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1.  The Emergence of Genome-Based Drug Repositioning 
Science translational medicine  2011;3(96):96ps35.
In this issue of Science Translational Medicine, the Butte Research group provides a concrete example of how reinterpreting and comparing genome-wide metrics may allow us to effectively hypothesize which drugs from one disease indication can be used for another. Here we discuss the basis of this shift toward genomic computational integrative approaches that has precedence in scalar theories of biological information and is aptly warranted for exploitation in drug repurposing.
PMCID: PMC4262402  PMID: 21849663
2.  Peripheral Blood Mononuclear Cell Gene Expression Profiles Predict Poor Outcome in Idiopathic Pulmonary Fibrosis 
Science translational medicine  2013;5(205):205ra136.
We aimed to identify peripheral blood mononuclear cell (PBMC) gene expression profiles predictive of poor outcomes in idiopathic pulmonary fibrosis (IPF) by performing microarray experiments of PBMCs in discovery and replication cohorts of IPF patients. Microarray analyses identified 52 genes associated with transplant-free survival (TFS) in the discovery cohort. Clustering the microarray samples of the replication cohort using the 52-gene outcome-predictive signature distinguished two patient groups with significant differences in TFS. We studied the pathways associated with TFS in each independent microarray cohort and identified decreased expression of “The costimulatory signal during T cell activation” Biocarta pathway and, in particular, the genes CD28, ICOS, LCK, and ITK, results confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A proportional hazards model, including the qRT-PCR expression of CD28, ICOS, LCK, and ITK along with patient’s age, gender, and percent predicted forced vital capacity (FVC%), demonstrated an area under the receiver operating characteristic curve of 78.5% at 2.4 months for death and lung transplant prediction in the replication cohort. To evaluate the potential cellular source of CD28, ICOS, LCK, and ITK expression, we analyzed and found significant correlation of these genes with the PBMC percentage of CD4+CD28+ T cells in the replication cohort. Our results suggest that CD28, ICOS, LCK, and ITK are potential outcome biomarkers in IPF and should be further evaluated for patient prioritization for lung transplantation and stratification in drug studies.
PMCID: PMC4175518  PMID: 24089408
3.  Conquering computational challenges of omics data and post-ENCODE paradigms 
Genome Biology  2013;14(8):310.
A report on the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 12th European Conference on Computational Biology (ECCB), held in Berlin, Germany, July 21-23, 2013.
PMCID: PMC4053832  PMID: 23998801
Epigenetic network; machine learning; next-generation sequencing; post-transcriptional modification; post-translational modification; regulation; statistic modeling; translational bioinformatics
4.  ‘N-of-1-pathways’ unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine 
The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery.
‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient.
Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03).
The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies.
PMCID: PMC4215042  PMID: 25301808
N-of-1; Single Subject Design; Precision Medicine; Personalized Medicine; Personal Transcriptome; Geneset
5.  In Silico cancer cell versus stroma cellularity index computed from species-specific human and mouse transcriptome of xenograft models: towards accurate stroma targeting therapy assessment 
BMC Medical Genomics  2014;7(Suppl 1):S2.
The current state of the art for measuring stromal response to targeted therapy requires burdensome and rate limiting quantitative histology. Transcriptome measures are increasingly affordable and provide an opportunity for developing a stromal versus cancer ratio in xenograft models. In these models, human cancer cells are transplanted into mouse host tissues (stroma) and together coevolve into a tumour microenvironment. However, profiling the mouse or human component separately remains problematic. Indeed, laser capture microdissection is labour intensive. Moreover, gene expression using commercial microarrays introduces significant and underreported cross-species hybridization errors that are commonly overlooked by biologists.
We developed a customized dual-species array, H&M array, and performed cross-species and species-specific hybridization measurements. We validated a new methodology for establishing the stroma vs cancer ratio using transcriptomic data.
In the biological validation of the H&M array, cross-species hybridization of human and mouse probes was significantly reduced (4.5 and 9.4 fold reduction, respectively; p < 2x10-16 for both, Mann-Whitney test). We confirmed the capability of the H&M array to determine the stromal to cancer cells ratio based on the estimation of cellularity index of mouse/human mRNA content in vitro. This new metrics enable to investigate more efficiently the stroma-cancer cell interactions (e.g. cellularity) bypassing labour intensive requirement and biases of laser capture microdissection.
