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Search Results: 1 - 10 of 408739 matches for " Dan M Roden "
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Molecular cloning and analysis of zebrafish voltage-gated sodium channel beta subunit genes: implications for the evolution of electrical signaling in vertebrates
Sameer S Chopra, Hiroshi Watanabe, Tao P Zhong, Dan M Roden
BMC Evolutionary Biology , 2007, DOI: 10.1186/1471-2148-7-113
Abstract: We identified and cloned single zebrafish gene homologs for beta1-beta3 (zbeta1-zbeta3) and duplicate genes for beta4 (zbeta4.1, zbeta4.2). Sodium channel beta subunit loci are similarly organized in fish and mammalian genomes. Unlike their mammalian counterparts, zbeta1 and zbeta2 subunit genes display extensive alternative splicing. Zebrafish beta subunit genes and their splice variants are differentially-expressed in excitable tissues, indicating tissue-specific regulation of zbeta1-4 expression and splicing. Co-expression of the genes encoding zbeta1 and the zebrafish sodium channel alpha subunit Nav1.5 in Chinese Hamster Ovary cells increased sodium current and altered channel gating, demonstrating functional interactions between zebrafish alpha and beta subunits. Analysis of the synteny and phylogeny of mammalian, teleost, amphibian, and avian beta subunit and related genes indicated that all extant vertebrate beta subunits are orthologous, that beta2/beta4 and beta1/beta3 share common ancestry, and that beta subunits are closely related to other proteins sharing the V-type immunoglobulin domain structure. Vertebrate sodium channel beta subunit genes were not identified in the genomes of invertebrate chordates and are unrelated to known subunits of the para sodium channel in Drosophila.The identification of conserved orthologs to all 4 voltage-gated sodium channel beta subunit genes in zebrafish and the lack of evidence for beta subunit genes in invertebrate chordates together indicate that this gene family emerged early in vertebrate evolution, prior to the divergence of teleosts and tetrapods. The evolutionary history of sodium channel beta subunits suggests that these genes may have played a key role in the diversification and specialization of electrical signaling in early vertebrates.Coordinated electrical signals in the metazoan nervous system, heart, and skeletal muscle depend on the generation of action potentials, rapid changes in membrane potential m
Enabling Genomic-Phenomic Association Discovery without Sacrificing Anonymity
Raymond D. Heatherly, Grigorios Loukides, Joshua C. Denny, Jonathan L. Haines, Dan M. Roden, Bradley A. Malin
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0053875
Abstract: Health information technologies facilitate the collection of massive quantities of patient-level data. A growing body of research demonstrates that such information can support novel, large-scale biomedical investigations at a fraction of the cost of traditional prospective studies. While healthcare organizations are being encouraged to share these data in a de-identified form, there is hesitation over concerns that it will allow corresponding patients to be re-identified. Currently proposed technologies to anonymize clinical data may make unrealistic assumptions with respect to the capabilities of a recipient to ascertain a patients identity. We show that more pragmatic assumptions enable the design of anonymization algorithms that permit the dissemination of detailed clinical profiles with provable guarantees of protection. We demonstrate this strategy with a dataset of over one million medical records and show that 192 genotype-phenotype associations can be discovered with fidelity equivalent to non-anonymized clinical data.
Characterization of Genome-Wide Association-Identified Variants for Atrial Fibrillation in African Americans
Jessica T. Delaney, Janina M. Jeff, Nancy J. Brown, Mias Pretorius, Henry E. Okafor, Dawood Darbar, Dan M. Roden, Dana C. Crawford
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032338
Abstract: Background Despite a greater burden of risk factors, atrial fibrillation (AF) is less common among African Americans than European-descent populations. Genome-wide association studies (GWAS) for AF in European-descent populations have identified three predominant genomic regions associated with increased risk (1q21, 4q25, and 16q22). The contribution of these loci to AF risk in African American is unknown. Methodology/Principal Findings We studied 73 African Americans with AF from the Vanderbilt-Meharry AF registry and 71 African American controls, with no history of AF including after cardiac surgery. Tests of association were performed for 148 SNPs across the three regions associated with AF, and 22 SNPs were significantly associated with AF (P<0.05). The SNPs with the strongest associations in African Americans were both different from the index SNPs identified in European-descent populations and independent from the index European-descent population SNPs (r2<0.40 in HapMap CEU): 1q21 rs4845396 (odds ratio [OR] 0.30, 95% confidence interval [CI] 0.13–0.67, P = 0.003), 4q25 rs4631108 (OR 3.43, 95% CI 1.59–7.42, P = 0.002), and 16q22 rs16971547 (OR 8.1, 95% CI 1.46–45.4, P = 0.016). Estimates of European ancestry were similar among cases (23.6%) and controls (23.8%). Accordingly, the probability of having two copies of the European derived chromosomes at each region did not differ between cases and controls. Conclusions/Significance Variable European admixture at known AF loci does not explain decreased AF susceptibility in African Americans. These data support the role of 1q21, 4q25, and 16q22 variants in AF risk for African Americans, although the index SNPs differ from those identified in European-descent populations.
