Imaging Genetics CourseOHBM, June 26, 2011

Imaging Genetics of Alzheimer’s Disease: The ADNI Experience

Indiana University School of MedicineAndrew J. Saykin

Overview• Overview of ADNI & access to data sets• Late onset AD (LOAD) genetics

– New developments in GWAS of LOAD– ADNI’s role; relevance of findings

• Methodological issues in mapping between quantitative phenotypes and genetic data

• Selected recent results:– Genome-wide whole brain analysis– GWAS of CSF biomarkers– Candidate gene and pathways-based analyses

• Ongoing work and future plans

M. Weiner, P. Aisen, R Peterson, C. Jack, W. Jagust, J. Trojanowski, L. Shaw, A. Toga, L. Beckett, D. Harvey,

C. Mathis, A. Gamst. R. Green. A. Saykin, S. Potkin, J. Morris, L Thal (D), Neil Buckholz, David Lee, Holly Soares

Industry Scientific Advisory Board (ISAB) and Site PIs, Study Coordinators, and

821 subjects enrolled in 58 sites in US and Canada

FUNDED BY THE NATIONAL INSTITUTE ON AGING

For more information & data access: http://adni.loni.ucla.edu/

Industry: Precompetitive Collaboration

ADNI-1: Naturalistic Study of AD

GOALS OF ADNI-1(Funded from 10/1/2004 to 9/30/2010 NCE)

• Optimize and standardize biomarkers for clinical trials

• Validate biomarkers as measures of change• Validate biomarkers as diagnostics or

predictors• Establish world-wide network for clinical AD

studies and treatment trials• Genetics: Only APOE genotyping included for

purpose of stratification; DNA & LCLs banked• For data access: http://adni.loni.ucla.edu/

NIA GRAND OPPORTUNITES (GO) ARRA GRANT

(Funded From 9/30/2009 to 9/30/2011)

• Adds cohort of 200 very mild “early” MCI (EMCI)

• LPs on 100 of new subjects• Follow ADNI-1 controls/MCI additional yr• F18 amyloid imaging on ALL existing and new

ADNI/GO subjects (AV-45)• Added Genetics Core• Complete analysis of all ADNI data

SCOPE OF ADNI-2 (Funded From 10/1/2010 To 9/30/2015)

• Goal to continue to follow >400 controls and MCI from ADNI-1 for 5 more years and enroll:– 100 additional EMCI (supplements 200 from GO)– 150 new controls, LMCI, and AD

• MRI at 3,6, months and annually• F18 amyloid (AV-45)/FDG baseline and Yr 2• LP on 100% of subjects at enrollment• Genetics Core

NA-ADNI

J-ADNIE-ADNI

World Wide ADNI

A-ADNI

C-ADNI K-ADNI

T-ADNI

Arg-ADNI

Future ADNI sites Courtesy of Maria Carillo of the Alzheimer’s Association Weiner et al Alzheimer’s & Dementia 6:202-211 (2010)

Timeline for the Onset and Progression of Alzheimer Disease Processes

Shaw LM, Korecka M, Clark CM, Lee VM.-Y, Trojanowski JQ. Nat Rev Drug Discovery, 6(4):295-303, 2007.

Biomarkers are needed for early diagnosis, to predict transitions from NCI to MCI to AD and clinical trials of disease modifying therapies

Biomarkers

Major Genes:EOAD & LOAD

Chromosome 14

Chromosome 19

Chromosome 21Chromosome 1

APP21q21.3

PS1

PS2APOE

LOAD: genetic factors account for ~60-80% of risk (Gatz et al 2006);

APOE accounts for up to 50%(Ashford & Mortimer 2002); soup to 30% remains to be found.

