Gene copy number variation in schizophrenia

Transcriptomics analysis of iPSC-derived neurons and modeling of neuropsychiatric disorders

Induced pluripotent stem cell (iPSC)-derived neurons and neural progenitors are great resources for studying neural development and differentiation and their disruptions in disease conditions, and hold the promise of future cell therapy. In general, iPSC lines can be established either specifically from patients with neuropsychiatric disorders or from healthy subjects. The iPSCs can then be induced to differentiate into neural lineages and the iPSC-derived neurons are valuable for various types of cell-based assays that seek to understand disease mechanisms and identify and test novel therapies. In addition, it is an ideal system for gene expression profiling (i.e., transcriptomic analysis), an efficient and cost-effective way to explore the genetic programs regulating neurodevelopment. Moreover, transcriptomic comparison, which can be performed between patient-derived samples and controls, or in control lines in which the expression of specific genes has been disrupted, can uncover convergent gene targets and pathways that are downstream of the hundreds of candidate genes that have been associated with neuropsychiatric disorders. The results, especially after integration with spatiotemporal transcriptomic profiles of normal human brain development, have indeed helped to uncover gene networks, molecular pathways, and cellular signaling that likely play critical roles in disease development and progression. On the other hand, despite the great promise, many challenges remain in the usage of iPSC-derived neurons for modeling neuropsychiatric disorders, for example, how to generate relatively homogenous populations of specific neuronal subtypes that are affected in a particular disorder and how to better address the genetic heterogeneity that exists in the patient population.

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs

Integrative analysis of multiple data types can take advantage of their complementary information and therefore may provide higher power to identify potential biomarkers that would be missed using individual data analysis. Due to different natures of diverse data modality, data integration is challenging. Here we address the data integration problem by developing a generalized sparse model (GSM) using weighting factors to integrate multi-modality data for biomarker selection. As an example, we applied the GSM model to a joint analysis of two types of schizophrenia data sets: 759,075 SNPs and 153,594 functional magnetic resonance imaging (fMRI) voxels in 208 subjects (92 cases/116 controls). To solve this small-sample-large-variable problem, we developed a novel sparse representation based variable selection (SRVS) algorithm, with the primary aim to identify biomarkers associated with schizophrenia. To validate the effectiveness of the selected variables, we performed multivariate classification followed by a ten-fold cross validation. We compared our proposed SRVS algorithm with an earlier sparse model based variable selection algorithm for integrated analysis. In addition, we compared with the traditional statistics method for uni-variant data analysis (Chi-squared test for SNP data and ANOVA for fMRI data). Results showed that our proposed SRVS method can identify novel biomarkers that show stronger capability in distinguishing schizophrenia patients from healthy controls. Moreover, better classification ratios were achieved using biomarkers from both types of data, suggesting the importance of integrative analysis.

Long tandem repeats as a form of genomic copy number variation: structure and length polymorphism of a chromosome 5p repeat in control and schizophrenia populations

OBJECTIVES

Genomic copy number variations (CNVs) are a major form of variation in the human genome and play an etiologic role in several neuropsychiatric diseases. Tandem repeats, particularly with long (>50 bp) repeat units, are a relatively common yet underexplored type of CNV that may significantly contribute to human genomic variation and disease risk. We therefore carried out a pilot experiment to explore the potential role of long tandem repeats as risk factors in psychiatric disorders.

METHODS

A bacterial artificial chromosome-based array comparative genomic hybridization (aCGH) platform was used to examine CNVs in genomic DNA from 34 probands with schizophrenia or schizoaffective disorder.

RESULTS

The aCGH screen detected an apparent deletion on 5p15.1 in two probands, caused by the presence in each proband of two low copy number (short) alleles of a tandem repeat that ranges in length from fewer than 10 to greater than 50 3.4 kb units in the population examined. Short alleles partially segregate with schizophrenia in a small number of families, though linkage was not significant. An association study showed no significant difference in repeat length between 406 schizophrenia cases and 392 controls.

CONCLUSION

Although we did not demonstrate a relationship between the 5p15.1 repeat and schizophrenia, our results illustrate that long tandem repeats represent an intriguing type of genetic variation that have not been studied in earlier connection with psychiatric illness. aCGH can detect a small subset of these repeats, but systematic investigation will require the development of specific arrays and improved analytical methods.

What we know: findings that every theory of schizophrenia should explain

The article summarizes the process used to distill schizophrenia science into 22 facts. These facts consist of 6 basic facts, 3 etiological facts, 6 pharmacological and treatment facts, 5 pathology facts, and 2 behavioral facts that were critically reviewed by the scholarly community through a special initiative in cooperation with the Schizophrenia Research Forum. A subset of 10 of these facts was selected to form a common set of findings to be explained from the different theoretical perspectives included in this special section of Schizophrenia Bulletin. The rationale for this exercise is to distinguish more precisely the areas of agreement and disagreement between theories of schizophrenia and to highlight where more thought and data can make the greatest impact for understanding this disease.

