Genome-wide imaging association study implicates functional activity and glial homeostasis of the caudate in smoking addiction
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D. Molfese | C. Amos | P. Baldwin | R. Salas | Humsini Viswanath | R. Krahe | A. Titus | Yafang Li | D. Qian | Jennifer L. Jin | Yixuan He | Maxime Vaissié
[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 .