Variation in Interleukin 6 Receptor Gene Associates with Risk of Crohn’s Disease and Ulcerative Colitis

Interleukin 6 (IL6) is an inflammatory cytokine; signaling via its receptor (IL6R) is believed to contribute to development of inflammatory bowel diseases (IBD). The single nucleotide polymorphism rs2228145 in IL6R associates with increased levels of soluble IL6R (s-IL6R), as well as reduced IL6R signaling and risk of inflammatory disorders; its effects are similar to those of a therapeutic monoclonal antibody that blocks IL6R signaling. We used the effect of rs2228145 on s-IL6R level as an indirect marker to investigate whether reduced IL6R signaling associates with risk of ulcerative colitis (UC) or Crohn’s disease (CD). In a genome-wide meta-analysis of 20,550 patients with CD, 17647 patients with UC, and more than 40,000 individuals without IBD (controls), we found that rs2228145 (scaled to a 2-fold increase in s-IL6R) was associated with reduced risk of CD (odds ratio, 0.876; 95% CI, 0.822–0.933; P=.00003) or UC (odds ratio, 0.932; 95% CI, 0.875–0.996; P=.036). These findings indicate that therapeutics designed to block IL6R signaling might be effective in treatment of IBD

Multiple jejuno-jejunal fistulae of uncertain origin: a case report

A 43 year-old male patient presented with small bowel obstruction while being treated for cervical tuberculous lymphadenopathy. Laparotomy revealed multiple adhesions and multiple jejuno-jejunal fistulae. Absence of previous abdominal surgery or other abdominal insult favoured an 'idiopathic' origin of these unusual lesions, although treated tuberculosis may have been the underlying cause. To the best of our knowledge this intestinal condition has never previously been reported in the medical literature

Progress in noncommutative function theory

In this expository paper we describe the study of certain non-self-adjoint operator algebras, the Hardy algebras, and their representation theory. We view these algebras as algebras of (operator valued) functions on their spaces of representations. We will show that these spaces of representations can be parameterized as unit balls of certain $W^{*}$-correspondences and the functions can be viewed as Schur class operator functions on these balls. We will provide evidence to show that the elements in these (non commutative) Hardy algebras behave very much like bounded analytic functions and the study of these algebras should be viewed as noncommutative function theory

How to estimate the association between change in a risk factor and a health outcome?

Estimating the effect of a change in a particular risk factor and a chronic disease requires information on the risk factor from two time points; the enrolment and the first follow-up. When using observational data to study the effect of such an exposure (change in risk factor) extra complications arise, namely (i) when is time zero? and (ii) which information on confounders should we account for in this type of analysis? From enrolment or the 1st follow-up? Or from both?. The combination of these questions has proven to be very challenging. Researchers have applied different methodologies with mixed success, because the different choices made when answering these questions induce systematic bias. Here we review these methodologies and highlight the sources of bias in each type of analysis. We discuss the advantages and the limitations of each method ending by making our recommendations on the analysis plan

Alterations of Erythrocyte Superoxide Dismutase activity in patients suffering from asthma attacks

Background. Oxidant-antioxidant imbalance may play an important role in the development and progression of bronchial asthma. However, the role of blood antioxidants especially in asthma exacerbation has not been fully discussed. Objective. This study examines a part of the intracellular antioxidant defense mechanism in asthmatic patients admitted to hospital due to severe exacerbation of their disease. Methods. Peripheral blood Erythrocyte Superoxide Dismutase (SOD) activity was measured in 38 patients (33 men - 5 women, with a mean age of 56±2.8 yrs), using a colorimetric method. On the days of admission and discharge the Forced Expiratory Volume in 1 second (FEV1) and the Partial arterial Oxygen pressure (PaO2) were recorded and correlated with SOD activity at the same time. Results. A statistically significant decrease of SOD activity was observed on the day of admission compared to SOD activity on the day of discharge (43.64±31.78 vs. 96.16±54.05 units/ml, p<0.001), suggesting the presence of oxidative stress during an asthma attack. A statistically significant correlation was observed between FEV1 on admission and SOD activity at the same time (r=0.57, p<0.001). Furthermore, SOD activity on admission was correlated with PaO2 on discharge (r=0.55, p<0.001), as well as SOD on discharge with PaO2 on discharge (r=0.53, p=0.001). Conclusions. Decreased systemic erythrocyte SOD activity was observed during asthma attacks. This activity was correlated with severity criteria such as FEV1 and PaO2. Therefore, it seems that measurement of SOD activity could be a useful tool in the evaluation of an asthma attack. The supplementary administration of antioxidants in the future needs further clarification

On the estimation of the effect of weight change on a health outcome using observational data, by utlilising the target trial emulation framework

Background/Objectives: When studying the effect of weight change between two time points on a health outcome using observational data, two main problems arise initially (i) ‘when is time zero?’ and (ii) ‘which confounders should we account for?’ From the baseline date or the 1st follow-up (when the weight change can be measured)? Different methods have been previously used in the literature that carry different sources of bias and hence produce different results. Methods: We utilised the target trial emulation framework and considered weight change as a hypothetical intervention. First, we used a simplified example from a hypothetical randomised trial where no modelling is required. Then we simulated data from an observational study where modelling is needed. We demonstrate the problems of each of these methods and suggest a strategy. Interventions: weight loss/gain vs maintenance. Results: The recommended method defines time-zero at enrolment, but adjustment for confounders (or exclusion of individuals based on levels of confounders) should be performed both at enrolment and the 1st follow-up. Conclusions: The implementation of our suggested method [adjusting for (or excluding based on) confounders measured both at baseline and the 1st follow-up] can help researchers attenuate bias by avoiding some common pitfalls. Other methods that have been widely used in the past to estimate the effect of weight change on a health outcome are more biased. However, two issues remain (i) the exposure is not well-defined as there are different ways of changing weight (however we tried to reduce this problem by excluding individuals who develop a chronic disease); and (ii) immortal time bias, which may be small if the time to first follow up is short

'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV)

Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement