1
|
Kubinyi E. Biologia Futura: four questions about ageing and the future of relevant animal models. Biol Futur 2022; 73:385-391. [PMID: 36131217 DOI: 10.1007/s42977-022-00135-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 09/02/2022] [Indexed: 01/10/2023]
Abstract
Understanding how active and healthy ageing can be achieved is one of the most relevant global problems. In this review, I use the "Four questions" framework of Tinbergen to investigate how ageing works, how it might contribute to the survival of species, how it develops during the lifetime of (human) individuals and how it evolved. The focus of ageing research is usually on losses, although trajectories in later life show heterogeneity and many individuals experience healthy ageing. In humans, mild changes in cognition might be a typical part of ageing, but deficits are a sign of pathology. The ageing of the world's populations, and relatedly, the growing number of pathologically ageing people, is one of the major global problems. Animal models can help to understand the intrinsic and extrinsic factors contributing to ageing.
Collapse
Affiliation(s)
- Enikő Kubinyi
- Department of Ethology, ELTE Eötvös Loránd University, Budapest, Hungary. .,MTA-ELTE Lendület "Momentum" Companion Animal Research Group, Budapest, Hungary.
| |
Collapse
|
2
|
Kochunov P, Hong LE, Dennis EL, Morey RA, Tate DF, Wilde EA, Logue M, Kelly S, Donohoe G, Favre P, Houenou J, Ching CRK, Holleran L, Andreassen OA, van Velzen LS, Schmaal L, Villalón-Reina JE, Bearden CE, Piras F, Spalletta G, van den Heuvel OA, Veltman DJ, Stein DJ, Ryan MC, Tan Y, van Erp TGM, Turner JA, Haddad L, Nir TM, Glahn DC, Thompson PM, Jahanshad N. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Hum Brain Mapp 2022; 43:194-206. [PMID: 32301246 PMCID: PMC8675425 DOI: 10.1002/hbm.24998] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 03/06/2020] [Accepted: 03/17/2020] [Indexed: 12/25/2022] Open
Abstract
The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.
Collapse
Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Emily L Dennis
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, USA
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - David F Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Mark Logue
- VA Boston Healthcare System, National Center for PTSD, Boston, Massachusetts, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, Massachusetts, USA
- Boston University School of Medicine, Biomedical Genetics, Boston, Massachusetts, USA
- Boston University School of Public Health, Department of Biostatistics, Boston, Massachusetts, USA
| | - Sinead Kelly
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Pauline Favre
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
| | - Josselin Houenou
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
- Psychiatry Department, Assistance Publique-Hôpitaux de Paris (AP-HP), CHU Mondor, Créteil, France
- Faculté de Médecine, Université Paris Est Créteil, Créteil, France
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Laura S van Velzen
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Julio E Villalón-Reina
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, California, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
- Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dick J Veltman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, University of Cape Town, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry, University of California Irvine, Irvine, California, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, California, USA
| | - Jessica A Turner
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Liz Haddad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Talia M Nir
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Olin Neuropsychiatric Research Center, Hartford Hospital, Hartford, Connecticut, USA
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| |
Collapse
|
3
|
The Integrity of the Substructure of the Corpus Callosum in Patients With Right Classic Trigeminal Neuralgia. J Craniofac Surg 2021; 32:632-636. [PMID: 33704998 DOI: 10.1097/scs.0000000000007082] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Patients with classic trigeminal neuralgia (CTN) have abnormalities in white matter integrity of the corpus callosum (CC). However, in CTN patients, it is unclear whether the CC substructure region is affected to varying degrees. MATERIAL AND METHODS A total of 22 patients with CTN and 22 healthy controls (HC) with matching age, gender, and education were selected. All subjects underwent 3.0 T magnetic resonance diffusion tensor imaging and high resolution T1-weighted imaging. The CC was reconstructed by DTI technology, which was divided into three substructure regions: genu, body, and splenium. Group differences in multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD), were compared between CTN patients and HC, and correlations between the white matter change and disease duration and VAS in CTN patients were assessed. RESULTS Compared with HC group, CTN patients had extensive damage to the CC white matter. The FA of the genu (P = 0.04) and body (P = 001) parts decreased, while RD (P = 0.003; P = 0.02) and MD (P = 0.002; P = 0.04) increased. In addition, the authors observed that the disease duration and VAS of CTN patients were negatively correlated with FA. CONCLUSION The corpus callosum substructure region has extensive damage in chronic pain, and the selective microstructural integrity damage was particularly manifested by changes in axons and myelin sheath in the genu and body of corpus callosum.
Collapse
|
4
|
Music Playing and Interhemispheric Communication: Older Professional Musicians Outperform Age-Matched Non-Musicians in Fingertip Cross-Localization Test. J Int Neuropsychol Soc 2021; 27:282-292. [PMID: 32967757 DOI: 10.1017/s1355617720000946] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Numerous investigations have documented that age-related changes in the integrity of the corpus callosum are associated with age-related decline in the interhemispheric transfer of information. Conversely, there is accumulating evidence for more efficient white matter organization of the corpus callosum in individuals with extensive musical training. However, the relationship between making music and accuracy in interhemispheric transfer remains poorly explored. METHODS To test the hypothesis that musicians show enhanced functional connectivity between the two hemispheres, 65 professional musicians (aged 56-90 years) and 65 age- and sex-matched non-musicians performed the fingertip cross-localization test. In this task, subjects must respond to a tactile stimulus presented to one hand using the ipsilateral (intra-hemispheric test) or contralateral (inter-hemispheric test) hand. Because the transfer of information from one hemisphere to another may imply a loss of accuracy, the value of the difference between the intrahemispheric and interhemispheric tests can be utilized as a reliable measure of the effectiveness of hemispheric interactions. RESULTS Older professional musicians show significantly greater accuracy in tactile interhemispheric transfer than non-musicians who suffer from age-related decline. CONCLUSIONS Musicians have more efficient interhemispheric communication than age-matched non-musicians. This finding is in keeping with studies showing that individuals with extensive musical training have a larger corpus callosum. The results are discussed in relation to relevant data suggesting that music positively influences aging brain plasticity.
