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Heart failure—either with reduced or preserved ejection fraction (HFrEF/HFpEF)—is a clinical syndrome of multifactorial and gender-dependent aetiology, indicating the insufficiency of the heart to pump blood adequately to maintain blood flow to meet the body's needs. Typical symptoms commonly include shortness of breath, excessive fatigue with impaired exercise capacity, and peripheral oedema, thereby alluding to the fact that heart failure is a syndrome that affects multiple organ systems. Patients suffering from progressed heart failure have a very limited life expectancy, lower than that of numerous cancer types. In this position paper, we provide an overview regarding interactions between the heart and other organ systems, the clinical evidence, underlying mechanisms, potential available or yet-to-establish animal models to study such interactions and finally discuss potential new drug interventions to be developed in the future. Our working group suggests that more experimental research is required to understand the individual molecular mechanisms underlying heart failure and reinforces the urgency for tailored therapeutic interventions that target not only the heart but also other related affected organ systems to effectively treat heart failure as a clinical syndrome that affects and involves multiple organs. [ABSTRACT FROM AUTHOR]

This paper seeks to clarify one of the deepest questions about the source or ground of normativity, while also presenting an essence-based approach to answering it. We call it the 'Arché Question.' Though all metanormative theories must address this question, very few realists have explicitly grappled with the challenge it poses; those who have appear to deny any need to give an answer. After critically discussing extant realist responses, this paper outlines an essence-based approach to answering the Arché Question that draws on theoretical resources forged in recent advances in post-modal metaphysics. [ABSTRACT FROM AUTHOR]

Background Although many musicians suffer from musculoskeletal disorders, aetiological factors are unclear. Aims To systematically search for and synthesize the best available evidence on risk factors for musculoskeletal disorders in musicians. Methods A database search was performed in PubMed, EMBASE, CINAHL, Pedro, OTseeker and Psychinfo. A manual search was conducted in the journals Medical Problems of Performing Artists and Psychology of Music. Studies with an objective to investigate determinants associated with playing-related musculoskeletal disorders were included. Papers were selected based on adequacy of statistical methods for the purpose of the study. Search, first screening and selection were performed by one author. Two reviewers independently performed the final selection using full-text reports. Methodological quality assessment was performed by two reviewers independently. Results One case-control and 14 cross-sectional studies were included. Methodological quality was in general low. Large heterogeneity existed in study design, population, measurement of determinant and outcome and analysis techniques. Data were presented descriptively. Consistent results were found indicating that previous musculoskeletal injury, music performance anxiety, high levels of stress and being a female playing a stringed instrument seemed to be associated with more musculoskeletal disorders. Influence over or support at work, orchestra category/status, exercise behaviour and cigarette smoking seemed to be unrelated with musculoskeletal disorders. No conclusions could be made on causality, as the current data only represent cross-sectional associations. Conclusions Because of lack of prospective studies, no causal relations could be identified in the aetiology of (playing-related) musculoskeletal disorders in instrumental musicians. [ABSTRACT FROM AUTHOR]

Motivation: Exploring the potential long noncoding RNA (lncRNA)-disease associations (LDAs) plays a critical role for understanding disease etiology and pathogenesis. Given the high cost of biological experiments, developing a computational method is a practical necessity to effectively accelerate experimental screening process of candidate LDAs. However, under the high sparsity of LDA dataset, many computational models hardly exploit enough knowledge to learn comprehensive patterns of node representations. Moreover, although the metapath-based GNN has been recently introduced into LDA prediction, it discards intermediate nodes along the meta-path and results in information loss. Results: This paper presents a new multi-view contrastive heterogeneous graph attention network (GAT) for lncRNA-disease association prediction, MCHNLDA for brevity. Specifically, MCHNLDA firstly leverages rich biological data sources of lncRNA, gene and disease to construct two-view graphs, feature structural graph of feature schema view and lncRNA-gene-disease heterogeneous graph of network topology view. Then, we design a cross-contrastive learning task to collaboratively guide graph embeddings of the two views without relying on any labels. In this way, we can pull closer the nodes of similar features and network topology, and push other nodes away. Furthermore, we propose a heterogeneous contextual GAT, where long short-term memory network is incorporated into attention mechanism to effectively capture sequential structure information along the meta-path. Extensive experimental comparisons against several state-of-the-art methods show the effectiveness of proposed framework.The code and data of proposed framework is freely available at  https://github.com/zhaoxs686/MCHNLDA. [ABSTRACT FROM AUTHOR]

With the development of research on the complex aetiology of many diseases, computational drug repositioning methodology has proven to be a shortcut to costly and inefficient traditional methods. Therefore, developing more promising computational methods is indispensable for finding new candidate diseases to treat with existing drugs. In this paper, a model integrating a new variant of message passing neural network and a novel-gated fusion mechanism called GLGMPNN is proposed for drug–disease association prediction. First, a light-gated message passing neural network (LGMPNN), including message passing, aggregation and updating, is proposed to separately extract multiple pieces of information from the similarity networks and the association network. Then, a gated fusion mechanism consisting of a forget gate and an output gate is applied to integrate the multiple pieces of information to extent. The forget gate calculated by the multiple embeddings is built to integrate the association information into the similarity information. Furthermore, the final node representations are controlled by the output gate, which fuses the topology information of the networks and the initial similarity information. Finally, a bilinear decoder is adopted to reconstruct an adjacency matrix for drug–disease associations. Evaluated by 10-fold cross-validations, GLGMPNN achieves excellent performance compared with the current models. The following studies show that our model can effectively discover novel drug–disease associations. [ABSTRACT FROM AUTHOR]

Summary: Background: Epidemiological studies indicate that gene–environment interactions play a role in atopic dermatitis (AD). Objectives: To review the evidence for gene–environment interactions in AD aetiology, focusing on filaggrin (FLG) loss‐of‐function mutations. Methods: A systematic search from inception to September 2018 in Embase, MEDLINE and BIOSIS was performed. Search terms included all synonyms for AD and filaggrin/FLG; any genetic or epidemiological study design using any statistical methods were included. Quality assessment using criteria modified from guidance (ROBINS‐I and Human Genome Epidemiology Network) for nonrandomized and genetic studies was completed, including consideration of power. Heterogeneity of study design and analyses precluded the use of meta‐analysis. Results: Of 1817 papers identified, 12 studies fulfilled the inclusion criteria required and performed formal interaction testing. There was some evidence for FLG–environment interactions in six of the studies (P‐value for interaction ≤ 0·05), including early‐life cat ownership, older siblings, water hardness, phthalate exposure, higher urinary phthalate metabolite levels (which all increased AD risk additional to FLG null genotype) and prolonged breastfeeding (which decreased AD risk in the context of FLG null genotype). Major limitations of published studies were the low numbers of individuals (ranging from five to 94) with AD and FLG loss‐of‐function mutations and exposure to specific environmental factors, and variation in exposure definitions. Conclusions: Evidence on FLG–environment interactions in AD aetiology is limited. However, many of the studies lacked large enough sample sizes to assess these interactions fully. Further research is needed with larger sample sizes and clearly defined exposure assessment. Linked Comment: Park and Seo. Br J Dermatol 2020; 183:411. What's already known about this topic? Gene–environment interactions are considered important in the aetiology of atopic dermatitis.Loss‐of-function mutations in the gene coding filaggrin (FLG) are the most consistently reported genetic variants for atopic dermatitis.Studies have reported evidence for gene–environment interaction involving FLG and a range of different environmental exposures. What does this study add? There is some evidence for FLG–environment interactions in the aetiology of atopic dermatitis; however, the evidence is limited.Studies lack large enough sample sizes to achieve adequate power in order to assess these interactions fully. Linked Comment: Park and Seo. Br J Dermatol 2020; 183:411. Plain language summary available online [ABSTRACT FROM AUTHOR]

