Genome-wide association study of LDL-cholesterol over ApoB ratio

Genome-Wide Association Study analytical (GWAS) methods were applied in a large biracial sample of individuals to investigate variation across the genome for its association with a surrogate low-density lipoprotein (LDL) particle size phenotype, the ratio of LDL-cholesterol level over ApoB level. Genotyping was performed on the Affymetrix 6.0 GeneChip with approximately one million single nucleotide polymorphisms (SNPs). The ratio of LDL cholesterol to ApoB was calculated, and association tests used multivariable linear regression analysis with an additive genetic model after adjustment for the covariates sex, age and BMI. Association tests were performed separately in African Americans and Caucasians. There were 9,562 qualified individuals in the Caucasian group and 3,015 qualified individuals in the African American group. Overall, in Caucasians two statistically significant loci were identified as being associated with the ratio of LDL-cholesterol over ApoB: rs10488699 (p<5 x10-8, 11q23.3 near BUD13) and the SNP rs964184 (p<5 x10-8 11q23.3 near ZNF259). We also found rs12286037 ((p<4x10-7) (11q23.3) near APOA5/A4/C3/A1 with suggestive associate in the Caucasian sample. In exploratory analyses, a difference in the pattern of association between individuals taking and not taking LDL-cholesterol lowering medications was observed. Individuals who were not taking medications had smaller p-value than those taking medication. In the African-American group, there were no significant (p<5x10-8) or suggestive associations (p<4x10-7) with the ratio of LDL-cholesterol over ApoB after adjusting for age, BMI, and sex and comparing individuals with and without LDL-cholesterol lowering medication. Conclusions: There were significant and suggestive associations between SNP genotype and the ratio of LDL-cholesterol to ApoB in Caucasians, but these associations may be modified by medication treatment.^

Network-based genome-wide association study of Crohn's disease

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. Many recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. The current study incorporated gene network information into gene-based analysis of GWAS data for Crohn's disease (CD). The purpose was to develop statistical models to boost the power of identifying disease-associated genes and gene subnetworks by maximizing the use of existing biological knowledge from multiple sources. The results revealed that Markov random field (MRF) based mixture model incorporating direct neighborhood information from a single gene network is not efficient in identifying CD-related genes based on the GWAS data. The incorporation of solely direct neighborhood information might lead to the low efficiency of these models. Alternative MRF models looking beyond direct neighboring information are necessary to be developed in the future for the purpose of this study.^

Pathway analysis of genome-wide association study data in primary biliary cirrhosisa

Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^

Genetic underpinnings of variation in brain ventricular volume: A genome-wide association study

The ventricular system is a critical component of the central nervous system (CNS) that is formed early in the developmental stages and remains functional through the lifetime. Changes in the ventricular system can be easily discerned via neuroimaging procedures and most of the time it reflects changes in the physiology of the CNS. In this study we attempted to identify specific genes associated with variation in ventricular volume in humans. Methods. We conducted a genome wide association (GWA) analysis of the volume of the lateral ventricles among 1605 individuals of European ancestry from two community based cohorts, the Genetics of Microangiopathic Brain Injury (GMBI; N=814) and Atherosclerosis Risk in Communities (ARIC; N=791). Significant findings from the analysis were tested for replication in both the cohorts and then meta-analyzed to get an estimate of overall significance. Results. In our GWA analyses, no single nucleotide polymorphism (SNP) reached a genome-wide significance of p<10−8. There were 25 SNPs in GMBI and 9 SNPs in ARIC that reached a threshold of p<10 −5. However, none of the top SNPs from each cohort were replicated in the other. In the meta-analysis, no SNP reached the genome-wide threshold of 5×10−8, but we identified five novel SNPs associated with variation in ventricular volume at the p<10 −5 level. Strongest association was for rs2112536 in an intergenic region on chromosome 5q33 (Pmeta= 8.46×10−7 ). The remaining four SNPs were located on chromosome 3q23 encompassing the gene for Calsyntenin-2 (CLSTN2). The SNPs with strongest association in this region were rs17338555 (Pmeta= 5.28×10 −6), rs9812091 (Pmeta= 5.89×10−6 ), rs9812283 (Pmeta= 5.97×10−6) and rs9833213 (Pmeta= 6.96×10−6). Conclusions. This GWA study of ventricular volumes in the community-based cohorts of European descent identifies potential locus on chromosomes 3 and 5. Further characterization of these loci may provide insights into pathophysiology of ventricular involvement in various neurological diseases.^

