Schizophrenia and the neurodevelopmental continuum:evidence from genomics

The idea that disturbances occurring early in brain development contribute to the pathogenesis of schizophrenia, often referred to as the neurodevelopmental hypothesis, has become widely accepted. Despite this, the disorder is viewed as being distinct nosologically, and by implication pathophysiologically and clinically, from syndromes such as autism spectrum disorders, attention‐deficit/hyperactivity disorder (ADHD) and intellectual disability, which typically present in childhood and are grouped together as “neurodevelopmental disorders”. An alternative view is that neurodevelopmental disorders, including schizophrenia, rather than being etiologically discrete entities, are better conceptualized as lying on an etiological and neurodevelopmental continuum, with the major clinical syndromes reflecting the severity, timing and predominant pattern of abnormal brain development and resulting functional abnormalities. It has also been suggested that, within the neurodevelopmental continuum, severe mental illnesses occupy a gradient of decreasing neurodevelopmental impairment as follows: intellectual disability, autism spectrum disorders, ADHD, schizophrenia and bipolar disorder. Recent genomic studies have identified large numbers of specific risk DNA changes and offer a direct and robust test of the predictions of the neurodevelopmental continuum model and gradient hypothesis. These findings are reviewed in detail. They not only support the view that schizophrenia is a disorder whose origins lie in disturbances of brain development, but also that it shares genetic risk and pathogenic mechanisms with the early onset neurodevelopmental disorders (intellectual disability, autism spectrum disorders and ADHD). They also support the idea that these disorders lie on a gradient of severity, implying that they differ to some extent quantitatively as well as qualitatively. These findings have important implications for nosology, clinical practice and research.     

Drosophila as a model system for studying lifespan and neuroprotective activities of plant-derived compounds

The fruit fly, Drosophila melanogaster, has been intensively used as a genetic model system for basic and applied research on human neurological diseases because of advantages over mammalian model systems such as ease of laboratory maintenance and genetic manipulations. Disease-associated gene mutations, whether endogenous or transgenically-inserted, often cause phenotypes in vivo that are similar to the clinical features of the human disorder. The Drosophila genome is simpler than that of mammals, in terms of gene and chromosome number, but nonetheless demonstrates extraordinary phylogenetic conservation of gene structure and function, especially notable among the genes whose mutations cause neurodevelopmental, neuropsychiatric, or neurodegenerative disorders. In addition, its well-established neuroanatomical, developmental, and molecular genetic research techniques allow many laboratories worldwide to study complex biological and genetic processes. Based on these merits of the Drosophila model system, it has been used for screening lifespan expansion and neuroprotective activities of plant extracts or their secondary metabolites to counteract pathological events such as mitochondrial damage by oxidative stress, which may cause sporadic neurodegenerative diseases. In this review, we have summarized that the fruit fly can be used for early-stage drug discovery and development to identify novel plant-derived compounds to protect against neurodegeneration in Alzheimer's disease and Parkinson's disease, and other neurological disorders caused by oxidative stress. Thus, the Drosophila system can directly or indirectly contribute to translational research for new therapeutic strategies to prevent or ameliorate neurodegenerative diseases.     

Environmental influence on neurodevelopmental disorders: Potential association of heavy metal exposure and autism

Environmental factors have been severally established to play major roles in the pathogenesis of neurodevelopmental disorders including autism spectrum disorder (ASD). ASD is a neurodevelopmental disorder that is associated with symptoms that reduce the quality of life of affected individuals such as social interaction deficit, cognitive impairment, intellectual disabilities, restricted and repetitive behavioural patterns. ASD pathogenesis has been associated with environmental and genetic factors that alter physiologic processes during development. Here, we review literatures highlighting the environmental impact on neurodevelopmental disorders, and mechanisms by which environmental toxins may influence neurodevelopment. Furthermore, this review discusses reports highlighting neurotoxic metals (specifically, lead, mercury, cadmium, nickel and manganese) as environmental risk factors in the aetiology of ASD. This work, thus suggests that improving the environment could be vital in the management of ASD.     

