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  • Original Article
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Genome-wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer's disease

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with considerable evidence suggesting an initiation of disease in the entorhinal cortex and hippocampus and spreading thereafter to the rest of the brain. In this study, we combine genetics and imaging data obtained from the Alzheimer's Disease Neuroimaging Initiative and the AddNeuroMed study. To identify genetic susceptibility loci for AD, we conducted a genome-wide study of atrophy in regions associated with neurodegeneration in this condition. We identified one single-nucleotide polymorphism (SNP) with a disease-specific effect associated with entorhinal cortical volume in an intron of the ZNF292 gene (rs1925690; P-value=2.6 × 10−8; corrected P-value for equivalent number of independent quantitative traits=7.7 × 10−8) and an intergenic SNP, flanking the ARPP-21 gene, with an overall effect on entorhinal cortical thickness (rs11129640; P-value=5.6 × 10−8; corrected P-value=1.7 × 10−7). Gene-wide scoring also highlighted PICALM as the most significant gene associated with entorhinal cortical thickness (P-value=6.7 × 10−6).

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References

  1. Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W et al. Ways toward an early diagnosis in Alzheimer's disease: the Alzheimer's Disease Neuroimaging Initiative (ADNI). Alzheimers Dement 2005; 1: 55–66.

    Article  Google Scholar 

  2. Lovestone S, Francis P, Strandgaard K . Biomarkers for disease modification trials—the innovative medicines initiative and AddNeuroMed. J Nutr Health Aging 2007; 11: 359–361.

    CAS  PubMed  Google Scholar 

  3. Harold D, Abraham R, Hollingworth P, Sims R, Gerrish A, Hamshere ML et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet 2009; 41: 1088–1093.

    Article  CAS  Google Scholar 

  4. Lambert JC, 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.

    Article  CAS  Google Scholar 

  5. Potkin SG, Guffanti G, Lakatos A, Turner JA, Kruggel F, Fallon JH et al. Hippocampal atrophy as a quantitative trait in a genome-wide association study identifying novel susceptibility genes for Alzheimer's disease. PloS One 2009; 4: e6501.

    Article  Google Scholar 

  6. Shen L, Kim S, Risacher SL, Nho K, Swaminathan S, West JD 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. NeuroImage 2010; 53: 1051–1063.

    Article  CAS  Google Scholar 

  7. Simmons A, Westman E, Muehlboeck S, Mecocci P, Vellas B, Tsolaki M et al. MRI measures of Alzheimer's disease and the AddNeuroMed study. Ann NY Acad Sci 2009; 1180: 47–55.

    Article  Google Scholar 

  8. Jack Jr CR, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D et al. The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 2008; 27: 685–691.

    Article  Google Scholar 

  9. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM . Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA Work Group under the Auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 1984; 34: 939–944.

    Article  CAS  Google Scholar 

  10. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E . Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999; 56: 303–308.

    Article  CAS  Google Scholar 

  11. Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV et al. Current concepts in mild cognitive impairment. Arch Neurol 2001; 58: 1985–1992.

    Article  CAS  Google Scholar 

  12. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Human Genet 2007; 81: 559–575.

    Article  CAS  Google Scholar 

  13. International HapMap Consortium. The International HapMap Project. Nature 2003; 426: 789–796.

    Article  Google Scholar 

  14. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D . Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 2006; 38: 904–909.

    Article  CAS  Google Scholar 

  15. Simmons A, Westman E, Muehlboeck S, Mecocci P, Vellas B, Tsolaki M et al. The AddNeuroMed framework for multi-centre MRI assessment of longitudinal changes in Alzheimer's disease: experience from the first 24 months. Int J Ger Psych (in press).

  16. Fischl B, Dale AM . Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci USA 2000; 97: 11050–11055.

    Article  CAS  Google Scholar 

  17. Fischl B, Salat DH, 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.

    Article  CAS  Google Scholar 

  18. Fischl B, Salat DH, van der Kouwe AJ, Makris N, Segonne F, Quinn BT et al. Sequence-independent segmentation of magnetic resonance images. NeuroImage 2004; 23 (Suppl 1): S69–S84.

    Article  Google Scholar 

  19. Nyholt DR . A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Human Genet 2004; 74: 765–769.

    Article  CAS  Google Scholar 

  20. Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007; 449: 851–861.

