.3-17.2) | 15.2 (13.4-16.2) | 0.8055 |
At diagnosis | 213 | 11.8 (10.1-14.6) | 12.7 (9.9-14.5) | 12.6 (10.0-13.9) | 0.8796 |
At worst flare | 184 | 13.3 (11.6-15.2) | 13.6 (11.3-15.8) | 14.3 (12.8-15.9) | 0.5121 |
Duration of the disease in yr | 211 | 2.8 (0.6-5.4) | 2.0 (0.8-4.0) | 2.3 (0.8-4.1) | 0.7843 |
Nutritional status | |||||
Weight at diagnosis in kg | 207 | 38.3 (27.6-48.0) | 37.3 (25.3-49.5) | 38.4 (28.3-57.6) | 0.5360 |
Weight at diagnosis, z score | 204 | -0.53 [(-1.02)-(-0.02)] | -0.91 [(-1.46)-(-0.12)] | -0.73 [(-1.34)-0.38] | 0.2062 |
Height at diagnosis in cm | 207 | 148.3 (141.0-164.0) | 151.5 (134.0-164.0) | 151.3 (141.0-170.0) | 0.6757 |
Height at diagnosis, z score | 204 | -0.17 [(-0.85)-0.51] | -0.47 [(-1.43)-0.32] | 0.05 [(-1.10)-0.96] | 0.0617 |
Body mass index at diagnosis in kg/m2 | 207 | 16.73 (14.28-18.42) | 16.59 (14.41-18.22) | 16.40 (14.78-20.78) | 0.8397 |
Body mass index at diagnosis, z score | 204 | -0.72 [(-1.33)-(-0.16)] | -0.79 [(-1.53)-(-0.08)] | -0.88 [(-1.29)-0.49] | 0.7878 |
Weight at worst flare in kg | 181 | 41.8 (34.8-50.3) | 41.9 (29.6-52.6) | 46.8 (36.2-58.9) | 0.2294 |
Weight at worst flare, z score | 178 | -0.67 [(-1.16)-0.10] | -1.14 [(-1.64)-(-0.25)] | -0.60 [(-1.22)-0.02] | 0.0756 |
Height at worst flare in cm | 183 | 153.0 (148.5-166.0) | 158.0 (141.5-167.0) | 162.0 (148.5-171.5) | 0.3088 |
Height at worst flare, z score | 180 | -0.15 [(-1.09)-0.61] | -0.52 [(-1.41)-0.21] | -0.24 [(-1.10)-0.43] | 0.1234 |
Body mass index at worst flare in kg/m2 | 181 | 17.29 (15.53-18.60) | 16.89 (14.87-19.03) | 17.09 (15.56-21.74) | 0.4172 |
Body mass index at worst flare, z score | 178 | -0.87 [(-1.38)-0.01] | -1.03 [(-1.55)-(-0.19)] | -0.53 [(-1.46)-0.49] | 0.3913 |
Albumin level | |||||
At diagnosis in g/dL | 186 | 3.9 (3.7-4.3) | 3.8 (3.4-4.2) | 3.9 (3.4-4.3) | 0.5796 |
At worst flare in g/dL | 179 | 3.9 (3.8-4.3) | 3.9 (3.4-4.1) | 3.9 (3.6-4.3) | 0.0611 |
Parameter of inflammation | |||||
CRP at diagnosis in mg/L | 208 | 13.8 (0.8-40.0) | 13.0 (2.1-29.6) | 12.0 (3.4-24.9) | 0.8818 |
CRP at worst flare in mg/L | 185 | 18.3 (1.7-31.5) | 14.0 (3.3-38.5) | 13.6 (3.2-26.8) | 0.7672 |
Disease activity scales | |||||
PCDAI at diagnosis | 190 | 25 (20-35) | 35 (25-50) | 30 (25-43) | 0.0282 |
PCDAI at worst flare | 170 | 35 (23-50) | 45 (30-53) | 38 (30-53) | 0.1898 |
Disease localisation and behaviour | |||||
L1 at diagnosis | 53/213 | 9 (25.7) | 35 (26.1) | 8 (19.5) | 0.6852 |
L2 at diagnosis | 40/213 | 9 (25.7) | 19 (14.2) | 11 (26.8) | 0.0935 |
L3 at diagnosis | 99/213 | 13 (37.1) | 67 (50.0) | 16 (39.0) | 0.2507 |
L4a at diagnosis | 23/213 | 4 (11.4) | 14 (10.4) | 4 (9.8) | 0.9721 |
L4b at diagnosis | 8/213 | 1 (2.9) | 7 (5.2) | 0 (0.0) | 0.2950 |
B1 at diagnosis | 146/213 | 24 (68.6) | 89 (66.4) | 33 (80.5) | 0.2287 |
B2 at diagnosis | 15/213 | 3 (8.6) | 11 (8.2) | 1 (2.4) | 0.4263 |
B3 at diagnosis | 19/213 | 3 (8.6) | 15 (11.2) | 1 (2.4) | 0.2304 |
B2B3 at diagnosis | 4/213 | 1 (2.9) | 3 (2.2) | 0 (0.0) | 0.5927 |
G0 at diagnosis | 145/213 | 24 (68.6) | 92 (68.7) | 29 (70.7) | 0.9667 |
G1 at diagnosis | 33/213 | 3 (8.6) | 24 (17.9) | 6 (14.6) | 0.3921 |
P at diagnosis | 19/213 | 0 (0.0) | 16 (11.9) | 3 (7.3) | 0.0824 |
L1 at worst flare | 40/213 | 5 (14.3) | 26 (19.4) | 9 (22.0) | 0.6873 |
L2 at worst flare | 27/213 | 7 (20.0) | 14 (10.4) | 6 (14.6) | 0.3007 |
L3 at worst flare | 92/213 | 10 (28.6) | 66 (49.3) | 16 (39.0) | 0.0708 |
L4a at worst flare | 18/213 | 3 (8.6) | 12 (9.0) | 3 (7.3) | 0.9477 |
L4b at worst flare | 9/213 | 1 (2.9) | 5 (3.7) | 3 (7.3) | 0.5507 |
B1 at worst flare | 114/213 | 17 (48.6) | 74 (55.2) | 23 (56.1) | 0.7549 |
B2 at worst flare | 19/213 | 2 (5.7) | 12 (9.0) | 5 (12.2) | 0.6165 |
B3 at worst flare | 21/213 | 1 (2.9) | 16 (11.9) | 4 (9.8) | 0.2798 |
B2B3 at worst flare | 5/213 | 1 (2.9) | 4 (9.8) | 0 (0.0) | 0.5367 |
