Parkinson's disease: a genetic perspective

Parkinson's disease (PD) is a common neurodegenerative disorder in the aging population, affecting more than 1% over the age of 65 years. Certain rare forms of the disease are monogenic, representing 5-10% of PD patients, but there is increasing evidence that multiple genetic risk factors are important also for common forms of PD. To date, 13 genetic loci, PARK1-13, have been suggested for rare forms of PD such as autosomal dominant and autosomal recessive PD. At six of these loci, genes have been identified and reported by several groups to carry mutations that are linked to affected family members. Genes in which mutations have been linked to familial PD have also been shown to be candidate genes for idiopathic forms of PD, as those same genes may also carry other mutations that merely increase the risk. Four of the PARK genes, SNCA at PARK1, UCH-L1 at PARK5, PINK1 at PARK6 and LRRK2 at PARK8, have been implicated in sporadic PD. There are indeed multiple genetic risk factors that combine in different ways to increase or decrease risk, and several of these need to be identified in order to begin unwinding the causative pathways leading to the different forms of PD. In this review, we present the molecular genetics of PD that are understood today, to help explain the pathways leading to neurodegeneration.     

The medical utility of genomics data in neuropsychiatry: mutational genetics versus association genetics

The long anticipated ‘genetic revolution’ in neuropsychiatry has yet to have an impact on the practice of clinical medicine. Excitement in the 1980s over major genetic breakthroughs in schizophrenia and manic depression, for example, has been replaced in the late 1990s by the sobering realization that most common neuropsychiatric disorders are multifactorial. Despite considerable effort and resources, no ‘causative’ genetic variation has been identified that plays a definitive major role in any common neuropsychiatric disorder.     

A Simple Cell-Based Assay Reveals That Diverse Neuropsychiatric Risk Genes Converge on Primary Cilia

Human genetic studies are beginning to identify a large number of genes linked to neuropsychiatric disorders. It is increasingly evident that different genes contribute to risk for similar syndromes and, conversely, the same genes or even the same alleles cross over traditional diagnostic categories. A current challenge is to understand the cellular biology of identified risk genes. However, most genes associated with complex neuropsychiatric phenotypes are not related through a known biochemical pathway, and many have an entirely unknown cellular function. One possibility is that diverse disease-linked genes converge at a higher-level cellular structure. The synapse is already known to be one such convergence, and emerging evidence suggests the primary cilium as another. Because many genes associated with neuropsychiatric illness are expressed also outside the nervous system, as are cilia, we tested the hypothesis that such genes affect conserved features of the primary cilium. Using RNA interference to test 41 broadly expressed candidate genes associated with schizophrenia, bipolar affective disorder, autism spectrum disorder and intellectual disability, we found 20 candidates that reduce ciliation in NIH3T3 cells when knocked down, and three whose manipulation increases cilia length. Three of the candidate genes were previously implicated in cilia formation and, altogether, approximately half of the candidates tested produced a ciliary phenotype. Our results support the hypothesis that primary cilia indeed represent a conserved cellular structure at which the effects of diverse neuropsychiatric risk genes converge. More broadly, they suggest a relatively simple cell-based approach that may be useful for exploring the complex biological underpinnings of neuropsychiatric disease.     

Mouse models of type 1 and type 2 diabetes derived from the same closed colony: genetic susceptibility shared between two types of diabetes