Molecular pathological epidemiology research provides information about pathogenic mechanisms. A common study goal is to evaluate whether the effects of risk factors on disease incidence vary between different disease subtypes. A popular approach to carrying out this type of research is to implement a multinomial regression in which each of the non-zero values corresponds to a bona fide disease subtype. Then, heterogeneity in the exposure effects across subtypes is examined by comparing the coefficients of the exposure between the different subtypes. In this paper, we explain why this common method potentially cannot recover causal effects, even when all confounders are measured, due to a particular type of selection bias. This bias can be explained by recognizing that the multinomial regression is equivalent to a series of logistic regressions; each compares cases of a certain subtype to the controls. We further explain how this bias arises using directed acyclic graphs and we demonstrate the potential magnitude of the bias by analysis of a hypothetical data set and by a simulation study. [ABSTRACT FROM AUTHOR]

Since the mid-1970s, there have been many reports that purport to implicate aluminium in the aetiology of neurodegenerative disease. After several decades of research, the role of aluminium in such disease remains controversial and is not the subject of this review. However, if aluminium is implicated in such disease then it follows that there must be a toxicological mechanism or mode of action, and many researchers have investigated various potential mechanisms including the involvement of oxidative damage, cytotoxicity and genotoxicity. This paper reviews many of the publications of studies using various salts of aluminium and various genotoxicity end points, both in vitro and in vivo , with a focus on oxidative damage. The conclusion of this review is that the majority, if not all, of the publications that report positive results have serious technical flaws and/or implausible findings and consequently should contribute little or no weight to a weight of evidence (WoE) argument. There are many high-quality, Good Laboratory Practice (GLP)-compliant genotoxicity studies, that follow relevant OECD test guidelines and the European Chemicals Agency (ECHA) integrated mutagenicity testing strategy, on several salts of aluminium; all demonstrate clear negative results for both in vitro and in vivo genotoxicity. In addition, the claim for an oxidative mode of action for aluminium can be shown to be spurious. This review concludes that there are no reliable studies that demonstrate a potential for genotoxicity, or oxidative mode of action, for aluminium. [ABSTRACT FROM AUTHOR]

Motivation: Copy number variants (CNVs) have been implicated in a variety of neurodevelopmental disorders, including autism spectrum disorders, intellectual disability and schizophrenia. Recent advances in high-throughput genomic technologies have enabled rapid discovery of many genetic variants including CNVs. As a result, there is increasing interest in studying the role of CNVs in the etiology of many complex diseases. Despite the availability of an unprecedented wealth of CNV data, methods for testing association between CNVs and disease-related traits are still underdeveloped due to the low prevalence and complicated multi-scale features of CNVs. Results: We propose a novel CNV kernel association test (CKAT) in this paper. To address the low prevalence, CNVs are first grouped into CNV regions (CNVR). Then, taking into account the multiscale features of CNVs, we first design a single-CNV kernel which summarizes the similarity between two CNVs, and next aggregate the single-CNV kernel to a CNVR kernel which summarizes the similarity between two CNVRs. Finally, association between CNVR and disease-related traits is assessed by comparing the kernel-based similarity with the similarity in the trait using a score test for variance components in a random effect model. We illustrate the proposed CKAT using simulations and show that CKAT is more powerful than existing methods, while always being able to control the type I error. We also apply CKAT to a real dataset examining the association between CNV and autism spectrum disorders, which demonstrates the potential usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

In population studies on the aetiology of disease, one goal is the estimation of the fraction of cases that are attributable to each of several causes. For example, pneumonia is a clinical diagnosis of lung infection that may be caused by viral, bacterial, fungal or other pathogens. The study of pneumonia aetiology is challenging because directly sampling from the lung to identify the aetiologic pathogen is not standard clinical practice in most settings. Instead, measurements from multiple peripheral specimens are made. The paper introduces the statistical methodology designed for estimating the population aetiology distribution and the individual aetiology probabilities in the Pneumonia Etiology Research for Child Health study of 9500 children for seven sites around the world. We formulate the scientific problem in statistical terms as estimating the mixing weights and latent class indicators under a partially latent class model (PLCM) that combines heterogeneous measurements with different error rates obtained from a case--control study. We introduce the PLCM as an extension of the latent class model. We also introduce graphical displays of the population data and inferred latent class frequencies. The methods are tested with simulated data, and then applied to Pneumonia Etiology Research for Child Health data. The paper closes with a brief description of extensions of the PLCM to the regression setting and to the case where conditional independence between the measures is relaxed. [ABSTRACT FROM AUTHOR]

Set-based association analysis is a valuable tool in studying the etiology of complex diseases in genome-wide association studies, as it allows for the joint testing of variants in a region or group. Two common types of single nucleotide polymorphism (SNP)–disease functional models are recognized when evaluating the joint function of a set of SNP: the cumulative weak signal model, in which multiple functional variants with small effects contribute to disease risk, and the dominating strong signal model, in which a few functional variants with large effects contribute to disease risk. However, existing methods have two main limitations that reduce their power. Firstly, they typically only consider one disease–SNP association model, which can result in significant power loss if the model is misspecified. Secondly, they do not account for the high-dimensional nature of SNPs, leading to low power or high false positives. In this study, we propose a solution to these challenges by using a high-dimensional inference procedure that involves simultaneously fitting many SNPs in a regression model. We also propose an omnibus testing procedure that employs a robust and powerful P-value combination method to enhance the power of SNP-set association. Our results from extensive simulation studies and a real data analysis demonstrate that our set-based high-dimensional inference strategy is both flexible and computationally efficient and can substantially improve the power of SNP-set association analysis. Application to a real dataset further demonstrates the utility of the testing strategy. [ABSTRACT FROM AUTHOR]

Motivation Somatic mutations result from processes related to DNA replication or environmental/lifestyle exposures. Knowing the activity of mutational processes in a tumor can inform personalized therapies, early detection, and understanding of tumorigenesis. Computational methods have revealed 30 validated signatures of mutational processes active in human cancers, where each signature is a pattern of single base substitutions. However, half of these signatures have no known etiology, and some similar signatures have distinct etiologies, making patterns of mutation signature activity hard to interpret. Existing mutation signature detection methods do not consider tumor-level clinical/demographic (e.g. smoking history) or molecular features (e.g. inactivations to DNA damage repair genes). Results To begin to address these challenges, we present the Tumor Covariate Signature Model (TCSM), the first method to directly model the effect of observed tumor-level covariates on mutation signatures. To this end, our model uses methods from Bayesian topic modeling to change the prior distribution on signature exposure conditioned on a tumor's observed covariates. We also introduce methods for imputing covariates in held-out data and for evaluating the statistical significance of signature-covariate associations. On simulated and real data, we find that TCSM outperforms both non-negative matrix factorization and topic modeling-based approaches, particularly in recovering the ground truth exposure to similar signatures. We then use TCSM to discover five mutation signatures in breast cancer and predict homologous recombination repair deficiency in held-out tumors. We also discover four signatures in a combined melanoma and lung cancer cohort—using cancer type as a covariate—and provide statistical evidence to support earlier claims that three lung cancers from The Cancer Genome Atlas are misdiagnosed metastatic melanomas. Availability and implementation TCSM is implemented in Python 3 and available at https://github.com/lrgr/tcsm , along with a data workflow for reproducing the experiments in the paper. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Neuropsychologists often face interpretational difficulties when assessing cognitive deficits, particularly in cases of unclear cerebral etiology. How can we be sure whether a single test score below the population average is indicative of a pathological brain condition or normal? In the past fewyears, the topic of intra-individual performance variability has gained great interest. On the basis of a large normative sample, two measures of performance variability and their importance for neuropsychological interpretation will be presented in this paper: the number of low scores and the level of dispersion. We conclude that lowscores arecommonin healthy individuals. On the other hand, the level of dispersion is relatively small. Here, base rate information about abnormally lowscores and abnormally high dispersion across cognitive abilities are provided to improve the awareness of normal variability and to serve clinicians as additional interpretive measures in the diagnostic process. [ABSTRACT FROM AUTHOR]

