The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior.

[1]  P. Basser,et al.  Focal magnetic stimulation of an axon , 1994, IEEE Transactions on Biomedical Engineering.

[2]  Paul M. Thompson,et al.  Fractional anisotropy of cerebral white matter and thickness of cortical gray matter across the lifespan , 2011, NeuroImage.

[3]  Joanna M. Wardlaw,et al.  A General Factor of Brain White Matter Integrity Predicts Information Processing Speed in Healthy Older People , 2010, The Journal of Neuroscience.

[4]  J. J. Ryan,et al.  Wechsler Adult Intelligence Scale-III , 2001 .

[5]  Abraham Z. Snyder,et al.  Human Connectome Project informatics: Quality control, database services, and data visualization , 2013, NeuroImage.

[6]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[7]  Christina N. Lessov-Schlaggar,et al.  Nicotine Addiction in Light Smoking African American Mothers , 2010, Journal of addiction medicine.

[8]  A A Schäffer,et al.  Towards a complete North American Anabaptist genealogy: A systematic approach to merging partially overlapping genealogy resources. , 1999, American journal of medical genetics.

[9]  F. Aboitiz,et al.  Brain connections: interhemispheric fiber systems and anatomical brain asymmetries in humans. , 1992, Biological research.

[10]  Owen Carmichael,et al.  White matter lesions and brain gray matter volume in cognitively normal elders , 2012, Neurobiology of Aging.

[11]  Thomas R. Knösche,et al.  White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI , 2013, NeuroImage.

[12]  Antonio Bastone,et al.  New mutations in MAPT gene causing frontotemporal lobar degeneration: biochemical and structural characterization , 2012, Neurobiology of Aging.

[13]  Wiro J Niessen,et al.  White matter microstructural integrity and cognitive function in a general elderly population. , 2009, Archives of general psychiatry.

[14]  G. D. Erausquin,et al.  What does anisotropy measure? Insights from increased and decreased anisotropy in selective fiber tracts in schizophrenia , 2012, Front. Integr. Neurosci..

[15]  T. Salthouse.  When does age-related cognitive decline begin? , 2009, Neurobiology of Aging.

[16]  Harold Alan Pincus,et al.  Prevalence and treatment of mental disorders, 1990 to 2003. , 2005, The New England journal of medicine.

[17]  P. Fox,et al.  High Dimensional Endophenotype Ranking in the Search for Major Depression Risk Genes , 2012, Biological Psychiatry.

[18]  J. Blangero,et al.  Quantitative genetic analysis of skin reflectance: a multivariate approach. , 1992, Human biology.

[19]  Peter Kochunov,et al.  Genetic Contributions to the Midsagittal Area of the Corpus Callosum , 2012, Twin Research and Human Genetics.

[20]  Paul M. Thompson,et al.  Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA–DTI working group , 2013, NeuroImage.

[21]  Paul M. Thompson,et al.  Investigating brain connectivity heritability in a twin study using diffusion imaging data , 2014, NeuroImage.

[22]  N. Jahanshad,et al.  Common Alzheimer's Disease Risk Variant Within the CLU Gene Affects White Matter Microstructure in Young Adults , 2011, The Journal of Neuroscience.

[23]  A. Toga,et al.  Gene Network Effects on Brain Microstructure and Intellectual Performance Identified in 472 Twins , 2012, The Journal of Neuroscience.

[24]  Benedicto Crespo-Facorro,et al.  White matter integrity and cognitive impairment in first-episode psychosis. , 2010, The American journal of psychiatry.

[25]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[26]  Arthur W. Toga,et al.  Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template , 2008, NeuroImage.

[27]  Noelle E Carlozzi,et al.  VI. NIH Toolbox Cognition Battery (CB): measuring processing speed. , 2013, Monographs of the Society for Research in Child Development.

[28]  Agatha D. Lee,et al.  Genetics of Brain Fiber Architecture and Intellectual Performance , 2009, The Journal of Neuroscience.

[29]  N. Jahanshad,et al.  Brain structure in healthy adults is related to serum transferrin and the H63D polymorphism in the HFE gene , 2012, Proceedings of the National Academy of Sciences.

[30]  Derek K. Jonesa,et al.  Controversies White matter integrity , fi ber count , and other fallacies : The do ' s and don ' ts of diffusion MRI , 2012 .

[31]  Patrick R Hof,et al.  Diffusion tensor imaging findings in first-episode and chronic schizophrenia patients. , 2008, The American journal of psychiatry.

[32]  N. Woodward,et al.  Processing speed impairment in schizophrenia is mediated by white matter integrity , 2014, Psychological Medicine.

[33]  A C Heath,et al.  Common genetic and environmental contributions to post-traumatic stress disorder and alcohol dependence in young women , 2010, Psychological Medicine.

[34]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[35]  Paul M. Thompson,et al.  journal homepage: www.elsevier.com/locate/ynimg Genetic influences on brain asymmetry: A DTI study of 374 twins and siblings , 2022 .

