Transferrin Level Before Treatment and Genetic Polymorphism in HFE Gene as Predictive Markers for Response to Adalimumab in Crohn’s Disease Patients

Abstract

Tumor necrosis factor α inhibitors (anti-TNF) have improved treatment of several complex diseases, including Crohn's disease (CD). However, the effect varies and approximately one-third of the patients do not respond. Since blood parameters as well as genetic factors have shown a great potential to predict response during treatment, the aim of the study was to evaluate response to anti-TNF treatment with adalimumab (ADA) between genes HFE and TF and haematological parameters in Slovenian refractory CD patients. Single nucleotide polymorphisms (SNPs) rs1799852 in gene TF and rs2071303 in gene HFE were genotyped in 68 refractory CD patients for which response has been measured using inflammatory bowel disease questionnaire (IBDQ) index. Haematological parameters and IBDQ index were determined before therapy and after 4, 12, 20 and 30 weeks. We found novel strong association between SNP rs2071303 in gene HFE and response to ADA treatment, particularly patients with G allele comparing to A allele had better response after 20 weeks (p = 0.008). Further, we found strong association between transferrin level at baseline and treatment response after 12, 20 and 30 weeks, where average transferrin level before therapy was lower in responders (2.38 g/L) compared to non-responders (2.89 g/L, p = 0.005). Association was found between transferrin level in week 30 and SNP rs1799852 (p = 0.023), and between MCHC level before treatment and SNP rs2071303 (p = 0.007). Our results suggest that SNP in gene HFE as well as haematological markers serve as promising prognostic markers of response to anti-TNF treatment in CD patients.

Reduced Transferrin Levels in Active Inflammatory Bowel Disease

“…A decrease in transferrin concentrations occurred solely in active IBD. This might corroborate the findings that anti-TNF therapy has resulted in the improvement of iron availability and in the increase in transferrin concentrations [ 27 , 28 ]. Interestingly, we found some differences between CD and UC concerning transferrin; it was generally more closely associated with oxidative stress and more loosely with inflammation (except for hsCRP and IL-1) and anemia/nutritional status in CD.…”

Systematic review: predictive biomarkers of therapeutic response in inflammatory bowel disease—personalised medicine in its infancy

“…Despite an abundance of observational studies examining the relationship between molecular markers and adverse events related to immunomodulator use in IBD, evidence regarding biomarkers as predictors of treatment efficacy are scarce (Table S5 and Figure ) . Homozygous carriers for IL23R‐G9T were more likely to respond to azathioprine therapy .…”

“…A total of 10 638 citations were identified from the electronic and manual search. After removing duplicates (n = 767) and non‐applicable references (n = 9620), 251 citations were screened, of which 92 met the inclusion criteria (Figure ) . Baseline characteristics of the included manuscripts, study quality and studies reporting negative results are provided in Table S1, S2 and S3 respectively.…”

“…Baseline characteristics of the included manuscripts, study quality and studies reporting negative results are provided in Table S1, S2 and S3 respectively. Data from several included studies are only presented in tables . Figures and provide an overview of different predictive molecular markers grouped by underlying biological mechanism.…”

Pre-Treatment Biomarkers of Anti-Tumour Necrosis Factor Therapy Response in Crohn’s Disease—A Systematic Review and Gene Ontology Analysis

“…Unfortunately, current clinical predictors of response to anti-TNFs do not satisfactorily predict the response. Genetic background and gene expression are therefore also under investigation [7,8,9,10,11,12,13]. There are several recent reviews on the topic, focusing either on clinical prediction of anti-TNF response [2,4,5,14,15] or summarizing genomic and/or expression data and proposing predictive sets of anti-TNF response markers [16,17,18,19,20].…”