Background: Conventional descriptions of central nervous system (CNS) infections are variably categorized into clinical syndromes for patient investigation, management and research. Aetiologies of the most commonly recognized syndromes, encephalitis and meningitis, tend to be attributed predominantly to viruses and bacteria, respectively. Methods: A systematic review was performed of aetiological studies of CNS syndromes and data extracted on reported author specialities. Results: The analysis identified an association between the author's speciality and the CNS syndrome studied, with a tendency for virologists to study encephalitis and microbiologists to study meningitis. Conclusions: We suggest there is bias in study design. Stronger multidisciplinary collaboration in CNS infection research is needed. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) develops when there are insufficient insulinproducing beta cells to maintain glucose homeostasis. The prevailing view has been that T1D is caused by immune-mediated destruction of the pancreatic beta cells. However, several recent papers have challenged the long-standing paradigm describing T1D as a tissue-specific autoimmune disease. These authors have highlighted the gaps in our knowledge and understanding of the aetiology of T1D in humans. Here we review the evidence and argue the case for the autoimmune basis of human T1D. In particular, recent analysis of human islet-infiltrating T cells brings important new evidence to this question. Further data in support of the autoimmune basis of T1D from many fields, including genetics, experimental therapies and immunology, is discussed. Finally, we highlight some of the persistent questions relating to the pathogenesis of human type 1 diabetes that remain to be answered. [ABSTRACT FROM AUTHOR]

In 1925, Sir Thomas Horder, a leading physician of his day, gave a lecture, published in this journal, entitled 'Some cases of pyrexia without physical signs'. The paper highlighted what was already a familiar clinical presentation "which taxes our resources to the utmost". Fast-forward through 90 years of careful clinical description, technological innovation in diagnosis and treatment, emergent infections, novel diagnoses, demographic shifts, and radical changes in the health economy. Sir Thomas would find certain aspects familiar, and others revolutionary, in the differential diagnosis and management of the 21st century patient with pyrexia of unknown origin (PUO). Within high-income settings, the proportion of cases due to infection has declined, albeit unevenly. The era of untreated HIV, and the consequences of iatrogenic intervention and immunosuppression, led to Durack and Street's subclassification of the condition in the early 1990 s into classic, nosocomial, neutropenic and HIV-associated PUO. Shifts towards ambulatory care have driven a change in the definition of many diseases. An era of observant clinicians, who lent their names to eponymous syndromes, followed by meticulous serological, genetic and clinicopathological correlation, generated a battery of diagnoses that, along with malignancy, form a large proportion of diagnoses in more recent clinical care. In the current era, universal access to cross-sectional imaging and an infinite array of laboratory tests has undermined the attention paid to history and examination. In some areas of the clinical assessment, such as assessing the fever pattern, this shift is supported by research evidence. The issues that need to be addressed in the next 90 years of technological innovation, information sharing and health service transformation are likely to include: transcriptomic approaches to diagnosis; the place of positron emission tomography (PET) in the diagnostic pathway; the optimal management of high ferritin states; and the most cost-effective diagnostic environment, in the face of this era of specialisation and fragmentation of care. In the meantime, this review covers some important early 21st century lessons to be shared in avoiding diagnostic pitfalls and choosing empirical therapy. [ABSTRACT FROM AUTHOR]

Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although, kernelbased statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data, but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. [ABSTRACT FROM AUTHOR]

Regression models are being used to quantify the effect of an exposure on an outcome, while adjusting for potential confounders. While the type of regression model to be used is determined by the nature of the outcome variable, e.g. linear regression has to be applied for continuous outcome variables, all regression models can handle any kind of exposure variables. However, some fundamentals of representation of the exposure in a regression model and also some potential pitfalls have to be kept in mind in order to obtain meaningful interpretation of results. The objective of this educational paper was to illustrate these fundamentals and pitfalls, using various multiple regression models applied to data from a hypothetical cohort of 3000 patients with chronic kidney disease. In particular, we illustrate how to represent different types of exposure variables (binary, categorical with two or more categories and continuous), and how to interpret the regression coefficients in linear, logistic and Cox models. We also discuss the linearity assumption in these models, and show how wrongly assuming linearity may produce biased results and how flexible modelling using spline functions may provide better estimates. [ABSTRACT FROM AUTHOR]

Elucidation of human disease similarities has provided new insights into etiology, disease classification and drug repositioning. Since dysfunctional regulation would be manifested as the decoupling of expression correlation, disease similarity (DS) in terms of dysfunctional regulation mechanism (DRM) could be estimated by using a differential coexpression based approach, which is described in a companion paper. Due to the lack of tools for estimating DS from the viewpoint of DRM in public domain, we implemented an R package 'DSviaDRM' to identify significant DS via DRM based on transcriptomic data. DSviaDRM contains five easy-to-use functions, DCEA, DCpathway, DS, comDCGL and comDCGLplot, for identifying disease relationships and showing common differential regulation information shared by similar diseases. [ABSTRACT FROM AUTHOR]

An association exists between severe respiratory syncytial virus (RSV)–bronchiolitis and a subsequent increased risk of recurrent wheezing (RW) and asthma. However, a causal relationship remains unproven. Using a retrospective population-based cohort study (339 814 children), bronchiolitis during the first 2 years of life (regardless of etiology and severity) was associated with at least a 3-fold increased risk of RW/asthma at 2–4 years and an increased prevalence of asthma at ≥5 years of age. The risk was similar in children with mild bronchiolitis as in those with hospitalized RSV-bronchiolitis and was higher in children with hospitalized non-RSV-bronchiolitis. The rate of RW/asthma was higher when bronchiolitis occurred after the first 6 months of life. Our results seem to support the hypothesis of a shared predisposition to bronchiolitis (irrespective of etiology) and RW/asthma. However, 60% of hospitalized bronchiolitis cases in our setting are due to RSV, which should be paramount in decision-making on imminent RSV prevention strategies. [ABSTRACT FROM AUTHOR]

