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Protein domains can be viewed as portable units of biological function that defines the functional properties of proteins. Therefore, if a protein is associated with a disease, protein domains might also be associated and define disease endophenotypes. However, knowledge about such domain-disease relationships is rarely available. Thus, identification of domains associated with human diseases would greatly improve our understanding of the mechanism of human complex diseases and further improve the prevention, diagnosis and treatment of these diseases.
Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies.
According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.
Alzheimer's disease (AD) is an age-dependent neurodegenerative disorder and the most common cause of dementia. The early stages of AD are characterized by short-term memory loss. Once the disease progresses, patients experience difficulties in sense of direction, oral communication, calculation, ability to learn, and cognitive thinking. The median duration of the disease is 10 years. The pathology is characterized by deposition of amyloid beta peptide (so-called senile plaques) and tau protein in the form of neurofibrillary tangles. Currently, two classes of drugs are licensed by the European Medicines Agency for the treatment of AD, ie, acetylcholinesterase inhibitors for mild to moderate AD, and memantine, an N-methyl-D-aspartate receptor antagonist, for moderate and severe AD. Treatment with acetylcholinesterase inhibitors or memantine aims at slowing progression and controlling symptoms, whereas drugs under development are intended to modify the pathologic steps leading to AD. Herein, we review the clinical features, pharmacologic properties, and cost-effectiveness of the available acetylcholinesterase inhibitors and memantine, and focus on disease-modifying drugs aiming to interfere with the amyloid beta peptide, including vaccination, passive immunization, and tau deposition.
Although Gaucher disease can be accompanied by Lewy pathology (LP) and extrapyramidal symptoms, it is unknown if LP exists in Fabry disease (FD), another progressive multisystem lysosomal storage disorder. We aimed to elucidate the distribution patterns of FD-related inclusions and LP in the brain of a 58-year-old cognitively unimpaired male FD patient suffering from predominant hypokinesia. Immunohistochemistry (CD77, α-synuclein, collagen IV) and neuropathological staging were performed on 100-µm sections. Tissue from the enteric or peripheral nervous system was unavailable. As controls, a second cognitively unimpaired 50-year-old male FD patient without LP or motor symptoms and 3 age-matched individuals were examined. Inclusion body pathology was semiquantitatively evaluated. Although Lewy neurites/bodies were not present in the 50-year-old individual or in controls, severe neuronal loss in the substantia nigra pars compacta and LP corresponding to neuropathological stage 4 of Parkinson disease was seen in the 58-year-old FD patient. Major cerebrovascular lesions and/or additional pathologies were absent in this individual. We conclude that Lewy body disease with parkinsonism can occur within the context of FD. Further studies determining the frequencies of both inclusion pathologies in large autopsy-controlled FD cohorts could help clarify the implications of both lesions for disease pathogenesis, potential spreading mechanisms, and therapeutic interventions.
Background: The characterizing symptom of Alzheimer disease (AD) is cognitive deterioration. While much recent work has focused on defining AD as a biological construct, most patients are still diagnosed, staged, and treated based on their cognitive symptoms. But the cognitive capability of a patient at any time throughout this deterioration reflects not only the disease state, but also the effect of the cognitive decline on the patient's pre-disease cognitive capability. Patients with high pre-disease cognitive capabilities tend to score better on cognitive tests that are sensitive early in disease relative to patients with low pre-disease cognitive capabilities at a similar disease stage. Thus, a single assessment with a cognitive test is often not adequate for determining the stage of an AD patient. Repeated evaluation of patients' cognition over time may improve the ability to stage AD patients, and such longitudinal assessments in combinations with biomarker assessments can help elucidate the time dynamics of biomarkers. In turn, this can potentially lead to identification of markers that are predictive of disease stage and future cognitive decline, possibly before any cognitive deficit is measurable. Methods and Findings: This article presents a class of statistical disease progression models and applies them to longitudinal cognitive scores. These non-linear mixed-effects disease progression models explicitly model disease stage, baseline cognition, and the patients' individual changes in cognitive ability as latent variables. Maximum-likelihood estimation in these models induces a data-driven criterion for separating disease progression and baseline cognition. Applied to data from the Alzheimer's Disease Neuroimaging Initiative, the model estimated a timeline of cognitive decline that spans ~15 years from the earliest subjective cognitive deficits to severe AD dementia. Subsequent analyses demonstrated how direct modeling of latent factors that modify the observed data patterns provides a scaffold for understanding disease progression, biomarkers, and treatment effects along the continuous time progression of disease. Conclusions: The presented framework enables direct interpretations of factors that modify cognitive decline. The results give new insights to the value of biomarkers for staging patients and suggest alternative explanations for previous findings related to accelerated cognitive decline among highly educated patients and patients on symptomatic treatments.
