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author:("Hicks, chinmo")
1.  Evaluation of microarray-based DNA methylation measurement using technical replicates: the Atherosclerosis Risk In Communities (ARIC) Study 
BMC Bioinformatics  2014;15(1):312.
Background
DNA methylation is a widely studied epigenetic phenomenon; alterations in methylation patterns influence human phenotypes and risk of disease. As part of the Atherosclerosis Risk in Communities (ARIC) study, the Illumina Infinium HumanMethylation450 (HM450) BeadChip was used to measure DNA methylation in peripheral blood obtained from ~3000 African American study participants. Over 480,000 cytosine-guanine (CpG) dinucleotide sites were surveyed on the HM450 BeadChip. To evaluate the impact of technical variation, 265 technical replicates from 130 participants were included in the study.
Results
For each CpG site, we calculated the intraclass correlation coefficient (ICC) to compare variation of methylation levels within- and between-replicate pairs, ranging between 0 and 1. We modeled the distribution of ICC as a mixture of censored or truncated normal and normal distributions using an EM algorithm. The CpG sites were clustered into low- and high-reliability groups, according to the calculated posterior probabilities. We also demonstrated the performance of this clustering when applied to a study of association between methylation levels and smoking status of individuals. For the CpG sites showing genome-wide significant association with smoking status, most (~96%) were seen from sites in the high reliability cluster.
Conclusions
We suggest that CpG sites with low ICC may be excluded from subsequent association analyses, or extra caution needs to be taken for associations at such sites.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-312) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2105-15-312
PMCID: PMC4180315  PMID: 25239148
DNA methylation; Infinium 450 K chip; Technical error; Intraclass correlation; Normal mixture models
2.  High CD49f expression is associated with osteosarcoma tumor progression: a study using patient-derived primary cell cultures 
Cancer Medicine  2014;3(4):796-811.
Overall prognosis for osteosarcoma (OS) is poor despite aggressive treatment options. Limited access to primary tumors, technical challenges in processing OS tissues, and the lack of well-characterized primary cell cultures has hindered our ability to fully understand the properties of OS tumor initiation and progression. In this study, we have isolated and characterized cell cultures derived from four central high-grade human OS samples. Furthermore, we used the cell cultures to study the role of CD49f in OS progression. Recent studies have implicated CD49f in stemness and multipotency of both cancer stem cells and mesenchymal stem cells. Therefore, we investigated the role of CD49f in osteosarcomagenesis. First, single cell suspensions of tumor biopsies were subcultured and characterized for cell surface marker expression. Next, we characterized the growth and differentiation properties, sensitivity to chemotherapy drugs, and anchorage-independent growth. Xenograft assays showed that cell populations expressing CD49fhi/CD90lo cell phenotype produced an aggressive tumor. Multiple lines of evidence demonstrated that inhibiting CD49f decreased the tumor-forming ability. Furthermore, the CD49fhi/CD90lo cell population is generating more aggressive OS tumor growth and indicating this cell surface marker could be a potential candidate for the isolation of an aggressive cell type in OSs.
doi:10.1002/cam4.249
PMCID: PMC4303148  PMID: 24802970
Cancer stem cell; CD49f; integrin; osteosarcoma; tumor-initiating cell; tumor progression
3.  Integrative Genomic Analysis for the Discovery of Biomarkers in Prostate Cancer 
Biomarker Insights  2014;9:39-51.
Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.
doi:10.4137/BMI.S13729
PMCID: PMC4085106  PMID: 25057237
GWAS; genetic variants; gene expression; prostate cancer
4.  Comprehensive Assessment and Network Analysis of the Emerging Genetic Susceptibility Landscape of Prostate Cancer 
Cancer Informatics  2013;12:175-191.
Background
Recent advances in high-throughput genotyping have made possible identification of genetic variants associated with increased risk of developing prostate cancer using genome-wide associations studies (GWAS). However, the broader context in which the identified genetic variants operate is poorly understood. Here we present a comprehensive assessment, network, and pathway analysis of the emerging genetic susceptibility landscape of prostate cancer.
Methods
We created a comprehensive catalog of genetic variants and associated genes by mining published reports and accompanying websites hosting supplementary data on GWAS. We then performed network and pathway analysis using single nucleotide polymorphism (SNP)-containing genes to identify gene regulatory networks and pathways enriched for genetic variants.