Except for rare subtypes of diabetes, both type 1 and type 2 diabetes are multifactorial diseases in which genetic factors consisting of multiple susceptibility genes and environmental factors contribute to the disease development. Due to complex interaction among multiple susceptibility genes and between genetic and environmental factors, genetic analysis of multifactorial diseases is difficult in humans. Inbred animal models, in which the genetic background is homogeneous and environmental factors can be controlled, are therefore valuable in genetic dissection of multifactorial diseases. We are fortunate to have excellent animal models for both type 1 and type 2 diabetes--the nonobese diabetic (NOD) mouse and the Nagoya-Shibata-Yasuda (NSY) mouse, respectively. Congenic mapping of susceptibility genes for type 1 diabetes in the NOD mouse has revealed that susceptibility initially mapped as a single locus often consists of multiple components on the same chromosome, indicating the importance of congenic mapping in defining genes responsible for polygenic diseases. The NSY mouse is an inbred animal model of type 2 diabetes established from Jcl:ICR, from which the NOD mouse was also derived. We have recently mapped three major loci contributing to type 2 diabetes in the NSY mouse. Interestingly, support intervals where type 2 diabetes susceptibility genes were mapped in the NSY mouse overlapped the regions where type 1 diabetes susceptibility genes have been mapped in the NOD mouse. Although additional evidence is needed, it may be possible that some of the genes predisposing to diabetes are derived from a common ancestor contained in the original closed colony, contributing to type 1 diabetes in the NOD mouse and type 2 diabetes in the NSY mouse. Such genes, if they exist, will provide valuable information on etiological pathways common to both forms of diabetes, for the establishment of effective methods for prediction, prevention, and intervention in both type 1 and type 2 diabetes.     

Fine mapping of the schizophrenia susceptibility locus on chromosome 1q22

Schizophrenia is a serious neuropsychiatric illness estimated to affect approximately 1% of the general population. As part of a genome scan for schizophrenia susceptibility loci, we have previously reported a maximum heterogeneity four-point lod score of 6.50 on chromosome 1q21-22 in a group of 22 medium-sized Canadian families, selected for study because multiple relatives were clinically diagnosed with schizophrenia or schizoaffective disorder. We have now conducted fine mapping of this locus in the same set of individuals using 15 genetic markers spanning an approximately 15-cM interval. Parametric linkage analysis with GENEHUNTER v2.1 and VITESSE v2.0 produced a maximum multipoint heterogeneity lod score of 6.50, with a Zmax-1 support interval of <3 cM, corresponding to approximately 1 Mb. Physical mapping and sequence analysis from this region confirmed the presence of an approximately 81-kb tandem duplication, containing low-affinity IgG receptor genes and heat shock protein genes. The sequences of the two copies of this duplication are approximately 97% identical, which has led to the collapse of the two copies into one in the June 2002 NCBI Build 30 of the Human Genome. This duplication may be involved in genomic instability, leading to gene deletion, and so presents an intriguing candidate locus for schizophrenia susceptibility.     

Autism: the quest for the genes

Autism, at its most extreme, is a severe neurodevelopmental disorder, and recent studies have indicated that autism spectrum disorders are considerably more common than previously supposed. However, although one of the most heritable neuropsychiatric syndromes, autism has so far eluded attempts to discover its genetic origins in the majority of cases. Several whole-genome scans for autism-susceptibility loci have identified specific chromosomal regions, but the results have been inconclusive and fine mapping and association studies have failed to identify the underlying genes. Recent advances in knowledge from the Human Genome and HapMap Projects, and progress in technology and bioinformatic resources, have aided study design and made data generation more efficient and cost-effective. Broadening horizons about the landscape of structural genetic variation and the field of epigenetics are indicating new possible mechanisms underlying autism aetiology, while endophenotypes are being used in an attempt to break down the complexity of the syndrome and refine genetic data. Although the genetic variants underlying idiopathic autism have proven elusive so far, the future for this field looks promising.     

Genetics of common forms of glycaemia with pathological impact on vascular biology: are we on the right track?

The common forms of abnormal glucose regulation including type 2 diabetes and impaired glucose tolerance with pathological implications on vascular biology have a complex aetiology involving multiple cross-talks between genetic influences and important environmental modifying factors. Due to complexity of the genetics and the clinical heterogeneity of these disorders it has proven difficult to apply the same methodological approaches that have recently given insights into the molecular genetics of several single-gene disorders of glucose metabolism. This review gives some reflections on the challenges posed by the current hypotheses about the genetics of the widespread forms of abnormal glucose regulation as well as on the strengths and limitations of the methodological approaches applied to unravel the genetic components of common disorders. Also, we review recent progress in relation to a model for the pathogenesis of the various stages of abnormal glucose regulation based on the concepts of thrifty genes of metabolism and pro-inflammation and genes responsible for the appearance of impaired pancreatic beta-cell function and insulin signalling under the pressure of a westernized environment.     