Copy number variation showers in schizophrenia: an emerging hypothesis

Genetic discoveries on Schizophrenia remain challenging. Traditional approaches have provided clues, but no genes. Novel theories that must account for extensive heterogeneity, including high discordance of monozygotic (MZD) twins, are needed. To this end, the extensive repeats of the human genome may provide the predisposition for DNA replication errors operational at every cell cycle during meiosis and mitosis. These errors will shower the genome with replication errors including copy number variations. Depending on the timing and the genes involved, this will contribute to the mutational load and disease. The evidence for such a mechanism in schizophrenia is emerging.

Copy variations in schizophrenia and bipolar disorder

The analysis of copy number variations (CNVs) is an emerging tool for identifying genetic factors underlying complex traits. In this chapter I will review studies that have been carried out showing that CNVs play a role in the development of two such complex traits; schizophrenia (SZ) and bipolar disorder (BD). There are two aspects to consider regarding the role of copy variations in these conditions. One is gene discovery in which DNA from patients is analyzed for the purpose of identifying rare, patient-specific CNVs that may be informative to a larger population of affected individuals. The model for this concept is based on the emergence of DISC1 as a SZ candidate gene, which was discovered in a single informative family with a rare chromosomal translocation. Another aspect revolves around the idea that polymorphic CNVs found in the general population, many of which appear to disrupt previously identified SZ and BD candidate genes, contribute to disease pathogenesis. Here, gene-disrupting CNVs are viewed in the same manner as functional SNPs and analyzed for involvement in disease susceptibility using genetic association. Although the analysis of CNVs in patients with psychiatric disorders is in its infancy, informative new findings have already been made, suggesting that this is a very promising line of research.

Update on key previously proposed candidate genes for schizophrenia

PURPOSE OF REVIEW

We will give an overview of more recent data concerning previously implicated candidate genes for schizophrenia. This includes functional data when available. Furthermore, studies on copy number repeats and their possible implications in schizophrenia will be described.

RECENT FINDINGS

Within the past year, schizophrenia genetics has focused on a more detailed investigation of previously implicated candidate genes. In addition, investigation of copy number variations has led to the identification of rare structural DNA variants that might play a major role in some cases of schizophrenia.

SUMMARY

There is emerging evidence that some cases of schizophrenia might be due to rare genetic structural variation, though the majority of cases should be due to a cumulative effect of common variations in multiple genes, which in combination with environmental stressors may lead to the development of schizophrenia.

Searching for the true genetic vulnerability for schizophrenia

The search for a genetic basis for schizophrenia has taken a new turn recently with the publication of three reports of various rare copy-number variations that are associated with schizophrenia. While some of the findings may simply disappear as spurious reports, others remain interesting: that is, deletions in the Velocardiofacial syndrome region of chromosome 22, and regions of chromosome 1q21.1 and 15q13.3. These results will gain greater significance if future validation in family studies shows their segregation with illness within families, and when it is understood how the genes containing these variants affect the underlying neurochemistry and neuropathology characteristic of schizophrenia.

Recent advances in the genetics of autoimmune disease

Extraordinary technical advances in the field of human genetics over the past few years have catalyzed an explosion of new information about the genetics of human autoimmunity. In particular, the ability to scan the entire genome for common polymorphisms that associate with disease has led to the identification of numerous new risk genes involved in autoimmune phenotypes. Several themes are emerging. Autoimmune disorders have a complex genetic basis; multiple genes contribute to disease risk, each with generally modest effects independently. In addition, it is now clear that common genes underlie multiple autoimmune disorders. There is also heterogeneity among subphenotypes within a disease and across major racial groups. The current crop of genetic associations are only the start of a complete catalog of genetic factors for autoimmunity, and it remains unclear to what extent common variation versus multiple rare variants contribute to disease susceptibility. The current review focuses on recent discoveries within functionally related groups of genes that provide clues to novel pathways of pathogenesis for human autoimmunity.

Small molecule protein-protein interaction inhibitors as CNS therapeutic agents: current progress and future hurdles

Protein-protein interactions are a crucial element in cellular function. The wealth of information currently available on intracellular-signaling pathways has led many to appreciate the untapped pool of potential drug targets that reside downstream of the commonly targeted receptors. Over the last two decades, there has been significant interest in developing therapeutics and chemical probes that inhibit specific protein-protein interactions. Although it has been a challenge to develop small molecules that are capable of occluding the large, often relatively featureless protein-protein interaction interface, there are increasing numbers of examples of small molecules that function in this manner with reasonable potency. This article will highlight the current progress in the development of small molecule protein-protein interaction inhibitors that have applications in the treatment or study of central nervous system function and disease. In particular, we will focus upon recent work towards developing small molecule inhibitors of amyloid-beta and alpha-synuclein aggregation, inhibitors of critical components of G-protein-signaling pathways, and PDZ domain inhibitors.