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Archival Report| Volume 2, ISSUE 8, P673-679, November 2017

Late-Onset Alzheimer’s Disease Polygenic Risk Profile Score Predicts Hippocampal Function

  • Author Footnotes
    1 EX and QC contributed equally to this work.
    Ena Xiao
    Correspondence
    Address correspondence to Venkata S. Mattay, M.D., Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 855 North Wolfe Street, Baltimore, MD 21205.
    Footnotes
    1 EX and QC contributed equally to this work.
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
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  • Author Footnotes
    1 EX and QC contributed equally to this work.
    Qiang Chen
    Footnotes
    1 EX and QC contributed equally to this work.
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
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  • Aaron L. Goldman
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
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  • Hao Yang Tan
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland
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  • Kaitlin Healy
    Affiliations
    Genes Cognition and Psychosis Program, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Brad Zoltick
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Saumitra Das
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Bhaskar Kolachana
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Joseph H. Callicott
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Dwight Dickinson
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Karen F. Berman
    Affiliations
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, Maryland
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  • Daniel R. Weinberger
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland

    Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland

    Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland

    Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Venkata S. Mattay
    Affiliations
    Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland

    Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland

    Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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  • Author Footnotes
    1 EX and QC contributed equally to this work.
Published:August 24, 2017DOI:https://doi.org/10.1016/j.bpsc.2017.08.004

      Abstract

      Background

      We explored the cumulative effect of several late-onset Alzheimer’s disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry.

      Methods

      In a sample of 231 healthy control subjects (19–55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level–dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects.

      Results

      There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested.

      Conclusions

      There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes.