G0 at worst flare | 121/213 | 18 (51.4) | 79 (59.0) | 24 (58.5) | 0.7184 |
G1 at worst flare | 34/213 | 2 (5.7) | 24 (17.9) | 8 (19.5) | 0.1776 |
P at worst flare | 20/213 | 0 (0.0) | 17 (12.7) | 3 (7.3) | 0.0649 |
Treatment | |||||
Systemic steroids1 | 214 | 19 (34.3) | 73 (54.1) | 21 (51.2) | 0.9455 |
Number of courses of steroid treatment | 212 | 1 (0-2) | 1 (0-2) | 1 (0-1) | 0.5535 |
Immunosuppressive treatment2 | 214 | 25 (71.4) | 110 (81.5) | 31 (75.6) | 0.3756 |
Number of immunosuppressants | 214 | 1 (0-1) | 1 (1-1) | 1 (1-1) | 0.2632 |
Time-to-first dose of immunosuppressive treatment in mo | 166 | 1.3 (0.0-13.0) | 2.0 (0.0-7.0) | 1.0 (0.0-9.6) | 0.8866 |
Age at first intake of immunosuppressive treatment in yr | 166 | 12.9 (10.3-13.9) | 13.0 (10.7-14.9) | 12.7 (9.6-14.3) | 0.6668 |
Biological therapy3 | 214 | 15 (42.9) | 73 (54.1) | 18 (43.9) | 0.3303 |
Total number of biologics | 214 | 0 (0-1) | 1 (0-1) | 0 (0-1) | 0.2243 |
Time-to-first dose of biological treatment in mo | 102 | 17.8 (6.3-44.0) | 12.6 (5.6-25.9) | 13.3 (6.1-26.7) | 0.6313 |
Age at first biological treatment | 102 | 13.8 (12.7-14.8) | 13.6 (11.3-15.3) | 14.0 (10.7-15.6) | 0.8880 |
Operative treatment4 | 214 | 2 (5.7) | 19 (14.1) | 8 (19.5) | 0.2158 |
Age at first surgery in yr | 30 | 11.3 (9.4-13.1) | 14.5 (12.5-16.5) | 14.9 (14.0-15.7) | 0.1698 |
Time-to-first surgery in mo | 26 | 12.0 | 19.4 (0.0-41.1) | 25.1 (7.9-43.5) | 0.7807 |
Hospitalisations, if duration ≥ 1 yr | |||||
Hospitalisations for relapse, per 1 yr of the disease | 133 | 0.4 (0.2-0.7) | 0.5 (0.3-0.8) | 0.4 (0.2-1.3) | 0.6615 |
Days of hospitalisation for relapse, per 1 yr of the disease | 132 | 2.7 (0.7-5.6) | 4.7 (1.6-7.5) | 4.0 (1.1-7.6) | 0.4001 |
Relapses from diagnosis, per 1 yr of the disease | 132 | 0.4 (0.2-0.9) | 0.5 (0.2-0.9) | 0.4 (0.2-1.4) | 0.8664 |
Severe relapses from diagnosis, per 1 yr of the disease | 129 | 0.0 (0.0-0.3) | 0.2 (0.0-0.5) | 0.2 (0.0-0.5) | 0.1996 |
Concomitant diseases5 | 214 | 16 (45.7) | 40 (29.6) | 8 (19.5) | 0.0446 |
Extraintestinal manifestations | 214 | 7 (20.0) | 34 (25.2) | 11 (26.8) | 0.7660 |
Variables median (IQR) or n (%) | n | ε3/ε3 | APOEε2-positive | APOEε4-positive | P value |
IBD | |||||
Albumin level at worst flare in g/dL | 327 | 3.9 (3.4-4.3) | 4.0 (3.9-4.5) | 4.1 (3.8-4.4) | 0.0176a |
CRP at worst flare in mg/L | 347 | 7.7 (1.9-31.3) | 4.3 (1.1-28.3) | 3.2 (0.5-16.7) | 0.0146b |
Age at first surgery in yr | 36 | 14.5 (11.7-16.7) | 9.5 (7.7-11.4) | 14.9 (14.0-15.6) | 0.0378 |
Days of hospitalisation for relapse, per 1 yr of the disease | 230 | 4.7 (1.6-8.3) | 2.2 (0.7-4.8) | 6.1 (1.7-8.7) | 0.0440c |
CD | |||||
Albumin level at worst flare in g/dL | 327 | 3.9 (3.4-4.1) | 3.9 (3.8-4.4) | 4.4 (3.6-4.3) | 0.0363 |
PCDAI at diagnosis | 190 | 35 (25-50) | 25 (20-35) | 30 (25-45) | 0.0204c |
Height at diagnosis, z score | 378 | -0.47 [(-1.43)-0.32] | -0.16 [(-0.85)-0.61] | 0.00 [(-1.10)-0.96] | 0.0482 |
UC | |||||
CRP at diagnosis in mg/L | 386 | 2.5 (0.7-12.2) | 3.8 (0.8-7.3) | 1.1 (0.2-8.2) | 0.0435 |
CRP at worst flare in mg/L | 347 | 3.7 (1.1-19.0) | 2.1 (1.8-7.3) | 0.9 (0.3-3.6) | 0.0013 |
Age at first biological treatment | 151 | 11.5 (7.9-14.6) | 15.7 (15.3-15.7) | 10.7 (4.8-15.5) | 0.0432 |
E2 at diagnosis | 192 | 16 (13.6) | 8 (40.0) | 9 (18.0) | 0.0160 |
The present study investigated the relationship between APOE genotype and disease severity in IBD, suggesting that the APOE genotype might be associated with some indices of disease course such as CRP and albumin levels at the worst flare, age at surgery and numbers of hospitalisation days. UC patients with the APOEε4 allele had the lowest values of CRP, both at diagnosis and the worst flare. The median age at first biological therapy in UC was lowest in patients with the APOEε4 allele, whereas left-side colitis was more frequent among patients with the APOEε2 allele. In CD patients, the APOEε4 allele was associated with higher albumin at worst flare and higher standardised body height at diagnosis. Moreover, patients with the APOEε2 allele scored lower on the PCDAI. This study is the largest to show the genetic distribution of APOE polymorphisms in IBD to date.
