GENETIC INFLUENCE OF APOE 4 GENOTYPE ON HIPPOCAMPAL MORPHOMETRY-AN N = 725 SURFACE-BASED ADNI STUDY

The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer’s disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 non-carriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database – the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling’s T2 test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.

[1]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[2]  Nick C Fox,et al.  The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods , 2008, Journal of magnetic resonance imaging : JMRI.

[3]  M N Rossor,et al.  Correlation between rates of brain atrophy and cognitive decline in AD , 1999, Neurology.

[4]  S. Thibodeau,et al.  Preclinical evidence of Alzheimer's disease in persons homozygous for the epsilon 4 allele for apolipoprotein E. , 1996, The New England journal of medicine.

[5]  C. Jack,et al.  Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD , 2004, Neurology.

[6]  Yalin Wang,et al.  Disease classification with hippocampal shape invariants , 2009, Hippocampus.

[7]  Paul M. Thompson,et al.  Mapping hippocampal and ventricular change in Alzheimer disease , 2004, NeuroImage.

[8]  J. Haines,et al.  Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. , 1993, Science.

[9]  Paul Suetens,et al.  A Viscous Fluid Model for Multimodal Non-rigid Image Registration Using Mutual Information , 2002, MICCAI.

[10]  Michael I. Miller,et al.  Large Deformation Diffeomorphism and Momentum Based Hippocampal Shape Discrimination in Dementia of the Alzheimer type , 2007, IEEE Transactions on Medical Imaging.

[11]  Morten Bro-Nielsen,et al.  Fast Fluid Registration of Medical Images , 1996, VBC.

[12]  Xiao Han,et al.  A Topology Preserving Level Set Method for Geometric Deformable Models , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Carole Dufouil,et al.  No epsilon4 gene dose effect on hippocampal atrophy in a large MRI database of healthy elderly subjects. , 2005, NeuroImage.

[14]  Shing-Tung Yau,et al.  Geometric Compression Using Riemann Surface Structure , 2003, Commun. Inf. Syst..

[15]  Douglas W. Jones,et al.  Shape analysis of brain ventricles using SPHARM , 2001, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001).

[16]  Norbert Schuff,et al.  Accurate measurement of brain changes in longitudinal MRI scans using tensor-based morphometry , 2011, NeuroImage.

[17]  Paul M. Thompson,et al.  Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis , 2013, NeuroImage.

[18]  Paul M. Thompson,et al.  APOE4 is associated with greater atrophy of the hippocampal formation in Alzheimer's disease , 2011, NeuroImage.

[19]  Wiro J Niessen,et al.  A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline. , 2010, Brain : a journal of neurology.

[20]  Thomas E. Nichols,et al.  The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data , 2014, Brain Imaging and Behavior.

[21]  Andrew J Saykin,et al.  Parametric surface modeling and registration for comparison of manual and automated segmentation of the hippocampus , 2009, Hippocampus.

[22]  A. Fagan,et al.  APOE predicts amyloid‐beta but not tau Alzheimer pathology in cognitively normal aging , 2010, Annals of neurology.

[23]  Paul M. Thompson,et al.  Brain Surface Conformal Parameterization With the Ricci Flow , 2012, IEEE Transactions on Medical Imaging.

[24]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[25]  Richard J. Caselli,et al.  Amyloid load in nondemented brains correlates with APOE e4 , 2010, Neuroscience Letters.

[26]  Paul A. Yushkevich,et al.  Segmentation, registration, and measurement of shape variation via image object shape , 1999, IEEE Transactions on Medical Imaging.

[27]  Paul M. Thompson,et al.  Surface fluid registration of conformal representation: Application to detect disease burden and genetic influence on hippocampus , 2013, NeuroImage.

[28]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[29]  Clifford R. Jack,et al.  Predicting Clinical Scores from Magnetic Resonance Scans in Alzheimer's Disease , 2010, NeuroImage.

[30]  Karl J. Friston,et al.  Reproducibility of PET Activation Studies: Lessons from a Multi-Center European Experiment EU Concerted Action on Functional Imaging , 1996, NeuroImage.

