Brain/physiopathology; Chromosomes, Human, Pair 12/genetics; Genetic Loci; Genetic Markers; Genome-Wide Association Study; Hippocampus/physiopathology; Humans; Meta-Analysis as Topic; Neuroimaging; Polymorphism, Single Nucleotide/genetics
Abstract :
[en] Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 x 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 x 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 x 10(-7)).
Jack, C.R. Jr. et al. Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease. Alzheimers Dement. 7, 474-485 e4 (2011).
Simić, G., Kostovic, I., Winblad, B. & Bogdanovic, N. Volume and number of neurons of the human hippocampal formation in normal aging and Alzheimer's disease. J. Comp. Neurol. 379, 482-494 (1997). (Pubitemid 27111150)
Wright, I.C. et al. Meta-analysis of regional brain volumes in schizophrenia. Am. J. Psychiatry 157, 16-25 (2000). (Pubitemid 30027416)
Videbech, P. & Ravnkilde, B. Hippocampal volume and depression: a meta-analysis of MRI studies. Am. J. Psychiatry 161, 1957-1966 (2004). (Pubitemid 39441394)
Keller, S.S. & Roberts, N. Voxel-based morphometry of temporal lobe epilepsy: an introduction and review of the literature. Epilepsia 49, 741-757 (2008). (Pubitemid 351652429)
Peper, J.S., Brouwer, R.M., Boomsma, D.I., Kahn, R.S. & Hulshoff Pol, H.E. Genetic influences on human brain structure: a review of brain imaging studies in twins. Hum. Brain Mapp. 28, 464-473 (2007). (Pubitemid 46849363)
Kremen, W.S. et al. Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study. Neuroimage 49, 1213-1223 (2010).
Maguire, E.A. et al. Navigation-related structural change in the hippocampi of taxi drivers. Proc. Natl. Acad. Sci. USA 97, 4398-4403 (2000). (Pubitemid 30226144)
Burgess, N., Maguire, E.A. & O'Keefe, J. The human hippocampus and spatial and episodic memory. Neuron 35, 625-641 (2002). (Pubitemid 35223024)
Snyder, J.S., Soumier, A., Brewer, M., Pickel, J. & Cameron, H.A. Adult hippocampal neurogenesis buffers stress responses and depressive behaviour. Nature 476, 458-461 (2011).
Freitag, C.M. et al. Total brain volume and corpus callosum size in medication-naive adolescents and young adults with autism spectrum disorder. Biol. Psychiatry 66, 316-319 (2009).
Stanfield, A.C. et al. Towards a neuroanatomy of autism: a systematic review and meta-analysis of structural magnetic resonance imaging studies. Eur. Psychiatry 23, 289-299 (2008). (Pubitemid 351938706)
Posthuma, D. et al. The association between brain volume and intelligence is of genetic origin. Nat. Neurosci. 5, 83-84 (2002). (Pubitemid 34121567)
Fears, S.C. et al. Identifying heritable brain phenotypes in an extended pedigree of vervet monkeys. J. Neurosci. 29, 2867-2875 (2009).
Rogers, J. et al. On the genetic architecture of cortical folding and brain volume in primates. Neuroimage 53, 1103-1108 (2010).
Patenaude, B., Smith, S.M., Kennedy, D.N. & Jenkinson, M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage 56, 907-922 (2011).
Fischl, B. et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341-355 (2002). (Pubitemid 34162530)
Buckner, R.L. 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. Neuroimage 23, 724-738 (2004). (Pubitemid 39370623)
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genome-wide association scans. Bioinformatics 26, 2190-2191 (2010).
Han, B. & Eskin, E. Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies. Am. J. Hum. Genet. 88, 586-598 (2011).
Bis, J.C. et al. Common variants at 12q14 and 12q24 are associated with hippocampal volume. Nat. Genet. published online (15 April 2012; doi:10.1038/ng.2237).
Ripke, S. et al. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969-976 (2011).
Sklar, P. et al. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat. Genet. 43, 977-983 (2011).
Li, M.X., Gui, H.S., Kwan, J.S. & Sham, P.C. GATES: a rapid and powerful gene-based association test using extended Simes procedure. Am. J. Hum. Genet. 88, 283-293 (2011).
Bao, Y. et al. Expression and evolutionary conservation of the tescalcin gene during development. Gene expression patterns. Gene Exp. Patterns 9, 273-281 (2009).
Baumgartner, M., Patel, H. & Barber, D.L. Na +H+ exchanger NHE1 as plasma membrane scaffold in the assembly of signaling complexes. Am. J. Physiol. Cell Physiol. 287, C844-C850 (2004). (Pubitemid 39238307)
Slepkov, E.R., Rainey, J.K., Sykes, B.D. & Fliegel, L. Structural and functional analysis of the Na +H+ exchanger. Biochem. J. 401, 623-633 (2007).
