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Find video protocols related to scientific articles indexed in Pubmed.
Prothymosin alpha variants isolated from CD8+ T cells and cervicovaginal fluids suppress HIV replication through type I IFN induction.
J. Infect. Dis.
PUBLISHED: 11-19-2014
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Soluble factors from CD8(+) T cells and cervicovaginal mucosa of women are recognized as important in controlling HIV-1 infection and transmission. Previously, we have shown the strong anti-HIV activity of prothymosin ? (ProT?) derived from CD8(+) T cells. ProT? is a small acidic protein with wide cell distribution, to which several functions have been ascribed depending on its intracellular or extracellular localization. To date, activities of ProT? have been attributed to a single protein known as isoform 2. Here we report the isolation and identification of two new ProT? variants from CD8(+) T cells and cervicovaginal lavage with potent anti-HIV activity. The first is a splice variant of the ProT? gene known as isoform CRA_b and the second is the product of a ProT? gene thus far classified as a pseudogene 7. Native or recombinant ProT? variants potently restrict HIV replication in macrophages through the induction of type I interferon. The baseline expression of IFN responsive genes in primary human cervical tissues positively correlate with high levels of intracellular ProT? and the knockdown of ProT? variants by siRNA leads to down-regulation of IFN target genes. Overall these findings suggest that ProT? variants are innate immune mediators involved in immune surveillance.
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TGF? Receptor 1: An Immune Susceptibility Gene in HPV-Associated Cancer.
Cancer Res.
PUBLISHED: 10-01-2014
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Only a minority of those exposed to human papillomavirus (HPV) develop HPV-related cervical and oropharyngeal cancer. Because host immunity affects infection and progression to cancer, we tested the hypothesis that genetic variation in immune-related genes is a determinant of susceptibility to oropharyngeal cancer and other HPV-associated cancers by performing a multitier integrative computational analysis with oropharyngeal cancer data from a head and neck cancer genome-wide association study (GWAS). Independent analyses, including single-gene, gene-interconnectivity, protein-protein interaction, gene expression, and pathway analysis, identified immune genes and pathways significantly associated with oropharyngeal cancer. TGF?R1, which intersected all tiers of analysis and thus selected for validation, replicated significantly in the head and neck cancer GWAS limited to HPV-seropositive cases and an independent cervical cancer GWAS. The TGF?R1 containing p38-MAPK pathway was significantly associated with oropharyngeal cancer and cervical cancer, and TGF?R1 was overexpressed in oropharyngeal cancer, cervical cancer, and HPV(+) head and neck cancer tumors. These concordant analyses implicate TGF?R1 signaling as a process dysregulated across HPV-related cancers. This study demonstrates that genetic variation in immune-related genes is associated with susceptibility to oropharyngeal cancer and implicates TGF?R1/TGF? signaling in the development of both oropharyngeal cancer and cervical cancer. Better understanding of the immunogenetic basis of susceptibility to HPV-associated cancers may provide insight into host/virus interactions and immune processes dysregulated in the minority of HPV-exposed individuals who progress to cancer. Cancer Res; 74(23); 1-12. ©2014 AACR.
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MODMatcher: multi-omics data matcher for integrative genomic analysis.
PLoS Comput. Biol.
PUBLISHED: 08-14-2014
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Errors in sample annotation or labeling often occur in large-scale genetic or genomic studies and are difficult to avoid completely during data generation and management. For integrative genomic studies, it is critical to identify and correct these errors. Different types of genetic and genomic data are inter-connected by cis-regulations. On that basis, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors in multiple types of molecular data, which can be used in further integrative analysis. Our results indicate that inspection of sample annotation and labeling error is an indispensable data quality assurance step. Applied to a large lung genomic study, MODMatcher increased statistically significant genetic associations and genomic correlations by more than two-fold. In a simulation study, MODMatcher provided more robust results by using three types of omics data than two types of omics data. We further demonstrate that MODMatcher can be broadly applied to large genomic data sets containing multiple types of omics data, such as The Cancer Genome Atlas (TCGA) data sets.
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Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
Mol. Syst. Biol.
PUBLISHED: 08-01-2014
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Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017).
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lrgpr: interactive linear mixed model analysis of genome-wide association studies with composite hypothesis testing and regression diagnostics in R.
Bioinformatics
PUBLISHED: 07-16-2014
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The linear mixed model is the state-of-the-art method to account for the confounding effects of kinship and population structure in genome-wide association studies (GWAS). Current implementations test the effect of one or more genetic markers while including prespecified covariates such as sex. Here we develop an efficient implementation of the linear mixed model that allows composite hypothesis tests to consider genotype interactions with variables such as other genotypes, environment, sex or ancestry. Our R package, lrgpr, allows interactive model fitting and examination of regression diagnostics to facilitate exploratory data analysis in the context of the linear mixed model. By leveraging parallel and out-of-core computing for datasets too large to fit in main memory, lrgpr is applicable to large GWAS datasets and next-generation sequencing data.
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Downregulation of Carnitine Acyl-Carnitine Translocase by miRNAs 132 and 212 Amplifies Glucose-Stimulated Insulin Secretion.
Diabetes
PUBLISHED: 06-26-2014
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We previously demonstrated that micro-RNAs (miRNAs) 132 and 212 are differentially upregulated in response to obesity in two mouse strains that differ in their susceptibility to obesity-induced diabetes. Here we show the overexpression of miRNAs 132 and 212 enhances insulin secretion (IS) in response to glucose and other secretagogues including nonfuel stimuli. We determined that carnitine acyl-carnitine translocase (CACT; Slc25a20) is a direct target of these miRNAs. CACT is responsible for transporting long-chain acyl-carnitines into the mitochondria for ?-oxidation. Small interfering RNA-mediated knockdown of CACT in ?-cells led to the accumulation of fatty acyl-carnitines and enhanced IS. The addition of long-chain fatty acyl-carnitines promoted IS from rat insulinoma ?-cells (INS-1) as well as primary mouse islets. The effect on INS-1 cells was augmented in response to suppression of CACT. A nonhydrolyzable ether analog of palmitoyl-carnitine stimulated IS, showing that ?-oxidation of palmitoyl-carnitine is not required for its stimulation of IS. These studies establish a link between miRNA-dependent regulation of CACT and fatty acyl-carnitine-mediated regulation of IS.
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Lim domain binding 2: a key driver of transendothelial migration of leukocytes and atherosclerosis.
Arterioscler. Thromb. Vasc. Biol.
PUBLISHED: 06-12-2014
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Using a multi-tissue, genome-wide gene expression approach, we recently identified a gene module linked to the extent of human atherosclerosis. This atherosclerosis module was enriched with inherited risk for coronary and carotid artery disease (CAD) and overlapped with genes in the transendothelial migration of leukocyte (TEML) pathway. Among the atherosclerosis module genes, the transcription cofactor Lim domain binding 2 (LDB2) was the most connected in a CAD vascular wall regulatory gene network. Here, we used human genomics and atherosclerosis-prone mice to evaluate the possible role of LDB2 in TEML and atherosclerosis.
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The role of macromolecular damage in aging and age-related disease.
J. Gerontol. A Biol. Sci. Med. Sci.
PUBLISHED: 05-17-2014
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Several decades of research have shown that macromolecular damage increases with age and that damage to protein, DNA, lipids, and other macromolecular components appears to be important factors in specific age-related diseases. The strongest evidence that macromolecular damage is a causative factor in aging comes from studies using manipulations that increase life span. However, it is currently unclear whether damage to macromolecules plays a role in the actual processes of aging. In other words, is macromolecular damage driven by aging or is it that damage to a key molecular component directly causes aging?
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Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.
PLoS Genet.
PUBLISHED: 05-01-2014
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Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of the approach by re-analysing a gene expression dataset in 966 liver samples with a published meta-analysis of lipid traits including >100,000 individuals of European ancestry. Combining all lipid biomarkers, our re-analysis supported 26 out of 38 reported colocalisation results with eQTLs and identified 14 new colocalisation results, hence highlighting the value of a formal statistical test. In three cases of reported eQTL-lipid pairs (SYPL2, IFT172, TBKBP1) for which our analysis suggests that the eQTL pattern is not consistent with the lipid association, we identify alternative colocalisation results with SORT1, GCKR, and KPNB1, indicating that these genes are more likely to be causal in these genomic intervals. A key feature of the method is the ability to derive the output statistics from single SNP summary statistics, hence making it possible to perform systematic meta-analysis type comparisons across multiple GWAS datasets (implemented online at http://coloc.cs.ucl.ac.uk/coloc/). Our methodology provides information about candidate causal genes in associated intervals and has direct implications for the understanding of complex diseases as well as the design of drugs to target disease pathways.
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Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.
Vinicius Tragante, Michael R Barnes, Santhi K Ganesh, Matthew B Lanktree, Wei Guo, Nora Franceschini, Erin N Smith, Toby Johnson, Michael V Holmes, Sandosh Padmanabhan, Konrad J Karczewski, Berta Almoguera, John Barnard, Jens Baumert, Yen-Pei Christy Chang, Clara C Elbers, Martin Farrall, Mary E Fischer, Tom R Gaunt, Johannes M I H Gho, Christian Gieger, Anuj Goel, Yan Gong, Aaron Isaacs, Marcus E Kleber, Irene Mateo Leach, Caitrin W McDonough, Matthijs F L Meijs, Olle Melander, Christopher P Nelson, Ilja M Nolte, Nathan Pankratz, Tom S Price, Jonathan Shaffer, Sonia Shah, Maciej Tomaszewski, Peter J van der Most, Erik P A van Iperen, Judith M Vonk, Kate Witkowska, Caroline O L Wong, Li Zhang, Amber L Beitelshees, Gerald S Berenson, Deepak L Bhatt, Morris Brown, Amber Burt, Rhonda M Cooper-DeHoff, John M Connell, Karen J Cruickshanks, Sean P Curtis, George Davey-Smith, Christian Delles, Ron T Gansevoort, Xiuqing Guo, Shen Haiqing, Claire E Hastie, Marten H Hofker, G Kees Hovingh, Daniel S Kim, Susan A Kirkland, Barbara E Klein, Ronald Klein, Yun R Li, Steffi Maiwald, Christopher Newton-Cheh, Eoin T O'Brien, N Charlotte Onland-Moret, Walter Palmas, Afshin Parsa, Brenda W Penninx, Mary Pettinger, Ramachandran S Vasan, Jane E Ranchalis, Paul M Ridker, Lynda M Rose, Peter Sever, Daichi Shimbo, Laura Steele, Ronald P Stolk, Barbara Thorand, Mieke D Trip, Cornelia M van Duijn, W Monique Verschuren, Cisca Wijmenga, Sharon Wyatt, J Hunter Young, Aeilko H Zwinderman, Connie R Bezzina, Eric Boerwinkle, Juan P Casas, Mark J Caulfield, Aravinda Chakravarti, Daniel I Chasman, Karina W Davidson, Pieter A Doevendans, Anna F Dominiczak, Garret A FitzGerald, John G Gums, Myriam Fornage, Hakon Hakonarson, Indrani Halder, Hans L Hillege, Thomas Illig, Gail P Jarvik, Julie A Johnson, John J P Kastelein, Wolfgang Koenig, Meena Kumari, Winfried März, Sarah S Murray, Jeffery R O'Connell, Albertine J Oldehinkel, James S Pankow, Daniel J Rader, Susan Redline, Muredach P Reilly, Eric E Schadt, Kandice Kottke-Marchant, Harold Snieder, Michael Snyder, Alice V Stanton, Martin D Tobin, André G Uitterlinden, Pim van der Harst, Yvonne T van der Schouw, Nilesh J Samani, Hugh Watkins, Andrew D Johnson, Alex P Reiner, Xiaofeng Zhu, Paul I W de Bakker, Daniel Levy, Folkert W Asselbergs, Patricia B Munroe, Brendan J Keating.
Am. J. Hum. Genet.
PUBLISHED: 02-20-2014
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Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.
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Cyclin-dependent kinase inhibitor 2B regulates efferocytosis and atherosclerosis.
J. Clin. Invest.
PUBLISHED: 02-17-2014
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Genetic variation at the chromosome 9p21 risk locus promotes cardiovascular disease; however, it is unclear how or which proteins encoded at this locus contribute to disease. We have previously demonstrated that loss of one candidate gene at this locus, cyclin-dependent kinase inhibitor 2B (Cdkn2b), in mice promotes vascular SMC apoptosis and aneurysm progression. Here, we investigated the role of Cdnk2b in atherogenesis and found that in a mouse model of atherosclerosis, deletion of Cdnk2b promoted advanced development of atherosclerotic plaques composed of large necrotic cores. Furthermore, human carriers of the 9p21 risk allele had reduced expression of CDKN2B in atherosclerotic plaques, which was associated with impaired expression of calreticulin, a ligand required for activation of engulfment receptors on phagocytic cells. As a result of decreased calreticulin, CDKN2B-deficient apoptotic bodies were resistant to efferocytosis and not efficiently cleared by neighboring macrophages. These uncleared SMCs elicited a series of proatherogenic juxtacrine responses associated with increased foam cell formation and inflammatory cytokine elaboration. The addition of exogenous calreticulin reversed defects associated with loss of Cdkn2b and normalized engulfment of Cdkn2b-deficient cells. Together, these data suggest that loss of CDKN2B promotes atherosclerosis by increasing the size and complexity of the lipid-laden necrotic core through impaired efferocytosis.
