Showing papers by "University of Kiel published in 2019"

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

Abstract: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus

Abstract: Objective To develop new classification criteria for systemic lupus erythematosus (SLE) jointly supported by the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR). Methods This international initiative had four phases. (1) Evaluation of antinuclear antibody (ANA) as an entry criterion through systematic review and meta-regression of the literature and criteria generation through an international Delphi exercise, an early patient cohort and a patient survey. (2) Criteria reduction by Delphi and nominal group technique exercises. (3) Criteria definition and weighting based on criterion performance and on results of a multi-criteria decision analysis. (4) Refinement of weights and threshold scores in a new derivation cohort of 1001 subjects and validation compared with previous criteria in a new validation cohort of 1270 subjects. Results The 2019 EULAR/ACR classification criteria for SLE include positive ANA at least once as obligatory entry criterion; followed by additive weighted criteria grouped in seven clinical (constitutional, haematological, neuropsychiatric, mucocutaneous, serosal, musculoskeletal, renal) and three immunological (antiphospholipid antibodies, complement proteins, SLE-specific antibodies) domains, and weighted from 2 to 10. Patients accumulating ≥10 points are classified. In the validation cohort, the new criteria had a sensitivity of 96.1% and specificity of 93.4%, compared with 82.8% sensitivity and 93.4% specificity of the ACR 1997 and 96.7% sensitivity and 83.7% specificity of the Systemic Lupus International Collaborating Clinics 2012 criteria. Conclusion These new classification criteria were developed using rigorous methodology with multidisciplinary and international input, and have excellent sensitivity and specificity. Use of ANA entry criterion, hierarchically clustered and weighted criteria reflect current thinking about SLE and provide an improved foundation for SLE research.

The IASP classification of chronic pain for ICD-11: chronic neuropathic pain.

Abstract: The upcoming 11th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD) of the World Health Organization (WHO) offers a unique opportunity to improve the representation of painful disorders. For this purpose, the International Association for the Study of Pain (IASP) has convened an interdisciplinary task force of pain specialists. Here, we present the case for a reclassification of nervous system lesions or diseases associated with persistent or recurrent pain for ≥3 months. The new classification lists the most common conditions of peripheral neuropathic pain: trigeminal neuralgia, peripheral nerve injury, painful polyneuropathy, postherpetic neuralgia, and painful radiculopathy. Conditions of central neuropathic pain include pain caused by spinal cord or brain injury, poststroke pain, and pain associated with multiple sclerosis. Diseases not explicitly mentioned in the classification are captured in residual categories of ICD-11. Conditions of chronic neuropathic pain are either insufficiently defined or missing in the current version of the ICD, despite their prevalence and clinical importance. We provide the short definitions of diagnostic entities for which we submitted more detailed content models to the WHO. Definitions and content models were established in collaboration with the Classification Committee of the IASP's Neuropathic Pain Special Interest Group (NeuPSIG). Up to 10% of the general population experience neuropathic pain. The majority of these patients do not receive satisfactory relief with existing treatments. A precise classification of chronic neuropathic pain in ICD-11 is necessary to document this public health need and the therapeutic challenges related to chronic neuropathic pain.

An update on anti-NMDA receptor encephalitis for neurologists and psychiatrists: mechanisms and models.

Abstract: The identification of anti-NMDA receptor (NMDAR) encephalitis about 12 years ago made it possible to recognise that some patients with rapidly progressive psychiatric symptoms or cognitive impairment, seizures, abnormal movements, or coma of unknown cause, had an autoimmune disease. In this disease, autoantibodies serve as a diagnostic marker and alter NMDAR-related synaptic transmission. At symptom onset, distinguishing the disease from a primary psychiatric disorder is challenging. The severity of symptoms often requires intensive care. Other than clinical assessment, no specific prognostic biomarkers exist. The disease is more prevalent in women (with a female to male ratio of around 8:2) and about 37% of patients are younger than 18 years at presentation of the disease. Tumours, usually ovarian teratoma, and herpes simplex encephalitis are known triggers of NMDAR autoimmunity. About 80% of patients improve with immunotherapy and, if needed, tumour removal, but the recovery is slow. Animal models have started to reveal the complexity of the underlying pathogenic mechanisms and will lead to novel treatments beyond immunotherapy. Future studies should aim at identifying prognostic biomarkers and treatments that accelerate recovery.