These results provide the initial evidence of improved and cost-efficient analytics for the investigation of cancer cell microenvironment, using species-specificity arrays specifically designed for xenografts models.
PMCID: PMC4101338  PMID: 25079962
6.  Concordance of deregulated mechanisms unveiled in underpowered experiments: PTBP1 knockdown case study 
BMC Medical Genomics  2014;7(Suppl 1):S1.
Genome-wide transcriptome profiling generated by microarray and RNA-Seq often provides deregulated genes or pathways applicable only to larger cohort. On the other hand, individualized interpretation of transcriptomes is increasely pursued to improve diagnosis, prognosis, and patient treatment processes. Yet, robust and accurate methods based on a single paired-sample remain an unmet challenge.
"N-of-1-pathways" translates gene expression data profiles into mechanism-level profiles on single pairs of samples (one p-value per geneset). It relies on three principles: i) statistical universe is a single paired sample, which serves as its own control; ii) statistics can be derived from multiple gene expression measures that share common biological mechanisms assimilated to genesets; iii) semantic similarity metric takes into account inter-mechanisms' relationships to better assess commonality and differences, within and cross study-samples (e.g. patients, cell-lines, tissues, etc.), which helps the interpretation of the underpinning biology.
In the context of underpowered experiments, N-of-1-pathways predictions perform better or comparable to those of GSEA and Differentially Expressed Genes enrichment (DEG enrichment), within-and cross-datasets. N-of-1-pathways uncovered concordant PTBP1-dependent mechanisms across datasets (Odds-Ratios≥13, p-values≤1 × 10−5), such as RNA splicing and cell cycle. In addition, it unveils tissue-specific mechanisms of alternatively transcribed PTBP1-dependent genesets. Furthermore, we demonstrate that GSEA and DEG Enrichment preclude accurate analysis on single paired samples.
N-of-1-pathways enables robust and biologically relevant mechanism-level classifiers with small cohorts and one single paired samples that surpasses conventional methods. Further, it identifies unique sample/ patient mechanisms, a requirement for precision medicine.
PMCID: PMC4101571  PMID: 25079003
7.  Role of FAM18B in diabetic retinopathy 
Molecular Vision  2014;20:1146-1159.
Genome-wide association studies have suggested an association between a previously uncharacterized gene, FAM18B, and diabetic retinopathy. This study explores the role of FAM18B in diabetic retinopathy. An improved understanding of FAM18B could yield important insights into the pathogenesis of this sight-threatening complication of diabetes mellitus.
Postmortem human eyes were examined with immunohistochemistry and immunofluorescence for the presence of FAM18B. Expression of FAM18B in primary human retinal microvascular endothelial cells (HRMECs) exposed to hyperglycemia, vascular endothelial growth factor (VEGF), or advanced glycation end products (AGEs) was determined with quantitative reverse-transcription PCR (qRT-PCR) and/or western blot. The role of FAM18B in regulating human retinal microvascular endothelial cell viability, migration, and endothelial tube formation was determined following RNAi-mediated knockdown of FAM18B. The presence of FAM18B was determined with qRT-PCR in CD34+/VEGFR2+ mononuclear cells isolated from a cohort of 17 diabetic subjects with and without diabetic retinopathy.
Immunohistochemistry and immunofluorescence demonstrated the presence of FAM18B in the human retina with prominent vascular staining. Hyperglycemia, VEGF, and AGEs downregulated the expression of FAM18B in HRMECs. RNAi-mediated knockdown of FAM18B in HRMECs contributed to enhanced migration and tube formation as well as exacerbating the hyperglycemia-induced decrease in HRMEC viability. The enhanced migration, tube formation, and decrease in the viability of HRMECs as a result of FAM18B downregulation was reversed with pyrrolidine dithiocarbamate (PDTC), a specific nuclear factor-kappa B (NF-κB) inhibitor. CD34+/VEGFR2+ mononuclear cells from subjects with proliferative diabetic retinopathy demonstrated significantly reduced mRNA expression of FAM18B compared to diabetic subjects without retinopathy.