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Causal effects of body mass index on cardiometabolic traits and events: a Mendelian randomization analysis.
Am. J. Hum. Genet.
PUBLISHED: 01-23-2014
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Elevated body mass index (BMI) associates with cardiometabolic traits on observational analysis, yet the underlying causal relationships remain unclear. We conducted Mendelian randomization analyses by using a genetic score (GS) comprising 14 BMI-associated SNPs from a recent discovery analysis to investigate the causal role of BMI in cardiometabolic traits and events. We used eight population-based cohorts, including 34,538 European-descent individuals (4,407 type 2 diabetes (T2D), 6,073 coronary heart disease (CHD), and 3,813 stroke cases). A 1 kg/m(2) genetically elevated BMI increased fasting glucose (0.18 mmol/l; 95% confidence interval (CI) = 0.12-0.24), fasting insulin (8.5%; 95% CI = 5.9-11.1), interleukin-6 (7.0%; 95% CI = 4.0-10.1), and systolic blood pressure (0.70 mmHg; 95% CI = 0.24-1.16) and reduced high-density lipoprotein cholesterol (-0.02 mmol/l; 95% CI = -0.03 to -0.01) and low-density lipoprotein cholesterol (LDL-C; -0.04 mmol/l; 95% CI = -0.07 to -0.01). Observational and causal estimates were directionally concordant, except for LDL-C. A 1 kg/m(2) genetically elevated BMI increased the odds of T2D (odds ratio [OR] = 1.27; 95% CI = 1.18-1.36) but did not alter risk of CHD (OR 1.01; 95% CI = 0.94-1.08) or stroke (OR = 1.03; 95% CI = 0.95-1.12). A meta-analysis incorporating published studies reporting 27,465 CHD events in 219,423 individuals yielded a pooled OR of 1.04 (95% CI = 0.97-1.12) per 1 kg/m(2) increase in BMI. In conclusion, we identified causal effects of BMI on several cardiometabolic traits; however, whether BMI causally impacts CHD risk requires further evidence.
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Unifying immunology with informatics and multiscale biology.
Nat. Immunol.
PUBLISHED: 01-23-2014
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The immune system is a highly complex and dynamic system. Historically, the most common scientific and clinical practice has been to evaluate its individual components. This kind of approach cannot always expose the interconnecting pathways that control immune-system responses and does not reveal how the immune system works across multiple biological systems and scales. High-throughput technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune-system function. New integrative analyses can help synthesize and transform these data into valuable biological insight. Here we review some of the computational analysis tools for high-dimensional data and how they can be applied to immunology.
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Autotransporters but not pAA are critical for rabbit colonization by Shiga toxin-producing Escherichia coli O104:H4.
Nat Commun
PUBLISHED: 01-22-2014
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The outbreak of diarrhoea and haemolytic uraemic syndrome that occurred in Germany in 2011 was caused by a Shiga toxin-producing enteroaggregative Escherichia coli (EAEC) strain. The strain was classified as EAEC owing to the presence of a plasmid (pAA) that mediates a characteristic pattern of aggregative adherence on cultured cells, the defining feature of EAEC that has classically been associated with virulence. Here we describe an infant rabbit-based model of intestinal colonization and diarrhoea caused by the outbreak strain, which we use to decipher the factors that mediate the pathogen's virulence. Shiga toxin is the key factor required for diarrhoea. Unexpectedly, we observe that pAA is dispensable for intestinal colonization and development of intestinal pathology. Instead, chromosome-encoded autotransporters are critical for robust colonization and diarrhoeal disease in this model. Our findings suggest that conventional wisdom linking aggregative adherence to EAEC intestinal colonization is false for at least a subset of strains.
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Dissection of immune gene networks in primary melanoma tumors critical for antitumor surveillance of patients with stage II-III resectable disease.
J. Invest. Dermatol.
PUBLISHED: 01-14-2014
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Patients with resected stage II-III cutaneous melanomas remain at high risk for metastasis and death. Biomarker development has been limited by the challenge of isolating high-quality RNA for transcriptome-wide profiling from formalin-fixed and paraffin-embedded (FFPE) primary tumor specimens. Using NanoString technology, RNA from 40 stage II-III FFPE primary melanomas was analyzed and a 53-immune-gene panel predictive of non-progression (area under the curve (AUC)=0.920) was defined. The signature predicted disease-specific survival (DSS P<0.001) and recurrence-free survival (RFS P<0.001). CD2, the most differentially expressed gene in the training set, also predicted non-progression (P<0.001). Using publicly available microarray data from 46 primary human melanomas (GSE15605), a coexpression module enriched for the 53-gene panel was then identified using unbiased methods. A Bayesian network of signaling pathways based on this data identified driver genes. Finally, the proposed 53-gene panel was confirmed in an independent test population of 48 patients (AUC=0.787). The gene signature was an independent predictor of non-progression (P<0.001), RFS (P<0.001), and DSS (P=0.024) in the test population. The identified driver genes are potential therapeutic targets, and the 53-gene panel should be tested for clinical application using a larger data set annotated on the basis of prospectively gathered data.
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Analytical validation of whole exome and whole genome sequencing for clinical applications.
BMC Med Genomics
PUBLISHED: 01-08-2014
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Whole exome and genome sequencing (WES/WGS) is now routinely offered as a clinical test by a growing number of laboratories. As part of the test design process each laboratory must determine the performance characteristics of the platform, test and informatics pipeline. This report documents one such characterization of WES/WGS.
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Personalized ovarian cancer disease surveillance and detection of candidate therapeutic drug target in circulating tumor DNA.
Neoplasia
PUBLISHED: 01-02-2014
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Retrospective studies have demonstrated that nearly 50% of patients with ovarian cancer with normal cancer antigen 125 (CA125) levels have persistent disease; however, prospectively distinguishing between patients is currently impossible. Here, we demonstrate that for one patient, with the first reported fibroblast growth factor receptor 2 (FGFR2) fusion transcript in ovarian cancer, circulating tumor DNA (ctDNA) is a more sensitive and specific biomarker than CA125, and it can also inform on a candidate therapeutic. For a 4-year period, during which the patient underwent primary debulking surgery and chemotherapy, tumor recurrences, and multiple chemotherapeutic regimens, blood samples were longitudinally collected and stored. Whereas postsurgical CA125 levels were elevated only three times for 28 measurements, the FGFR2 fusion ctDNA biomarker was readily detectable by quantitative real-time reverse transcription-polymerase chain reaction (PCR) in all of these same blood samples and in the tumor recurrences. Given the persistence of the FGFR2 fusion, we treated tumor cells derived from this patient and others with the FGFR2 inhibitor BGJ398. Only tumor cells derived from this patient were sensitive to FGFR2 inhibitor treatment. Using the same methodologic approach, we demonstrate in a second patient with a different fusion that PCR and agarose gel electrophoresis can also be used to identify tumor-specific DNA in the circulation. Taken together, we demonstrate that a relatively inexpensive, PCR-based ctDNA surveillance assay can outperform CA125 in identifying occult disease.
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Biomarkers for combat-related PTSD: focus on molecular networks from high-dimensional data.
Eur J Psychotraumatol
PUBLISHED: 01-01-2014
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Posttraumatic stress disorder (PTSD) and other deployment-related outcomes originate from a complex interplay between constellations of changes in DNA, environmental traumatic exposures, and other biological risk factors. These factors affect not only individual genes or bio-molecules but also the entire biological networks that in turn increase or decrease the risk of illness or affect illness severity. This review focuses on recent developments in the field of systems biology which use multidimensional data to discover biological networks affected by combat exposure and post-deployment disease states. By integrating large-scale, high-dimensional molecular, physiological, clinical, and behavioral data, the molecular networks that directly respond to perturbations that can lead to PTSD can be identified and causally associated with PTSD, providing a path to identify key drivers. Reprogrammed neural progenitor cells from fibroblasts from PTSD patients could be established as an in vitro assay for high throughput screening of approved drugs to determine which drugs reverse the abnormal expression of the pathogenic biomarkers or neuronal properties.
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Characterization of the human ESC transcriptome by hybrid sequencing.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 11-26-2013
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Although transcriptional and posttranscriptional events are detected in RNA-Seq data from second-generation sequencing, full-length mRNA isoforms are not captured. On the other hand, third-generation sequencing, which yields much longer reads, has current limitations of lower raw accuracy and throughput. Here, we combine second-generation sequencing and third-generation sequencing with a custom-designed method for isoform identification and quantification to generate a high-confidence isoform dataset for human embryonic stem cells (hESCs). We report 8,084 RefSeq-annotated isoforms detected as full-length and an additional 5,459 isoforms predicted through statistical inference. Over one-third of these are novel isoforms, including 273 RNAs from gene loci that have not previously been identified. Further characterization of the novel loci indicates that a subset is expressed in pluripotent cells but not in diverse fetal and adult tissues; moreover, their reduced expression perturbs the network of pluripotency-associated genes. Results suggest that gene identification, even in well-characterized human cell lines and tissues, is likely far from complete.
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Disease-related growth factor and embryonic signaling pathways modulate an enhancer of TCF21 expression at the 6q23.2 coronary heart disease locus.
PLoS Genet.
PUBLISHED: 07-01-2013
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Coronary heart disease (CHD) is the leading cause of mortality in both developed and developing countries worldwide. Genome-wide association studies (GWAS) have now identified 46 independent susceptibility loci for CHD, however, the biological and disease-relevant mechanisms for these associations remain elusive. The large-scale meta-analysis of GWAS recently identified in Caucasians a CHD-associated locus at chromosome 6q23.2, a region containing the transcription factor TCF21 gene. TCF21 (Capsulin/Pod1/Epicardin) is a member of the basic-helix-loop-helix (bHLH) transcription factor family, and regulates cell fate decisions and differentiation in the developing coronary vasculature. Herein, we characterize a cis-regulatory mechanism by which the lead polymorphism rs12190287 disrupts an atypical activator protein 1 (AP-1) element, as demonstrated by allele-specific transcriptional regulation, transcription factor binding, and chromatin organization, leading to altered TCF21 expression. Further, this element is shown to mediate signaling through platelet-derived growth factor receptor beta (PDGFR-?) and Wilms tumor 1 (WT1) pathways. A second disease allele identified in East Asians also appears to disrupt an AP-1-like element. Thus, both disease-related growth factor and embryonic signaling pathways may regulate CHD risk through two independent alleles at TCF21.
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Improving breast cancer survival analysis through competition-based multidimensional modeling.
PLoS Comput. Biol.
PUBLISHED: 05-01-2013
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Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.
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Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimers disease.
Cell
PUBLISHED: 03-22-2013
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The genetics of complex disease produce alterations in the molecular interactions of cellular pathways whose collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimers disease (LOAD), we constructed gene-regulatory networks in 1,647 postmortem brain tissues from LOAD patients and nondemented subjects, and we demonstrate that LOAD reconfigures specific portions of the molecular interaction structure. Through an integrative network-based approach, we rank-ordered these network structures for relevance to LOAD pathology, highlighting an immune- and microglia-specific module that is dominated by genes involved in pathogen phagocytosis, contains TYROBP as a key regulator, and is upregulated in LOAD. Mouse microglia cells overexpressing intact or truncated TYROBP revealed expression changes that significantly overlapped the human brain TYROBP network. Thus the causal network structure is a useful predictor of response to gene perturbations and presents a framework to test models of disease mechanisms underlying LOAD.
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A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.
