Genomic architecture of human neuroanatomical diversity

[1]  Peter M Visscher,et al.  Explaining additional genetic variation in complex traits. , 2014, Trends in genetics : TIG.

[2]  Naomi R. Wray,et al.  Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples , 2014, PLoS genetics.

[3]  Eric S. Lander,et al.  A polygenic burden of rare disruptive mutations in schizophrenia , 2014, Nature.

[4]  Ryota Kanai,et al.  Heritability of subcortical brain measures: A perspective for future genome-wide association studies , 2013, NeuroImage.

[5]  R. Plomin,et al.  No Genetic Influence for Childhood Behavior Problems From DNA Analysis , 2013, Journal of the American Academy of Child and Adolescent Psychiatry.

[6]  Jianxin Shi,et al.  Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs , 2013, Nature Genetics.

[7]  Naomi R. Wray,et al.  Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis , 2012, Human molecular genetics.

[8]  Kathryn Roeder,et al.  Common genetic variants, acting additively, are a major source of risk for autism , 2012, Molecular Autism.

[9]  Sang Hong Lee,et al.  Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood , 2012, Bioinform..

[10]  Katie L McMahon,et al.  Genetic and Environmental Influences on Neuroimaging Phenotypes: A Meta-Analytical Perspective on Twin Imaging Studies , 2012, Twin Research and Human Genetics.

[11]  M. Jarvelin,et al.  Common variants at 6q22 and 17q21 are associated with intracranial volume , 2012, Nature Genetics.

[12]  Marisa O. Hollinshead,et al.  Identification of common variants associated with human hippocampal and intracranial volumes , 2012, Nature Genetics.

[13]  Paul M. Thompson,et al.  Common variants at 12q14 and 12q24 are associated with hippocampal volume , 2012, Nature Genetics.

[14]  Wiro J Niessen,et al.  Common variants at 6q22 and 17q21 are associated with intracranial volume , 2012, Nature Genetics.

[15]  Stephan Ripke,et al.  Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs , 2012, Nature Genetics.

[16]  Lorna M. Lopez,et al.  Genome-wide association studies establish that human intelligence is highly heritable and polygenic , 2011, Molecular Psychiatry.

[17]  Stephen M. Smith,et al.  A Bayesian model of shape and appearance for subcortical brain segmentation , 2011, NeuroImage.

[18]  W. G. Hill,et al.  Genome partitioning of genetic variation for complex traits using common SNPs , 2011, Nature Genetics.

[19]  Alan C. Evans,et al.  Genetic and environmental influences on structural variability of the brain in pediatric twin: Deformation based morphometry , 2011, Neuroscience Letters.

[20]  M. Rietschel,et al.  The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology , 2010, Molecular Psychiatry.

[21]  Anderson M. Winkler,et al.  Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies , 2010, NeuroImage.

[22]  Paul M. Thompson,et al.  Genetics of microstructure of cerebral white matter using diffusion tensor imaging , 2010, NeuroImage.

[23]  Joshua M. Korn,et al.  Accurately Assessing the Risk of Schizophrenia Conferred by Rare Copy-Number Variation Affecting Genes with Brain Function , 2010, PLoS genetics.

[24]  Paul M. Thompson,et al.  journal homepage: www.elsevier.com/locate/ynimg Genetic influences on brain asymmetry: A DTI study of 374 twins and siblings , 2022 .

[25]  P. Visscher,et al.  Common SNPs explain a large proportion of heritability for human height , 2011 .

[26]  Nilanjan Chatterjee,et al.  Estimation of effect size distribution from genome-wide association studies and implications for future discoveries , 2010, Nature Genetics.

[27]  Alkes L. Price,et al.  New approaches to population stratification in genome-wide association studies , 2010, Nature Reviews Genetics.

[28]  Anders M. Dale,et al.  Genetic and environmental influences on the size of specific brain regions in midlife: The VETSA MRI study , 2010, NeuroImage.

[29]  Anders M. Dale,et al.  Sex-dependent association of common variants of microcephaly genes with brain structure , 2009, Proceedings of the National Academy of Sciences.

[30]  David H. Alexander,et al.  Fast model-based estimation of ancestry in unrelated individuals. , 2009, Genome research.

[31]  Edwin H. Cook,et al.  Copy-number variations associated with neuropsychiatric conditions , 2008, Nature.

[32]  D. Amaral,et al.  Neuroanatomy of autism , 2008, Trends in Neurosciences.

[33]  Pablo Villoslada,et al.  Analysis and Application of European Genetic Substructure Using 300 K SNP Information , 2008, PLoS genetics.

[34]  K. Taylor,et al.  Genome-Wide Association , 2007, Diabetes.

[35]  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.

[36]  A. Meyer-Lindenberg,et al.  Intermediate phenotypes and genetic mechanisms of psychiatric disorders , 2006, Nature Reviews Neuroscience.

[37]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[38]  J. Lieberman,et al.  Brain volume in first-episode schizophrenia , 2006, British Journal of Psychiatry.

[39]  McCarthyEd,et al.  A Unified Approach , 2005 .

[40]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[41]  A. Meyer-Lindenberg,et al.  The Brain-derived Neurotrophic Factor Val66met Polymorphism and Variation in Human Cortical Morphology , 2022 .

[42]  Abraham Z. Snyder,et al.  A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume , 2004, NeuroImage.

[43]  Toshihiro Tanaka.  The International HapMap Project , 2003, Nature.

[44]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[45]  M. Lynch,et al.  Estimation of pairwise relatedness with molecular markers. , 1999, Genetics.

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

[47]  Kermit Ritland,et al.  A MARKER‐BASED METHOD FOR INFERENCES ABOUT QUANTITATIVE INHERITANCE IN NATURAL POPULATIONS , 1996, Evolution; international journal of organic evolution.

[48]  Robin Thompson,et al.  Average information REML: An efficient algorithm for variance parameter estimation in linear mixed models , 1995 .

[49]  M. Carskadon,et al.  A self-administered rating scale for pubertal development. , 1993, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[50]  S. R. Searle,et al.  Restricted Maximum Likelihood (REML) Estimation of Variance Components in the Mixed Model , 1976 .

[51]  D. Falconer.  The inheritance of liability to certain diseases, estimated from the incidence among relatives , 1965 .

[52]  T. Crow.  GENETIC AND ENVIRONMENTAL INFLUENCES , 2002 .

[53]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.