The lysosomal degradation of neuromedin B is dependent on tripeptidyl peptidase-I: evidence for the impairment of neuropeptide degradation in late-infantile neuronal ceroid lipofuscinosis

Late-infantile neuronal ceroid lipofuscinosis (CLN2), previously known as the late-infantile form of Batten disease, is a lysosomal storage disease which results from mutations in the gene that codes for tripeptidyl peptidase-I (TPP-I). This disease is characterised by progressive neurodegeneration in young children although the molecular mechanisms responsible for neuronal cell death are unclear. TPP-I is an exopeptidase which removes N-terminal tripeptides from small peptides, including several peptide hormones. We report that the degradation of the neuropeptide, neuromedin B, by mouse brain cells is restricted to lysosomes and that the pattern of degradation products is consistent with a predominant role for TPP-I. Neuromedin B is degraded by a similar pathway in a mouse neuronal cell line and also in cultured human fibroblasts. A specific inhibitor of TPP-I is able to abolish neuromedin B degradation in a variety of cell types. Fibroblasts from CLN2 patients, which are deficient in TPP-I activity, are unable to degrade neuromedin B. These observations suggest that TPP-I is the predominant proteolytic enzyme responsible for the intracellular degradation of neuromedin B. The inability of cells from CLN2 patients to degrade neuromedin B and other neuropeptides may contribute to the pathogenesis of the disease.     

Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data

Population-level disease risk varies between communities, and public health professionals are interested in mapping this spatial variation to monitor the locations of high-risk areas and the magnitudes of health inequalities. Almost all of these risk maps relate to a single severity of disease outcome, such as hospitalization, which thus ignores any cases of disease of a different severity, such as a mild case treated in a primary care setting. These spatially-varying risk maps are estimated from spatially aggregated disease count data, but the set of areal units to which these disease counts relate often varies by severity. Thus, the statistical challenge is to provide spatially comparable inference from multiple sets of spatially misaligned disease count data, and an additional complexity is that the spatial extents of the areal units for some severities are partially unknown. This paper thus proposes a novel spatial realignment approach for multivariate misaligned count data, and applies it to the first study delivering spatially comparable inference for multiple severities of the same disease. Inference is via a novel spatially smoothed data augmented MCMC algorithm, and the methods are motivated by a new study of respiratory disease risk in Scotland in 2017.     

Socialization strategies and disease transmission in captive colonies of nonhuman primates

In captive research environments for nonhuman primates (NHP), social housing strategies are often in conflict with protocols designed to minimize disease transmission. This is particularly true in breeding colonies, and is especially relevant when attempting to eliminate specific pathogens from a population of primates. Numerous strategies have been used to establish such specific pathogen free (SPF) breeding colonies (primarily of macaques), ranging from nursery rearing of neonates to single housing of socially reared yearlings to the rearing of infants in large social groups. All these strategies attempt to balance the effects of the chosen socialization strategy on parameters related to disease transmission, including the ultimate elimination of the target pathogens. Such strategies may affect the overall disease states of NHP breeding colonies through selective breeding processes. This can occur either by creating subpopulations of animals that do not have target diseases (SPF colonies), but may have other issues; or by creating situations in which the "best" animals are sold and the breeding colony is stocked with animals that may be more disease susceptible than those that were sold. The disease states of NHP research colonies also may be affected by selective utilization programs, in which animals removed from the breeding colony for health/behavior reasons, are preferentially chosen for use in scientific investigations. Such utilization criteria raise the question of whether ideal subjects are being chosen for use in research. Finally, captive primate colonies, where both socialization and disease states are intensely managed, may provide opportunities for those testing predictions from models of the interactions of socialization and disease transmission in the evolution of wild populations of NHP. This would be especially true for some extreme conditions of these disease ecology models, given the exceedingly high social densities and levels of pathogen control that exist in many captive nonhuman primate colonies.     