FAM18B is expressed in the retina. Diabetic culture conditions decrease the expression of FAM18B in HRMECs. The downregulation of FAM18B by siRNA in HRMECs results in enhanced migration and tube formation, but also exacerbates the hyperglycemia-induced decrease in HRMEC viability. The pathogenic changes observed in HRMECs as a result of FAM18B downregulation were reversed with PDTC, a specific NF-κB inhibitor. This study is the first to demonstrate a potential role for FAM18B in the pathogenesis of diabetic retinopathy.
PMCID: PMC4124103  PMID: 25221423
8.  Breakthroughs in genomics data integration for predicting clinical outcome 
Journal of biomedical informatics  2012;45(6):1199-1201.
PMCID: PMC3632294  PMID: 23117078
9.  The rise of translational bioinformatics 
Genome Biology  2012;13(8):319.
A report on the 20th International Conference on Intelligent Systems for Molecular Biology (ISMB), held at Long Beach, California, USA, July 15-17, 2012.
PMCID: PMC3491366  PMID: 22943369
Biomarkers; complex diseases; computational medicine; drug repositioning; mechanism classifiers; next-generation sequencing; off-target mechanisms; translational bioinformatics
11.  Curation-free biomodules mechanisms in prostate cancer predict recurrent disease 
BMC Medical Genomics  2013;6(Suppl 2):S4.
Gene expression-based prostate cancer gene signatures of poor prognosis are hampered by lack of gene feature reproducibility and a lack of understandability of their function. Molecular pathway-level mechanisms are intrinsically more stable and more robust than an individual gene. The Functional Analysis of Individual Microarray Expression (FAIME) we developed allows distinctive sample-level pathway measurements with utility for correlation with continuous phenotypes (e.g. survival). Further, we and others have previously demonstrated that pathway-level classifiers can be as accurate as gene-level classifiers using curated genesets that may implicitly comprise ascertainment biases (e.g. KEGG, GO). Here, we hypothesized that transformation of individual prostate cancer patient gene expression to pathway-level mechanisms derived from automated high throughput analyses of genomic datasets may also permit personalized pathway analysis and improve prognosis of recurrent disease.
Via FAIME, three independent prostate gene expression arrays with both normal and tumor samples were transformed into two distinct types of molecular pathway mechanisms: (i) the curated Gene Ontology (GO) and (ii) dynamic expression activity networks of cancer (Cancer Modules). FAIME-derived mechanisms for tumorigenesis were then identified and compared. Curated GO and computationally generated "Cancer Module" mechanisms overlap significantly and are enriched for known oncogenic deregulations and highlight potential areas of investigation. We further show in two independent datasets that these pathway-level tumorigenesis mechanisms can identify men who are more likely to develop recurrent prostate cancer (log-rank_p = 0.019).
Curation-free biomodules classification derived from congruent gene expression activation breaks from the paradigm of recapitulating the known curated pathway mechanism universe.
PMCID: PMC3654873  PMID: 23819917
12.  The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools 
Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties.
Materials and Methods
Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty.
We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with ‘abdominal pain’ and ‘gastroenteritis’ accounting for approximately 3.5%.
Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables.
Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The web portal provides insight in linking onerous diseases to the ICD-10 transition.
PMCID: PMC3721160  PMID: 23645552
ICD-9-CM; ICD-10-CM; billing complexity; transition to ICD-10-CM; networks; motifs
13.  Chronic intestinal inflammation induces stress response genes in commensal Escherichia coli 
Gastroenterology  2011;141(5):1842-51.e1-10.
Intestinal microbes induce homeostatic mucosal immune responses, but can also cause inappropriate immune activation in genetically susceptible hosts. While immune responses to bacterial products have been studied extensively, little is known about how intestinal inflammation affects the function of commensal luminal microbes.
Microarrays and real-time PCR were used to profile transcriptional changes in luminal bacteria from wild-type (WT) and IL-10−/− (KO) mice monoassociated with a non-pathogenic murine Escherichia coli isolate (NC101), which causes colitis in gnotobiotic KO mice. Colonic inflammation, innate and adaptive immune responses were measured in WT and KO mice monoassociated with mutant NC101 lacking selected upregulated genes and in KO mice co-colonized with mutant and parental NC101. Intracellular survival of bacteria within primary mouse macrophages and resultant TNF production was measured.