Sequence and cultivation study of Muribaculaceae reveals novel species, host preference, and functional potential of this yet undescribed family

Abstract: Bacteria within family S24-7 (phylum Bacteroidetes) are dominant in the mouse gut microbiota and detected in the intestine of other animals. Because they had not been cultured until recently and the family classification is still ambiguous, interaction with their host was difficult to study and confusion still exists regarding sequence data annotation. We investigated family S24-7 by combining data from large-scale 16S rRNA gene analysis and from functional and taxonomic studies of metagenomic and cultured species. A total of 685 species was inferred by full-length 16S rRNA gene sequence clustering. While many species could not be assigned ecological habitats (93,045 samples analyzed), the mouse was the most commonly identified host (average of 20% relative abundance and nine co-occurring species). Shotgun metagenomics allowed reconstruction of 59 molecular species, of which 34 were representative of the 16S rRNA gene-derived species clusters. In addition, cultivation efforts allowed isolating five strains representing three species, including two novel taxa. Genome analysis revealed that S24-7 spp. are functionally distinct from neighboring families and versatile with respect to complex carbohydrate degradation. We provide novel data on the diversity, ecology, and description of bacterial family S24-7, for which the name Muribaculaceae is proposed.

Update of the MDS research criteria for prodromal Parkinson's disease.

Abstract: The MDS Research Criteria for Prodromal PD allow the diagnosis of prodromal Parkinson's disease using an evidence-based conceptual framework, which was designed to be updated as new evidence becomes available. New prospective evidence of predictive values of risk and prodromal markers published since 2015 was reviewed and integrated into the criteria. Many of the predictive values (likelihood ratios, LR) remain unchanged. The positive likelihood ratio notably increase for olfactory loss and decreased for substantia nigra hyperechogenicity. Negative likelihood ratio remained largely unchanged for all markers. New levels of diagnostic certainty for neurogenic and symptomatic orthostatic hypotension have been added, which substantially differ in positive likelihood ratio from the original publication. For intermediate strength genetic variants, their age-related penetrance is now incorporated in the calculation of the positive likelihood ratio. Moreover, apart from prospective studies, evidence from cross-sectional case-control genome-wide association studies is also considered (given their likely lack of confounding and reverse causation), and to account for the effect of multiple low-penetrance genetic variants polygenic risk scores are added to the model. Diabetes, global cognitive deficit, physical inactivity, and low plasma urate levels in men enter the criteria as new markers. A web-based prodromal PD risk calculator allows the calculation of probabilities of prodromal PD for individuals. Several promising candidate markers may improve the diagnostic accuracy of prodromal PD in the future. © 2019 International Parkinson and Movement Disorder Society.

Evaluation of variable selection methods for random forests and omics data sets.

Abstract: Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE). In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta. In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings.

Discovery of common and rare genetic risk variants for colorectal cancer

Abstract: To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.

The interplay of landscape composition and configuration: new pathways to manage functional biodiversity and agroecosystem services across Europe

Abstract: Managing agricultural landscapes to support biodiversity and ecosystem services is a key aim of a sustainable agriculture. However, how the spatial arrangement of crop fields and other habitats in landscapes impacts arthropods and their functions is poorly known. Synthesising data from 49 studies (1515 landscapes) across Europe, we examined effects of landscape composition (% habitats) and configuration (edge density) on arthropods in fields and their margins, pest control, pollination and yields. Configuration effects interacted with the proportions of crop and non-crop habitats, and species’ dietary, dispersal and overwintering traits led to contrasting responses to landscape variables. Overall, however, in landscapes with high edge density, 70% of pollinator and 44% of natural enemy species reached highest abundances and pollination and pest control improved 1.7- and 1.4-fold respectively. Arable-dominated landscapes with high edge densities achieved high yields. This suggests that enhancing edge density in European agroecosystems can promote functional biodiversity and yield-enhancing ecosystem services.