Collapse
|
5
|
Danielsen VM, Vidal-Piñeiro D, Mowinckel AM, Sederevicius D, Fjell AM, Walhovd KB, Westerhausen R. Lifespan trajectories of relative corpus callosum thickness: Regional differences and cognitive relevance. Cortex 2020; 130:127-141. [PMID: 32652340 DOI: 10.1016/j.cortex.2020.05.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 05/11/2020] [Accepted: 05/25/2020] [Indexed: 02/03/2023]
Abstract
The cerebral hemispheres are specialized for different cognitive functions and receive divergent information from the sensory organs, so that the interaction between the hemispheres is a crucial aspect of perception and cognition. At the same time, the major fiber tract responsible for this interaction, the corpus callosum, shows a structural development across the lifespan which is over-proportional. That is, compared to changes in overall forebrain volume, the corpus callosum shows an accentuated growth during childhood, adolescence, and early adulthood, as well as pronounced decline in older age. However, this over-proportionality of growth and decline along with potential consequences for cognition, have been largely overlooked in empirical research. In the present study we systematically address the proportionality of callosal development in a large mixed cross-sectional and longitudinal sample (1867 datasets from 1014 unique participants), covering the human lifespan (age range 4-93 years), and examine the cognitive consequences of the observed changes. Relative corpus callosum thickness was measured at 60 segments along the midsagittal surface, and lifespan trajectories were clustered to identify callosal subsections of comparable lifespan development. While confirming the expected inverted u-shaped lifespan trajectories, we also found substantial regional variation. Compared with anterior clusters, the most posterior sections exhibited an accentuated growth during development which extends well into the third decade of life, and a protracted decline in older age which is delayed by about 10 years (starting mid to late 50s). We further showed that the observed longitudinal changes in relative thickness of the mid splenium significantly mediates age-related changes in tests assessing verbal knowledge and non-verbal visual-spatial abilities across the lifespan. In summary, we demonstrate that analyzing the proportionality of callosal growth and decline offers valuable insight into lifespan development of structural connectivity between the hemispheres, and suggests consequences for the cognitive development of perception and cognition.
Collapse
Affiliation(s)
- V M Danielsen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - D Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - A M Mowinckel
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - D Sederevicius
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway
| | - A M Fjell
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - K B Walhovd
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - R Westerhausen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Norway.
| |
Collapse
|
6
|
Piccirilli M, D'Alessandro P, Germani A, Boccardi V, Pigliautile M, Ancarani V, Dioguardi MS. Age-related decline in interhemispheric transfer of tactile information: The fingertip cross-localization task. J Clin Neurosci 2020; 77:75-80. [PMID: 32446807 DOI: 10.1016/j.jocn.2020.05.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 05/04/2020] [Indexed: 11/28/2022]
Abstract
According to the disconnection hypothesis of cognitive aging, cognitive deficits associated with brain aging could be a result of damage to connective fibres. It has been suggested that the age-related decline in cognitive abilities is accompanied by age-related changes in interhemispheric communication ensured by commissural fibres. This study aimed to contribute to this topic by investigating the effects of aging on the efficiency of interhemispheric transfer of tactile information. A total of 168 right-handed subjects, aged 20-90 years, have been tested using the fingertip cross-localization task: the subject must respond to a tactile stimulus presented to one hand using the ipsilateral (uncrossed condition) or contralateral hand (crossed condition). Because the crossed task requires interhemispheric transfer of information, the value of the difference between the uncrossed and crossed conditions (CUD) can be deemed to be a reliable measure of the efficiency of the interhemispheric interactions. The uncrossed condition was more accurate than the crossed condition for all ages. However, the degree of the CUD was significantly age-dependent. The effectiveness of the interhemispheric transfer of tactile information decreased significantly with age and may indicate the occurrence of age-related changes of the corpus callosum. Considerably, performance appears to decline around the seventh decade of life with the fastest decline in the subsequent decades. The results suggest a relationship between brain aging and the efficiency of the interhemispheric transfer of tactile information. The findings are discussed in relation to the strategic role of white matter integrity in preserving behavioural performances.
Collapse
Affiliation(s)
- Massimo Piccirilli
- Department of Experimental Medicine, University of Perugia, Perugia, Italy.
| | | | - Alessandro Germani
- Department of Philosophy, Social Sciences and Education, University of Perugia, Italy.
| | | | | | - Viola Ancarani
- Degree Course in Speech and Language Therapy, University of Perugia, Perugia, Italy.
| | | |
Collapse
|
7
|
Wang Y, Li X, Zhang C, Wang H, Li Z, Zhu J, Yu Y. Selective micro-structural integrity impairment of the isthmus subregion of the corpus callosum in alcohol-dependent males. BMC Psychiatry 2019; 19:96. [PMID: 30909890 PMCID: PMC6434796 DOI: 10.1186/s12888-019-2079-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 03/15/2019] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Previous studies have provided evidence that alcohol-dependent patients have abnormality in corpus callosum (CC); however, it is unclear whether micro-structural integrity of the CC subregions is differentially affected in this disorder. METHODS In this study, a total of 39 male individuals, including 19 alcohol-dependent patients and 20 age-matched healthy controls, underwent diffusion tensor imaging (DTI). CC was reconstructed by DTI tractography and was divided into seven subregions. Multiple diffusion metrics of each subregion were compared between two groups. RESULTS Compared to healthy controls, patients exhibited increased axial diffusivity (P = 0.007), radial diffusivity (P = 0.009) and mean diffusivity (P = 0.005) in the isthmus. In addition, we observed that daily alcohol intake was correlated positively with radial diffusivity and mean diffusivity and negatively with fractional anisotropy, while abstinence time of hospitalization was negatively correlated with mean diffusivity in the patients. CONCLUSION These findings suggest a selective micro-structural integrity impairment of the corpus callosum subregions in alcohol dependence, characterized by axon and myelin alterations in the isthmus.
Collapse
Affiliation(s)
- Yajun Wang
- 0000 0004 1771 3402grid.412679.fDepartment of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui Province China
| | - Xiaohu Li
- 0000 0004 1771 3402grid.412679.fDepartment of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui Province China
| | - Cun Zhang
- 0000 0004 1771 3402grid.412679.fDepartment of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui Province China
| | - Haibao Wang
- 0000 0004 1771 3402grid.412679.fDepartment of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui Province China
| | - Zipeng Li
- 0000 0004 1771 3402grid.412679.fDepartment of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 Anhui Province China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui Province, China.
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui Province, China.
| |
Collapse
|
8
|
Kochunov P, Patel B, Ganjgahi H, Donohue B, Ryan M, Hong EL, Chen X, Adhikari B, Jahanshad N, Thompson PM, Van't Ent D, den Braber A, de Geus EJC, Brouwer RM, Boomsma DI, Hulshoff Pol HE, de Zubicaray GI, McMahon KL, Martin NG, Wright MJ, Nichols TE. Homogenizing Estimates of Heritability Among SOLAR-Eclipse, OpenMx, APACE, and FPHI Software Packages in Neuroimaging Data. Front Neuroinform 2019; 13:16. [PMID: 30914942 PMCID: PMC6422938 DOI: 10.3389/fninf.2019.00016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 02/25/2019] [Indexed: 11/30/2022] Open
Abstract
Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.