APOE is known to be associated with inflammation indicators[13]. The findings of the present study confirm this relationship as the CRP levels differed between APOE genotypes. Patients with the APOEε4 allele and APOEε3ε4 genotype had lower CRP values at diagnosis and the worst flare, while patients with the APOEε3ε3 genotype had higher levels of CRP at the worst flare. These results are similar to those obtained in healthy adults, which showed that subjects with APOEε3ε3 had the highest plasma levels of CRP and individuals with APOEε4ε4 and APOEε2ε4 had the lowest levels[13]. A similar pattern has also been observed in other diseases such as coronary artery disease[43-46]. März et al[47] proved that in coronary artery disease, both white cell count and fibrinogen were not related to the APOE genotype, suggesting that the underlying mechanism is not associated with inflammation[46] but rather to the mevalonate/ cholesterol synthetic pathway, which may be downregulated in patients with APOEε4 in response to altered lipoprotein metabolism and hepatic uptake[46]. In another study, the APOEε4 allele was also associated with lower CRP but not white blood cell count[47]. Further mechanistic studies are needed to explain the link.
Our study is the first to report that in CD patients, the APOEε4 allele is associated with higher median levels of albumins at the worst flare. Albumin level is negatively correlated with the extent of the inflammatory response, which is caused by a hypercatabolic state and a decrease of albumin synthesis in the liver[48]. Tumour necrosis factor-α inhibits albumin expression causing hypoalbuminemia[48] , a state associated with IBD activity, unresponsiveness to treatment, and increased risk of colectomy in UC. Patients with hypoalbuminemia had a higher likelihood of having more than two courses of corticosteroids, thiopurine, or anti-tumour necrosis factor treatment[49]. In CD, albumin levels were reported as a marker of postoperative complications[50] and active clinical disease[51]. Low albumin level together with high CRP may correlate with an increased inflammatory response[52]. In the study of Sayar et al[53], the area under the curve values for severe UC were 0.883 for albumin levels (cut-off 3.6 g/dL) and 0.941 for CRP/albumin ratio (cut-off 0.6)[52]. Given these data, the results of our study may suggest that the APOEε4 allele is associated with a milder disease course of CD. The association of the APOEε2 allele with lower PCDAI scores and fewer days of hospitalisation due to relapse might suggest a protective role of this allele on disease severity. However, this relationship is more complicated as we found that the APOEε2 allele is also associated with a younger age at first surgery. This finding should be verified, preferably in a group of adult patients with a longer disease course and higher surgery rates.
The biology of APOE in IBD has not been fully elucidated, but recent studies have shown that the APOE transcript is overexpressed in paediatric IBD patients[53]. Studies in colonic epithelial cells in a mouse model showed that the apoE-mimetic peptide (COG112) inhibited the inflammatory response to Citrobacter rodentium[54], a bacterium known to cause colitis in mice[55]. The authors suggested this occurred by preventing the activation of nuclear factor κB[54]. Therefore, further mechanistic studies of APOE action are warranted.