Significant upregulation of the stress response regulon, including the small heat shock proteins IbpA and IbpB that protect E. coli from oxidative stress, was observed in bacteria from KO mice with colitis compared to healthy WT controls. In KO mice, ibpAB expression resulted in reduced colonic histologic inflammation, secretion of IL-12/23p40 by colonic explant cultures, serologic reactivity to NC101 antigens, and IFNγ secretion by stimulated mesenteric lymph node cells. Infection of primary macrophages by bacteria expressing ibpAB was associated with decreased intracellular survival and attenuated TNF secretion.
Chronic intestinal inflammation causes functional alterations in gene expression of a commensal gut bacterium. Further studies of this component of the host-microbial dialogue may identify potential novel therapeutic targets to treat inflammatory bowel diseases.
PMCID: PMC3624969  PMID: 21726510
Inflammation; Bacteria; Gene Expression
14.  Genomic assessment of a multikinase inhibitor, sorafenib, in a rodent model of pulmonary hypertension 
Physiological genomics  2008;33(2):278-291.
Pulmonary hypertension (PH) and cancer pathology share growth factor- and MAPK stress-mediated signaling pathways resulting in endothelial and smooth muscle cell dysfunction and angioproliferative vasculopathy. In this study, we assessed sorafenib, an antineoplastic agent and inhibitor of multiple kinases important in angiogenesis [VEGF receptor (VEGFR)-1–3, PDGF receptor (PDGFR)-β, Raf-1 kinase] as a potential PH therapy. Two PH rat models were used: a conventional hypoxia-induced PH model and an augmented PH model combining dual VEGFR-1 and -2 inhibition (SU-5416, single 20 mg/kg injection) with hypoxia. In addition to normoxia-exposed control animals, four groups were maintained at 10% inspired O2 fraction for 3.5 wk (hypoxia/vehicle, hypoxia/SU-5416, hypoxia/sorafenib, and hypoxia/SU-5416/sorafenib). Compared with normoxic control animals, rats exposed to hypoxia/SU-5416 developed hemodynamic and histological evidence of severe PH while rats exposed to hypoxia alone displayed only mild elevations in hemodynamic values (pulmonary vascular and right ventricular pressures). Sorafenib treatment (daily gavage, 2.5 mg/kg) prevented hemodynamic changes and demonstrated dramatic attenuation of PH-associated vascular remodeling. Compared with normoxic control rats, expression profiling (Affymetrix platform) of lung RNA obtained from hypoxia [false discovery rate (FDR) 6.5%]- and hypoxia/SU-5416 (FDR 1.6%)-challenged rats yielded 1,019 and 465 differentially regulated genes (fold change >1.4), respectively. A novel molecular signature consisting of 38 differentially expressed genes between hypoxia/SU-5416 and hypoxia/SU-5416/sorafenib (FDR 6.7%) was validated by either real-time RT-PCR or immunoblotting. Finally, immunoblotting studies confirmed the upregulation of the MAPK cascade in both PH models, which was abolished by sorafenib. In summary, sorafenib represents a novel potential treatment for severe PH with the MAPK cascade a potential canonical target.
PMCID: PMC3616402  PMID: 18303084
microarrays; SU-5416; bioinformatics
15.  Use of consomic rats for genomic insights into ventilator-associated lung injury 
Increasing evidence supports the contribution of genetic influences on susceptibility/severity in acute lung injury (ALI), a devastating syndrome requiring mechanical ventilation with subsequent risk for ventilator-associated lung injury (VALI). To identify VALI candidate genes, we determined that Brown Norway (BN) and Dahl salt-sensitive (SS) rat strains were differentially sensitive to VALI (tidal volume of 20 ml/kg, 85 breaths/min, 2 h) defined by bronchoalveolar lavage (BAL) protein and leukocytes. We next exploited differential sensitivities and phenotyped both the VALI-sensitive BN and the VALI-resistant SS rat strains by expression profiling coupled to a bioinformatic-intense candidate gene approach (Significance Analysis of Microarrays, i.e., SAM). We identified 106 differentially expressed VALI genes representing gene ontologies such as “transcription” and “chemotaxis/cell motility.” We mapped the chromosomal location of the differentially expressed probe sets and selected consomic SS rats with single BN introgressions of chromosomes 2, 13, and 16 (based on the highest density of probe sets) while also choosing chromosome 20 (low probe sets density). VALI exposure of consomic rats with introgressions of BN chromosomes 13 and 16 resulted in significant increases in both BAL cells and protein (compared to parental SS strain), whereas introgression of BN chromosome 2 displayed a large increase only in BAL protein. Introgression of BN chromosome 20 had a minimal effect. These results suggest that genes residing on BN chromosomes 2, 13, and 16 confer increased sensitivity to high tidal volume ventilation. We speculate that the consomic-microarray-SAM approach is a time- and resource-efficient tool for the genetic dissection of complex diseases including VALI.
