Other search tools

About this data

The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.

If you have any questions or comments, please contact us.

Results: 1 to 10 of 144

Publication Record

Connections

A unified framework for joint-tissue transcriptome-wide association and Mendelian randomization analysis.
Zhou D, Jiang Y, Zhong X, Cox NJ, Liu C, Gamazon ER
(2020) Nat Genet 52: 1239-1246
MeSH Terms: Animals, Gene Expression Profiling, Genetic Association Studies, Humans, Lipoproteins, LDL, Mendelian Randomization Analysis, Mice, Models, Genetic, Multifactorial Inheritance, Predictive Value of Tests
Show Abstract · Added October 7, 2020
Here, we present a joint-tissue imputation (JTI) approach and a Mendelian randomization framework for causal inference, MR-JTI. JTI borrows information across transcriptomes of different tissues, leveraging shared genetic regulation, to improve prediction performance in a tissue-dependent manner. Notably, JTI includes the single-tissue imputation method PrediXcan as a special case and outperforms other single-tissue approaches (the Bayesian sparse linear mixed model and Dirichlet process regression). MR-JTI models variant-level heterogeneity (primarily due to horizontal pleiotropy, addressing a major challenge of transcriptome-wide association study interpretation) and performs causal inference with type I error control. We make explicit the connection between the genetic architecture of gene expression and of complex traits and the suitability of Mendelian randomization as a causal inference strategy for transcriptome-wide association studies. We provide a resource of imputation models generated from GTEx and PsychENCODE panels. Analysis of biobanks and meta-analysis data, and extensive simulations show substantially improved statistical power, replication and causal mapping rate for JTI relative to existing approaches.
0 Communities
1 Members
0 Resources
10 MeSH Terms
APOE ε4-specific associations of VEGF gene family expression with cognitive aging and Alzheimer's disease.
Moore AM, Mahoney E, Dumitrescu L, De Jager PL, Koran MEI, Petyuk VA, Robinson RA, Ruderfer DM, Cox NJ, Schneider JA, Bennett DA, Jefferson AL, Hohman TJ
(2020) Neurobiol Aging 87: 18-25
MeSH Terms: Aged, Aged, 80 and over, Aging, Apolipoprotein E4, Cognitive Aging, Cognitive Dysfunction, Female, Gene Expression, Genetic Association Studies, Genetic Predisposition to Disease, Genotype, Humans, Male, Neovascularization, Physiologic, Neuropilin-1, Vascular Endothelial Growth Factor A
Show Abstract · Added March 30, 2020
Literature suggests vascular endothelial growth factor A (VEGFA) is protective among those at highest risk for Alzheimer's disease (AD). Apolipoprotein E (APOE) ε4 allele carriers represent a highly susceptible population for cognitive decline, and VEGF may confer distinct protection among APOE-ε4 carriers. We evaluated interactions between cortical expression of 10 VEGF gene family members and APOE-ε4 genotype to clarify which VEGF genes modify the association between APOE-ε4 and cognitive decline. Data were obtained from the Religious Orders Study and Rush Memory and Aging Project (N = 531). Linear regression assessed interactions on global cognition. VEGF genes NRP1 and VEGFA interacted with APOE-ε4 on cognitive performance (p.fdr < 0.05). Higher NRP1 expression correlated with worse outcomes among ε4 carriers but better outcomes among ε4 noncarriers, suggesting NRP1 modifies the risk for poor cognitive scores based on APOE-ε4 status. NRP1 regulates angiogenesis, and literature suggests vessels in APOE-ε4 brains are more prone to leaking, perhaps placing young vessels at risk for ischemia. Results suggest that future therapeutics targeting brain angiogenesis should also consider ε4 allele status.
Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
16 MeSH Terms
A catalog of genetic loci associated with kidney function from analyses of a million individuals.
Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, Tin A, Wang L, Chu AY, Hoppmann A, Kirsten H, Giri A, Chai JF, Sveinbjornsson G, Tayo BO, Nutile T, Fuchsberger C, Marten J, Cocca M, Ghasemi S, Xu Y, Horn K, Noce D, van der Most PJ, Sedaghat S, Yu Z, Akiyama M, Afaq S, Ahluwalia TS, Almgren P, Amin N, Ärnlöv J, Bakker SJL, Bansal N, Baptista D, Bergmann S, Biggs ML, Biino G, Boehnke M, Boerwinkle E, Boissel M, Bottinger EP, Boutin TS, Brenner H, Brumat M, Burkhardt R, Butterworth AS, Campana E, Campbell A, Campbell H, Canouil M, Carroll RJ, Catamo E, Chambers JC, Chee ML, Chee ML, Chen X, Cheng CY, Cheng Y, Christensen K, Cifkova R, Ciullo M, Concas MP, Cook JP, Coresh J, Corre T, Sala CF, Cusi D, Danesh J, Daw EW, de Borst MH, De Grandi A, de Mutsert R, de Vries APJ, Degenhardt F, Delgado G, Demirkan A, Di Angelantonio E, Dittrich K, Divers J, Dorajoo R, Eckardt KU, Ehret G, Elliott P, Endlich K, Evans MK, Felix JF, Foo VHX, Franco OH, Franke A, Freedman BI, Freitag-Wolf S, Friedlander Y, Froguel P, Gansevoort RT, Gao H, Gasparini P, Gaziano JM, Giedraitis V, Gieger C, Girotto G, Giulianini F, Gögele M, Gordon SD, Gudbjartsson DF, Gudnason V, Haller T, Hamet P, Harris TB, Hartman CA, Hayward C, Hellwege JN, Heng CK, Hicks AA, Hofer E, Huang W, Hutri-Kähönen N, Hwang SJ, Ikram MA, Indridason OS, Ingelsson E, Ising M, Jaddoe VWV, Jakobsdottir J, Jonas JB, Joshi PK, Josyula NS, Jung B, Kähönen M, Kamatani Y, Kammerer CM, Kanai M, Kastarinen M, Kerr SM, Khor CC, Kiess W, Kleber ME, Koenig W, Kooner JS, Körner A, Kovacs P, Kraja AT, Krajcoviechova A, Kramer H, Krämer BK, Kronenberg F, Kubo M, Kühnel B, Kuokkanen M, Kuusisto J, La Bianca M, Laakso M, Lange LA, Langefeld CD, Lee JJ, Lehne B, Lehtimäki T, Lieb W, Lifelines Cohort Study, Lim SC, Lind L, Lindgren CM, Liu J, Liu J, Loeffler M, Loos RJF, Lucae S, Lukas MA, Lyytikäinen LP, Mägi R, Magnusson PKE, Mahajan A, Martin NG, Martins J, März W, Mascalzoni D, Matsuda K, Meisinger C, Meitinger T, Melander O, Metspalu A, Mikaelsdottir EK, Milaneschi Y, Miliku K, Mishra PP, V. A. Million Veteran Program, Mohlke KL, Mononen N, Montgomery GW, Mook-Kanamori DO, Mychaleckyj JC, Nadkarni GN, Nalls MA, Nauck M, Nikus K, Ning B, Nolte IM, Noordam R, O'Connell J, O'Donoghue ML, Olafsson I, Oldehinkel AJ, Orho-Melander M, Ouwehand WH, Padmanabhan S, Palmer ND, Palsson R, Penninx BWJH, Perls T, Perola M, Pirastu M, Pirastu N, Pistis G, Podgornaia AI, Polasek O, Ponte B, Porteous DJ, Poulain T, Pramstaller PP, Preuss MH, Prins BP, Province MA, Rabelink TJ, Raffield LM, Raitakari OT, Reilly DF, Rettig R, Rheinberger M, Rice KM, Ridker PM, Rivadeneira F, Rizzi F, Roberts DJ, Robino A, Rossing P, Rudan I, Rueedi R, Ruggiero D, Ryan KA, Saba Y, Sabanayagam C, Salomaa V, Salvi E, Saum KU, Schmidt H, Schmidt R, Schöttker B, Schulz CA, Schupf N, Shaffer CM, Shi Y, Smith AV, Smith BH, Soranzo N, Spracklen CN, Strauch K, Stringham HM, Stumvoll M, Svensson PO, Szymczak S, Tai ES, Tajuddin SM, Tan NYQ, Taylor KD, Teren A, Tham YC, Thiery J, Thio CHL, Thomsen H, Thorleifsson G, Toniolo D, Tönjes A, Tremblay J, Tzoulaki I, Uitterlinden AG, Vaccargiu S, van Dam RM, van der Harst P, van Duijn CM, Velez Edward DR, Verweij N, Vogelezang S, Völker U, Vollenweider P, Waeber G, Waldenberger M, Wallentin L, Wang YX, Wang C, Waterworth DM, Bin Wei W, White H, Whitfield JB, Wild SH, Wilson JF, Wojczynski MK, Wong C, Wong TY, Xu L, Yang Q, Yasuda M, Yerges-Armstrong LM, Zhang W, Zonderman AB, Rotter JI, Bochud M, Psaty BM, Vitart V, Wilson JG, Dehghan A, Parsa A, Chasman DI, Ho K, Morris AP, Devuyst O, Akilesh S, Pendergrass SA, Sim X, Böger CA, Okada Y, Edwards TL, Snieder H, Stefansson K, Hung AM, Heid IM, Scholz M, Teumer A, Köttgen A, Pattaro C
(2019) Nat Genet 51: 957-972
MeSH Terms: Chromosome Mapping, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, Inheritance Patterns, Kidney Function Tests, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Renal Insufficiency, Chronic, Uromodulin
Show Abstract · Added March 3, 2020
Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
0 Communities
1 Members
0 Resources
MeSH Terms
Multi-tissue transcriptome analyses identify genetic mechanisms underlying neuropsychiatric traits.