Rhizosphere size and shape: Temporal dynamics and spatial stationarity

Abstract: The soil volume affected by roots – the rhizosphere – is one of the most important microbial hotspots determining the processes, dynamics and cycling of carbon (C), nutrients and water in terrestrial ecosystems. Rhizosphere visualization is necessary to understand, localize and quantify the ongoing processes and functions, but quantitative conclusions are very uncertain because of: 1) the continuum of the parameters between the root surface and root-free soil, i.e., there are no sharp borders, 2) differences in the distributions of various parameters (C, nutrients, pH, enzyme and microbial activities, gases, water etc.) across and along roots, 3) temporal changes of the parameters and processes with root growth as well as with water and C flows. In situ techniques: planar optodes, zymography, sensitive gels, 14C and neutron imaging as well as destructive approaches (thin layer slicing) have been used to analyze the rhizosphere extent and the gradients of various physico-chemical and biological characteristics: pH, CO2, O2, redox potential, enzyme activities, content of water, nutrients and excess elements, and organic compounds. A literature analysis allows the conclusion that: i) the rhizosphere extent for most of the parameters assessed by non-destructive visualization techniques is 0.5–4 mm but exceeds 4 mm for gases, nitrate, water and redox potential. ii) The rhizosphere extent of nutrients (N, P) is decoupled from the extent of the corresponding enzyme activities. iii) The imbalance between element flows to and uptake by roots may lead to accumulation of excess elements and formation of root carapaces (e.g. CaCO3 rhizoliths, Fe plaque) ranging up to a few cm. iv) All destructive approaches show a much (3–5 times) larger rhizosphere extent compared to visualization techniques. These conclusions are crucial for a mechanistic understanding of rhizosphere properties and functioning, estimation of the nutrient stocks available to roots, and for rhizosphere modelling considering root growth and architecture. Overall, roots function as ecosystem engineers and build their environment, serving as the main factors shaping rhizosphere extent. Sharp gradients are formed within a few days for nutrients and enzymes, but more time is necessary for the establishment of specific microbial communities. Despite the very strong dynamics of most parameters, their stationarity is reached within a few days because the release of C and enzymes or nutrient uptake are very quickly compensated by utilization by surrounding microorganisms or/and sorption and diffusion processes. We conclude that despite the dynamic nature of each property, the rhizosphere gradients, their extent and shape are quasi-stationary because of the opposite directions of their formation processes.

AlScN: A III-V semiconductor based ferroelectric

Abstract: Ferroelectric switching is unambiguously demonstrated for the first time in a III-V semiconductor based material: Al1-xScxN—A discovery which could help to satisfy the urgent demand for thin film ferroelectrics with high performance and good technological compatibility with generic semiconductor technology which arises from a multitude of memory, micro/nano-actuator, and emerging applications based on controlling electrical polarization. The appearance of ferroelectricity in Al1-xScxN can be related to the continuous distortion of the original wurtzite-type crystal structure towards a layered-hexagonal structure with increasing Sc content and tensile strain, which is expected to be extendable to other III-nitride based solid solutions. Coercive fields which are systematically adjustable by more than 3 MV/cm, high remnant polarizations in excess of 100 μC/cm2—which constitute the first experimental estimate of the previously inaccessible spontaneous polarization in a III-nitride based material, an almost ideally square-like hysteresis resulting in excellent piezoelectric linearity over a wide strain interval from −0.3% to + 0.4% and a paraelectric transition temperature in excess of 600 °C are confirmed. This intriguing combination of properties is to our knowledge as of now unprecedented in the field of polycrystalline ferroelectric thin films and promises to significantly advance the commencing integration of ferroelectric functionality to micro- and nanotechnology, while at the same time providing substantial insight to one of the central open questions of the III-nitride semiconductors—that of their spontaneous polarization.