PMCID: PMC3616407  PMID: 17468131
rodent mechanical ventilation; consomics; bioinformatics; microarrays; candidate gene approach
16.  Integrating Governance of Research Informatics and Health Care IT Across an Enterprise: Experiences from the Trenches  
Advances in health information technology and biomedical informatics have laid the groundwork for significant improvements in healthcare and biomedical research. For instance, Electronic Health Records can help improve the delivery of evidence-based care, enhance quality, and contribute to discoveries and evidence generation. Despite this promise, there are many challenges to achieving the vision and missions of our healthcare and research enterprises. Given the challenges inherent in doing so, institutions are increasingly moving to establish dedicated leadership and governance models charged with designing, deploying and leveraging various information resources to advance research and advanced care activities at AHCs. Some institutions have even created a new leadership position to oversee such activities, such as the Chief Research Information Officer. This panel will include research informatics leaders discussing their experiences from the proverbial trenches as they work to operationalize such cross-mission governance models. Panelists will start by providing an overview their respective positions and environments, discuss their experiences, and share lessons learned through their work at the intersection of clinical and translational research informatics and Health IT.
PMCID: PMC3845750  PMID: 24303236
Despite thousands of reported studies unveiling gene-level signatures for complex diseases, few of these techniques work at the single-sample level with explicit underpinning of biological mechanisms. This presents both a critical dilemma in the field of personalized medicine as well as a plethora of opportunities for analysis of RNA-seq data. In this study, we hypothesize that the “Functional Analysis of Individual Microarray Expression” (FAIME) method we developed could be smoothly extended to RNA-seq data and unveil intrinsic underlying mechanism signatures across different scales of biological data for the same complex disease. Using publicly available RNA-seq data for gastric cancer, we confirmed the effectiveness of this method (i) to translate each sample transcriptome to pathway-scale scores, (ii) to predict deregulated pathways in gastric cancer against gold standards (FDR<5%, Precision=75%, Recall =92%), and (iii) to predict phenotypes in an independent dataset and expression platform (RNA-seq vs microarrays, Fisher Exact Test p<10−6). Measuring at a single-sample level, FAIME could differentiate cancer samples from normal ones; furthermore, it achieved comparative performance in identifying differentially expressed pathways as compared to state-of-the-art cross-sample methods. These results motivate future work on mechanism-level biomarker discovery predictive of diagnoses, treatment, and therapy.
PMCID: PMC3595401  PMID: 23424121
18.  People, organizational, and leadership factors impacting informatics support for clinical and translational research 
In recent years, there have been numerous initiatives undertaken to describe critical information needs related to the collection, management, analysis, and dissemination of data in support of biomedical research (J Investig Med 54:327-333, 2006); (J Am Med Inform Assoc 16:316–327, 2009); (Physiol Genomics 39:131-140, 2009); (J Am Med Inform Assoc 18:354–357, 2011). A common theme spanning such reports has been the importance of understanding and optimizing people, organizational, and leadership factors in order to achieve the promise of efficient and timely research (J Am Med Inform Assoc 15:283–289, 2008). With the emergence of clinical and translational science (CTS) as a national priority in the United States, and the corresponding growth in the scale and scope of CTS research programs, the acuity of such information needs continues to increase (JAMA 289:1278–1287, 2003); (N Engl J Med 353:1621–1623, 2005); (Sci Transl Med 3:90, 2011). At the same time, systematic evaluations of optimal people, organizational, and leadership factors that influence the provision of data, information, and knowledge management technologies and methods are notably lacking.
In response to the preceding gap in knowledge, we have conducted both: 1) a structured survey of domain experts at Academic Health Centers (AHCs); and 2) a subsequent thematic analysis of public-domain documentation provided by those same organizations. The results of these approaches were then used to identify critical factors that may influence access to informatics expertise and resources relevant to the CTS domain.