Nonalcoholic fatty liver disease is increasingly recognized as a major global health problem. Intertwined with diabetes, metabolic syndrome, and obesity, nonalcoholic fatty liver disease embraces a spectrum of liver conditions spanning from steatosis to inflammation, fibrosis, and liver failure. Compared with the general population, the prevalence of cardiovascular disease is higher among nonalcoholic fatty liver disease patients, in whom comprehensive cardiovascular risk assessment is highly desirable. Preclinical effects of nonalcoholic fatty liver disease on the heart include both metabolic and structural changes eventually preceding overt myocardial dysfunction. Particularly, nonalcoholic fatty liver disease is associated with enhanced atherosclerosis, heart muscle disease, valvular heart disease, and arrhythmias, with endothelial dysfunction, inflammation, metabolic dysregulation, and oxidative stress playing in the background. In this topical review, we aimed to summarize current evidence on the epidemiology of nonalcoholic fatty liver disease, discuss the pathophysiological links between nonalcoholic fatty liver disease and cardiovascular disease, illustrate nonalcoholic fatty liver disease-related cardiovascular phenotypes, and finally provide a glimpse on the relationship between nonalcoholic fatty liver disease and cardiac steatosis, mitochondrial (dys)function, and cardiovascular autonomic dysfunction.
Gallstone disease (GD) is a common digestive disorder that shares many risk factors with cardiovascular disease (CVD). CVD is an important public health issue that encompasses a large percentage of overall mortality. Several recent studies have suggested an association between GD and CVD, while others have not. In this report, we present a meta-analysis of cohort studies to assess the association between GD and CVD. We included eight studies published from 1980 to 2017, including nearly one million participants. The pooled relative risk (RR, 95% confidence interval [CI]) from the random-effects model associates with GD is 1.23 (95% CI: 1.17-1.30) for fatal and nonfatal CVD events. The pooled RR from the random-effects model of CVD events in female patients with GD is 1.24 (95% CI: 1.16-1.32). In male GD patients, the pooled RR from the random-effects model for CVD is 1.18 (95% CI: 1.06-1.31). Our meta-analysis demonstrates a substantially increased risk of fatal and nonfatal CVD events among patients with a medical history of GD. We suggest that interested investigators should further pursue the subject. In addition, both male and female patients with GD have a risk of CVD, and women have a higher risk than men.
The Disease Ontology (DO) database (http://disease-ontology.org) represents a comprehensive knowledge base of 8043 inherited, developmental and acquired human diseases (DO version 3, revision 2510). The DO web browser has been designed for speed, efficiency and robustness through the use of a graph database. Full-text contextual searching functionality using Lucene allows the querying of name, synonym, definition, DOID and cross-reference (xrefs) with complex Boolean search strings. The DO semantically integrates disease and medical vocabularies through extensive cross mapping and integration of MeSH, ICD, NCI's thesaurus, SNOMED CT and OMIM disease-specific terms and identifiers. The DO is utilized for disease annotation by major biomedical databases (e.g. Array Express, NIF, IEDB), as a standard representation of human disease in biomedical ontologies (e.g. IDO, Cell line ontology, NIFSTD ontology, Experimental Factor Ontology, Influenza Ontology), and as an ontological cross mappings resource between DO, MeSH and OMIM (e.g. GeneWiki). The DO project (http://diseaseontology.sf.net) has been incorporated into open source tools (e.g. Gene Answers, FunDO) to connect gene and disease biomedical data through the lens of human disease. The next iteration of the DO web browser will integrate DO's extended relations and logical definition representation along with these biomedical resource cross-mappings.
