A sex-stratified analysis of the genetic architecture of human brain anatomy.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
13 Sep 2024
13 Sep 2024
Historique:
received:
28
08
2023
accepted:
30
08
2024
medline:
14
9
2024
pubmed:
14
9
2024
entrez:
13
9
2024
Statut:
epublish
Résumé
Large biobanks have dramatically advanced our understanding of genetic influences on human brain anatomy. However, most studies have combined rather than compared male and female participants. Here we screen for sex differences in the common genetic architecture of over 1000 neuroanatomical phenotypes in the UK Biobank and establish a general concordance between male and female participants in heritability estimates, genetic correlations, and variant-level effects. Notable exceptions include higher mean heritability in the female group for regional volume and surface area phenotypes; between-sex genetic correlations that are significantly below 1 in the insula and parietal cortex; and a common variant with stronger effect in male participants mapping to RBFOX1 - a gene linked to multiple neuropsychiatric disorders more common in men. This work suggests that common variant influences on human brain anatomy are largely consistent between males and females, with a few exceptions that will guide future research in growing datasets.
Identifiants
pubmed: 39271676
doi: 10.1038/s41467-024-52244-2
pii: 10.1038/s41467-024-52244-2
doi:
Substances chimiques
RBFOX1 protein, human
0
RNA Splicing Factors
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8041Subventions
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)
ID : ZIA MH002949-07
Organisme : Intramural NIH HHS
ID : ZIC MH002960
Pays : United States
Organisme : U.S. Department of Health & Human Services | NIH | Center for Scientific Review (NIH Center for Scientific Review)
ID : T32HG010464
Informations de copyright
© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
Références
Grasby, K. L. et al. The genetic architecture of the human cerebral cortex. Science 367, eaay6690 (2020).
pubmed: 32193296
pmcid: 7295264
doi: 10.1126/science.aay6690
Smith, S. M. et al. An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank. Nat. Neurosci. 24, 737–745 (2021).
pubmed: 33875891
pmcid: 7610742
doi: 10.1038/s41593-021-00826-4
Satizabal, C. L. et al. Genetic architecture of subcortical brain structures in 38,851 individuals. Nat. Genet. 51, 1624–1636 (2019).
pubmed: 31636452
pmcid: 7055269
doi: 10.1038/s41588-019-0511-y
Sudlow, C. et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
pubmed: 25826379
pmcid: 4380465
doi: 10.1371/journal.pmed.1001779
Thompson, P. ENIGMA and global neuroscience: A decade of largescale studies of the brain in health and disease across more Than 40 countries. Transl. Psychiatry. 10, 100 (2020).
pubmed: 32198361
pmcid: 7083923
doi: 10.1038/s41398-020-0705-1
Elliott, L. T. et al. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 562, 210–216 (2018).
pubmed: 30305740
pmcid: 6786974
doi: 10.1038/s41586-018-0571-7
Zhao, B. et al. Heritability of regional brain volumes in large-scale neuroimaging and genetic studies. Cereb. Cortex 29, 2904–2914 (2019).
pubmed: 30010813
doi: 10.1093/cercor/bhy157
Ritchie, S. J. et al. Sex Differences in the adult human brain: Evidence from 5216 UK Biobank participants. Cereb. Cortex 28, 2959–2975 (2018).
pubmed: 29771288
pmcid: 6041980
doi: 10.1093/cercor/bhy109
Williams, C. M., Peyre, H., Toro, R. & Ramus, F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum. Brain Mapp. 42, 4623–4642 (2021).
pubmed: 34268815
pmcid: 8410561
doi: 10.1002/hbm.25572
Williams, C. M., Peyre, H., Toro, R. & Ramus, F. Sex differences in the brain are not reduced to differences in body size. Neurosci. Biobehav. Rev. 130, 509–511 (2021).
pubmed: 34520800
doi: 10.1016/j.neubiorev.2021.09.015
Liu, S., Seidlitz, J., Blumenthal, J. D., Clasen, L. S. & Raznahan, A. Integrative structural, functional, and transcriptomic analyses of sex-biased brain organization in humans. Proc. Natl. Acad. Sci. USA 117, 18788–18798 (2020).
pubmed: 32690678
pmcid: 7414084
doi: 10.1073/pnas.1919091117
DeCasien, A. R., Guma, E., Liu, S. & Raznahan, A. Sex differences in the human brain: a roadmap for more careful analysis and interpretation of a biological reality. Biol. Sex Differ. 13, 43 (2022).
pubmed: 35883159
pmcid: 9327177
doi: 10.1186/s13293-022-00448-w
Lotze, M. et al. Novel findings from 2838 adult brains on sex differences in gray matter brain volume. Sci. Rep. 9, 1671 (2019).