Dynamics of an SIQS epidemic model with transport-related infection and exit-entry screenings

Population dispersal, as a common phenomenon in human society, may cause the spreading of many diseases such as influenza, SARS, etc. which are easily transmitted from one region to other regions. Exit and entry screenings at the border are considered as effective ways for controlling the spread of disease. In this paper, the dynamics of an SIQS model are analyzed and the combined effects of transport-related infection enhancing and exit-entry screenings suppressing on disease spread are discussed. The basic reproduction number is computed and proved to be a threshold for disease control. If it is not greater than the unity, the disease free equilibrium is globally asymptotically stable. And there exists an endemic equilibrium which is locally asymptotically stable if the reproduction number is greater than unity. It is shown that the disease is endemic in the sense of permanence if and only if the endemic equilibrium exists. Exit screening and entry screening are shown to be helpful for disease eradication since they can always have the possibility to eradicate the disease endemic led by transport-related infection and furthermore have the possibility to eradicate disease even when the isolated cites are disease endemic.     

A Pathway-Based View of Human Diseases and Disease Relationships

It is increasingly evident that human diseases are not isolated from each other. Understanding how different diseases are related to each other based on the underlying biology could provide new insights into disease etiology, classification, and shared biological mechanisms. We have taken a computational approach to studying disease relationships through 1) systematic identification of disease associated genes by literature mining, 2) associating diseases to biological pathways where disease genes are enriched, and 3) linking diseases together based on shared pathways. We identified 4,195 candidate disease associated genes for 1028 diseases. On average, about 50% of disease associated genes of a disease are statistically mapped to pathways. We generated a disease network which consists of 591 diseases and 6,931 disease relationships. We examined properties of this network and provided examples of novel disease relationships which cannot be readily captured through simple literature search or gene overlap analysis. Our results could potentially provide insights into the design of novel, pathway-guided therapeutic interventions for diseases.     

From sheep to mice to cells: Tools for the study of the sphingolipidoses

The sphingolipidoses are a group of inherited lysosomal storage diseases in which sphingolipids accumulate due to the defective activity of one or other enzymes involved in their degradation. For most of the sphingolipidoses, little is known about the molecular mechanisms that lead to disease, which has negatively impacted attempts to develop therapies for these devastating human diseases. Use of both genetically-modified animals, ranging from mice to larger mammals, and of novel cell culture systems, is of utmost importance in delineating the molecular mechanisms that cause pathophysiology, and in providing tools that enable testing the efficacy of new therapies. In this review, we discuss eight sphingolipidoses, namely Gaucher disease, Fabry disease, metachromatic leukodystrophy, Krabbe disease, Niemann–Pick diseases A and B, Farber disease, GM1 gangliosidoses, and GM2 gangliosidoses, and describe the tools that are currently available for their study. This article is part of a Special Issue entitled Tools to study lipid functions.     

Understanding diet-gene interactions: lessons from studying nutrigenomics and cardiovascular disease

Socioeconomic development has resulted in an epidemiologic transition which has involved an increase in mortality and morbidity from chronic non-communicable diseases. Cardiovascular disease is one such disease. The rapidity with which this transition has occurred suggests that genetic factors are unlikely to be responsible. However, studies in twins suggest significant heritability for cardiovascular disease and its associated risk factors. We present data showing diet-gene interactions involving polymorphisms at the PPARA and PLIN loci. These data support the hypothesis that chronic diseases such as cardiovascular disease are a consequence of a complex interplay of genetic and environmental factors, of which diet plays an important role. They suggest that the effects of diet on chronic disease may be masked by heterogeneity of effect related to genetic variability between individuals and that consideration of diet-gene interactions may contribute to our understanding of the pathogenesis of cardiovascular disease. The identification of diet-gene interactions offers us an opportunity to develop dietary interventions that will obviate the effects of genetic factors on the risk of disease. In this way, we may be able to develop personalized dietary recommendations that optimize the outcome for the individual concerned. Nevertheless, while existing data points to the value of these studies, significant challenges need to be met to ensure that our conclusions are scientifically valid.     

Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray co-expressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown.     

How diseases affect symbiotic communities

Examples of species living in symbiotic communities are well known among biologists. In this study we extend our previous analysis of predator-prey or competing models subject to a disease spreading among one of the species to populations mutually benefiting from interactions. We assume that one of the species is subject to a disease which cannot cross the species barrier and investigate the behavior of such a community. Our findings indicate that there are parameter ranges for which an interesting phenomenon occurs. Namely, the equilibrium shifts to a higher value. That is, the disease seems to have a positive effect on the environment as also field experiments show.     

