An overview on the correlation of neurological disorders with cardiovascular disease

Neurological disorders (NDs) are one of the leading causes of death especially in the developed countries. Among those NDs, Alzheimer’s disease (AD) and Parkinson disease (PD) are heading the table. There have been several reports in the scientific literatures which suggest the linkage between cardiovascular disorders (CVDs) and NDs. In the present communication, we have tried to compile NDs (AD and PD) association with CVDs reported in the literature. Based on the available scientific literature, we believe that further comprehensive study needs to be done to elucidate the molecular linking points associated with the above mentioned disorders.Abbreviations: AD, Alzheimer’s disease, Aβ, β amyloid, PD, Parkinson disease, l-DOPA, l-dihydroxyphenylalanine, LBs, Lewy bodies, DA, dopamine, APP, amyloid precursor protein, CVD, cardiovascular disease     

Genetic Variants in Diseases of the Extrapyramidal System

Knowledge on the genetics of movement disorders has advanced significantly in recent years. It is now recognized that disorders of the basal ganglia have genetic basis and it is suggested that molecular genetic data will provide clues to the pathophysiology of normal and abnormal motor control. Progress in molecular genetic studies, leading to the detection of genetic mutations and loci, has contributed to the understanding of mechanisms of neurodegeneration and has helped clarify the pathogenesis of some neurodegenerative diseases. Molecular studies have also found application in the diagnosis of neurodegenerative diseases, increasing the range of genetic counseling and enabling a more accurate diagno-sis. It seems that understanding pathogenic processes and the significant role of genetics has led to many experiments that may in the future will result in more effective treatment of such diseases as Parkinson’s or Huntington’s. Currently used molecular diagnostics based on DNA analysis can identify 9 neurodegenerative diseases, including spinal cerebellar ataxia inherited in an autosomal dominant manner, dentate-rubro-pallido-luysian atrophy, Friedreich’s disease, ataxia with ocu-lomotorapraxia, Huntington''s disease, dystonia type 1, Wilson’s disease, and some cases of Parkinson''s disease.     

The dominantly expressed class II molecule from a resistant MHC haplotype presents only a few Marek’s disease virus peptides by using an unprecedented binding motif

Viral diseases pose major threats to humans and other animals, including the billions of chickens that are an important food source as well as a public health concern due to zoonotic pathogens. Unlike humans and other typical mammals, the major histocompatibility complex (MHC) of chickens can confer decisive resistance or susceptibility to many viral diseases. An iconic example is Marek’s disease, caused by an oncogenic herpesvirus with over 100 genes. Classical MHC class I and class II molecules present antigenic peptides to T lymphocytes, and it has been hard to understand how such MHC molecules could be involved in susceptibility to Marek’s disease, given the potential number of peptides from over 100 genes. We used a new in vitro infection system and immunopeptidomics to determine peptide motifs for the 2 class II molecules expressed by the MHC haplotype B2, which is known to confer resistance to Marek’s disease. Surprisingly, we found that the vast majority of viral peptide epitopes presented by chicken class II molecules arise from only 4 viral genes, nearly all having the peptide motif for BL2*02, the dominantly expressed class II molecule in chickens. We expressed BL2*02 linked to several Marek’s disease virus (MDV) peptides and determined one X-ray crystal structure, showing how a single small amino acid in the binding site causes a crinkle in the peptide, leading to a core binding peptide of 10 amino acids, compared to the 9 amino acids in all other reported class II molecules. The limited number of potential T cell epitopes from such a complex virus can explain the differential MHC-determined resistance to MDV, but raises questions of mechanism and opportunities for vaccine targets in this important food species, as well as providing a basis for understanding class II molecules in other species including humans.

This study shows that chicken MHC class II molecules present peptides from only a handful of the more than 100 genes of the oncogenic herpesvirus Marek’s disease virus, explaining the strong genetic association of chicken MHC with resistance and susceptibility to this and other economically-important pathogens.     

TRIM family proteins: roles in proteostasis and neurodegenerative diseases

Neurodegenerative diseases (NDs) are a diverse group of disorders characterized by the progressive degeneration of the structure and function of the central or peripheral nervous systems. One of the major features of NDs, such as Alzheimer''s disease (AD), Parkinson''s disease (PD) and Huntington''s disease (HD), is the aggregation of specific misfolded proteins, which induces cellular dysfunction, neuronal death, loss of synaptic connections and eventually brain damage. By far, a great amount of evidence has suggested that TRIM family proteins play crucial roles in the turnover of normal regulatory and misfolded proteins. To maintain cellular protein quality control, cells rely on two major classes of proteostasis: molecular chaperones and the degradative systems, the latter includes the ubiquitin-proteasome system (UPS) and autophagy; and their dysfunction has been established to result in various physiological disorders including NDs. Emerging evidence has shown that TRIM proteins are key players in facilitating the clearance of misfolded protein aggregates associated with neurodegenerative disorders. Understanding the different pathways these TRIM proteins employ during episodes of neurodegenerative disorder represents a promising therapeutic target. In this review, we elucidated and summarized the diverse roles with underlying mechanisms of members of the TRIM family proteins in NDs.     