Collapse
Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Binish Patel
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Habib Ganjgahi
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Brian Donohue
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Meghann Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Elliot L Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Xu Chen
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Paul M Thompson
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Dennis Van't Ent
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Rachel M Brouwer
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Greig I de Zubicaray
- Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | | | - Margaret J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Thomas E Nichols
- Big Data Institute, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
9
|
Scally B, Burke MR, Bunce D, Delvenne JF. Visual and visuomotor interhemispheric transfer time in older adults. Neurobiol Aging 2018; 65:69-76. [DOI: 10.1016/j.neurobiolaging.2018.01.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 11/07/2017] [Accepted: 01/09/2018] [Indexed: 12/01/2022]
|
10
|
Neural predictors of cognitive improvement by multi-strategic memory training based on metamemory in older adults with subjective memory complaints. Sci Rep 2018; 8:1095. [PMID: 29348440 PMCID: PMC5773558 DOI: 10.1038/s41598-018-19390-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 12/28/2017] [Indexed: 11/08/2022] Open
Abstract
Previous studies have indicated that memory training may help older people improve cognition. However, evidence regarding who will benefit from such memory trainings has not been fully discovered yet. Understanding the clinical and neural inter-individual differences for predicting cognitive improvement is important for maximizing the training efficacy of memory-training programs. The purpose of this study was to find the individual characteristics and brain morphological characteristics that predict cognitive improvement after a multi-strategic memory training based on metamemory concept. Among a total of 49 older adults, 39 participated in the memory-training program and 10 did not. All of them underwent brain MRIs at the entry of the training and received the neuropsychological tests twice, before and after the training. Stepwise regression analysis showed that lower years of education predicted cognitive improvement in the training group. In MRI, thinner cortices of precuneus, cuneus and posterior cingulate gyrus and higher white matter anisotropy of the splenium of corpus callosum predicted cognitive improvement in the training group. Old age, lower education level and individual differences in cortical thickness and white matter microstructure of the episodic memory network may predict outcomes following multi-strategic training.
Collapse
|
11
|
|
12
|
Callosotomy affects performance IQ: A meta-analysis of individual participant data. Neurosci Lett 2017; 665:43-47. [PMID: 29174639 DOI: 10.1016/j.neulet.2017.11.040] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 10/24/2017] [Accepted: 11/20/2017] [Indexed: 11/22/2022]
Abstract
Morphometric neuroimaging studies on healthy adult individuals regularly report a positive association between intelligence test performance (IQ) and structural properties of the corpus callosum (CC). At the same time, studies examining the effect of callosotomy on epilepsy patients report only negligible changes in IQ as result of the surgery, partially contradicting the findings of the morphometry studies. Objective of the present meta-analysis of individual participant data (IPD) of 87 cases from 16 reports was to re-investigate the effect of callosotomy on full scale IQ as well as on the verbal and performance subscale under special consideration of two possible moderating factors: pre-surgical IQ levels and the extent of the surgery (complete vs. anterior transsection). The main finding was that callosotomy selectively affects performance IQ, whereby the effect is modulated by the pre-surgical level of performance. Patients with an above-median pre-surgery performance IQ level show a significant average decrease of -5.44 (CI95%: - 8.33 to - 2.56) IQ points following the surgery, while the below-median group does not reveal a significant change in IQ (mean change: 1.01 IQ points; CI95%: -1.83 to 3.86). Thus, the present analyses support the notion that callosotomy has a negative effect on the patients' performance IQ, but only in those patients, who at least have an average performance levels before the surgery. This observation also lends support to the findings of previous morphometry studies, indicating that the frequently observed CC-IQ correlation might indeed reflect a functional contribution of callosal interhemispheric connectivity to intelligence-test performance.
Collapse
|
13
|
Giddaluru S, Espeseth T, Salami A, Westlye LT, Lundquist A, Christoforou A, Cichon S, Adolfsson R, Steen VM, Reinvang I, Nilsson LG, Le Hellard S, Nyberg L. Genetics of structural connectivity and information processing in the brain. Brain Struct Funct 2016; 221:4643-4661. [PMID: 26852023 PMCID: PMC5102980 DOI: 10.1007/s00429-016-1194-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 01/22/2016] [Indexed: 12/20/2022]
Abstract
Understanding the genetic factors underlying brain structural connectivity is a major challenge in imaging genetics. Here, we present results from genome-wide association studies (GWASs) of whole-brain white matter (WM) fractional anisotropy (FA), an index of microstructural coherence measured using diffusion tensor imaging. Data from independent GWASs of 355 Swedish and 250 Norwegian healthy adults were integrated by meta-analysis to enhance power. Complementary GWASs on behavioral data reflecting processing speed, which is related to microstructural properties of WM pathways, were performed and integrated with WM FA results via multimodal analysis to identify shared genetic associations. One locus on chromosome 17 (rs145994492) showed genome-wide significant association with WM FA (meta P value = 1.87 × 10-08). Suggestive associations (Meta P value <1 × 10-06) were observed for 12 loci, including one containing ZFPM2 (lowest meta P value = 7.44 × 10-08). This locus was also implicated in multimodal analysis of WM FA and processing speed (lowest Fisher P value = 8.56 × 10-07). ZFPM2 is relevant in specification of corticothalamic neurons during brain development. Analysis of SNPs associated with processing speed revealed association with a locus that included SSPO (lowest meta P value = 4.37 × 10-08), which has been linked to commissural axon growth. An intergenic SNP (rs183854424) 14 kb downstream of CSMD1, which is implicated in schizophrenia, showed suggestive evidence of association in the WM FA meta-analysis (meta P value = 1.43 × 10-07) and the multimodal analysis (Fisher P value = 1 × 10-07). These findings provide novel data on the genetics of WM pathways and processing speed, and highlight a role of ZFPM2 and CSMD1 in information processing in the brain.