Histoplasmosis—A Review of Three Cases Studied in San Diego County

Three cases of histoplasmosis, a disease seldom reported in California, were diagnosed clinically by the authors in San Diego County. It is probable that there is a higher incidence of this disease in California than is at present recognized.Travel history, histoplasmin skin testing and serologic studies for mycotic infection are important in the diagnosis. Cultures of secretions and biopsy material are of great value if positive; but negative cultures (at least in non-endemic areas) do not rule out the disease. Travel and migration to and from endemic areas present opportunities for this disease to constitute a diagnostic problem far from the geographic area in which the disease was acquired.Although usually benign, histoplasmosis may be severe in the acute state, may disseminate or may be chronically active and progressive. Amphotericin B is the only effective chemotherapeutic agent and it is usually reserved for these forms of the disease.     

The Leeuwenhoek Lecture, 1997. Marek's disease herpesvirus: oncogenesis and prevention.

There are a number of neoplasias for which a herpesvirus is an essential part of the aetiology. Of these, Marek''s disease is the most common and provides excellent opportunities for the study of a herpesvirus-induced tumour both experimentally and under natural conditions in the field. Marek''s disease is caused by an alpha herpesvirus; it differs from the other oncogenic herpesviruses which are gamma herpesviruses. It is a ubiquitous virus in poultry populations of the world and is highly cell-associated and contagious, yet only a proportion of infected fowl develop tumours. Evidence is presented to suggest that at least one of the reasons for a wide variation in the incidence of the disease is a temporal interplay between virulent viruses and viruses of low or no virulence. The viral genes associated with the oncogenicity of Marek''s disease virus (MDV) are discussed and it is concluded that it is likely that several genes are involved. Finally, a brief history of vaccination to control Marek''s disease is given and mode of action discussed. It is concluded that the mechanism of protection is mainly through an antiviral cell mediated immune response, resulting in a lowered challenge virus burden. Marek''s disease viruses over the past 40 years have been evolving greater oncogenicity, some of which are not adequately controlled by the vaccines that are currently available. It is suggested that for MDV to produce tumours, there is a need for the cytolytic infection phase and that infection must be with an MDV which possesses a functional gC, ICP4 for maintaining latency which allows the expression of at least the 1.8 kb family, pp38, meq, and possibly pp14 genes, for maintaining the tumour state and possibly initiating this state. Intervention in this process reduces the chance of tumour formation and incidence in a population which can occur through natural or man-mediated infection with non-pathogenic MDVs.     

Contributions to the mathematical theory of epidemics—II. The problem of endemicity

(1) A mathematical investigation has been made of the prevalence of a disease in a population from which certain individuals are being removed as the result of the disease, whilst fresh individuals are being introduced as the result of birth or immigration. Allowance is made for the effects of the immunity produced as the result of an attack of the disease, but the effect of deaths from other causes is not taken into account, and the action of the disease is supposed to be independent of the age of the individual. (2) As a special case of the above, results have been obtained for a closed population in which no deaths occur and to which no fresh individuals are added, but in which the individuals after being infected acquire immunity, and then may be again infected. A threshold density of population exists analogous to that described in the previous paper, which is such that no disease can exist in a population, the density of which is below the threshold. (3) In other special cases investigated when either immigration or birth is operative in the supply of fresh individuals, as well as in the general case, only one steady state of disease is possible. To reach this state the population must be of a certain density which will be determined by the functions characterizing the infectivity, morbidity, etc., of the disease. (4) Increase of the immigration rate or of the birth-rate results in an increase in the rate of infection of the healthy individuals and also in the percentage rate of infection, the percentage of sick, and in the percentage of mortality from the disease. This result is, of course, a necessary consequence of our assumption that the disease is the only cause of death. (5) More particular results have been obtained by substituting constants in the place of the undetermined functions assumed in the general theory. Further, under these conditions the nature of the steady states has been more fully investigated and it has been shown that in all cases, except one, the steady states are stable ones. In the exception, a disturbance would result in purely periodic oscillations about the steady state.     