Keri L Monda, Gary K Chen, Kira C Taylor, Cameron Palmer, Todd L Edwards, Leslie A Lange, Maggie C Y Ng, Adebowale A Adeyemo, Matthew A Allison, Lawrence F Bielak, Guanjie Chen, Mariaelisa Graff, Marguerite R Irvin, Suhn K Rhie, Guo Li, Yongmei Liu, Youfang Liu, Yingchang Lu, Michael A Nalls, Yan V Sun, Mary K Wojczynski, Lisa R Yanek, Melinda C Aldrich, Adeyinka Ademola, Christopher I Amos, Elisa V Bandera, Cathryn H Bock, Angela Britton, Ulrich Broeckel, Quiyin Cai, Neil E Caporaso, Chris S Carlson, John Carpten, Graham Casey, Wei-Min Chen, Fang Chen, Yii-Der I Chen, Charleston W K Chiang, Gerhard A Coetzee, Ellen Demerath, Sandra L Deming-Halverson, Ryan W Driver, Patricia Dubbert, Mary F Feitosa, Ye Feng, Barry I Freedman, Elizabeth M Gillanders, Omri Gottesman, Xiuqing Guo, Talin Haritunians, Tamara Harris, Curtis C Harris, Anselm J M Hennis, Dena G Hernandez, Lorna H McNeill, Timothy D Howard, Barbara V Howard, Virginia J Howard, Karen C Johnson, Sun J Kang, Brendan J Keating, Suzanne Kolb, Lewis H Kuller, Abdullah Kutlar, Carl D Langefeld, Guillaume Lettre, Kurt Lohman, Vaneet Lotay, Helen Lyon, JoAnn E Manson, William Maixner, Yan A Meng, Kristine R Monroe, Imran Morhason-Bello, Adam B Murphy, Josyf C Mychaleckyj, Rajiv Nadukuru, Katherine L Nathanson, Uma Nayak, Amidou N'Diaye, Barbara Nemesure, Suh-Yuh Wu, M Cristina Leske, Christine Neslund-Dudas, Marian Neuhouser, Sarah Nyante, Heather Ochs-Balcom, Adesola Ogunniyi, Temidayo O Ogundiran, Oladosu Ojengbede, Olufunmilayo I Olopade, Julie R Palmer, Edward A Ruiz-Narváez, Nicholette D Palmer, Michael F Press, Evandine Rampersaud, Laura J Rasmussen-Torvik, Jorge L Rodriguez-Gil, Babatunde Salako, Eric E Schadt, Ann G Schwartz, Daniel A Shriner, David Siscovick, Shad B Smith, Sylvia Wassertheil-Smoller, Elizabeth K Speliotes, Margaret R Spitz, Lara Sucheston, Herman Taylor, Bamidele O Tayo, Margaret A Tucker, David J Van Den Berg, Digna R Velez Edwards, Zhaoming Wang, John K Wiencke, Thomas W Winkler, John S Witte, Margaret Wrensch, Xifeng Wu, James J Yang, Albert M Levin, Taylor R Young, Neil A Zakai, Mary Cushman, Krista A Zanetti, Jing Hua Zhao, Wei Zhao, Yonglan Zheng, Jie Zhou, Regina G Ziegler, Joseph M Zmuda, Jyotika K Fernandes, Gary S Gilkeson, Diane L Kamen, Kelly J Hunt, Ida J Spruill, Christine B Ambrosone, Stefan Ambs, Donna K Arnett, Larry Atwood, Diane M Becker, Sonja I Berndt, Leslie Bernstein, William J Blot, Ingrid B Borecki, Erwin P Bottinger, Donald W Bowden, Gregory Burke, Stephen J Chanock, Richard S Cooper, Jingzhong Ding, David Duggan, Michele K Evans, Caroline Fox, W Timothy Garvey, Jonathan P Bradfield, Hakon Hakonarson, Struan F A Grant, Ann Hsing, Lisa Chu, Jennifer J Hu, Dezheng Huo, Sue A Ingles, Esther M John, Joanne M Jordan, Edmond K Kabagambe, Sharon L R Kardia, Rick A Kittles, Phyllis J Goodman, Eric A Klein, Laurence N Kolonel, Loic Le Marchand, Simin Liu, Barbara McKnight, Robert C Millikan, Thomas H Mosley, Badri Padhukasahasram, L Keoki Williams, Sanjay R Patel, Ulrike Peters, Curtis A Pettaway, Patricia A Peyser, Bruce M Psaty, Susan Redline, Charles N Rotimi, Benjamin A Rybicki, Michèle M Sale, Pamela J Schreiner, Lisa B Signorello, Andrew B Singleton, Janet L Stanford, Sara S Strom, Michael J Thun, Mara Vitolins, Wei Zheng, Jason H Moore, Scott M Williams, Shamika Ketkar, Xiaofeng Zhu, Alan B Zonderman, , Charles Kooperberg, George J Papanicolaou, Brian E Henderson, Alex P Reiner, Joel N Hirschhorn, Ruth J F Loos, Kari E North, Christopher A Haiman.
Nat. Genet.
PUBLISHED: 03-18-2013
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Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.
Sonja I Berndt, Stefan Gustafsson, Reedik Mägi, Andrea Ganna, Eleanor Wheeler, Mary F Feitosa, Anne E Justice, Keri L Monda, Damien C Croteau-Chonka, Felix R Day, Tonu Esko, Tove Fall, Teresa Ferreira, Davide Gentilini, Anne U Jackson, Jian'an Luan, Joshua C Randall, Sailaja Vedantam, Cristen J Willer, Thomas W Winkler, Andrew R Wood, Tsegaselassie Workalemahu, Yi-Juan Hu, Sang Hong Lee, Liming Liang, Dan-Yu Lin, Josine L Min, Benjamin M Neale, Gudmar Thorleifsson, Jian Yang, Eva Albrecht, Najaf Amin, Jennifer L Bragg-Gresham, Gemma Cadby, Martin den Heijer, Niina Eklund, Krista Fischer, Anuj Goel, Jouke-Jan Hottenga, Jennifer E Huffman, Ivonne Jarick, Asa Johansson, Toby Johnson, Stavroula Kanoni, Marcus E Kleber, Inke R König, Kati Kristiansson, Zoltan Kutalik, Claudia Lamina, Cécile Lecoeur, Guo Li, Massimo Mangino, Wendy L McArdle, Carolina Medina-Gomez, Martina Müller-Nurasyid, Julius S Ngwa, Ilja M Nolte, Lavinia Paternoster, Sonali Pechlivanis, Markus Perola, Marjolein J Peters, Michael Preuss, Lynda M Rose, Jianxin Shi, Dmitry Shungin, Albert Vernon Smith, Rona J Strawbridge, Ida Surakka, Alexander Teumer, Mieke D Trip, Jonathan Tyrer, Jana V van Vliet-Ostaptchouk, Liesbeth Vandenput, Lindsay L Waite, Jing Hua Zhao, Devin Absher, Folkert W Asselbergs, Mustafa Atalay, Antony P Attwood, Anthony J Balmforth, Hanneke Basart, John Beilby, Lori L Bonnycastle, Paolo Brambilla, Marcel Bruinenberg, Harry Campbell, Daniel I Chasman, Peter S Chines, Francis S Collins, John M Connell, William O Cookson, Ulf de Faire, Femmie de Vegt, Mariano Dei, Maria Dimitriou, Sarah Edkins, Karol Estrada, David M Evans, Martin Farrall, Marco M Ferrario, Jean Ferrières, Lude Franke, Francesca Frau, Pablo V Gejman, Harald Grallert, Henrik Grönberg, Vilmundur Gudnason, Alistair S Hall, Per Hall, Anna-Liisa Hartikainen, Caroline Hayward, Nancy L Heard-Costa, Andrew C Heath, Johannes Hebebrand, Georg Homuth, Frank B Hu, Sarah E Hunt, Elina Hyppönen, Carlos Iribarren, Kevin B Jacobs, John-Olov Jansson, Antti Jula, Mika Kähönen, Sekar Kathiresan, Frank Kee, Kay-Tee Khaw, Mika Kivimäki, Wolfgang Koenig, Aldi T Kraja, Meena Kumari, Kari Kuulasmaa, Johanna Kuusisto, Jaana H Laitinen, Timo A Lakka, Claudia Langenberg, Lenore J Launer, Lars Lind, Jaana Lindström, Jianjun Liu, Antonio Liuzzi, Marja-Liisa Lokki, Mattias Lorentzon, Pamela A Madden, Patrik K Magnusson, Paolo Manunta, Diana Marek, Winfried März, Irene Mateo Leach, Barbara McKnight, Sarah E Medland, Evelin Mihailov, Lili Milani, Grant W Montgomery, Vincent Mooser, Thomas W Mühleisen, Patricia B Munroe, Arthur W Musk, Narisu Narisu, Gerjan Navis, George Nicholson, Ellen A Nohr, Ken K Ong, Ben A Oostra, Colin N A Palmer, Aarno Palotie, John F Peden, Nancy Pedersen, Annette Peters, Ozren Polašek, Anneli Pouta, Peter P Pramstaller, Inga Prokopenko, Carolin Pütter, Aparna Radhakrishnan, Olli Raitakari, Augusto Rendon, Fernando Rivadeneira, Igor Rudan, Timo E Saaristo, Jennifer G Sambrook, Alan R Sanders, Serena Sanna, Jouko Saramies, Sabine Schipf, Stefan Schreiber, Heribert Schunkert, So-Youn Shin, Stefano Signorini, Juha Sinisalo, Boris Skrobek, Nicole Soranzo, Alena Stančáková, Klaus Stark, Jonathan C Stephens, Kathleen Stirrups, Ronald P Stolk, Michael Stumvoll, Amy J Swift, Eirini V Theodoraki, Barbara Thorand, David-Alexandre Trégouët, Elena Tremoli, Melanie M van der Klauw, Joyce B J van Meurs, Sita H Vermeulen, Jorma Viikari, Jarmo Virtamo, Veronique Vitart, Gérard Waeber, Zhaoming Wang, Elisabeth Widén, Sarah H Wild, Gonneke Willemsen, Bernhard R Winkelmann, Jacqueline C M Witteman, Bruce H R Wolffenbuttel, Andrew Wong, Alan F Wright, M Carola Zillikens, Philippe Amouyel, Bernhard O Boehm, Eric Boerwinkle, Dorret I Boomsma, Mark J Caulfield, Stephen J Chanock, L Adrienne Cupples, Daniele Cusi, George V Dedoussis, Jeanette Erdmann, Johan G Eriksson, Paul W Franks, Philippe Froguel, Christian Gieger, Ulf Gyllensten, Anders Hamsten, Tamara B Harris, Christian Hengstenberg, Andrew A Hicks, Aroon Hingorani, Anke Hinney, Albert Hofman, Kees G Hovingh, Kristian Hveem, Thomas Illig, Marjo-Riitta Järvelin, Karl-Heinz Jöckel, Sirkka M Keinanen-Kiukaanniemi, Lambertus A Kiemeney, Diana Kuh, Markku Laakso, Terho Lehtimäki, Douglas F Levinson, Nicholas G Martin, Andres Metspalu, Andrew D Morris, Markku S Nieminen, Inger Njølstad, Claes Ohlsson, Albertine J Oldehinkel, Willem H Ouwehand, Lyle J Palmer, Brenda Penninx, Chris Power, Michael A Province, Bruce M Psaty, Lu Qi, Rainer Rauramaa, Paul M Ridker, Samuli Ripatti, Veikko Salomaa, Nilesh J Samani, Harold Snieder, Thorkild I A Sørensen, Timothy D Spector, Kari Stefansson, Anke Tönjes, Jaakko Tuomilehto, André G Uitterlinden, Matti Uusitupa, Pim van der Harst, Peter Vollenweider, Henri Wallaschofski, Nicholas J Wareham, Hugh Watkins, H-Erich Wichmann, James F Wilson, Gonçalo R Abecasis, Themistocles L Assimes, Inês Barroso, Michael Boehnke, Ingrid B Borecki, Panos Deloukas, Caroline S Fox, Timothy Frayling, Leif C Groop, Talin Haritunian, Iris M Heid, David Hunter, Robert C Kaplan, Fredrik Karpe, Miriam F Moffatt, Karen L Mohlke, Jeffrey R O'Connell, Yudi Pawitan, Eric E Schadt, David Schlessinger, Valgerdur Steinthorsdottir, David P Strachan, Unnur Thorsteinsdottir, Cornelia M van Duijn, Peter M Visscher, Anna Maria Di Blasio, Joel N Hirschhorn, Cecilia M Lindgren, Andrew P Morris, David Meyre, André Scherag, Mark I McCarthy, Elizabeth K Speliotes, Kari E North, Ruth J F Loos, Erik Ingelsson.
Nat. Genet.
PUBLISHED: 03-14-2013
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Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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Detecting DNA modifications from SMRT sequencing data by modeling sequence context dependence of polymerase kinetic.
PLoS Comput. Biol.
PUBLISHED: 01-08-2013
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DNA modifications such as methylation and DNA damage can play critical regulatory roles in biological systems. Single molecule, real time (SMRT) sequencing technology generates DNA sequences as well as DNA polymerase kinetic information that can be used for the direct detection of DNA modifications. We demonstrate that local sequence context has a strong impact on DNA polymerase kinetics in the neighborhood of the incorporation site during the DNA synthesis reaction, allowing for the possibility of estimating the expected kinetic rate of the enzyme at the incorporation site using kinetic rate information collected from existing SMRT sequencing data (historical data) covering the same local sequence contexts of interest. We develop an Empirical Bayesian hierarchical model for incorporating historical data. Our results show that the model could greatly increase DNA modification detection accuracy, and reduce requirement of control data coverage. For some DNA modifications that have a strong signal, a control sample is not even needed by using historical data as alternative to control. Thus, sequencing costs can be greatly reduced by using the model. We implemented the model in a R package named seqPatch, which is available at https://github.com/zhixingfeng/seqPatch.
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Loci influencing blood pressure identified using a cardiovascular gene-centric array.