A previous study on APOE in IBD in a group with a different genetic background (Saudi Arabia) did not focus on disease severity. Therefore, any comparisons are difficult[35]. In that study, the APOEε4 allele was associated with the risk of developing IBD and early onset, whereas our study did not identify significant differences between APOE genotypes and age at diagnosis. The frequencies of APOEε3ε3 genotype were lower in IBD patients in comparison to controls, which is consistent with the above-mentioned report[35].
The present study involved a large multicentre paediatric cohort, including a comprehensive clinical description, which allowed a detailed genotype-phenotype analysis. However, defining the global severity of the disease course remains challenging, especially in diseases with such a differentiated clinical presentation. The major limitation of this study is related to the retrospective character of the data collection regarding diagnosis and the worst flare. Need for surgery, which is one of the most crucial measures of disease course, would require longer follow-up in order to describe disease severity. Although we did not include a control group, APOE polymorphisms in healthy subjects have been studied in the Polish population[40-42,56], which allowed us to estimate whether there was any frequency distribution difference.
APOE polymorphisms are associated with the risk of developing IBD and seem to be associated with the clinical expression of the disease and applied treatment (with inflammatory markers and nutritional status, disease activity and localisation, hospitalisations). However, the clinical relevance of the differences identified is relatively modest.
Apolipoprotein E (APOE) polymorphisms were previously reported to be linked with the risk of developing inflammatory bowel diseases (IBD).
No data on the relationship between APOE polymorphisms and disease severity are available.
This study aimed to investigate the link between APOE variants and disease severity in IBD.
The TaqMan hydrolysis probe assay was used to genotype 406 patients with IBD (192 had ulcerative colitis and 214 had Crohn’s disease). Clinical expression involved disease activity scales, albumin and C-reactive protein levels, disease localisation and behaviour, and treatment with the time and age of the first intervention. The number of hospitalisations and days spent in hospital due to exacerbation as well as the number of relapses and severe relapses were also estimated.
Ulcerative colitis patients with the APOEε4 allele had the lowest C-reactive protein values both at diagnosis (P = 0.0435) and the worst flare (P = 0.0013) compared to patients with the APOEε2 allele and genotype APOEε3/ε3. Crohn’s disease patients with the APOEε2 allele scored lower on the Pediatric Crohn’s Disease Activity Index at diagnosis (P = 0.0204). All IBD patients with the APOEε2 allele spent fewer days in the hospital due to relapse (P = 0.0440).
The APOE genotype seems to be associated with some indices of disease course such as inflammatory markers, disease activity, and applied treatment. However, the clinical significance of the differences identified remains modest.
Further mechanistic studies of APOE action in IBD are warranted.
Manuscript source: Unsolicited manuscript
Specialty type: Gastroenterology and hepatology
Country/Territory of origin: Poland
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P-Reviewer: Tsibouris P, Tsujinaka S S-Editor: Zhang H L-Editor: Filipodia P-Editor: Ma YJ
1. | Wawrzyniak M, Scharl M. Genetics and epigenetics of inflammatory bowel disease. Swiss Med Wkly. 2018;148:w14671. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 9] [Cited by in F6Publishing: 18] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
2. | Brant SR. Promises, delivery, and challenges of inflammatory bowel disease risk gene discovery. Clin Gastroenterol Hepatol. 2013;11:22-26. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 40] [Cited by in F6Publishing: 37] [Article Influence: 3.1] [Reference Citation Analysis (0)] |
3. | Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, Lee JC, Schumm LP, Sharma Y, Anderson CA, Essers J, Mitrovic M, Ning K, Cleynen I, Theatre E, Spain SL, Raychaudhuri S, Goyette P, Wei Z, Abraham C, Achkar JP, Ahmad T, Amininejad L, Ananthakrishnan AN, Andersen V, Andrews JM, Baidoo L, Balschun T, Bampton PA, Bitton A, Boucher G, Brand S, Büning C, Cohain A, Cichon S, D’Amato M, De Jong D, Devaney KL, Dubinsky M, Edwards C, Ellinghaus D, Ferguson LR, Franchimont D, Fransen K, Gearry R, Georges M, Gieger C, Glas J, Haritunians T, Hart A, Hawkey C, Hedl M, Hu X, Karlsen TH, Kupcinskas L, Kugathasan S, Latiano A, Laukens D, Lawrance IC, Lees CW, Louis E, Mahy G, Mansfield J, Morgan AR, Mowat C, Newman W, Palmieri O, Ponsioen CY, Potocnik U, Prescott NJ, Regueiro M, Rotter JI, Russell RK, Sanderson JD, Sans M, Satsangi J, Schreiber S, Simms LA, Sventoraityte J, Targan SR, Taylor KD, Tremelling M, Verspaget HW, De Vos M, Wijmenga C, Wilson DC, Winkelmann J, Xavier RJ, Zeissig S, Zhang B, Zhang CK, Zhao H; International IBD Genetics Consortium (IIBDGC); Silverberg MS, Annese V, Hakonarson H, Brant SR, Radford-Smith G, Mathew CG, Rioux JD, Schadt EE, Daly MJ, Franke A, Parkes M, Vermeire S, Barrett JC, Cho JH. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012;491:119-124. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 3733] [Cited by in F6Publishing: 3459] [Article Influence: 266.1] [Reference Citation Analysis (0)] |