Results
We identified multiple gene networks and pathways enriched for genetic variants including IGF-1, androgen biosynthesis and androgen signaling pathways, and the molecular mechanisms of cancer. The results provide putative functional bridges between GWAS findings and gene regulatory networks and biological pathways.
doi:10.4137/CIN.S12128
PMCID: PMC3769142  PMID: 24031161
prostate cancer GWAS network pathway analysis
5.  Analysis of Patterns of Gene Expression Variation within and between Ethnic Populations in Pediatric B-ALL 
Cancer Informatics  2013;12:155-173.
B-Precursor acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. Although 80% of B-ALL patients are able to be cured, significant challenges persist. Significant disparities in clinical outcomes and mortality rates exist between racial/ethnic populations. The objective of this study was to determine whether gene expression levels significantly differ between ethnic populations. We compared gene expression levels between four ethnic populations (Whites, Blacks, Hispanics, and Asians) in the United States. Additionally, we performed network and pathway analysis to identify gene networks and pathways. Gene expression data involved 198 samples distributed as follows: 126 Whites, 51 Hispanics, 13 Blacks, and 8 Asians. We identified 300 highly significantly (P < 0.001) differentially expressed genes between the four ethnic populations. Among the identified genes included the genes PHF6, BRD3, CRLF2, and RNF135 which have been implicated in pediatric B-ALL. We identified key pathways implicated in B-ALL including the PDGF, PI3/AKT, ERBB2-ERBB3, and IL-15 signaling pathways.
doi:10.4137/CIN.S11831
PMCID: PMC3762614  PMID: 24023509
leukemia gene expression variation pediatric B-ALL
6.  Novel Integrative Genomics Approach for Associating GWAS Information with Intrinsic Subtypes of Breast Cancer 
Cancer Informatics  2013;12:125-142.
Genome-wide association studies (GWAS) have achieved great success in identifying common variants associated with increased risk of developing breast cancer. However, GWAS do not typically provide information about the broader context in which genetic variants operate in different subtypes of breast cancer. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs, herein called genetic variants) are associated with different subtypes of breast cancer. Additionally, we sought to identify gene regulator networks and biological pathways enriched for these genetic variants. Using supervised analysis, we identified 201 genes that were significantly associated with the six intrinsic subtypes of breast cancer. The results demonstrate that integrative genomics analysis is a powerful approach for linking GWAS information to distinct disease states and provide insights about the broader context in which genetic variants operate in different subtypes of breast cancer.
doi:10.4137/CIN.S11452
PMCID: PMC3663490  PMID: 23761956
GWAS subtypes breast cancer
7.  An Integrative Genomics Approach for Associating GWAS Information with Triple-Negative Breast Cancer 
Cancer Informatics  2013;12:1-20.
Genome-wide association studies (GWAS) have identified genetic variants associated with an increased risk of developing breast cancer. However, the association of genetic variants and their associated genes with the most aggressive subset of breast cancer, the triple-negative breast cancer (TNBC), remains a central puzzle in molecular epidemiology. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs) associated with an increased risk of developing breast cancer are connected to and could stratify different subtypes of TNBC. Additionally, we sought to identify molecular pathways and networks involved in TNBC. We performed integrative genomics analysis, combining information from GWAS studies involving over 400,000 cases and over 400,000 controls, with gene expression data derived from 124 breast cancer patients classified as TNBC (at the time of diagnosis) and 142 cancer-free controls. Analysis of GWAS reports produced 500 SNPs mapped to 188 genes. We identified a signature of 159 functionally related SNP-containing genes which were significantly (P <10−5) associated with and stratified TNBC. Additionally, we identified 97 genes which were functionally related to, and had similar patterns of expression profiles, SNP-containing genes. Network modeling and pathway prediction revealed multi-gene pathways including p53, NFkB, BRCA, apoptosis, DNA repair, DNA mismatch, and excision repair pathways enriched for SNPs mapped to genes significantly associated with TNBC. The results provide convincing evidence that integrating GWAS information with gene expression data provides a unified and powerful approach for biomarker discovery in TNBC.
