51
|
Yeo RA, Ryman SG, Pommy J, Thoma RJ, Jung RE. General cognitive ability and fluctuating asymmetry of brain surface area. INTELLIGENCE 2016. [DOI: 10.1016/j.intell.2016.03.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
|
52
|
Vuoksimaa E, Panizzon MS, Chen CH, Fiecas M, Eyler LT, Fennema-Notestine C, Hagler DJ, Franz CE, Jak AJ, Lyons MJ, Neale MC, Rinker DA, Thompson WK, Tsuang MT, Dale AM, Kremen WS. Is bigger always better? The importance of cortical configuration with respect to cognitive ability. Neuroimage 2016; 129:356-366. [PMID: 26827810 PMCID: PMC4838639 DOI: 10.1016/j.neuroimage.2016.01.049] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Revised: 01/21/2016] [Accepted: 01/22/2016] [Indexed: 02/08/2023] Open
Abstract
General cognitive ability (GCA) has substantial explanatory power for behavioral and health outcomes, but its cortical substrate is still not fully established. GCA is highly polygenic and research to date strongly suggests that its cortical substrate is highly polyregional. We show in map-based and region-of-interest-based analyses of adult twins that a complex cortical configuration underlies GCA. Having relatively greater surface area in evolutionary and developmentally high-expanded prefrontal, lateral temporal, and inferior parietal regions is positively correlated with GCA, whereas relatively greater surface area in low-expanded occipital, medial temporal, and motor cortices is negatively correlated with GCA. Essentially the opposite pattern holds for relative cortical thickness. The phenotypic positive-to-negative gradients in our cortical-GCA association maps were largely driven by a similar pattern of genetic associations. The patterns are consistent with regional cortical stretching whereby relatively greater surface area is related to relatively thinner cortex in high-expanded regions. Thus, the typical "bigger is better" view does not adequately capture cortical-GCA associations. Rather, cognitive ability is influenced by complex configurations of cortical development patterns that are strongly influenced by genetic factors. Optimal cognitive ability appears to be driven both by the absolute size and the polyregional configuration of the entire cortex rather than by small, circumscribed regions.
Collapse
Affiliation(s)
- Eero Vuoksimaa
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA; Department of Public Health, and Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Chi-Hua Chen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA; Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Mark Fiecas
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Lisa T Eyler
- Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Amy J Jak
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA 23220, USA
| | - Daniel A Rinker
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
| | - Wesley K Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA 92093, USA.
| |
Collapse
|
53
|
Chiarello C, Vazquez D, Felton A, McDowell A. Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification. Neuropsychologia 2016; 93:365-379. [PMID: 26792368 DOI: 10.1016/j.neuropsychologia.2016.01.012] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Revised: 12/07/2015] [Accepted: 01/11/2016] [Indexed: 10/22/2022]
Abstract
Structural asymmetry varies across individuals, brain regions, and metrics of cortical organization. The current study investigated regional differences in asymmetry of cortical surface area, thickness, and local gyrification, and the extent of between-subject variability in these metrics, in a sample of healthy young adults (N=200). Between-subject variability in cortical structure may provide a means to assess the extent of biological flexibility or constraint of brain regions, and we explored the potential influence of this variability on the phenotypic expression of structural asymmetry. The findings demonstrate that structural asymmetries are nearly ubiquitous across the cortex, with differing regional organization for the three cortical metrics. This implies that there are multiple, only partially overlapping, maps of structural asymmetry. The results further indicate that the degree of asymmetry of a brain region can be predicted by the extent of the region's between-subject variability. These findings provide evidence that reduced biological constraint promotes the expression of strong structural asymmetry.
Collapse
|
54
|
Lyall AE, Savadjiev P, Shenton ME, Kubicki M. Insights into the Brain: Neuroimaging of Brain Development and Maturation. JOURNAL OF NEUROIMAGING IN PSYCHIATRY & NEUROLOGY 2016; 1:10-19. [PMID: 28620654 PMCID: PMC5469407 DOI: 10.17756/jnpn.2016-003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The study of how the human brain develops has always been a challenge and an interest to the scientific community. In recent years, new evidence has suggested that many neuropsychiatric disorders may originate from aberrations early in development. This discovery necessitates the application of methodologies that make possible the investigation of human brain development in vivo and across the lifespan. In this commentary, we present evidence that the advent of structural neuroimaging has specifically and significantly contributed critical information about the developmental trajectories of postnatal human brain development that would otherwise not have been possible. We believe that this is particularly relevant to present day research as it has become increasingly clear that growth trajectories within the brain might serve as an endophenotype for a number of factors, ranging from IQ to psychiatric illness. We highlight seminal early works that helped to jumpstart the field of developmental neuroimaging and which inspired incredible new advances in neuroimaging methodologies that are being developed and applied in the field today.