Collapse
Affiliation(s)
- Sudheer Giddaluru
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Thomas Espeseth
- K.G. Jebsen Center for Psychosis Research, Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424, Oslo, Norway.,Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,Aging Research Center, Karolinska Institutet and Stockholm University, 11330, Stockholm, Sweden
| | - Lars T Westlye
- K.G. Jebsen Center for Psychosis Research, Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424, Oslo, Norway.,Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,Department of Statistics, USBF, Umeå University, 90187, Umeå, Sweden
| | - Andrea Christoforou
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Sven Cichon
- Division of Medical Genetics, Department of Biomedicine, University of Basel, 4058, Basel, Switzerland.,Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, 52425, Juelich, Germany.,Department of Genomics, Life and Brain Center, University of Bonn, 53127, Bonn, Germany
| | - Rolf Adolfsson
- Department of Clinical Sciences, Psychiatry, Umeå University, 90187, Umeå, Sweden
| | - Vidar M Steen
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Ivar Reinvang
- Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Lars Göran Nilsson
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,ARC, Karolinska Institutet, Stockholm, Sweden
| | - Stéphanie Le Hellard
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden. .,Department of Radiation Sciences, Umeå University, 90187, Umeå, Sweden. .,Department of Integrative Medical Biology, Umeå University, 90187, Umeå, Sweden.
| |
Collapse
|
14
|
Kochunov P, Jahanshad N, Marcus D, Winkler A, Sprooten E, Nichols TE, Wright SN, Hong LE, Patel B, Behrens T, Jbabdi S, Andersson J, Lenglet C, Yacoub E, Moeller S, Auerbach E, Ugurbil K, Sotiropoulos SN, Brouwer RM, Landman B, Lemaitre H, den Braber A, Zwiers MP, Ritchie S, vanHulzen K, Almasy L, Curran J, deZubicaray GI, Duggirala R, Fox P, Martin NG, McMahon KL, Mitchell B, Olvera RL, Peterson C, Starr J, Sussmann J, Wardlaw J, Wright M, Boomsma DI, Kahn R, de Geus EJC, Williamson DE, Hariri A, van t Ent D, Bastin ME, McIntosh A, Deary IJ, Hulshoff pol HE, Blangero J, Thompson PM, Glahn DC, Van Essen DC. Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data. Neuroimage 2015; 111:300-11. [PMID: 25747917 PMCID: PMC4387079 DOI: 10.1016/j.neuroimage.2015.02.050] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Revised: 01/10/2015] [Accepted: 02/23/2015] [Indexed: 01/23/2023] Open
Abstract
The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application.
Collapse
Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Department of Neurology Keck School of Medicine University of Southern California, Marina del Rey, USA
| | - Daniel Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, USA
| | | | - Emma Sprooten
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, USA
| | | | - Susan N Wright
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Binish Patel
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | | | | | | | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, USA
| | - Steen Moeller
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, USA
| | - Eddie Auerbach
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, USA
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, USA
| | | | | | | | | | | | | | | | | | - Laura Almasy
- Texas Biomedical Research Institute, San Antonio, TX
| | - Joanne Curran
- Texas Biomedical Research Institute, San Antonio, TX
| | | | | | - Peter Fox
- University of Texas Health Science Center San Antonio, San Antonio, TX
| | | | | | | | - Rene L Olvera
- University of Texas Health Science Center San Antonio, San Antonio, TX
| | | | | | | | | | | | | | - Rene Kahn
- University Medical Center Utrecht, Utrecht, The Netherlands
| | | | | | | | | | | | | | | | | | - John Blangero
- Texas Biomedical Research Institute, San Antonio, TX
| | - Paul M. Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Department of Neurology Keck School of Medicine University of Southern California, Marina del Rey, USA
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, USA
| | - David C. Van Essen
- Anatomy & Neurobiology Department at Washington University in St. Louis, St. Louis, USA
| |
Collapse
|
15
|
Cox SR, Bastin ME, Ferguson KJ, Allerhand M, Royle NA, Maniega SM, Starr JM, MacLullich AMJ, Wardlaw JM, Deary IJ, MacPherson SE. Compensation or inhibitory failure? Testing hypotheses of age-related right frontal lobe involvement in verbal memory ability using structural and diffusion MRI. Cortex 2015; 63:4-15. [PMID: 25241394 PMCID: PMC4317301 DOI: 10.1016/j.cortex.2014.08.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Revised: 07/04/2014] [Accepted: 08/02/2014] [Indexed: 02/02/2023]
Abstract
Functional neuroimaging studies report increased right prefrontal cortex (PFC) involvement during verbal memory tasks amongst low-scoring older individuals, compared to younger controls and their higher-scoring contemporaries. Some propose that this reflects inefficient use of neural resources through failure of the left PFC to inhibit non-task-related right PFC activity, via the anterior corpus callosum (CC). For others, it indicates partial compensation - that is, the right PFC cannot completely supplement the failing neural network, but contributes positively to performance. We propose that combining structural and diffusion brain MRI can be used to test predictions from these theories which have arisen from fMRI studies. We test these hypotheses in immediate and delayed verbal memory ability amongst 90 healthy older adults of mean age 73 years. Right hippocampus and left dorsolateral prefrontal cortex (DLPFC) volumes, and fractional anisotropy (FA) in the splenium made unique contributions to verbal memory ability in the whole group. There was no significant effect of anterior callosal white matter integrity on performance. Rather, segmented linear regression indicated that right DLPFC volume was a significantly stronger positive predictor of verbal memory for lower-scorers than higher-scorers, supporting a compensatory explanation for the differential involvement of the right frontal lobe in verbal memory tasks in older age.
Collapse
Affiliation(s)
- Simon R Cox
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK.
| | - Mark E Bastin
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - Karen J Ferguson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Geriatric Medicine, University of Edinburgh, Edinburgh, UK
| | - Mike Allerhand
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Natalie A Royle
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - Susanna Muñoz Maniega
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Geriatric Medicine, University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Alasdair M J MacLullich
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Geriatric Medicine, University of Edinburgh, Edinburgh, UK; Endocrinology Unit, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK; Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Sarah E MacPherson
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| |
Collapse
|
16
|
Raffield LM, Cox AJ, Hugenschmidt CE, Freedman BI, Langefeld CD, Williamson JD, Hsu FC, Maldjian JA, Bowden DW. Heritability and genetic association analysis of neuroimaging measures in the Diabetes Heart Study. Neurobiol Aging 2014; 36:1602.e7-15. [PMID: 25523635 DOI: 10.1016/j.neurobiolaging.2014.11.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2014] [Accepted: 11/15/2014] [Indexed: 12/24/2022]
Abstract
Patients with type 2 diabetes are at increased risk of age-related cognitive decline and dementia. Neuroimaging measures such as white matter lesion volume, brain volume, and fractional anisotropy may reflect the pathogenesis of these cognitive declines, and genetic factors may contribute to variability in these measures. This study examined multiple neuroimaging measures in 465 participants from 238 families with extensive genotype data in the type 2 diabetes enriched Diabetes Heart Study-Mind cohort. Heritability of these phenotypes and their association with candidate single-nucleotide polymorphisms (SNPs), and SNP data from genome- and exome-wide arrays were explored. All neuroimaging measures analyzed were significantly heritable (ĥ(2) = 0.55-0.99 in unadjusted models). Seventeen candidate SNPs (from 16 genes/regions) associated with neuroimaging phenotypes in prior studies showed no significant evidence of association. A missense variant (rs150706952, A432V) in PLEKHG4B from the exome-wide array was significantly associated with white matter mean diffusivity (p = 3.66 × 10(-7)) and gray matter mean diffusivity (p = 2.14 × 10(-7)). This analysis suggests genetic factors contribute to variation in neuroimaging measures in a population enriched for metabolic disease and other associated comorbidities.