doi:10.4137/CIN.S10413
PMCID: PMC3565545  PMID: 23423317
triple negative breast cancer GWAS gene expression
9.  Integrative Analysis of Response to Tamoxifen Treatment in ER-Positive Breast Cancer Using GWAS Information and Transcription Profiling 
Variable response and resistance to tamoxifen treatment in breast cancer patients remains a major clinical problem. To determine whether genes and biological pathways containing SNPs associated with risk for breast cancer are dysregulated in response to tamoxifen treatment, we performed analysis combining information from 43 genome-wide association studies with gene expression data from 298 ER+ breast cancer patients treated with tamoxifen and 125 ER+ controls. We identified 95 genes which distinguished tamoxifen treated patients from controls. Additionally, we identified 54 genes which stratified tamoxifen treated patients into two distinct groups. We identified biological pathways containing SNPs associated with risk for breast cancer, which were dysregulated in response to tamoxifen treatment. Key pathways identified included the apoptosis, P53, NFkB, DNA repair and cell cycle pathways. Combining GWAS with transcription profiling provides a unified approach for associating GWAS findings with response to drug treatment and identification of potential drug targets.
doi:10.4137/BCBCR.S8652
PMCID: PMC3292850  PMID: 22399860
tamoxifen genome-wide association studies gene expression
11.  An Integrative Genomics Approach to Biomarker Discovery in Breast Cancer 
Cancer Informatics  2011;10:185-204.
Genome-wide association studies (GWAS) have successfully identified genetic variants associated with risk for breast cancer. However, the molecular mechanisms through which the identified variants confer risk or influence phenotypic expression remains poorly understood. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to assess the combined contribution of multiple genetic variants acting within genes and putative biological pathways, and to identify novel genes and biological pathways that could not be identified using traditional GWAS. The results show that genes containing SNPs associated with risk for breast cancer are functionally related and interact with each other in biological pathways relevant to breast cancer. Additionally, we identified novel genes that are co-expressed and interact with genes containing SNPs associated with breast cancer. Integrative analysis combining GWAS information with gene expression data provides functional bridges between GWAS findings and biological pathways involved in breast cancer.
doi:10.4137/CIN.S6837
PMCID: PMC3153161  PMID: 21869864
genome-wide association studies gene expression pathway
12.  Associating GWAS Information with the Notch Signaling Pathway Using Transcription Profiling 
Cancer Informatics  2011;10:93-108.
Genome-wide association studies (GWAS) have identified SNPs associated with breast cancer. However, they offer limited insights about the biological mechanisms by which SNPs confer risk. We investigated the association of GWAS information with a major oncogenic pathway in breast cancer, the Notch signaling pathway. We first identified 385 SNPs and 150 genes associated with risk for breast cancer by mining data from 41 GWAS. We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations. Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer. Additionally, we identified other SNP-associated biological pathways relevant to breast cancer, including the P53, apoptosis and MAP kinase pathways.
doi:10.4137/CIN.S6072
PMCID: PMC3091413  PMID: 21584266
GWAS; gene expression; Notch signaling pathway
13.  A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements 
BMC Bioinformatics  2010;11:22.
Background
Polymorphic variants and mutations disrupting canonical splicing isoforms are among the leading causes of human hereditary disorders. While there is a substantial evidence of aberrant splicing causing Mendelian diseases, the implication of such events in multi-genic disorders is yet to be well understood. We have developed a new tool (SpliceScan II) for predicting the effects of genetic variants on splicing and cis-regulatory elements. The novel Bayesian non-canonical 5'GC splice site (SS) sensor used in our tool allows inference on non-canonical exons.
Results
Our tool performed favorably when compared with the existing methods in the context of genes linked to the Autism Spectrum Disorder (ASD). SpliceScan II was able to predict more aberrant splicing isoforms triggered by the mutations, as documented in DBASS5 and DBASS3 aberrant splicing databases, than other existing methods. Detrimental effects behind some of the polymorphic variations previously associated with Alzheimer's and breast cancer could be explained by changes in predicted splicing patterns.