Collapse
Affiliation(s)
- Amanda E Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter Savadjiev
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,VA Boston Healthcare System, Brockton, MA, USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
55
|
Román FJ, Lewis LB, Chen CH, Karama S, Burgaleta M, Martínez K, Lepage C, Jaeggi SM, Evans AC, Kremen WS, Colom R. Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study. Brain Struct Funct 2015; 221:4369-4382. [PMID: 26701168 DOI: 10.1007/s00429-015-1168-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 12/01/2015] [Indexed: 10/22/2022]
Abstract
Here we analyze gray matter indices before and after completing a challenging adaptive cognitive training program based on the n-back task. The considered gray matter indices were cortical thickness (CT) and cortical surface area (CSA). Twenty-eight young women (age range 17-22 years) completed 24 training sessions over the course of 3 months (12 weeks, 24 sessions), showing expected performance improvements. CT and CSA values for the training group were compared with those of a matched control group. Statistical analyses were computed using a ROI framework defined by brain areas distinguished by their genetic underpinning. The interaction between group and time was analyzed. Middle temporal, ventral frontal, inferior parietal cortices, and pars opercularis were the regions where the training group showed conservation of gray matter with respect to the control group. These regions support working memory, resistance to interference, and inhibition. Furthermore, an interaction with baseline intelligence differences showed that the expected decreasing trend at the biological level for individuals showing relatively low intelligence levels at baseline was attenuated by the completed training.
Collapse
Affiliation(s)
| | - Lindsay B Lewis
- Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | | | - Sherif Karama
- Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | | | - Kenia Martínez
- Universidad Autónoma de Madrid, 28049, Madrid, Spain.,Hospital Gregorio Marañon, Madrid, Spain
| | - Claude Lepage
- Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | | | - Alan C Evans
- Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | | | - Roberto Colom
- Universidad Autónoma de Madrid, 28049, Madrid, Spain.
| |
Collapse
|
56
|
Development and aging of cortical thickness correspond to genetic organization patterns. Proc Natl Acad Sci U S A 2015; 112:15462-7. [PMID: 26575625 DOI: 10.1073/pnas.1508831112] [Citation(s) in RCA: 176] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.
Collapse
|
57
|
Docherty A. Regarding brain structure characteristics in intellectually superior schizophrenia. Psychiatry Res 2015; 233:496. [PMID: 26319294 PMCID: PMC4768797 DOI: 10.1016/j.pscychresns.2015.07.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2015] [Accepted: 07/26/2015] [Indexed: 11/24/2022]
Affiliation(s)
- A.R. Docherty
- Virginia Institute for Psychiatric & Behavioral Genetics,
Virginia Commonwealth University
| |
Collapse
|
58
|
Docherty AR, Sawyers CK, Panizzon MS, Neale MC, Eyler LT, Fennema-Notestine C, Franz CE, Chen CH, McEvoy LK, Verhulst B, Tsuang MT, Kremen WS. Genetic network properties of the human cortex based on regional thickness and surface area measures. Front Hum Neurosci 2015; 9:440. [PMID: 26347632 PMCID: PMC4542323 DOI: 10.3389/fnhum.2015.00440] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Accepted: 07/20/2015] [Indexed: 11/26/2022] Open
Abstract
We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques-biometrical genetic modeling, cluster analysis, and graph theory-to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.