Collapse
Affiliation(s)
- Laura M Raffield
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Amanda J Cox
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Christina E Hugenschmidt
- Department of Gerontology and Geriatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Barry I Freedman
- Department of Internal Medicine-Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jeff D Williamson
- Department of Gerontology and Geriatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Fang-Chi Hsu
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Joseph A Maldjian
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA.
| |
Collapse
|
17
|
Kochunov P, Jahanshad N, Sprooten E, Nichols TE, Mandl RC, Almasy L, Booth T, Brouwer RM, Curran JE, de Zubicaray GI, Dimitrova R, Duggirala R, Fox PT, Hong LE, Landman BA, Lemaitre H, Lopez LM, Martin NG, McMahon KL, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Wright SN, Bastin ME, McIntosh AM, Boomsma DI, Kahn RS, den Braber A, de Geus EJC, Deary IJ, Hulshoff Pol HE, Williamson DE, Blangero J, van 't Ent D, Thompson PM, Glahn DC. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling. Neuroimage 2014; 95:136-50. [PMID: 24657781 PMCID: PMC4043878 DOI: 10.1016/j.neuroimage.2014.03.033] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2013] [Revised: 02/21/2014] [Accepted: 03/04/2014] [Indexed: 01/25/2023] Open
Abstract
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
Collapse
Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Emma Sprooten
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
| | - Thomas E Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK; Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford University, UK
| | - René C Mandl
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Rachel M Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Rali Dimitrova
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bennett A Landman
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Hervé Lemaitre
- U1000 Research Unit Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris-Sud, Orsay, France
| | - Lorna M Lopez
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | | | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Charles P Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Jessika E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Arthur W Toga
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Susan N Wright
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Douglas E Williamson
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dennis van 't Ent
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA; Department of Neurology, Pediatrics, Engineering, Psychiatry, Radiology, & Ophthalmology, University of Southern California, Los Angeles, CA, USA
| | - David C Glahn
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
| |
Collapse
|
18
|
Nyberg L, Salami A. The APOE ε4 allele in relation to brain white-matter microstructure in adulthood and aging. Scand J Psychol 2014; 55:263-7. [PMID: 24506254 DOI: 10.1111/sjop.12099] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2013] [Accepted: 11/28/2013] [Indexed: 01/13/2023]
Abstract
The Apolipoprotein E (ApoE) ε4 allele is a major genetic risk factor for sporadic Alzheimer's disease and has been associated with structural and functional brain alterations across the adult life span. Recent studies have presented evidence that ε4 affects microstructural properties of brain white matter (WM) in non-demented carriers of the ε4 allele, but conflicting evidence has been presented as well. The main purpose of the present study was therefore to examine ApoE effects on WM in a large sample of middle-aged and older adults (N = 273). Diffusion tensor imaging (DTI) data was acquired, and tract-based as well as voxel-wise analyses were conducted. The tract-based analyses revealed no significant ApoE effects, and no significant interactions between genotype and age were observed. Taken together, the findings of the present study suggest that ApoE effects on white-matter microstructure are less abundant than has been suggested in some previous studies.
Collapse
Affiliation(s)
- Lars Nyberg
- Umea Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | | |
Collapse
|
19
|
Bennett IJ, Madden DJ. Disconnected aging: cerebral white matter integrity and age-related differences in cognition. Neuroscience 2013; 276:187-205. [PMID: 24280637 DOI: 10.1016/j.neuroscience.2013.11.026] [Citation(s) in RCA: 327] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2013] [Revised: 11/08/2013] [Accepted: 11/13/2013] [Indexed: 12/13/2022]
Abstract
Cognition arises as a result of coordinated processing among distributed brain regions and disruptions to communication within these neural networks can result in cognitive dysfunction. Cortical disconnection may thus contribute to the declines in some aspects of cognitive functioning observed in healthy aging. Diffusion tensor imaging (DTI) is ideally suited for the study of cortical disconnection as it provides indices of structural integrity within interconnected neural networks. The current review summarizes results of previous DTI aging research with the aim of identifying consistent patterns of age-related differences in white matter integrity, and of relationships between measures of white matter integrity and behavioral performance as a function of adult age. We outline a number of future directions that will broaden our current understanding of these brain-behavior relationships in aging. Specifically, future research should aim to (1) investigate multiple models of age-brain-behavior relationships; (2) determine the tract-specificity versus global effect of aging on white matter integrity; (3) assess the relative contribution of normal variation in white matter integrity versus white matter lesions to age-related differences in cognition; (4) improve the definition of specific aspects of cognitive functioning related to age-related differences in white matter integrity using information processing tasks; and (5) combine multiple imaging modalities (e.g., resting-state and task-related functional magnetic resonance imaging; fMRI) with DTI to clarify the role of cerebral white matter integrity in cognitive aging.