Santhi K Ganesh, Vinicius Tragante, Wei Guo, Yiran Guo, Matthew B Lanktree, Erin N Smith, Toby Johnson, Berta Almoguera Castillo, John Barnard, Jens Baumert, Yen-Pei Christy Chang, Clara C Elbers, Martin Farrall, Mary E Fischer, Nora Franceschini, Tom R Gaunt, Johannes M I H Gho, Christian Gieger, Yan Gong, Aaron Isaacs, Marcus E Kleber, Irene Mateo Leach, Caitrin W McDonough, Matthijs F L Meijs, Olle Mellander, Cliona M Molony, Ilja M Nolte, Sandosh Padmanabhan, Tom S Price, Ramakrishnan Rajagopalan, Jonathan Shaffer, Sonia Shah, Haiqing Shen, Nicole Soranzo, Peter J van der Most, Erik P A van Iperen, Jessica van Setten, Jessic A Van Setten, Judith M Vonk, Li Zhang, Amber L Beitelshees, Gerald S Berenson, Deepak L Bhatt, Jolanda M A Boer, Eric Boerwinkle, Ben Burkley, Amber Burt, Aravinda Chakravarti, Wei Chen, Rhonda M Cooper-DeHoff, Sean P Curtis, Albert Dreisbach, David Duggan, Georg B Ehret, Richard R Fabsitz, Myriam Fornage, Ervin Fox, Clement E Furlong, Ron T Gansevoort, Marten H Hofker, G Kees Hovingh, Susan A Kirkland, Kandice Kottke-Marchant, Abdullah Kutlar, Andrea Z LaCroix, Taimour Y Langaee, Yun R Li, Honghuang Lin, Kiang Liu, Steffi Maiwald, Rainer Malik, , Gurunathan Murugesan, Christopher Newton-Cheh, Jeffery R O'Connell, N Charlotte Onland-Moret, Willem H Ouwehand, Walter Palmas, Brenda W Penninx, Carl J Pepine, Mary Pettinger, Joseph F Polak, Vasan S Ramachandran, Jane Ranchalis, Susan Redline, Paul M Ridker, Lynda M Rose, Hubert Scharnag, Nicholas J Schork, Daichi Shimbo, Alan R Shuldiner, Sathanur R Srinivasan, Ronald P Stolk, Herman A Taylor, Barbara Thorand, Mieke D Trip, Cornelia M van Duijn, W Monique Verschuren, Cisca Wijmenga, Bernhard R Winkelmann, Sharon Wyatt, J Hunter Young, Bernhard O Boehm, Mark J Caulfield, Daniel I Chasman, Karina W Davidson, Pieter A Doevendans, Garret A FitzGerald, John G Gums, Hakon Hakonarson, Hans L Hillege, Thomas Illig, Gail P Jarvik, Julie A Johnson, John J P Kastelein, Wolfgang Koenig, Winfried März, Braxton D Mitchell, Sarah S Murray, Albertine J Oldehinkel, Daniel J Rader, Muredach P Reilly, Alex P Reiner, Eric E Schadt, Roy L Silverstein, Harold Snieder, Alice V Stanton, André G Uitterlinden, Pim van der Harst, Yvonne T van der Schouw, Nilesh J Samani, Andrew D Johnson, Patricia B Munroe, Paul I W de Bakker, Xiaofeng Zhu, Daniel Levy, Brendan J Keating, Folkert W Asselbergs.
Hum. Mol. Genet.
PUBLISHED: 01-08-2013
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Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ?50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ?2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
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Comprehensive methylome characterization of Mycoplasma genitalium and Mycoplasma pneumoniae at single-base resolution.
PLoS Genet.
PUBLISHED: 01-03-2013
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In the bacterial world, methylation is most commonly associated with restriction-modification systems that provide a defense mechanism against invading foreign genomes. In addition, it is known that methylation plays functionally important roles, including timing of DNA replication, chromosome partitioning, DNA repair, and regulation of gene expression. However, full DNA methylome analyses are scarce due to a lack of a simple methodology for rapid and sensitive detection of common epigenetic marks (ie N(6)-methyladenine (6 mA) and N(4)-methylcytosine (4 mC)), in these organisms. Here, we use Single-Molecule Real-Time (SMRT) sequencing to determine the methylomes of two related human pathogen species, Mycoplasma genitalium G-37 and Mycoplasma pneumoniae M129, with single-base resolution. Our analysis identified two new methylation motifs not previously described in bacteria: a widespread 6 mA methylation motif common to both bacteria (5-CTAT-3), as well as a more complex Type I m6A sequence motif in M. pneumoniae (5-GAN(7)TAY-3/3-CTN(7)ATR-5). We identify the methyltransferase responsible for the common motif and suggest the one involved in M. pneumoniae only. Analysis of the distribution of methylation sites across the genome of M. pneumoniae suggests a potential role for methylation in regulating the cell cycle, as well as in regulation of gene expression. To our knowledge, this is one of the first direct methylome profiling studies with single-base resolution from a bacterial organism.
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Informed decision-making among students analyzing their personal genomes on a whole genome sequencing course: a longitudinal cohort study.
Genome Med
PUBLISHED: 01-01-2013
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Multiple laboratories now offer clinical whole genome sequencing (WGS). We anticipate WGS becoming routinely used in research and clinical practice. Many institutions are exploring how best to educate genetics and other professionals about WGS. Providing students on WGS courses with the option to analyze their own genome sequence is one strategy that might enhance students engagement and motivation to learn about personal genomes. However, if this option is presented to students, it is vital they make informed decisions, do not feel pressured into analyzing their own genomes by their course directors or peers, and feel free to analyze a third-party genome if they prefer. We therefore developed a 26-hour introductory genomics course in part to help students make informed decisions about whether to receive personal WGS data in a subsequent advanced genomics course. In the advanced course, they had the option to receive their own personal genome data, or an anonymous genome, at no financial cost to them. Our primary aims were to examine whether students made informed decisions regarding analyzing their personal genomes, and whether there was evidence that the introductory course enabled the students to make a more informed decision.
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Fine-mapping, gene expression and splicing analysis of the disease associated LRRK2 locus.
PLoS ONE
PUBLISHED: 01-01-2013
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Association studies have identified several signals at the LRRK2 locus for Parkinsons disease (PD), Crohns disease (CD) and leprosy. However, little is known about the molecular mechanisms mediating these effects. To further characterize this locus, we fine-mapped the risk association in 5,802 PD and 5,556 controls using a dense genotyping array (ImmunoChip). Using samples from 134 post-mortem control adult human brains (UK Human Brain Expression Consortium), where up to ten brain regions were available per individual, we studied the regional variation, splicing and regulation of LRRK2. We found convincing evidence for a common variant PD association located outside of the LRRK2 protein coding region (rs117762348, A>G, P?=?2.56×10(-8), case/control MAF 0.083/0.074, odds ratio 0.86 for the minor allele with 95% confidence interval [0.80-0.91]). We show that mRNA expression levels are highest in cortical regions and lowest in cerebellum. We find an exon quantitative trait locus (QTL) in brain samples that localizes to exons 32-33 and investigate the molecular basis of this eQTL using RNA-Seq data in n?=?8 brain samples. The genotype underlying this eQTL is in strong linkage disequilibrium with the CD associated non-synonymous SNP rs3761863 (M2397T). We found two additional QTLs in liver and monocyte samples but none of these explained the common variant PD association at rs117762348. Our results characterize the LRRK2 locus, and highlight the importance and difficulties of fine-mapping and integration of multiple datasets to delineate pathogenic variants and thus develop an understanding of disease mechanisms.
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Integrative genomics strategies to elucidate the complexity of drug response.
Pharmacogenomics
PUBLISHED: 11-29-2011
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Pharmacogenomic investigation from both genome-wide association studies and experiments focused on candidate loci involved in drug mechanism and metabolism has yielded a substantial and increasing list of robust genetic effects on drug therapy in humans. At the same time, reasonably comprehensive molecular data such as gene expression, proteomic and metabolomic data are now available for collections of hundreds to thousands of individuals. If these data are structured in a statistically robust and computationally tractable way, such as a network model, they can aid in the analysis of new pharmacogenomics studies by suggesting novel hypotheses for the regulation of genes involved in drug metabolism and response. Similarly, hypotheses taken from these same models can direct genome-wide association studies by focusing the genome-wide association studies analysis on a number of specific hypotheses informed by the relationships customarily seen between a genes expression or protein activity and genetic variation at a particular locus. Network models based on other sorts of systematic biological data such as cell-based surveys of drug effect on gene expression and mining of literature and electronic medical records for associations between clinical and molecular phenotypes also promise similar utility. Although surely primitive in comparison with what will be developed, these model-based approaches to leveraging the increasing volume of data generated in the course of patient care and medical research nevertheless suggest a huge opportunity to improve our understanding of biological systems involved in pharmacogenomics and apply them to questions of medical relevance.
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Construction of regulatory networks using expression time-series data of a genotyped population.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 11-14-2011
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The inference of regulatory and biochemical networks from large-scale genomics data is a basic problem in molecular biology. The goal is to generate testable hypotheses of gene-to-gene influences and subsequently to design bench experiments to confirm these network predictions. Coexpression of genes in large-scale gene-expression data implies coregulation and potential gene-gene interactions, but provide little information about the direction of influences. Here, we use both time-series data and genetics data to infer directionality of edges in regulatory networks: time-series data contain information about the chronological order of regulatory events and genetics data allow us to map DNA variations to variations at the RNA level. We generate microarray data measuring time-dependent gene-expression levels in 95 genotyped yeast segregants subjected to a drug perturbation. We develop a Bayesian model averaging regression algorithm that incorporates external information from diverse data types to infer regulatory networks from the time-series and genetics data. Our algorithm is capable of generating feedback loops. We show that our inferred network recovers existing and novel regulatory relationships. Following network construction, we generate independent microarray data on selected deletion mutants to prospectively test network predictions. We demonstrate the potential of our network to discover de novo transcription-factor binding sites. Applying our construction method to previously published data demonstrates that our method is competitive with leading network construction algorithms in the literature.
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Identification of causal genes, networks, and transcriptional regulators of REM sleep and wake.
Sleep
PUBLISHED: 11-02-2011
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Sleep-wake traits are well-known to be under substantial genetic control, but the specific genes and gene networks underlying primary sleep-wake traits have largely eluded identification using conventional approaches, especially in mammals. Thus, the aim of this study was to use systems genetics and statistical approaches to uncover the genetic networks underlying 2 primary sleep traits in the mouse: 24-h duration of REM sleep and wake.
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Systems genetics of susceptibility to obesity-induced diabetes in mice.
Physiol. Genomics
PUBLISHED: 10-18-2011
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Inbred strains of mice are strikingly different in susceptibility to obesity-driven diabetes. For instance, deficiency in leptin receptor (db/db) leads to hyperphagia and obesity in both C57BL/6 and DBA/2 mice, but only on the DBA/2 background do the mice develop beta-cell loss leading to severe diabetes, while C57BL/6 mice are relatively resistant. To further investigate the genetic factors predisposing to diabetes, we have studied leptin receptor-deficient offspring of an F2 cross between C57BL/6J (db/+) males and DBA/2J females. The results show that the genetics of diabetes susceptibility are enormously complex and a number of quantitative trait loci (QTL) contributing to diabetes-related traits were identified, notably on chromosomes 4, 6, 7, 9, 10, 11, 12, and 19. The Chr. 4 locus is likely due to a disruption of the Zfp69 gene in C57BL/6J mice. To identify candidate genes and to model coexpression networks, we performed global expression array analysis in livers of the F2 mice. Expression QTL (eQTL) were identified and used to prioritize candidate genes at clinical trait QTL. In several cases, clusters of eQTLs colocalized with clinical trait QTLs, suggesting a common genetic basis. We constructed coexpression networks for both 5 and 12 wk old mice and identified several modules significantly associated with clinical traits. One module in 12 wk old mice was associated with several measures of hepatic fat content as well as with other lipid- and diabetes-related traits. These results add to the understanding of the complex genetic interactions contributing to obesity-induced diabetes.
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Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany.
N. Engl. J. Med.
PUBLISHED: 07-27-2011
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A large outbreak of diarrhea and the hemolytic-uremic syndrome caused by an unusual serotype of Shiga-toxin-producing Escherichia coli (O104:H4) began in Germany in May 2011. As of July 22, a large number of cases of diarrhea caused by Shiga-toxin-producing E. coli have been reported--3167 without the hemolytic-uremic syndrome (16 deaths) and 908 with the hemolytic-uremic syndrome (34 deaths)--indicating that this strain is notably more virulent than most of the Shiga-toxin-producing E. coli strains. Preliminary genetic characterization of the outbreak strain suggested that, unlike most of these strains, it should be classified within the enteroaggregative pathotype of E. coli.
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A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort.
Genome Res.
PUBLISHED: 05-20-2011
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To map the genetics of gene expression in metabolically relevant tissues and investigate the diversity of expression SNPs (eSNPs) in multiple tissues from the same individual, we collected four tissues from approximately 1000 patients undergoing Roux-en-Y gastric bypass (RYGB) and clinical traits associated with their weight loss and co-morbidities. We then performed high-throughput genotyping and gene expression profiling and carried out a genome-wide association analyses for more than 100,000 gene expression traits representing four metabolically relevant tissues: liver, omental adipose, subcutaneous adipose, and stomach. We successfully identified 24,531 eSNPs corresponding to about 10,000 distinct genes. This represents the greatest number of eSNPs identified to our knowledge by any study to date and the first study to identify eSNPs from stomach tissue. We then demonstrate how these eSNPs provide a high-quality disease map for each tissue in morbidly obese patients to not only inform genetic associations identified in this cohort, but in previously published genome-wide association studies as well. These data can aid in elucidating the key networks associated with morbid obesity, response to RYGB, and disease as a whole.
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A systems genetic analysis of high density lipoprotein metabolism and network preservation across mouse models.
Biochim. Biophys. Acta
PUBLISHED: 05-05-2011
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We report a systems genetic analysis of high density lipoprotein (HDL) levels in an F2 intercross between inbred strains CAST/EiJ and C57BL/6J. We previously showed that there are dramatic differences in HDL metabolism in a cross between these strains, and we now report co-expression network analysis of HDL that integrates global expression data from liver and adipose with relevant metabolic traits. Using data from a total of 293 F2 intercross mice, we constructed weighted gene co-expression networks and identified modules (subnetworks) associated with HDL and clinical traits. These were examined for genes implicated in HDL levels based on large human genome-wide associations studies (GWAS) and examined with respect to conservation between tissue and sexes in a total of 9 data sets. We identify genes that are consistently ranked high by association with HDL across the 9 data sets. We focus in particular on two genes, Wfdc2 and Hdac3, that are located in close proximity to HDL QTL peaks where causal testing indicates that they may affect HDL. Our results provide a rich resource for studies of complex metabolic interactions involving HDL. This article is part of a Special Issue entitled Advances in High Density Lipoprotein Formation and Metabolism: A Tribute to John F. Oram (1945-2010).
