Structural Neuroimaging Genetics Interactions in Alzheimer's Disease.

This article investigates late-onset cognitive impairment using neuroimaging and genetics biomarkers for Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Eight-hundred and eight ADNI subjects were identified and divided into three groups: 200 subjects with Alzheimer's disease (AD), 383 subjects with mild cognitive impairment (MCI), and 225 asymptomatic normal controls (NC). Their structural magnetic resonance imaging (MRI) data were parcellated using BrainParser, and the 80 most important neuroimaging biomarkers were extracted using the global shape analysis Pipeline workflow. Using Plink via the Pipeline environment, we obtained 80 SNPs highly-associated with the imaging biomarkers. In the AD cohort, rs2137962 was significantly associated bilaterally with changes in the hippocampi and the parahippocampal gyri, and rs1498853, rs288503, and rs288496 were associated with the left and right hippocampi, the right parahippocampal gyrus, and the left inferior temporal gyrus. In the MCI cohort, rs17028008 and rs17027976 were significantly associated with the right caudate and right fusiform gyrus, rs2075650 (TOMM40) was associated with the right caudate, and rs1334496 and rs4829605 were significantly associated with the right inferior temporal gyrus. In the NC cohort, Chromosome 15 [rs734854 (STOML1), rs11072463 (PML), rs4886844 (PML), and rs1052242 (PML)] was significantly associated with both hippocampi and both insular cortices, and rs4899412 (RGS6) was significantly associated with the caudate. We observed significant correlations between genetic and neuroimaging phenotypes in the 808 ADNI subjects. These results suggest that differences between AD, MCI, and NC cohorts may be examined by using powerful joint models of morphometric, imaging and genotypic data.

[1]  M. Kotze,et al.  Clinical relevance of apolipoprotein E genotyping based on a family history of Alzheimer's disease. , 2015, Current Alzheimer research.

[2]  Sam Griffiths-Jones,et al.  Bias in microRNA functional enrichment analysis , 2015, Bioinform..

[3]  J. Haines,et al.  A rare mutation in UNC5C predisposes to late-onset Alzheimer's disease and increases neuronal cell death , 2014, Nature Medicine.

[4]  Matthew Schreiber,et al.  Alzheimer’s Disease Genetics , 2014, Current Behavioral Neuroscience Reports.

[5]  Carlos Cruchaga,et al.  The epigenetic landscape of Alzheimer's disease , 2014, Nature Neuroscience.

[6]  J. Hardy,et al.  Genetics of Alzheimer’s Disease , 2014, Neurotherapeutics.

[7]  A. Goate,et al.  Alzheimer’s Disease Genetics: From the Bench to the Clinic , 2014, Neuron.

[8]  Ronald C. Petersen,et al.  HMGCR is a genetic modifier for risk, age of onset and MCI conversion to Alzheimer’s disease in a three cohorts study , 2014, Molecular Psychiatry.

[9]  M. Barmada,et al.  Connecting the Dots: Potential of Data Integration to Identify Regulatory SNPs in Late-Onset Alzheimer's Disease GWAS Findings , 2014, PloS one.

[10]  Peter M Visscher,et al.  Explaining additional genetic variation in complex traits. , 2014, Trends in genetics : TIG.

[11]  Robert C. Green,et al.  Genome-wide association study of the rate of cognitive decline in Alzheimer's disease , 2014, Alzheimer's & Dementia.

[12]  L. Fratiglioni,et al.  The influence of APOE and TOMM40 polymorphisms on hippocampal volume and episodic memory in old age , 2013, Front. Hum. Neurosci..

[13]  Thomas W. Mühleisen,et al.  Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease , 2013, Nature Genetics.

[14]  L. Tran,et al.  Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease , 2013, Cell.

[15]  M. Tejada-Simon,et al.  Impaired cognitive function and reduced anxiety‐related behavior in a promyelocytic leukemia (PML) tumor suppressor protein‐deficient mouse , 2013, Genes, brain, and behavior.

