New Insight into Neurodegeneration: the Role of Proteomics

Recent advances within the field of proteomics, including both upstream and downstream protocols, have fuelled a transition from simple protein identification to functional analysis. A battery of proteomics approaches is now being employed for the analysis of protein expression levels, the monitoring of cellular activities and for gaining an increased understanding into biochemical pathways. Combined, these approaches are changing the way we study disease by allowing accurate and targeted, large scale protein analysis, which will provide invaluable insight into disease pathogenesis. Neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS), prion disease, and other diseases that affect the neuromuscular system, are a leading cause of disability in the aging population. There are no effective intervention strategies for these disorders and diagnosis is challenging as it relies primarily on clinical symptomatic features, which often overlap at early stages of disease. There is, therefore, an urgent need to develop reliable biomarkers to improve early and specific diagnosis, to track disease progression, to measure molecular responses towards treatment regimes and ultimately devise new therapeutic strategies. To accomplish this, a better understanding of disease mechanisms is needed. In this review we summarize recent advances in the field of proteomics applicable to neurodegenerative disorders, and how these advances are fueling our understanding, diagnosis, and treatment of these complex disorders.     

Moving towards a new era of genomics in the neuronal ceroid lipofuscinoses

The neuronal ceroid lipofuscinoses (NCL) are a group of disorders defined by shared clinical and pathological features, including seizures and progressive decline in vision, neurocognition, and motor functioning, as well as accumulation of autofluorescent lysosomal storage material, or ‘ceroid lipofuscin’. Research has revealed thirteen distinct genetic subtypes. Precisely how the gene mutations lead to the clinical phenotype is still incompletely understood, but recent research progress is starting to shed light on disease mechanisms, in both gene-specific and shared pathways. As the application of new sequencing technologies to genetic disease diagnosis has grown, so too has the spectrum of clinical phenotypes caused by mutations in the NCL genes. Most genes causing NCL have probably been identified, underscoring the need for a shift towards applying genomics approaches to achieve a deeper understanding of the molecular basis of the NCLs and related disorders. Here, we summarize the current understanding of the thirteen identified NCL genes and the proteins they encode, touching upon the spectrum of clinical manifestations linked to each of the genes, and we highlight recent progress leading to a broader understanding of key pathways involved in NCL disease pathogenesis and commonalities with other neurodegenerative diseases.     

Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data

Coronary artery disease(CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism(SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium(WTCCC) SNP datasets of CAD and control samples were used to assess the jointeffect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction(PPI)knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer's disease, non-alcoholic fatty liver disease, and Huntington's disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer's disease.These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer's disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.     

MitoPhen database: a human phenotype ontology-based approach to identify mitochondrial DNA diseases

Diagnosing mitochondrial disorders remains challenging. This is partly because the clinical phenotypes of patients overlap with those of other sporadic and inherited disorders. Although the widespread availability of genetic testing has increased the rate of diagnosis, the combination of phenotypic and genetic heterogeneity still makes it difficult to reach a timely molecular diagnosis with confidence. An objective, systematic method for describing the phenotypic spectra for each variant provides a potential solution to this problem. We curated the clinical phenotypes of 6688 published individuals with 89 pathogenic mitochondrial DNA (mtDNA) mutations, collating 26 348 human phenotype ontology (HPO) terms to establish the MitoPhen database. This enabled a hypothesis-free definition of mtDNA clinical syndromes, an overview of heteroplasmy-phenotype relationships, the identification of under-recognized phenotypes, and provides a publicly available reference dataset for objective clinical comparison with new patients using the HPO. Studying 77 patients with independently confirmed positive mtDNA diagnoses and 1083 confirmed rare disease cases with a non-mitochondrial nuclear genetic diagnosis, we show that HPO-based phenotype similarity scores can distinguish these two classes of rare disease patients with a false discovery rate <10% at a sensitivity of 80%. Enriching the MitoPhen database with more patients will improve predictions for increasingly rare variants.     