The Effects of Two Polymorphisms on p21cip1 Function and Their Association with Alzheimer’s Disease in a Population of European Descent

With the exception of ApoE4, genome-wide association studies have failed to identify strong genetic risk factors for late-onset Alzheimer’s disease, despite strong evidence of heritability, suggesting that many low penetrance genes may be involved. Additionally, the nature of the identified genetic risk factors and their relation to disease pathology is also largely obscure. Previous studies have found that a cancer-associated variant of the cell cycle inhibitor gene p21^cip1 is associated with increased risk of Alzheimer’s disease. The aim of this study was to confirm this association and to elucidate the effects of the variant on protein function and Alzheimer-type pathology. We examined the association of the p21^cip1 variant with Alzheimer’s disease and Parkinson’s disease with dementia. The genotyping studies were performed on 719 participants of the Oxford Project to Investigate Memory and Ageing, 225 participants of a Parkinson’s disease DNA bank, and 477 participants of the Human Random Control collection available from the European Collection of Cell Cultures. The post mortem studies were carried out on 190 participants. In the in-vitro study, human embryonic kidney cells were transfected with either the common or rare p21^cip1 variant; and cytometry was used to assess cell cycle kinetics, p21^cip1 protein expression and sub-cellular localisation. The variant was associated with an increased risk of Alzheimer’s disease, and Parkinson’s disease with dementia, relative to age matched controls. Furthermore, the variant was associated with an earlier age of onset of Alzheimer’s disease, and a more severe phenotype, with a primary influence on the accumulation of tangle pathology. In the in-vitro study, we found that the SNPs reduced the cell cycle inhibitory and anti-apoptotic activity of p21^cip1. The results suggest that the cancer-associated variant of p21^cip1 may contribute to the loss of cell cycle control in neurons that may lead to Alzheimer-type neurodegeneration.     

Selective vulnerability to neurodegenerative disease: the curious case of Prion Protein

The mechanisms underlying the selective targeting of specific brain regions by different neurodegenerative diseases is one of the most intriguing mysteries in medicine. For example, it is known that Alzheimer’s disease primarily affects parts of the brain that play a role in memory, whereas Parkinson’s disease predominantly affects parts of the brain that are involved in body movement. However, the reasons that other brain regions remain unaffected in these diseases are unknown. A better understanding of the phenomenon of selective vulnerability is required for the development of targeted therapeutic approaches that specifically protect affected neurons, thereby altering the disease course and preventing its progression. Prion diseases are a fascinating group of neurodegenerative diseases because they exhibit a wide phenotypic spectrum caused by different sequence perturbations in a single protein. The possible ways that mutations affecting this protein can cause several distinct neurodegenerative diseases are explored in this Review to highlight the complexity underlying selective vulnerability. The premise of this article is that selective vulnerability is determined by the interaction of specific protein conformers and region-specific microenvironments harboring unique combinations of subcellular components such as metals, chaperones and protein translation machinery. Given the abundance of potential contributory factors in the neurodegenerative process, a better understanding of how these factors interact will provide invaluable insight into disease mechanisms to guide therapeutic discovery.KEY WORDS: Huntington’s disease, Neurodegeneration, Spinocerebellar ataxia, Knock-in mice, Neuropathology, Prion diseases     

A brief overview of amyloids and Alzheimer’s disease

Amyloid fibrils are self-assembled fibrous protein aggregates that are associated with a number of presently incurable diseases such as Alzheimer’s and Parkinson’s disease. Millions of people worldwide suffer from amyloid diseases. This review summarizes the unique cross-β structure of amyloid fibrils, morphological variations, the kinetics of amyloid fibril formation, and the cytotoxic effects of these fibrils and oligomers. Alzheimer’s disease is also explored as an example of an amyloid disease to show the various approaches to treat these amyloid diseases. Finally, this review investigates the nanotechnological and biological applications of amyloid fibrils; as well as a summary of the typical biological pathways involved in the disposal of amyloid fibrils and their precursors.     