GENOME-WIDE PROFILING UNVEILS CRITICIAL FUNCTIONS OF p53 IN HUMAN EMBRYONIC STEM CELLS

Embryonic stem cells (ESCs) possess two unique characteristics: infinite self-renewal and the potential to differentiate into almost every cell type (pluripotency). Recently, global expression analyses of metastatic breast and lung cancers revealed an ESC-like expression program or signature, specifically for cancers that are mutant for p53 function. Surprisingly, although p53 is widely recognized as the guardian of the genome, due to its roles in cell cycle checkpoints, programmed cell death or senescence, relatively little is known about p53 functions in normal cells, especially in ESCs. My hypothesis is that p53 has specific transcription regulatory functions in human ESCs (hESCs) that a) oppose pluripotency and b) protect the stem cell genome in response to DNA damage and stress signaling. In mouse ESCs, these roles are believed to coincide, as p53 promotes differentiation in response to DNA damage, but this is unexplored in hESCs. To determine the biological roles of p53, specifically in hESCs, we mapped genome-wide chromatin interactions of p53 by chromatin immunoprecipitation and massively parallel tag sequencing (ChIP-Seq), and did so under three VIdifferent conditions of hESC status: pluripotency, differentiation-initiated and DNA-damage-induced. ChIP-Seq showed that p53 is enriched at distinct, induction-specific gene loci during each of these different conditions. Microarray gene expression analysis and functional annotation of the distinct p53-target genes revealed that p53 regulates specific genes encoding developmental regulators, which are expressed in differentiation-initiated but not DNA- damaged hESCs. We further discovered that, in response to differentiation signaling, p53 binds regions of chromatin that are repressed but also poised for rapid activation by core pluripotency factors OCT4 and NANOG in pluripotent hESCs. In response to DNA damage, genes associated with migration and motility are targeted by p53; whereas, the prime targets of p53 in control of cell death are conserved for p53 regulation in both differentiation and DNA damage. Our genome-wide profiling and bioinformatics analyses show that p53 occupies a special set of developmental regulatory genes during early differentiation of hESCs and functions in an induction-specific manner. In conclusion, our research unveiled previously unknown functions of p53 in ESC biology, which augments our understanding of one of the most deregulated proteins in human cancers.

Nonlinear dimension reduction in pathway-based genome-wide association analysis

Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

Genome -wide and locus -specific instability

The discovery of expanded simple repeated sequences causing or associated with human disease has lead to a new area of research involved in the elucidation of how the expanded repeat causes disease and how the repeat becomes unstable. ^ To study the genetic basis of the (CTG)n repeat instability in the DMPK gene in myotonic dystrophy (DM1) patients, somatic cell hybrids were constructed between the lymphocytes of DM1 patients and a variety of Chinese hamster ovary (CHO) cell DNA repair gene deficient mutants. By using small pool PCR (SP-PCR), the instability of the (CTG)n can be quantitated for both the frequency and sizes of length change mutations. ^ Additional SP-PCR analysis on 2/11 subclones generated from this original hybrid showed a marked increase in large repeat deletions, ∼50%. A bimodal distribution of repeats was seen around the progenitor allele and at a large deleted product (within the normal range) with no intermediate products present. ^ To determine if the repair capacity of the CHO cell led to a mutator phenotype in the hamster and hybrid clones, SP-PCR was also done on 3 hamster microsatellites in a variety of hamster cell backgrounds. No variant alleles were seen in over 2500 genome equivalents screened. ^ Human-hamster hybrids have long been shown to be chromosomally unstable, yet information about the stability of repeated sequences was not known. To test if repeat instability was associated with either intact or non-intact human chromosomes, more than 300 microsatellite repeats on 13 human chromosomes (intact and non-intact) were analyzed in eight hybrid cells. No variants were seen between the hybrid and patient alleles in the hybrids. ^ To identify whether DM1 patients have a previously undetected level of genome wide instability or if the instability is truly locus specific, SP-PCR was done on 6 human microsatellites within the patient used to make the hybrid cells. No variants were seen in over 1000 genomes screened. ^ These studies show that the somatic cell hybrid approach is a genetically stable system that allows for the determination of factors that could lead to changes in microsatellite instability. It also shows that there is something inherent about the DM1 expanded (CTG)n repeat that it is solely targeted by, as of yet, and unknown mechanism that causes the repeat to be unstable. (Abstract shortened by UMI.)^

Genome-Wide Analysis of the Response of Dickeya dadantii 3937 to Plant Antimicrobial Peptides

