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The heart is the most important muscular organ in the body as it provides oxygen and vital nutrients to all tissues within the body and supports excretion of waste products. Nowadays cardiovascular disease is the number one cause of mortality worldwide. Arrhythmogenic cardiomyopathy (ACM) is a familial myocardial disease and patients with ACM generally manifest with ventricular arrhythmias, palpitations, syncope and have an increased risk for sudden cardiac death (SCD). SCD often is the first, and dramatic, disease manifestation in a high proportion of probands and is often associated with exercise, affecting in particular athletes and young adults. In 60-70% of patients diagnosed with ACM the underlying cause is a mutation in genes encoding desmosomal proteins. In the far majority of inherited ACM cases, in which a desmosomal mutation is found, the affected gene is PKP2 that encodes for the protein plakophilin-2 (PKP2). The identification of ACM-associated mutations in the sarcoplasmic reticulum associated protein phospholamban (PLN) encouraged us to focus in this thesis specifically on calcium (Ca2+) handling related pathways. The general aim of the work described in this thesis was to study new disease mechanisms in ACM and we postulated and confirmed a thus far unrecognized role for Ca2+ handling related disease mechanisms in ACM. Besides that, we explored pharmaceutical interventions to treat the PKP2 and PLN-R14del- related cardiomyopathy. For the future, it is important to re-evaluate the one gene-one disease paradigm, and to focus on studying mutation -and patient specific disease mechanisms.

The heart is the most important muscular organ in the body as it provides oxygen and vital nutrients to all tissues within the body and supports excretion of waste products. Nowadays cardiovascular disease is the number one cause of mortality worldwide. Arrhythmogenic cardiomyopathy (ACM) is a familial myocardial disease and patients with ACM generally manifest with ventricular arrhythmias, palpitations, syncope and have an increased risk for sudden cardiac death (SCD). SCD often is the first, and dramatic, disease manifestation in a high proportion of probands and is often associated with exercise, affecting in particular athletes and young adults. In 60-70% of patients diagnosed with ACM the underlying cause is a mutation in genes encoding desmosomal proteins. In the far majority of inherited ACM cases, in which a desmosomal mutation is found, the affected gene is PKP2 that encodes for the protein plakophilin-2 (PKP2). The identification of ACM-associated mutations in the sarcoplasmic reticulum associated protein phospholamban (PLN) encouraged us to focus in this thesis specifically on calcium (Ca2+) handling related pathways. The general aim of the work described in this thesis was to study new disease mechanisms in ACM and we postulated and confirmed a thus far unrecognized role for Ca2+ handling related disease mechanisms in ACM. Besides that, we explored pharmaceutical interventions to treat the PKP2 and PLN-R14del- related cardiomyopathy. For the future, it is important to re-evaluate the one gene-one disease paradigm, and to focus on studying mutation -and patient specific disease mechanisms.

The heart is the most important muscular organ in the body as it provides oxygen and vital nutrients to all tissues within the body and supports excretion of waste products. Nowadays cardiovascular disease is the number one cause of mortality worldwide. Arrhythmogenic cardiomyopathy (ACM) is a familial myocardial disease and patients with ACM generally manifest with ventricular arrhythmias, palpitations, syncope and have an increased risk for sudden cardiac death (SCD). SCD often is the first, and dramatic, disease manifestation in a high proportion of probands and is often associated with exercise, affecting in particular athletes and young adults. In 60-70% of patients diagnosed with ACM the underlying cause is a mutation in genes encoding desmosomal proteins. In the far majority of inherited ACM cases, in which a desmosomal mutation is found, the affected gene is PKP2 that encodes for the protein plakophilin-2 (PKP2). The identification of ACM-associated mutations in the sarcoplasmic reticulum associated protein phospholamban (PLN) encouraged us to focus in this thesis specifically on calcium (Ca2+) handling related pathways. The general aim of the work described in this thesis was to study new disease mechanisms in ACM and we postulated and confirmed a thus far unrecognized role for Ca2+ handling related disease mechanisms in ACM. Besides that, we explored pharmaceutical interventions to treat the PKP2 and PLN-R14del- related cardiomyopathy. For the future, it is important to re-evaluate the one gene-one disease paradigm, and to focus on studying mutation -and patient specific disease mechanisms.