A hierarchical Bayesian model for next-generation population genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.     

Autism genetics: Methodological issues and experimental design

Autism is a complex neuropsychiatric disorder of developmental origin, where multiple genetic and environmental factors likely interact resulting in a clinical continuum between "affected" and "unaffected" individuals in the general population. During the last two decades, relevant progress has been made in identifying chromosomal regions and genes in linkage or association with autism, but no single gene has emerged as a major cause of disease in a large number of patients. The purpose of this paper is to discuss specific methodological issues and experimental strategies in autism genetic research, based on fourteen years of experience in patient recruitment and association studies of autism spectrum disorder in Italy.     

Pleiotropic Effects of Immune Responses Explain Variation in the Prevalence of Fibroproliferative Diseases

Many diseases are differentially distributed among human populations. Differential selection on genetic variants in ancestral environments that coincidentally predispose to disease can be an underlying cause of these unequal prevalence patterns. Selected genes may be pleiotropic, affecting multiple phenotypes and resulting in more than one disease or trait. Patterns of pleiotropy may be helpful in understanding the underlying causes of an array of conditions in a population. For example, several fibroproliferative diseases are more prevalent and severe in populations of sub-Saharan ancestry. We propose that this disparity is due to selection for an enhanced Th2 response that confers resistance to helminthic infections, and concurrently increases susceptibility to fibrosis due to the profibrotic action of Th2 cytokines. Many studies on selection of Th2-related genes for host resistance to helminths have been reported, but the pleiotropic impact of this selection on the distribution of fibrotic disorders has not been explicitly investigated. We discuss the disproportionate occurrence of fibroproliferative diseases in individuals of African ancestry and provide evidence that adaptation of the immune system has shaped the genetic structure of these human populations in ways that alter the distribution of multiple fibroproliferative diseases.     

Endosomal trafficking in schizophrenia

Schizophrenia is a severe and heritable neuropsychiatric disorder, which arises due to a combination of common genetic variation, rare loss of function variation, and copy number variation. Functional genomic evidence has been used to identify candidate genes affected by this variation, which revealed biological pathways that may be disrupted in schizophrenia. Understanding the contributions of these pathways are critical next steps in understanding schizophrenia pathogenesis. A number of genes involved in endocytosis are implicated in schizophrenia. In this review, we explore the history of endosomal trafficking in schizophrenia and highlight new endosomal candidate genes. We explore the function of these candidate genes and hypothesize how their dysfunction may contribute to schizophrenia.     

Mammalian cochlear genes and hereditary deafness

Deafness is the most common sensory hereditary disorder. It is a genetically heterogeneous and multifactorial disease affecting approximately 1 infant in 2000. It can be acquired or congenital and can also be syndromic or nonsyndromic. There are approximately 70 genetic loci that have been described for nonsyndromic deafness in humans and 25 auditory-pigmentary diseases in mice. The past 2 years have witnessed remarkable progress in identifying the genes involved in both syndromic and nonsyndromic disorders in humans and mice. Many of these are expressed in the inner ear and are most likely involved in cochlear physiology and development. However, the phenotypic variability in patients carrying the same genetic change, and discrepancies between the phenotypes of mice and humans carrying the same gene defect, emphasize environmental factors and interacting genes in producing the clinical outcome. In the future, molecular understanding of the etiology of the disorder may lead to a cure or delay the onset of the disorder.     

Power of sib-pair and sib-trio linkage analysis with assortative mating and multiple disease loci.