pubmed: 30737437
pmcid: 6368548
doi: 10.1038/s41598-018-38239-2
Premachandran, H., Zhao, M. & Arruda-Carvalho, M. Sex differences in the development of the rodent corticolimbic system. Front. Neurosci. 14, 583477 (2020).
pubmed: 33100964
pmcid: 7554619
doi: 10.3389/fnins.2020.583477
Vousden, D. A. et al. Impact of X/Y genes and sex hormones on mouse neuroanatomy. Neuroimage 173, 551–563 (2018).
pubmed: 29501873
doi: 10.1016/j.neuroimage.2018.02.051
Neufang, S. et al. Sex differences and the impact of steroid hormones on the developing human brain. Cereb. Cortex 19, 464–473 (2008).
pubmed: 18550597
doi: 10.1093/cercor/bhn100
McCarthy, M. M., Arnold, A. P., Ball, G. F., Blaustein, J. D. & De Vries, G. J. Sex differences in the brain: the not so inconvenient truth. J. Neurosci. 32, 2241–2247 (2012).
pubmed: 22396398
pmcid: 3295598
doi: 10.1523/JNEUROSCI.5372-11.2012
McCarthy, M. M., Nugent, B. M. & Lenz, K. M. Neuroimmunology and neuroepigenetics in the establishment of sex differences in the brain. Nat. Rev. Neurosci. 18, 471–484 (2017).
pubmed: 28638119
pmcid: 5771241
doi: 10.1038/nrn.2017.61
McCarthy, M. M. A new view of sexual differentiation of mammalian brain. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 206, 369–378 (2020).
pubmed: 31705197
doi: 10.1007/s00359-019-01376-8
Corre, C. et al. Separate effects of sex hormones and sex chromosomes on brain structure and function revealed by high-resolution magnetic resonance imaging and spatial navigation assessment of the Four Core Genotype mouse model. Brain Struct. Funct. 221, 997–1016 (2016).
pubmed: 25445841
doi: 10.1007/s00429-014-0952-0
Wright, C. L., Schwarz, J. S., Dean, S. L. & McCarthy, M. M. Cellular mechanisms of estradiol-mediated sexual differentiation of the brain. Trends Endocrinol. Metab. 21, 553–561 (2010).
pubmed: 20813326
pmcid: 2941875
doi: 10.1016/j.tem.2010.05.004
Mallard, T. T. et al. X-chromosome influences on neuroanatomical variation in humans. Nat. Neurosci. 24, 1216–1224 (2021).
pubmed: 34294918
doi: 10.1038/s41593-021-00890-w
Warling, A. et al. Sex chromosome dosage effects on white matter structure in the human brain. Cereb. Cortex 31, 5339–5353 (2021).
pubmed: 34117759
pmcid: 8568008
doi: 10.1093/cercor/bhab162
Guma, E. et al. A cross-species study of sex chromosome dosage effects on human and mouse brain anatomy. J. Neurosci. 43, 1321–1333 (2023).
Supekar, K. et al. Deep learning identifies robust gender differences in functional brain organization and their dissociable links to clinical symptoms in autism. Br. J. Psychiatry 1–8, https://doi.org/10.1192/bjp.2022.13 (2022).
Guma, E. et al. Neuroanatomical and symptomatic sex differences in individuals at clinical high risk for psychosis. Front. Psychiatry 8, 291 (2017).
pubmed: 29312018
pmcid: 5744013
doi: 10.3389/fpsyt.2017.00291
Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171 (2016).
pubmed: 27437579
pmcid: 4990127
doi: 10.1038/nature18933
Fogel, B. L. et al. RBFOX1 regulates both splicing and transcriptional networks in human neuronal development. Hum. Mol. Genet. 21, 4171–4186 (2012).
pubmed: 22730494
pmcid: 3441119
doi: 10.1093/hmg/dds240
Cross-Disorder, Group. of the Psychiatric Genomics Consortium. Genomic relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders. Cell 179, 1469–1482 (2019).
Visscher, P. M. et al. 10 Years of GWAS discovery: Biology, function, and translation. Am. J. Hum. Genet. 101, 5–22 (2017).
pubmed: 28686856
pmcid: 5501872
doi: 10.1016/j.ajhg.2017.06.005
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).
pubmed: 21167468
pmcid: 3014363
doi: 10.1016/j.ajhg.2010.11.011
Bernabeu, E. et al. Sex differences in genetic architecture in the UK Biobank. Nat. Genet. 53, 1283–1289 (2021).
pubmed: 34493869
doi: 10.1038/s41588-021-00912-0
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
pubmed: 25885710
pmcid: 4401657
doi: 10.1371/journal.pcbi.1004219
Watanabe, K., Taskesen, E., van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).
pubmed: 29184056
pmcid: 5705698
doi: 10.1038/s41467-017-01261-5
Yeo, B. T. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).
pubmed: 21653723
doi: 10.1152/jn.00338.2011
Wagstyl, K. et al. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 12, RP86933 (2024).