By definition, a rare disease affects fewer than one indi-vidual in 2000 people in the general population. However, as there are nearly 8000 rare diseases (some even without a name), it turns out that these “rare” diseases affect more than 300 million people worldwide (about 6% of the world’s population). Rare diseases, however, take a disproportionately high share of the health budget, estimated at about 20%. Some of them affect only a few individuals, while others affect hundreds of thousands. Regardless of whether a single rare disease affects millions or just one person, it has enormous medical and social implications, and its impact on the affected individuals and their families is generally devastating. This is especially the case because over 50% of rare diseases affect children, almost half of whom die before the age of 10. Historically, rare diseases have become also known as orphan diseases because pharmaceutical companies were not interested in developing treatments for them. However, after much struggle by parents’ non-profit organizations (eg, Families of SMA, Cure SMA, among others), and through the SMA Treatment Acceleration Act, in 2009 SMA entered the list of top 50 medical priorities in the USA. After a series of clinical trials, on December 23, 2016 these joint efforts finally resulted in the approval by the Food and Drug Administration of nusinersen (Spinraza), a medication for all types of SMA. This example shows how a deeper understanding of the genome and disease pathogenesis, combined with energetic involvement of families, may change clinical research and drug development. These efforts could also pave the way for the replacement of larger classifications of common disorders with more precisely defined individual diseases based on genetic markers.

Proteins carry out a broad range of functions in living organisms usually by interacting with other molecules. Protein–protein interaction (PPI) is an important base for understanding disease mechanisms and for deciphering rational drug design. The identification of protein interactions using experimental methods is expensive and time-consuming. Therefore, efficient computational methods to predict PPIs are of great value to biologists.

Rheumatoid arthritis (RA) is a progressive, inflammatory autoimmune disease of unknown aetiology. The complex mechanism of aetiopathogenesis, progress and chronicity of the disease involves genetic, epigenetic and environmental factors. To understand the molecular mechanisms underlying disease phenotypes, one has to place implicated factors in their functional context. However, integration and organization of such data in a systematic manner remains a challenging task. Molecular maps are widely used in biology to provide a useful and intuitive way of depicting a variety of biological processes and disease mechanisms. Recent large-scale collaborative efforts such as the Disease Maps Project demonstrate the utility of such maps as versatile tools to organize and formalize disease-specific knowledge in a comprehensive way, both human and machine-readable. We present a systematic effort to construct a fully annotated, expert validated, state-of-the-art knowledge base for RA in the form of a molecular map. The RA map illustrates molecular and signalling pathways implicated in the disease. Signal transduction is depicted from receptors to the nucleus using the Systems Biology Graphical Notation (SBGN) standard representation. High-quality manual curation, use of only human-specific studies and focus on small-scale experiments aim to limit false positives in the map. The state-of-the-art molecular map for RA, using information from 353 peer-reviewed scientific publications, comprises 506 species, 446 reactions and 8 phenotypes. The species in the map are classified to 303 proteins, 61 complexes, 106 genes, 106 RNA entities, 2 ions and 7 simple molecules. The RA map is available online at ramap.elixir-luxembourg.org as an open-access knowledge base allowing for easy navigation and search of molecular pathways implicated in the disease. Furthermore, the RA map can serve as a template for omics data visualization.

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight., Summary: This Review discusses approaches to deal with and reduce cellular heterogeneity in induced pluripotent stem cell-based studies, enabling experiments to be reproducible and meaningful.

Metabolomics involves the study of a complex and diverse array of compounds that can be thought of as the ultimate end products of the complex systems that are characteristic of molecular biology. The compounds that constitute the metabolome are small in size relative to the genome and proteome and include amino acids, carbohydrates, organic acids, lipids, and nucleotides with a mass less than 1800 Da. Understanding the role of these metabolites and the way in which changes in these important molecules impact biological processes has great potential to improve public health through better understanding of disease mechanisms. A comprehensive understanding of the metabolome will ultimately lead to better candidate biomarkers and drug targets enabling improvements in patient care. Metabolomics experiments can be divided primarily into two experimental strategies: targeted and untargeted. This monograph details these two approaches and the specific considerations for sample preparation, analytical separations, instrumental considerations, and data analysis that are required in the practice of these important technologies. Furthermore, selected applications of targeted and untargeted experiments are showcased to demonstrate the role of metabolomics as part of multi-omics studies and how metabolites can be spatially mapped in biological systems using imaging mass spectrometry.

The global prevalence of diabetes mellitus and other metabolic diseases is rapidly increasing. Animal models play pivotal roles in unravelling disease mechanisms and developing and testing therapeutic strategies. Rodents are the most widely used animal models but may have limitations in their resemblance to human disease mechanisms and phenotypes. Findings in rodent models are consequently often difficult to extrapolate to human clinical trials. To overcome this ‘translational gap’, we and other groups are developing porcine disease models. Pigs share many anatomical and physiological traits with humans and thus hold great promise as translational animal models. Importantly, the toolbox for genetic engineering of pigs is rapidly expanding. Human disease mechanisms and targets can therefore be reproduced in pigs on a molecular level, resulting in precise and predictive porcine (PPP) models. In this short review, we summarize our work on the development of genetically (pre)diabetic pig models and how they have been used to study disease mechanisms and test therapeutic strategies. This includes the generation of reporter pigs for studying beta-cell maturation and physiology. Furthermore, genetically engineered pigs are promising donors of pancreatic islets for xenotransplantation. In summary, genetically tailored pig models have become an important link in the chain of translational diabetes and metabolic research.