Sib-pair linkage analysis has been proposed for identifying genes that predispose to common diseases. We have shown that the presence of assortative mating and multiple disease-susceptibility loci (genetic heterogeneity) can increase the required sample size for affected-affected sib pairs several fold over the sample size required under random mating. We propose a new test statistic based on sib trios composed of either one unaffected and two affected siblings or one affected and two unaffected siblings. The sample-size requirements under assortative mating and multiple disease loci for these sib-trio statistics are much smaller, under most conditions, than the corresponding sample sizes for sib pairs. Study designs based on data from sib trios with one or two affected members are recommended whenever assortative mating and genetic heterogeneity are suspected.     

Nonparametric tests of association of multiple genes with human disease

The genetic basis of many common human diseases is expected to be highly heterogeneous, with multiple causative loci and multiple alleles at some of the causative loci. Analyzing the association of disease with one genetic marker at a time can have weak power, because of relatively small genetic effects and the need to correct for multiple testing. Testing the simultaneous effects of multiple markers by multivariate statistics might improve power, but they too will not be very powerful when there are many markers, because of the many degrees of freedom. To overcome some of the limitations of current statistical methods for case-control studies of candidate genes, we develop a new class of nonparametric statistics that can simultaneously test the association of multiple markers with disease, with only a single degree of freedom. Our approach, which is based on U-statistics, first measures a score over all markers for pairs of subjects and then compares the averages of these scores between cases and controls. Genetic scoring for a pair of subjects is measured by a "kernel" function, which we allow to be fairly general. However, we provide guidelines on how to choose a kernel for different types of genetic effects. Our global statistic has the advantage of having only one degree of freedom and achieves its greatest power advantage when the contrasts of average genotype scores between cases and controls are in the same direction across multiple markers. Simulations illustrate that our proposed methods have the anticipated type I-error rate and that they can be more powerful than standard methods. Application of our methods to a study of candidate genes for prostate cancer illustrates their potential merits, and offers guidelines for interpretation.     

Emerging evidence implicating a role for neurexins in neurodegenerative and neuropsychiatric disorders

Synaptopathies are brain disorders characterized by dysfunctional synapses, which are specialized junctions between neurons that are essential for the transmission of information. Synaptic dysfunction can occur due to mutations that alter the structure and function of synaptic components or abnormal expression levels of a synaptic protein. One class of synaptic proteins that are essential to their biology are cell adhesion proteins that connect the pre- and post-synaptic compartments. Neurexins are one type of synaptic cell adhesion molecule that have, recently, gained more pathological interest. Variants in both neurexins and their common binding partners, neuroligins, have been associated with several neuropsychiatric disorders. In this review, we summarize some of the key physiological functions of the neurexin protein family and the protein networks they are involved in. Furthermore, examination of published literature has implicated neurexins in both neuropsychiatric and neurodegenerative disorders. There is a clear link between neurexins and neuropsychiatric disorders, such as autism spectrum disorder and schizophrenia. However, multiple expression studies have also shown changes in neurexin expression in several neurodegenerative disorders, including Alzheimer''s disease and Parkinson''s disease. Therefore, this review highlights the potential importance of neurexins in brain disorders and the importance of doing more targeted studies on these genes and proteins.     

CONVERGENCE AND DIVERGENCE DURING THE ADAPTATION TO SIMILAR ENVIRONMENTS BY AN AUSTRALIAN GROUNDSEL

Adaptation to replicate environments is often achieved through similar phenotypic solutions. Whether selection also produces convergent genomic changes in these situations remains largely unknown. The variable groundsel, Senecio lautus, is an excellent system to investigate the genetic underpinnings of convergent evolution, because morphologically similar forms of these plants have adapted to the same environments along the coast of Australia. We compared range‐wide patterns of genomic divergence in natural populations of this plant and searched for regions putatively affected by natural selection. Our results indicate that environmental adaptation followed complex genetic trajectories, affecting multiple loci, implying both the parallel recruitment of the same alleles and the divergence of completely different genomic regions across geography. An analysis of the biological functions of candidate genes suggests that adaptation to coastal environments may have occurred through the recruitment of different genes participating in similar processes. The relatively low genetic convergence that characterizes the parallel evolution of S. lautus forms suggests that evolution is more constrained at higher levels of biological organization.     