Hyponatremia is the most common electrolyte disorder, affecting more than 15% of patients in the hospital. Syndrome of inappropriate antidiuresis (SIAD) is the most frequent cause of hypotonic hyponatremia, mediated by nonosmotic release of arginine vasopressin (AVP, previously known as antidiuretic hormone), which acts on the renal V2 receptors to promote water retention. There are a variety of underlying causes of SIAD, including malignancy, pulmonary pathology, and central nervous system pathology. In clinical practice, the etiology of hyponatremia is frequently multifactorial and the management approach may need to evolve during treatment of a single episode. It is therefore important to regularly reassess clinical status and biochemistry, while remaining alert to potential underlying etiological factors that may become more apparent during the course of treatment. In the absence of severe symptoms requiring urgent intervention, fluid restriction (FR) is widely endorsed as the first-line treatment for SIAD in current guidelines, but there is considerable controversy regarding second-line therapy in instances where FR is unsuccessful, which occurs in around half of cases. We review the epidemiology, pathophysiology, and differential diagnosis of SIAD, and summarize recent evidence for therapeutic options beyond FR, with a focus on tolvaptan, urea, and sodium-glucose cotransporter 2 inhibitors. [ABSTRACT FROM AUTHOR]

While chronic heart failure (CHF) treatment has considerably improved patient prognosis and survival, the therapeutic management of acute heart failure (AHF) has remained virtually unchanged in the last decades. This is partly due to the scarcity of pre-clinical models for the pathophysiological assessment and, consequently, the limited knowledge of molecular mechanisms involved in the different AHF phenotypes. This scientific statement outlines the different trajectories from acute to CHF originating from the interaction between aetiology, genetic and environmental factors, and comorbidities. Furthermore, we discuss the potential molecular targets capable of unveiling new therapeutic perspectives to improve the outcome of the acute phase and counteracting the evolution towards CHF. [ABSTRACT FROM AUTHOR]

BACKGROUND Abnormal uterine bleeding (AUB) has a significant socioeconomic impact since it considerably impacts quality of life. Therapeutic options are frequently based on trial and error and do not target disease aetiology. Pathophysiological insight in this disease is required for the development of novel treatment options. If no underlying cause is found for the AUB (e.g. fibroids, adenomyosis, polyps), endometrial-AUB (AUB-E) is usually caused by a primary endometrium disorder. When AUB is induced by prescribed (exogenous) hormones, it is classified as iatrogenic-AUB (AUB-I). Considering vascular modulation and function, AUB-E and AUB-I both could potentially result from abnormal vascularization in the endometrium due to alterations in the process of angiogenesis and vascular maturation. OBJECTIVE AND RATIONALE We aim to investigate the fundamental role of angiogenesis and vascular maturation in patients with AUB and hypothesize that aberrant endometrial angiogenesis has an important role in the aetiology of both AUB-E and AUB-I, possibly through different mechanisms. SEARCH METHODS A systematic literature search was performed until September 2021 in the Cochrane Library Databases, Embase, PubMed, and Web of Science, with search terms such as angiogenesis and abnormal uterine bleeding. Included studies reported on angiogenesis in the endometrium of premenopausal women with AUB-E or AUB-I. Case reports, letters, reviews, editorial articles, and studies on AUB with causes classified by the International Federation of Gynecology and Obstetrics as myometrial, oncological, or infectious, were excluded. Study quality was assessed by risk of bias, using the Cochrane tool and the Newcastle–Ottawa Scale. OUTCOMES Thirty-five out of 2158 articles were included. In patients with AUB-E, vascular endothelial growth factor A and its receptors (1 and 2), as well as the angiopoietin-1:angiopoietin-2 ratio and Tie-1, were significantly increased. Several studies reported on the differential expression of other pro- and antiangiogenic factors in patients with AUB-E, suggesting aberrant vascular maturation and impaired vessel integrity. Overall, endometrial microvessel density (MVD) was comparable in patients with AUB-E and controls. Interestingly, patients with AUB-I showed a higher MVD and higher expression of proangiogenic factors when compared to controls, in particular after short-term hormone exposure. This effect was gradually lost after longer-term exposure, while alterations in vessel maturation were observed after both short- and long-term exposures. WIDER IMPLICATIONS AUB-E and AUB-I are most likely associated with aberrant endometrial angiogenesis and impaired vessel maturation. This review supports existing evidence that increased proangiogenic and decreased antiangiogenic factors cause impaired vessel maturation, resulting in more fragile and permeable vessels. This matches our hypothesis and these mechanisms appear to play an important role in the pathophysiology of AUB-E and AUB-I. Exploring the alterations in angiogenesis in these patients could provide treatment targets for AUB. [ABSTRACT FROM AUTHOR]

There is a lack of imaging markers revealing the functional characteristics of different brain regions in paediatric dystonia. In this observational study, we assessed the utility of [18F]2-fluoro-2-deoxy-D-glucose (FDG)-PET in understanding dystonia pathophysiology by revealing specific resting awake brain glucose metabolism patterns in different childhood dystonia subgroups. PET scans from 267 children with dystonia being evaluated for possible Deep Brain Stimulation (DBS) surgery between September 2007 and February 2018 at Evelina London Children's Hospital (ELCH) United Kingdom were examined. Scans without gross anatomical abnormality (e.g. large cysts, significant ventriculomegaly; n = 240) were analysed with Statistical Parametric Mapping (SPM12). Glucose metabolism patterns were examined in the 144/240 (60%) cases with the ten commonest childhood-onset dystonias, focusing on nine anatomical regions. A group of thirty-nine adult controls was used for comparisons. The genetic dystonias were associated with the following genes: TOR1A, THAP1, SGCE, KMT2B, HPRT1 (Lesch Nyhan disease), PANK2 and GCDH (Glutaric Aciduria type 1). The acquired Cerebral Palsy (CP) cases were divided into those related to prematurity (CP-Preterm), neonatal jaundice/kernicterus (CP-Kernicterus) and hypoxic-ischaemic encephalopathy (CP-Term). Each dystonia subgroup had distinct patterns of altered FDG-PET uptake. Focal glucose hypometabolism of the pallidi, putamina, or both, was the commonest finding, except in PANK2, where basal ganglia metabolism appeared normal. HPRT1 uniquely showed glucose hypometabolism across all nine cerebral regions. Temporal lobe glucose hypometabolism was found in KMT2B, HPRT1 and CP-Kernicterus. Frontal lobe hypometabolism was found in SGCE, HPRT1, and PANK2. Thalamic and brainstem hypometabolism were seen only in HPRT1, CP-Preterm and CP-term dystonia cases. The combination of frontal and parietal lobe hypermetabolism was uniquely found in CP-term cases. PANK2 cases showed a distinct combination of parietal hypermetabolism with cerebellar hypometabolism but intact putaminal-pallidal glucose metabolism. HPRT1, PANK2, CP-kernicterus and CP-preterm cases had cerebellar and insula glucose hypometabolism as well as parietal glucose hypermetabolism. The study findings offer insights into the pathophysiology of dystonia and support the network theory for dystonia pathogenesis. "Signature" patterns for each dystonia subgroup could be a useful biomarker to guide differential diagnosis and inform personalised management strategies. [ABSTRACT FROM AUTHOR]