Purpose: The current review provides a recapitulation of recent advances in pharmacological neuroimaging in headache, a promising tool to understanding of how a drug works in the brain and how it may lead to new insights of disease mechanisms of headache. Results: Pharmacological positron emission tomography with radioligand-labeled medication may provide evidence whether and where a medication binds in the brain but is still mostly restricted to animal work. Pharmacological functional MRI using task-specific approaches identified central modulation patterns as a consequence of attack and preventative headache medication, which may be distinct to a specific drug mechanism. Pharmacological neuroimaging and specifically in combination with functional imaging is a promising tool to better understand not only certain medications but also certain disease mechanisms. Summary: Pharmacological imaging techniques have advanced over the last few years and showed great potential of providing new insights into drug pharmacodynamics and disease mechanism. There are still limitations and challenges to be overcome.

Animal models can provide insight into the pathophysiology of disease mechanisms, and provide important information for translational medicine and the testing and treatment of novel therapies. The laboratory rat is widely studied for its similarities to diseases in humans. An understanding of species-specific features is critical for the development of sound experimental design and reproducibility. This chapter gives an overview of the most important anatomical structures of the laboratory rat, and highlights those that are unique to the rat as a species. An additional goal is to describe the anatomical and physiologic features that make the rat of particular value as an animal model in research. The chapter is divided into subcategories by organ system. Each subsection presents a summary of gross anatomy and organ function, along with selected features of normal microscopic anatomy and physiology. The chapter information is not intended to be comprehensive, but is meant to provide a starting point for scientists and veterinarians who work with the rat in a research setting to learn and review basic information.

Transcranial magnetic stimulation (TMS) is a noninvasive technique that is accelerating our current understanding of disease mechanisms across a spectrum of neurological disorders. Importantly, TMS has allowed in vivo exploration of complex dementia networks and the cortical pathology delineating dementia subtypes, lending insight into the differentiation of underlying neurobiochemistry. The application of TMS to investigate disease stages has also allowed for a dynamic understanding of key changes across the temporal progression of disease and provided important clues for the development of potential biomarkers for clinical and monitoring purposes. Although results have been encouraging, particularly for Alzheimer's dementia, outcomes remain clinically variable and require further exploration. As such, this review will explore key TMS findings from the main cortical, cortico-subcortical, and subcortical dementia subtypes and discuss pathophysiological implications.

People who have Down syndrome are at significantly elevated risk of developing early onset Alzheimer's disease that causes dementia (AD-DS). Here we review recent progress in modeling the development of AD-DS in mouse models. These studies provide insight into mechanisms underlying Alzheimer's disease and generate new clinical research questions. In addition, they suggest potential new targets for disease prevention therapies.

Laboratory models derived from clinical samples represent a solid platform in preclinical research for drug testing and investigation of disease mechanisms. The integration of these laboratory models with their digital counterparts (i.e., predictive mathematical models) allows to set up digital twins essential to fully exploit their potential to face the enormous molecular complexity of human organisms. In particular, due to the close integration of cell metabolism with all other cellular processes, any perturbation in cellular physiology typically reflect on altered cells metabolic profiling. In this regard, changes in metabolism have been shown, also in our laboratory, to drive a causal role in the emergence of cancer disease. Nevertheless, a unique metabolic program does not describe the altered metabolic profile of all tumour cells due to many causes from genetic variability to intratumour heterogeneous dependency on nutrients consumption and metabolism by multiple co-existing subclones. Currently, fluxomics approaches just match with the necessity of characterizing the overall flux distribution of cells within given samples, by disregarding possible heterogeneous behaviors. For the purpose of stratifying cancer heterogeneous subpopulations, quantification of fluxes at the single-cell level is needed. To this aim, we here present a new computational framework called single-cell Flux Balance Analysis (scFBA) that aims to set up digital metabolic twins in the perspective of being better exploited within a framework that makes also use of laboratory patient cell models. In particular, scFBA aims at integrating single-cell RNA-seq data within computational population models in order to depict a snapshot of the corresponding single-cell metabolic phenotypes at a given moment, together with an unsupervised identification of metabolic subpopulations.