Collapse
Affiliation(s)
- Anna R. Docherty
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Chelsea K. Sawyers
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Center for Behavioral Genomics Twin Research Laboratory, University of California, San DiegoSan Diego, CA, USA
| | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Lisa T. Eyler
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Mental Illness Research Education and Clinical Center, VA San Diego Healthcare SystemSan Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Department of Radiology, University of California, San DiegoSan Diego, CA, USA
| | - Carol E. Franz
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Center for Behavioral Genomics Twin Research Laboratory, University of California, San DiegoSan Diego, CA, USA
| | - Chi-Hua Chen
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Center for Behavioral Genomics Twin Research Laboratory, University of California, San DiegoSan Diego, CA, USA
| | - Linda K. McEvoy
- Department of Radiology, University of California, San DiegoSan Diego, CA, USA
| | - Brad Verhulst
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Center for Behavioral Genomics Twin Research Laboratory, University of California, San DiegoSan Diego, CA, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare SystemSan Diego, CA, USA
- Department of Neurosciences, University of California, San DiegoSan Diego, CA, USA
| | - William S. Kremen
- Department of Psychiatry, University of California, San DiegoSan Diego, CA, USA
- Center for Behavioral Genomics Twin Research Laboratory, University of California, San DiegoSan Diego, CA, USA
- Department of Neurosciences, University of California, San DiegoSan Diego, CA, USA
| |
Collapse
|
59
|
Córdova-Palomera A, Fatjó-Vilas M, Falcón C, Bargalló N, Alemany S, Crespo-Facorro B, Nenadic I, Fañanás L. Birth Weight and Adult IQ, but Not Anxious-Depressive Psychopathology, Are Associated with Cortical Surface Area: A Study in Twins. PLoS One 2015; 10:e0129616. [PMID: 26086820 PMCID: PMC4472844 DOI: 10.1371/journal.pone.0129616] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 05/11/2015] [Indexed: 11/18/2022] Open
Abstract
Background Previous research suggests that low birth weight (BW) induces reduced brain cortical surface area (SA) which would persist until at least early adulthood. Moreover, low BW has been linked to psychiatric disorders such as depression and psychological distress, and to altered neurocognitive profiles. Aims We present novel findings obtained by analysing high-resolution structural MRI scans of 48 twins; specifically, we aimed: i) to test the BW-SA association in a middle-aged adult sample; and ii) to assess whether either depression/anxiety disorders or intellectual quotient (IQ) influence the BW-SA link, using a monozygotic (MZ) twin design to separate environmental and genetic effects. Results Both lower BW and decreased IQ were associated with smaller total and regional cortical SA in adulthood. Within a twin pair, lower BW was related to smaller total cortical and regional SA. In contrast, MZ twin differences in SA were not related to differences in either IQ or depression/anxiety disorders. Conclusion The present study supports findings indicating that i) BW has a long-lasting effect on cortical SA, where some familial and environmental influences alter both foetal growth and brain morphology; ii) uniquely environmental factors affecting BW also alter SA; iii) higher IQ correlates with larger SA; and iv) these effects are not modified by internalizing psychopathology.
Collapse
Affiliation(s)
- Aldo Córdova-Palomera
- Unidad de Antropología, Departamento de Biología Animal, Facultad de Biología and Instituto de Biomedicina (IBUB), Universitat de Barcelona, Av. Diagonal, 643, 08028, Barcelona, Spain
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
| | - Mar Fatjó-Vilas
- Unidad de Antropología, Departamento de Biología Animal, Facultad de Biología and Instituto de Biomedicina (IBUB), Universitat de Barcelona, Av. Diagonal, 643, 08028, Barcelona, Spain
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
| | - Carles Falcón
- Medical Image Core Facility, the Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS); C/Rosselló, 149–153, 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomedicina y Nanomedicina (CIBER-BBN), C/ Poeta Mariano Esquillor, s/n., 50018, Zaragoza, Spain
| | - Nuria Bargalló
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
- Medical Image Core Facility, the Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS); C/Rosselló, 149–153, 08036, Barcelona, Spain
- Centro de Diagnóstico por Imagen, Hospital Clínico, C/Villarroel, 170, 08036, Barcelona, Spain
| | - Silvia Alemany
- Unidad de Antropología, Departamento de Biología Animal, Facultad de Biología and Instituto de Biomedicina (IBUB), Universitat de Barcelona, Av. Diagonal, 643, 08028, Barcelona, Spain
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
- University Hospital Marqués de Valdecilla, Department of Psychiatry, School of Medicine, University of Cantabria, Av. Valdecilla, s/n, 39008, Santander, Cantabria, Spain
- IFIMAV, Instituto de Formación e Investigación Marqués de Valdecilla, Av. Valdecilla, s/n, 39008, Santander, Cantabria, Spain
| | - Igor Nenadic
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Friedrich Schiller University Jena, Philosophenweg 3, 07743, Jena, Germany
| | - Lourdes Fañanás
- Unidad de Antropología, Departamento de Biología Animal, Facultad de Biología and Instituto de Biomedicina (IBUB), Universitat de Barcelona, Av. Diagonal, 643, 08028, Barcelona, Spain
