Genomic medicine in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a term for two conditions (Crohn’s disease [CD] and ulcerative colitis [UC]) that are characterised by chronic inflammation of the gastrointestinal tract. Clinical symptoms of IBD include recurrent episodes of abdominal pain, diarrhoea, and weight loss. The exact cause of IBD remains unknown, but IBD is likely to be the result of a defective immune response to enteric bacteria in a genetically susceptibly individual. The first part of this thesis has focused on causal genes for the onset of IBD, and it has been demonstrated that specific intestinal T-cell subsets express these genes. In turn, it is hypothesised that these specific immune cell subsets are detrimental to disease mechanisms, and therefore potential targets for therapeutic intervention. The course IBD takes over time is unpredictable and heterogeneous, and there is a need for better patient stratification to aid clinical decision making. In the second part of this thesis it has been demonstrated that patients with a high genetic risk of disease susceptibility are also at risk of specific clinical aspects of disease such as disease location or disease behaviour. Adverse reactions and therapeutic failure are common in the management of IBD. In the final part of this thesis, several genetic mutations that predict adverse reactions to therapies used in the management of IBD have been identified. It has been demonstrated that if patients were to be genotyped prior to initiation of treatment, subsequent genotype-based therapies would lead to a decrease in adverse reactions

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

In patients with coronary artery stenoses of intermediate severity, the functional significance needs to be determined. Fractional flow reserve (FFR) measurement, performed during invasive coronary angiography (ICA), is most often used in clinical practice. To reduce the number of ICA procedures, we present a method for automatic identification of patients with functionally significant coronary artery stenoses, employing deep learning analysis of the left ventricle (LV) myocardium in rest coronary CT angiography (CCTA). The study includes consecutively acquired CCTA scans of 166 patients with FFR measurements. To identify patients with a functionally significant coronary artery stenosis, analysis is performed in several stages. First, the LV myocardium is segmented using a multiscale convolutional neural network (CNN). To characterize the segmented LV myocardium, it is subsequently encoded using unsupervised convolutional autoencoder (CAE). Thereafter, patients are classified according to the presence of functionally significant stenosis using an SVM classifier based on the extracted and clustered encodings. Quantitative evaluation of LV myocardium segmentation in 20 images resulted in an average Dice coefficient of 0.91 and an average mean absolute distance between the segmented and reference LV boundaries of 0.7 mm. Classification of patients was evaluated in the remaining 126 CCTA scans in 50 10-fold cross-validation experiments and resulted in an area under the receiver operating characteristic curve of 0.74 +- 0.02. At sensitivity levels 0.60, 0.70 and 0.80, the corresponding specificity was 0.77, 0.71 and 0.59, respectively. The results demonstrate that automatic analysis of the LV myocardium in a single CCTA scan acquired at rest, without assessment of the anatomy of the coronary arteries, can be used to identify patients with functionally significant coronary artery stenosis.Comment: This paper was submitted in April 2017 and accepted in November 2017 for publication in Medical Image Analysis. Please cite as: Zreik et al., Medical Image Analysis, 2018, vol. 44, pp. 72-8

Serial Morphological and Functional Assessment of Drug-Eluting Balloon for In-Stent Restenotic Lesions Mechanisms of Action Evaluated With Angiography, Optical Coherence Tomography, and Fractional Flow Reserve

