Genome-wide imaging association study implicates functional activity and glial homeostasis of the caudate in smoking addiction

[1]  Yangding Li,et al.  The implication of frontostriatal circuits in young smokers: A resting‐state study , 2016, Human brain mapping.

[2]  W. Schultz Reward functions of the basal ganglia , 2016, Journal of Neural Transmission.

[3]  K. Delucchi,et al.  An international systematic review of smoking prevalence in addiction treatment. , 2016, Addiction.

[4]  P. Kalivas,et al.  The effects of N-Acetylcysteine on frontostriatal resting-state functional connectivity, withdrawal symptoms and smoking abstinence: A double-blind, placebo-controlled fMRI pilot study. , 2015, Drug and alcohol dependence.

[5]  Mathias J Friedrich,et al.  CRISPR/Cas9 somatic multiplex-mutagenesis for high-throughput functional cancer genomics in mice , 2015, Proceedings of the National Academy of Sciences.

[6]  M. Farah,et al.  Progress and challenges in probing the human brain , 2015, Nature.

[7]  M. Simons,et al.  Actin filament turnover drives leading edge growth during myelin sheath formation in the central nervous system. , 2015, Developmental cell.

[8]  Daniel H. Geschwind,et al.  Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders , 2015, Nature Reviews Genetics.

[9]  Yuzheng Hu,et al.  Impaired functional connectivity within and between frontostriatal circuits and its association with compulsive drug use and trait impulsivity in cocaine addiction. , 2015, JAMA psychiatry.

[10]  Jun S. Liu,et al.  The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans , 2015, Science.

[11]  E. Hol,et al.  Glial fibrillary acidic protein (GFAP) and the astrocyte intermediate filament system in diseases of the central nervous system. , 2015, Current opinion in cell biology.

[12]  Thomas E. Nichols,et al.  Common genetic variants influence human subcortical brain structures , 2015, Nature.

[13]  Laura J. Scott,et al.  Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways , 2015, Nature Neuroscience.

[14]  E. Forbes,et al.  Dissociated Effects of Anticipating Smoking versus Monetary Reward in the Caudate as a Function of Smoking Abstinence , 2014, Biological Psychiatry.

[15]  J. Nigg,et al.  Functional and genomic context in pathway analysis of GWAS data. , 2014, Trends in genetics : TIG.

[16]  I. Deary,et al.  GWAS-based pathway analysis differentiates between fluid and crystallized intelligence , 2014, Genes, brain, and behavior.

[17]  Karen S. Frese,et al.  Systematic permutation testing in GWAS pathway analyses: identification of genetic networks in dilated cardiomyopathy and ulcerative colitis , 2014, BMC Genomics.

[18]  Olivier Delaneau,et al.  Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel , 2014, Nature Communications.

[19]  David L. Molfese,et al.  The role of the habenula in drug addiction , 2014, Front. Hum. Neurosci..

[20]  Thomas E. Nichols,et al.  The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data , 2014, Brain Imaging and Behavior.

[21]  Juan C. Vivar,et al.  Integrative pathway analysis of a genome-wide association study of (V)O(2max) response to exercise training. , 2013, Journal of applied physiology.

[22]  D. Srivastava,et al.  Insights into Rapid Modulation of Neuroplasticity by Brain Estrogens , 2013, Pharmacological Reviews.

[23]  Vivek Prabhakaran,et al.  The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated , 2013, NeuroImage.

[24]  L. Aaltonen,et al.  Lessons from functional analysis of genome-wide association studies. , 2013, Cancer research.

[25]  Eivind Hovig,et al.  Pathway analysis of genetic markers associated with a functional MRI faces paradigm implicates polymorphisms in calcium responsive pathways , 2013, NeuroImage.

[26]  John Ashburner,et al.  SPM: A history , 2012, NeuroImage.

[27]  Susan L. Whitfield-Gabrieli,et al.  Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks , 2012, Brain Connect..

[28]  P. Visscher,et al.  Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits , 2012, Nature Genetics.

[29]  Frank Bradke,et al.  Assembly of a new growth cone after axotomy: the precursor to axon regeneration , 2012, Nature Reviews Neuroscience.

[30]  Jean-Baptiste Poline,et al.  Genetic Variants of FOXP2 and KIAA0319/TTRAP/THEM2 Locus Are Associated with Altered Brain Activation in Distinct Language-Related Regions , 2012, The Journal of Neuroscience.

[31]  O. Delaneau,et al.  A linear complexity phasing method for thousands of genomes , 2011, Nature Methods.