4. | de Lange KM, Moutsianas L, Lee JC, Lamb CA, Luo Y, Kennedy NA, Jostins L, Rice DL, Gutierrez-Achury J, Ji SG, Heap G, Nimmo ER, Edwards C, Henderson P, Mowat C, Sanderson J, Satsangi J, Simmons A, Wilson DC, Tremelling M, Hart A, Mathew CG, Newman WG, Parkes M, Lees CW, Uhlig H, Hawkey C, Prescott NJ, Ahmad T, Mansfield JC, Anderson CA, Barrett JC. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat Genet. 2017;49:256-261. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 803] [Cited by in F6Publishing: 874] [Article Influence: 109.3] [Reference Citation Analysis (0)] |
5. | Lichtenstein GR, Targan SR, Dubinsky MC, Rotter JI, Barken DM, Princen F, Carroll S, Brown M, Stachelski J, Chuang E, Landers CJ, Stempak JM, Singh S, Silverberg MS. Combination of genetic and quantitative serological immune markers are associated with complicated Crohn’s disease behavior. Inflamm Bowel Dis. 2011;17:2488-2496. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 60] [Cited by in F6Publishing: 57] [Article Influence: 4.1] [Reference Citation Analysis (0)] |
6. | Brant SR, Picco MF, Achkar JP, Bayless TM, Kane SV, Brzezinski A, Nouvet FJ, Bonen D, Karban A, Dassopoulos T, Karaliukas R, Beaty TH, Hanauer SB, Duerr RH, Cho JH. Defining complex contributions of NOD2/CARD15 gene mutations, age at onset, and tobacco use on Crohn’s disease phenotypes. Inflamm Bowel Dis. 2003;9:281-289. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 166] [Cited by in F6Publishing: 162] [Article Influence: 7.4] [Reference Citation Analysis (0)] |
7. | Abreu MT, Taylor KD, Lin YC, Hang T, Gaiennie J, Landers CJ, Vasiliauskas EA, Kam LY, Rojany M, Papadakis KA, Rotter JI, Targan SR, Yang H. Mutations in NOD2 are associated with fibrostenosing disease in patients with Crohn’s disease. Gastroenterology. 2002;123:679-688. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 352] [Cited by in F6Publishing: 326] [Article Influence: 14.2] [Reference Citation Analysis (0)] |
8. | Cleynen I, González JR, Figueroa C, Franke A, McGovern D, Bortlík M, Crusius BJ, Vecchi M, Artieda M, Szczypiorska M, Bethge J, Arteta D, Ayala E, Danese S, van Hogezand RA, Panés J, Peña SA, Lukas M, Jewell DP, Schreiber S, Vermeire S, Sans M. Genetic factors conferring an increased susceptibility to develop Crohn’s disease also influence disease phenotype: results from the IBDchip European Project. Gut. 2013;62:1556-1565. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 190] [Cited by in F6Publishing: 206] [Article Influence: 17.2] [Reference Citation Analysis (0)] |
9. | Alvarez-Lobos M, Arostegui JI, Sans M, Tassies D, Plaza S, Delgado S, Lacy AM, Pique JM, Yagüe J, Panés J. Crohn’s disease patients carrying Nod2/CARD15 gene variants have an increased and early need for first surgery due to stricturing disease and higher rate of surgical recurrence. Ann Surg. 2005;242:693-700. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 127] [Cited by in F6Publishing: 128] [Article Influence: 6.4] [Reference Citation Analysis (0)] |
10. | Adler J, Rangwalla SC, Dwamena BA, Higgins PD. The prognostic power of the NOD2 genotype for complicated Crohn’s disease: a meta-analysis. Am J Gastroenterol. 2011;106:699-712. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 135] [Cited by in F6Publishing: 144] [Article Influence: 10.3] [Reference Citation Analysis (0)] |
11. | Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW, Roses AD, Haines JL, Pericak-Vance MA. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science. 1993;261:921-923. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 5968] [Cited by in F6Publishing: 6289] [Article Influence: 196.5] [Reference Citation Analysis (0)] |
12. | Mahley RW, Rall SC Jr. Apolipoprotein E: far more than a lipid transport protein. Annu Rev Genomics Hum Genet. 2000;1:507-537. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 1164] [Cited by in F6Publishing: 1233] [Article Influence: 53.6] [Reference Citation Analysis (0)] |
13. | Hubacek JA, Peasey A, Pikhart H, Stavek P, Kubinova R, Marmot M, Bobak M. APOE polymorphism and its effect on plasma C-reactive protein levels in a large general population sample. Hum Immunol. 2010;71:304-308. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 54] [Cited by in F6Publishing: 55] [Article Influence: 3.7] [Reference Citation Analysis (0)] |