This International Consensus Guideline was developed by experts in the field of small for gestational age (SGA) of 10 pediatric endocrine societies worldwide. A consensus meeting was held and 1300 articles formed the basis for discussions. All experts voted about the strengths of the recommendations. The guideline gives new and clinically relevant insights into the etiology of short stature after SGA birth, including novel knowledge about (epi)genetic causes. Further, it presents long-term consequences of SGA birth and also reviews new treatment options, including treatment with gonadotropin-releasing hormone agonist (GnRHa) in addition to growth hormone (GH) treatment, as well as the metabolic and cardiovascular health of young adults born SGA after cessation of childhood GH treatment in comparison with appropriate control groups. To diagnose SGA, accurate anthropometry and use of national growth charts are recommended. Follow-up in early life is warranted and neurodevelopment evaluation in those at risk. Excessive postnatal weight gain should be avoided, as this is associated with an unfavorable cardiometabolic health profile in adulthood. Children born SGA with persistent short stature < −2.5 SDS at age 2 years or < −2 SDS at 3 to 4 years of age, should be referred for diagnostic workup. In case of dysmorphic features, major malformations, microcephaly, developmental delay, intellectual disability, and/or signs of skeletal dysplasia, genetic testing should be considered. Treatment with 0.033 to 0.067 mg GH/kg/day is recommended in case of persistent short stature at age of 3 to 4 years. Adding GnRHa treatment could be considered when short adult height is expected at pubertal onset. All young adults born SGA require counseling to adopt a healthy lifestyle. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide OBJECTIVES The prevalence and aetiology of acute aortic dissection type A (AADA) in patients ≤30 years is unknown. The aims of this clinical study were to determine the prevalence and potential aetiology of AADA in surgically treated patients ≤30 years and to evaluate the respective postoperative outcomes in this selective group of patients in a large multicentre study. METHODS Retrospective data collection was performed at 16 participating international aortic institutions. All patients ≤30 years at the time of dissection onset were included. The postoperative results were analysed with regard to connective tissue disease (CTD). RESULTS The overall prevalence of AADA ≤30 years was 1.8% (139 out of 7914 patients), including 51 (36.7%) patients who were retrospectively diagnosed with CTD. Cumulative postoperative mortality was 8.6%, 2.2% and 1.4%. Actuarial survival was 80% at 10 years postoperatively. Non-CTD patients (n  = 88) had a significantly higher incidence of arterial hypertension (46.6% vs 9.8%; P  < 0.001) while AADA affected the aortic root (P  < 0.001) and arch (P  = 0.029) significantly more often in the CTD group. A positive family history of aortic disease was present in 9.4% of the study cohort (n  = 13). CONCLUSIONS The prevalence of AADA in surgically treated patients ≤30 years is <2% with CTD and arterial hypertension as the 2 most prevalent triggers of AADA. Open surgery may be performed with good early results and excellent mid- to long-term outcomes. [ABSTRACT FROM AUTHOR]

Somatic mutational signatures (MSs) identified by genome sequencing play important roles in exploring the cause and development of cancer. Thus far, many such signatures have been identified, and some of them do imply causes of cancer. However, a major bottleneck is that we do not know the potential meanings (i.e. carcinogenesis or biological functions) and contributing genes for most of them. Here, we presented a computational framework, Gene Somatic Genome Pattern (GSGP), which can decipher the molecular mechanisms of the MSs. More importantly, it is the first time that the GSGP is able to process MSs from ribonucleic acid (RNA) sequencing, which greatly extended the applications of both MS analysis and RNA sequencing (RNAseq). As a result, GSGP analyses match consistently with previous reports and identify the etiologies for a number of novel signatures. Notably, we applied GSGP to RNAseq data and revealed an RNA-derived MS involved in deficient deoxyribonucleic acid mismatch repair and microsatellite instability in colorectal cancer. Researchers can perform customized GSGP analysis using the web tools or scripts we provide. [ABSTRACT FROM AUTHOR]

Background The Kidney Disease: Improving Global Outcomes guidelines advocate the cause–glomerular filtration rate (GFR)–albuminuria (CGA) classification for predicting outcomes. However, there is a dearth of data supporting the use of the cause of chronic kidney disease. This study aimed to address how to incorporate a prior biopsy-proven diagnosis in outcome prediction. Methods We examined the association of biopsy-proven kidney disease diagnoses with kidney failure with replacement therapy (KFRT) and all-cause death before KFRT in patients with various biopsy-proven diagnoses (n  = 778, analysis A) and patients with diabetes mellitus labeled with biopsy-proven diabetic nephropathy (DN), other biopsy-proven diseases and no biopsy (n  = 1117, analysis B). Results In analysis A, adding biopsy-proven diagnoses to the GFR–albuminuria (GA) classification improved the prediction of 8-year incidence of KFRT and all-cause death significantly regarding integrated discrimination improvement and net reclassification index. Fine–Gray (FG) models with KFRT as a competing event showed significantly higher subdistribution hazard ratios (SHRs) for all-cause death in nephrosclerosis {4.12 [95% confidence interval (CI) 1.11–15.2)], focal segmental glomerulosclerosis [3.77 (95% CI 1.09–13.1)]} and membranous nephropathy (MN) [2.91 (95% CI 1.02–8.30)] than in immunoglobulin A nephropathy (IgAN), while the Cox model failed to show significant associations. Crescentic glomerulonephritis had the highest risk of all-cause death [SHR 5.90 (95% CI 2.05–17.0)]. MN had a significantly lower risk of KFRT than IgAN [SHR 0.45 (95% CI 0.24–0.84)]. In analysis B, other biopsy-proven diseases had a lower risk of KFRT than biopsy-proven DN in the FG model, with death as a competing event [SHR 0.62 (95% CI 0.39–0.97)]. Conclusions The CGA classification is of greater value in predicting outcomes than the GA classification. [ABSTRACT FROM AUTHOR]

Objective: Hypothalamic syndrome (HS) in childhood is a rare condition. Its epidemiology is not well known because incidence and prevalence are related to very rare underlying diseases. In addition, different criteria for the syndrome are used across studies. Recognizing the HS may be difficult, due to its rareness and variety of symptoms. Having diagnostic criteria for signs and symptoms of hypothalamic dysfunction may aid in early recognition and diagnosis, in the reporting and understanding of its etiology, in predicting its course and its management. We aimed to define diagnostic criteria for hypothalamic dysfunction and a score for the presence of HS in childhood. Methods: Diagnostic criteria for hypothalamic dysfunction were developed and subdivided into hyperphagia, hypophagia, body mass index, behavioral problems, sleep disorders, temperature regulation disorders, pituitary dysfunction, radiological hypothalamic assessment, and presence/suspicion of a hypothalamic genetic syndrome. Subsequently, the scoring system was tested in a retrospective cohort of 120 patients at risk for hypothalamic dysfunction. Results: A score for presence of HS was developed. Using this new hypothalamic score, in total 52.5% were scored as having HS. Of these patients, 76.7% were diagnosed with pituitary dysfunction, 32.5% with hyperphagia, 40% with sleep disorders, and 14.2% with temperature dysregulation. For several criteria, clinical data was missing in more than 50% of cases. Conclusions: The here proposed diagnostic criteria for hypothalamic dysfunction and score for presence of HS may be used for care purposes and to aid in early recognition. Also it will be useful for research or registration purposes. [ABSTRACT FROM AUTHOR]

The medical research literature is abundant with regression analyses that include multiple covariates, so-called multivariable regression models. Despite their common application, the interpretation of their results is not always clear or claimed interpretations are not justified. To outline the distinctions between different interpretations, we describe several possible research objectives for which a multivariable regression analysis might be an appropriate way of analyzing the data. In addition, we describe caveats in the interpretation of results of multivariable regression analysis. [ABSTRACT FROM AUTHOR]