[16]  Christine Van Broeckhoven,et al.  Genetic insights in Alzheimer's disease , 2013, The Lancet Neurology.

[17]  J. H. Boo,et al.  Critical role of presenilin-dependent γ-secretase activity in DNA damage-induced promyelocytic leukemia protein expression and apoptosis , 2013, Cell Death and Differentiation.

[18]  John Hardy,et al.  TOMM40 association with Alzheimer disease: tales of APOE and linkage disequilibrium. , 2012, Archives of neurology.

[19]  Simon Lovestone,et al.  Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS) , 2012, Neurobiology of Aging.

[20]  M. Riemenschneider,et al.  Plasmalogens Inhibit APP Processing by Directly Affecting γ-Secretase Activity in Alzheimer's Disease , 2012, TheScientificWorldJournal.

[21]  Jie Huang,et al.  RGS Proteins in Heart: Brakes on the Vagus , 2012, Front. Physio..

[22]  Arthur W. Toga,et al.  Applications of the pipeline environment for visual informatics and genomics computations , 2011, BMC Bioinformatics.

[23]  Michael Weiner,et al.  Voxelwise gene-wide association study (vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects , 2011, NeuroImage.

[24]  Nick C Fox,et al.  Common variants in ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease , 2011, Nature Genetics.

[25]  D. Holtzman,et al.  Apolipoprotein E in Alzheimer's disease and other neurological disorders , 2011, The Lancet Neurology.

[26]  Nick C Fox,et al.  Common variants at ABCA 7 , MS 4 A 6 A / MS 4 A 4 E , EPHA 1 , CD 33 and CD 2 AP are associated with Alzheimer ’ s disease , 2011 .

[27]  Michael Weiner,et al.  Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort , 2010, NeuroImage.

[28]  Andrew J. Saykin,et al.  Voxelwise genome-wide association study (vGWAS) , 2010, NeuroImage.

[29]  Ivo D Dinov,et al.  SOCR Motion Charts: An Efficient, Open-Source, Interactive and Dynamic Applet for Visualizing Longitudinal Multivariate Data , 2010, Journal of statistics education : an international journal on the teaching and learning of statistics.

[30]  D. Stott Parker,et al.  Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline , 2010, PloS one.

[31]  Alkes L. Price,et al.  New approaches to population stratification in genome-wide association studies , 2010, Nature Reviews Genetics.

[32]  Mert Sabuncu,et al.  Genetic variation and neuroimaging measures in Alzheimer disease. , 2010, Archives of neurology.

[33]  C. Jack,et al.  Alzheimer's Disease Neuroimaging Initiative (ADNI) , 2010, Neurology.

[34]  A D Roses,et al.  A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease , 2009, The Pharmacogenomics Journal.

[35]  L. Kiemeney,et al.  Corrigendum: Genetic variation in the prostate stem cell antigen gene PSCA confers susceptibility to urinary bladder cancer , 2009, Nature Genetics.

[36]  P. Bosco,et al.  Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease , 2009, Nature Genetics.

[37]  Steven J. M. Jones,et al.  Circos: an information aesthetic for comparative genomics. , 2009, Genome research.

[38]  Andrew J. Saykin,et al.  Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease , 2009, PloS one.

[39]  Evan Fletcher,et al.  Fully-Automated White Matter Hyperintensity Detection with Anatomical Prior Knowledge and without FLAIR , 2009, IPMI.

[40]  S. Potkin,et al.  Genome-wide strategies for discovering genetic influences on cognition and cognitive disorders: Methodological considerations , 2009, Cognitive neuropsychiatry.

[41]  Arthur W. Toga,et al.  Effi cient , distributed and interactive neuroimaging data analysis using the LONI Pipeline , 2009 .