Towards a comprehensive understanding of new regional industrial path development

Abstract: Path creation is a key concept in economic geography. So far, particularly scholars within evolutionary economic geography have pioneered research on this topic. This paper critically discusses the...

A meta-analysis of genome-wide association studies identifies multiple longevity genes

Abstract: Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) e4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE e2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Deep Learning for the Radiographic Detection of periodontal Bone Loss

Abstract: We applied deep convolutional neural networks (CNNs) to detect periodontal bone loss (PBL) on panoramic dental radiographs. We synthesized a set of 2001 image segments from panoramic radiographs. Our reference test was the measured % of PBL. A deep feed-forward CNN was trained and validated via 10-times repeated group shuffling. Model architectures and hyperparameters were tuned using grid search. The final model was a seven-layer deep neural network, parameterized by a total number of 4,299,651 weights. For comparison, six dentists assessed the image segments for PBL. Averaged over 10 validation folds the mean (SD) classification accuracy of the CNN was 0.81 (0.02). Mean (SD) sensitivity and specificity were 0.81 (0.04), 0.81 (0.05), respectively. The mean (SD) accuracy of the dentists was 0.76 (0.06), but the CNN was not statistically significant superior compared to the examiners (p = 0.067/t-test). Mean sensitivity and specificity of the dentists was 0.92 (0.02) and 0.63 (0.14), respectively. A CNN trained on a limited amount of radiographic image segments showed at least similar discrimination ability as dentists for assessing PBL on panoramic radiographs. Dentists’ diagnostic efforts when using radiographs may be reduced by applying machine-learning based technologies.

Historical increase in agricultural machinery weights enhanced soil stress levels and adversely affected soil functioning

Abstract: Soil compaction caused by vehicular traffic adversely affects key soil functions and ecosystem services that soils provide. Although compaction is a well-recognized problem, it remains challenging to quantify the economic and ecological costs of compaction. The mechanization in agriculture has resulted in a steady increase in weight of farm vehicles. It is reasonable to assume that this has exacerbated soil compaction, but there is little quantitative knowledge on the development of compaction levels in arable soils. To quantify these trends, we use historical records of harvester and tractor weights to simulate how the weight increase has changed soil stresses and bulk density of arable soil, and to predict impacts on the mechanical resistance for root growth and on soil hydraulic properties. Our simulations show a clear increase in soil stress levels with higher bulk density and mechanical penetration resistance, and a decrease in soil hydraulic conductivity in agreement with available data. We show that increased mechanical resistance has resulted in decreased root elongation rates and consequently prolonged the time required for roots to reach a certain soil depth. The historical changes of compaction levels and associated limitations on root elongation rates coincide with a stagnation in crop yields in the 1990s observed for cereals in many countries. Our calculations illustrate that the historical increase in compaction levels has drastically decreased saturated hydraulic conductivity and water storage capacity of subsoils. We speculate that this has contributed to the increase in the incidence and severity of flood events during recent decades in Europe. Finally, we take Sweden as an example and estimate annual compaction costs due to agricultural productivity loss and flooding damage of several hundred M€ yr−1 for Sweden. Considering the continuation of upwards trends in the average weight of farm machinery and the projected increase in extreme weather events, the costs of soil compaction are likely to escalate. The study highlights that we have likely exceeded the acceptable loads, and that future agricultural operations must consider the inherent mechanical limit of soil.