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The arrestin domain-containing 3 protein regulates body mass and energy expenditure.
Cell Metab.
PUBLISHED: 04-29-2011
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A human genome-wide linkage scan for obesity identified a linkage peak on chromosome 5q13-15. Positional cloning revealed an association of a rare haplotype to high body-mass index (BMI) in males but not females. The risk locus contains a single gene, "arrestin domain-containing 3" (ARRDC3), an uncharacterized ?-arrestin. Inactivating Arrdc3 in mice led to a striking resistance to obesity, with greater impact on male mice. Mice with decreased ARRDC3 levels were protected from obesity due to increased energy expenditure through increased activity levels and increased thermogenesis of both brown and white adipose tissues. ARRDC3 interacted directly with ?-adrenergic receptors, and loss of ARRDC3 increased the response to ?-adrenergic stimulation in isolated adipose tissue. These results demonstrate that ARRDC3 is a gender-sensitive regulator of obesity and energy expenditure and reveal a surprising diversity for arrestin family protein functions.
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Dissecting cis regulation of gene expression in human metabolic tissues.
PLoS ONE
PUBLISHED: 04-18-2011
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Complex diseases such as obesity and type II diabetes can result from a failure in multiple organ systems including the central nervous system and tissues involved in partitioning and disposal of nutrients. Studying the genetics of gene expression in tissues that are involved in the development of these diseases can provide insights into how these tissues interact within the context of disease. Expression quantitative trait locus (eQTL) studies identify mRNA expression changes linked to proximal genetic signals (cis eQTLs) that have been shown to affect disease. Given the high impact of recent eQTL studies, it is important to understand what role sample size and environment plays in identification of cis eQTLs. Here we show in a genotyped obese human population that the number of cis eQTLs obey precise scaling laws as a function of sample size in three profiled tissues, i.e. omental adipose, subcutaneous adipose and liver. Also, we show that genes (or transcripts) with cis eQTL associations detected in a small population are detected at approximately 90% rate in the largest population available for our study, indicating that genes with strong cis acting regulatory elements can be identified with relatively high confidence in smaller populations. However, by increasing the sample size we allow for better detection of weaker and more distantly located cis-regulatory elements. Yet, we determined that the number of tissue specific cis eQTLs saturates in a modestly sized cohort while the number of cis eQTLs common to all tissues fails to reach a maximum value. Understanding the power laws that govern the number and specificity of eQTLs detected in different tissues, will allow a better utilization of genetics of gene expression to inform the molecular mechanism underlying complex disease traits.
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Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques.
Mol. Syst. Biol.
PUBLISHED: 04-08-2011
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Integrative genomics and genetics approaches have proven to be a useful tool in elucidating the complex relationships often found in gene regulatory networks. More importantly, a number of studies have provided the necessary experimental evidence confirming the validity of the causal relationships inferred using such an approach. By integrating messenger RNA (mRNA) expression data with microRNA (miRNA) (i.e. small non-coding RNA with well-established regulatory roles in a myriad of biological processes) expression data, we show how integrative genomics approaches can be used to characterize the role played by approximately a third of registered mouse miRNAs within the context of a liver gene regulatory network. Our analysis reveals that the transcript abundances of miRNAs are subject to regulatory control by many more loci than previously observed for mRNA expression. Moreover, our results indicate that miRNAs exist as highly connected hub-nodes and function as key sensors within the transcriptional network. We also provide evidence supporting the hypothesis that miRNAs can act cooperatively or redundantly to regulate a given pathway and that miRNAs play a subtle role by dampening expression of their target gene through the use of feedback loops.
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COSINE: COndition-SpecIfic sub-NEtwork identification using a global optimization method.
Bioinformatics
PUBLISHED: 03-16-2011
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The identification of condition specific sub-networks from gene expression profiles has important biological applications, ranging from the selection of disease-related biomarkers to the discovery of pathway alterations across different phenotypes. Although many methods exist for extracting these sub-networks, very few existing approaches simultaneously consider both the differential expression of individual genes and the differential correlation of gene pairs, losing potentially valuable information in the data.
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Clinicopathologic and gene expression parameters predict liver cancer prognosis.
BMC Cancer
PUBLISHED: 03-15-2011
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The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model.
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Inferring causal genomic alterations in breast cancer using gene expression data.
BMC Syst Biol
PUBLISHED: 03-14-2011
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One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies.
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Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.
John C Chambers, Weihua Zhang, Joban Sehmi, Xinzhong Li, Mark N Wass, Pim van der Harst, Hilma Holm, Serena Sanna, Maryam Kavousi, Sebastian E Baumeister, Lachlan J Coin, Guohong Deng, Christian Gieger, Nancy L Heard-Costa, Jouke-Jan Hottenga, Brigitte Kühnel, Vinod Kumar, Vasiliki Lagou, Liming Liang, Jian'an Luan, Pedro Marques Vidal, Irene Mateo Leach, Paul F O'Reilly, John F Peden, Nilufer Rahmioglu, Pasi Soininen, Elizabeth K Speliotes, Xin Yuan, Gudmar Thorleifsson, Behrooz Z Alizadeh, Larry D Atwood, Ingrid B Borecki, Morris J Brown, Pimphen Charoen, Francesco Cucca, Debashish Das, Eco J C de Geus, Anna L Dixon, Angela Döring, Georg Ehret, Gudmundur I Eyjolfsson, Martin Farrall, Nita G Forouhi, Nele Friedrich, Wolfram Goessling, Daniel F Gudbjartsson, Tamara B Harris, Anna-Liisa Hartikainen, Simon Heath, Gideon M Hirschfield, Albert Hofman, Georg Homuth, Elina Hyppönen, Harry L A Janssen, Toby Johnson, Antti J Kangas, Ido P Kema, Jens P Kühn, Sandra Lai, Mark Lathrop, Markus M Lerch, Yun Li, T Jake Liang, Jing-Ping Lin, Ruth J F Loos, Nicholas G Martin, Miriam F Moffatt, Grant W Montgomery, Patricia B Munroe, Kiran Musunuru, Yusuke Nakamura, Christopher J O'Donnell, Isleifur Olafsson, Brenda W Penninx, Anneli Pouta, Bram P Prins, Inga Prokopenko, Ralf Puls, Aimo Ruokonen, Markku J Savolainen, David Schlessinger, Jeoffrey N L Schouten, Udo Seedorf, Srijita Sen-Chowdhry, Katherine A Siminovitch, Johannes H Smit, Timothy D Spector, Wenting Tan, Tanya M Teslovich, Taru Tukiainen, André G Uitterlinden, Melanie M van der Klauw, Ramachandran S Vasan, Chris Wallace, Henri Wallaschofski, H-Erich Wichmann, Gonneke Willemsen, Peter Würtz, Chun Xu, Laura M Yerges-Armstrong, , Gonçalo R Abecasis, Kourosh R Ahmadi, Dorret I Boomsma, Mark Caulfield, William O Cookson, Cornelia M van Duijn, Philippe Froguel, Koichi Matsuda, Mark I McCarthy, Christa Meisinger, Vincent Mooser, Kirsi H Pietiläinen, Gunter Schumann, Harold Snieder, Michael J E Sternberg, Ronald P Stolk, Howard C Thomas, Unnur Thorsteinsdottir, Manuela Uda, Gérard Waeber, Nicholas J Wareham, Dawn M Waterworth, Hugh Watkins, John B Whitfield, Jacqueline C M Witteman, Bruce H R Wolffenbuttel, Caroline S Fox, Mika Ala-Korpela, Kari Stefansson, Peter Vollenweider, Henry Völzke, Eric E Schadt, James Scott, Marjo-Riitta Järvelin, Paul Elliott, Jaspal S Kooner.
Nat. Genet.
PUBLISHED: 03-08-2011
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Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
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Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.
Heribert Schunkert, Inke R König, Sekar Kathiresan, Muredach P Reilly, Themistocles L Assimes, Hilma Holm, Michael Preuss, Alexandre F R Stewart, Maja Barbalic, Christian Gieger, Devin Absher, Zouhair Aherrahrou, Hooman Allayee, David Altshuler, Sonia S Anand, Karl Andersen, Jeffrey L Anderson, Diego Ardissino, Stephen G Ball, Anthony J Balmforth, Timothy A Barnes, Diane M Becker, Lewis C Becker, Klaus Berger, Joshua C Bis, S Matthijs Boekholdt, Eric Boerwinkle, Peter S Braund, Morris J Brown, Mary Susan Burnett, Ian Buysschaert, , John F Carlquist, Li Chen, Sven Cichon, Veryan Codd, Robert W Davies, George Dedoussis, Abbas Dehghan, Serkalem Demissie, Joseph M Devaney, Patrick Diemert, Ron Do, Angela Doering, Sandra Eifert, Nour Eddine El Mokhtari, Stephen G Ellis, Roberto Elosua, James C Engert, Stephen E Epstein, Ulf de Faire, Marcus Fischer, Aaron R Folsom, Jennifer Freyer, Bruna Gigante, Domenico Girelli, Solveig Gretarsdottir, Vilmundur Gudnason, Jeffrey R Gulcher, Eran Halperin, Naomi Hammond, Stanley L Hazen, Albert Hofman, Benjamin D Horne, Thomas Illig, Carlos Iribarren, Gregory T Jones, J Wouter Jukema, Michael A Kaiser, Lee M Kaplan, John J P Kastelein, Kay-Tee Khaw, Joshua W Knowles, Genovefa Kolovou, Augustine Kong, Reijo Laaksonen, Diether Lambrechts, Karin Leander, Guillaume Lettre, Mingyao Li, Wolfgang Lieb, Christina Loley, Andrew J Lotery, Pier M Mannucci, Seraya Maouche, Nicola Martinelli, Pascal P McKeown, Christa Meisinger, Thomas Meitinger, Olle Melander, Pier Angelica Merlini, Vincent Mooser, Thomas Morgan, Thomas W Mühleisen, Joseph B Muhlestein, Thomas Münzel, Kiran Musunuru, Janja Nahrstaedt, Christopher P Nelson, Markus M Nöthen, Oliviero Olivieri, Riyaz S Patel, Chris C Patterson, Annette Peters, Flora Peyvandi, Liming Qu, Arshed A Quyyumi, Daniel J Rader, Loukianos S Rallidis, Catherine Rice, Frits R Rosendaal, Diana Rubin, Veikko Salomaa, M Lourdes Sampietro, Manj S Sandhu, Eric Schadt, Arne Schäfer, Arne Schillert, Stefan Schreiber, Jürgen Schrezenmeir, Stephen M Schwartz, David S Siscovick, Mohan Sivananthan, Suthesh Sivapalaratnam, Albert Smith, Tamara B Smith, Jaapjan D Snoep, Nicole Soranzo, John A Spertus, Klaus Stark, Kathy Stirrups, Monika Stoll, W H Wilson Tang, Stephanie Tennstedt, Gudmundur Thorgeirsson, Gudmar Thorleifsson, Maciej Tomaszewski, André G Uitterlinden, Andre M van Rij, Benjamin F Voight, Nick J Wareham, George A Wells, H-Erich Wichmann, Philipp S Wild, Christina Willenborg, Jaqueline C M Witteman, Benjamin J Wright, Shu Ye, Tanja Zeller, Andreas Ziegler, Francois Cambien, Alison H Goodall, L Adrienne Cupples, Thomas Quertermous, Winfried März, Christian Hengstenberg, Stefan Blankenberg, Willem H Ouwehand, Alistair S Hall, Panos Deloukas, John R Thompson, Kari Stefansson, Robert Roberts, Unnur Thorsteinsdottir, Christopher J O'Donnell, Ruth McPherson, Jeanette Erdmann, Nilesh J Samani.
Nat. Genet.
PUBLISHED: 02-10-2011
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We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10?? and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.
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Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits.
PLoS Genet.
PUBLISHED: 02-02-2011
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Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (?26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n?=?880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ?2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10(-8)) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT-assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.
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Systematic detection of polygenic cis-regulatory evolution.
PLoS Genet.
PUBLISHED: 01-26-2011
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The idea that most morphological adaptations can be attributed to changes in the cis-regulation of gene expression levels has been gaining increasing acceptance, despite the fact that only a handful of such cases have so far been demonstrated. Moreover, because each of these cases involves only one gene, we lack any understanding of how natural selection may act on cis-regulation across entire pathways or networks. Here we apply a genome-wide test for selection on cis-regulation to two subspecies of the mouse Mus musculus. We find evidence for lineage-specific selection at over 100 genes involved in diverse processes such as growth, locomotion, and memory. These gene sets implicate candidate genes that are supported by both quantitative trait loci and a validated causality-testing framework, and they predict a number of phenotypic differences, which we confirm in all four cases tested. Our results suggest that gene expression adaptation is widespread and that these adaptations can be highly polygenic, involving cis-regulatory changes at numerous functionally related genes. These coordinated adaptations may contribute to divergence in a wide range of morphological, physiological, and behavioral phenotypes.