New insights into the role of microRNAs and long noncoding RNAs in most common neurodegenerative diseases

Neurodegenerative diseases (NDs) are a diversity of neurological disorders characterized by the progressive degeneration of the structure and function of the central nervous system (CNS). The most common NDs are Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Recently, many studies have investigated associations between common NDs with noncoding RNAs (ncRNAs) molecules. ncRNAs are regulatory molecules in the normal functioning of the CNS. Two of the most important ncRNAs are microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). These types of ncRNAs are involved in different biological processes including brain development, maturation, differentiation, neuronal cell specification, neurogenesis, and neurotransmission. Increasing data has demonstrated that miRNAs and lncRNAs have strong correlations with the development of NDs, particularly gene expression. Besides, ncRNAs can be introduced as new biomarkers for diagnosis and prognosis of NDs. Hence, in this review, we summarized the involvement of various miRNAs and lncRNAs in most common NDs followed by a correlation of ncRNAs dysregulation with the AD, PD, and HD.     

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer’s Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10^-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.     

Astrocytes in Neurodegenerative Disease

Astrocytes contribute to the maintenance of the health and function of the central nervous system (CNS). Thus, it is not surprising that these multifunctional cells have been implicated in the onset and progression of several neurodegenerative diseases. The involvement of astrocytes in the neuropathology of these diseases is likely a consequence of both the loss of normal homeostatic functions and gain of toxic functions. Intracellular aggregates in astrocytes are a common feature of various neurodegenerative diseases, and these aggregates perturb normal astrocytic functions in ways that can be harmful to neuronal viability. Here, we review the role of astrocytes in neurodegenerative diseases, focusing on their dysfunction in Huntington’s disease (HD), Parkinson’s disease (PD), Alzheimer’s disease (AD), and amyotrophic lateral sclerosis (ALS).     

Huntington’s Disease: The Past,Present, and Future Search for Disease Modifiers

Huntington’s disease (HD) is an autosomal dominant genetic disorder that specifically causes neurodegeneration of striatal neurons, resulting in a triad of symptoms that includes emotional, cognitive, and motor disturbances. The HD mutation causes a polyglutamine repeat expansion within the N-terminal of the huntingtin (Htt) protein. This expansion causes aggregate formation within the cytosol and nucleus due to the presence of misfolded mutant Htt, as well as altered interactions with Htt’s multiple binding partners, and changes in post-translational Htt modifications. The present review charts efforts toward a therapy that delays age of onset or slows symptom progression in patients affected by HD, as there is currently no effective treatment. Although silencing Htt expression appears promising as a disease modifying treatment, it should be attempted with caution in light of Htt’s essential roles in neural maintenance and development. Other therapeutic targets include those that boost aggregate dissolution, target excitotoxicity and metabolic issues, and supplement growth factors.     

Evidence for the Convergence Model: The Emergence of Highly Pathogenic Avian Influenza (H5N1) in Viet Nam

Building on a series of ground breaking reviews that first defined and drew attention to emerging infectious diseases (EID), the ‘convergence model’ was proposed to explain the multifactorial causality of disease emergence. The model broadly hypothesizes disease emergence is driven by the co-incidence of genetic, physical environmental, ecological, and social factors. We developed and tested a model of the emergence of highly pathogenic avian influenza (HPAI) H5N1 based on suspected convergence factors that are mainly associated with land-use change. Building on previous geospatial statistical studies that identified natural and human risk factors associated with urbanization, we added new factors to test whether causal mechanisms and pathogenic landscapes could be more specifically identified. Our findings suggest that urbanization spatially combines risk factors to produce particular types of peri-urban landscapes with significantly higher HPAI H5N1 emergence risk. The work highlights that peri-urban areas of Viet Nam have higher levels of chicken densities, duck and geese flock size diversities, and fraction of land under rice or aquaculture than rural and urban areas. We also found that land-use diversity, a surrogate measure for potential mixing of host populations and other factors that likely influence viral transmission, significantly improves the model’s predictability. Similarly, landscapes where intensive and extensive forms of poultry production overlap were found at greater risk. These results support the convergence hypothesis in general and demonstrate the potential to improve EID prevention and control by combing geospatial monitoring of these factors along with pathogen surveillance programs.     