14. | Zhang HL, Wu J, Zhu J. The immune-modulatory role of apolipoprotein E with emphasis on multiple sclerosis and experimental autoimmune encephalomyelitis. Clin Dev Immunol. 2010;2010:186813. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 43] [Cited by in F6Publishing: 62] [Article Influence: 4.1] [Reference Citation Analysis (0)] |
15. | Zhang H, Wu LM, Wu J. Cross-talk between apolipoprotein E and cytokines. Mediators Inflamm. 2011;2011:949072. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 96] [Cited by in F6Publishing: 127] [Article Influence: 9.1] [Reference Citation Analysis (0)] |
16. | Toms TE, Smith JP, Panoulas VF, Blackmore H, Douglas KM, Kitas GD. Apolipoprotein E gene polymorphisms are strong predictors of inflammation and dyslipidemia in rheumatoid arthritis. J Rheumatol. 2012;39:218-225. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 21] [Cited by in F6Publishing: 23] [Article Influence: 1.6] [Reference Citation Analysis (0)] |
17. | Coto-Segura P, Coto E, Alvarez V, Morales B, Soto-Sánchez J, Corao AI, Santos-Juanes J. Apolipoprotein epsilon4 allele is associated with psoriasis severity. Arch Dermatol Res. 2010;302:145-149. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 16] [Cited by in F6Publishing: 17] [Article Influence: 1.1] [Reference Citation Analysis (0)] |
18. | Furumoto H, Nakamura K, Imamura T, Hamamoto Y, Shimizu T, Muto M, Asagami C. Association of apolipoprotein allele epsilon 2 with psoriasis vulgaris in Japanese population. Arch Dermatol Res. 1997;289:497-500. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 18] [Cited by in F6Publishing: 19] [Article Influence: 0.7] [Reference Citation Analysis (0)] |
19. | Avila EM, Holdsworth G, Sasaki N, Jackson RL, Harmony JA. Apoprotein E suppresses phytohemagglutinin-activated phospholipid turnover in peripheral blood mononuclear cells. J Biol Chem. 1982;257:5900-5909. [PubMed] [Cited in This Article: ] |
20. | Schumacher K, Maerker-Alzer G, Wehmer U. A lymphocyte-inhibiting factor isolated from normal human liver. Nature. 1974;251:655-656. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 44] [Cited by in F6Publishing: 44] [Article Influence: 0.9] [Reference Citation Analysis (0)] |
21. | Hui DY, Harmony JA. Phosphatidylinositol turnover in mitogen-activated lymphocytes. Suppression by low-density lipoproteins. Biochem J. 1980;192:91-98. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 51] [Cited by in F6Publishing: 55] [Article Influence: 1.2] [Reference Citation Analysis (0)] |
22. | Hui DY, Harmony JA, Innerarity TL, Mahley RW. Immunoregulatory plasma lipoproteins. Role of apoprotein E and apoprotein B. J Biol Chem. 1980;255:11775-11781. [PubMed] [Cited in This Article: ] |
23. | Pepe MG, Curtiss LK. Apolipoprotein E is a biologically active constituent of the normal immunoregulatory lipoprotein, LDL-In. J Immunol. 1986;136:3716-3723. [PubMed] [Cited in This Article: ] |
24. | Mistry MJ, Clay MA, Kelly ME, Steiner MA, Harmony JA. Apolipoprotein E restricts interleukin-dependent T lymphocyte proliferation at the G1A/G1B boundary. Cell Immunol. 1995;160:14-23. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 46] [Cited by in F6Publishing: 47] [Article Influence: 1.6] [Reference Citation Analysis (0)] |
25. | Terkeltaub RA, Dyer CA, Martin J, Curtiss LK. Apolipoprotein (apo) E inhibits the capacity of monosodium urate crystals to stimulate neutrophils. Characterization of intraarticular apo E and demonstration of apo E binding to urate crystals in vivo. J Clin Invest. 1991;87:20-26. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 63] [Cited by in F6Publishing: 72] [Article Influence: 2.1] [Reference Citation Analysis (0)] |
26. | Vitek MP, Brown CM, Colton CA. APOE genotype-specific differences in the innate immune response. Neurobiol Aging. 2009;30:1350-1360. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 248] [Cited by in F6Publishing: 249] [Article Influence: 15.6] [Reference Citation Analysis (0)] |
27. | Colton CA, Brown CM, Czapiga M, Vitek MP. Apolipoprotein-E allele-specific regulation of nitric oxide production. Ann N Y Acad Sci. 2002;962:212-225. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 32] [Cited by in F6Publishing: 35] [Article Influence: 1.5] [Reference Citation Analysis (0)] |
28. | Colton CA, Brown CM, Cook D, Needham LK, Xu Q, Czapiga M, Saunders AM, Schmechel DE, Rasheed K, Vitek MP. APOE and the regulation of microglial nitric oxide production: a link between genetic risk and oxidative stress. Neurobiol Aging. 2002;23:777-785. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 92] [Cited by in F6Publishing: 103] [Article Influence: 4.5] [Reference Citation Analysis (0)] |
29. | Maezawa I, Nivison M, Montine KS, Maeda N, Montine TJ. Neurotoxicity from innate immune response is greatest with targeted replacement of E4 allele of apolipoprotein E gene and is mediated by microglial p38MAPK. FASEB J. 2006;20:797-799. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 81] [Cited by in F6Publishing: 86] [Article Influence: 4.5] [Reference Citation Analysis (0)] |