Gamazon ER, Zwinderman AH, Cox NJ, Denys D, Derks EM
(2019) Nat Genet 51: 933-940
MeSH Terms: Algorithms, Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mental Disorders, Organ Specificity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Transcriptome
Show Abstract · Added July 17, 2019
The genetic architecture of psychiatric disorders is characterized by a large number of small-effect variants located primarily in non-coding regions, suggesting that the underlying causal effects may influence disease risk by modulating gene expression. We provide comprehensive analyses using transcriptome data from an unprecedented collection of tissues to gain pathophysiological insights into the role of the brain, neuroendocrine factors (adrenal gland) and gastrointestinal systems (colon) in psychiatric disorders. In each tissue, we perform PrediXcan analysis and identify trait-associated genes for schizophrenia (n associations = 499; n unique genes = 275), bipolar disorder (n associations = 17; n unique genes = 13), attention deficit hyperactivity disorder (n associations = 19; n unique genes = 12) and broad depression (n associations = 41; n unique genes = 31). Importantly, both PrediXcan and summary-data-based Mendelian randomization/heterogeneity in dependent instruments analyses suggest potentially causal genes in non-brain tissues, showing the utility of these tissues for mapping psychiatric disease genetic predisposition. Our analyses further highlight the importance of joint tissue approaches as 76% of the genes were detected only in difficult-to-acquire tissues.
0 Communities
1 Members
0 Resources
MeSH Terms
Functionally oriented analysis of cardiometabolic traits in a trans-ethnic sample.
Petty LE, Highland HM, Gamazon ER, Hu H, Karhade M, Chen HH, de Vries PS, Grove ML, Aguilar D, Bell GI, Huff CD, Hanis CL, Doddapaneni H, Munzy DM, Gibbs RA, Ma J, Parra EJ, Cruz M, Valladares-Salgado A, Arking DE, Barbeira A, Im HK, Morrison AC, Boerwinkle E, Below JE
(2019) Hum Mol Genet 28: 1212-1224
MeSH Terms: Adult, Aged, Blood Pressure, Body Mass Index, Chromosome Mapping, Ethnic Groups, European Continental Ancestry Group, Female, Forecasting, Genetic Association Studies, Genome-Wide Association Study, Humans, Male, Metabolome, Middle Aged, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Transcriptome
Show Abstract · Added February 15, 2019
Interpretation of genetic association results is difficult because signals often lack biological context. To generate hypotheses of the functional genetic etiology of complex cardiometabolic traits, we estimated the genetically determined component of gene expression from common variants using PrediXcan (1) and determined genes with differential predicted expression by trait. PrediXcan imputes tissue-specific expression levels from genetic variation using variant-level effect on gene expression in transcriptome data. To explore the value of imputed genetically regulated gene expression (GReX) models across different ancestral populations, we evaluated imputed expression levels for predictive accuracy genome-wide in RNA sequence data in samples drawn from European-ancestry and African-ancestry populations and identified substantial predictive power using European-derived models in a non-European target population. We then tested the association of GReX on 15 cardiometabolic traits including blood lipid levels, body mass index, height, blood pressure, fasting glucose and insulin, RR interval, fibrinogen level, factor VII level and white blood cell and platelet counts in 15 755 individuals across three ancestry groups, resulting in 20 novel gene-phenotype associations reaching experiment-wide significance across ancestries. In addition, we identified 18 significant novel gene-phenotype associations in our ancestry-specific analyses. Top associations were assessed for additional support via query of S-PrediXcan (2) results derived from publicly available genome-wide association studies summary data. Collectively, these findings illustrate the utility of transcriptome-based imputation models for discovery of cardiometabolic effect genes in a diverse dataset.