[42]  B T Hyman,et al.  Temporoparietal MR Imaging Measures of Atrophy in Subjects with Mild Cognitive Impairment That Predict Subsequent Diagnosis of Alzheimer Disease , 2009, American Journal of Neuroradiology.

[43]  C. Bellodi,et al.  The tumor suppressor Pml regulates cell fate in the developing neocortex , 2009, Nature Neuroscience.

[44]  Nick C Fox,et al.  Letter abstract - Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's Disease , 2009 .

[45]  Michael Weiner,et al.  Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects , 2008, NeuroImage.

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

[47]  Arthur W. Toga,et al.  Construction of a 3D probabilistic atlas of human cortical structures , 2008, NeuroImage.

[48]  D. Lai,et al.  Angiopoietin-like protein 1 decreases blood brain barrier damage and edema following focal cerebral ischemia in mice , 2008, Neurochemistry International.

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

[50]  R. Mayeux.  Alzheimer's disease: epidemiology. , 2008, Handbook of clinical neurology.

[51]  Martin Klein,et al.  Precuneus atrophy in early-onset Alzheimer’s disease: a morphometric structural MRI study , 2007, Neuroradiology.

[52]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[53]  Nilüfer Ertekin-Taner,et al.  Genetics of Alzheimer's disease: a centennial review. , 2007, Neurologic clinics.

[54]  A. VanDongen,et al.  Activity-regulated cytoskeleton-associated protein Arc/Arg3.1 binds to spectrin and associates with nuclear promyelocytic leukemia (PML) bodies , 2007, Brain Research.

[55]  Paul M Thompson,et al.  Imaging genomics: Mapping the influence of genetics on brain structure and function , 2007, Human brain mapping.

[56]  W. Willett,et al.  A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer , 2007, Nature Genetics.

[57]  Paul M. Thompson,et al.  Mapping heritability and molecular genetic associations with cortical features using probabilistic brain atlases , 2007, Neuroinformatics.

[58]  D. Galati,et al.  Accumulation of Amyloid Precursor Protein in the Mitochondrial Import Channels of Human Alzheimer’s Disease Brain Is Associated with Mitochondrial Dysfunction , 2006, The Journal of Neuroscience.

[59]  D. Weinberger,et al.  Imaging Genetics: Perspectives from Studies of Genetically Driven Variation in Serotonin Function and Corticolimbic Affective Processing , 2006, Biological Psychiatry.

[60]  William E. Lorensen,et al.  The NA-MIC Kit: ITK, VTK, pipelines, grids and 3D slicer as an open platform for the medical image computing community , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[61]  L. Fratiglioni,et al.  Role of genes and environments for explaining Alzheimer disease. , 2006, Archives of general psychiatry.

[62]  G. Frisoni,et al.  Structural correlates of early and late onset Alzheimer’s disease: voxel based morphometric study , 2004, Journal of Neurology, Neurosurgery & Psychiatry.

[63]  Richard Mayeux,et al.  Epidemiology of neurodegeneration. , 2003, Annual review of neuroscience.

[64]  P. McKeigue,et al.  For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group. Problems of Reporting Genetic Associations with Complex Outcomes , 2022 .

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

[66]  A. Toga.  Neuroimage databases: The good, the bad and the ugly , 2002, Nature Reviews Neuroscience.

[67]  J. Growdon,et al.  Risk of dementia among relatives of Alzheimer's disease patients in the MIRAGE study , 1996, Neurology.

[68]  M. Laakso,et al.  Apolipoprotein E4 phenotype is not an important risk factor for coronary heart disease or stroke in elderly subjects. , 1995, Arteriosclerosis, thrombosis, and vascular biology.

[69]  J. Morris.  The Clinical Dementia Rating (CDR) , 1993, Neurology.

[70]  Demetri Terzopoulos,et al.  The Computation of Visible-Surface Representations , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[71]  L. Santaló.  Integral geometry and geometric probability , 1976 .