The rheumatological diseases are a group of chronic, painful, degenerative and debilitating conditions with an increasing prevalence across the globe. The pathogenesis of these disorders is complex, overlapping and not fully understood. As such, it is difficult and time consuming to achieve correct diagnosis and complete remission for an individual patient. In this review we describe the most common forms of inflammatory arthritis and discuss how the management and treatment options for these rheumatic diseases have developed over time. We outline the successes and the limitations of current treatment regimens and discuss the economic burden of the current options. With advancements in understanding of disease mechanisms, we discuss the importance of the biologics revolution in the context of rheumatological disease and how the development of biosimilars and small molecule inhibitors will impact current treatment options in order to alleviate some of the cost burden of biological therapies. The ideal treatment strategy for the future would involve personalized and predictive medicine where by treatments can be tailored to an individual patient's needs in order to achieve fast and successful remission with no adverse events.

Alzheimer's disease (AD) is a major cause of dementia, disability, and death in the elderly. Despite recent advances in our understanding of the basic biological mechanisms underlying AD, we do not know how to prevent it, nor do we have an approved disease‐modifying intervention. Both are essential to slow or stop the growth in dementia prevalence. While our current animal models of AD have provided novel insights into AD disease mechanisms, thus far, they have not been successfully used to predict the effectiveness of therapies that have moved into AD clinical trials. The Model Organism Development and Evaluation for Late‐onset Alzheimer's Disease (MODEL‐AD; www.model-ad.org) Consortium was established to maximize human datasets to identify putative variants, genes, and biomarkers for AD; to generate, characterize, and validate the next generation of mouse models of AD; and to develop a preclinical testing pipeline. MODEL‐AD is a collaboration among Indiana University (IU); The Jackson Laboratory (JAX); University of Pittsburgh School of Medicine (Pitt); Sage BioNetworks (Sage); and the University of California, Irvine (UCI) that will generate new AD modeling processes and pipelines, data resources, research results, standardized protocols, and models that will be shared through JAX's and Sage's proven dissemination pipelines with the National Institute on Aging–supported AD Centers, academic and medical research centers, research institutions, and the pharmaceutical industry worldwide.

Since their discovery 15 years ago, human pluripotent stem cell (hPSC) technologies have begun to revolutionize science and medicine, rapidly expanding beyond investigative research to drug discovery and development. Efforts to leverage hPSCs over the last decade have focused on increasing both the complexity and in vivo fidelity of human cellular models through enhanced differentiation methods. While these evolutions have fostered novel insights into disease mechanisms and influenced clinical drug discovery and development, there are still several considerations that limit the utility of hPSC models. In this review, we highlight important, yet underexplored avenues to broaden their reach. We focus on (i) the importance of diversifying existing hPSC collections, and their utilization to investigate therapeutic strategies in individuals from different genetic backgrounds, ancestry and sex; (ii) considerations for the selection of therapeutically relevant hPSC-based models; (iii) strategies to adequately increase the scale of cell-based studies; and (iv) the advances and constraints of clinical trials in a dish. Moreover, we advocate for harnessing the translational capabilities of hPSC models along with the use of innovative, scalable approaches for understanding genetic biases and the impact of sex and ancestry on disease mechanisms and drug efficacy and response. The next decade of hPSC innovation is poised to provide vast insights into the genetic basis of human disease and enable rapid advances to develop, repurpose, and ensure the safety of the next generation of disease therapies across diverse human populations.

The American College of Rheumatology's case definitions for 19 neuropsychiatric syndromes in systemic lupus erythematosus (SLE) constitute a comprehensive classification of nervous system events in this disease. However, additional strategies are needed to determine whether a neuropsychiatric syndrome is attributable to SLE versus a competing comorbidity. Cognitive function is a clinical surrogate of overall brain health, with applications in both diagnosis and determination of clinical outcomes. Ischemic and inflammatory mechanisms are both key components of the immunopathogenesis of neuropsychiatric SLE (NPSLE), including abnormalities of the blood-brain barrier and autoantibody-mediated production of proinflammatory cytokines. Advances in neuroimaging provide a platform to assess novel disease mechanisms in a noninvasive way. The convergence of more rigorous clinical characterization, validation of biomarkers, and brain neuroimaging provides opportunities to determine the efficacy of novel targeted therapies in the treatment of NPSLE.