ObjectivesThis study sought to elucidate the underlying mechanism through which drug-eluting balloons (DEB) restore coronary blood flow, by assessing the coronary vessel before, immediately after, and at 6-month follow-up with angiography, optical coherence tomography (OCT), and fractional flow reserve (FFR).BackgroundIn-stent restenosis (ISR) treatment remains challenging. Drug-eluting balloons have been shown to be a valid treatment option in several studies. These studies focused on efficiency of the device, whereas the mechanisms of action of DEB in ISR treatment have not been investigated.MethodsIn this prospective, single-center observational study, patients with ISR were treated with a second-generation DEB. Serial angiographic, OCT, and FFR measurements were performed before and after the procedure, as well as at 6-month follow-up.ResultsTwenty-five patients were assigned to DEB treatment, with an angiographic and device success of 100% and 92%, respectively. Late luminal loss was 0.01 ± 0.43 mm. Median percent changes [interquartile range] between pre-and post-procedure, and post-procedure and follow-up were, respectively: lumen volume 75.1% increase [43.7 to 115.0], and 8% increase [−14.0 to 25.8]; stent volume 23.7% increase [15.5 to 40.0], and −1.2% decrease [−6.9 to 5.9]; and neointimal volume −14.4% decrease [−29.2 to −9.5], and −15.8% decrease [−38.1 to 28.3]. The FFR gradient along the treated stent (difference in FFR between the distal and the proximal stent edge) was 0.37 ± 0.18 pre-procedure, 0.06 ± 0.04 post-procedure, and 0.05 ± 0.05 at follow-up. In all post-procedural OCT images, intrastent dissections were seen, which were sealed at follow-up OCT.ConclusionsDEB restore coronary blood flow by means of a short-term mechanical effect, causing an increase in lumen and stent volumes and compression of neointimal hyperplasia (with intra-stent dissections). Due to the local drug effect, patency persists and may even improve at follow-up, with further increase in lumen volume, decrease in neointimal volume, and complete sealing of neointimal dissections

Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography

In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically established through fractional flow reserve (FFR) measurement, performed during invasive coronary angiography (ICA). We present a method for automatic and non-invasive detection of patients requiring ICA, employing deep unsupervised analysis of complete coronary arteries in cardiac CT angiography (CCTA) images. We retrospectively collected CCTA scans of 187 patients, 137 of them underwent invasive FFR measurement in 192 different coronary arteries. These FFR measurements served as a reference standard for the functional significance of the coronary stenosis. The centerlines of the coronary arteries were extracted and used to reconstruct straightened multi-planar reformatted (MPR) volumes. To automatically identify arteries with functionally significant stenosis that require ICA, each MPR volume was encoded into a fixed number of encodings using two disjoint 3D and 1D convolutional autoencoders performing spatial and sequential encodings, respectively. Thereafter, these encodings were employed to classify arteries using a support vector machine classifier. The detection of coronary arteries requiring invasive evaluation, evaluated using repeated cross-validation experiments, resulted in an area under the receiver operating characteristic curve of $0.81 \pm 0.02$ on the artery-level, and $0.87 \pm 0.02$ on the patient-level. The results demonstrate the feasibility of automatic non-invasive detection of patients that require ICA and possibly subsequent coronary artery intervention. This could potentially reduce the number of patients that unnecessarily undergo ICA.Comment: This work has been accepted to IEEE TMI for publicatio

Polygenetic risk scores do not add predictive power to clinical models for response to anti-TNFα therapy in inflammatory bowel disease

BACKGROUND: Anti-tumour necrosis factor alpha (TNFα) therapy is widely used in the management of Crohn’s disease (CD) and ulcerative colitis (UC). However, up to a third of patients do not respond to induction therapy and another third of patients lose response over time. To aid patient stratification, polygenetic risk scores have been identified as predictors of response to anti-TNFα therapy. We aimed to replicate the association between polygenetic risk scores and response to anti-TNFα therapy in an independent cohort of patients, to establish its clinical validity. MATERIALS AND METHODS: Primary non-response, primary response, durable response and loss of response to anti-TNFα therapy was retrospectively assessed for each patient using stringent definitions. Genome wide genotyping was performed and previously described polygenetic risk scores for primary non-response and durable response were calculated. We compared polygenetic risk scores between patients with primary response and primary non-response, and between patients with durable response and loss of response, using separate analyses for CD and UC. RESULTS: Out of 334 patients with CD, 15 (4%) patients met criteria for primary non-response, 221 (66%) for primary response, 115 (34%) for durable response and 35 (10%) for loss of response. Out of 112 patients with UC, 12 (11%) met criteria for primary non-response, 68 (61%) for primary response, 19 (17%) for durable response and 20 (18%) for loss of response. No significant differences in polygenetic risk scores were found between primary non-responders and primary responders, and between durable responders and loss of responders. CONCLUSIONS: We could not replicate the previously reported association between polygenetic risk scores and response to anti-TNFα therapy in an independent cohort of patients with CD or UC. Currently, there is insufficient evidence to use polygenetic risk scores to predict response to anti-TNFα therapy in patients with IBD

