Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression

Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks

The UKB envirome of depression

Major depressive disorder is a result of the complex interplay between a large number of environmental and genetic factors but the comprehensive analysis of contributing environmental factors is still an open challenge. The primary aim of this work was to create a Bayesian dependency map of environmental factors of depression, including life stress, social and lifestyle factors, using the UK Biobank data to determine direct dependencies and to characterize mediating or interacting effects of other mental health, metabolic or pain conditions. As a complementary approach, we also investigated the non-linear, synergistic multi-factorial risk of the UKB envirome on depression using deep neural network architectures. Our results showed that a surprisingly small number of core factors mediate the effects of the envirome on lifetime depression: neuroticism, current depressive symptoms, parental depression, body fat, while life stress and household income have weak direct effects. Current depressive symptom showed strong or moderate direct relationships with life stress, pain conditions, falls, age, insomnia, weight change, satisfaction, confiding in someone, exercise, sports and Townsend index. In conclusion, the majority of envirome exerts their effects in a dynamic network via transitive, interactive and synergistic relationships explaining why environmental effects may be obscured in studies which consider them individually

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

The age-related somatic evolution of clonal haematopoiesis

Over a lifetime, human cells continually acquire mutations, some of which may alter cell division's complex homeostasis and lead to the subsequent expansion of somatic clones. Such expansions are frequent in the haematopoietic system and become detectable as we age. Haematopoiesis is a complex and hierarchical system that generates millions of functionally diverse cells daily. This multi-tiered system allows for the rapid regeneration of our blood system in response to stress whilst protecting the pool of long-lived haematopoietic stem and progenitor cells (HSPCs) from excessive replicative stress. Haematopoiesis can function with high fidelity for many decades but is inevitably challenged by ageing and the time-dependent accumulation of somatic variation. Clonal Haematopoiesis of Indeterminate Potential (CHIP) is defined as the expansion of HSPCs in healthy-aged individuals that results from genetic alterations. Although mostly inconsequential, the constant rate of the acquisition of mutations in HSPCs (17 mutations/year) leads to an increasing probability, with respect to age, of a variant occurring in a gene that dysregulates the tightly maintained mechanism of haematopoiesis. In healthy individuals, the differentiated cells that comprise our blood are the progeny of equally contributing stem cells that produce a genetically diverse, polyclonal population. CHIP, however, is marked by the population of blood cells becoming increasingly dominated by single (or multiple) genetic clone(s) that are genotypically identical. In 2014, several independent studies confirmed that CHIP is a condition that increases with age: more than 10% of the population over 65 years are affected, with a prevalence that increases dramatically over subsequent decades. It has been associated with all-cause mortality, cardiovascular disease and haematological malignancies – a risk that scales with clone size. Observing the relationship between CHIP and age-related pathologies, we sought to test the relationship between clonal haematopoiesis and ageing using a range of published epigenetic clocks (which use DNA methylation states to predict biological age) to assess any association with biological ageing. In Robertson et al., we characterised the landscape of somatic mutations in a range of core haematopoietic marker genes in the Lothian Birth Cohorts (LBCs). The LBCs are two parallel studies of ageing that consist of individuals over 70 and 79 years, in LBC36 and LBC21, respectively. We observed a significant association with biological ageing in several published cell-intrinsic clocks in participants that harboured a mutation in one of the six most prevalent CHIP genes versus our control group. CHIP status was associated with a significant increase in Horvath age acceleration: with an increase of 4.5 (SE 0.9) years in LBC1936 and 3.7 (SE 1.2) years in LBC1921 (p = 2.3 x 10-6 and 2.5 x 10-3, respectively). In addition, we note significant epigenetic age accelerations in both DNMT3A and TET2 in isolation – the most commonly affected genes in clonal haematopoiesis. This result might indicate that CHIP is either driven or a driver of systemic ageing, explaining its links to non-haematological age-dependent pathologies. A triptych of fundamental forces shape evolution: mutation, drift and selection. Whilst the first two are essentially stochastic processes, the third is the driving force: aiming to maximize fitness within an environment. Currently, it’s not understood whether mutations in differing CHIP genes lead to distinct fitness advantages that would lead to patient stratification. Since mutations in HSPCs often instigate leukaemia, we hypothesize that HSC fitness substantially contributes to the transformation to disease states. We again leverage the LBCs, using a particularly unique aspect of their curation - the collection of peripheral blood over 12 years of later life - to develop a longitudinal assay for HSPC fitness using error-corrected sequencing. We then create a novel method we call the likelihood-based filter for time series data (LiFT) to determine fitness effects across our longitudinal data, quantifying the growth potential of somatic mutations within each participant. This approach discriminates naturally drifting populations of cells that typically harbour synonymous or non-functional variants and those that harbour driver mutations that give rise to rapidly growing clones. We characterise the fitness effects of mutations in many known CHIP driver genes and observe that differences in gene-specific fitness effects outweigh inter-individual variation, which could constitute a new method of personalised clinical management. This work has shown that CHIP confers a strong association with biological ageing through the prism of epigenetic clocks. Furthermore, we have begun characterising the fitness effects of genes that characterise CHIP whilst beginning to understand the molecular mechanisms behind their distinct fitness effects. We hope this should aid in a greater understanding of the pathogenesis of CHIP and assist in the improved stratification of patients