Progress and promise in understanding the genetic basis of common diseases

Susceptibility to common human diseases is influenced by both genetic and environmental factors. The explosive growth of genetic data, and the knowledge that it is generating, are transforming our biological understanding of these diseases. In this review, we describe the technological and analytical advances that have enabled genome-wide association studies to be successful in identifying a large number of genetic variants robustly associated with common disease. We examine the biological insights that these genetic associations are beginning to produce, from functional mechanisms involving individual genes to biological pathways linking associated genes, and the identification of functional annotations, some of which are cell-type-specific, enriched in disease associations. Although most efforts have focused on identifying and interpreting genetic variants that are irrefutably associated with disease, it is increasingly clear that—even at large sample sizes—these represent only the tip of the iceberg of genetic signal, motivating polygenic analyses that consider the effects of genetic variants throughout the genome, including modest effects that are not individually statistically significant. As data from an increasingly large number of diseases and traits are analysed, pleiotropic effects (defined as genetic loci affecting multiple phenotypes) can help integrate our biological understanding. Looking forward, the next generation of population-scale data resources, linking genomic information with health outcomes, will lead to another step-change in our ability to understand, and treat, common diseases.     

Genetic Changes Accompanying the Domestication of Pisum sativum: Is there a Common Genetic Basis to the ‘Domestication Syndrome’ for Legumes?

BACKGROUND AND AIMS: The changes that occur during the domestication of crops such as maize and common bean appear to be controlled by relatively few genes. This study investigates the genetic basis of domestication in pea (Pisum sativum) and compares the genes involved with those determined to be important in common bean domestication. METHODS: Quantitative trait loci and classical genetic analysis are used to investigate and identify the genes modified at three stages of the domestication process. Five recombinant inbred populations involving crosses between different lines representing different stages are examined. KEY RESULTS: A minimum of 15 known genes, in addition to a relatively few major quantitative trait loci, are identified as being critical to the domestication process. These genes control traits such as pod dehiscence, seed dormancy, seed size and other seed quality characters, stem height, root mass, and harvest index. Several of the genes have pleiotropic effects that in species possessing a more rudimentary genetic characterization might have been interpreted as clusters of genes. Very little evidence for gene clustering was found in pea. When compared with common bean, pea has used a different set of genes to produce the same or similar phenotypic changes. CONCLUSIONS: Similar to results for common bean, relatively few genes appear to have been modified during the domestication of pea. However, the genes involved are different, and there does not appear to be a common genetic basis to 'domestication syndrome' in the Fabaceae.     

The neurobiological context of autism

Autistic disorder (AD) is a complex neuropsychiatric disorder of neurodevelopmental origin, where multiple genetic and environmental factors may interact, resulting in a clinical continuum. The genetic component is best described by a multilocus model that takes into account epistatic interactions between several susceptibility genes. In the past ten years enormous progress has been made in identifying chromosomal regions in linkage with AD, but moving from chromosomal regions to candidate genes has proven to be tremendously difficult. Neuroanatomical findings point to early dysgenetic events taking place in the cerebral cortex, cerebellum, and brainstem. At the cellular level, disease mechanisms may include altered cell migration, increased cell proliferation, decreased cell death, or altered synapse elimination. Neurochemical findings in AD point to involvement of multiple neurotransmitter systems. The serotoninergic system has been intensively investigated in AD, but other neurotransmitter systems (e.g., the GABAergic and the cholinergic system) are also coming under closer scrutiny. The role of environmental factors is still poorly characterized. It is not clear yet whether environmental factors act merely as precipitating agents, always requiring an underlying genetic liability, or whether they represent an essential component of a pathogenetic process where genetic liability alone does not lead to the full-blown autism phenotype. A third potential player in the pathogenesis of autism, in addition to genetic and environmental factors, is developmental variability due to “random” factors, e.g. small fluctuations of gene expression and complex, non-deterministic interactions between genes during brain development. These considerations suggest that a non-deterministic conceptual framework is highly appropriate for autism research.