Advances in proteomic prostate cancer biomarker discovery

Prostate cancer is the most common non-cutaneous cancer in men in the United States. For reasons largely unknown, the incidence of prostate cancer has increased in the last two decades, in spite or perhaps because of a concomitant increase in serum prostate-specific antigen (PSA) screening. While PSA is acknowledged not to be an ideal biomarker for prostate cancer detection, it is however widely used by physicians due to lack of an alternative. Thus, the identification of a biomarker(s) that can complement or replace PSA represents a major goal for prostate cancer research. Screening complex biological specimens such as blood, urine, and tissue to identify protein biomarkers has become increasingly popular over the last decade thanks to advances in proteomic discovery methods. The completion of human genome sequence together with new development in mass spectrometry instrumentation and bioinformatics has been a major driving force in biomarker discovery research. Here we review the current state of proteomic applications as applied to various sample sources including blood, urine, tissue, and “secretome” for the purpose of prostate cancer biomarker discovery. Additionally, we review recent developments in validation of putative markers, efforts at systems biology approach, and current challenges of proteomics in biomarker discovery.     

Fatty acid metabolism in neurodevelopmental disorder: a new perspective on associations between attention-deficit/hyperactivity disorder, dyslexia, dyspraxia and the autistic spectrum

There is increasing evidence that abnormalities of fatty acid and membrane phospholipid metabolism play a part in a wide range of neurodevelopmental and psychiatric disorders. This proposal is discussed here in relation to attention-deficit/hyperactivity disorder (ADHD), dyslexia, developmental coordination disorder (dyspraxia) and the autistic spectrum. These are among the most common neurodevelopmental disorders of childhood, with significant implications for society as well as for those directly affected. However, controversy still surrounds both the identification and management of these conditions, and while their aetiology is recognized as being complex and multifactorial, little progress has yet been made in elucidating predisposing factors at the biological level.An overview is provided here of the contents of this Special Issue, which contains a selection of reports from a unique multidisciplinary workshop involving both researchers and clinicians. Its purpose was to explore the possibility that ADHD, dyslexia, dyspraxia and autism fall within a phospholipid spectrum of disorders. This proposal could explain the high degree of co-morbidity between these conditions, their aggregation within families and relation to other psychiatric disorders, and a range of associated features that are already well known at a clinical level. The existing evidence for fatty acid abnormalities in these disorders is summarized, and new approaches are outlined that have the potential to improve both the identification and the management of these and related neurodevelopmental and psychiatric conditions.     

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.     

Autistic disorder and phospholipids: A review

Dysregulated phospholipid metabolism has been proposed as an underlying biological component of neurodevelopmental disorders such as autistic disorder (AD) and attention-deficit/hyperactivity disorder (ADHD). This review provides an overview of fatty acid and phospholipid metabolism and evidence for phospholipid dysregulation with reference to the membrane hypothesis of schizophrenia. While there is evidence that phospholipid metabolism is at least impaired in individuals with AD, it has not been established whether phospholipid metabolism is implicated in causal, mechanistic or epiphenomenological models. More research is needed to ascertain whether breastfeeding, and specifically, the administration of colostrum or an adequate substitute can play a preventative role by supplying the neonate with essential fatty acids (EFAs) at a critical juncture in their development. Regarding treatment, further clinical trials of EFA supplementation are essential to determine the efficacy of EFAs in reducing AD symptomatology and whether supplementation can serve as a cost-effective and readily available intervention.     

An integrative functional genomics approach for discovering biomarkers in schizophrenia

Schizophrenia (SZ) is a complex disorder resulting from both genetic and environmental causes with a lifetime prevalence world-wide of 1%; however, there are no specific, sensitive and validated biomarkers for SZ. A general unifying hypothesis has been put forward that disease-associated single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) are more likely to be associated with gene expression quantitative trait loci (eQTL). We will describe this hypothesis and review primary methodology with refinements for testing this paradigmatic approach in SZ. We will describe biomarker studies of SZ and testing enrichment of SNPs that are associated both with eQTLs and existing GWAS of SZ. SZ-associated SNPs that overlap with eQTLs can be placed into gene-gene expression, protein-protein and protein-DNA interaction networks. Further, those networks can be tested by reducing/silencing the gene expression levels of critical nodes. We present pilot data to support these methods of investigation such as the use of eQTLs to annotate GWASs of SZ, which could be applied to the field of biomarker discovery. Those networks that have association with SNP markers, especially cis-regulated expression, might lead to a more clear understanding of important candidate genes that predispose to disease and alter expression. This method has general application to many complex disorders.     