Etiologic theories,methods of treatment,and results

Although it has been postulated that a pterygium develops from the ordinary pinguecula which is a phenomenon of aging, the average age of patients in a Veterans Administration hospital who were operated upon for removal of pterygia was 34.9 years. Mexicans appeared to be particularly susceptible to the disease. Analysis of the literature and review of observations in the present series of cases indicated that long-continued exposure to the elements, particularly the sun's rays, is a prime etiologic factor and that dust and other irritants are of less importance. In a study of 285 patients who had pterygia, no correlation of this disease with other local or general disease was observed. An operation which brings previously unexposed conjunctiva into the area from which a pterygium is removed, and which does not bury the epithelium, was used successfully.     

Prediction of individual genetic risk of complex disease

Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each individual person's genetic risk for a disease? In this review we consider the lessons from GWAS and the implications for genetic risk prediction to common disease. We conclude that with larger GWAS sample sizes or by combining studies, accurate prediction of genetic risk will be possible, even if the causal mutations or the mechanisms by which they affect susceptibility are unknown.     

How to make predictions about future infectious disease risks

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the 'art of the possible', which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for 'good practice' for the development and the use of predictive models.     

Long chain omega-3 fatty acids: Micronutrients in disguise

Considerable information has accumulated to show that DHA and EPA have unique roles that differ from other n-3 fatty acids and the n-6 fatty acids, with increasing understanding of the mechanisms through which these fatty acids reduce risk of disease. DHA and EPA regulate hepatic lipid and glucose metabolism, but are present in foods of animal origin, which are generally high in protein with variable triglycerides and low carbohydrate. Biological activity at intakes too low to provide significant amounts of energy is consistent with the definition of a vitamin for which needs are modified by life-stage, diet and genetic variables, and disease. Recent studies reveal that DHA may play a central role in co-coordinating complex networks that integrate hepatic glucose, fatty acid and amino acid metabolism for the purpose of efficient utilization of dietary protein, particularly during early development when the milk diet provides large amounts of energy from fat.     

Studying the global distribution of infectious diseases using GIS and RS

West Nile virus, severe acute respiratory syndrome and monkeypox are infectious diseases that have recently been introduced into areas far from their region of origin. The greatest risk of new diseases comes from zoonoses--pathogens that circulate among wild animals and are occasionally transferred to humans by intermediate invertebrate hosts or vectors that are sensitive to climatic conditions. Analytical tools that are based on geographical information systems and that can incorporate remotely sensed information about the environment offer the potential to define the limiting conditions for any disease in its native region for which there are at least some distribution data. The direction, intensity or likelihood of its spread to new regions could then be predicted, potentially allowing disease early-warning systems to be developed.     

Mechano-potential etiologies of aortic valve disease

Aortic valve leaflets experience varying applied loads during the cardiac cycle. These varying loads act on both cell types of the leaflets, endothelial and interstitial cells, and cause molecular signaling events that are required for repairing the leaflet tissue, which is continually damaged from the applied loads. However, with increasing age, this reparative mechanism appears to go awry as valve interstitial cells continue to remain in their ‘remodeling’ phenotype and subsequently cause the tissue to become stiff, which results in heart valve disease. The etiology of this disease remains elusive; however, multiple clues are beginning to coalesce and mechanical cues are turning out to be large predicators of cellular function in the aortic valve leaflets, when compared to the cells from the pulmonary valve leaflets, which are under a significantly less demanding mechanical loading regime. Finally, this paper discusses the mechanical environment of the constitutive cell populations, mechanobiological processes that are currently unclear, and a mechano-potential etiology of aortic disease will be presented.     

The future of the management of ischaemic heart disease.

Ischaemic heart disease will kill over 150,000 people in the next year in Britain, more than any other single disease process, and cost more than 1.4bn pounds in health care alone. Faced with the continuing problems arising from ischaemic heart disease cardiological clinician scientists are moving from technology based solutions to basic sciences. This article explains how basic science may contribute to new understanding and treatments for patients with ischaemic heart disease. Highlighted are three problems which face any clinical cardiologist on a daily basis and for which basic science may provide solutions: the uncertainty of plaque stability in coronary disease; restenosis after percutaneous transluminal angioplasty; and the shortage of organs for cardiac transplant programmes for patients with heart failure.