Donor tobacco smoking is associated with postoperative thrombosis after primary liver transplantation

Background: Thrombosis after liver transplantation is a leading cause of graft loss, morbidity, and mortality. Several known recipient- and surgery-related characteristics have been associated with increased risk of thrombosis after transplantation. Potential donor-related risk factors, however, remain largely undefined. Objectives: We aimed to identify risk factors for early post-transplantation thrombosis ('90 days) and to determine the impact of early postoperative thrombosis on long-term graft and patient survival. Patients/Methods: A post hoc analysis was performed of an observational cohort study including all primary, adult liver transplantations performed between 1993 and 2018. Donor-, recipient-, and surgery-related characteristics were collected. Competing risk model analyses and multivariable regression analyses were performed to identify risk factors for developing early post-transplant thrombosis and graft failure. Results: From a total of 748 adult liver transplantations, 58 recipients (7.8%) developed a thrombosis after a median of 7 days. Post-transplantation thrombotic events included 25 hepatic artery thromboses, 13 portal vein thromboses, and 22 other thrombotic complications. Donor history of smoking was independently associated with early postoperative thrombosis (odds ratio [OR] 2.42; 95% confidence interval [CI], 1.29-4.52). Development of early post-transplant thrombosis was independently associated with patient mortality (hazard ratio [HR] 3.61; 95% CI 1.54-8.46) and graft failure (HR 5.80, 95% CI 3.26-10.33), respectively. Conclusion: Donor history of smoking conveys a more than two-fold increased risk of thrombosis after liver transplantation, independent of other factors. Post-transplant thrombosis was independently associated with decreased patient and graft survival

Latent cytomegalovirus infection does not influence long-term disease outcomes in inflammatory bowel disease, but is associated with later onset of disease

Objectives: Cytomegalovirus (CMV) infection is common in the general population. CMV infection negatively affects disease course in transplant recipients and HIV patients. Whereas primary CMV infections may occur sporadically in seronegative patients, all seropositive patients with inflammatory bowel syndrome (IBD) are at risk for CMV reactivation due to the inflammatory mucosal and use of immunosuppressive medication. It is unclear whether latent CMV infection, and risk of reactivations, influences long-term disease outcomes. In this study, we aim to explore whether CMV infection affects disease outcomes in IBD patients. Methods: We performed a cross-sectional cohort study with 1404 patients with IBD from a single center. Clinical characteristics and disease outcomes were prospectively collected. We scrutinized CMV serology test results and performed additional CMV serology testing if serum was available. Results: Out of 699 IBD patients with CMV serology, 303 (43.3%) were seropositive, comparable to the general Dutch population. CMV seropositivity was associated with older age, longer IBD disease duration, non-Western origin, birth outside the Netherlands and a lower educational level (p-values ≤.004). CMV seropositivity was not associated with more complicated long-term disease outcomes of IBD (p-values >.05). Seropositive patients presented with symptoms and were diagnosed at an older age compared to seronegative patients (p-values <.01). Conclusions: CMV seropositivity does not influence disease outcomes of IBD patients and seems to be associated with a delay in IBD onset. Guidelines regarding CMV screening in patients with IBD are currently based on a low level of evidence. These data support the recommendation that routine CMV serology measurement is not necessary in the clinical care of IBD