A roadmap for implementation of patient‐centered digital outcome measures in Parkinson's disease obtained using mobile health technologies

Abstract: Obtaining reliable longitudinal information about everyday functioning from individuals with Parkinson's disease (PD) in natural environments is critical for clinical care and research. Despite advances in mobile health technologies, the implementation of digital outcome measures is hindered by a lack of consensus on the type and scope of measures, the most appropriate approach for data capture (eg, in clinic or at home), and the extraction of timely information that meets the needs of patients, clinicians, caregivers, and health care regulators. The Movement Disorder Society Task Force on Technology proposes the following objectives to facilitate the adoption of mobile health technologies: (1) identification of patient-centered and clinically relevant digital outcomes; (2) selection criteria for device combinations that offer an acceptable benefit-to-burden ratio to patients and that deliver reliable, clinically relevant insights; (3) development of an accessible, scalable, and secure platform for data integration and data analytics; and (4) agreement on a pathway for approval by regulators, adoption into e-health systems and implementation by health care organizations. We have developed a tentative roadmap that addresses these needs by providing the following deliverables: (1) results and interpretation of an online survey to define patient-relevant endpoints, (2) agreement on the selection criteria for use of device combinations, (3) an example of an open-source platform for integrating mobile health technology output, and (4) recommendations for assessing readiness for deployment of promising devices and algorithms suitable for regulatory approval. This concrete implementation guidance, harmonizing the collaborative endeavor among stakeholders, can improve assessments of individuals with PD, tailor symptomatic therapy, and enhance health care outcomes. © 2019 International Parkinson and Movement Disorder Society.

The Refined Consensus Model of Pedagogical Content Knowledge in Science Education

Abstract: This chapter chronicles the developmental journey of a model for teacher pedagogical content knowledge (PCK) in science education, now identified as the Refined Consensus Model (RCM) of PCK, that represents the contributions and collective thinking of two dozen international researchers in science teacher education. This journey starts by recounting the process that led to an update and significant revisions to the model of teacher professional knowledge and skills including PCK (informally known as the 2012 Consensus Model (CM)). Then, we unpack and describe the different components of the model in both diagrammatic form and in explanatory text. The RCM describes the complex layers of knowledge and experiences that shape and inform teachers’ practice and mediate student outcomes. A key feature of this model is the identification of three distinct realms of PCK—collective PCK, personal PCK, and enacted PCK. These realms are used to situate the specialised professional knowledge held by different science educators in different settings ranging from the collected knowledge understood by many to the unique subset of knowledge an individual teacher draws upon. The model also recognises that the broader professional knowledge bases are foundational to teacher PCK while the learning context a teacher is working in can greatly influence the teaching and learning that takes place.

Toward an Atomic-Scale Understanding of Electrochemical Interface Structure and Dynamics

Abstract: For the knowledged-based development of electrochemical processes, a better fundamental understanding of the interfaces between electrodes and electrolytes is necessary. This requires insight into the interface structure and dynamics on the atomic-scale, including that of the liquid electrolyte in the near-surface region, i.e., in the inner and outer part of the electrochemical double layer. This perspective describes current studies of simple and well-defined electrochemical interfaces by first-principles electronic structure calculations and in situ structure-sensitive methods. It is shown that these experimental and theoretical studies are now approaching a level, where they can operate on the same footing, making direct comparison of the obtained results feasible. Using selected examples, progress in clarifying the structure and dynamics of the double layer, of adsorbed species on electrode surfaces, and of initial steps in electrochemical phase formation processes is discussed.

On-Board Microgrids for the More Electric Aircraft—Technology Review

Abstract: This paper presents an overview of technology related to on-board microgrids for the more electric aircraft. All aircraft use an isolated system, where security of supply and power density represents the main requirements. Different distribution systems (ac and dc) and voltage levels coexist, and power converters have the central role in connecting them with high reliability and high power density. Ensuring the safety of supply with a limited redundancy is one of the targets of the system design since it allows increasing the power density. This main challenge is often tackled with proper load management and advanced control strategies, as highlighted in this paper.

Awakening: Predicting external stimulation to force transitions between different brain states.