Conclusions
We have developed SpliceScan II, an effective and sensitive tool for predicting the detrimental effects of genomic variants on splicing leading to Mendelian and complex hereditary disorders. The method could potentially be used to screen resequenced patient DNA to identify de novo mutations and polymorphic variants that could contribute to a genetic disorder.
doi:10.1186/1471-2105-11-22
PMCID: PMC3098058  PMID: 20067640
14.  Computational prediction of splicing regulatory elements shared by Tetrapoda organisms 
BMC Genomics  2009;10:508.
Background
Auxiliary splicing sequences play an important role in ensuring accurate and efficient splicing by promoting or repressing recognition of authentic splice sites. These cis-acting motifs have been termed splicing enhancers and silencers and are located both in introns and exons. They co-evolved into an intricate splicing code together with additional functional constraints, such as tissue-specific and alternative splicing patterns. We used orthologous exons extracted from the University of California Santa Cruz multiple genome alignments of human and 22 Tetrapoda organisms to predict candidate enhancers and silencers that have reproducible and statistically significant bias towards annotated exonic boundaries.
Results
A total of 2,546 Tetrapoda enhancers and silencers were clustered into 15 putative core motifs based on their Markov properties. Most of these elements have been identified previously, but 118 putative silencers and 260 enhancers (~15%) were novel. Examination of previously published experimental data for the presence of predicted elements showed that their mutations in 21/23 (91.3%) cases altered the splicing pattern as expected. Predicted intronic motifs flanking 3' and 5' splice sites had higher evolutionary conservation than other sequences within intronic flanks and the intronic enhancers were markedly differed between 3' and 5' intronic flanks.
Conclusion
Difference in intronic enhancers supporting 5' and 3' splice sites suggests an independent splicing commitment for neighboring exons. Increased evolutionary conservation for ISEs/ISSs within intronic flanks and effect of modulation of predicted elements on splicing suggest functional significance of found elements in splicing regulation. Most of the elements identified were shown to have direct implications in human splicing and therefore could be useful for building computational splicing models in biomedical research.
doi:10.1186/1471-2164-10-508
PMCID: PMC2777938  PMID: 19889216
15.  fMRI Study of Language Activation in Schizophrenia, Schizoaffective Disorder and in Individuals Genetically at High Risk 
Schizophrenia research  2007;96(1-3):14-24.
Background:
Structural and functional abnormalities have been found in language-related brain regions in patients with schizophrenia. We previously reported findings pointing to differences in word processing between people with schizophrenia and individuals who are at high-risk for schizophrenia using a voxel-based (whole brain) fMRI approach. We now extend this finding to specifically examine functional activity in three language related cortical regions using a larger cohort of individuals.
Method:
A visual lexical discrimination task was performed by 36 controls, 21 subjects at high genetic-risk for schizophrenia, and 20 patients with schizophrenia during blood oxygenation level dependent (BOLD) fMRI scanning. Activation in bilateral inferior frontal gyri (Brodmann's area 44-45), bilateral inferior parietal lobe (Brodmann's area 39-40), and bilateral superior temporal gyri (Brodmann's area 22) was investigated. For all subjects, two-tailed Pearson correlations were calculated between the computed laterality index and a series of cognitive test scores determining language functioning.
Results:
Regional activation in Brodmann's area 44-45 was left lateralized in normal controls, while high-risk subjects and patients with schizophrenia or schizoaffective disorder showed more bilateral activation. No significant differences among the three diagnostic groups in the other two regions of interest (Brodmann's area 22 or areas 39-40) were found. Furthermore, the apparent reasons for loss of leftward language lateralization differed between groups. In high-risk subjects, the loss of lateralization was based on reduced left hemisphere activation, while in the patient group, it was due to increased right side activation. Language ability related cognitive scores were positively correlations with the laterality indices obtained from Brodmann's areas 44-45 in the high-risk group, and with the laterality indices from Brodmann's areas 22 and 44-45 in the patient group.
Conclusions:
This study reinforces previous language related imaging studies in high-risk subjects and patients with schizophrenia suggesting that reduced functional lateralization in language related frontal cortex may be a vulnerability marker for schizophrenia. Future studies will determine whether it is predictive of who develops illness.
doi:10.1016/j.schres.2007.07.013
PMCID: PMC2212592  PMID: 17719745
fMRI; schizophrenia; High risk, genetic; Language lateralization; ROI based study

Results 1-15 (15)