[32]  N. Volkow,et al.  Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications , 2011, Nature Reviews Neuroscience.

[33]  Stavros J. Baloyannis Mitochondria Are Related to Synaptic Pathology in Alzheimer's Disease , 2011, International journal of Alzheimer's disease.

[34]  T. Montine,et al.  White matter lesions defined by diffusion tensor imaging in older adults , 2011, Annals of neurology.

[35]  Zhaoxia Yu,et al.  SNP-based pathway enrichment analysis for genome-wide association studies , 2011, BMC Bioinformatics.

[36]  Frank B Gertler,et al.  The growth cone cytoskeleton in axon outgrowth and guidance. , 2011, Cold Spring Harbor perspectives in biology.

[37]  P. Mazzone,et al.  Pathophysiological Impact of Cigarette Smoke Exposure on the Cerebrovascular System with a Focus on the Blood-brain Barrier: Expanding the Awareness of Smoking Toxicity in an Underappreciated Area , 2010, International journal of environmental research and public health.

[38]  Andrew J. Saykin,et al.  Voxelwise genome-wide association study (vGWAS) , 2010, NeuroImage.

[39]  P. Read Montague,et al.  Human Neuroscience , 2022 .

[40]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[41]  A. Basu,et al.  Tobacco carcinogen induces microglial activation and subsequent neuronal damage , 2009, Journal of neurochemistry.

[42]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[43]  M. Rolls,et al.  Microtubules have opposite orientation in axons and dendrites of Drosophila neurons. , 2008, Molecular biology of the cell.

[44]  A. Graybiel Habits, rituals, and the evaluative brain. , 2008, Annual review of neuroscience.

[45]  I. McGregor,et al.  From ultrasocial to antisocial: a role for oxytocin in the acute reinforcing effects and long‐term adverse consequences of drug use? , 2008, British journal of pharmacology.

[46]  Michael J. Martinez,et al.  Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template , 2007, Human brain mapping.

[47]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[48]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.

[49]  G. Forloni,et al.  JNK signalling: a possible target to prevent neurodegeneration. , 2007, Current pharmaceutical design.

[50]  H. Damasio,et al.  Damage to the Insula Disrupts Addiction to Cigarette Smoking , 2007, Science.

[51]  P. Insel,et al.  Microtubules and Actin Microfilaments Regulate Lipid Raft/Caveolae Localization of Adenylyl Cyclase Signaling Components* , 2006, Journal of Biological Chemistry.

[52]  T. Robbins,et al.  Neural systems of reinforcement for drug addiction: from actions to habits to compulsion , 2005, Nature Neuroscience.

[53]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[54]  P. Insel,et al.  G-protein-coupled Receptor Signaling Components Localize in Both Sarcolemmal and Intracellular Caveolin-3-associated Microdomains in Adult Cardiac Myocytes* , 2005, Journal of Biological Chemistry.

[55]  J. O'Doherty,et al.  Reward representations and reward-related learning in the human brain: insights from neuroimaging , 2004, Current Opinion in Neurobiology.

[56]  S. Oliet,et al.  Physiological contribution of the astrocytic environment of neurons to intersynaptic crosstalk , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[57]  R. Parton,et al.  Lipid Rafts and Caveolae as Portals for Endocytosis: New Insights and Common Mechanisms , 2003, Traffic.

[58]  Richard G. W. Anderson,et al.  Function of Caveolae in Ca2+ Entry and Ca2+‐Dependent Signal Transduction , 2003, Traffic.

[59]  Samuel M. McClure,et al.  Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.

[60]  Y. Benjamini,et al.  THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .

[61]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[62]  William Arbuthnot Sir Lane,et al.  Affinity-purification and characterization of caveolins from the brain: Differential expression of caveolin-1, -2, and -3 in brain endothelial and astroglial cell types , 1998, Brain Research.

[63]  C. Chiamulera,et al.  Common Neural Substrates for the Addictive Properties of Nicotine and Cocaine , 1997, Science.

[64]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[65]  S. Shiffman,et al.  Smoking withdrawal symptoms in two weeks of abstinence , 1976, Psychopharmacology.

[66]  R. Chang,et al.  Neuropathology of cigarette smoking , 2013, Acta Neuropathologica.

[67]  Daniel Mathalon,et al.  A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype. , 2009, Schizophrenia bulletin.

[68]  B. Douglas Ward,et al.  Deconvolution Analysis of FMRI Time Series Data , 2006 .