mTOR signaling in polycystic kidney disease

Polycystic kidney diseases (PKDs) comprise a large group of genetic disorders characterized by formation of cysts in the kidneys and other organs, ultimately leading to end-stage renal disease. Although PKDs can be caused by mutations in different genes, they converge on a set of common molecular mechanisms involved in cystogenesis and ciliary dysfunction, and can be qualified as ciliopathies. Recent advances in understanding the mechanisms regulating disease progression have led to the development of new therapies that are being tested in both preclinical and clinical trials. In this article, we briefly review a network of molecular pathways of cystogenesis that are regulated by ciliary functions. We discuss the mTOR pathway in depth, highlighting recent progress in understanding its role in PKD and the current results of clinical trials.     

Identification of pathways and genes associated with cerebral palsy

Cerebral palsy (CP) is a non-progressive neurological disease, of which susceptibility is linked to genetic and environmental risk factors. More and more studies have shown that CP might be caused by multiple genetic factors, similar to other neurodevelopmental disorders. Due to the high genetic heterogeneity of CP, we focused on investigating related molecular pathways. Ten children with CP were collected for whole-exome sequencing by next-generation sequencing (NGS) technology. Customized processes were used to identify potential pathogenic pathways and variants. Three pathways (axon guidance, transmission across chemical synapses, protein–protein interactions at synapses) with twenty-three genes were identified to be highly correlated with CP. This study showed that the three pathways associated with CP might be the molecular mechanism of pathogenesis. These findings could provide useful clues for developing pathway-based pharmacotherapies. Further studies are required to confirm potential roles for these pathways in the pathogenesis of CP.     

Drosophila as a model to study the genetic mechanisms of obesity-associated heart dysfunction

Obesity and cardiovascular disease are among the world's leading causes of death, especially in Western countries where consumption of high caloric food is commonly accompanied by low physical activity. This lifestyle often leads to energy imbalance, obesity, diabetes and their associated metabolic disorders, including cardiovascular diseases. It has become increasingly recognized that obesity and cardiovascular disease are metabolically linked, and a better understanding of this relationship requires that we uncover the fundamental genetic mechanisms controlling obesity-related heart dysfunction, a goal that has been difficult to achieve in higher organisms with intricate metabolic complexity. However, the high degree of evolutionary conservation of genes and signalling pathways allows researchers to use lower animal models such as Drosophila, which is the simplest genetic model with a heart, to uncover the mechanistic basis of obesity-related heart disease and its likely relevance to humans. Here, we discuss recent advances made by using the power of the Drosophila as a powerful model to investigate the genetic pathways by which a high fat diet may lead to heart dysfunction.     

Molecular genetics of chronic neutrophilic leukemia,chronic myelomonocytic leukemia and atypical chronic myeloid leukemia

According to the 2008 World Health Organization classification, chronic neutrophilic leukemia, chronic myelomonocytic leukemia and atypical chronic myeloid leukemia are rare diseases. The remarkable progress in our understanding of the molecular genetics of myeloproliferative neoplasms and myelodysplastic/myeloproliferative neoplasms has made it clear that there are some specific genetic abnormalities in these 3 rare diseases. At the same time, there is considerable overlap among these disorders at the molecular level. The various combinations of genetic abnormalities indicate a multi-step pathogenesis, which likely contributes to the marked clinical heterogeneity of these disorders. This review focuses on the current knowledge and challenges related to the molecular pathogenesis of chronic neutrophilic leukemia, chronic myelomonocytic leukemia and atypical chronic myeloid leukemia and relationships between molecular findings, clinical features and prognosis.     

