Tuesday, July 16, 2013: Poster Presentations: P3P554

disease in the presence of high genetic risk for disease). These approaches

have not yet been extensively applied in AD research.

P3-011 GENOME-WIDE ASSOCIATION ANALYSES OF

ONSETAGE IN LATE-ONSETALZHEIMER

DISEASE (LOAD) DEMONSTRATE NO STRONG

EFFECT OUTSIDE OF THE APOE REGION

Adam Naj1, Brian Kunkle2, Yo Park3, Gyungah Jun4, Christiane Reitz5,

Ruchita Rajbhandary2, Kara Hamilton-Nelson2, Gary Beecham2,

Eden Martin2, Richard Mayeux5, Jonathan Haines6, Lindsay Farrer4,

Gerard Schellenberg1, Margaret Pericak-Vance2, Alzheimer’s Disease

Genetics Consortium7,1University of Pennsylvania Perelman School of

Medicine, Philadelphia, Pennsylvania, United States; 2University of Miami,

Miami, Florida, United States; 3University of Miami Miller School of

Medicine, Miami, Florida, United States; 4Boston University School of

Medicine, Boston, Massachusetts, United States; 5Columbia University,

New York, New York, United States; 6Vanderbilt University, Nashville,

Tennessee, United States; 7University of Pennsylvania School of Medicine,

Philadelphia, Pennsylvania, United States. Contact e-mail: adamnaj@mail.

med.upenn.edu

Background: LOAD risk loci may also contribute to variation in age of on-

set (AAO) of LOAD, as do the allelic variants in APOE, however roles in

AAO for the other newly identified risk loci (CLU, BIN1, and others)

have not been explored. We examined variants at ten confirmed LOAD

risk loci (APOE, CLU, PICALM, CR1, BIN1, CD2AP, EPHA1, the

MS4A region, ABCA7, and CD33) to determine if they contribute to vari-

ation in AAO among 9,160 LOAD cases in the Alzheimer’s disease Genetics

Consortium (ADGC). Methods: We tested association with AAO for each

locus using linear modeling with covariate adjustment for population sub-

structure and performed a random-effects meta-analysis across datasets.

We also examined genetic burden using genotype scores weighted by risk

effect sizes to examine the aggregate contribution of these loci to variation

in AAO. Results: Analyses confirmed association of APOE regional

variation with AAO (rs6857, P¼3.30310 -96), with statistically significant

associations with AAO (P<0.005) demonstrated at several other LOAD risk

loci, including rs6701713 in CR1 (P ¼0.00717), rs7561528 in BIN1

(P ¼0.00478), rs561655 in PICALM (P ¼0.00223). Associations remained

largely unchanged after additional adjustment for dosage of APOE ε4 al-

leles. Burden analyses showed APOE contributes to 3.1% of variation in

AAO (R 2 ¼0.078) whereas the other nine genes contribute to 1.1% of var-

iation (R 2 ¼0.058) over baseline (R 2 ¼0.047). Secondary analyses of ge-

nome-wide association with AAO among non-risk loci identified several

regions with multiple SNPs demonstrating suggestive associations

(P<10 -6), including one nearing genome-wide statistical significance:

MYO16 (47 SNPs; most significant: rs9521011, P ¼7.62310 -8), CDH20

(4 SNPs; most significant: rs12956834, P ¼6.17310 -6), and SGCZ

(10 SNPs; most significant: rs7016159, P ¼7.70310 -6). Conclusions:

We confirmed the association of APOE variants with AAO among LOAD

cases, and observe associations with AAO in CR1, BIN1, and PICALM.

In contrast to earlier hypothetical modeling, we show that the combined ef-

fects of other loci do not exceed the effect of APOE on AAO, and if addi-

tional genetic contributions to AAO exist, they are likely very small

individually or are hidden in gene-gene interactions.

P3-012 GENETIC DETERMINANTS OF PROGRESSION OF

ALZHEIMER’S DISEASE

Xingbin Wang1, Oscar Lopez1, Robert Sweet2, Michael Barmada1,

Yesim Demirci1, Ilyas Kamboh3, 1University of Pittsburgh, Pittsburgh,

Pennsylvania, United States; 2University of Pittsburgh, Pittsburgh,

Pennsylvania, United States; 3University of Pittsburgh, Pittsburgh,

Pennsylvania, United States. Contact e-mail: xbw1@pitt.edu

Background: Alzheimer’s disease (AD) is characterized by a gradual cog-

nitive and functional decline. Previous studies have shown that the rate of

progression of AD is not uniform, as some patients progress slower than

others, and there are many factors that can affect the slope of progression.