Genome-Wide Association Studies (GWAS)

• Mitochondrial SNPs

• Non-synonymous SNPs• MHC markers• Y chromosome SNPs

• 620,901 markers (~90% genomic coverage, CEU)• Single nucleotide polymorphisms (SNPs)• Copy number variation (CNVs) probes

“Gene Chip” - Illumina Human 610-Quad

Harold et al 2009 & Lambert et al 2009Large Case/Control GWAS in AD

Gene Discoveries and AD Pathophysiology

Sleegers, Lambert, Bertram, Cruts, Amouyel & Van Broeckhoven; Trends in Genetics, 2010

Pathways:A Beta (pink)Neurofibrillary tangles (blue)Inflammation (green)Atherosclerosis (yellow)Synaptic dysfunction (purple)Others (orange)

Naj et al ADGC GWAS Meta-analysis

published online 3 April 2011; doi:10.1038/ng.801

(~23K: ADNI AD cases & controls included)

Hollingworth et al GWAS Meta-analysis

published online 3 April 2011; doi:10.1038/ng.803

(~ 26K: ADNI AD cases & controls included)

AlzGene Top Ten (4/18/11)

http://www.alzgene.org/TopResults.asp

• ABCA7: ATP-binding cassette (ABC) transporter; role in lipoprotein particle processing (APOE & CLU)

• CD33: sialic-acid-binding IG-like lectins (Siglec) family; role in cell-cell interactions, regulation of immune cell function; role in endocytosis

• CD2AP: CD2-associated protein. Scaffold adaptor protein associates with cortactin, a protein involved in regulation of endocytosis

• EPHA1: expressed mainly in epithelial tissues; regulates cell morphology and motility; possible role in apoptosis & inflammation

• MS4A family: (MS4A4, MS4A6E, MS4A6A, MS4A4E): role in immune function

New Candidate Genes

Putative Roles of New Candidate GenesGene Lipid

ProcessingImmune Function

Endocytosis

APOE X X XABCA7 X XBIN1 XCD33 X XCD2AP XCLU X XCR1 XEPHA1 XMS4A family XPICALM X

A. Saykin, OHBM, 2011

Imaging, Biomarkers & Clinical Endophenotypes

Gene “Chip”

Other QT phenotypes: clinical, cognitive, fluid biomarker data

Brain-Genome Association Strategies

Risacher et al 2010

Sloan et al 2010

Potkin et al 2009; Saykin et al 2010

Egan et al 2001 COMTSwaminathan et al 2010 PiB

ROIs & amyloid pathwayPotkin et al 2009 Mol Psych

schizophrenia study

Reiman et al PNAS 2009;Also Ho et al 2010 FTO

Reiman et al 2008 cholesterol pathway genes

Shen et al 2010 ROIs; Stein et al 2010 voxels

ROI

Circuit

Whole Brain

Candidate Gene/SNP

Biological Pathway

Genome-wide Analysis

ε40 1

2 AD

Global Grey Matter Density of Patient Groups (AD, MCI-Converter, MCI-Stable) Relative to HC Participants

n=693 (148 AD, 62 MCI-C, 277 MCI-S, 206 HC)Covaried for age, gender, education, handedness

and total intracranial volume (ICV)

HC>ADRL LR R L R

HC>MCI-ConvertersRL LR R L R

HC>MCI-StableRL LR R L R

Risacher, Saykin, Shen et al; Current Alzheimer Research 2009; 6(4): 347-361

p<0.005 (FDR), k=27

Relationship of Global Grey Matter Density Among Patient Groups (AD, MCI-Converter, MCI-Stable)

n=693 (148 AD, 62 MCI-C, 277 MCI-S, 206 HC); p<0.005 (FDR), k=27

Covaried for age, gender, education, handedness and total intracranial volume (ICV)

MCI-Converters>AD – No Significantly Different Voxels

MCI-Stable>ADRL LR R L R

MCI-Stable>MCI-ConvertersRL LR R L R

Risacher, Saykin, Shen et al; Current Alzheimer Research 2009; 6(4): 347-361

AD Phenotype: MTL Grey Matter Density, Volume, and Cortical Thickness in the ADNI Sample at BaselineN=693 (148 AD, 62 MCI-C, 277 MCI-S, 206 HC); p<0.005 (FDR)