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Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile.
Tuomas O Kilpeläinen, M Carola Zillikens, Alena Stančáková, Francis M Finucane, Janina S Ried, Claudia Langenberg, Weihua Zhang, Jacques S Beckmann, Jian'an Luan, Liesbeth Vandenput, Unnur Styrkarsdottir, Yanhua Zhou, Albert Vernon Smith, Jing-Hua Zhao, Najaf Amin, Sailaja Vedantam, So-Youn Shin, Talin Haritunians, Mao Fu, Mary F Feitosa, Meena Kumari, Bjarni V Halldórsson, Emmi Tikkanen, Massimo Mangino, Caroline Hayward, Ci Song, Alice M Arnold, Yurii S Aulchenko, Ben A Oostra, Harry Campbell, L Adrienne Cupples, Kathryn E Davis, Angela Döring, Gudny Eiriksdottir, Karol Estrada, José Manuel Fernández-Real, Melissa Garcia, Christian Gieger, Nicole L Glazer, Candace Guiducci, Albert Hofman, Steve E Humphries, Bo Isomaa, Leonie C Jacobs, Antti Jula, David Karasik, Magnus K Karlsson, Kay-Tee Khaw, Lauren J Kim, Mika Kivimäki, Norman Klopp, Brigitte Kühnel, Johanna Kuusisto, Yongmei Liu, Osten Ljunggren, Mattias Lorentzon, Robert N Luben, Barbara McKnight, Dan Mellström, Braxton D Mitchell, Vincent Mooser, Jose María Moreno, Satu Mannisto, Jeffery R O'Connell, Laura Pascoe, Leena Peltonen, Belén Peral, Markus Perola, Bruce M Psaty, Veikko Salomaa, David B Savage, Robert K Semple, Tatjana Skarić-Jurić, Gunnar Sigurdsson, Kijoung S Song, Timothy D Spector, Ann-Christine Syvänen, Philippa J Talmud, Gudmar Thorleifsson, Unnur Thorsteinsdottir, André G Uitterlinden, Cornelia M van Duijn, Antonio Vidal-Puig, Sarah H Wild, Alan F Wright, Deborah J Clegg, Eric Schadt, James F Wilson, Igor Rudan, Samuli Ripatti, Ingrid B Borecki, Alan R Shuldiner, Erik Ingelsson, John-Olov Jansson, Robert C Kaplan, Vilmundur Gudnason, Tamara B Harris, Leif Groop, Douglas P Kiel, Fernando Rivadeneira, Mark Walker, Inês Barroso, Peter Vollenweider, Gérard Waeber, John C Chambers, Jaspal S Kooner, Nicole Soranzo, Joel N Hirschhorn, Kari Stefansson, H-Erich Wichmann, Claes Ohlsson, Stephen O'Rahilly, Nicholas J Wareham, Elizabeth K Speliotes, Caroline S Fox, Markku Laakso, Ruth J F Loos.
Nat. Genet.
PUBLISHED: 01-18-2011
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Genome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ?2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10(-6)) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10(-26)) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10(-11)) and one near SPRY2 (P = 3 × 10(-8)). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat-decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.
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Identification of a common variant in the TFR2 gene implicated in the physiological regulation of serum iron levels.
Hum. Mol. Genet.
PUBLISHED: 12-28-2010
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The genetic determinants of variation in iron status are actively sought, but remain incompletely understood. Meta-analysis of two genome-wide association (GWA) studies and replication in three independent cohorts was performed to identify genetic loci associated in the general population with serum levels of iron and markers of iron status, including transferrin, ferritin, soluble transferrin receptor (sTfR) and sTfR-ferritin index. We identified and replicated a novel association of a common variant in the type-2 transferrin receptor (TFR2) gene with iron levels, with effect sizes highly consistent across samples. In addition, we identified and replicated an association between the HFE locus and ferritin and confirmed previously reported associations with the TF, TMPRSS6 and HFE genes. The five replicated variants were tested for association with expression levels of the corresponding genes in a publicly available data set of human liver samples, and nominally statistically significant expression differences by genotype were observed for all genes, although only rs3811647 in the TF gene survived the Bonferroni correction for multiple testing. In addition, we measured for the first time the effects of the common variant in TMPRSS6, rs4820268, on hepcidin mRNA in peripheral blood (n = 83 individuals) and on hepcidin levels in urine (n = 529) and observed an association in the same direction, though only borderline significant. These functional findings require confirmation in further studies with larger sample sizes, but they suggest that common variants in TMPRSS6 could modify the hepcidin-iron feedback loop in clinically unaffected individuals, thus making them more susceptible to imbalances of iron homeostasis.
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The origin of the Haitian cholera outbreak strain.
N. Engl. J. Med.
PUBLISHED: 12-09-2010
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Although cholera has been present in Latin America since 1991, it had not been epidemic in Haiti for at least 100 years. Recently, however, there has been a severe outbreak of cholera in Haiti.
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A model selection approach for expression quantitative trait loci (eQTL) mapping.
Genetics
PUBLISHED: 11-29-2010
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Identifying the genetic basis of complex traits remains an important and challenging problem with the potential to affect a broad range of biological endeavors. A number of statistical methods are available for mapping quantitative trait loci (QTL), but their application to high-throughput phenotypes has been limited as most require user input and interaction. Recently, methods have been developed specifically for expression QTL (eQTL) mapping, but they too are limited in that they do not allow for interactions and QTL of moderate effect. We here propose an automated model-selection-based approach that identifies multiple eQTL in experimental populations, allowing for eQTL of moderate effect and interactions. Output can be used to identify groups of transcripts that are likely coregulated, as demonstrated in a study of diabetes in mouse.
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Identification of genes and networks driving cardiovascular and metabolic phenotypes in a mouse F2 intercross.
PLoS ONE
PUBLISHED: 10-15-2010
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To identify the genes and pathways that underlie cardiovascular and metabolic phenotypes we performed an integrated analysis of a mouse C57BL/6JxA/J F2 (B6AF2) cross by relating genome-wide gene expression data from adipose, kidney, and liver tissues to physiological endpoints measured in the population. We have identified a large number of trait QTLs including loci driving variation in cardiac function on chromosomes 2 and 6 and a hotspot for adiposity, energy metabolism, and glucose traits on chromosome 8. Integration of adipose gene expression data identified a core set of genes that drive the chromosome 8 adiposity QTL. This chromosome 8 trans eQTL signature contains genes associated with mitochondrial function and oxidative phosphorylation and maps to a subnetwork with conserved function in humans that was previously implicated in human obesity. In addition, human eSNPs corresponding to orthologous genes from the signature show enrichment for association to type II diabetes in the DIAGRAM cohort, supporting the idea that the chromosome 8 locus perturbs a molecular network that in humans senses variations in DNA and in turn affects metabolic disease risk. We functionally validate predictions from this approach by demonstrating metabolic phenotypes in knockout mice for three genes from the trans eQTL signature, Akr1b8, Emr1, and Rgs2. In addition we show that the transcriptional signatures for knockout of two of these genes, Akr1b8 and Rgs2, map to the F2 network modules associated with the chromosome 8 trans eQTL signature and that these modules are in turn very significantly correlated with adiposity in the F2 population. Overall this study demonstrates how integrating gene expression data with QTL analysis in a network-based framework can aid in the elucidation of the molecular drivers of disease that can be translated from mice to humans.
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A window into third-generation sequencing.
Hum. Mol. Genet.
PUBLISHED: 09-21-2010
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First- and second-generation sequencing technologies have led the way in revolutionizing the field of genomics and beyond, motivating an astonishing number of scientific advances, including enabling a more complete understanding of whole genome sequences and the information encoded therein, a more complete characterization of the methylome and transcriptome and a better understanding of interactions between proteins and DNA. Nevertheless, there are sequencing applications and aspects of genome biology that are presently beyond the reach of current sequencing technologies, leaving fertile ground for additional innovation in this space. In this review, we describe a new generation of single-molecule sequencing technologies (third-generation sequencing) that is emerging to fill this space, with the potential for dramatically longer read lengths, shorter time to result and lower overall cost.
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Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height.
Matthew B Lanktree, Yiran Guo, Muhammed Murtaza, Joseph T Glessner, Swneke D Bailey, N Charlotte Onland-Moret, Guillaume Lettre, Halit Ongen, Ramakrishnan Rajagopalan, Toby Johnson, Haiqing Shen, Christopher P Nelson, Norman Klopp, Jens Baumert, Sandosh Padmanabhan, Nathan Pankratz, James S Pankow, Sonia Shah, Kira Taylor, John Barnard, Bas J Peters, Cliona M Maloney, Maximilian T Lobmeyer, Alice Stanton, M Hadi Zafarmand, Simon P R Romaine, Amar Mehta, Erik P A van Iperen, Yan Gong, Tom S Price, Erin N Smith, Cecilia E Kim, Yun R Li, Folkert W Asselbergs, Larry D Atwood, Kristian M Bailey, Deepak Bhatt, Florianne Bauer, Elijah R Behr, Tushar Bhangale, Jolanda M A Boer, Bernhard O Boehm, Jonathan P Bradfield, Morris Brown, Peter S Braund, Paul R Burton, Cara Carty, Hareesh R Chandrupatla, Wei Chen, John Connell, Chrysoula Dalgeorgou, Anthonius de Boer, Fotios Drenos, Clara C Elbers, James C Fang, Caroline S Fox, Edward C Frackelton, Barry Fuchs, Clement E Furlong, Quince Gibson, Christian Gieger, Anuj Goel, Diederik E Grobbee, Claire Hastie, Philip J Howard, Guan-Hua Huang, W Craig Johnson, Qing Li, Marcus E Kleber, Barbara E K Klein, Ronald Klein, Charles Kooperberg, Bonnie Ky, Andrea LaCroix, Paul Lanken, Mark Lathrop, Mingyao Li, Vanessa Marshall, Olle Melander, Frank D Mentch, Nuala J Meyer, Keri L Monda, Alexandre Montpetit, Gurunathan Murugesan, Karen Nakayama, Dave Nondahl, Abiodun Onipinla, Suzanne Rafelt, Stephen J Newhouse, F George Otieno, Sanjey R Patel, Mary E Putt, Santiago Rodriguez, Radwan N Safa, Douglas B Sawyer, Pamela J Schreiner, Claire Simpson, Suthesh Sivapalaratnam, Sathanur R Srinivasan, Christine Suver, Gary Swergold, Nancy K Sweitzer, Kelly A Thomas, Barbara Thorand, Nicholas J Timpson, Sam Tischfield, Martin Tobin, Maciej Tomaszewski, Maciej Tomaszweski, W M Monique Verschuren, Chris Wallace, Bernhard Winkelmann, Haitao Zhang, Dongling Zheng, Li Zhang, Joseph M Zmuda, Robert Clarke, Anthony J Balmforth, John Danesh, Ian N Day, Nicholas J Schork, Paul I W de Bakker, Christian Delles, David Duggan, Aroon D Hingorani, Joel N Hirschhorn, Marten H Hofker, Steve E Humphries, Mika Kivimäki, Debbie A Lawlor, Kandice Kottke-Marchant, Jessica L Mega, Braxton D Mitchell, David A Morrow, Jutta Palmen, Susan Redline, Denis C Shields, Alan R Shuldiner, Patrick M Sleiman, George Davey Smith, Martin Farrall, Yalda Jamshidi, David C Christiani, Juan P Casas, Alistair S Hall, Pieter A Doevendans, Jason D Christie, Gerald S Berenson, Sarah S Murray, Thomas Illig, Gerald W Dorn, Thomas P Cappola, Eric Boerwinkle, Peter Sever, Daniel J Rader, Muredach P Reilly, Mark Caulfield, Philippa J Talmud, Eric Topol, James C Engert, Kai Wang, Anna Dominiczak, Anders Hamsten, Sean P Curtis, Roy L Silverstein, Leslie A Lange, Marc S Sabatine, Mieke Trip, Danish Saleheen, John F Peden, Karen J Cruickshanks, Winfried März, Jeffrey R O'Connell, Olaf H Klungel, Cisca Wijmenga, Anke Hilse Maitland-van der Zee, Eric E Schadt, Julie A Johnson, Gail P Jarvik, George J Papanicolaou, , Struan F A Grant, Patricia B Munroe, Kari E North, Nilesh J Samani, Wolfgang Koenig, Tom R Gaunt, Sonia S Anand, Yvonne T van der Schouw, Nicole Soranzo, Garret A FitzGerald, Alex Reiner, Robert A Hegele, Hakon Hakonarson, Brendan J Keating.
Am. J. Hum. Genet.
PUBLISHED: 09-14-2010
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Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.
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Correction for hidden confounders in the genetic analysis of gene expression.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 09-01-2010
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Understanding the genetic underpinnings of disease is important for screening, treatment, drug development, and basic biological insight. One way of getting at such an understanding is to find out which parts of our DNA, such as single-nucleotide polymorphisms, affect particular intermediary processes such as gene expression. Naively, such associations can be identified using a simple statistical test on all paired combinations of genetic variants and gene transcripts. However, a wide variety of confounders lie hidden in the data, leading to both spurious associations and missed associations if not properly addressed. We present a statistical model that jointly corrects for two particular kinds of hidden structure--population structure (e.g., race, family-relatedness), and microarray expression artifacts (e.g., batch effects), when these confounders are unknown. Applying our method to both real and synthetic, human and mouse data, we demonstrate the need for such a joint correction of confounders, and also the disadvantages of other possible approaches based on those in the current literature. In particular, we show that our class of models has maximum power to detect eQTL on synthetic data, and has the best performance on a bronze standard applied to real data. Lastly, our software and the associations we found with it are available at http://www.microsoft.com/science.