Design: Thyroid-stimulating hormone deficiency (TSHD) is a rare disease. It may be isolated, secondary to abnormalities of genes involved in TSH biosynthesis, or associated with other pituitary deficits or abnormalities of genes involved in pituitary ontogenesis. Several genes are involved in thyrotroph development and function. Objective: Our aim was to determine the genetic causes of TSHD, either isolated (ITSHD) or associated with somatotroph deficiency (TSHD-GHD), in the cohort of patients from the GENHYPOPIT network. Methods: Next-generation sequencing (NGS) analyses were performed as a panel of genes on a cohort of patients with non-syndromic ITSHD or TSHGHD. The variants were classified according to the American College of Medical Genetics classification reviewed by the NGS-Diag network and correlated with the phenotype. Class 3, 4, and 5 single-nucleotide variants were checked by Sanger sequencing and copy number variants by multiplex ligation-dependent probe amplification (MLPA). Results: A total of 64 index cases (22 ITSHD and 42 TSHD-GHD) were included in this cohort. A genetic cause was identified in 26.5% of patients, with 36.3% in the ITSHD group (variants in TSH$ and IGSF1) and 21.4% in TSHD-GHD (variants in IGSF1, TSH$, TRHR, GH1, POU1F1, and PROP1). Among the pathogenic and likely pathogenic variants identified, 42% were in IGSF1, including six not previously reported. Conclusion: Our results show that IGSF1 variants represent the most frequent aetiology of TSH deficiency. Despite a systematic NGS approach and the identification of new variants, most patients remain without a molecular diagnosis. Larger scale studies, such as exome or genome studies, should be considered in the future. [ABSTRACT FROM AUTHOR]

In recent years, pancreatic pathologies have become common problems and their etiology and pathogenesis are generally unknown. Studies have shown that smoking may increase the risk of pancreatic disorders but very scant knowledge is available about the pathogenesis of cigarette induced pancreatic pathology. This study aimed to evaluate the oxidative stress status, biochemical, pathological and immunohistochemical findings of rats exposed to cigarette smoke, pathogenesis of smoking related pancreatic damage and usability of Alpha Lipoic Acid (ALA) for amelioration of cigarette smoking induced harmful effects on rat pancreas. Twenty eight female, Sprague Dawley rats were randomly distributed into three groups. The sham group (S) (n = 8), rats were given 0.1 ml of physiological serum by oral gavage for 8 weeks. The cigarette smoke exposed group (CSE) (n = 10), rats were exposed to successive periods of cigarette smoke for 2 hours per day per 8 weeks and given 0.1 ml of physiological serum orally during the study. The cigarette smoke exposed and ALA treated group (CSE + ALA) (n = 10), animals were exposed to cigarette smoke (2 hours per day per 8 weeks) and simultaneously treated with 100 mg per kg per day ALA orally during the study. At the end of the study, the serum samples were collected for insulin, glucagon, glucose and amylase analyses. Tissue samples were collected for biochemical, histopathological and immunohistochemical examinations. Total oxidant status (TOS), total antioxidant status (TAS) levels and oxidative stress index (OSI) were evaluated in the pancreas samples. Immunohistochemical analyses of insulin, glucagon, calcitonin gene related protein (CGRP), active caspase-3, hypoxia inducible factor-1 (Hif-1), Hif-2 and tumor necrosis factor (TNF-α) expressions of pancreas were examined. Cigarette smoke caused statistically significant increase in serum amylase and glucose but decreased insulin levels indicating both endocrine and exocrine cell damage. There were no statistically significant differences in serum glucagon levels between the groups. Histopathological examination of the pancreas exhibited generally normal tissue architecture but slightly degenerative and apoptotic cells were noticed both in the endocrine and exocrine part of the pancreas in the CSE group. Immunohistochemical analyses revealed marked increase in active caspase-3, Hif-1 and Hif-2, CGRP and TNF-α expressions with a slight increase in glucagon immunoreactivity in cells while a marked decrease was observed in insulin expression in some Langerhans islets in the CSE group. ALA ameliorated biochemical and pathological findings in the CSE + ALA group. These findings clearly demonstrated that cigarette smoke can cause damage in both endocrine and exocrine cells in rat pancreas and ALA has an ameliorative effect of cigarette induced lesions. [ABSTRACT FROM AUTHOR]

The spatial and temporal domain of a gene's expression can range from ubiquitous to highly specific. Quantifying the degree to which this expression is unique to a specific tissue or developmental timepoint can provide insight into the etiology of genetic diseases. However, quantifying specificity remains challenging as measures of specificity are sensitive to similarity between samples in the sample set. For example, in the Gene-Tissue Expression project (GTEx), brain subregions are overrepresented at 13 of 54 (24%) unique tissues sampled. In this dataset, existing specificity measures have a decreased ability to identify genes specific to the brain relative to other organs. To solve this problem, we leverage sample similarity information to weight samples such that overrepresented tissues do not have an outsized effect on specificity estimates. We test this reweighting procedure on 4 measures of specificity, Z-score, Tau, Tsi and Gini, in the GTEx data and in single cell datasets for zebrafish and mouse. For all of these measures, incorporating sample similarity information to weight samples results in greater stability of sets of genes called as specific and decreases the overall variance in the change of specificity estimates as sample sets become more unbalanced. Furthermore, the genes with the largest improvement in their specificity estimate's stability are those with functions related to the overrepresented sample types. Our results demonstrate that incorporating similarity information improves specificity estimates' stability to the choice of the sample set used to define the transcriptome, providing more robust and reproducible measures of specificity for downstream analyses. [ABSTRACT FROM AUTHOR]

Background Deposition of Schistosoma mansoni eggs in the brain of patients with hepatosplenic schistosomiasis (HS-SM) is frequent and usually asymptomatic. However, it is questioned whether it could cause seizures. Thus, we investigated the occurrence of seizures in these patients and also searched for parameters associated with this disorder. Methods In a cross-sectional survey, we compared 128 patients with HS-SM with 102 patients with portal hypertension due to compensated chronic hepatic disease of other etiologies. A standardized questionnaire, emphasizing epilepsy-related parameters, was applied to all participants. Results Eight (6.3%) patients with HS-SM had a history of seizures, whereas this condition was reported by three (2.9%) individuals from the comparison group (p=0.354). None of the variables were associated with the occurrence of seizures, either in univariate or in multivariate analysis. Conclusions The frequency of seizures was similar in both study groups. However, it was higher than that described in population-based studies. Thus, we hypothesize that HS-SM individuals may have a higher frequency of seizure. The lack of difference between the two study groups may be explained by the inclusion of cases of HS-MS overlapping other chronic liver diseases in the comparison group, because this finding is relatively common in schistosome-endemic areas. [ABSTRACT FROM AUTHOR]

Context: Primary hyperparathyroidism and malignancy are the etiologies in 90% of cases of hypercalcemia. When these entities are not the etiology of hypercalcemia, uncommon conditions need to be considered. In 2005, Jacobs and Bilezikian published a clinical review of rare causes of hypercalcemia, focusing on mechanisms and pathophysiology. This review is an updated synopsis of rare causes of hypercalcemia, extending the observations of the original article.Evidence Acquisition: Articles reporting rare associations between hypercalcemia and unusual conditions were identified through a comprehensive extensive PubMed-based search using the search terms "hypercalcemia" and "etiology," as well as examining the references in the identified case reports. We categorized the reports by adults vs pediatric and further categorized the adult reports based on etiology. Some included reports lacked definitive assessment of etiology and are reported as unknown mechanism with discussion of likely etiology.Evidence Synthesis: There is a growing understanding of the breadth of unusual causes of hypercalcemia. When the cause of hypercalcemia is elusive, a focus on mechanism and review of prior reported cases is key to successful determination of the etiology.Conclusions: The ever-expanding reports of patients with rare and even unknown mechanisms of hypercalcemia illustrate the need for continued investigation into the complexities of human calcium metabolism. [ABSTRACT FROM AUTHOR]