Levay, K. & Slepak, V.Z. Tescalcin is an essential factor in megakaryocytic differentiation associated with Ets family gene expression. J. Clin. Invest. 117, 2672-2683 (2007). (Pubitemid 47494367)
Levay, K. & Slepak, V.Z. Up-or downregulation of tescalcin in HL-60 cells is associated with their differentiation to either granulocytic or macrophage-like lineage. Exp. Cell Res. 316, 1254-1262 (2010).
Lango Allen, H. et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467, 832-838 (2010).
Gudbjartsson, D.F. et al. Many sequence variants affecting diversity of adult human height. Nat. Genet. 40, 609-615 (2008). (Pubitemid 351601211)
Sanna, S. et al. Common variants in the GDF5-UQCC region are associated with variation in human height. Nat. Genet. 40, 198-203 (2008). (Pubitemid 351171401)
Weedon, M.N. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nat. Genet. 40, 575-583 (2008). (Pubitemid 351601210)
Fusco, A. & Fedele, M. Roles of HMGA proteins in cancer. Nat. Rev. Cancer 7, 899-910 (2007). (Pubitemid 350165857)
Litterman, N. et al. An OBSL1-Cul7Fbxw8 ubiquitin ligase signaling mechanism regulates Golgi morphology and dendrite patterning. PLoS Biol. 9, e1001060 (2011).
Wright, M.J. & Martin, N.G. Brisbane adolescent twin study: outline of study methods and research projects. Aust. J. Psychol. 56, 65-78 (2004). (Pubitemid 39216642)
Vogel, W. Discoidin domain receptors: structural relations and functional implications. FASEB J. 13 (suppl), S77-S82 (1999).
Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362-9367 (2009).
Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336-2337 (2010).
Johnson, M.B. et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 62, 494-509 (2009).
Smith, S.M. et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23 (suppl 1), S208-S219 (2004). (Pubitemid 39421720)
Zhang, Y., Brady, M. & Smith, S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging 20, 45-57 (2001). (Pubitemid 32293419)
Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825-841 (2002). (Pubitemid 35317016)
Morey, R.A. et al. A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. Neuroimage 45, 855-866 (2009).
Pardoe, H.R., Pell, G.S., Abbott, D.F. & Jackson, G.D. Hippocampal volume assessment in temporal lobe epilepsy: how good is automated segmentation? Epilepsia 50, 2586-2592 (2009).
Morey, R.A. et al. Scan-rescan reliability of subcortical brain volumes derived from automated segmentation. Hum. Brain Mapp. 31, 1751-1762 (2010).
Pantel, J. et al. A new method for the in vivo volumetric measurement of the human hippocampus with high neuroanatomical accuracy. Hippocampus 10, 752-758 (2000).
Morra, J.H. et al. Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls. Neuroimage 43, 59-68 (2008).
Almasy, L. & Blangero, J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am. J. Hum. Genet. 62, 1198-1211 (1998). (Pubitemid 28199022)
Purcell, S., Cherny, S.S. & Sham, P.C. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19, 149-150 (2003). (Pubitemid 36150192)
Pei, Y.F., Li, J., Zhang, L., Papasian, C.J. & Deng, H.W. Analyses and comparison of accuracy of different genotype imputation methods. PLoS ONE 3, e3551 (2008).
Marchini, J. & Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499-511 (2010).
Allen, A.S., Martin, E.R., Qin, X. & Li, Y.J. Genetic association tests based on ranks (GATOR) for quantitative traits with and without censoring. Genet. Epidemiol. 30, 248-258 (2006).
Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906-913 (2007). (Pubitemid 47014502)
Browning, B.L. & Browning, S.R. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84, 210-223 (2009).
Durston, S. et al. Differential effects of DRD4 and DAT1 genotype on fronto-striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls. Mol. Psychiatry 10, 678-685 (2005). (Pubitemid 40961738)
Dick, D.M. et al. Genome-wide association study of conduct disorder symptomatology. Mol. Psychiatry 16, 800-808 (2011).
Stein, J.L. et al. Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search. Mol. Psychiatry 16, 927-937, 881 (2011).
Chen, W.M. & Abecasis, G.R. Family-based association tests for genomewide association scans. Am. J. Hum. Genet. 81, 913-926 (2007). (Pubitemid 47580246)
Aulchenko, Y.S., Struchalin, M.V. & van Duijn, C.M. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11, 134 (2010).
Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997-1004 (1999).
Li, M.X., Sham, P.C., Cherny, S.S. & Song, Y.Q. A knowledge-based weighting framework to boost the power of genome-wide association studies. PLoS ONE 5, e14480 (2010).
Li, J. & Ji, L. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity 95, 221-227 (2005). (Pubitemid 43093236)
Kasperaviciūte, D. et al. Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study. Brain 133, 2136-2147 (2010).
Trabzuni, D. et al. Quality control parameters on a large dataset of regionally-dissected human control brains for whole genome expression studies. J. Neurochem. 119, 275-282 (2011).
Heinzen, E.L. et al. Tissue-specific genetic control of splicing: implications for the study of complex traits. PLoS Biol. 6, e1 (2008).