Interaction between pathogenic proteins in neurodegenerative disorders

The misfolding and progressive aggregation of specific proteins in selective regions of the nervous system is a seminal occurrence in many neurodegenerative disorders, and the interaction between pathological/toxic proteins to cause neurodegeneration is a hot topic of current neuroscience research. Despite clinical, genetic and experimental differences, increasing evidence indicates considerable overlap between synucleinopathies, tauopathies and other protein-misfolding diseases. Inclusions, often characteristic hallmarks of these disorders, suggest interactions of pathological proteins enganging common downstream pathways. Novel findings that have shifted our understanding in the role of pathologic proteins in the pathogenesis of Alzheimer, Parkinson, Huntington and prion diseases, have confirmed correlations/overlaps between these and other neurodegenerative disorders. Emerging evidence, in addition to synergistic effects of tau protein, amyloid-β, α-synuclein and other pathologic proteins, suggests that prion-like induction and spreading, involving secreted proteins, are major pathogenic mechanisms in various neurodegenerative diseases, depending on genetic backgrounds and environmental factors. The elucidation of the basic molecular mechanisms underlying the interaction and spreading of pathogenic proteins, suggesting a dualism or triad of neurodegeneration in protein-misfolding disorders, is a major challenge for modern neuroscience, to provide a deeper insight into their pathogenesis as a basis of effective diagnosis and treatment.     

Modeling psychiatric disorders through reprogramming

Psychiatric disorders, including autism spectrum disorders and schizophrenia, are extremely heritable complex genetic neurodevelopmental disorders. It is now possible to directly reprogram fibroblasts from psychiatric patients into human induced pluripotent stem cells (hiPSCs) and subsequently differentiate these disorder-specific hiPSCs into neurons. This means that researchers can generate nearly limitless quantities of live human neurons with genetic backgrounds that are known to result in psychiatric disorders, without knowing which genes are interacting to produce the disease state in each patient. With these new human-cell-based models, scientists can investigate the precise cell types that are affected in these disorders and elucidate the cellular and molecular defects that contribute to disease initiation and progression. Here, we present a short review of experiments using hiPSCs and other sophisticated in vitro approaches to study the pathways underlying psychiatric disorders.     

Cerebellar ataxia and functional genomics: Identifying the routes to cerebellar neurodegeneration

Cerebellar ataxias are progressive neurodegenerative disorders characterized by atrophy of the cerebellum leading to motor dysfunction, balance problems, and limb and gait ataxia. These include among others, the dominantly inherited spinocerebellar ataxias, recessive cerebellar ataxias such as Friedreich's ataxia, and X-linked cerebellar ataxias. Since all cerebellar ataxias display considerable overlap in their disease phenotypes, common pathological pathways must underlie the selective cerebellar neurodegeneration. Therefore, it is important to identify the molecular mechanisms and routes to neurodegeneration that cause cerebellar ataxia. In this review, we discuss the use of functional genomic approaches including whole-exome sequencing, genome-wide gene expression profiling, miRNA profiling, epigenetic profiling, and genetic modifier screens to reveal the underlying pathogenesis of various cerebellar ataxias. These approaches have resulted in the identification of many disease genes, modifier genes, and biomarkers correlating with specific stages of the disease. This article is part of a Special Issue entitled: From Genome to Function.     

Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (～1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.     

Molecular genetics and genomics of heart failure

Heart failure is a major disease burden worldwide, and its incidence continues to increase as premature deaths from other cardiovascular conditions decline. Although the overall molecular portrait of this multifactorial disease remains incomplete, molecular and genetic studies have implicated, in recent decades, various pathways and genes that participate in the pathophysiology of heart failure. Here, we highlight the current understanding of the molecular and genetic basis of heart failure and show how recently developed genomic tools are providing a new perspective on this complex disease.     

Nosology of Parkinson's disease: looking for the way out of a quagmire

The discovery of SNCA mutations pathogenic for autosomal-dominant Lewy body Parkinson's disease (PD) in 1997 heralded a revolution in understanding the molecular and genetic basis of PD. Indeed, it now is clear that Lewy body PD is one of many neurodegenerative parkinsonian disorders that result from nigrostriatal degeneration caused by diverse mechanisms. However, to capitalize on these new insights and facilitate efforts to improve the diagnosis and therapy of neurodegenerative movement disorders, it is timely to define a nosology for these diseases that is based on their genetic and molecular underpinnings, as proposed here.