Neuromuscular disorders (NMDs) are chronic conditions that affect the neuromuscular system. Many NMDs currently have no cure; however, as more effective therapies become available for NMD patients, these individuals will exhibit improved health and/or prolonged lifespans. As a result, persons with NMDs will likely desire to engage in a more diverse variety of activities of daily living, including increased physical activity or exercise. Therefore, there is a need to increase our knowledge of the effects of acute exercise and chronic training on the neuromuscular system in NMD contexts. Here, we discuss the disease mechanisms and exercise biology of Duchenne muscular dystrophy (DMD), spinal muscular atrophy (SMA), and myotonic dystrophy type 1 (DM1), which are among the most prevalent NMDs in children and adults. Evidence from clinical and preclinical studies are reviewed, with emphasis on the functional outcomes of exercise, as well as on the putative cellular mechanisms that drive exercise-induced remodelling of the neuromuscular system. Continued investigation of the molecular mechanisms of exercise adaptation in DMD, SMA, and DM1 will assist in enhancing our understanding of the biology of these most prevalent NMDs. This information may also be useful for guiding the development of novel therapeutic targets for future pursuit.

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

Spinocerebellar ataxia (SCA) is a heterogeneous group of neurodegenerative ataxic disorders with autosomal dominant inheritance. We aim to provide an update on the recent clinical and scientific progresses in SCA where numerous novel genes have been identified with next-generation sequencing techniques. The main disease mechanisms of these SCAs include toxic RNA gain-of-function, mitochondrial dysfunction, channelopathies, autophagy and transcription dysregulation. Recent studies have also demonstrated the importance of DNA repair pathways in modifying SCA with CAG expansions. In addition, we summarise the latest technological advances in detecting known and novel repeat expansion in SCA. Finally, we discuss the roles of antisense oligonucleotides and RNA-based therapy as potential treatments. Electronic supplementary material The online version of this article (10.1007/s00415-018-9076-4) contains supplementary material, which is available to authorized users.

Publicly-available next-generation sequencing data has greatly expanded in the past decade, particularly through the work of several international consortia. These collaborative efforts have applied numerous assays profiling diverse features of gene regulation, such as genome-wide chromatin structure, transcriptional activity, and transcription factor binding, to thousands of biosamples from several organisms. Newly-developed computational analyses and statistical methods link findings to gene expression changes and phenotypic changes. Integrative analysis of these datasets holds the potential to revolutionize our understanding of organismal development, cell type differentiation, cellular response to stimuli, and disease mechanisms. However, standardized methods for data access, uniform data processing, and integrative analysis largely do not exist, hindering the impacts of these efforts. Here we review advancements made by consortia and directions of ongoing efforts, as well as challenges in accessing and analyzing publicly-available consortium data and emerging tools for addressing these challenges.

Accurate detection and interpretation of eye movement abnormalities often guides differential diagnosis, discussions on prognosis and disease mechanisms, and directed treatment of disabling visual symptoms and signs. A comprehensive clinical eye movement examination is high yield from a diagnostic standpoint; however, skillful recording and quantification of eye movements can increase detection of subclinical deficits, confirm clinical suspicions, guide therapeutics, and generate expansive research opportunities. This review encompasses an overview of the clinical eye movement examination, provides examples of practical diagnostic contributions from quantitative recordings of eye movements, and comments on recording equipment and related challenges.

This state-of-the-art review aims to provide an up-to-date look at breakthrough omic technologies that are helping to unravel heart failure (HF) disease mechanisms and heterogeneity. Genomics, transcriptomics, proteomics, and metabolomics in HF are reviewed in depth. In addition, there is a thorough, expert discussion regarding the value of omics in identifying novel disease pathways, advancing understanding of disease mechanisms, differentiating HF phenotypes, yielding biomarkers for diagnosis or prognosis, or identifying new therapeutic targets in HF. The combination of multiple omics technologies may create a more comprehensive picture of the factors and physiology involved in HF than achieved by either one alone and provides a rich resource for predictive phenotype modelling. However, the successful translation of omics tools as solutions to clinical HF requires that the observations are robust and reproducible and can be validated across multiple independent populations to ensure confidence in clinical decision-making.

Being etiologically positioned between the genome and the environment, epigenetic markers (e.g., DNA methylation) represent the cumulative memory of genetic susceptibility and environmental exposures. Hence, the premise of epigenetics is that it can serve as a biomarker of the interplay between genetic predisposition and current and past environmental exposures. Such biomarkers can identify at-risk subgroups and related past and current exposures, supportive in devising mitigating and preventive strategies. As explained in this chapter, exposures to environmental chemicals result in epigenetic modifications that, conditional on genetic susceptibilities, mediate exposure effects on disease development. However, to gain better insights on the link between environmental exposures, epigenetic modifications, and disease mechanisms, researchers need to develop and incorporate epidemiologic methods and strategies that can explain how epigenetics might mediate the influence of environmental exposures on disease development. Once causal and molecular pathways are elucidated, epigenetic markers will serve as diagnostic and therapeutic targets facilitating the vision of personalized precision medicine.