A total of 31 domain experts, spanning the Biomedical Informatics (BMI), Computer Science (CS), Information Science (IS), and Information Technology (IT) disciplines participated in a structured surveyprocess. At a high level, respondents identified notable differences in theaccess to BMI, CS, and IT expertise and services depending on the establishment of a formal BMI academic unit and the perceived relationship between BMI, CS, IS, and IT leaders. Subsequent thematic analysis of the aforementioned public domain documents demonstrated a discordance between perceived and reported integration across and between BMI, CS, IS, and IT programs and leaders with relevance to the CTS domain.
Differences in people, organization, and leadership factors do influence the effectiveness of CTS programs, particularly with regard to the ability to access and leverage BMI, CS, IS, and IT expertise and resources. Based on this finding, we believe that the development of a better understanding of how optimal BMI, CS, IS, and IT organizational structures and leadership models are designed and implemented is critical to both the advancement of CTS and ultimately, to improvements in the quality, safety, and effectiveness of healthcare.
PMCID: PMC3577661  PMID: 23388243
19.  Network models of genome-wide association studies uncover the topological centrality of protein interactions in complex diseases 
While genome-wide association studies (GWAS) of complex traits have revealed thousands of reproducible genetic associations to date, these loci collectively confer very little of the heritability of their respective diseases and, in general, have contributed little to our understanding the underlying disease biology. Physical protein interactions have been utilized to increase our understanding of human Mendelian disease loci but have yet to be fully exploited for complex traits.
We hypothesized that protein interaction modeling of GWAS findings could highlight important disease-associated loci and unveil the role of their network topology in the genetic architecture of diseases with complex inheritance.
Network modeling of proteins associated with the intragenic single nucleotide polymorphisms of the National Human Genome Research Institute catalog of complex trait GWAS revealed that complex trait associated loci are more likely to be hub and bottleneck genes in available, albeit incomplete, networks (OR=1.59, Fisher's exact test p<2.24×10−12). Network modeling also prioritized novel type 2 diabetes (T2D) genetic variations from the Finland–USA Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics and the Wellcome Trust GWAS data, and demonstrated the enrichment of hubs and bottlenecks in prioritized T2D GWAS genes. The potential biological relevance of the T2D hub and bottleneck genes was revealed by their increased number of first degree protein interactions with known T2D genes according to several independent sources (p<0.01, probability of being first interactors of known T2D genes).
Virtually all common diseases are complex human traits, and thus the topological centrality in protein networks of complex trait genes has implications in genetics, personal genomics, and therapy.
PMCID: PMC3721168  PMID: 23355459
Protein Interactions; SNPs; Complex Disease Inheritance; Adult Onset Diabetes; Crohn's Disease
20.  Oligo- and Polymetastatic Progression in Lung Metastasis(es) Patients Is Associated with Specific MicroRNAs 
PLoS ONE  2012;7(12):e50141.
Strategies to stage and treat cancer rely on a presumption of either localized or widespread metastatic disease. An intermediate state of metastasis termed oligometastasis(es) characterized by limited progression has been proposed. Oligometastases are amenable to treatment by surgical resection or radiotherapy.
We analyzed microRNA expression patterns from lung metastasis samples of patients with ≤5 initial metastases resected with curative intent.
Patients were stratified into subgroups based on their rate of metastatic progression. We prioritized microRNAs between patients with the highest and lowest rates of recurrence. We designated these as high rate of progression (HRP) and low rate of progression (LRP); the latter group included patients with no recurrences. The prioritized microRNAs distinguished HRP from LRP and were associated with rate of metastatic progression and survival in an independent validation dataset.
Oligo- and poly- metastasis are distinct entities at the clinical and molecular level.
PMCID: PMC3518475  PMID: 23251360
21.  Towards Mechanism Classifiers: Expression-anchored Gene Ontology Signature Predicts Clinical Outcome in Lung Adenocarcinoma Patients 
AMIA Annual Symposium Proceedings  2012;2012:1040-1049.