    Article  CAS  Google Scholar 

  21. The 1000 Genomes Project. http://www1000genomesorg/.

  22. Browning SR, Browning BL . Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Human Genet 2007; 81: 1084–1097.

    Article  CAS  Google Scholar 

  23. Howie BN, Donnelly P, Marchini J . A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009; 5: e1000529.

    Article  Google Scholar 

  24. Kesslak JP, Nalcioglu O, Cotman CW . Quantification of magnetic resonance scans for hippocampal and parahippocampal atrophy in Alzheimer's disease. Neurology 1991; 41: 51–54.

    Article  CAS  Google Scholar 

  25. Convit A, De Leon MJ, Tarshish C, De Santi S, Tsui W, Rusinek H et al. Specific hippocampal volume reductions in individuals at risk for Alzheimer's disease. Neurobiol Aging 1997; 18: 131–138.

    Article  CAS  Google Scholar 

  26. Jack Jr CR, Petersen RC, Xu Y, O'Brien PC, Smith GE, Ivnik RJ et al. Rate of medial temporal lobe atrophy in typical aging and Alzheimer's disease. Neurology 1998; 51: 993–999.

    Article  Google Scholar 

  27. Hemmings Jr HC, Girault JA, Williams KR, LoPresti MB, Greengard P . ARPP- 21 a cyclic AMP-regulated phosphoprotein (Mr=21 000) enriched in dopamine-innervated brain regions. Amino acid sequence of the site phosphorylated by cyclic AMP in intact cells and kinetic studies of its phosphorylation in vitro. J Biol Chem 1989; 264: 7726–7733.

    CAS  PubMed  Google Scholar 

  28. Risacher SL, Saykin AJ, West JD, Shen L, Firpi HA, McDonald BC . Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Curr Alzheimer Res 2009; 6: 347–361.

    Article  CAS  Google Scholar 

  29. Mitchell AJ, Shiri-Feshki M . Rate of progression of mild cognitive impairment to dementia—meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand 2009; 119: 252–265.

    Article  CAS  Google Scholar 

  30. Rakhilin SV, Olson PA, Nishi A, Starkova NN, Fienberg AA, Nairn AC et al. A network of control mediated by regulator of calcium/calmodulin-dependent signaling. Science (New York, NY) 2004; 306: 698–701.

    Article  CAS  Google Scholar 

  31. O'Day DH, Myre MA . Calmodulin-binding domains in Alzheimer's disease proteins: extending the calcium hypothesis. Biochem Biophys Res Commun 2004; 320: 1051–1054.

    Article  CAS  Google Scholar 

  32. Nagase T, Ishikawa K, Miyajima N, Tanaka A, Kotani H, Nomura N et al. Prediction of the coding sequences of unidentified human genes. IX. The complete sequences of 100 new cDNA clones from brain which can code for large proteins in vitro. DNA Res 1998; 5: 31–39.

    Article  CAS  Google Scholar 

  33. Cirrito JR, Kang JE, Lee J, Stewart FR, Verges DK, Silverio LM et al. Endocytosis is required for synaptic activity-dependent release of amyloid-beta in vivo. Neuron 2008; 58: 42–51.

    Article  CAS  Google Scholar 

  34. Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, de Bakker PI . SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics (Oxford, England) 2008; 24: 2938–2939.

    Article  CAS  Google Scholar 

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Acknowledgements

AddNeuroMed is funded through the EU FP6 program as part of InnoMed. In addition, we are grateful for additional support from the NIHR Specialist Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and King's College London, Institute of Psychiatry, London, United Kingdom. Data collection and sharing for this project were funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace Inc., Merck and Co. Inc., Novartis AG, Pfizer Inc., F Hoffman-La Roche, Schering-Plough, Synarc Inc., and Wyeth, as well as nonprofit partners, the Alzheimer's Association and Alzheimer's Drug Discovery Foundation, with participation from the US Food and Drug Administration. Private sector contributions to ADNI are facilitated by the Foundation for the National Institutes of Health (http://www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129, K01 AG030514 and the Dana Foundation. We thank Mike Weale for assistance with the implementation of population stratification and are grateful to Cathryn Lewis, Amanda Myers and Peter Holmans for advice on the analysis. Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data, but did not participate in analysis or writing of this report. ADNI investigators include (complete listing available at http://www.loni.ucla.edu/ADNI/Collaboration/ADNI_Manuscript_Citations.pdf).

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Correspondence to S Lovestone.

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Furney, S., Simmons, A., Breen, G. et al. Genome-wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer's disease. Mol Psychiatry 16, 1130–1138 (2011). https://doi.org/10.1038/mp.2010.123

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