Abstract: A fundamental problem in systems neuroscience is how to force a transition from one brain state to another by external driven stimulation in, for example, wakefulness, sleep, coma, or neuropsychiatric diseases. This requires a quantitative and robust definition of a brain state, which has so far proven elusive. Here, we provide such a definition, which, together with whole-brain modeling, permits the systematic study in silico of how simulated brain stimulation can force transitions between different brain states in humans. Specifically, we use a unique neuroimaging dataset of human sleep to systematically investigate where to stimulate the brain to force an awakening of the human sleeping brain and vice versa. We show where this is possible using a definition of a brain state as an ensemble of "metastable substates," each with a probabilistic stability and occurrence frequency fitted by a generative whole-brain model, fine-tuned on the basis of the effective connectivity. Given the biophysical limitations of direct electrical stimulation (DES) of microcircuits, this opens exciting possibilities for discovering stimulation targets and selecting connectivity patterns that can ensure propagation of DES-induced neural excitation, potentially making it possible to create awakenings from complex cases of brain injury.

A multi-criteria approach for assessing urban flood resilience in Tehran, Iran

Abstract: Operationalizing the concept of urban disaster resilience is a major milestone toward understanding both the characteristics that contribute to the resilience of cities to natural hazards and the interactions required to build and sustain it. While the measurement of urban disaster resilience has recently gained much attention, there is so far no optimal approach for operationalizing this concept and therefore there is a need to conduct more empirical studies on what constitutes disaster resilience and how to assess it. In this study, a resilience assessment focuses on the inherent characteristics and capacities of Tehran in the context of flash floods from surface water or from the overflow of rivers. The measurement approach is based on constructing a composite index based on six resilience dimensions social, economic, institutional, infrastructural, community capital and environmental of community flood resilience. This follows by developing a hybrid multi-criteria decision-making method. The applied method is a combination of the AHP for prioritizing the selected indicators and the TOPSIS tools in order to get Tehran's urban districts ranked based on their resilience levels. Data were mostly from the Statistical Center of Iran and Tehran Municipality's accessible data sources. The results clarify that Districts 6 and 22 are comparatively the most resilient districts, while District 1 is the only district with the lowest level of resilience. Such place-based assessments have an opportunity to track community performance over time and provide the tool to decision-makers in order to integrate resilience thinking into urban development and resilience-oriented urban planning.

Vedolizumab is associated with changes in innate rather than adaptive immunity in patients with inflammatory bowel disease

Abstract: Objective Vedolizumab, a monoclonal antibody directed against the integrin heterodimer α4β7, is approved for the treatment of Crohn’s disease and ulcerative colitis. The efficacy of vedolizumab has been suggested to result from inhibition of intestinal T cell trafficking although human data to support this conclusion are scarce. We therefore performed a comprehensive analysis of vedolizumab-induced alterations in mucosal and systemic immunity in patients with inflammatory bowel disease (IBD), using anti-inflammatory therapy with the TNFα antibody infliximab as control. Design Immunophenotyping, immunohistochemistry, T cell receptor profiling and RNA sequencing were performed using blood and colonic biopsies from patients with IBD before and during treatment with vedolizumab (n=18) or, as control, the anti-TNFα antibody infliximab (n=20). Leucocyte trafficking in vivo was assessed using single photon emission computed tomography and endomicroscopy. Results Vedolizumab was not associated with alterations in the abundance or phenotype of lamina propria T cells and did not affect the mucosal T cell repertoire or leucocyte trafficking in vivo. Surprisingly, however, α4β7 antibody treatment was associated with substantial effects on innate immunity including changes in macrophage populations and pronounced alterations in the expression of molecules involved in microbial sensing, chemoattraction and regulation of the innate effector response. These effects were specific to vedolizumab, not observed in response to the TNFα antibody infliximab, and associated with inhibition of intestinal inflammation. Conclusion Our findings suggest that modulation of innate immunity contributes to the therapeutic efficacy of vedolizumab in IBD. Trial registration number NCT02694588