We aim to provide clinically applicable, reproducible, mechanistic interpretations of gene expression changes that lack in gene overlap among predictive gene-signatures. Using a method we recently developed, Functional Analysis of Individual Microarray Expression (FAIME), we provide evidence that Gene Ontology-anchored signatures (GO-signatures) show reliable prognosis in lung cancer. In order to demonstrate the biological congruence and reproducibility of FAIME-derived mechanism classifiers, we chose a disease where gene expression classifiers signatures alone had failed to significantly stratify a larger collection of samples and that exhibited poor or no genetic overlap. For each patient in the two lung adenocarcinoma studies, personalized FAIME-profiles of GO biological processes are generated from genome-wide expression profiles. For both training studies, GO-signatures significantly associated to patient mortality were identified (Prediction Analysis for Microarrays; three-fold cross-validation). These two GO-signatures could effectively stratify patients from an independent validation cohort into sub-groups that show significant differences in disease-free survival (log-rank test P=0.019; P=0.001). Importantly, significant mechanism overlaps assessed by information-theory similarity were detected between the two GO-signatures (Fischer Exact Test p=0.001). Hence, together with machine learning technologies, FAIME could be utilized to develop an ontology-driven and expression-anchored prognostic signature that is personalized for an individual patient.
PMCID: PMC3540430  PMID: 23304380
22.  A Sphingosine 1–Phosphate 1 Receptor Agonist Modulates Brain Death–Induced Neurogenic Pulmonary Injury 
Lung transplantation remains the only viable therapy for patients with end-stage lung disease. However, the full utilization of this strategy is severely compromised by a lack of donor lung availability. The vast majority of donor lungs available for transplantation are from individuals after brain death (BD). Unfortunately, the early autonomic storm that accompanies BD often results in neurogenic pulmonary edema (NPE), producing varying degrees of lung injury or leading to primary graft dysfunction after transplantation. We demonstrated that sphingosine 1–phosphate (S1P)/analogues, which are major barrier-enhancing agents, reduce vascular permeability via the S1P1 receptor, S1PR1. Because primary lung graft dysfunction is induced by lung vascular endothelial cell barrier dysfunction, we hypothesized that the S1PR1 agonist, SEW-2871, may attenuate NPE when administered to the donor shortly after BD. Significant lung injury was observed after BD, with increases of approximately 60% in bronchoalveolar lavage (BAL) total protein, cell counts, and lung tissue wet/dry (W/D) weight ratios. In contrast, rats receiving SEW-2871 (0.1 mg/kg) 15 minutes after BD and assessed after 4 hours exhibited significant lung protection (∼ 50% reduction, P = 0.01), as reflected by reduced BAL protein/albumin, cytokines, cellularity, and lung tissue wet/dry weight ratio. Microarray analysis at 4 hours revealed a global impact of both BD and SEW on lung gene expression, with a differential gene expression of enriched immune-response/inflammation pathways across all groups. Overall, SEW served to attenuate the BD-mediated up-regulation of gene expression. Two potential biomarkers, TNF and chemokine CC motif receptor-like 2, exhibited gene array dysregulation. We conclude that SEW-2871 significantly attenuates BD-induced lung injury, and may serve as a potential candidate to improve human donor availability.
PMCID: PMC3262681  PMID: 21617203
neurogenic pulmonary edema; lung injury; sphingosine 1–phosphate; sphingolipids; lung transplant donors
23.  Variants Affecting Exon Skipping Contribute to Complex Traits 
PLoS Genetics  2012;8(10):e1002998.
DNA variants that affect alternative splicing and the relative quantities of different gene transcripts have been shown to be risk alleles for some Mendelian diseases. However, for complex traits characterized by a low odds ratio for any single contributing variant, very few studies have investigated the contribution of splicing variants. The overarching goal of this study is to discover and characterize the role that variants affecting alternative splicing may play in the genetic etiology of complex traits, which include a significant number of the common human diseases. Specifically, we hypothesize that single nucleotide polymorphisms (SNPs) in splicing regulatory elements can be characterized in silico to identify variants affecting splicing, and that these variants may contribute to the etiology of complex diseases as well as the inter-individual variability in the ratios of alternative transcripts. We leverage high-throughput expression profiling to 1) experimentally validate our in silico predictions of skipped exons and 2) characterize the molecular role of intronic genetic variations in alternative splicing events in the context of complex human traits and diseases. We propose that intronic SNPs play a role as genetic regulators within splicing regulatory elements and show that their associated exon skipping events can affect protein domains and structure. We find that SNPs we would predict to affect exon skipping are enriched among the set of SNPs reported to be associated with complex human traits.