Amyloid-β as a biomarker for Alzheimer’s disease: quantification methods in body fluids

Alzheimer’s disease (AD) is the most common neurodegenerative disorder, characterized by neuronal impairment leading to dramatic changes in brain. Amyloid-β peptides and tau protein are the most promising biomarkers for AD. Cerebrospinal fluid and plasma are used to determine the concentration of these species. Since the pathological processes of AD start decades before the first symptoms, biomarkers may provide the possibility of early disease detection. The application of rapidly emerging technology, such as mass spectrometry, has opened new avenues to accelerate biomarker discovery, both for diagnostic as well as for prognostic purposes. This review summarizes AD biomarker studies with focus on amyloid-β peptides in biological fluids and their quantification with immunoassays as well as the latest mass spectrometry-based methods.     

Anticipation in myotonic dystrophy: new light on an old problem.

The concept of anticipation, the occurrence of a genetic disorder at progressively earlier ages in successive generations, has been debated from the early years of this century, with myotonic dystrophy as the most striking example. Throughout most of this period there has been controversy as to whether the phenomenon resulted from observational and ascertainment biases or reflected a more fundamental mechanism. The recent discovery of inherited unstable DNA sequences, first in fragile-X mental retardation and now in myotonic dystrophy, not only confirms that anticipation indeed has a true biological basis but provides a specific molecular mechanism for it; this discovery can explain many of the puzzling anomalies in the inheritance of myotonic dystrophy and may prove relevant to comparable problems in other genetic disorders.     

Revisiting Mendelian disorders through exome sequencing

Over the past several years, more focus has been placed on dissecting the genetic basis of complex diseases and traits through genome-wide association studies. In contrast, Mendelian disorders have received little attention mainly due to the lack of newer and more powerful methods to study these disorders. Linkage studies have previously been the main tool to elucidate the genetics of Mendelian disorders; however, extremely rare disorders or sporadic cases caused by de novo variants are not amendable to this study design. Exome sequencing has now become technically feasible and more cost-effective due to the recent advances in high-throughput sequence capture methods and next-generation sequencing technologies which have offered new opportunities for Mendelian disorder research. Exome sequencing has been swiftly applied to the discovery of new causal variants and candidate genes for a number of Mendelian disorders such as Kabuki syndrome, Miller syndrome and Fowler syndrome. In addition, de novo variants were also identified for sporadic cases, which would have not been possible without exome sequencing. Although exome sequencing has been proven to be a promising approach to study Mendelian disorders, several shortcomings of this method must be noted, such as the inability to capture regulatory or evolutionary conserved sequences in non-coding regions and the incomplete capturing of all exons.     

Trends in childhood disease

Child mortality has declined remarkably during the last decades. While neonatal disorders, diarrhoea, pneumonia, and malaria as well as being underweight account for most of the child deaths worldwide, children's health discussions in Europe and the USA focus on other issues such as asthma, neurodevelopmental disorders, male genital malformations, and childhood cancer. There is clear evidence of increasing rates of asthma in various countries during the last decades, although rates in some countries may now have stabilised or even decline as recent UK data indicate. Although an increase in the frequency of neurodevelopmental disorders such as autism and attention deficit disorder has frequently been discussed, the limited data in this field does not justify such a conclusion. While geographic heterogeneity regarding reproductive outcomes is apparent, global trends have not been identified. Interpretation of the available information on asthma, neurodevelopmental disorders and reproductive outcomes is hampered by inconstant diagnostic criteria over place and time and the lack of good and comprehensive population-based surveillance data, which makes it impossible to ascertain trends in actual disease frequency. Data indicate that developed countries have a gradually increasing incidence in leukaemia with a corresponding drop in the incidence of lymphoma. Increases in brain tumour frequency may be related to the development and wide application of new diagnostic capabilities, rather than a true change in the incidence of malignant disease. With a better prognosis for childhood cancer survival, secondary cancers following chemotherapy appear to be increasing. A wide range of environmental factors is thought to have an impact on children's health. These factors include nutrition (protein, vitamins, antioxidants), lifestyle and behaviour choices such as tobacco and alcohol use, parental health, socio-economic status, choice of living environment (urban versus rural, etc.), and parent-sibling behaviour. From the available data, no general conclusions on the contribution of specific chemicals can be drawn.     

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science.     

Neurogenomics of speech and language disorders: the road ahead

Next-generation sequencing is set to transform the discovery of genes underlying neurodevelopmental disorders, and so offer important insights into the biological bases of spoken language. Success will depend on functional assessments in neuronal cell lines, animal models and humans themselves.     