© The Author(s) 2019. Published by Oxford University Press.
0 Communities
1 Members
0 Resources
19 MeSH Terms
Nuclear-Mitochondrial interactions influence susceptibility to HIV-associated neurocognitive impairment.
Smieszek S, Jia P, Samuels DC, Zhao Z, Barnholtz-Sloan J, Kaur H, Letendre S, Ellis R, Franklin DR, Hulgan T, Kallianpur A, Bush WS, CHARTER Study Group
(2019) Mitochondrion 46: 247-255
MeSH Terms: AIDS Dementia Complex, Cell Nucleus, Continental Population Groups, Genetic Association Studies, HIV Infections, Haplotypes, Humans, Mitochondria, Mitochondrial Proteins, Nuclear Proteins, Polymorphism, Single Nucleotide, Prospective Studies
Show Abstract · Added December 11, 2019
HIV-associated neurocognitive impairment (NCI) is a term established to capture a wide spectrum of HIV related neurocognitive deficits ranging in severity from asymptomatic to dementia. The genetic underpinnings of this complex phenotype are incompletely understood. Mitochondrial function has long been thought to play a role in neurodegeneration, along with iron metabolism and transport. In this work, we aimed to characterize the interplay of mitochondrial DNA (mtDNA) haplogroup and nuclear genetic associations to NCI phenotypes in the CHARTER cohort, encompassing 1025 individuals of European-descent, African-descent, or admixed Hispanic. We first employed a polygenic modeling approach to investigate the global effect of previous marginally associated nuclear SNPs, and to examine how the polygenic effect of these SNPs is influenced by mtDNA haplogroups. We see evidence of a significant interaction between nuclear SNPs en masse and mtDNA haplogroups within European-descent and African-descent individuals. Subsequently, we performed an analysis of each SNP by mtDNA haplogroup, and detected significant interactions between two nuclear SNPs (rs17160128 and rs12460243) and European haplogroups. These findings, which require validation in larger cohorts, indicate a potential new role for nuclear-mitochondrial DNA interactions in susceptibility to NCI and shed light onto the pathophysiology of this neurocognitive phenotype.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
0 Communities
1 Members
0 Resources
MeSH Terms
Transcriptional profiling of the ductus arteriosus: Comparison of rodent microarrays and human RNA sequencing.
Yarboro MT, Durbin MD, Herington JL, Shelton EL, Zhang T, Ebby CG, Stoller JZ, Clyman RI, Reese J
(2018) Semin Perinatol 42: 212-220
MeSH Terms: Animals, Animals, Newborn, Ductus Arteriosus, Embryo, Mammalian, Gene Expression Profiling, Gene Expression Regulation, Developmental, Genetic Association Studies, Humans, Microarray Analysis, Models, Animal, Rodentia, Sequence Analysis, RNA, Species Specificity, Vascular Patency
Show Abstract · Added November 26, 2018
DA closure is crucial for the transition from fetal to neonatal life. This closure is supported by changes to the DA's signaling and structural properties that distinguish it from neighboring vessels. Examining transcriptional differences between these vessels is key to identifying genes or pathways responsible for DA closure. Several microarray studies have explored the DA transcriptome in animal models but varied experimental designs have led to conflicting results. Thorough transcriptomic analysis of the human DA has yet to be performed. A clear picture of the DA transcriptome is key to guiding future research endeavors, both to allow more targeted treatments in the clinical setting, and to understand the basic biology of DA function. In this review, we use a cross-species cross-platform analysis to consider all available published rodent microarray data and novel human RNAseq data in order to provide high priority candidate genes for consideration in future DA studies.
Copyright © 2018 Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
14 MeSH Terms
Loss of CENP-F Results in Dilated Cardiomyopathy with Severe Disruption of Cardiac Myocyte Architecture.