The scientific landscape surrounding amyotrophic lateral sclerosis (ALS) continues to shift as the number of genes associated with the disease risk and pathogenesis, and the cellular processes involved, continues to grow. Despite decades of intense research and over 50 potentially causative or disease-modifying genes identified, etiology remains unexplained and treatment options remain limited for the majority of ALS patients. Various factors have contributed to the slow progress in understanding and developing therapeutics for this disease. Here, we review the genetic basis of ALS, highlighting factors that have contributed to the elusiveness of genetic heritability. The most commonly mutated ALS-linked genes are reviewed with an emphasis on disease-causing mechanisms. The cellular processes involved in ALS pathogenesis are discussed, with evidence implicating their involvement in ALS summarized. Past and present therapeutic strategies and the benefits and limitations of the model systems available to ALS researchers are discussed with future directions for research that may lead to effective treatment strategies outlined.

Hypoglycaemia is a common, life-threatening complication that occurs as a component of a wide variety of disease processes. Despite its frequent occurrence, information concerning the aetiology, characteristics and outcomes of hypoglycaemic crises in veterinary medicine is limited. This review summarises the current understanding of the pathophysiology of hypoglycaemia, the body's counter-regulatory response, underlying aetiologies, diagnosis and treatment. Disease mechanisms are discussed and published evidence in veterinary literature regarding prognostic indicators, prevalence, diagnosis and treatment is examined for hypoglycaemia-related disease processes including insulinoma, glucose-lowering toxins and medications.

The present review aims to summarize available knowledge on the role of the ubiquitin-proteasome system (UPS) in the pathogenesis of scleroderma and scleroderma-related disease mechanisms. This will provide the reader with a more mechanistic understanding of disease pathogenesis and help to identify putative novel targets within the UPS for potential therapeutic intervention. Because of the heterogenous manifestations of scleroderma, we will primarily focus on conserved mechanisms that are involved in the development of lung scleroderma phenotypes.

Background: While significant benefits of lexical retrieval intervention are evident within the primary progressive aphasia (PPA) and Alzheimer’s disease (AD) literature, an understanding of the me...

Introduction: The Crigler–Najjar syndrome (CNS) is an ultra-rare recessive disorder of the liver. There is no effective cure, except for liver transplantation, a procedure with many risks and short...

Beta-thalassaemia causes defective haemoglobin synthesis leading to ineffective erythropoiesis, chronic haemolytic anaemia, and subsequent clinical complications. Blood transfusion and iron chelation allow long-term disease control, and haematopoietic stem cell transplantation offers a potential cure for some patients. Nonetheless, there are still many challenges in the management of beta-thalassaemia. The main treatment option for most patients is supportive care; furthermore, the long-term efficacy and safety of current therapeutic strategies are limited and adherence is suboptimal. An increasing understanding of the underlying molecular and cellular disease mechanisms plus an awareness of limitations of current management strategies are driving research into novel therapeutic options. Here we provide an overview of the current pathophysiology, clinical manifestations, and global burden of beta-thalassaemia. We reflect on what has been achieved to date, describe the challenges associated with currently available therapy, and discuss how these issues might be addressed by novel therapeutic approaches in development.

Brain imaging technology provides a powerful tool to visualize the living human brain, provide insights into disease mechanisms, and potentially provide a tool to assist clinical decision-making. The brain has a very specific structural substrate providing a foundation for functional information; however, most studies ignore the very interesting and complex relationships between brain structure and brain function. While a variety of approaches have been used to study how brain structure informs function, the study of such relationships in living humans in most cases is limited to noninvasive approaches at the macroscopic scale. The use of data-driven approaches to link structure and function provides a tool which is especially important at the macroscopic scale at which we can study the human brain. This paper reviews data-driven approaches, with a focus on independent component analysis approaches, which leverage higher order statistics to link together macroscopic structural and functional MRI data. Such approaches provide the benefit of allowing us to identify links which do not necessarily correspond spatially (eg, structural changes in one region related to functional changes in other regions). They also provide a "network level" perspective on the data, by enabling us to identify sets of brain regions that covary together. This also opens up the ability to evaluate both within and between network relationships. A variety of examples are presented, including several showing the potential of such approaches to inform us about mental illness, particularly about schizophrenia.

Understanding the aspects of cell functionality that account for disease mechanisms or drug modes of action is a main challenge for precision medicine. Classical gene-based approaches ignore the modular nature of most human traits, whereas conventional pathway enrichment approaches produce only illustrative results of limited practical utility. Recently, a family of new methods has emerged that change the focus from the whole pathways to the definition of elementary subpathways within them that have any mechanistic significance and to the study of their activities. Thus, mechanistic pathway activity (MPA) methods constitute a new paradigm that allows recoding poorly informative genomic measurements into cell activity quantitative values and relate them to phenotypes. Here we provide a review on the MPA methods available and explain their contribution to systems medicine approaches for addressing challenges in the diagnostic and treatment of complex diseases. This work was supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness and “Plataforma de Recursos Biomoleculares y Bioinformáticos” PT13/0001/0007 from the ISCIII, both co-funded with European Regional Development Funds (ERDF), and EU H2020-INFRADEV-1-2015-1 ELIXIR-EXCELERATE (ref. 676559).