Risacher, Saykin, Shen et al; Current Alzheimer Research 2009; 6(4): 347-361

Regions Showing the Greatest Effect Sizes when Comparing MCI-Converter and MCI-Stable Participants at Baseline

Risacher et al Curr Alzheimer Res 2009; 6(4): 347-361

Overview of ADNI Genetics

Saykin et al (2010) Alzheimer’s & Dementia

1. Biffi, A., et al., Genetic Variation and Neuroimaging Measures in Alzheimer Disease. Arch Neurol, 2010. 67(6): p. 677-685.2. Cruchaga, C., et al., SNPs associated with cerebrospinal fluid phospho-tau levels influence rate of decline in Alzheimer's disease. PLoS

Genet, 2010. 6(9).3. Furney, S.J., et al., Genome wide association with MRI atrophy measures as a quantitative trait locus for Alzheimer’s disease. Molecular

Psychiatry, 2010. in press.4. Hibar, D.P., et al., Voxelwise gene-wide association study (vGeneWAS): multivariate gene-based association testing in 731 elderly

subjects. NeuroImage, 2011 in press.5. Ho, A.J., et al., A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly.

Proceedings of the National Academy of Sciences, 2010. 107(18): p. 8404-8409.6. Jun, G., et al., Meta-analysis Confirms CR1, CLU, and PICALM as Alzheimer Disease Risk Loci and Reveals Interactions With APOE

Genotypes. Arch Neurol, 2010.7. Kauwe, J., et al., Suggestive synergy between genetic variants in TF and HFE as risk factors for Alzheimer's disease. American Journal

of Medical Genetics Part B: Neuropsychiatric Genetics, 2010. 153B(4): p. 955-959.8. Kauwe, J.S.K., et al., Validating Predicted Biological Effects of Alzheimer's Disease Associated SNPs Using CSF Biomarker Levels.

Journal of Alzheimer's Disease, 2010.9. Kim, S., et al., Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort. Neurology, 2011.

76(1): p. 69-79.10. Lakatos, A., et al., Association between mitochondrial DNA variations and Alzheimer's disease in the ADNI cohort. Neurobiology of Aging,

2010. 31(8): p. 1355-1363.11. Naj, A.C., et al., Dementia revealed: novel chromosome 6 locus for late-onset Alzheimer disease provides genetic evidence for folate-

pathway abnormalities. PLoS Genet, 2010. 6(9).12. Naj, A., et al., Common variants in MS4A4/MS4A6E, CD2AP, CD33, and EPHA1 are associated with late-onset Alzheimer's disease.

Nature Genetics, 2011 in press.13. Potkin, S.G., 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(8): p. e6501.14. Rimol, L.M., et al., Sex-dependent association of common variants of microcephaly genes with brain structure. Proceedings of the

National Academy of Sciences, 2010. 107(1): p. 384-388.15. Saykin, A.J., et al., Alzheimer's Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress,

and plans. Alzheimer's and Dementia, 2010. 6(3): p. 265-273.16. Shen, L., 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(3): p. 1051-1063.17. Stein, J.L., et al., Voxelwise genome-wide association study (vGWAS). NeuroImage, 2010. 53(3): p. 1160-1174.18. Stein, J.L., et al., Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in

Alzheimer's disease. NeuroImage, 2010. 51(2): p. 542-554.19. Swaminathan, S., et al., Genomic copy number analysis in Alzheimer's disease and MCI: An ADNI Study. International Journal of

Alzheimer’s Disease, 2011 in press.20. Xu, C., et al., Effects of BDNF Val66Met polymorphism on brain metabolism in Alzheimer's disease. Neuroreport, 2010. 21(12): p. 802-7.