Integrating EMR-Linked and In Vivo Functional Genetic Data to Identify New Genotype-Phenotype Associations
Jonathan D. Mosley, Sara L. Van Driest, Peter E. Weeke, Jessica T. Delaney, Quinn S. Wells, Lisa Bastarache, Dan M. Roden, Josh C. Denny
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0100322
Abstract: The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among homozygotes of a genetic variant. We explored the feasibility of this approach to identify phenotypes associated with low frequency variants using Vanderbilt's EMR-based BioVU resource. We analyzed 1,658 low frequency non-synonymous SNPs (nsSNPs) with a minor allele frequency (MAF)<10% collected on 8,546 subjects. For each nsSNP, we identified diagnoses shared by at least 2 minor allele homozygotes and with an association p<0.05. The diagnoses were reviewed by a clinician to ascertain whether they may share a common mechanistic basis. While a number of biologically compelling clinical patterns of association were observed, the frequency of these associations was identical to that observed using genotype-permuted data sets, indicating that the associations were likely due to chance. To refine our analysis associations, we then restricted the analysis to 711 nsSNPs in genes with phenotypes in the On-line Mendelian Inheritance in Man (OMIM) or knock-out mouse phenotype databases. An initial comparison of the EMR diagnoses to the known in vivo functions of the gene identified 25 candidate nsSNPs, 19 of which had significant genotype-phenotype associations when tested using matched controls. Twleve of the 19 nsSNPs associations were confirmed by a detailed record review. Four of 12 nsSNP-phenotype associations were successfully replicated in an independent data set: thrombosis (F5,rs6031), seizures/convulsions (GPR98,rs13157270), macular degeneration (CNGB3,rs3735972), and GI bleeding (HGFAC,rs16844401). These analyses demonstrate the feasibility and challenges of using reverse genetics approaches to identify novel gene-phenotype associations in human subjects using low frequency variants. As increasing amounts of rare variant data are generated from modern genotyping and sequence platforms, model organism data may be an important tool to enable discovery.
Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action
Jingchun Sun?,Min Zhao?,Peilin Jia?,Lily Wang?,Yonghui Wu?,Carissa Iverson?,Yubo Zhou?,Erica Bowton?,Dan M. Roden,Joshua C. Denny
PLOS Computational Biology , 2015, DOI: 10.1371/journal.pcbi.1004202
Abstract: A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin’s antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.
Hypertonie und Sekund r-/Terti rpr vention bei Diabetes
Roden M,Pfeiler G
Journal für Hypertonie , 2005,
Abstract: Mindestens 20 60 % aller Diabetiker leiden an Hypertonie. Hypertensive Diabetiker weisen gegenüber normotensiven Diabetikern ein erh htes Risiko auf, kardiovaskul re Ereignisse zu erleiden bzw. an einem solchen zu versterben. Randomisierte kontrollierte Untersuchungen zeigen, da intensive Blutdruck-Einstellung und -Kontrolle dieses erh hte Risiko in diabetischen Kollektiven senken k nnen. Gro angelegte klinische Studien, wie LIFE, ALLHAT, NORDIL, UKPDS or MICRO-HOPE, haben verschiedene Medikamentengruppen in ihrer antihypertensiven als auch risikoreduzierenden Wirksamkeit bezogen auf mikro- und makrovaskul re Folgen bei hypertensiven Diabetikern untersucht. Die vorliegende übersicht vergleicht Studien seit 1985 bezüglich der Bedeutung der Blutdruckkontrolle in der Sekund r- und Terti rpr vention bei hypertensiven Diabetikern.
Mechanisms by which circadian rhythm disruption may lead to cancer
M. Beckett,L. C. Roden
South African Journal of Science , 2010, DOI: 10.4102/sajs.v105i11/12.125
Abstract: Humans have evolved in a rhythmic environment and display daily (circadian) rhythms in physiology, metabolism and behaviour that are in synchrony with the solar day. Modern lifestyles have compromised the exposure to bright light during the day and dark nights, resulting in the desynchronisation of endogenously generated circadian rhythms from the external environment and loss of coordination between rhythms within the body. This has detrimental effects on physical and mental health, due to the misregulation and uncoupling of important cellular and physiological processes. Long-term shift workers who are exposed to bright light at night experience the greatest disruption of their circadian rhythms. Studies have shown an association between exposure to light at night, circadian rhythm disruption and an increased risk of cancer. Previous reviews have explored the relevance of light and melatonin in cancer, but here we explore the correlation of circadian rhythm disruption and cancer in terms of molecular mechanisms affecting circadian gene expression and melatonin secretion.