Background: This study analyzes the clinical characteristics, outcomes, and conditions associated with hyperferritinemia (≥5000 ng/mL) in a high-complexity center in Colombia. Methods: This retrospective and descriptive study was performed between 2011 and 2020, at the Fundación Valle del Lili, Cali, Colombia, by reviewing medical charts from patients who had serum ferritin measurements equal to or greater than 5000 ng/mL. Results: We found 350 reports of ferritin values ≥5000 ng/mL, corresponding to 317 patients, with a median ferritin value of 8789 (6001–15 373)  ng/mL. The most frequent etiologies were infection (n = 198, 56.57%), hematologic disorders (n = 104, 29.71%), and blood transfusion (n = 98, 28.00%). These last 2 etiologies cooccurred in 37 (10.57%) cases. The main clinical signs accompanying hyperferritinemia were fever in 199 (56.86%) cases, multiorgan involvement in 125 (35.71%), and hepatomegaly in 95 (27.14%) cases. Ninety-four (29.65%) patients died in the hospital, and 11 (3.47%) died within 30 days after medical discharge, mainly due to infection (n = 51, 48.57%). Intrahospital mortality was associated with significantly higher ferritin levels (10 846, IQR: 6425–23 459) than survival (8452, IQR: 5980–13 932) (P = 0.018). Conclusions: Hyperferritinemia is related to many underlying causes, with infection being the principal cause in our cohort, followed by hematologic disorders. Additionally, in-hospital mortality was related to higher ferritin levels. [ABSTRACT FROM AUTHOR]

Despite the volume of experiments performed and data available, the complex biology of coronavirus SARS-COV-2 is not yet fully understood. Existing molecular profiling studies have focused on analysing functional omics data of a single type, which captures changes in a small subset of the molecular perturbations caused by the virus. As the logical next step, results from multiple such omics analysis may be aggregated to comprehensively interpret the molecular mechanisms of SARS-CoV-2. An alternative approach is to integrate data simultaneously in a parallel fashion to highlight the inter-relationships of disease-driving biomolecules, in contrast to comparing processed information from each omics level separately. We demonstrate that valuable information may be masked by using the former fragmented views in analysis, and biomarkers resulting from such an approach cannot provide a systematic understanding of the disease aetiology. Hence, we present a generic, reproducible and flexible open-access data harmonisation framework that can be scaled out to future multi-omics analysis to study a phenotype in a holistic manner. The pipeline source code, detailed documentation and automated version as a R package are accessible. To demonstrate the effectiveness of our pipeline, we applied it to a drug screening task. We integrated multi-omics data to find the lowest level of statistical associations between data features in two case studies. Strongly correlated features within each of these two datasets were used for drug–target analysis, resulting in a list of 84 drug–target candidates. Further computational docking and toxicity analyses revealed seven high-confidence targets, amsacrine, bosutinib, ceritinib, crizotinib, nintedanib and sunitinib as potential starting points for drug therapy and development. [ABSTRACT FROM AUTHOR]

Epilepsies of early childhood are frequently resistant to therapy and often associated with cognitive and behavioural comorbidity. Aetiology focused precision medicine, notably gene-based therapies, may prevent seizures and comorbidities. Epidemiological data utilizing modern diagnostic techniques including whole genome sequencing and neuroimaging can inform diagnostic strategies and therapeutic trials. We present a 3-year, multicentre prospective cohort study, involving all children under 3 years of age in Scotland presenting with epilepsies. We used two independent sources for case identification: clinical reporting and EEG record review. Capture-recapture methodology was then used to improve the accuracy of incidence estimates. Socio-demographic and clinical details were obtained at presentation, and 24 months later. Children were extensively investigated for aetiology. Whole genome sequencing was offered for all patients with drug-resistant epilepsy for whom no aetiology could yet be identified. Multivariate logistic regression modelling was used to determine associations between clinical features, aetiology, and outcome. Three hundred and ninety children were recruited over 3 years. The adjusted incidence of epilepsies presenting in the first 3 years of life was 239 per 100 000 live births [95% confidence interval (CI) 216-263]. There was a socio-economic gradient to incidence, with a significantly higher incidence in the most deprived quintile (301 per 100 000 live births, 95% CI 251-357) compared with the least deprived quintile (182 per 100 000 live births, 95% CI 139-233), χ2 odds ratio = 1.7 (95% CI 1.3-2.2). The relationship between deprivation and incidence was only observed in the group without identified aetiology, suggesting that populations living in higher deprivation areas have greater multifactorial risk for epilepsy. Aetiology was determined in 54% of children, and epilepsy syndrome was classified in 54%. Thirty-one per cent had an identified genetic cause for their epilepsy. We present novel data on the aetiological spectrum of the most commonly presenting epilepsies of early childhood. Twenty-four months after presentation, 36% of children had drug-resistant epilepsy (DRE), and 49% had global developmental delay (GDD). Identification of an aetiology was the strongest determinant of both DRE and GDD. Aetiology was determined in 82% of those with DRE, and 75% of those with GDD. In young children with epilepsy, genetic testing should be prioritized as it has the highest yield of any investigation and is most likely to inform precision therapy and prognosis. Epilepsies in early childhood are 30% more common than previously reported. Epilepsies of undetermined aetiology present more frequently in deprived communities. This likely reflects increased multifactorial risk within these populations. [ABSTRACT FROM AUTHOR]

Pelvic inflammatory disease (PID) is a clinical syndrome that has been associated with a wide range of potential causal pathogens. Three broad groups of organisms have been isolated from the genital tract of people with PID: sexually transmitted organisms such as Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, and Trichomonas vaginalis; bacterial vaginosis (BV)-associated species and genera such as Atopobium vaginae, Sneathia, and Megasphaera; and genera and species usually associated with the gastrointestinal or respiratory tracts such as Bacteroides, Escherichia coli, Streptococcus, or Haemophilus influenza. Although PID is often considered to be synonymous with gonorrhea or chlamydia, these pathogens are found in only one quarter to one third of people with PID, suggesting that broader screening and diagnostic and treatment strategies need to be considered to reduce the burden of PID and its associated sequelae. [ABSTRACT FROM AUTHOR]

By 2018 approximately 32 million deaths worldwide had been attributed to HIV/AIDS. Yet the impact of the AIDS pandemic has been profoundly uneven. In the Global North, HIV has been constructed as marginal; in much of Africa, it is pervasive and transformative, fundamentally reshaping local economies, civil society, state structures and the continent's relations with the outside world. HIV is in reality a series of distinct epidemics, each with their own histories. In recent years, scientists have challenged historians' understanding of HIV's chronology and patterns of transmission, providing alternative histories of the virus's origins, expansion and resilience within mature epidemic settings. Epidemiologists and geneticists have realigned the temporal focus of archival and oral research while conceptualizing change over time around moments of divergence and focusing on historical episodes rather than process, and on diffusion over intensification. This article analyses scientists' historical understanding of sexually transmitted infections, migration and same-sex relationships, challenging narrow understandings of causality and the assumption that the contexts of the recent past can be applied backwards to more distant periods. Reconstructing HIV's long history requires recognition of the evolving complexity of sex and marriage, morality and discretion, migrancy and displacement, ethnic and racial preconceptions, and locality and connection. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a chronic, multisystemic autoimmune disease of variable presentation. Massive ascites in the context of SLE is infrequent. Even so, it has been reported that ascites may be the first manifestation of SLE. It is difficult to diagnose due to the multiple possible aetiological causes of ascites. There is a rare entity called Pseudo-Pseudo Meigs Syndrome (PPMS) in patients with SLE who have ascites, pleural effusion, and CA-125 elevation unrelated to malignancy. We present two cases of massive ascites, pleural effusion and elevation of CA-125 with a history of SLE diagnosis. One of these cases was diagnosed with PPMS and another associated with neoplasm of ovarian origin. [ABSTRACT FROM AUTHOR]