[31]  Jun Ma,et al.  Atlas Generation for Subcortical and Ventricular Structures With Its Applications in Shape Analysis , 2010, IEEE Transactions on Image Processing.

[32]  C. Jack,et al.  Alzheimer's Disease Neuroimaging Initiative , 2008 .

[33]  K. Worsley,et al.  THE DETECTION OF LOCAL SHAPE CHANGES VIA THE GEOMETRY OF HOTELLING’S T 2 FIELDS 1 , 1999 .

[34]  H. Hotelling The Generalization of Student’s Ratio , 1931 .

[35]  S. Joshi,et al.  Early DAT is distinguished from aging by high-dimensional mapping of the hippocampus , 2000, Neurology.

[36]  Michael I. Miller,et al.  APOE related hippocampal shape alteration in geriatric depression , 2009, NeuroImage.

[37]  N. Ayache,et al.  Log‐Euclidean metrics for fast and simple calculus on diffusion tensors , 2006, Magnetic resonance in medicine.

[38]  Neil Roberts,et al.  Statistical analysis of normal and abnormal dissymmetry in volumetric medical images , 1998, Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162).

[39]  C. Jack,et al.  Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) , 2005, Alzheimer's & Dementia.

[40]  Yi-Yu Chou,et al.  Global and regional alterations of hippocampal anatomy in long‐term meditation practitioners , 2013, Human brain mapping.

[41]  Nick C Fox,et al.  The clinical use of structural MRI in Alzheimer disease , 2010, Nature Reviews Neurology.

[42]  D. Selkoe Alzheimer's disease. , 2011, Cold Spring Harbor perspectives in biology.

[43]  Stephen M. Smith,et al.  A Bayesian model of shape and appearance for subcortical brain segmentation , 2011, NeuroImage.

[44]  Michael I. Miller,et al.  Landmark matching via large deformation diffeomorphisms , 2000, IEEE Trans. Image Process..

[45]  L. Berg Clinical Dementia Rating (CDR). , 1988, Psychopharmacology bulletin.

[46]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[47]  Paul M. Thompson,et al.  Multivariate Tensor-Based Brain Anatomical Surface Morphometry via Holomorphic One-Forms , 2009, MICCAI.

[48]  Sung Yong Shin,et al.  A multi-resolution scheme for distortion-minimizing mapping between human subcortical structures based on geodesic construction on Riemannian manifolds , 2011, NeuroImage.

[49]  O. Simonin,et al.  Geometric Compression Using Riemann Surface Structure , 2004 .

[50]  Polina Golland,et al.  Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI , 2009, Hippocampus.

[51]  Douglas W. Jones,et al.  Morphometric analysis of lateral ventricles in schizophrenia and healthy controls regarding genetic and disease-specific factors. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[52]  G. Alexander,et al.  Correlations between apolipoprotein E ε4 gene dose and brain-imaging measurements of regional hypometabolism , 2005 .

[53]  Michael I. Miller,et al.  Changes in hippocampal volume and shape across time distinguish dementia of the Alzheimer type from healthy aging☆ , 2003, NeuroImage.

[54]  M A Pericak-Vance,et al.  Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease. , 1993, Neurology.

[55]  Stephan Heckers,et al.  The hippocampus in schizophrenia. , 2004, The American journal of psychiatry.

[56]  Eric M Reiman,et al.  Linking Brain Imaging and Genomics in the Study of Alzheimer's Disease and Aging , 2007, Annals of the New York Academy of Sciences.

[57]  Sirkka Goebeler,et al.  Apolipoprotein E–dependent accumulation of Alzheimer disease–related lesions begins in middle age , 2009, Annals of neurology.

[58]  Marisa O. Hollinshead,et al.  Identification of common variants associated with human hippocampal and intracranial volumes , 2012, Nature Genetics.

[59]  Carole Dufouil,et al.  No ɛ4 gene dose effect on hippocampal atrophy in a large MRI database of healthy elderly subjects , 2005, NeuroImage.

[60]  Guojun Lu,et al.  Review of shape representation and description techniques , 2004, Pattern Recognit..