Admixture Mapping and Subsequent Fine-Mapping Suggests a Biologically Relevant and Novel Association on Chromosome 11 for Type 2 Diabetes in African Americans
Janina M. Jeff, Loren L. Armstrong, Marylyn D. Ritchie, Joshua C. Denny, Abel N. Kho, Melissa A. Basford, Wendy A. Wolf, Jennifer A. Pacheco, Rongling Li, Rex L. Chisholm, Dan M. Roden, M. Geoffrey Hayes, Dana C. Crawford
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0086931
Abstract: Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Genome-wide association studies (GWAS) have identified several loci that contribute to T2D in European Americans, but few studies have been performed in admixed populations. We first performed a GWAS of 1,563 African Americans from the Vanderbilt Genome-Electronic Records Project and Northwestern University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in this African American dataset. We were unable to identify novel associations at p<5.0×10?8 by GWAS. Using admixture mapping as an alternative method for discovery, we performed a genome-wide admixture scan that suggests multiple candidate genes associated with T2D. One finding, TCIRG1, is a T-cell immune regulator expressed in the pancreas and liver that has not been previously implicated for T2D. We performed subsequent fine-mapping to further assess the association between TCIRG1 and T2D in >5,000 African Americans. We identified 13 independent associations between TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11 and T2D. Our results suggest a novel region on chromosome 11 identified by admixture mapping is associated with T2D in African Americans.
Clinical and Genetic Determinants of Warfarin Pharmacokinetics and Pharmacodynamics during Treatment Initiation
Inna Y. Gong,Ute I. Schwarz,Natalie Crown,George K. Dresser,Alejandro Lazo-Langner,GuangYong Zou,Dan M. Roden,C. Michael Stein,Marc Rodger,Philip S. Wells,Richard B. Kim,Rommel G. Tirona
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0027808
Abstract: Variable warfarin response during treatment initiation poses a significant challenge to providing optimal anticoagulation therapy. We investigated the determinants of initial warfarin response in a cohort of 167 patients. During the first nine days of treatment with pharmacogenetics-guided dosing, S-warfarin plasma levels and international normalized ratio were obtained to serve as inputs to a pharmacokinetic-pharmacodynamic (PK-PD) model. Individual PK (S-warfarin clearance) and PD (Imax) parameter values were estimated. Regression analysis demonstrated that CYP2C9 genotype, kidney function, and gender were independent determinants of S-warfarin clearance. The values for Imax were dependent on VKORC1 and CYP4F2 genotypes, vitamin K status (as measured by plasma concentrations of proteins induced by vitamin K absence, PIVKA-II) and weight. Importantly, indication for warfarin was a major independent determinant of Imax during initiation, where PD sensitivity was greater in atrial fibrillation than venous thromboembolism. To demonstrate the utility of the global PK-PD model, we compared the predicted initial anticoagulation responses with previously established warfarin dosing algorithms. These insights and modeling approaches have application to personalized warfarin therapy.
Knowledge-Driven Multi-Locus Analysis Reveals Gene-Gene Interactions Influencing HDL Cholesterol Level in Two Independent EMR-Linked Biobanks
Stephen D. Turner,Richard L. Berg,James G. Linneman,Peggy L. Peissig,Dana C. Crawford,Joshua C. Denny,Dan M. Roden,Catherine A. McCarty,Marylyn D. Ritchie,Russell A. Wilke
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0019586
Abstract: Genome-wide association studies (GWAS) are routinely being used to examine the genetic contribution to complex human traits, such as high-density lipoprotein cholesterol (HDL-C). Although HDL-C levels are highly heritable (h2~0.7), the genetic determinants identified through GWAS contribute to a small fraction of the variance in this trait. Reasons for this discrepancy may include rare variants, structural variants, gene-environment (GxE) interactions, and gene-gene (GxG) interactions. Clinical practice-based biobanks now allow investigators to address these challenges by conducting GWAS in the context of comprehensive electronic medical records (EMRs). Here we apply an EMR-based phenotyping approach, within the context of routine care, to replicate several known associations between HDL-C and previously characterized genetic variants: CETP (rs3764261, p = 1.22e-25), LIPC (rs11855284, p = 3.92e-14), LPL (rs12678919, p = 1.99e-7), and the APOA1/C3/A4/A5 locus (rs964184, p = 1.06e-5), all adjusted for age, gender, body mass index (BMI), and smoking status. By using a novel approach which censors data based on relevant co-morbidities and lipid modifying medications to construct a more rigorous HDL-C phenotype, we identified an association between HDL-C and TRIB1, a gene which previously resisted identification in studies with larger sample sizes. Through the application of additional analytical strategies incorporating biological knowledge, we further identified 11 significant GxG interaction models in our discovery cohort, 8 of which show evidence of replication in a second biobank cohort. The strongest predictive model included a pairwise interaction between LPL (which modulates the incorporation of triglyceride into HDL) and ABCA1 (which modulates the incorporation of free cholesterol into HDL). These results demonstrate that gene-gene interactions modulate complex human traits, including HDL cholesterol.
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