[36]  Peter Stoeter,et al.  Correlation of Brain White Matter Diffusion Anisotropy and Mean Diffusivity with Reaction Time in an Oddball Task , 2009, Neuropsychobiology.

[37]  O. Josephs,et al.  Retrospective Correction of Physiological Noise in DTI Using an Extended Tensor Model and Peripheral Measurements , 2012, Magnetic resonance in medicine.

[38]  Steen Moeller,et al.  Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project , 2013, NeuroImage.

[39]  Kenneth J. Smith,et al.  Conduction in Segmentally Demyelinated Mammalian Central Axons , 1997, The Journal of Neuroscience.

[40]  D. Glahn,et al.  Fractional anisotropy of water diffusion in cerebral white matter across the lifespan , 2012, Neurobiology of Aging.

[41]  A. Scheibel,et al.  Fiber composition of the human corpus callosum , 1992, Brain Research.

[42]  M. Bennett,et al.  Relative conduction velocities of small myelinated and non-myelinated fibres in the central nervous system. , 1972, Nature: New biology.

[43]  A. David,et al.  Processing speed deficits in schizophrenia: reexamining the evidence. , 2010, The American journal of psychiatry.

[44]  L. Almasy,et al.  Bivariate quantitative trait linkage analysis: Pleiotropy versus co‐incident linkages , 1997, Genetic epidemiology.

[45]  G. Bartzokis.  Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease , 2004, Neurobiology of Aging.

[46]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[47]  Richard C. Gershon,et al.  NIH Toolbox Cognitive Battery (NIHTB-CB): The NIHTB Pattern Comparison Processing Speed Test , 2014, Journal of the International Neuropsychological Society.

[48]  Paul M. Thompson,et al.  Lifespan trajectory of myelin integrity and maximum motor speed , 2010, Neurobiology of Aging.

[49]  H. Markus,et al.  decline which is associated with working memory white matter change over a 2 year follow-up Diffusion tensor imaging detects age related , 2009 .

[50]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[51]  R. Morris,et al.  Imaging age‐related cognitive decline: A comparison of diffusion tensor and magnetization transfer MRI , 2009, Journal of magnetic resonance imaging : JMRI.

[52]  Peter Kochunov,et al.  Perfusion shift from white to gray matter may account for processing speed deficits in schizophrenia , 2015, Human brain mapping.

[53]  G. Wylie,et al.  Altered effective connectivity during performance of an information processing speed task in multiple sclerosis , 2012, Multiple sclerosis.

[54]  Peter Kochunov,et al.  Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging , 2013, Proceedings of the National Academy of Sciences.

[55]  Steen Moeller,et al.  Advances in diffusion MRI acquisition and processing in the Human Connectome Project , 2013, NeuroImage.

[56]  Timothy Edward John Behrens,et al.  Characterization and propagation of uncertainty in diffusion‐weighted MR imaging , 2003, Magnetic resonance in medicine.

[57]  N. Raz,et al.  Aging white matter and cognition: Differential effects of regional variations in diffusion properties on memory, executive functions, and speed , 2009, Neuropsychologia.

[58]  R. Kikinis,et al.  A review of diffusion tensor imaging studies in schizophrenia. , 2007, Journal of psychiatric research.

[59]  M. Horsfield,et al.  Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging , 1999, Magnetic resonance in medicine.

[60]  Peter T. Fox,et al.  Can structural MRI indices of cerebral integrity track cognitive trends in executive control function during normal maturation and adulthood? , 2009, Human brain mapping.

[61]  M Mallar Chakravarty,et al.  Alterations of Superficial White Matter in Schizophrenia and Relationship to Cognitive Performance , 2013, Neuropsychopharmacology.

[62]  Bryon A. Mueller,et al.  The development of corpus callosum microstructure and associations with bimanual task performance in healthy adolescents , 2008, NeuroImage.

[63]  P. Zijl,et al.  Correction of motional artifacts in diffusion‐weighted images using a reference phase map , 1995, Magnetic resonance in medicine.

[64]  Jack L. Lancaster,et al.  Processing speed is correlated with cerebral health markers in the frontal lobes as quantified by neuroimaging , 2010, NeuroImage.

[65]  Daniel Rueckert,et al.  Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data , 2006, NeuroImage.

[66]  E. Bullmore,et al.  Meta-analysis of diffusion tensor imaging studies in schizophrenia , 2009, Schizophrenia Research.

[67]  Steen Moeller,et al.  Heritability of fractional anisotropy in human white matter: A comparison of Human Connectome Project and ENIGMA-DTI data , 2015, NeuroImage.

[68]  L. Almasy,et al.  Variance component methods for analysis of complex phenotypes. , 2010, Cold Spring Harbor protocols.

[69]  E. Akbudak,et al.  Encoding of anisotropic diffusion with tetrahedral gradients: A general mathematical diffusion formalism and experimental results , 1996, Magnetic resonance in medicine.