The Central Role of AMP-Kinase and Energy Homeostasis Impairment in Alzheimer’s Disease: A Multifactor Network Analysis

Alzheimer’s disease is the most common cause of dementia worldwide, affecting the elderly population. It is characterized by the hallmark pathology of amyloid-β deposition, neurofibrillary tangle formation, and extensive neuronal degeneration in the brain. Wealth of data related to Alzheimer’s disease has been generated to date, nevertheless, the molecular mechanism underlying the etiology and pathophysiology of the disease is still unknown. Here we described a method for the combined analysis of multiple types of genome-wide data aimed at revealing convergent evidence interest that would not be captured by a standard molecular approach. Lists of Alzheimer-related genes (seed genes) were obtained from different sets of data on gene expression, SNPs, and molecular targets of drugs. Network analysis was applied for identifying the regions of the human protein-protein interaction network showing a significant enrichment in seed genes, and ultimately, in genes associated to Alzheimer’s disease, due to the cumulative effect of different combinations of the starting data sets. The functional properties of these enriched modules were characterized, effectively considering the role of both Alzheimer-related seed genes and genes that closely interact with them. This approach allowed us to present evidence in favor of one of the competing theories about AD underlying processes, specifically evidence supporting a predominant role of metabolism-associated biological process terms, including autophagy, insulin and fatty acid metabolic processes in Alzheimer, with a focus on AMP-activated protein kinase. This central regulator of cellular energy homeostasis regulates a series of brain functions altered in Alzheimer’s disease and could link genetic perturbation with neuronal transmission and energy regulation, representing a potential candidate to be targeted by therapy.     

Community Size Effects on Epidemic Spreading in Multiplex Social Networks

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people’s reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals’ alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals’ risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals’ protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.     

Zooming in on the cell biology of disease

Today’s cell biology could be considered a fusion of disciplines that blends advanced genetics, molecular biology, biochemistry, and engineering to answer fundamental as well as medically relevant scientific questions. Accordingly, our understanding of diseases is greatly aided by an existing vast knowledge base of fundamental cell biology. Gunter Blobel captured this concept when he said, “the tremendous acquisition of basic knowledge will allow a much more rational treatment of cancer, viral infection, degenerative disease and mental disease.” In other words, without cell biology can we truly understand, prevent, or effectively treat a disease?

R. M. Perera     

Genetic Insights into Cardiometabolic Risk Factors

Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as ‘cardiometabolic’ risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.     

Identifying rare and common disease associated variants in genomic data using Parkinson’s disease as a model

Background

Genome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson’s disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.

Results

We propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson’s disease case–control dataset as a model to demonstrate the application of our method.Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson’s disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson’s disease.

Conclusions

Our method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson’s disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12929-014-0088-9) contains supplementary material, which is available to authorized users.     

Enrichment of Bruch's Membrane from Human Donor Eyes

Age-related macular degeneration (AMD) is a leading cause of visual impairment in the developed world. The disease manifests itself by the destruction of the center of the retina, called the macula, resulting in the loss of central vision. Early AMD is characterised by the presence of small, yellowish lesions called soft drusen that can progress onto late AMD such as geographic atrophy (dry AMD) or neovascularisation (wet AMD). Although the clinical changes are well described, and the understanding of genetic influences on conferring AMD risk are getting ever more detailed, one area lacking major progress is an understanding of the biochemical consequences of genetic risk. This is partly due to difficulties in understanding the biochemistry of Bruch’s membrane, a very thin extracellular matrix that acts as a biological filter of material from the blood supply and a scaffold on which the retinal pigment epithelial (RPE) cell monolayer resides. Drusen form within Bruch’s membrane and their presence disrupts nutrient flow to the RPE cells. Only by investigating the protein composition of Bruch’s membrane, and indeed how other proteins interact with it, can researchers hope to unravel the biochemical mechanisms underpinning drusen formation, development of AMD and subsequent vision loss. This paper details methodologies for enriching either whole Bruch’s membrane, or just from the macula region, so that it can be used for downstream biochemical analysis, and provide examples of how this is already changing the understanding of Bruch’s membrane biochemistry.     

Why are viral genomes so fragile? The bottleneck hypothesis

If they undergo new mutations at each replication cycle, why are RNA viral genomes so fragile, with most mutations being either strongly deleterious or lethal? Here we provide theoretical and numerical evidence for the hypothesis that genetic fragility is partly an evolutionary response to the multiple population bottlenecks experienced by viral populations at various stages of their life cycles. Modelling within-host viral populations as multi-type branching processes, we show that mutational fragility lowers the rate at which Muller’s ratchet clicks and increases the survival probability through multiple bottlenecks. In the context of a susceptible-exposed-infectious-recovered epidemiological model, we find that the attack rate of fragile viral strains can exceed that of more robust strains, particularly at low infectivities and high mutation rates. Our findings highlight the importance of demographic events such as transmission bottlenecks in shaping the genetic architecture of viral pathogens.