      Keywords

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      References

        • Gatz M.
        • Pedersen N.L.
        • Berg S.
        • Johansson B.
        • Johansson K.
        • Mortimer J.A.
        • et al.
        Heritability for Alzheimer's disease: The study of dementia in Swedish twins.
        J Gerontol Ser A Biol Sci Med Sci. 1997; 52: M117-M125
        • Pedersen N.L.
        • Gatz M.
        • Berg S.
        • Johansson B.
        How heritable is Alzheimer's disease late in life? Findings from Swedish twins.
        Ann Neurol. 2004; 55: 180-185
        • Bagyinszky E.
        • Youn Y.C.
        • An S.S.
        • Kim S.
        The genetics of Alzheimer's disease.
        Clin Interv Aging. 2014; 9: 535-551
        • Harold D.
        • Abraham R.
        • Hollingworth P.
        • Sims R.
        • Gerrish A.
        • Hamshere M.L.
        • et al.
        Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease.
        Nat Genet. 2009; 41: 1088-1093
        • Naj A.C.
        • Jun G.
        • Beecham G.W.
        • Wang L.S.
        • Vardarajan B.N.
        • Buros J.
        • et al.
        Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease.
        Nat Genet. 2011; 43: 436-441
        • Hollingworth P.
        • Harold D.
        • Sims R.
        • Gerrish A.
        • Lambert J.C.
        • Carrasquillo M.M.
        • et al.
        Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease.
        Nat Genet. 2011; 43: 429-435
        • Lambert J.C.
        • Heath S.
        • Even G.
        • Campion D.
        • Sleegers K.
        • Hiltunen M.
        • et al.
        Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease.
        Nat Genet. 2009; 41: 1094-1099
        • Lambert J.C.
        • Ibrahim-Verbaas C.A.
        • Harold D.
        • Naj A.C.
        • Sims R.
        • Bellenguez C.
        • et al.
        Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease.
        Nat Genet. 2013; 45: 1452-1458
        • Escott-Price V.
        • Sims R.
        • Bannister C.
        • Harold D.
        • Vronskaya M.
        • Majounie E.
        • et al.
        Common polygenic variation enhances risk prediction for Alzheimer's disease.
        Brain. 2015; 138: 3673-3684
        • Roussotte F.F.
        • Gutman B.A.
        • Madsen S.K.
        • Colby J.B.
        • Thompson P.M.
        Combined effects of Alzheimer risk variants in the CLU and ApoE genes on ventricular expansion patterns in the elderly.
        J Neurosci. 2014; 34: 6537-6545
        • Roses A.D.
        • Lutz M.W.
        • Amrine-Madsen H.
        • Saunders A.M.
        • Crenshaw D.G.
        • Sundseth S.S.
        • et al.
        A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease.
        Pharmacogenomics J. 2010; 10: 375-384
        • Medway C.
        • Morgan K.
        Review: The genetics of Alzheimer's disease; putting flesh on the bones.
        Neuropathol Appl Neurobiol. 2014; 40: 97-105
        • Carrasquillo M.M.
        • Crook J.E.
        • Pedraza O.
        • Thomas C.S.
        • Pankratz V.S.
        • Allen M.
        • et al.
        Late-onset Alzheimer's risk variants in memory decline, incident mild cognitive impairment, and Alzheimer's disease.
        Neurobiol Aging. 2015; 36: 60-67
        • Sabuncu M.R.
        • Buckner R.L.
        • Smoller J.W.
        • Lee P.H.
        • Fischl B.
        • Sperling R.A.
        The association between a polygenic Alzheimer score and cortical thickness in clinically normal subjects.
        Cereb Cortex. 2012; 22: 2653-2661
        • Sperling R.
        • Johnson K.
        Biomarkers of Alzheimer disease: Current and future applications to diagnostic criteria.
        Continuum (Minneap Minn). 2013; 19: 325-338
        • Terry D.P.
        • Sabatinelli D.
        • Puente A.N.
        • Lazar N.A.
        • Miller L.S.
        A meta-analysis of fMRI activation differences during episodic memory in Alzheimer's disease and mild cognitive impairment.
        J Neuroimaging. 2015; 25: 849-860
        • Harrison T.M.
        • Bookheimer S.Y.
        Neuroimaging genetic risk for Alzheimer's disease in preclinical individuals: From candidate genes to polygenic approaches.
        Biol Psychiatry Cogn Neurosci Neuroimaging. 2016; 1: 14-23
        • Rasetti R.
        • Mattay V.S.
        • White M.G.
        • Sambataro F.
        • Podell J.E.
        • Zoltick B.
        • et al.
        Altered hippocampal-parahippocampal function during stimulus encoding: A potential indicator of genetic liability for schizophrenia.
        JAMA Psychiatry. 2014; 71: 236-247
        • Muse J.
        • Emery M.
        • Sambataro F.
        • Lemaitre H.
        • Tan H.Y.
        • Chen Q.
        • et al.
        WWC1 genotype modulates age-related decline in episodic memory function across the adult life span.
        Biol Psychiatry. 2014; 75: 693-700
        • Murty V.P.
        • Sambataro F.
        • Das S.
        • Tan H.Y.
        • Callicott J.H.
        • Goldberg T.E.
        • et al.
        Age-related alterations in simple declarative memory and the effect of negative stimulus valence.
        J Cogn Neurosci. 2009; 21: 1920-1933
        • Rasetti R.
        • Sambataro F.
        • Chen Q.
        • Callicott J.H.
        • Mattay V.S.
        • Weinberger D.R.
        Altered cortical network dynamics: A potential intermediate phenotype for schizophrenia and association with ZNF804A.
        Arch Gen Psychiatry. 2011; 68: 1207-1217
        • Lang P.J.
        • Bradley M.M.
        • Cuthbert B.N.
        International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual. Technical Report A-8.
        NIMH, Center for the Study of Emotion & Attention, Gainesville, FL2005
        • Desikan R.S.
        • Segonne F.
        • Fischl B.
        • Quinn B.T.
        • Dickerson B.C.
        • Blacker D.
        • et al.
        An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.
        Neuroimage. 2006; 31: 968-980
        • Fischl B.
        • Salat D.H.
        • Busa E.
        • Albert M.
        • Dieterich M.
        • Haselgrove C.
        • et al.
        Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain.
        Neuron. 2002; 33: 341-355
        • Schizophrenia Working Group of the Psychiatric Genomics Consortium
        Biological insights from 108 schizophrenia-associated genetic loci.
        Nature. 2014; 511: 421-427
        • Purcell S.M.
        • Wray N.R.
        • Stone J.L.
        • Visscher P.M.
        • O'Donovan M.C.
        • Sullivan P.F.
        • et al.
        Common polygenic variation contributes to risk of schizophrenia and bipolar disorder.
        Nature. 2009; 460: 748-752
        • Darst B.F.
        • Koscik R.L.
        • Racine A.M.
        • Oh J.M.
        • Krause R.A.
        • Carlsson C.M.
        • et al.
        Pathway-specific polygenic risk scores as predictors of amyloid-beta deposition and cognitive function in a sample at increased risk for Alzheimer's disease.
        J Alzheimers Dis. 2017; 55: 473-484
        • Nichols L.M.
        • Masdeu J.C.
        • Mattay V.S.
        • Kohn P.
        • Emery M.
        • Sambataro F.
        • et al.
        Interactive effect of apolipoprotein E genotype and age on hippocampal activation during memory processing in healthy adults.
        Arch Gen Psychiatry. 2012; 69: 804-813
        • Adamson M.M.
        • Hutchinson J.B.
        • Shelton A.L.
        • Wagner A.D.
        • Taylor J.L.
        Reduced hippocampal activity during encoding in cognitively normal adults carrying the APOE varepsilon4 allele.
        Neuropsychologia. 2011; 49: 2448-2455
        • Salles A.
        • Romano A.
        • Freudenthal R.
        Synaptic NF-kappa B pathway in neuronal plasticity and memory.
        J Physiol Paris. 2014; 108: 256-262
        • Essabbani A.
        • Margottin-Goguet F.
        • Chiocchia G.
        Identification of clusterin domain involved in NF-kappaB pathway regulation.
        J Biol Chem. 2010; 285: 4273-4277
        • Xiao Q.
        • Gil S.C.
        • Yan P.
        • Wang Y.
        • Han S.
        • Gonzales E.
        • et al.
        Role of phosphatidylinositol clathrin assembly lymphoid-myeloid leukemia (PICALM) in intracellular amyloid precursor protein (APP) processing and amyloid plaque pathogenesis.
        J Biol Chem. 2012; 287: 21279-21289
        • Foo S.Y.
        • Nolan G.P.
        NF-kappaB to the rescue: RELs, apoptosis and cellular transformation.
        Trends Genet. 1999; 15: 229-235
        • Perkins N.D.
        The Rel/NF-kappa B family: Friend and foe.
        Trends Biochem Sci. 2000; 25: 434-440
        • International Genomics of Alzheimer’s Disease Consortium
        Convergent genetic and expression data implicate immunity in Alzheimer's disease.
        Alzheimers Dement. 2015; 11: 658-671
        • Lopez M.
        • Aoubala M.
        • Jordier F.
        • Isnardon D.
        • Gomez S.
        • Dubreuil P.
        The human poliovirus receptor related 2 protein is a new hematopoietic/endothelial homophilic adhesion molecule.
        Blood. 1998; 92: 4602-4611