- Centro de Investigaciones Biomédicas en Red de Salud Mental (CIBERSAM), C/Doctor Esquerdo, 46, 28007, Madrid, Spain
- * E-mail:
| |
Collapse
|
60
|
Docherty AR, Hagler DJ, Panizzon MS, Neale MC, Eyler LT, Fennema-Notestine C, Franz CE, Jak A, Lyons MJ, Rinker DA, Thompson WK, Tsuang MT, Dale AM, Kremen WS. Does degree of gyrification underlie the phenotypic and genetic associations between cortical surface area and cognitive ability? Neuroimage 2015; 106:154-60. [PMID: 25433211 PMCID: PMC4313767 DOI: 10.1016/j.neuroimage.2014.11.040] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Revised: 11/12/2014] [Accepted: 11/18/2014] [Indexed: 01/19/2023] Open
Abstract
The phenotypic and genetic relationship between global cortical size and general cognitive ability (GCA) appears to be driven by surface area (SA) and not cortical thickness (CT). Gyrification (cortical folding) is an important property of the cortex that helps to increase SA within a finite space, and may also improve connectivity by reducing distance between regions. Hence, gyrification may be what underlies the SA-GCA relationship. In previous phenotypic studies, a 3-dimensional gyrification index (3DGI) has been positively associated with cognitive ability and negatively associated with mild cognitive impairment, Alzheimer's disease, and psychiatric disorders affecting cognition. However, the differential genetic associations of 3DGI and SA with GCA are still unclear. We examined the heritability of 3DGI, and the phenotypic, genetic, and environmental associations of 3DGI with SA and GCA in a large sample of adult male twins (N = 512). Nearly 85% of the variance in 3DGI was due to genes, and 3DGI had a strong phenotypic and genetic association with SA. Both 3DGI and total SA had positive phenotypic correlations with GCA. However, the SA-GCA correlation remained significant after controlling for 3DGI, but not the other way around. There was also significant genetic covariance between SA and GCA, but not between 3DGI and GCA. Thus, despite the phenotypic and genetic associations between 3DGI and SA, our results do not support the hypothesis that gyrification underlies the association between SA and GCA.
Collapse
Affiliation(s)
- Anna R Docherty
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA 23220, USA.
| | - Donald J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA 23220, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, 92093, CA USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA
| | - Amy Jak
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA 92093, USA
| | - Michael J Lyons
- Department of Psychology, Boston University, Boston, MA 02215, USA
| | - Daniel A Rinker
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Wesley K Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA 92093, USA; Institute of Genomic Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA; Center for Behavioral Genomics Twin Research Laboratory, University of California, San Diego, La Jolla, CA 92093, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA 92093, USA
| |
Collapse
|
61
|
Differential longitudinal changes in cortical thickness, surface area and volume across the adult life span: regions of accelerating and decelerating change. J Neurosci 2014; 34:8488-98. [PMID: 24948804 DOI: 10.1523/jneurosci.0391-14.2014] [Citation(s) in RCA: 366] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Human cortical thickness and surface area are genetically independent, emerge through different neurobiological events during development, and are sensitive to different clinical conditions. However, the relationship between changes in the two over time is unknown. Additionally, longitudinal studies have almost invariably been restricted to older adults, precluding the delineation of adult life span trajectories of change in cortical structure. In this longitudinal study, we investigated changes in cortical thickness, surface area, and volume after an average interval of 3.6 years in 207 well screened healthy adults aged 23-87 years. We hypothesized that the relationships among metrics are dynamic across the life span, that the primary contributor to cortical volume reductions in aging is cortical thinning, and that magnitude of change varies with age and region. Changes over time were seen in cortical area (mean annual percentage change [APC], -0.19), thickness (APC, -0.35), and volume (APC, -0.51) in most regions. Volume changes were primarily explained by changes in thickness rather than area. A negative relationship between change in thickness and surface area was found across several regions, where more thinning was associated with less decrease in area, and vice versa. Accelerating changes with increasing age was seen in temporal and occipital cortices. In contrast, decelerating changes were seen in prefrontal and anterior cingulate cortices. In conclusion, a dynamic relationship between cortical thickness and surface area changes exists throughout the adult life span. The mixture of accelerating and decelerating changes further demonstrates the importance of studying these metrics across the entire adult life span.
Collapse
|
62
|
Toward neurobiological characterization of functional homogeneity in the human cortex: regional variation, morphological association and functional covariance network organization. Brain Struct Funct 2014; 220:2485-507. [DOI: 10.1007/s00429-014-0795-8] [Citation(s) in RCA: 90] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 05/11/2014] [Indexed: 01/14/2023]
|