Author Summary
Alternative splicing is a common eukaryotic cellular mechanism that allows for the production of multiple proteins from one gene and occurs in 40%–90% of all human genes. Alternative splicing has been shown to be important for many critical biological processes, including development, evolution, and even psychological behavior. Additionally, alternative splicing has been associated with 15%–50% of human genetic diseases, including breast cancer; however, the precise mechanism by which genetic variations regulate this process remains to be fully elucidated. In this study, we develop an integrative approach that utilizes sequence-based analysis and genome-wide expression profiling to identify genetic variations that may affect alternative splicing. We also evaluate their enrichment among established disease-associated variations. Our study provides insights into the functionality of these variations and emphasizes their importance for complex human traits and diseases.
PMCID: PMC3486879  PMID: 23133393
24.  Deregulation of a Hox Protein Regulatory Network Spanning Prostate Cancer Initiation and Progression 
The aberrant activity of developmental pathways in prostate cancer may provide significant insight into predicting tumor initiation and progression, as well as identifying novel therapeutic targets. To this end, despite shared androgen-dependence and functional similarities to the prostate gland, seminal vesicle cancer is exceptionally rare.
Experimental Design
We conducted genomic pathway analyses comparing patient-matched normal prostate and seminal vesicle epithelial cells to identify novel pathways for tumor initiation and progression. Derived gene expression profiles were grouped into cancer biomodules using a protein–protein network algorithm to analyze their relationship to known oncogenes. Each resultant biomodule was assayed for its prognostic ability against publically available prostate cancer patient gene array datasets.
Analyses show that the embryonic developmental biomodule containing four homeobox gene family members (Meis1, Meis2, Pbx1, and HoxA9) detects a survival difference in a set of watchful-waiting patients (n = 172, P = 0.05), identify men who are more likely to recur biochemically postprostatectomy (n = 78, P = 0.02), correlate with Gleason score (r = 0.98, P = 0.02), and distinguish between normal prostate, primary tumor, and metastatic disease. In contrast to other cancer types, Meis1, Meis2, and Pbx1 expression is decreased in poor-prognosis tumors, implying that they function as tumor suppressor genes for prostate cancer. Immunohistochemical staining documents nuclear basal-epithelial and stromal Meis2 staining, with loss of Meis2 expression in prostate tumors.
These data implicate deregulation of the Hox protein cofactors Meis1, Meis2, and Pbx1 as serving a critical function to suppress prostate cancer initiation and progression.
PMCID: PMC3479663  PMID: 22723371
25.  Replication Analysis for Severe Diabetic Retinopathy 
The purpose of this study is to attempt to replicate the top single nucleotide polymorphism (SNP) associations from a previous genome-wide association study (GWAS) for the sight-threatening complications of diabetic retinopathy in an independent cohort of diabetic subjects from the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR).
This study included 469 type 1 diabetic, Caucasian subjects from WESDR. Cases (n = 208) were defined by prior laser treatment for either proliferative diabetic retinopathy or diabetic macular edema. Controls (n = 261) were all other subjects in the cohort. Three hundred eighty-nine SNPs were tested for association using the Illumina GoldenGate custom array. A retinopathy-only subanalysis was conducted in 437 subjects by removing those with end-stage renal disease. Evaluation for association between cases and controls was conducted by using chi-square tests. A combined analysis incorporated the results from WESDR with the prior GWAS.
No associations were significant at a genome-wide level. The analysis did identify SNPs that can be pursued in future replication studies. The top association was at rs4865047, an intronic SNP, in the gene CEP135 (P value 2.06 × 10−5). The top association from the subanalysis was at rs1902491 (P value 2.81 × 10−5), a SNP that sits upstream of the gene NPY2R.
This study nominates several novel genetic loci that may be associated with severe diabetic retinopathy. In order to confirm these findings, replication and extension in additional cohorts will be necessary as susceptibility alleles for diabetic retinopathy appear to be of modest effect.
In an attempt to replicate the top single nucleotide polymorphism associations from a previous genome-wide association, this study nominates genetic loci that may be associated with severe diabetic retinopathy.
PMCID: PMC3777289  PMID: 22427569

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