Manalo A, Schroer AK, Fenix AM, Shancer Z, Coogan J, Brolsma T, Burnette DT, Merryman WD, Bader DM
(2018) Sci Rep 8: 7546
MeSH Terms: Animals, Cardiomyopathy, Dilated, Chromosomal Proteins, Non-Histone, Disease Models, Animal, Genetic Association Studies, Genetic Predisposition to Disease, Heart Failure, Humans, Intercellular Junctions, Loss of Function Mutation, Mice, Microfilament Proteins, Microtubules, Myocytes, Cardiac, Polymorphism, Single Nucleotide, Stroke Volume
Show Abstract · Added March 27, 2019
Centromere-binding protein F (CENP-F) is a very large and complex protein with many and varied binding partners including components of the microtubule network. Numerous CENP-F functions impacting diverse cellular behaviors have been identified. Importantly, emerging data have shown that CENP-F loss- or gain-of-function has critical effects on human development and disease. Still, it must be noted that data at the single cardiac myocyte level examining the impact of CENP-F loss-of-function on fundamental cellular behavior is missing. To address this gap in our knowledge, we analyzed basic cell structure and function in cardiac myocytes devoid of CENP-F. We found many diverse structural abnormalities including disruption of the microtubule network impacting critical characteristics of the cardiac myocyte. This is the first report linking microtubule network malfunction to cardiomyopathy. Importantly, we also present data demonstrating a direct link between a CENP-F single nucleotide polymorphism (snp) and human cardiac disease. In a proximate sense, these data examining CENP-F function explain the cellular basis underlying heart disease in this genetic model and, in a larger sense, they will hopefully provide a platform upon which the field can explore diverse cellular outcomes in wide-ranging areas of research on this critical protein.
0 Communities
1 Members
0 Resources
16 MeSH Terms
Opportunities and Challenges in Cardiovascular Pharmacogenomics: From Discovery to Implementation.
Roden DM, Van Driest SL, Wells QS, Mosley JD, Denny JC, Peterson JF
(2018) Circ Res 122: 1176-1190
MeSH Terms: Biological Variation, Individual, Biotransformation, Cardiovascular Agents, Drug Development, Drug-Related Side Effects and Adverse Reactions, Forecasting, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Testing, Genetic Variation, Genomics, Genotyping Techniques, Human Genome Project, Humans, Pharmacogenetics, Precision Medicine, Randomized Controlled Trials as Topic, Risk Assessment, Sample Size
Show Abstract · Added March 24, 2020
This review will provide an overview of the principles of pharmacogenomics from basic discovery to implementation, encompassing application of tools of contemporary genome science to the field (including areas of apparent divergence from disease-based genomics), a summary of lessons learned from the extensively studied drugs clopidogrel and warfarin, the current status of implementing pharmacogenetic testing in practice, the role of genomics and related tools in the drug development process, and a summary of future opportunities and challenges.
© 2018 American Heart Association, Inc.
0 Communities
1 Members
0 Resources
MeSH Terms
APOE genotype modifies the association between central arterial stiffening and cognition in older adults.
Cambronero FE, Liu D, Neal JE, Moore EE, Gifford KA, Terry JG, Nair S, Pechman KR, Osborn KE, Hohman TJ, Bell SP, Sweatt JD, Wang TJ, Beckman JA, Carr JJ, Jefferson AL
(2018) Neurobiol Aging 67: 120-127
MeSH Terms: Aged, Aged, 80 and over, Aging, Alzheimer Disease, Apolipoproteins E, Cognition, Cognitive Dysfunction, Female, Genetic Association Studies, Genotype, Humans, Magnetic Resonance Imaging, Male, Pulse Wave Analysis, Risk Factors, Vascular Stiffness
Show Abstract · Added September 11, 2018
Arterial stiffening is associated with cognitive impairment and prodromal Alzheimer's disease. This study tested the interaction between arterial stiffening and an Alzheimer's disease genetic risk factor (apolipoprotein E [APOE] genotype) on cognition among older adults. Vanderbilt Memory & Aging Project participants with normal cognition (n = 162, 72 ± 7 years, 29% APOE-ε4 carrier) and mild cognitive impairment (n = 121, 73 ± 8 years, 42% APOE-ε4 carrier) completed neuropsychological assessment and cardiac MRI to assess aortic stiffening using pulse wave velocity (PWV, m/s). Linear regression models stratified by cognitive diagnosis related aortic PWV × APOE-ε4 status to neuropsychological performances, adjusting for demographic and vascular risk factors. PWV × APOE-ε4 related to poorer performance on measures of lexical retrieval (β = -0.29, p = 0.01), executive function (β = -0.44, p = 0.02), and episodic memory (β = -3.07, p = 0.02). Among participants with higher aortic PWV, APOE-ε4 modified the association between central arterial stiffening and cognition, such that carriers had worse performances than noncarriers. Findings add to a growing body of evidence for APOE-vascular interactions on cognition in older adults and warrant further research into less heart-healthy cohorts where the association between PWV and cognition among older adults might be stronger.
Copyright © 2018 Elsevier Inc. All rights reserved.
0 Communities
4 Members
0 Resources
16 MeSH Terms