Genetic and Environmental Factors in Complex Neurodevelopmental Disorders

Complex neurodevelopmental disorders, such as schizophrenia, autism, attention deficit (hyperactivity) disorder, (manic) depressive illness and addiction, are thought to result from an interaction between genetic and environmental factors. Association studies on candidate genes and genome-wide linkage analyses have identified many susceptibility chromosomal regions and genes, but considerable efforts to replicate association have been surprisingly often disappointing. Here, we summarize the current knowledge of the genetic contribution to complex neurodevelopmental disorders, focusing on the findings from association and linkage studies. Furthermore, the contribution of the interaction of the genetic with environmental and epigenetic factors to the aetiology of complex neurodevelopmental disorders as well as suggestions for future research are discussed.Key Words: Neurodevelopmental disorders, susceptibility genes, environmental factors, gene-environment interactions, association studies, linkage analysis.     

Data processing and classification analysis of proteomic changes: a case study of oil pollution in the mussel, Mytilus edulis

Background  

Proteomics may help to detect subtle pollution-related changes, such as responses to mixture pollution at low concentrations, where clear signs of toxicity are absent. The challenges associated with the analysis of large-scale multivariate proteomic datasets have been widely discussed in medical research and biomarker discovery. This concept has been introduced to ecotoxicology only recently, so data processing and classification analysis need to be refined before they can be readily applied in biomarker discovery and monitoring studies.     

The neurobiology of lipid metabolism in autism spectrum disorders

Autism is a neurodevelopmental disorder characterized by impairments in communication and reciprocal social interaction, coupled with repetitive behavior, which typically manifests by 3 years of age. Multiple genes and early exposure to environmental factors are the etiological determinants of the disorder that contribute to variable expression of autism-related traits. Increasing evidence indicates that altered fatty acid metabolic pathways may affect proper function of the nervous system and contribute to autism spectrum disorders. This review provides an overview of the reported abnormalities associated with the synthesis of membrane fatty acids in individuals with autism as a result of insufficient dietary supplementation or genetic defects. Moreover, we discuss deficits associated with the release of arachidonic acid from the membrane phospholipids and its subsequent metabolism to bioactive prostaglandins via phospholipase A(2)-cyclooxygenase biosynthetic pathway in autism spectrum disorders. The existing evidence for the involvement of lipid neurobiology in the pathology of neurodevelopmental disorders such as autism is compelling and opens up an interesting possibility for further investigation of this metabolic pathway.     

Prospective MEG Biomarkers in ASD: Pre-Clinical Evidence and Clinical Promise of Electrophysiological Signatures

Autism spectrum disorders (ASD) are characterized by social impairments and restricted/stereotyped behaviors and currently affect an estimated 1 in 68 children aged 8 years old. While there has been substantial recent focus on ASD in research, both the biological pathology and, perhaps consequently, a fully effective treatment have yet to be realized. What has remained throughout is the hypothesis that ASD has neurobiological underpinnings and the observation that both the phenotypic expression and likely the underlying etiology is highly heterogeneous. Given the neurodevelopmental basis of ASD, a biologically based marker (biomarker) could prove useful not only for diagnostic and prognostic purposes, but also for stratification and response indices for pharmaceutical development. In this review, we examine the current state of the field for MEG-related biomarkers in ASD. We describe several potential biomarkers (middle latency delays [M50/M100], mismatch negativity latency, gamma-band oscillatory activity), and investigate their relation to symptomology, core domains of dysfunction (e.g., language impairment), and putative biological underpinnings.     

Proteomic and metabolomic profiling of a trait anxiety mouse model implicate affected pathways

Depression and anxiety disorders affect a great number of people worldwide. Whereas singular factors have been associated with the pathogenesis of psychiatric disorders, growing evidence emphasizes the significance of dysfunctional neural circuits and signaling pathways. Hence, a systems biology approach is required to get a better understanding of psychiatric phenotypes such as depression and anxiety. Furthermore, the availability of biomarkers for these disorders is critical for improved diagnosis and monitoring treatment response. In the present study, a mouse model presenting with robust high versus low anxiety phenotypes was subjected to thorough molecular biomarker and pathway discovery analyses. Reference animals were metabolically labeled with the stable (15)N isotope allowing an accurate comparison of protein expression levels between the high anxiety-related behavior versus low anxiety-related behavior mouse lines using quantitative mass spectrometry. Plasma metabolomic analyses identified a number of small molecule biomarkers characteristic for the anxiety phenotype with particular focus on myo-inositol and glutamate as well as the intermediates involved in the tricarboxylic acid cycle. In silico analyses suggested pathways and subnetworks as relevant for the anxiety phenotype. Our data demonstrate that the high anxiety-related behavior and low anxiety-related behavior mouse model is a valuable tool for anxiety disorder drug discovery efforts.