[61]  Michael Weiner,et al.  Nearly automatic segmentation of hippocampal subfields in in vivo focal T2-weighted MRI , 2010, NeuroImage.

[62]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[63]  Michael Elad,et al.  Shape from moments - an estimation theory perspective , 2004, IEEE Transactions on Signal Processing.

[64]  G. Christensen,et al.  Hippocampal MR imaging morphometry by means of general pattern matching. , 1996, Radiology.

[65]  Michael I. Miller,et al.  Abnormalities of hippocampal surface structure in very mild dementia of the Alzheimer type , 2006, NeuroImage.

[66]  Moo K. Chung,et al.  Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination , 2012, NIPS.

[67]  Martin Styner,et al.  Boundary and Medial Shape Analysis of the Hippocampus in Schizophrenia , 2003, MICCAI.

[68]  Jyrki Lötjönen,et al.  Measurement of hippocampal atrophy using 4D graph-cut segmentation: Application to ADNI , 2010, NeuroImage.

[69]  P. Davies,et al.  Dementia of the Alzheimer type. , 1980, Annual review of neuroscience.

[70]  M. Weiner,et al.  Selective effect of age, Apo e4, and Alzheimer's disease on hippocampal subfields , 2009, Hippocampus.

[71]  Clifford R. Jack,et al.  Antemortem MRI based STructural Abnormality iNDex (STAND)-scores correlate with postmortem Braak neurofibrillary tangle stage , 2008, NeuroImage.

[72]  J. Reiber,et al.  Ventricular shape biomarkers for Alzheimer's disease in clinical MR images , 2008, Magnetic resonance in medicine.

[73]  A. Dale,et al.  Subregional neuroanatomical change as a biomarker for Alzheimer's disease , 2009, Proceedings of the National Academy of Sciences.

[74]  Paul M. Thompson,et al.  Multivariate Tensor-based Morphometry on Surfaces: Application to Mapping Ventricular Abnormalities in Hiv/aids Mapping Methods Have Revealed the 3d Profile of Structural Brain , 2022 .

[75]  Anqi Qiu,et al.  Evolution of hippocampal shapes across the human lifespan , 2013, Human brain mapping.

[76]  Norbert Schuff,et al.  Mapping Alzheimer's Disease Progression in 1309 Mri Scans: Power Estimates for Different Inter-scan Intervals ☆ ⁎ and the Alzheimer's Disease Neuroimaging Initiative , 2022 .

[77]  Greg Miller,et al.  Alzheimer's biomarker initiative hits its stride. , 2009, Science.

[78]  Amity E. Green,et al.  Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls , 2009, Human brain mapping.

[79]  Paul M. Thompson,et al.  Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors , 2008, IEEE Transactions on Medical Imaging.

[80]  Paul M. Thompson,et al.  Inverse Consistent Mapping in 3D Deformable Image Registration: Its Construction and Statistical Properties , 2005, IPMI.

[81]  C. Studholme,et al.  Brain atrophy associated with baseline and longitudinal measures of cognition , 2011, Neurobiology of Aging.

[82]  Rachel L. Mistur,et al.  Subregional hippocampal atrophy predicts Alzheimer's dementia in the cognitively normal , 2010, Neurobiology of Aging.

[83]  Clifford R. Jack,et al.  Alzheimer's disease diagnosis in individual subjects using structural MR images: Validation studies , 2008, NeuroImage.

[84]  Martin Styner,et al.  Common variants in psychiatric risk genes predict brain structure at birth. , 2014, Cerebral cortex.

[85]  A. W. Toga,et al.  3D maps localize caudate nucleus atrophy in 400 Alzheimer’s disease, mild cognitive impairment, and healthy elderly subjects , 2010, Neurobiology of Aging.

[86]  C. Jack,et al.  MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD , 2003, Neurology.

[87]  David A. Bennett,et al.  Neuropathologic intermediate phenotypes enhance association to Alzheimer susceptibility alleles , 2009, Neurology.