30. | Saura J, Petegnief V, Wu X, Liang Y, Paul SM. Microglial apolipoprotein E and astroglial apolipoprotein J expression in vitro: opposite effects of lipopolysaccharide. J Neurochem. 2003;85:1455-1467. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 60] [Cited by in F6Publishing: 64] [Article Influence: 2.9] [Reference Citation Analysis (0)] |
31. | Werb Z, Chin JR. Apoprotein E is synthesized and secreted by resident and thioglycollate-elicited macrophages but not by pyran copolymer- or bacillus Calmette-Guerin-activated macrophages. J Exp Med. 1983;158:1272-1293. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 55] [Cited by in F6Publishing: 68] [Article Influence: 1.6] [Reference Citation Analysis (0)] |
32. | Levy E, Rizwan Y, Thibault L, Lepage G, Brunet S, Bouthillier L, Seidman E. Altered lipid profile, lipoprotein composition, and oxidant and antioxidant status in pediatric Crohn disease. Am J Clin Nutr. 2000;71:807-815. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 110] [Cited by in F6Publishing: 115] [Article Influence: 4.6] [Reference Citation Analysis (0)] |
33. | Hrabovský V, Zadák Z, Bláha V, Hyspler R, Karlík T, Martínek A, Mendlová A. Cholesterol metabolism in active Crohn’s disease. Wien Klin Wochenschr. 2009;121:270-275. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 14] [Cited by in F6Publishing: 18] [Article Influence: 1.1] [Reference Citation Analysis (0)] |
34. | Gazouli M, Anagnostopoulos AK, Papadopoulou A, Vaiopoulou A, Papamichael K, Mantzaris G, Theodoropoulos GE, Anagnou NP, Tsangaris GT. Serum protein profile of Crohn’s disease treated with infliximab. J Crohns Colitis. 2013;7:e461-e470. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 30] [Cited by in F6Publishing: 38] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
35. | Al-Meghaiseeb ES, Al-Otaibi MM, Al-Robayan A, Al-Amro R, Al-Malki AS, Arfin M, Al-Asmari AK. Genetic association of apolipoprotein E polymorphisms with inflammatory bowel disease. World J Gastroenterol. 2015;21:897-904. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 8] [Cited by in F6Publishing: 7] [Article Influence: 0.7] [Reference Citation Analysis (0)] |
36. | IBD Working Group of the European Society for Paediatric Gastroenterology; Hepatology and Nutrition. Inflammatory bowel disease in children and adolescents: recommendations for diagnosis--the Porto criteria. J Pediatr Gastroenterol Nutr. 2005;41:1-7. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 484] [Cited by in F6Publishing: 493] [Article Influence: 24.7] [Reference Citation Analysis (0)] |
37. | Van Assche G, Dignass A, Panes J, Beaugerie L, Karagiannis J, Allez M, Ochsenkühn T, Orchard T, Rogler G, Louis E, Kupcinskas L, Mantzaris G, Travis S, Stange E; European Crohn’s and Colitis Organisation (ECCO). The second European evidence-based Consensus on the diagnosis and management of Crohn’s disease: Definitions and diagnosis. J Crohns Colitis. 2010;4:7-27. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 818] [Cited by in F6Publishing: 780] [Article Influence: 52.0] [Reference Citation Analysis (0)] |
38. | Best WR, Becktel JM, Singleton JW, Kern F Jr. Development of a Crohn’s disease activity index. National Cooperative Crohn’s Disease Study. Gastroenterology. 1976;70:439-444. [PubMed] [Cited in This Article: ] |
39. | Assa A, Rinawi F, Shamir R. The Long-Term Predictive Properties of the Paris Classification in Paediatric Inflammatory Bowel Disease Patients. J Crohns Colitis. 2018;12:39-47. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 18] [Cited by in F6Publishing: 17] [Article Influence: 2.4] [Reference Citation Analysis (0)] |
40. | Jasienska G, Ellison PT, Galbarczyk A, Jasienski M, Kalemba-Drozdz M, Kapiszewska M, Nenko I, Thune I, Ziomkiewicz A. Apolipoprotein E (ApoE) polymorphism is related to differences in potential fertility in women: a case of antagonistic pleiotropy? Proc Biol Sci. 2015;282:20142395. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 32] [Cited by in F6Publishing: 39] [Article Influence: 3.9] [Reference Citation Analysis (0)] |
41. | Kowalska A, Wiechmann I, Walter H. Genetic variability of apolipoprotein E in a Polish population. Hum Biol. 1998;70:1093-1099. [PubMed] [Cited in This Article: ] |
42. | Bednarska-Makaruk M, Broda G, Kurjata P, Rodo M, Roszczynko M, Rywik S, Wehr H. Apolipoprotein E genotype, lipid levels and coronary heart disease in a Polish population group. Eur J Epidemiol. 2001;17:789-792. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 14] [Cited by in F6Publishing: 16] [Article Influence: 0.7] [Reference Citation Analysis (0)] |
43. | Bojar I, Owoc J, Wójcik-Fatla A, Raszewski G, Stančiak J, Raczkiewicz D. Cognitive functions, lipid profile, and Apolipoprotein E gene polymorphism in postmenopausal women. Ann Agric Environ Med. 2015;22:313-319. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 10] [Cited by in F6Publishing: 13] [Article Influence: 1.3] [Reference Citation Analysis (0)] |