Collapse
Affiliation(s)
- I J Bennett
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, United States
| | - D J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, United States; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, United States.
| |
Collapse
|
20
|
Papp KV, Kaplan RF, Springate B, Moscufo N, Wakefield DB, Guttmann CRG, Wolfson L. Processing speed in normal aging: effects of white matter hyperintensities and hippocampal volume loss. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2013; 21:197-213. [PMID: 23895570 PMCID: PMC3974573 DOI: 10.1080/13825585.2013.795513] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Changes in cognitive functioning are said to be part of normal aging. Quantitative MRI has made it possible to measure structural brain changes during aging which may underlie these decrements which include slowed information processing and memory loss. Much has been written on white matter hyperintensities (WMH), which are associated with cognitive deficits on tasks requiring processing speed and executive functioning, and hippocampal volume loss, which is associated with memory decline. Here we examine volumetric MRI measures of WMH and hippocampal volume loss together in relation to neuropsychological tests considered to be measures of executive functioning and processing speed in 81 non-demented elderly individuals, aged 75-90. Correlational analysis showed that when controlling for age, both greater WMH volume and smaller hippocampal volume were correlated with slower performances on most tests with the exception of a battery of continuous performance tests in which only WMH was correlated with slower reaction time (RT). We then performed a series of hierarchical multiple regression analyses to examine the independent contributions of greater WMH volume and reduced hippocampal volume to executive functioning and processing speed. The results showed that for the four measures requiring executive functioning and speed of processing, WMH volume and hippocampal volume combined predicted between 21.4% and 37% of the explained variance. These results suggest that WM integrity and hippocampal volume influence cognitive decline independently on tasks involving processing speed and executive function independent of age.
Collapse
Affiliation(s)
- Kathryn V Papp
- a Department of Psychiatry , University of Connecticut Health Center , Farmington , CT , USA
| | | | | | | | | | | | | |
Collapse
|
21
|
Jahanshad N, Kochunov PV, Sprooten E, Mandl RC, Nichols TE, Almasy L, Blangero J, Brouwer RM, Curran JE, de Zubicaray GI, Duggirala R, Fox PT, Hong LE, Landman BA, Martin NG, McMahon KL, Medland SE, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Hulshoff Pol HE, Bastin ME, McIntosh AM, Deary IJ, Thompson PM, Glahn DC. Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group. Neuroimage 2013; 81:455-469. [PMID: 23629049 DOI: 10.1016/j.neuroimage.2013.04.061] [Citation(s) in RCA: 312] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2013] [Revised: 03/28/2013] [Accepted: 04/10/2013] [Indexed: 10/26/2022] Open
Abstract
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).
Collapse
Affiliation(s)
- Neda Jahanshad
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA
| | - Peter V Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Emma Sprooten
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - René C Mandl
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thomas E Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK; Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford University, UK
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Rachel M Brouwer
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA; South Texas Veterans Administration Medical Center, San Antonio, TX, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | | | - Katie L McMahon
- University of Queensland, Center for Advanced Imaging, Brisbane, Australia
| | - Sarah E Medland
- Queensland Institute of Medical Research, Brisbane, Australia
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rene L Olvera
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Charles P Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Jessika E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Arthur W Toga
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Paul M Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.
| | - David C Glahn
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
| |
Collapse
|
22
|
Genetics of ageing-related changes in brain white matter integrity - a review. Ageing Res Rev 2013; 12:391-401. [PMID: 23128052 DOI: 10.1016/j.arr.2012.10.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2012] [Revised: 10/05/2012] [Accepted: 10/15/2012] [Indexed: 12/14/2022]
Abstract
White matter (WM) plays a vital role in the efficient transfer of information between grey matter regions. Modern imaging techniques such as diffusion tensor imaging (DTI) have enabled the examination of WM microstructural changes across the lifespan, but there is limited knowledge about the role genetics plays in the pattern and aetiology of age-related WM microstructural changes. Family and twin studies suggest that the heritability of WM integrity measures changes over the lifespan, with the common DTI measure, fractional anisotropy (FA), showing moderate to high heritability in adults. However, few heritability studies have been undertaken in older adults. Linkage studies in middle-aged adults suggest that specific regions on chromosomes 3 and 15 may harbour genetic variants for WM integrity. A number of studies have investigated candidate genes, with the APOE ɛ4 polymorphism being the most frequently studied. Although these candidate gene studies suggest associations of particular genes with WM integrity measures in some specific brain regions, the findings remain inconsistent due to differences in their methodologies, samples and the outcome measures used. The APOE ɛ4 allele has been associated with decreased WM integrity (FA) in the cingulum, corpus callosum and parahippocampal gyrus. Only one genome-wide association study of global WM integrity measures in older adults has been published, and reported suggestive single nucleotide polymorphisms await replication. Overall, genetic age-related WM integrity studies are lacking and a concerted effort to examine the genetic determinants of age-related decline in WM integrity is clearly needed to improve our understanding of the ageing brain.
Collapse
|
23
|
Lyall DM, Lopez LM, Bastin ME, Maniega SM, Penke L, Valdés Hernández MDC, Royle NA, Starr JM, Porteous DJ, Wardlaw JM, Deary IJ. ADRB2, brain white matter integrity and cognitive ageing in the Lothian Birth Cohort 1936. Behav Genet 2012; 43:13-23. [PMID: 23229623 DOI: 10.1007/s10519-012-9570-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2012] [Accepted: 11/29/2012] [Indexed: 10/27/2022]
Abstract
The non-synonymous mutations arg16gly (rs1042713) and gln27glu (rs1042714) in the adrenergic β-2 receptor gene (ADRB2) have been associated with cognitive function and brain white matter integrity. The current study aimed to replicate these findings and expand them to a broader range of cognitive and brain phenotypes. The sample used is a community-dwelling group of older people, the Lothian Birth Cohort 1936. They had been assessed cognitively at age 11 years, and undertook further cognitive assessments and brain diffusion MRI tractography in older age. The sample size range for cognitive function variables was N = 686-765, and for neuroimaging variables was N = 488-587. Previously-reported findings with these genetic variants did not replicate in this cohort. Novel, nominally significant associations were observed; notably, the integrity of the left arcuate fasciculus mediated the association between rs1042714 and the Digit Symbol Coding test of information processing speed. No significant associations of cognitive and brain phenotypes with ADRB2 variants survived correction for false discovery rate. Previous findings may therefore have been subject to type 1 error. Further study into links between ADRB2, cognitive function and brain white matter integrity is required.