Publications using ADNI GWAS data (partial): Spring 2011

Initial ADNIGWASReport

Potkinet al8/09

Translocase of Outer Mitochondrial Membrane 40 homolog (TOMM40) 523 PolyT Assay:

Collaboration with Roses et al to replicate & extend

Whole Brain & Genome-wide Analysis

Shen et al NeuroImage 53 (2010)1051–1063

Stein et al NeuroImage 53 (2010) 1160–1174

ROI-based Voxel-based

Shen et al 2010 [Epub] ,NeuroImage

GWAS of Mean Grey Matter Density: Right Hippocampus

Shen et al 2010 NeuroImage

NXPH1: Novel Candidate Gene for ADthat codes for neurexophilin-1 protein

Expressed in Brain Neuroexphilin-1’s likely role in synaptogenesis:

Protein forms a very tight complex with alpha neurexins, a group of proteins that promote adhesion between dendrites and axons(EntrezGene).

VBM Analysis of NXPH1Baseline Diagnosis x SNP for rs6463843: GG > TT

n=715 166 AD (44 TT, 78 GT, 44 GG); 346 MCI (82 TT, 170 GT, 94 GG); 203 HC (35 TT, 105 GT, 63 GG)

p<0.001 (unc.), k=27Covaried for age, gender,

education, handedness and baseline ICV

AD

R L R L R

HC

R L R L R

MCI

R L R L R

Shen et al 2010 NeuroImage

vGWAS, ROIs and Candidate Genes (UCLA)

NeuroImage 51 (2010) 542–554

Voxelwise GWAS: Ran genome-wide association for a quarter of a million points across 700 subjects -new gene discovery method; many new SNPs; power calculations for replication (Stein et al, NeuroImage, 2010a)

GRIN2b, a common glutamate receptor genetic variant, is associated with greater temporal lobe atrophy and with AD; NMDA-receptor is a target for memantine therapy (Stein et al, NeuroImage, 2010b)

FTO, an obesity risk gene carried by 46% of Europeans, is associated with 10-15% frontal and occipital atrophy, and with a ~1.7kg weight gain, on average (April Ho et al, PNAS, 2010)

N = 377AD+MCIc: 60 AA, 62 AG, 14 GG

MCI-S: 75 AA, 55 AG, 12 GGHC: 77 AA, 22 AG, 1 GG

CSF Biomarkers: Aβ1-42 & TOMM40

Shen

Kim, Swaminathan, et al Neurology (Jan 4 2011)

Kim, Swaminathan, et al Neurology (Jan 4 2011)

CSF Biomarkers: Total Tau

10 -6

10 -83.1 x 10-8 corrected p<.01

EPC2 (rs4499362)

New finding from CSF t-tau GWAS: Enhancer of polycomb homolog 2 (EPC2)

Kim, Swaminathan, et al Neurology (Jan 4 2011)

Genome Wide Association Study (GWAS) on Annual Percent

Change of 1.5T MRI: Initial Data• 818 ADNI Subjects

– 589 cases (MCI or AD), 229 controls– 476 males, 342 females

• 620901 +2 Markers– 620901 from Illumina 610 Quad array– 2 APOE SNPs

• Extensive QC protocol

Saykin et al 2010 Alz Dementia

Annual Percent Change in Hippocampal Volume and Grey Matter Density (ADNI Cohort)

Risacher et al Neurobiol Aging (2010)

Covaried for baseline age, sex, education, handedness & ICV

Rate of Change: Role of APOEMain effect versus Interaction

Risacher et al Neurobiology of Aging (2010); 31:1401-1418

Adjusted Annual Percent Change in Hippocampal Volume

APOE (Chr 19): rs429358 is the epsilon 4 allele markerTOMM40 (Chr 19): translocase of outer mitochondrial membrane 40 homolog (LD with APOE)CADH8 (Chr 16): cadherin 8, type 2; synaptic adhesion, axonal growth/guidance (no data in AD)