Gallstone disease (GD) is one of the most common presentations to surgical units worldwide and shares several risk factors with cardiovascular disease (CVD). CVD remains the most common cause of death worldwide and results in considerable economic burden. Recent observational studies have demonstrated an association between GD and CVD with some studies demonstrating a stronger association with cholecystectomy. We present the findings of a meta-analysis assessing the relationship between GD and CVD. A total of fourteen cohort studies with over 1.2 million participants were included. The pooled hazard ratio (HR, 95% confidence interval [CI]) for association with GD from a random-effects model is 1.23 (95%CI: 1.16-1.30) for fatal and non-fatal CVD events. The association was present in females and males. Three studies report the relationship between cholecystectomy and CVD with a pooled HR of 1.41 (95%CI: 1.21-1.64) which compares to a HR of 1.30 (95%CI: 1.07-1.58) when cholecystectomy is excluded although confounding may influence this result. Our meta-analysis demonstrates a significant relationship between GD and CVD events which is present in both sexes. Further research is needed to assess the influence of cholecystectomy on this association.
Huntington disease (HD) is a common autosomal dominant neurodegenerative disease with early adult-onset motor abnormalities and dementia. Many studies of HD show that huntingtin (CAG)n repeat-expansion length is a sensitive and specific marker for HD. However, there are a significant number of examples of HD in the absence of a huntingtin (CAG)n expansion, suggesting that mutations in other genes can provoke HD-like disorders. The identification of genes responsible for these "phenocopies" may greatly improve the reliability of genetic screens for HD and may provide further insight into neurodegenerative disease. We have examined an HD phenocopy pedigree with linkage to chromosome 20p12 for mutations in the prion protein (PrP) gene (PRNP). This reveals that affected individuals are heterozygous for a 192-nucleotide (nt) insertion within the PrP coding region, which encodes an expanded PrP with eight extra octapeptide repeats. This reveals that this HD phenocopy is, in fact, a familial prion disease and that PrP repeat-expansion mutations can provoke an HD "genocopy." PrP repeat expansions are well characterized and provoke early-onset, slowly progressive atypical prion diseases with an autosomal dominant pattern of inheritance and a remarkable range of clinical features, many of which overlap with those of HD. This observation raises the possibility that an unknown number of HD phenocopies are, in fact, familial prion diseases and argues that clinicians should consider screening for PrP mutations in individuals with HD-like diseases in which the characteristic HD (CAG)n repeat expansions are absent.
Small vessel cerebrovascular disease, visualized as white matter hyperintensities on T2-weighted magnetic resonance imaging, contributes to the clinical presentation of Alzheimer's disease. However, the extent to which cerebrovascular disease represents an independent pathognomonic feature of Alzheimer's disease or directly promotes Alzheimer's pathology is unclear. The purpose of this study was to examine the association between white matter hyperintensities and plasma levels of tau and to determine if white matter hyperintensities and tau levels interact to predict Alzheimer's disease diagnosis. To confirm that cerebrovascular disease promotes tau pathology, we examined tau fluid biomarker concentrations and pathology in a mouse model of ischaemic injury. Three hundred ninety-one participants from the Alzheimer's Disease Neuroimaging Initiative (74.5 ± 7.1 years of age) were included in this cross-sectional analysis. Participants had measurements of plasma total-tau, cerebrospinal fluid beta-amyloid, and white matter hyperintensities, and were diagnosed clinically as Alzheimer's disease (n = 97), mild cognitive impairment (n = 186) or cognitively normal control (n = 108). We tested the relationship between plasma tau concentration and white matter hyperintensity volume across diagnostic groups. We also examined the extent to which white matter hyperintensity volume, plasma tau, amyloid positivity status and the interaction between white matter hyperintensities and plasma tau correctly classifies diagnostic category. Increased white matter hyperintensity volume was associated with higher plasma tau concentration, particularly among those diagnosed clinically with Alzheimer's disease. Presence of brain amyloid and the interaction between plasma tau and white matter hyperintensity volume distinguished Alzheimer's disease and mild cognitive impairment participants from controls with 77.6% and 63.3% accuracy, respectively. In 63 Alzheimer's Disease Neuroimaging Initiative participants who came to autopsy (82.33 ± 7.18 age at death), we found that higher degrees of arteriosclerosis were associated with higher Braak staging, indicating a positive relationship between cerebrovascular disease and neurofibrillary pathology. In a transient middle cerebral artery occlusion mouse model, aged mice that received transient middle cerebral artery occlusion, but not sham surgery, had increased plasma and cerebrospinal fluid tau concentrations, induced myelin loss, and hyperphosphorylated tau pathology in the ipsilateral hippocampus and cerebral hemisphere. These findings demonstrate a relationship between cerebrovascular disease, operationalized as white matter hyperintensities, and tau levels, indexed in the plasma, suggesting that hypoperfusive injury promotes tau pathology. This potential causal association is supported by the demonstration that transient cerebral artery occlusion induces white matter damage, increases biofluidic markers of tau, and promotes cerebral tau hyperphosphorylation in older-adult mice.
Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's and RGD's disease term annotations identified new terms that enhance DO's representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO's usability across human data, MGD, RGD and the rest of the model organism database community.
The Rat Genome Database (RGD;http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene-disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL:http://rgd.mcw.edu.
The role of non-neuronal cells in Alzheimer's disease progression has not been fully elucidated. Using single-nucleus RNA sequencing, we identified a population of disease-associated astrocytes in an Alzheimer's disease mouse model. These disease-associated astrocytes appeared at early disease stages and increased in abundance with disease progression. We discovered that similar astrocytes appeared in aged wild-type mice and in aging human brains, suggesting their linkage to genetic and age-related factors.
This review is based on the material obtained via MEDLINE (PubMed), EMBASE, and Clinical Trials databases, from January 1980 until May 2019. The search term used was "Alzheimer's disease," combined with "cardiovascular disease," "hypertension," "dyslipidaemia," "diabetes mellitus," "atrial fibrillation," "coronary artery disease," "heart valve disease," and "heart failure." Out of the 1,328 papers initially retrieved, 431 duplicates and 216 records in languages other than English were removed. Among the 681 remaining studies, 98 were included in our research material on the basis of the following inclusion criteria: (a) the community-based studies; (b) using standardized diagnostic criteria; (c) reporting raw prevalence data; (d) with separate reported data for sex and age classes.
An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time.
Sickle cell disease afflicts millions of people worldwide and approximately 100,000 Americans. Complications are myriad and arise as a result of complex pathological pathways 'downstream' to a point mutation in DNA, and include red blood cell membrane damage, inflammation, chronic hemolytic anemia with episodic vaso-occlusion, ischemia and pain, and ultimately risk of cumulative organ damage with reduced lifespan of affected individuals. The National Heart, Lung, and Blood Institute's 2014 evidence-based guideline for sickle cell disease management states that additional research is needed before investigational curative therapies will be widely available to most patients with sickle cell disease. To date, sickle cell disease has been cured by hematopoietic stem cell transplantation in approximately 1,000 people, most of whom were children, and significantly ameliorated by gene therapy in a handful of subjects who have only limited follow-up thus far. During a timespan in which over 20 agents were approved for the treatment of cystic fibrosis by the Food and Drug Administration, similar approval was granted for only two drugs for sickle cell disease (hydroxyurea and L-glutamine) despite the higher prevalence of sickle cell disease. This trajectory appears to be changing, as the lack of multimodal agent therapy in sickle cell disease has spurred engagement among many in academia and industry who, in the last decade, have developed new drugs poised to prevent complications and alleviate suffering. Identified therapeutic strategies include fetal hemoglobin induction, inhibition of intracellular HbS polymerization, inhibition of oxidant stress and inflammation, and perturbation of the activation of the endothelium and other blood components (e.g. platelets, white blood cells, coagulation proteins) involved in the pathophysiology of sickle cell disease. In this article, we present a crash-course review of disease-modifying approaches (minus hematopoietic stem cell transplant and gene therapy) for patients with sickle cell disease currently, or recently, tested in clinical trials in the era following approval of hydroxyurea.
From a group of 115 children with hereditary haemorrhagic disease, nine suffered avoidable accidents or incidents during their treatment, these nine patients represent 8.6% of the cases. The observed complications included a giant cervical hematoma and hemomediastinum after a puncture of the internal jugular vein; an encephalic lesion associated with descompressive craneotomy; a hemophilic pseudo cyst associated with inappropriate treatment of a tibial fracture; acute bleeding and shock after surgery for tonsillectomy and circumcision; subdural hygroma after a subdural puncture; giant hematoma and acute anemia secondary to a venous dissection; permanent dyslexia after inappropriate puncture; giant hematoma and acute anemia secondary to a venous dissection; permanent dyslexia after inappropriate management of intracranial bleeding; bleeding and acute anemia after surgical drainage of a prepucial hematoma and a joint hematoma of the left knee after synovectomy and application of a prosthesis.
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