Collapse
Affiliation(s)
- Donald M Lyall
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
24
|
Wardlaw JM, Bastin ME, Valdés Hernández MC, Maniega SM, Royle NA, Morris Z, Clayden JD, Sandeman EM, Eadie E, Murray C, Starr JM, Deary IJ. Brain aging, cognition in youth and old age and vascular disease in the Lothian Birth Cohort 1936: rationale, design and methodology of the imaging protocol. Int J Stroke 2012; 6:547-59. [PMID: 22111801 DOI: 10.1111/j.1747-4949.2011.00683.x] [Citation(s) in RCA: 149] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
RATIONALE As the population of the world ages, age-related cognitive decline is becoming an ever-increasing problem. However, the changes in brain structure that accompany normal aging, and the role they play in cognitive decline, remain to be fully elucidated. AIMS This study aims to characterize changes in brain structure in old age, and to investigate relationships between brain aging and cognitive decline using the Lothian Birth Cohort 1936. Here, we report the rationale, design and methodology of the brain and neurovascular imaging protocol developed to study this cohort. DESIGN An observational, longitudinal study of the Lothian Birth Cohort 1936, which comprises 1091 relatively healthy individuals now in their 70s and living in the Edinburgh area. They are surviving participants of the Scottish Mental Survey 1947, which involved a test of general intelligence taken at age 11 years. At age 70 years, the Lothian Birth Cohort 1936 undertook detailed cognitive, medical and genetic testing, and provided social, family, nutritional, quality of life and physical activity information. At mean age 73 years they underwent detailed brain MRI and neurovascular ultrasound imaging, repeat cognitive and other testing. The MRI protocol is designed to provide qualitative and quantitative measures of gray and white matter atrophy, severity and location of white matter lesions, enlarged perivascular spaces, brain mineral deposits, microbleeds and integrity of major white matter tracts. The neurovascular ultrasound imaging provides velocity, stenosis and intima-media thickness measurements of the carotid and vertebral arteries. STUDY This valuable imaging dataset will be used to determine which changes in brain structural parameters have the largest effects on cognitive aging. Analysis will include multimodal image analysis and multivariate techniques, such as factor analysis and structural equation modelling. Especially valuable is the ability within this sample to examine the influence that early life intelligence has on brain structural parameters in old age, and the role of genetic, vascular, educational and lifestyle factors. OUTCOMES Final outcomes include associations between early and late life cognition and integrity of key white matter tracts, volume of gray and white matter, myelination, brain water content, and visible abnormalities such as white matter lesions and mineral deposits; and influences of vascular risk factors, diet, environment, social metrics, education and genetics on healthy brain aging. It is intended that this information will help to inform and develop strategies for successful cognitive aging.
Collapse
Affiliation(s)
- Joanna M Wardlaw
- Brain Research Imaging Centre, Division of Clinical Neurosciences, University of Edinburgh, Edinburgh, UK
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
25
|
A genome-wide search for genetic influences and biological pathways related to the brain's white matter integrity. Neurobiol Aging 2012; 33:1847.e1-14. [PMID: 22425255 DOI: 10.1016/j.neurobiolaging.2012.02.003] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2011] [Revised: 01/31/2012] [Accepted: 02/04/2012] [Indexed: 01/04/2023]
Abstract
A genome-wide search for genetic variants influencing the brain's white matter integrity in old age was conducted in the Lothian Birth Cohort 1936 (LBC1936). At ∼73 years of age, members of the LBC1936 underwent diffusion MRI, from which 12 white matter tracts were segmented using quantitative tractography, and tract-averaged water diffusion parameters were determined (n = 668). A global measure of white matter tract integrity, g(FA), derived from principal components analysis of tract-averaged fractional anisotropy measurements, accounted for 38.6% of the individual differences across the 12 white matter tracts. A genome-wide search was performed with g(FA) on 535 individuals with 542,050 single nucleotide polymorphisms (SNPs). No single SNP association was genome-wide significant (all p > 5 × 10(-8)). There was genome-wide suggestive evidence for two SNPs, one in ADAMTS18 (p = 1.65 × 10(-6)), which is related to tumor suppression and hemostasis, and another in LOC388630 (p = 5.08 × 10(-6)), which is of unknown function. Although no gene passed correction for multiple comparisons in single gene-based testing, biological pathways analysis suggested evidence for an over-representation of neuronal transmission and cell adhesion pathways relating to g(FA).
Collapse
|
26
|
Holland PR, Bastin ME, Jansen MA, Merrifield GD, Coltman RB, Scott F, Nowers H, Khallout K, Marshall I, Wardlaw JM, Deary IJ, McCulloch J, Horsburgh K. MRI is a sensitive marker of subtle white matter pathology in hypoperfused mice. Neurobiol Aging 2011; 32:2325.e1-6. [PMID: 21194797 DOI: 10.1016/j.neurobiolaging.2010.11.009] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2010] [Revised: 11/02/2010] [Accepted: 11/10/2010] [Indexed: 11/16/2022]
Abstract
White matter (WM) abnormalities, possibly resulting from hypoperfusion, are key features of the aging human brain. It is unclear, however, whether in vivo magnetic resonance imaging (MRI) approaches, such as diffusion tensor and magnetization transfer MRI are sufficiently sensitive to detect subtle alterations to WM integrity in mouse models developed to study the aging brain. We therefore investigated the use of diffusion tensor and magnetization transfer MRI to measure structural changes in 4 WM tracts following 1 month of moderate hypoperfusion, which results in diffuse WM pathology in C57Bl/6J mice. Following MRI, brains were processed for evaluation of white and gray matter pathology. Significant reductions in fractional anisotropy were observed in the corpus callosum (p = 0.001) and internal capsule (p = 0.016), and significant decreases in magnetization transfer ratio were observed in the corpus callosum (p = 0.023), fimbria (p = 0.032), internal capsule (p = 0.046) and optic tract (p = 0.047) following hypoperfusion. Hypoperfused mice demonstrated diffuse axonal and myelin pathology which was essentially absent in control mice. Both fractional anisotropy and magnetization transfer ratio correlate with markers of myelin integrity/degradation and not axonal pathology. The study demonstrates that in vivo MRI is a sensitive measure of diffuse, subtle WM changes in the murine brain.
Collapse
Affiliation(s)
- Philip R Holland
- Centre for Cognitive Ageing and Cognitive Epidemiology, Centre for Cognitive and Neural Systems, University of Edinburgh, Edinburgh, UK.
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
27
|
Harris SE, Deary IJ. The genetics of cognitive ability and cognitive ageing in healthy older people. Trends Cogn Sci 2011; 15:388-94. [PMID: 21840749 DOI: 10.1016/j.tics.2011.07.004] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2011] [Revised: 07/14/2011] [Accepted: 07/15/2011] [Indexed: 01/01/2023]
Abstract
Determining the genetic influences on cognitive ability in old age and in cognitive ageing are important areas of research in an increasingly ageing society. Heritability studies indicate that genetic variants strongly influence cognitive ability differences throughout the lifespan, including in old age. To date, however, only the genes encoding apolipoprotein E (APOE) and possibly catechol-O-methyl transferase (COMT), brain-derived neurotrophic factor (BDNF) and dystrobrevin binding protein 1 (DTNBP1) have repeatedly been associated in candidate gene studies with cognitive decline or with cognitive ability in older individuals. Genome-wide association studies have identified further potential loci, but results are tentative. Advances in exome and/or whole-genome sequencing, transcriptomics, proteomics and methylomics hold significant promise for uncovering the genetic underpinnings of cognitive ability and decline in old age.
