Marco A. Azaro

Identification of a Schizophrenia-Associated Functional Noncoding Variant in NOS1AP

OBJECTIVE The authors previously demonstrated significant association between markers within NOS1AP and schizophrenia in a set of Canadian families of European descent, as well as significantly increased expression in schizophrenia of NOS1AP in unrelated postmortem samples from the dorsolateral prefrontal cortex. In this study the authors sought to apply novel statistical methods and conduct additional biological experiments to isolate at least one risk allele within NOS1AP. METHOD Using the posterior probability of linkage disequilibrium (PPLD) to measure the probability that a single nucleotide polymorphism (SNP) is in linkage disequilibrium with schizophrenia, the authors evaluated 60 SNPs from NOS1AP in 24 Canadian families demonstrating linkage and association to this region. SNPs exhibiting strong evidence of linkage disequilibrium were tested for regulatory function by luciferase reporter assay. Two human neural cell lines (SK-N-MC and PFSK-1) were transfected with a vector containing each allelic variant of the SNP, the NOS1AP promoter, and a luciferase gene. Alleles altering expression were further assessed for binding of nuclear proteins by electrophoretic mobility shift assay. RESULTS Three SNPs produced PPLDs >40%. One of them, rs12742393, demonstrated significant allelic expression differences in both cell lines tested. The allelic variation at this SNP altered the affinity of nuclear protein binding to this region of DNA. CONCLUSIONS The A allele of rs12742393 appears to be a risk allele associated with schizophrenia that acts by enhancing transcription factor binding and increasing gene expression.

Arm Sequences Contribute to the Architecture and Catalytic Function of a λ Integrase-Holliday Junction Complex.

λ integrase (Int) mediates recombination between attachment sites on λ phage and E. coli DNAs. With the assistance of accessory proteins that induce DNA loops, Int bridges pairs of distinct arm- and core-type DNA binding sites to form synapsed recombination complexes, which then recombine via a Holliday junction (HJ) intermediate. We show that, in addition to promoting the proper positioning of Int protomers, the arm sequences facilitate the catalytic activities of the Int tetramer, independent of accessory proteins or physical continuity between the arm and core sites. We have determined the architecture of ternary complexes containing a HJ, Int, and P′1,2 arm-type DNA. These structures accommodate simultaneous binding of Int to direct-repeat arm sites and indirect-repeat core sites and afford a new view of the higher-order recombinogenic complexes.

Improvements to bead-based oligonucleotide ligation SNP genotyping assays

We describe a bead-based, multiplexed, oligonucleotide ligation assay (OLA) performed on the Luminex flow cytometer. Differences between this method and those previously reported include the use of far fewer beads and the use of a universal oligonucleotide for signal detection. These innovations serve to significantly reduce the cost of the assay, while maintaining robustness and accuracy. Comparisons are made between the Luminex OLA and both pyrosequencing and direct sequencing. Experiments to assess conversion rates, call rates, and concordance across technical replicates are also presented.

Increasing Genotype-Phenotype Model Determinism: Application to Bivariate Reading/Language Traits and Epistatic Interactions in Language-Impaired Families

While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from .

Combined linkage and linkage disequilibrium analysis of a motor speech phenotype within families ascertained for autism risk loci

Using behavioral and genetic information from the Autism Genetics Resource Exchange (AGRE) data set we developed phenotypes and investigated linkage and association for individuals with and without Autism Spectrum Disorders (ASD) who exhibit expressive language behaviors consistent with a motor speech disorder. Speech and language variables from Autism Diagnostic Interview-Revised (ADI-R) were used to develop a motor speech phenotype associated with non-verbal or unintelligible verbal behaviors (NVMSD:ALL) and a related phenotype restricted to individuals without significant comprehension difficulties (NVMSD:C). Using Affymetrix 5.0 data, the PPL framework was employed to assess the strength of evidence for or against trait-marker linkage and linkage disequilibrium (LD) across the genome. Ingenuity Pathway Analysis (IPA) was then utilized to identify potential genes for further investigation. We identified several linkage peaks based on two related language-speech phenotypes consistent with a potential motor speech disorder: chromosomes 1q24.2, 3q25.31, 4q22.3, 5p12, 5q33.1, 17p12, 17q11.2, and 17q22 for NVMSD:ALL and 4p15.2 and 21q22.2 for NVMSD:C. While no compelling evidence of association was obtained under those peaks, we identified several potential genes of interest using IPA. Conclusion: Several linkage peaks were identified based on two motor speech phenotypes. In the absence of evidence of association under these peaks, we suggest genes for further investigation based on their biological functions. Given that autism spectrum disorders are complex with a wide range of behaviors and a large number of underlying genes, these speech phenotypes may belong to a group of several that should be considered when developing narrow, well-defined, phenotypes in the attempt to reduce genetic heterogeneity.

A highly sensitive and specific system for large-scale gene expression profiling

BackgroundRapid progress in the field of gene expression-based molecular network integration has generated strong demand on enhancing the sensitivity and data accuracy of experimental systems. To meet the need, a high-throughput gene profiling system of high specificity and sensitivity has been developed.ResultsBy using specially designed primers, the new system amplifies sequences in neighboring exons separated by big introns so that mRNA sequences may be effectively discriminated from other highly related sequences including their genes, unprocessed transcripts, pseudogenes and pseudogene transcripts. Probes used for microarray detection consist of sequences in the two neighboring exons amplified by the primers. In conjunction with a newly developed high-throughput multiplex amplification system and highly simplified experimental procedures, the system can be used to analyze >1,000 mRNA species in a single assay. It may also be used for gene expression profiling of very few (n = 100) or single cells. Highly reproducible results were obtained from duplicate samples with the same number of cells, and from those with a small number (100) and a large number (10,000) of cells. The specificity of the system was demonstrated by comparing results from a breast cancer cell line, MCF-7, and an ovarian cancer cell line, NCI/ADR-RES, and by using genomic DNA as starting material.ConclusionOur approach may greatly facilitate the analysis of combinatorial expression of known genes in many important applications, especially when the amount of RNA is limited.