Background Hyperplasia of mammary gland (HMG) has become a common disorder in women. A family history of breast cancer and female reproductive factors may work together to increase the risk of HMG. However, this specific relationship has not been fully characterized. Methods A total of 1881 newly diagnosed HMG cases and 1900 controls were recruited from 2012 to 2017. Demographic characteristics including female reproductive factors and a family history of breast cancer were collected. A multi-analytic strategy combining unconditional logistic regression, multifactor dimensionality reduction (MDR) and crossover approaches were applied to systematically identify the interaction effect of family history of breast cancer and reproductive factors on HMG susceptibility. Results In MDR analysis, high-order interactions among higher-level education, shorter breastfeeding duration and family history of breast cancer were identified (odds ratio [OR] 7.07 [95% confidence interval {CI} 6.08 to 8.22]). Similarly, in crossover analysis, HMG risk increased significantly for those with higher-level education (OR 36.39 [95% CI 11.47 to 115.45]), shorter duration of breastfeeding (OR 27.70 [95% CI 3.73 to 205.70]) and a family history of breast cancer. Conclusion Higher-level education, shorter breastfeeding duration and a family history of breast cancer may synergistically increase the risk of HMG. [ABSTRACT FROM AUTHOR]

Aims The role of psychological stress in the aetiology of atrial fibrillation (AF) is unclear. The death of a child is one of the most severe sources of stress. We aimed to investigate whether the death of a child is associated with an increased risk of AF. Methods and results We studied parents with children born during 1973–2014 included the Swedish Medical Birth Register (n  = 3 924 237). Information on death of a child, AF and socioeconomic, lifestyle and health-related covariates was obtained through linkage to nationwide population and health registers. We examined the link between death of a child and AF risk using Poisson regression. Parents who lost a child had a 15% higher risk of AF than unexposed parents [incidence rate ratio (IRR) and 95% confidence intervals (CI): 1.15 (1.10–1.20)]. An increased risk of AF was observed not only if the child died due to cardiovascular causes [IRR (95% CI): 1.35 (1.17–1.56)], but also in case of deaths due to other natural [IRR (95% CI): 1.15 (1.09–1.21)] or unnatural [IRR (95% CI): 1.10 (1.02–1.19)] causes. The risk of AF was highest in the 1st week after the loss [IRR (95% CI): 2.87 (1.44–5.75)] and remained 10–40% elevated on the long term. Conclusions Death of a child was associated with a modestly increased risk of AF. Our finding that an increased risk was observed also after loss of a child due to unnatural deaths suggests that stress-related mechanisms may also be implicated in the development of AF. [ABSTRACT FROM AUTHOR]

Keywords: Cardiac fibrosis; Diagnostic biomarkers; Heart failure; Personalized therapy; Precision medicine EN Cardiac fibrosis Diagnostic biomarkers Heart failure Personalized therapy Precision medicine e20 e22 3 02/04/22 20220201 NES 220201 A diffuse accumulation of collagen fibres within the myocardial interstitium occurs in nearly all chronic cardiac diseases.[1] Because cardiac fibrosis is a key contributor to heart failure (HF) and its progression, it has important prognostic implications both in ischaemic heart disease[2] and non-ischaemic cardiac diseases.[3] In this regard, cardiac fibrosis is a major driver associated with the growing burden of HF, especially in older people.[4] However, integrating cardiac fibrosis in HF management is still an unmet medical need, which may be explained by its high tissue heterogeneity and clinical diversity, and, as a consequence, the very real limitations of its diagnosis and treatment. In summary, cardiac fibrosis represents a true challenge for transitioning from usual care to biomarker-based personalized treatment and precision medicine in HF. [Extracted from the article]

Background Aortobronchial fistula (ABF) formation following the rupture of thoracic pseudoaneurysm is a rare clinical entity. Its aetiology includes atherosclerosis, infections, trauma, post-surgery, and post-endovascular aortic repair. The clinical presentation of ABF includes intermittent or massive haemoptysis, acute respiratory distress, hypotension, and even death. These patients require an emergency aortic intervention to stop active haemorrhage. Thoracic endovascular aortic repair (TEVAR) is a less invasive, safe, and effective treatment compared to conventional open surgical repair Case summary We hereby report three cases of ruptured descending thoracic aortic pseudoaneurysms resulting in a fistula formation. The first two cases had tuberculosis as their underlying aetiology, while the third case was the result of previous open post-aortic surgery. All patients presented with massive haemoptysis and were successfully treated by emergency TEVAR and had favourable outcomes. Discussion Thoracic endovascular aortic repair is a rapid, less invasive, and effective treatment for emergency management of ABF. It has more than 85% technical success rates in the reported literature. We had procedural success in all three cases. The short and midterm outcome of ABF following TEVAR is favourable and encouraging. [ABSTRACT FROM AUTHOR]

Objective: To describe the etiology of severe short stature in the Helsinki University Hospital district covering a population of 1.2 million that is subject to frequent growth mo nitoring and screening rules during childhood. Design: Retrospective cohort study. Methods: We identified all subjects born 1990 or later with a height SD score <-3, after the age of 3 years, from the Helsinki University Hospital district growth database. A total of 785 subjects (376 females and 409 males) fulfilled our inclusion criteria; we reviewed their medical records and growt h data and report their underlying diagnoses. Results: A pathological cause for short stature was diagnosed in 76% of the girls and 71% of the boys (P = NS). Syndromes were the most numerous pathological cause (n = 160; 20%), followed by organ disorders (n = 127; 16%), growth hormone deficiency (GHD, n = 94; 12%), SGA without catch-up growth (n = 73; 9%), and skeletal dysplasias (n = 57; 7%). Idiopathic short stature (ISS) was diagnosed in 210 (27%) subjects. The probability of growth-related pathology, particularly of a syndrome or skeletal dysplasia, in creased with the shorter height SD score and the greater deviation from the target height. Sitting height to height SDS was increased in subjects with ISS, GHD, and SGA (all P < 0.01). Conclusions: Height <-3 SDS after 3 years of age usually results from a pathological cause and should be thoroughly investigated in specialized health care. The chance of finding a specific etiology increased with the severity of short stature, and the mismatch with target height. [ABSTRACT FROM AUTHOR]

A central hypothesis of The Etiology, Risk Factors and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study is that enteropathogens contribute to growth faltering. To examine this question, the MAL-ED network of investigators set out to achieve 3 goals: (1) develop harmonized protocols to test for a diverse range of enteropathogens, (2) provide quality-assured and comparable results from 8 global sites, and (3) achieve maximum laboratory throughput and minimum cost. This paper describes the rationale for the microbiologic assays chosen and methodologies used to accomplish the 3 goals. [ABSTRACT FROM AUTHOR]