Collapse
Affiliation(s)
- Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, Medical Genetics Section, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | | |
Collapse
|
28
|
van Oers K, Mueller JC. Evolutionary genomics of animal personality. Philos Trans R Soc Lond B Biol Sci 2011; 365:3991-4000. [PMID: 21078651 DOI: 10.1098/rstb.2010.0178] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Research on animal personality can be approached from both a phenotypic and a genetic perspective. While using a phenotypic approach one can measure present selection on personality traits and their combinations. However, this approach cannot reconstruct the historical trajectory that was taken by evolution. Therefore, it is essential for our understanding of the causes and consequences of personality diversity to link phenotypic variation in personality traits with polymorphisms in genomic regions that code for this trait variation. Identifying genes or genome regions that underlie personality traits will open exciting possibilities to study natural selection at the molecular level, gene-gene and gene-environment interactions, pleiotropic effects and how gene expression shapes personality phenotypes. In this paper, we will discuss how genome information revealed by already established approaches and some more recent techniques such as high-throughput sequencing of genomic regions in a large number of individuals can be used to infer micro-evolutionary processes, historical selection and finally the maintenance of personality trait variation. We will do this by reviewing recent advances in molecular genetics of animal personality, but will also use advanced human personality studies as case studies of how molecular information may be used in animal personality research in the near future.
Collapse
Affiliation(s)
- Kees van Oers
- Netherlands Institute of Ecology (NIOO-KNAW), Heteren, The Netherlands.
| | | |
Collapse
|
29
|
Abstract
The structure of the brain is constantly changing from birth throughout the lifetime, meaning that normal aging, free from dementia, is associated with structural brain changes. This paper reviews recent evidence from magnetic resonance imaging (MRI) studies about age-related changes in the brain. The main conclusions are that (1) the brain shrinks in volume and the ventricular system expands in healthy aging. However, the pattern of changes is highly heterogeneous, with the largest changes seen in the frontal and temporal cortex, and in the putamen, thalamus, and accumbens. With modern approaches to analysis of MRI data, changes in cortical thickness and subcortical volume can be tracked over periods as short as one year, with annual reductions of between 0.5% and 1.0% in most brain areas. (2) The volumetric brain reductions in healthy aging are likely only to a minor extent related to neuronal loss. Rather, shrinkage of neurons, reductions of synaptic spines, and lower numbers of synapses probably account for the reductions in grey matter. In addition, the length of myelinated axons is greatly reduced, up to almost 50%. (3) Reductions in specific cognitive abilities--for instance processing speed, executive functions, and episodic memory--are seen in healthy aging. Such reductions are to a substantial degree mediated by neuroanatomical changes, meaning that between 25% and 100% of the differences between young and old participants in selected cognitive functions can be explained by group differences in structural brain characteristics.
Collapse
Affiliation(s)
- Anders M Fjell
- Center for the Study of Human Cognition, Department of Psychology, University of Oslo, Norway.
| | | |
Collapse
|
30
|
A general factor of brain white matter integrity predicts information processing speed in healthy older people. J Neurosci 2010; 30:7569-74. [PMID: 20519531 DOI: 10.1523/jneurosci.1553-10.2010] [Citation(s) in RCA: 228] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Human white matter integrity has been related to information processing speed, but it is unknown whether impaired integrity results from localized processes or is a general property shared across white matter tracts. Based on diffusion MRI scans of 132 healthy individuals with a narrow age range around 72 years, the integrity of eight major white matter tracts was quantified using probabilistic neighborhood tractography. Principal component analyses (PCAs) were conducted on the correlations between the eight tracts, separately for four tract-averaged integrity parameters: fractional anisotropy, mean diffusivity, and radial and axial diffusivity. For all four parameters, the PCAs revealed a single general factor explaining approximately 45% of the individual differences across all eight tracts. Individuals' scores on a general factor that captures the common variance in white matter integrity had significant associations with a general factor of information processing speed for fractional anisotropy (r = -0.24, p = 0.007) and radial diffusivity (r = 0.21, p = 0.016), but not with general intelligence or memory factors. Individual tracts showed no associations beyond what the common integrity factor explained. Just as different types of cognitive ability tests share much of their variance, these novel findings show that a substantial amount of variance in white matter integrity is shared between different tracts. Therefore, impaired cortical connection is substantially a global process affecting various major tracts simultaneously. Further studies should investigate whether these findings relate more to the role of tract integrity and information processing speed in nonpathological cognitive aging or in lifelong-stable processes.
Collapse
|
31
|
Kulminski AM, Culminskaya I, Ukraintseva SV, Arbeev KG, Land KC, Yashin AI. Beta2-adrenergic receptor gene polymorphisms as systemic determinants of healthy aging in an evolutionary context. Mech Ageing Dev 2010; 131:338-45. [PMID: 20399803 DOI: 10.1016/j.mad.2010.04.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2009] [Revised: 03/25/2010] [Accepted: 04/09/2010] [Indexed: 10/19/2022]
Abstract
The Gln(27)Glu polymorphism but not the Arg(16)Gly polymorphism of the beta2-adrenergic receptor (ADRB2) gene appears to be associated with a broad range of aging-associated phenotypes, including cancers at different sites, myocardial infarction (MI), intermittent claudication (IC), and overall/healthy longevity in the Framingham Heart Study Offspring cohort. The Gln(27)Gln genotype increases risks of cancer, MI and IC, whereas the Glu(27) allele or, equivalently, the Gly(16)Glu(27) haplotype tends to be protective against these diseases. Genetic associations with longevity are of opposite nature at young-old and oldest-old ages highlighting the phenomenon of antagonistic pleiotropy. The mechanism of antagonistic pleiotropy is associated with an evolutionary-driven advantage of carriers of a derived Gln(27) allele at younger ages and their survival disadvantage at older ages as a result of increased risks of cancer, MI and IC. The ADRB2 gene can play an important systemic role in healthy aging in evolutionary context that warrants exploration in other populations.
Collapse
Affiliation(s)
- Alexander M Kulminski
- Center for Population Health and Aging, Duke University Population Research Institute, Durham, NC 27708, USA.
| | | | | | | | | | | |
Collapse
|