For example, psychotic symptoms can accelerate progression of the disease,

while dementia medication can reduce the rate of decline. However, there

are no studies on the genetic determinants of progression of AD. In the pres-

ent study, we examined the genetic factors associated with the rate of change

at 12 months follow up in a group of patients with AD recruited from a re-

ferral clinic.Methods:We examined the genetic association of 200 SNPs in

ten loci for late-onset AD (APOE, BIN1, CLU, EPHA1, PICALM, CD2AP,

CD33, ABCA7, MS4A4A/MS4A6E, and CR1). Association analysis was

performed using logistic regression model that included age, sex, education,

baseline MMSE score, medication and psychosis.Results:While no signif-

icant association was observed with SNPs in the APOE gene (APOE*4:

P-value¼0.3099; APOE*2: P-value¼0.1935), we found multiple nominal

significant associations (P<0.05) in the CD2AP, BIN1, PICALM and

CD33 genes that harbor both risk and protective SNPs. The most number

of significant SNPs were observed in CD2AP (n¼6; top P-value¼0.00102)

and BIN1 (n¼ 11; top P-value¼ 0.00484).Conclusions: These results indi-

cate that genetic variation in recently identified genes for late-onset ADmay

affect AD progression. Deep resequencing of these genes may enable iden-

tification of causal variants for AD progression.

P3-013 IMAGING GENETICS OF THE SPON1 GENE

VARIANT RS11023139 IN ALZHEIMER’S DISEASE

Kwangsik Nho1, Sungeun Kim1, Shannon Risacher1, Li Shen1,

Richard Sherva2, Robert Green3, Michael Weiner4, Andrew Saykin5,1Indiana University School of Medicine, Indianapolis, Indiana, United

States; 2Boston University, Boston, Massachusetts, United States; 3Brigham

and Women’s Hospital and Harvard Medical School, Boston,

Massachusetts, United States; 4University of California, San Francisco, San

Francisco, California, United States; 5Indiana University School of

Medicine, Indianapolis, Indiana, United States. Contact e-mail: knho@

iupui.edu

Background:Alzheimer’s disease (AD) is a progressive neurodegenerative

condition. Although the genetic effects on rates of cognitive decline and

brain atrophy in AD have received little attention, a recent Genome Wide

Association Study (GWAS) identified rs11023139 in the spondin 1

(SPON1) gene whose minor allele was significantly associated with

a slow rate of cognitive decline. [1] Our aimwas to perform quantitative trait

loci (QTL) association analysis using structural MRI endophenotypes in or-

der to further study the association of the SPON1 gene variant with neuro-

degeneration. Methods: We imputed rs11023139 using MACH and 1000

Genomes Project reference panel in 750 non-Hispanic Caucasian partici-

pants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). The

sample included 185 healthy control (HC) participants and 369 AD. In order

to increase statistical power, the AD group included any subjects diagnosed

with AD as of 3/29/2011 and MCI participants with CSF-positive profile

(Ab1-42 protein <192 pg/mL and 181-phosphorylated-tau protein >23

pg/ml). [2] We used hippocampal grey matter (GM) density and entorhinal

cortex thickness as imaging endophenotypes and performed 1) cross-sec-

tional and 2) longitudinal QTL analysis at baseline and over 2 years, respec-

tively. For the longitudinal QTL analysis, we used imaging endophenotypes

at baseline as a covariate. In addition, we performed voxel-wisewhole-brain

analysis and vertex-wise cortical thickness analysis. Results: SPON1 gene

variant, rs11023139, was significantly associated with hippocampal GM

density at baseline (P ¼0.0173 - 0.0259; uncorrected) and longitudinal

change of the entorhinal cortical thickness (P ¼0.0096 - 0.0292; uncor-

rected) over 2 years in AD only (Table 1,). Furthermore, our whole brain

analysis demonstrated association in multiple brain regions between

rs11023139 and both GM density at baseline (Figure 1,) and decreased

rate of cortical thickness loss over 2 years (Figure 2). Conclusions: Neuro-

imaging genetics suggests that AD patients who are minor allele (A) carriers

of SPON1 gene variant rs11023139 show decreased neurodegeneration.

SPON1 encodes F-spondin protein, which impairs binding of cells to the