Hibar, D. P. et al. Common genetic variants influence human subcortical brain structures. Nature 520, 224–229 (2015).
pubmed: 25607358
pmcid: 4393366
doi: 10.1038/nature14101
Strike, L. T. et al. Genetic complexity of cortical structure: Differences in genetic and environmental factors influencing cortical surface area and thickness. Cereb. Cortex 29, 952–962 (2018).
pmcid: 6373676
doi: 10.1093/cercor/bhy002
Jiang, Z. et al. The pivotal role of the X-chromosome in the genetic architecture of the human brain. Preprint at medRxiv https://doi.org/10.1101/2023.08.30.23294848 (2023).
Ge, T., Chen, C.-Y., Neale, B. M., Sabuncu, M. R. & Smoller, J. W. Phenome-wide heritability analysis of the UK Biobank. PLoS Genet. 13, e1006711 (2017).
pubmed: 28388634
pmcid: 5400281
doi: 10.1371/journal.pgen.1006711
Gilks, W. P., Abbott, J. K. & Morrow, E. H. Sex differences in disease genetics: evidence, evolution, and detection. Trends Genet. 30, 453–463 (2014).
pubmed: 25239223
doi: 10.1016/j.tig.2014.08.006
Uhlén, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).
pubmed: 25613900
doi: 10.1126/science.1260419
Naqvi, S. et al. Conservation, acquisition, and functional impact of sex-biased gene expression in mammals. Science 365, eaaw7317 (2019).
pubmed: 31320509
pmcid: 6896219
doi: 10.1126/science.aaw7317
Oliva, M. et al. The impact of sex on gene expression across human tissues. Science 369, eaba3066 (2020).
pubmed: 32913072
pmcid: 8136152
doi: 10.1126/science.aba3066
Zhu, C., Ming, M. J., Cole, J. M., Kirkpatrick, M. & Harpak, A. Amplification is the primary mode of gene-by-sex interaction in complex human traits. Cell Genom. 3, 100297 (2023).
Buimer, E. E. L. et al. The YOUth cohort study: MRI protocol and test-retest reliability in adults. Dev. Cogn. Neurosci. 45, 100816 (2020).
pubmed: 33040972
pmcid: 7365929
doi: 10.1016/j.dcn.2020.100816
Knussmann, G. N. et al. Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images. Neuroimage Rep. 2, 100086 (2022).
pubmed: 36032692
pmcid: 9409374
doi: 10.1016/j.ynirp.2022.100086
Noble, S. et al. Influences on the test–retest reliability of functional connectivity MRI and its relationship with behavioral utility. Cereb. Cortex 27, 5415–5429 (2017).
pubmed: 28968754
pmcid: 6248395
doi: 10.1093/cercor/bhx230
Fischl, B. et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341–355 (2002).
pubmed: 11832223
doi: 10.1016/S0896-6273(02)00569-X
Fischl, B. & Dale, A. M. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl. Acad. Sci. 97, 11050–11055 (2000).
pubmed: 10984517
pmcid: 27146
doi: 10.1073/pnas.200033797
Dale, A. M., Fischl, B. & Sereno, M. I. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9, 179–194 (1999).
pubmed: 9931268
doi: 10.1006/nimg.1998.0395
Rosen, A. F. G. et al. Quantitative assessment of structural image quality. Neuroimage 169, 407–418 (2018).
pubmed: 29278774
doi: 10.1016/j.neuroimage.2017.12.059
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
pubmed: 17701901
pmcid: 1950838
doi: 10.1086/519795
Yang, J. et al. Genome-wide genetic homogeneity between sexes and populations for human height and body mass index. Hum. Mol. Genet. 24, 7445–7449 (2015).
pubmed: 26494901
doi: 10.1093/hmg/ddv443
Mowinckel, A. M. & Vidal-Piñeiro, D. Visualization of brain statistics with R packages ggseg and ggseg3d. Adv. Meth. Pract. Psychol. Sci. 3, 466–483 (2020).
doi: 10.1177/2515245920928009
Core Team, R. R: A language and environment for statistical computing. Vienna: R foundation for statistical computing. (No Title) (2021).
Martin, J. et al. Examining sex-differentiated genetic effects across neuropsychiatric and behavioral Traits. Biol. Psychiatry 89, 1127–1137 (2021).
pubmed: 33648717
pmcid: 8163257
doi: 10.1016/j.biopsych.2020.12.024
1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Alexander-Bloch, A. F. et al. On testing for spatial correspondence between maps of human brain structure and function. Neuroimage 178, 540–551 (2018).
pubmed: 29860082
doi: 10.1016/j.neuroimage.2018.05.070
Markello, R. D. & Misic, B. Comparing spatial null models for brain maps. Neuroimage 236, 118052 (2021).
pubmed: 33857618
doi: 10.1016/j.neuroimage.2021.118052