Saykin et al Alzheimer’s & Dementia (2010); 6:265–273

Adjusted Annual Percent Change in Hippocampal Gray Matter Density

Saykin et al Alzheimer’s & Dementia (2010); 6:265–273

MAD2L2 (Chr 1) mitotic arrest deficient-like 2 (mitotic spindle assembly) – role in cell cyclingQPCT (Chr 2): possible role in pyroglutamate formation of amyloid plaque-forming peptidesGRB2 (Chr 17): growth factor receptor-bound protein 2; one isoform may trigger apoptosisLOC728574 (Chr 22): similar to retinitis pigmentosa GTPase regulator isoform C

Neurodegeneration &AD Pathophysiology

Plasticity / Repair & Growth Factors

Cerebrovascular,Metabolic & Endocrine

Inflammation

Neurotransmission &Receptors

Molecular Biology of Memory/ LTP

Brain Activity

Brain Structure

Treatment Response

Proposed model of allelic variation in candidate genes related to cognition, brain structure and activity in healthy aging and preclinical AD.

Candidate Molecular Pathways for Age Related

Memory Decline

Saykin , OHBM 2011

Sloan et al 2010 [Epub], Am J Med Genet, DOI 10.1002/ajmg.b.31078

Amyloid Pathway PET Study: [11C]PiB

Swaminathan et al, ASHG, Wash DC, Nov 2010 & submitted

Amyloid Gene Pathway-PiB: Preliminary Results

Swaminathan et al, ASHG, Wash DC, Nov 2010 & submitted

Recent Development: AV-45 (Florbetapir) Amyloid Imaging Neuropathological Validation

JAMA Jan 19, 2011

Copy Number Variation (CNV)

PDF: http://www.sage-hindawi.com/journals/ijad/aip/729478/

CHRFAM7A CNV

Swaminathan, et al (2011) IJAD; Epub Jun 2.

Potkin Group (UCI):

Mitochondrial DNA Analysis

ADNI Genetics: Next Steps• ADNI-GO/2

– Ongoing DNA, RNA, cell line sample collection– Planning for genotyping of new samples

• ADNI-1 data analysis– Baseline and rate of change– Copy number variation– Candidate genes & pathways, GWAS approaches– Associations with PET & CSF/plasma biomarkers– Collaborative projects, replication, other cohorts

• Future: – Targeted DNA and RNA resequencing – identify

key regions for intensive scrutiny– Epistasis, Transcriptomics/expression, microRNA– Epigenomics (DNA methylation, etc)

Timeline for the Onset and Progression of Alzheimer Disease Processes

Shaw LM, Korecka M, Clark CM, Lee VM.-Y, Trojanowski JQ. Nat Rev Drug Discovery, 6(4):295-303, 2007.

Biomarkers are needed for early diagnosis, to predict transitions from NCI to MCI to AD and clinical trials of disease modifying therapies

Biomarkers

Acknowledgements

ADNI Genotyping Working GroupIndiana University • Imaging Genomics Lab

– Andrew J. Saykin– Li Shen– Mark Inlow– Sungeun Kim– Kwangsik Nho– Susan Conroy– Shannon Risacher– Shanker Swaminathan

• NCRAD & Genetics– Tatiana M. Foroud– Kelley M. Faber– Nathan Pankratz

• Pfizer Genetics– Bryan DeChairo– Elyse Katz

• TGen– Eric Reiman– David W. Craig– Matt J. Huentelman

• UC Irvine:– Steven G. Potkin– Guia Guffanti– Anita Lakatos

• Core Consultants (ADNI-2):– Lars Bertram (Max Planck)– Lindsay Farrer (BU)– Robert Green (BU)– Jason Moore (Dartmouth)– Paul Thompson (UCLA)

Support for ADNI Genetics• National Institute on Aging

– ADNI U01 AG024904 & RC2 AG036535– R01 AG19771 & P30 AG10133-18S1– U01 AG032984, U24 AG21886, P30 AG010129,

K01 AG030514• Institute of Biomedical Imaging and Bioengineering• Foundation for the NIH

– Anonymous Foundation (Challenge Grant)– Gene Network Sciences– Merck– Pfizer (DNA extraction)

• Alzheimer’s Association• Indiana Economic Development Corporation (IEDC)