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Computational solutions to large-scale data management and analysis.
Nat. Rev. Genet.
PUBLISHED: 08-19-2010
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Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist - such as cloud and heterogeneous computing - to successfully tackle our big data problems.
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An integrative multi-network and multi-classifier approach to predict genetic interactions.
PLoS Comput. Biol.
PUBLISHED: 08-10-2010
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Genetic interactions occur when a combination of mutations results in a surprising phenotype. These interactions capture functional redundancy, and thus are important for predicting function, dissecting protein complexes into functional pathways, and exploring the mechanistic underpinnings of common human diseases. Synthetic sickness and lethality are the most studied types of genetic interactions in yeast. However, even in yeast, only a small proportion of gene pairs have been tested for genetic interactions due to the large number of possible combinations of gene pairs. To expand the set of known synthetic lethal (SL) interactions, we have devised an integrative, multi-network approach for predicting these interactions that significantly improves upon the existing approaches. First, we defined a large number of features for characterizing the relationships between pairs of genes from various data sources. In particular, these features are independent of the known SL interactions, in contrast to some previous approaches. Using these features, we developed a non-parametric multi-classifier system for predicting SL interactions that enabled the simultaneous use of multiple classification procedures. Several comprehensive experiments demonstrated that the SL-independent features in conjunction with the advanced classification scheme led to an improved performance when compared to the current state of the art method. Using this approach, we derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature. We also used this approach to predict SL interactions between all non-essential gene pairs in yeast (http://sage.fhcrc.org/downloads/downloads/predicted_yeast_genetic_interactions.zip). This integrative approach is expected to be more effective and robust in uncovering new genetic interactions from the tens of millions of unknown gene pairs in yeast and from the hundreds of millions of gene pairs in higher organisms like mouse and human, in which very few genetic interactions have been identified to date.
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FoxM1 is up-regulated by obesity and stimulates beta-cell proliferation.
Mol. Endocrinol.
PUBLISHED: 07-21-2010
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beta-Cell mass expansion is one mechanism by which obese animals compensate for insulin resistance and prevent diabetes. FoxM1 is a transcription factor that can regulate the expression of multiple cell cycle genes and is necessary for the maintenance of adult beta-cell mass, beta-cell proliferation, and glucose homeostasis. We hypothesized that FoxM1 is up-regulated by nondiabetic obesity and initiates a transcriptional program leading to beta-cell proliferation. We performed gene expression analysis on islets from the nondiabetic C57BL/6 Leptin(ob/ob) mouse, the diabetic BTBR Leptin(ob/ob) mouse, and an F2 Leptin(ob/ob) population derived from these strains. We identified obesity-driven coordinated up-regulation of islet Foxm1 and its target genes in the nondiabetic strain, correlating with beta-cell mass expansion and proliferation. This up-regulation was absent in the diabetic strain. In the F2 Leptin(ob/ob) population, increased expression of Foxm1 and its target genes segregated with higher insulin and lower glucose levels. We next studied the effects of FOXM1b overexpression on isolated mouse and human islets. We found that FoxM1 stimulated mouse and human beta-cell proliferation by activating many cell cycle phases. We asked whether FOXM1 expression is also responsive to obesity in human islets by collecting RNA from human islet donors (body mass index range: 24-51). We found that the expression of FOXM1 and its target genes is positively correlated with body mass index. Our data suggest that beta-cell proliferation occurs in adult obese humans in an attempt to expand beta-cell mass to compensate for insulin resistance, and that the FoxM1 transcriptional program plays a key role in this process.
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Genetic variation at the phospholipid transfer protein locus affects its activity and high-density lipoprotein size and is a novel marker of cardiovascular disease susceptibility.
Circulation
PUBLISHED: 07-19-2010
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In contrast to clear associations between variants in genes participating in low-density lipoprotein metabolism and cardiovascular disease risk, such associations for high-density lipoprotein (HDL)-related genes are not well supported by recent large studies. We aimed to determine whether genetic variants at the locus encoding phospholipid transfer protein (PLTP), a protein involved in HDL remodeling, underlie altered PLTP activity, HDL particle concentration and size, and cardiovascular disease risk.
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Drug discovery in a multidimensional world: systems, patterns, and networks.
J Cardiovasc Transl Res
PUBLISHED: 06-17-2010
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Despite great strides in revealing and understanding the physiological and molecular bases of cardiovascular disease, efforts to translate this understanding into needed therapeutic interventions continue to lag far behind the initial discoveries. Although pharmaceutical companies continue to increase investments into research and development, the number of drugs gaining federal approval is in decline. Many factors underlie these trends, and a vast number of technological and scientific innovations are being sought through efforts to reinvigorate drug discovery pipelines. Recent advances in molecular profiling technologies and development of sophisticated computational approaches for analyzing these data are providing new, systems-oriented approaches towards drug discovery. Unlike the traditional approach to drug discovery which is typified by a one-drug-one-target mindset, systems-oriented approaches to drug discovery leverage the parallelism and high-dimensionality of the molecular data to construct more comprehensive molecular models that aim to model broader bimolecular systems. These models offer a means to explore complex molecular states (e.g., disease) where thousands to millions of molecular entities comprising multiple molecular data types (e.g., proteomics and gene expression) can be evaluated simultaneously as components of a cohesive biomolecular system. In this paper, we discuss emerging approaches towards systems-oriented drug discovery and contrast these efforts with the traditional, unidimensional approach to drug discovery. We also highlight several applications of these system-oriented approaches across various aspects of drug discovery, including target discovery, drug repositioning and drug toxicity. When available, specific applications to cardiovascular drug discovery are highlighted and discussed.
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Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver.
Genome Res.
PUBLISHED: 06-10-2010
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Liver cytochrome P450s (P450s) play critical roles in drug metabolism, toxicology, and metabolic processes. Despite rapid progress in the understanding of these enzymes, a systematic investigation of the full spectrum of functionality of individual P450s, the interrelationship or networks connecting them, and the genetic control of each gene/enzyme is lacking. To this end, we genotyped, expression-profiled, and measured P450 activities of 466 human liver samples and applied a systems biology approach via the integration of genetics, gene expression, and enzyme activity measurements. We found that most P450s were positively correlated among themselves and were highly correlated with known regulators as well as thousands of other genes enriched for pathways relevant to the metabolism of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis-regulation of P450 expression (especially for CYP2D6) and more complex trans-regulation of P450 activity. Several novel SNPs associated with CYP2D6 expression and enzyme activity were validated in an independent human cohort. By constructing a weighted coexpression network and a Bayesian regulatory network, we defined the human liver transcriptional network structure, uncovered subnetworks representative of the P450 regulatory system, and identified novel candidate regulatory genes, namely, EHHADH, SLC10A1, and AKR1D1. The P450 subnetworks were then validated using gene signatures responsive to ligands of known P450 regulators in mouse and rat. This systematic survey provides a comprehensive view of the functionality, genetic control, and interactions of P450s.
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From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus.
Nature
PUBLISHED: 06-09-2010
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Recent genome-wide association studies (GWASs) have identified a locus on chromosome 1p13 strongly associated with both plasma low-density lipoprotein cholesterol (LDL-C) and myocardial infarction (MI) in humans. Here we show through a series of studies in human cohorts and human-derived hepatocytes that a common noncoding polymorphism at the 1p13 locus, rs12740374, creates a C/EBP (CCAAT/enhancer binding protein) transcription factor binding site and alters the hepatic expression of the SORT1 gene. With small interfering RNA (siRNA) knockdown and viral overexpression in mouse liver, we demonstrate that Sort1 alters plasma LDL-C and very low-density lipoprotein (VLDL) particle levels by modulating hepatic VLDL secretion. Thus, we provide functional evidence for a novel regulatory pathway for lipoprotein metabolism and suggest that modulation of this pathway may alter risk for MI in humans. We also demonstrate that common noncoding DNA variants identified by GWASs can directly contribute to clinical phenotypes.
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Genetic validation of whole-transcriptome sequencing for mapping expression affected by cis-regulatory variation.
BMC Genomics
PUBLISHED: 05-26-2010
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Identifying associations between genotypes and gene expression levels using microarrays has enabled systematic interrogation of regulatory variation underlying complex phenotypes. This approach has vast potential for functional characterization of disease states, but its prohibitive cost, given hundreds to thousands of individual samples from populations have to be genotyped and expression profiled, has limited its widespread application.
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Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.
