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Article: Genetic contributions to regional variability in human brain structure: Methods and preliminary results

TitleGenetic contributions to regional variability in human brain structure: Methods and preliminary results
Authors
KeywordsAsymmetry
Brain anatomy
Genetic correlation matrix
Heritability
MRI
Path analysis
Structural equation modeling
Twins
Issue Date2002
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimg
Citation
Neuroimage, 2002, v. 17 n. 1, p. 256-271 How to Cite?
AbstractTwin studies provide one approach for investigating and partitioning genetic and environmental contributions to phenotypic variability in human brain structure. Previous twin studies have found that cerebral volume, hemispheric volume, ventricular volume, and cortical gyral pattern variability were heritable. We investigated the contributions of genetic and environmental factors to both global (brain volume and lateral ventricular volume) and regional (parcellated gray matter) variability in brain structure. We examined MR images from 10 pairs of healthy monozygotic and 10 pairs of same-sex dizygotic twins. Regional gray matter volume was estimated by automated image segmentation, transformation to standard space, and parcellation using a digital atlas. Heritability was estimated by path analysis. Estimated heritability for brain volume variability was high (0.66; 95% confidence interval 0.17, 1.0) but the major effects on lateral ventricular volume variability were common and unique environmental factors. We constructed a map of regional brain heritability and found large genetic effects shared in common between several bilateral brain regions, particularly paralimbic structures and temporal-parietal neocortex. We tested three specific hypotheses with regard to the genetic control of brain variability: (i) that the strength of the genetic effect is related to gyral ontogenesis, (ii) that there is greater genetic control of left than of right hemisphere variability, and (iii) that random or fluctuating asymmetry in bilateral structures is not heritable. We found no evidence in support of the first two hypotheses, but our results were consistent with the third hypothesis. Finally, we used principal component (PC) analysis of the genetic correlation matrix, to identify systems of anatomically distributed gray matter regions which shared major genetic effects in common. Frontal and parietal neocortical areas loaded positively on the first PC; some paralimbic and limbic areas loaded negatively. Bilateral insula, some frontal regions, and temporal neocortical regions functionally specialized for audition and language loaded strongly on the second PC. We conclude that large samples are required for powerful investigation of genetic effects in imaging data from twins. However, these preliminary results suggest that genetic effects on structure of the human brain are regionally variable and predominantly symmetric in paralimbic structures and lateral temporal cortex. © 2002 Elsevier Science (USA).
Persistent Identifierhttp://hdl.handle.net/10722/175867
ISSN
2023 Impact Factor: 4.7
2023 SCImago Journal Rankings: 2.436
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWright, ICen_US
dc.contributor.authorSham, Pen_US
dc.contributor.authorMurray, RMen_US
dc.contributor.authorWeinberger, DRen_US
dc.contributor.authorBullmore, ETen_US
dc.date.accessioned2012-11-26T09:01:54Z-
dc.date.available2012-11-26T09:01:54Z-
dc.date.issued2002en_US
dc.identifier.citationNeuroimage, 2002, v. 17 n. 1, p. 256-271en_US
dc.identifier.issn1053-8119en_US
dc.identifier.urihttp://hdl.handle.net/10722/175867-
dc.description.abstractTwin studies provide one approach for investigating and partitioning genetic and environmental contributions to phenotypic variability in human brain structure. Previous twin studies have found that cerebral volume, hemispheric volume, ventricular volume, and cortical gyral pattern variability were heritable. We investigated the contributions of genetic and environmental factors to both global (brain volume and lateral ventricular volume) and regional (parcellated gray matter) variability in brain structure. We examined MR images from 10 pairs of healthy monozygotic and 10 pairs of same-sex dizygotic twins. Regional gray matter volume was estimated by automated image segmentation, transformation to standard space, and parcellation using a digital atlas. Heritability was estimated by path analysis. Estimated heritability for brain volume variability was high (0.66; 95% confidence interval 0.17, 1.0) but the major effects on lateral ventricular volume variability were common and unique environmental factors. We constructed a map of regional brain heritability and found large genetic effects shared in common between several bilateral brain regions, particularly paralimbic structures and temporal-parietal neocortex. We tested three specific hypotheses with regard to the genetic control of brain variability: (i) that the strength of the genetic effect is related to gyral ontogenesis, (ii) that there is greater genetic control of left than of right hemisphere variability, and (iii) that random or fluctuating asymmetry in bilateral structures is not heritable. We found no evidence in support of the first two hypotheses, but our results were consistent with the third hypothesis. Finally, we used principal component (PC) analysis of the genetic correlation matrix, to identify systems of anatomically distributed gray matter regions which shared major genetic effects in common. Frontal and parietal neocortical areas loaded positively on the first PC; some paralimbic and limbic areas loaded negatively. Bilateral insula, some frontal regions, and temporal neocortical regions functionally specialized for audition and language loaded strongly on the second PC. We conclude that large samples are required for powerful investigation of genetic effects in imaging data from twins. However, these preliminary results suggest that genetic effects on structure of the human brain are regionally variable and predominantly symmetric in paralimbic structures and lateral temporal cortex. © 2002 Elsevier Science (USA).en_US
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimgen_US
dc.relation.ispartofNeuroImageen_US
dc.subjectAsymmetry-
dc.subjectBrain anatomy-
dc.subjectGenetic correlation matrix-
dc.subjectHeritability-
dc.subjectMRI-
dc.subjectPath analysis-
dc.subjectStructural equation modeling-
dc.subjectTwins-
dc.subject.meshAlgorithmsen_US
dc.subject.meshAnalysis Of Varianceen_US
dc.subject.meshBrain - Anatomy & Histology - Growth & Developmenten_US
dc.subject.meshCerebral Ventricles - Anatomy & Histologyen_US
dc.subject.meshFemaleen_US
dc.subject.meshFunctional Laterality - Physiologyen_US
dc.subject.meshGeneticsen_US
dc.subject.meshGestational Ageen_US
dc.subject.meshHumansen_US
dc.subject.meshImage Interpretation, Computer-Assisteden_US
dc.subject.meshMagnetic Resonance Imagingen_US
dc.subject.meshPhenotypeen_US
dc.subject.meshPregnancyen_US
dc.subject.meshPrincipal Component Analysisen_US
dc.subject.meshTwins, Dizygoticen_US
dc.subject.meshTwins, Monozygoticen_US
dc.titleGenetic contributions to regional variability in human brain structure: Methods and preliminary resultsen_US
dc.typeArticleen_US
dc.identifier.emailSham, P: pcsham@hku.hken_US
dc.identifier.authoritySham, P=rp00459en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1006/nimg.2002.1163en_US
dc.identifier.pmid12482082-
dc.identifier.scopuseid_2-s2.0-0036742131en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036742131&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume17en_US
dc.identifier.issue1en_US
dc.identifier.spage256en_US
dc.identifier.epage271en_US
dc.identifier.isiWOS:000178102000019-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridWright, IC=7202889221en_US
dc.identifier.scopusauthoridSham, P=34573429300en_US
dc.identifier.scopusauthoridMurray, RM=35406239400en_US
dc.identifier.scopusauthoridWeinberger, DR=7202213462en_US
dc.identifier.scopusauthoridBullmore, ET=35405771500en_US
dc.identifier.citeulike7891276-
dc.identifier.issnl1053-8119-

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