Lipopolysaccharide (LPS) potentiates hydrogen peroxide toxicity in T98G astrocytoma cells by suppression of anti-oxidative and growth factor gene expression

BackgroundLipopolysaccharide (LPS) is a cell wall component of Gram-negative bacteria with proved role in pathogenesis of sepsis. Brain injury was observed with both patients dead from sepsis and animal septic models. However, in vitro administration of LPS has not shown obvious cell damage to astrocytes and other relative cell lines while it does cause endothelial cell death in vitro. These observations make it difficult to understand the role of LPS in brain parenchymal injury.ResultsTo test the hypothesis that LPS may cause biological changes in astrocytes and make the cells to become vulnerable to reactive oxygen species, a recently developed highly sensitive and highly specific system for large-scale gene expression profiling was used to examine the gene expression profile of a group of 1,135 selected genes in a cell line, T98G, a derivative of human glioblastoma of astrocytic origin. By pre-treating T98G cells with different dose of LPS, it was found that LPS treatment caused a broad alteration in gene expression profile, but did not cause obvious cell death. However, after short exposure to H2O2, cell death was dramatically increased in the LPS pretreated samples. Interestingly, cell death was highly correlated with down-regulated expression of antioxidant genes such as cytochrome b561, glutathione s-transferase a4 and protein kinase C-epsilon. On the other hand, expression of genes encoding growth factors was significantly suppressed. These changes indicate that LPS treatment may suppress the anti-oxidative machinery, decrease the viability of the T98G cells and make the cells more sensitive to H2O2 stress.ConclusionThese results provide very meaningful clue for further exploring and understanding the mechanism underlying astrocyte injury in sepsis in vivo, and insight for why LPS could cause astrocyte injury in vivo, but not in vitro. It will also shed light on the therapeutic strategy of sepsis.

Revisiting schizophrenia linkage data in the NIMH Repository: reanalysis of regularized data across multiple studies.

OBJECTIVE The Combined Analysis of Psychiatric Studies (CAPS) project conducted extensive review and regularization across studies of all schizophrenia linkage data available as of 2011 from the National Institute of Mental Health-funded Center for Collaborative Genomic Studies on Mental Disorders, also known as the Human Genetics Initiative (HGI). The authors reanalyzed the data using statistical methods tailored to accumulation of evidence across multiple, potentially highly heterogeneous, sets of data. METHOD Data were subdivided based on contributing study, major population group, and presence or absence within families of schizophrenia with a substantial affective component. The posterior probability of linkage (PPL) statistical framework was used to sequentially update linkage evidence across these data subsets (omnibus results). RESULTS While some loci previously implicated using the HGI data were also identified in the present omnibus analysis (2q36.1, 15q23), others were not. Several loci were found that had not previously been reported in the HGI samples but are supported by independent linkage or association studies (3q28, 12q23.1, 11p11.2, Xq26.1). Not surprisingly, differences were seen across population groups. Of particular interest are signals on 11p15.3, 11p11.2, and Xq26.1, for which data from families with a substantial affective component support linkage while data from the remaining families provide evidence against linkage. All three of these loci overlap with loci reported in independent studies of bipolar disorder or mixed bipolar-schizophrenia samples. CONCLUSIONS Public data repositories provide the opportunity to leverage large multisite data sets for studying complex disorders. Analysis with a statistical method specifically designed for such data enables us to extract new information from an existing data resource.

Validation of a cost-efficient multi-purpose SNP panel for disease based research.

Background Here we present convergent methodologies using theoretical calculations, empirical assessment on in-house and publicly available datasets as well as in silico simulations, that validate a panel of SNPs for a variety of necessary tasks in human genetics disease research before resources are committed to larger-scale genotyping studies on those samples. While large-scale well-funded human genetic studies routinely have up to a million SNP genotypes, samples in a human genetics laboratory that are not yet part of such studies may be productively utilized in pilot projects or as part of targeted follow-up work though such smaller scale applications require at least some genome-wide genotype data for quality control purposes such as DNA “barcoding” to detect swaps or contamination issues, determining familial relationships between samples and correcting biases due to population effects such as population stratification in pilot studies. Principal Findings Empirical performance in classification of relative types for any two given DNA samples (e.g., full siblings, parental, etc) indicated that for outbred populations the panel performs sufficiently to classify relationship in extended families and therefore also for smaller structures such as trios and for twin zygosity testing. Additionally, familial relationships do not significantly diminish the (mean match) probability of sharing SNP genotypes in pedigrees, further indicating the uniqueness of the “barcode.” Simulation using these SNPs for an African American case-control disease association study demonstrated that population stratification, even in complex admixed samples, can be adequately corrected under a range of disease models using the SNP panel. Conclusion The panel has been validated for use in a variety of human disease genetics research tasks including sample barcoding, relationship verification, population substructure detection and statistical correction. Given the ease of genotyping our specific assay contained herein, this panel represents a useful and economical panel for human geneticists.