44. | Mänttäri M, Manninen V, Palosuo T, Ehnholm C. Apolipoprotein E polymorphism and C-reactive protein in dyslipidemic middle-aged men. Atherosclerosis. 2001;156:237-238. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 34] [Cited by in F6Publishing: 34] [Article Influence: 1.4] [Reference Citation Analysis (0)] |
45. | Tziakas DN, Chalikias GK, Antonoglou CO, Veletza S, Tentes IK, Kortsaris AX, Hatseras DI, Kaski JC. Apolipoprotein E genotype and circulating interleukin-10 Levels in patients with stable and unstable coronary artery disease. J Am Coll Cardiol. 2006;48:2471-2481. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 33] [Cited by in F6Publishing: 32] [Article Influence: 1.7] [Reference Citation Analysis (0)] |
46. | Judson R, Brain C, Dain B, Windemuth A, Ruaño G, Reed C. New and confirmatory evidence of an association between APOE genotype and baseline C-reactive protein in dyslipidemic individuals. Atherosclerosis. 2004;177:345-351. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 54] [Cited by in F6Publishing: 54] [Article Influence: 2.7] [Reference Citation Analysis (0)] |
47. | März W, Scharnagl H, Hoffmann MM, Boehm BO, Winkelmann BR. The apolipoprotein E polymorphism is associated with circulating C-reactive protein (the Ludwigshafen risk and cardiovascular health study). Eur Heart J. 2004;25:2109-2119. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 68] [Cited by in F6Publishing: 63] [Article Influence: 3.2] [Reference Citation Analysis (0)] |
48. | Yun YW, Kweon SS, Choi JS, Rhee JA, Lee YH, Nam HS, Jeong SK, Park KS, Ryu SY, Choi SW, Kim HN, Cauley JA, Shin MH. APOE Polymorphism Is Associated with C-reactive Protein Levels but Not with White Blood Cell Count: Dong-gu Study and Namwon Study. J Korean Med Sci. 2015;30:860-865. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 0.8] [Reference Citation Analysis (0)] |
49. | Chojkier M. Inhibition of albumin synthesis in chronic diseases: molecular mechanisms. J Clin Gastroenterol. 2005;39:S143-S146. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 97] [Cited by in F6Publishing: 138] [Article Influence: 6.9] [Reference Citation Analysis (0)] |
50. | Khan N, Patel D, Shah Y, Trivedi C, Yang YX. Albumin as a prognostic marker for ulcerative colitis. World J Gastroenterol. 2017;23:8008-8016. [PubMed] [DOI] [Cited in This Article: ] [Cited by in CrossRef: 48] [Cited by in F6Publishing: 41] [Article Influence: 5.1] [Reference Citation Analysis (0)] |
51. | Müller C, Stift A, Argeny S, Bergmann M, Gnant M, Marolt S, Unger L, Riss S. Delta albumin is a better prognostic marker for complications following laparoscopic intestinal resection for Crohn’s disease than albumin alone - A retrospective cohort study. PLoS One. 2018;13:e0206911. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 7] [Cited by in F6Publishing: 13] [Article Influence: 1.9] [Reference Citation Analysis (0)] |
52. | Harris P, Matin T, Zhang N, Talha M. 778 Association Between Serum Albumin Levels and the Rate of Active Crohn’s Disease in Patients Seen at a Tertiary Care IBD Center. Am J Gastroenterol. 2019;114:S452-S452. [DOI] [Cited in This Article: ] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis (0)] |
53. | Sayar S, Kurbuz K, Kahraman R, Caliskan Z, Atalay R, Ozturk O, Doganay HL, Ozdil K. A practical marker to determining acute severe ulcerative colitis: CRP/albumin ratio. North Clin Istanb. 2020;7:49-55. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 1.2] [Reference Citation Analysis (0)] |
54. | Ostrowski J, Dabrowska M, Lazowska I, Paziewska A, Balabas A, Kluska A, Kulecka M, Karczmarski J, Ambrozkiewicz F, Piatkowska M, Goryca K, Zeber-Lubecka N, Kierkus J, Socha P, Lodyga M, Klopocka M, Iwanczak B, Bak-Drabik K, Walkowiak J, Radwan P, Grzybowska-Chlebowczyk U, Korczowski B, Starzynska T, Mikula M. Redefining the Practical Utility of Blood Transcriptome Biomarkers in Inflammatory Bowel Diseases. J Crohns Colitis. 2019;13:626-633. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 19] [Cited by in F6Publishing: 21] [Article Influence: 3.5] [Reference Citation Analysis (0)] |
55. | Singh K, Chaturvedi R, Asim M, Barry DP, Lewis ND, Vitek MP, Wilson KT. The apolipoprotein E-mimetic peptide COG112 inhibits the inflammatory response to Citrobacter rodentium in colonic epithelial cells by preventing NF-kappaB activation. J Biol Chem. 2008;283:16752-16761. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 44] [Cited by in F6Publishing: 45] [Article Influence: 2.6] [Reference Citation Analysis (0)] |
56. | Gobert AP, Cheng Y, Akhtar M, Mersey BD, Blumberg DR, Cross RK, Chaturvedi R, Drachenberg CB, Boucher JL, Hacker A, Casero RA Jr, Wilson KT. Protective role of arginase in a mouse model of colitis. J Immunol. 2004;173:2109-2117. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 101] [Cited by in F6Publishing: 107] [Article Influence: 5.1] [Reference Citation Analysis (0)] |