[88]  Michael Weiner,et al.  Automated 3d Mapping of Baseline and 12-month Associations between Three Verbal Memory Measures and Hippocampal Atrophy in 490 Adni Subjects and the Alzheimer's Disease Neuroimaging Initiative , 2022 .

[89]  Craig E. L. Stark,et al.  High-resolution structural and functional MRI of hippocampal CA3 and dentate gyrus in patients with amnestic Mild Cognitive Impairment , 2010, NeuroImage.

[90]  G. Alexander,et al.  Fibrillar amyloid-β burden in cognitively normal people at 3 levels of genetic risk for Alzheimer's disease , 2009, Proceedings of the National Academy of Sciences.

[91]  Hervé Delingette,et al.  Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis , 1999, IPMI.

[92]  Jerry L Prince,et al.  A computerized approach for morphological analysis of the corpus callosum. , 1996, Journal of computer assisted tomography.

[93]  J. Haines,et al.  Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. , 1997, JAMA.

[94]  Michael Weiner,et al.  Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer's disease, mild cognitive impairment and elderly controls , 2009, NeuroImage.

[95]  H. Soininen,et al.  Volumes of hippocampus, amygdala and frontal lobe in Alzheimer patients with different apolipoprotein E genotypes , 1995, Neuroscience.

[96]  Yalin Wang,et al.  A Multivariate Surface-Based Analysis of the Putamen in Premature Newborns: Regional Differences within the Ventral Striatum , 2013, PloS one.

[97]  D. Weinberger,et al.  Genetic variability of human brain size and cortical gyral patterns. , 1997, Brain : a journal of neurology.

[98]  G. Vogler,et al.  Apolipoprotein E polymorphism in a Danish population compared to findings in 45 other study populations around the world , 1992, Genetic epidemiology.

[99]  R. Castellani,et al.  Alzheimer disease. , 2010, Disease-a-month : DM.

[100]  Xianfeng Gu,et al.  Matching 3D Shapes Using 2D Conformal Representations , 2004, MICCAI.

[101]  David F. Tate,et al.  Reliability and validity of MRI-based automated volumetry software relative to auto-assisted manual measurement of subcortical structures in HIV-infected patients from a multisite study , 2010, NeuroImage.

[102]  G. Alexander,et al.  Declining brain activity in cognitively normal apolipoprotein E ɛ4 heterozygotes: A foundation for using positron emission tomography to efficiently test treatments to prevent Alzheimer's disease , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[103]  N R Relkin,et al.  Increased apolipoprotein E ϵ4 in epilepsy with senile plaques , 1997, Annals of neurology.

[104]  Nick C Fox,et al.  Volumetric MRI and cognitive measures in Alzheimer disease , 2008, Journal of Neurology.

[105]  Daniel Bandy,et al.  Hippocampal volumes in cognitively normal persons at genetic risk for Alzheimer's disease , 1998, Annals of neurology.

[106]  Peter Davies,et al.  Identification of normal and pathological aging in prospectively studied nondemented elderly humans , 1992, Neurobiology of Aging.

[107]  Norbert Schuff,et al.  Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls , 2009, NeuroImage.

[108]  G. Alexander,et al.  Longitudinal modeling of age-related memory decline and the APOE epsilon4 effect. , 2009, The New England journal of medicine.

[109]  Arthur W. Toga,et al.  Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment , 2011, NeuroImage.

[110]  B. Hyman,et al.  Amyloid-dependent and amyloid-independent stages of Alzheimer disease. , 2011, Archives of neurology.

[111]  Moo K. Chung,et al.  Computational Neuroanatomy: The Methods , 2012 .

[112]  J D Watson,et al.  Nonparametric Analysis of Statistic Images from Functional Mapping Experiments , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[113]  C. Rowe,et al.  The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging: methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer's disease , 2009, International Psychogeriatrics.

[114]  Richard J. Caselli,et al.  Correlations Between Apolipoprotein E ε4 Gene Dose and Whole Brain Atrophy Rates , 2007 .

[115]  R. Gnanadesikan,et al.  Multivariate Analysis of Variance (MANOVA) , 1962 .