Relating ion-channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of Artificial Intelligence Machine Learning (ML). Using this approach, we studied molecular processes that underlie human IKs voltage mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (pore forming tetramer) and KCNE1 (auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage (I-V) relationship. New mechanistic insights include - (1) pore energy profile determines iCh subconductance (SC), (2) entire protein structure, not limited to the pore, contributes to pore energy and channel SC, (3) interactions with KCNE1 result in two distinct VS movements, causing gating charge saturation at positive membrane voltages and current activation delay, and (4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function.

Migraine is a complex brain disorder characterized by recurrent attacks of unilateral headache and a global dysfunction in multisensory information processing. Genetic studies implicate several ion channel genes in migraine, ether as causative of a monogenic subtype (FHM) or possible contributors. Here we mainly discuss functional studies in transgenic mice carrying a CaV2.1 mutation causing FHM, and the insights they provide into the disease mechanisms, in particular regarding susceptibility to cortical spreading depression (CSD), the phenomenon that underlies migraine aura and can trigger the headache mechanisms. We also discuss recent findings implicating the ATP-gated P2X7 receptor in initiation of experimental CSD, and review some properties of the channels identified by genome-wide association studies as having a potential role in migraine.

Malassezia are lipid dependent basidiomycetous yeasts that inhabit the skin and mucosa of humans and other warm-blooded animals, and are a major component of the skin microbiome. They occur as skin commensals, but are also associated with various skin disorders and bloodstream infections. The genus currently comprises 17 species and has recently been assigned its own class, Malasseziomycetes. Importantly, multiple Malassezia species and/or genotypes may cause unique or similar pathologies and vary in their antifungal susceptibility. In addition to culture-based approaches, culture-independent methods have added to our understanding of Malassezia presence and abundance and their relationship to pathogenicity. Moreover, these novel approaches have suggested a much wider-spread presence, including other human body parts and even other ecosystems, but their role in these arenas requires further clarification. With recent successful transformation and genetic engineering of Malassezia, the role of specific genes in pathogenesis can now be studied. We suggest that characterizing the metabolic impact of Malassezia communities rather than species identification is key in elucidation of pathophysiological associations. Finally, the increasing availability of genome sequences may provide key information aiding faster diagnostics, and understanding of the biochemical mechanisms for Malassezia skin adaptation and the design of future drugs.

The terms Pediatric Autoimmune Neuropsychiatric disorders associated with streptococcal infections (PANDAS), Pediatric acute-onset neuropsychiatric Syndrome (PANS), and Childhood Acute Neuropsychiatric Symptoms (CANS) have been used to describe certain acute onset neuropsychiatric pediatric disorders. This clinical characteristic was unusually abrupt onset of obsessive compulsive symptoms and/or severe eating restrictions and concomitant cognitive, behavioral or neurological symptoms. Because the CANS/PANS criteria define a broad spectrum of neuropsychiatric conditions, the syndrome is presumed to result from a variety of disease mechanisms and to have multiple etiologies, ranging from postinfectious autoimmune and neuroinflammatory disorders to toxic, endocrine or metabolic disorders. We suggest a diagnostic flow-chart in case of acute onset neuropsychiatric syndrome to better define diagnostic criteria, identify possible subtypes and delineate treatment.

Background Epileptic encephalopathies represent the most severe epilepsies, with onset in infancy and childhood and seizures continuing in adulthood in most cases. New genetic causes are being identified at a rapid rate. Treatment is challenging and the overall outcome remains poor. Available targeted treatments, based on the precision medicine approach, are currently few. Objective To provide an overview of the treatment of epileptic encephalopathies with known genetic determinants, including established treatment, anecdotal reports of specific treatment, and potential tailored precision medicine strategies. Method Genes known to be associated to epileptic encephalopathy were selected. Genes where the association was uncertain or with no reports of details on treatment, were not included. Although some of the genes included are associated with multiple epilepsy phenotypes or other organ involvement, we have mainly focused on the epileptic encephalopathies and their antiepileptic treatments. Results Most epileptic encephalopathies show genotypic and phenotypic heterogeneity. The treatment of seizures is difficult in most cases. The available evidence may provide some guidance for treatment: for example, ACTH seems to be effective in controlling infantile spams in a number of genetic epileptic encephalopathies. There are potentially effective tailored precision medicine strategies available for some of the encephalopathies, and therapies with currently unexplained effectiveness in others. Conclusions Understanding the effect of the mutation is crucial for targeted treatment. There is a broad range of disease mechanisms underlying epileptic encephalopathies, and this makes the application of targeted treatments challenging. However, there is evidence that tailored treatment could significantly improve epilepsy treatment and prognosis.