Elizabeth K Speliotes, Cristen J Willer, Sonja I Berndt, Keri L Monda, Gudmar Thorleifsson, Anne U Jackson, Hana Lango Allen, Cecilia M Lindgren, Jian'an Luan, Reedik Mägi, Joshua C Randall, Sailaja Vedantam, Thomas W Winkler, Lu Qi, Tsegaselassie Workalemahu, Iris M Heid, Valgerdur Steinthorsdottir, Heather M Stringham, Michael N Weedon, Eleanor Wheeler, Andrew R Wood, Teresa Ferreira, Robert J Weyant, Ayellet V Segrè, Karol Estrada, Liming Liang, James Nemesh, Ju-Hyun Park, Stefan Gustafsson, Tuomas O Kilpeläinen, Jian Yang, Nabila Bouatia-Naji, Tonu Esko, Mary F Feitosa, Zoltan Kutalik, Massimo Mangino, Soumya Raychaudhuri, André Scherag, Albert Vernon Smith, Ryan Welch, Jing Hua Zhao, Katja K Aben, Devin M Absher, Najaf Amin, Anna L Dixon, Eva Fisher, Nicole L Glazer, Michael E Goddard, Nancy L Heard-Costa, Volker Hoesel, Jouke-Jan Hottenga, Asa Johansson, Toby Johnson, Shamika Ketkar, Claudia Lamina, Shengxu Li, Miriam F Moffatt, Richard H Myers, Narisu Narisu, John R B Perry, Marjolein J Peters, Michael Preuss, Samuli Ripatti, Fernando Rivadeneira, Camilla Sandholt, Laura J Scott, Nicholas J Timpson, Jonathan P Tyrer, Sophie van Wingerden, Richard M Watanabe, Charles C White, Fredrik Wiklund, Christina Barlassina, Daniel I Chasman, Matthew N Cooper, John-Olov Jansson, Robert W Lawrence, Niina Pellikka, Inga Prokopenko, Jianxin Shi, Elisabeth Thiering, Helene Alavere, Maria T S Alibrandi, Peter Almgren, Alice M Arnold, Thor Aspelund, Larry D Atwood, Beverley Balkau, Anthony J Balmforth, Amanda J Bennett, Yoav Ben-Shlomo, Richard N Bergman, Sven Bergmann, Heike Biebermann, Alexandra I F Blakemore, Tanja Boes, Lori L Bonnycastle, Stefan R Bornstein, Morris J Brown, Thomas A Buchanan, Fabio Busonero, Harry Campbell, Francesco P Cappuccio, Christine Cavalcanti-Proença, Yii-Der Ida Chen, Chih-Mei Chen, Peter S Chines, Robert Clarke, Lachlan Coin, John Connell, Ian N M Day, Martin den Heijer, Jubao Duan, Shah Ebrahim, Paul Elliott, Roberto Elosua, Gudny Eiriksdottir, Michael R Erdos, Johan G Eriksson, Maurizio F Facheris, Stephan B Felix, Pamela Fischer-Posovszky, Aaron R Folsom, Nele Friedrich, Nelson B Freimer, Mao Fu, Stefan Gaget, Pablo V Gejman, Eco J C Geus, Christian Gieger, Anette P Gjesing, Anuj Goel, Philippe Goyette, Harald Grallert, Jürgen Gräßler, Danielle M Greenawalt, Christopher J Groves, Vilmundur Gudnason, Candace Guiducci, Anna-Liisa Hartikainen, Neelam Hassanali, Alistair S Hall, Aki S Havulinna, Caroline Hayward, Andrew C Heath, Christian Hengstenberg, Andrew A Hicks, Anke Hinney, Albert Hofman, Georg Homuth, Jennie Hui, Wilmar Igl, Carlos Iribarren, Bo Isomaa, Kevin B Jacobs, Ivonne Jarick, Elizabeth Jewell, Ulrich John, Torben Jørgensen, Pekka Jousilahti, Antti Jula, Marika Kaakinen, Eero Kajantie, Lee M Kaplan, Sekar Kathiresan, Johannes Kettunen, Leena Kinnunen, Joshua W Knowles, Ivana Kolčić, Inke R König, Seppo Koskinen, Peter Kovacs, Johanna Kuusisto, Peter Kraft, Kirsti Kvaløy, Jaana Laitinen, Olivier Lantieri, Chiara Lanzani, Lenore J Launer, Cécile Lecoeur, Terho Lehtimäki, Guillaume Lettre, Jianjun Liu, Marja-Liisa Lokki, Mattias Lorentzon, Robert N Luben, Barbara Ludwig, , Paolo Manunta, Diana Marek, Michel Marre, Nicholas G Martin, Wendy L McArdle, Anne McCarthy, Barbara McKnight, Thomas Meitinger, Olle Melander, David Meyre, Kristian Midthjell, Grant W Montgomery, Mario A Morken, Andrew P Morris, Rosanda Mulić, Julius S Ngwa, Mari Nelis, Matt J Neville, Dale R Nyholt, Christopher J O'Donnell, Stephen O'Rahilly, Ken K Ong, Ben Oostra, Guillaume Paré, Alex N Parker, Markus Perola, Irene Pichler, Kirsi H Pietiläinen, Carl G P Platou, Ozren Polašek, Anneli Pouta, Suzanne Rafelt, Olli Raitakari, Nigel W Rayner, Martin Ridderstråle, Winfried Rief, Aimo Ruokonen, Neil R Robertson, Peter Rzehak, Veikko Salomaa, Alan R Sanders, Manjinder S Sandhu, Serena Sanna, Jouko Saramies, Markku J Savolainen, Susann Scherag, Sabine Schipf, Stefan Schreiber, Heribert Schunkert, Kaisa Silander, Juha Sinisalo, David S Siscovick, Jan H Smit, Nicole Soranzo, Ulla Sovio, Jonathan Stephens, Ida Surakka, Amy J Swift, Mari-Liis Tammesoo, Jean-Claude Tardif, Maris Teder-Laving, Tanya M Teslovich, John R Thompson, Brian Thomson, Anke Tönjes, Tiinamaija Tuomi, Joyce B J van Meurs, Gert-Jan van Ommen, Vincent Vatin, Jorma Viikari, Sophie Visvikis-Siest, Veronique Vitart, Carla I G Vogel, Benjamin F Voight, Lindsay L Waite, Henri Wallaschofski, G Bragi Walters, Elisabeth Widén, Susanna Wiegand, Sarah H Wild, Gonneke Willemsen, Daniel R Witte, Jacqueline C Witteman, Jianfeng Xu, Qunyuan Zhang, Lina Zgaga, Andreas Ziegler, Paavo Zitting, John P Beilby, I Sadaf Farooqi, Johannes Hebebrand, Heikki V Huikuri, Alan L James, Mika Kähönen, Douglas F Levinson, Fabio Macciardi, Markku S Nieminen, Claes Ohlsson, Lyle J Palmer, Paul M Ridker, Michael Stumvoll, Jacques S Beckmann, Heiner Boeing, Eric Boerwinkle, Dorret I Boomsma, Mark J Caulfield, Stephen J Chanock, Francis S Collins, L Adrienne Cupples, George Davey Smith, Jeanette Erdmann, Philippe Froguel, Henrik Grönberg, Ulf Gyllensten, Per Hall, Torben Hansen, Tamara B Harris, Andrew T Hattersley, Richard B Hayes, Joachim Heinrich, Frank B Hu, Kristian Hveem, Thomas Illig, Marjo-Riitta Järvelin, Jaakko Kaprio, Fredrik Karpe, Kay-Tee Khaw, Lambertus A Kiemeney, Heiko Krude, Markku Laakso, Debbie A Lawlor, Andres Metspalu, Patricia B Munroe, Willem H Ouwehand, Oluf Pedersen, Brenda W Penninx, Annette Peters, Peter P Pramstaller, Thomas Quertermous, Thomas Reinehr, Aila Rissanen, Igor Rudan, Nilesh J Samani, Peter E H Schwarz, Alan R Shuldiner, Timothy D Spector, Jaakko Tuomilehto, Manuela Uda, André Uitterlinden, Timo T Valle, Martin Wabitsch, Gérard Waeber, Nicholas J Wareham, Hugh Watkins, James F Wilson, Alan F Wright, M Carola Zillikens, Nilanjan Chatterjee, Steven A McCarroll, Shaun Purcell, Eric E Schadt, Peter M Visscher, Themistocles L Assimes, Ingrid B Borecki, Panos Deloukas, Caroline S Fox, Leif C Groop, Talin Haritunians, David J Hunter, Robert C Kaplan, Karen L Mohlke, Jeffrey R O'Connell, Leena Peltonen, David Schlessinger, David P Strachan, Cornelia M van Duijn, H-Erich Wichmann, Timothy M Frayling, Unnur Thorsteinsdottir, Gonçalo R Abecasis, Inês Barroso, Michael Boehnke, Kari Stefansson, Kari E North, Mark I McCarthy, Joel N Hirschhorn, Erik Ingelsson, Ruth J F Loos.
Nat. Genet.
PUBLISHED: 05-13-2010
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Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ? 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10??), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.
Iris M Heid, Anne U Jackson, Joshua C Randall, Thomas W Winkler, Lu Qi, Valgerdur Steinthorsdottir, Gudmar Thorleifsson, M Carola Zillikens, Elizabeth K Speliotes, Reedik Mägi, Tsegaselassie Workalemahu, Charles C White, Nabila Bouatia-Naji, Tamara B Harris, Sonja I Berndt, Erik Ingelsson, Cristen J Willer, Michael N Weedon, Jian'an Luan, Sailaja Vedantam, Tonu Esko, Tuomas O Kilpeläinen, Zoltan Kutalik, Shengxu Li, Keri L Monda, Anna L Dixon, Christopher C Holmes, Lee M Kaplan, Liming Liang, Josine L Min, Miriam F Moffatt, Cliona Molony, George Nicholson, Eric E Schadt, Krina T Zondervan, Mary F Feitosa, Teresa Ferreira, Hana Lango Allen, Robert J Weyant, Eleanor Wheeler, Andrew R Wood, , Karol Estrada, Michael E Goddard, Guillaume Lettre, Massimo Mangino, Dale R Nyholt, Shaun Purcell, Albert Vernon Smith, Peter M Visscher, Jian Yang, Steven A McCarroll, James Nemesh, Benjamin F Voight, Devin Absher, Najaf Amin, Thor Aspelund, Lachlan Coin, Nicole L Glazer, Caroline Hayward, Nancy L Heard-Costa, Jouke-Jan Hottenga, Asa Johansson, Toby Johnson, Marika Kaakinen, Karen Kapur, Shamika Ketkar, Joshua W Knowles, Peter Kraft, Aldi T Kraja, Claudia Lamina, Michael F Leitzmann, Barbara McKnight, Andrew P Morris, Ken K Ong, John R B Perry, Marjolein J Peters, Ozren Polašek, Inga Prokopenko, Nigel W Rayner, Samuli Ripatti, Fernando Rivadeneira, Neil R Robertson, Serena Sanna, Ulla Sovio, Ida Surakka, Alexander Teumer, Sophie van Wingerden, Veronique Vitart, Jing Hua Zhao, Christine Cavalcanti-Proença, Peter S Chines, Eva Fisher, Jennifer R Kulzer, Cécile Lecoeur, Narisu Narisu, Camilla Sandholt, Laura J Scott, Kaisa Silander, Klaus Stark, Mari-Liis Tammesoo, Tanya M Teslovich, Nicholas John Timpson, Richard M Watanabe, Ryan Welch, Daniel I Chasman, Matthew N Cooper, John-Olov Jansson, Johannes Kettunen, Robert W Lawrence, Niina Pellikka, Markus Perola, Liesbeth Vandenput, Helene Alavere, Peter Almgren, Larry D Atwood, Amanda J Bennett, Reiner Biffar, Lori L Bonnycastle, Stefan R Bornstein, Thomas A Buchanan, Harry Campbell, Ian N M Day, Mariano Dei, Marcus Dörr, Paul Elliott, Michael R Erdos, Johan G Eriksson, Nelson B Freimer, Mao Fu, Stefan Gaget, Eco J C Geus, Anette P Gjesing, Harald Grallert, Jürgen Gräßler, Christopher J Groves, Candace Guiducci, Anna-Liisa Hartikainen, Neelam Hassanali, Aki S Havulinna, Karl-Heinz Herzig, Andrew A Hicks, Jennie Hui, Wilmar Igl, Pekka Jousilahti, Antti Jula, Eero Kajantie, Leena Kinnunen, Ivana Kolčić, Seppo Koskinen, Peter Kovacs, Heyo K Kroemer, Vjekoslav Krželj, Johanna Kuusisto, Kirsti Kvaloy, Jaana Laitinen, Olivier Lantieri, G Mark Lathrop, Marja-Liisa Lokki, Robert N Luben, Barbara Ludwig, Wendy L McArdle, Anne McCarthy, Mario A Morken, Mari Nelis, Matt J Neville, Guillaume Paré, Alex N Parker, John F Peden, Irene Pichler, Kirsi H Pietiläinen, Carl G P Platou, Anneli Pouta, Martin Ridderstråle, Nilesh J Samani, Jouko Saramies, Juha Sinisalo, Jan H Smit, Rona J Strawbridge, Heather M Stringham, Amy J Swift, Maris Teder-Laving, Brian Thomson, Gianluca Usala, Joyce B J van Meurs, Gert-Jan van Ommen, Vincent Vatin, Claudia B Volpato, Henri Wallaschofski, G Bragi Walters, Elisabeth Widén, Sarah H Wild, Gonneke Willemsen, Daniel R Witte, Lina Zgaga, Paavo Zitting, John P Beilby, Alan L James, Mika Kähönen, Terho Lehtimäki, Markku S Nieminen, Claes Ohlsson, Lyle J Palmer, Olli Raitakari, Paul M Ridker, Michael Stumvoll, Anke Tönjes, Jorma Viikari, Beverley Balkau, Yoav Ben-Shlomo, Richard N Bergman, Heiner Boeing, George Davey Smith, Shah Ebrahim, Philippe Froguel, Torben Hansen, Christian Hengstenberg, Kristian Hveem, Bo Isomaa, Torben Jørgensen, Fredrik Karpe, Kay-Tee Khaw, Markku Laakso, Debbie A Lawlor, Michel Marre, Thomas Meitinger, Andres Metspalu, Kristian Midthjell, Oluf Pedersen, Veikko Salomaa, Peter E H Schwarz, Tiinamaija Tuomi, Jaakko Tuomilehto, Timo T Valle, Nicholas J Wareham, Alice M Arnold, Jacques S Beckmann, Sven Bergmann, Eric Boerwinkle, Dorret I Boomsma, Mark J Caulfield, Francis S Collins, Gudny Eiriksdottir, Vilmundur Gudnason, Ulf Gyllensten, Anders Hamsten, Andrew T Hattersley, Albert Hofman, Frank B Hu, Thomas Illig, Carlos Iribarren, Marjo-Riitta Järvelin, W H Linda Kao, Jaakko Kaprio, Lenore J Launer, Patricia B Munroe, Ben Oostra, Brenda W Penninx, Peter P Pramstaller, Bruce M Psaty, Thomas Quertermous, Aila Rissanen, Igor Rudan, Alan R Shuldiner, Nicole Soranzo, Timothy D Spector, Ann-Christine Syvänen, Manuela Uda, André Uitterlinden, Henry Völzke, Peter Vollenweider, James F Wilson, Jacqueline C Witteman, Alan F Wright, Gonçalo R Abecasis, Michael Boehnke, Ingrid B Borecki, Panos Deloukas, Timothy M Frayling, Leif C Groop, Talin Haritunians, David J Hunter, Robert C Kaplan, Kari E North, Jeffrey R O'Connell, Leena Peltonen, David Schlessinger, David P Strachan, Joel N Hirschhorn, Themistocles L Assimes, H-Erich Wichmann, Unnur Thorsteinsdottir, Cornelia M van Duijn, Kari Stefansson, L Adrienne Cupples, Ruth J F Loos, Inês Barroso, Mark I McCarthy, Caroline S Fox, Karen L Mohlke, Cecilia M Lindgren.
Nat. Genet.
PUBLISHED: 05-06-2010
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Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10?? to P = 1.8 × 10???) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10?³ to P = 1.2 × 10?¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
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An integration of genome-wide association study and gene expression profiling to prioritize the discovery of novel susceptibility Loci for osteoporosis-related traits.
PLoS Genet.
PUBLISHED: 05-06-2010
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Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6x10(-8)), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6x10(-13); SOX6, p = 6.4x10(-10)) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.
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Expression quantitative trait loci: replication, tissue- and sex-specificity in mice.
Genetics
PUBLISHED: 05-03-2010
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By treating the transcript abundance as a quantitative trait, gene expression can be mapped to local or distant genomic regions relative to the gene encoding the transcript. Local expression quantitative trait loci (eQTL) generally act in cis (that is, control the expression of only the contiguous structural gene), whereas distal eQTL act in trans. Distal eQTL are more difficult to identify with certainty due to the fact that significant thresholds are very high since all regions of the genome must be tested, and confounding factors such as batch effects can produce false positives. Here, we compare findings from two large genetic crosses between mouse strains C3H/HeJ and C57BL/6J to evaluate the reliability of distal eQTL detection, including "hotspots" influencing the expression of multiple genes in trans. We found that >63% of local eQTL and >18% of distal eQTL were replicable at a threshold of LOD > 4.3 between crosses and 76% of local and >24% of distal eQTL at a threshold of LOD > 6. Additionally, at LOD > 4.3 four tissues studied (adipose, brain, liver, and muscle) exhibited >50% preservation of local eQTL and >17% preservation of distal eQTL. We observed replicated distal eQTL hotspots between the crosses on chromosomes 9 and 17. Finally, >69% of local eQTL and >10% of distal eQTL were preserved in most tissues between sexes. We conclude that most local eQTL are highly replicable between mouse crosses, tissues, and sex as compared to distal eQTL, which exhibited modest replicability.
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