Antimicrobial peptides constitute an important factor in the defense of plants against pathogens, and bacterial resistance to these peptides have previously been shown to be an important virulence factor in Dickeya dadantii, the causal agent of soft-rot disease of vegetables. In order to understand the bacterial response to antimicrobial pep- tides, a transcriptional microarray analysis was performed upon treatment with sub-lethal concentration of thionins, a widespread plant peptide. In all, 36 genes were found to be overexpressed, and were classified according to their deduced function as i) transcriptional regulators, ii) transport, and iii) modification of the bacterial membrane. One gene encoding a uricase was found to be repressed. The majority of these genes are known to be under the control of the PhoP/PhoQ system. Five genes representing the different functions induced were selected for further analysis. The results obtained indicate that the presence of antimicrobial peptides induces a complex response which includes peptide-specific elements and general stress-response elements contributing differentially to the virulence in different hosts.

Yeast microarrays for genome wide parallel genetic and gene expression analysis

We have developed high-density DNA microarrays of yeast ORFs. These microarrays can monitor hybridization to ORFs for applications such as quantitative differential gene expression analysis and screening for sequence polymorphisms. Automated scripts retrieved sequence information from public databases to locate predicted ORFs and select appropriate primers for amplification. The primers were used to amplify yeast ORFs in 96-well plates, and the resulting products were arrayed using an automated micro arraying device. Arrays containing up to 2,479 yeast ORFs were printed on a single slide. The hybridization of fluorescently labeled samples to the array were detected and quantitated with a laser confocal scanning microscope. Applications of the microarrays are shown for genetic and gene expression analysis at the whole genome level.

Cluster analysis and display of genome-wide expression patterns

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

Genome-wide Responses to Mitochondrial DysfunctionV⃞

Mitochondrial dysfunction can lead to diverse cellular and organismal responses. We used DNA microarrays to characterize the transcriptional responses to different mitochondrial perturbations in Saccharomyces cerevisiae. We examined respiratory-deficient petite cells and respiratory-competent wild-type cells treated with the inhibitors of oxidative phosphorylation antimycin, carbonyl cyanide m-chlorophenylhydrazone, or oligomycin. We show that respiratory deficiency, but not inhibition of mitochondrial ATP synthesis per se, induces a suite of genes associated with both peroxisomal activities and metabolite-restoration (anaplerotic) pathways that would mitigate the loss of a complete tricarboxylic acid cycle. The array data suggested, and direct microscopic observation of cells expressing a derivative of green fluorescent protein with a peroxisomal matrix-targeting signal confirmed, that respiratory deficiency dramatically induces peroxisome biogenesis. Transcript profiling of cells harboring null alleles of RTG1, RTG2, or RTG3, genes known to control signaling from mitochondria to the nucleus, suggests that there are multiple pathways of cross-talk between these organelles in yeast.

Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia

Neuropathological and brain imaging studies suggest that schizophrenia may result from neurodevelopmental defects. Cytoarchitectural studies indicate cellular abnormalities suggestive of a disruption in neuronal connectivity in schizophrenia, particularly in the dorsolateral prefrontal cortex. Yet, the molecular mechanisms underlying these findings remain unclear. To identify molecular substrates associated with schizophrenia, DNA microarray analysis was used to assay gene expression levels in postmortem dorsolateral prefrontal cortex of schizophrenic and control patients. Genes determined to have altered expression levels in schizophrenics relative to controls are involved in a number of biological processes, including synaptic plasticity, neuronal development, neurotransmission, and signal transduction. Most notable was the differential expression of myelination-related genes suggesting a disruption in oligodendrocyte function in schizophrenia.

Genome-wide gene expression profiles of the developing mouse hippocampus

We have analyzed the developmental molecular programs of the mouse hippocampus, a cortical structure critical for learning and memory, by means of large-scale DNA microarray techniques. Of 11,000 genes and expressed sequence tags examined, 1,926 showed dynamic changes during hippocampal development from embryonic day 16 to postnatal day 30. Gene-cluster analysis was used to group these genes into 16 distinct clusters with striking patterns that appear to correlate with major developmental hallmarks and cellular events. These include genes involved in neuronal proliferation, differentiation, and synapse formation. A complete list of the transcriptional changes has been compiled into a comprehensive gene profile database (http://BrainGenomics.Princeton.edu), which should prove valuable in advancing our understanding of the molecular and genetic programs underlying both the development and the functions of the mammalian brain.