Advances in genetic techniques have led to the discovery of new autoinflammatory syndromes in the last three years. The purpose of this review is to discuss novel autoinflammatory syndromes including disease mechanisms, characteristics, and treatments. We will also discuss recent findings regarding the pathophysiology of well-known autoinflammatory disorders. Several recently described autoinflammatory disorders will be discussed including NLRC4-MAS, NAIAD, CANDLE, SAVI, ORAS, HA20, DADA2, and APLAID. There is now a better understanding of the pathophysiology of autoinflammatory disorders that has allowed for categorization of these disorders into interferonopathies, inflammasome mediated, or NF-κB dysregulated. With a better understanding of these disorders, targeted treatments based on their mechanism are now possible. Some of these disorders have an unknown mechanism of action, and novel disorders are likely. Further research on autoinflammatory disorders is necessary to improve the outcomes of these patients.

The discovery of induced pluripotent stem cells (iPSC) 12 years ago has fostered the development of innovative patient-derived in vitro models for better understanding of disease mechanisms. This is particularly relevant to neurodegenerative diseases, where availability of live human brain tissue for research is limited and post-mortem interval changes influence readouts from autopsy-derived human tissue. Hundreds of iPSC lines have now been prepared and banked, thanks to several large scale initiatives and cell banks. Patient- or engineered iPSC-derived neural models are now being used to recapitulate cellular and molecular aspects of a variety of neurodegenerative diseases, including early and pre-clinical disease stages. The broad relevance of these models derives from the availability of a variety of differentiation protocols to generate disease-specific cell types and the manipulation to either introduce or correct disease-relevant genetic modifications. Moreover, the use of chemical and physical three-dimensional (3D) matrices improves control over the extracellular environment and cellular organization of the models. These iPSC-derived neural models can be utilised to identify target proteins and, importantly, provide high-throughput screening for drug discovery. Choosing Alzheimer’s disease (AD) as an example, this review describes 3D iPSC-derived neural models and their advantages and limitations. There is now a requirement to fully characterise and validate these 3D iPSC-derived neural models as a viable research tool that is capable of complementing animal models of neurodegeneration and live human brain tissue. With further optimization of differentiation, maturation and aging protocols, as well as the 3D cellular organisation and extracellular matrix to recapitulate more closely, the molecular extracellular-environment of the human brain, 3D iPSC-derived models have the potential to deliver new knowledge, enable discovery of novel disease mechanisms and identify new therapeutic targets for neurodegenerative diseases.

Differential coexpression analysis has gradually become an important approach to improve the conventional method of analysing differentially expressed genes. With this approach, it is possible to discover disease mechanisms and underlying regulatory dynamics which remain obscure in differential expression analysis. The detection of differential coexpression links and functional clusters between different disease states is a demanding task. Nevertheless, there is no gold standard for detecting differential coexpression links and functional clusters. Consequently, we developed a novel fusion algorithm FDvDe (Fusion of differential vertex and differential edge) to detect differential coexpression links by aggregating the set of ‘differential vertex’ and ‘differential edge.’ Then, we constructed differential coexpression networks between normal and tumour states by integrating the differential coexpression links. With this approach, we identified 1823 genes and 29370 links. Then, we developed the algorithms GTHC (GO term hierarchical clusters) to identify functional modules. The distance matrix used in the hierarchical process was formed by the GO semantic similarity. Furthermore, we aggregated the densities among clusters describing the connectivity among clusters and topological property analysis to discover the hub genes and hub pathways which play an important role in disease mechanism. In this paper, we showed that our approach worked well on a data set of breast cancer samples (68 tumour samples) and normal samples (73 normal samples), and revealed the crucial role and biological significance of the modules and hub genes found in this approach.

Epilepsy is a common and serious neurologic disease with a strong genetic component. Genetic studies have identified an increasing collection of disease-causing genes. The impact of these genetic discoveries is wide reaching—from precise diagnosis and classification of syndromes to the discovery and validation of new drug targets and the development of disease-targeted therapeutic strategies. About 25% of genes identified in epilepsy encode ion channels. Much of our understanding of disease mechanisms comes from work focused on this class of protein. In this study, we review the genetic, molecular, and physiologic evidence supporting the pathogenic role of a number of different voltage- and ligand-activated ion channels in genetic epilepsy. We also review proposed disease mechanisms for each ion channel and highlight targeted therapeutic strategies.