ASSOCIATION ANALYSIS OF RARE VARIANTS NEAR THE APOE REGION WITH CEREBROSPINAL FLUID (CSF) BIOMARKERS OF ALZHEIMER'S DISEASE

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Poster Presentations: P3

regions studied. MRS showed significant AD-related changes in brain metabolites starting at 9 months of age. Conclusions: The CVN mouse model provides several desired AD-related end points and hence a more complete tool to study novel therapies targeted for treatment of AD. P3-015

HEIGHTENED ANXIETY LEVEL OF APPSW MICE UNVEILED BY A NOVEL ELEVATED PLATFORM TASK

William Suo1, XueFeng Ding1, Wei Peng2, Qiang Zhang1, 1Veterans Affairs Medical Center, Kansas City, Missouri, United States; 2Veterans Affairs Medical Center, Kansas City, Missouri, United States. Contact e-mail: [email protected] Background: Anxiety disorders affect 18% of Americans, and their managements remain to be a great challenge for the society. Aside from the anxiety disorders, there are many diseases, including Alzheimer’s disease (AD), that have anxiety as one of their clinic symptoms. Mechanistic and therapeutic studies of the anxiety disorders often begin at animal level, such as rodent. For the latter, the anxiety level is most commonly assessed by elevated plus maze (EPM). However, the existing anxiety assessment methods, including EPM, display limited sensitivity, often due to very high in-group variations. Thus a more sensitive method is needed for better assessing animal anxiety. Methods: We created a novel elevated platform (EP) with open edges. The platform was divided into three consecutive concentric ring zones so that the anxiety challenge increased in a continuous gradient from the central zone towards the outer zone. For comparisons, the anxiety levels of APPsw (Tg2576) mice and GRK5 +/- mice were assessed with open field (OF), EPM and the new EP. Results: Neither the OF, nor the EPM was able to reveal significant difference between any groups, but the EP did discover that APPsw mice displayed statistically significant higher anxiety level than the wild type controls. Conclusions: The EP is more sensitive than the OF and EPM in assessing the animal anxiety.

Timothy Behrens5, Martin Medrano7, Ivonne Jimenez-Velazquez8, Richard Mayeux9, 1Columbia University College of Physicians and Surgeons, New York, New York, United States; 2Columbia University, New York, New York, United States; 3Columbia University, New York, New York, United States; 4Columbia University, New York, New York, United States; 5Genentech, South San Francisco, California, United States; 6Genentech, Inc., South San Francisco, California, United States; 7School of Medicine, Pontificia Universidad Catolica Madre y Maestra, Santiago, Dominican Republic; 8 University of Puerto Rico, San Juan, United States; 9Columbia University, New York, New York, United States. Contact e-mail: [email protected] Background: A founder mutation G206A in PSEN1 was reported in Caribbean Hispanic families with early onset Alzheimer’s disease (EOAD). The age at onset (AAO) of Alzheimer’s disease (AD) in carriers of this mutation varied widely (range: 22-77). However, neither the APOE-ε4 allele nor environmental factors explained the differences in onset among mutation carriers. To identify genetic factors that may modify AAO, we conducted a 2-stage genomic study of EOAD, and then examined those genes in Caribbean Hispanics with late onset AD (LOAD). Methods: Three sets of Caribbean Hispanics with familial AD were investigated. First, 5 multiplex EOAD families that carry the G206A-PSEN1 mutation were examined using linkage analysis. Second, 31 individuals who carry the G206A-PSEN1 mutation were investigated using exome sequencing. Lastly, two LOAD GWAS sets of Caribbean Hispanics were used to determine whether the same genes influence AAO. Results: Genome wide linkage analysis of AD identified the strongest linkage support for rs13478 at 4q35.1 (LOD¼3.69). We then examined the exome data under the linkage peak. An effect allele of rs13130022 in SORBS2 was associated with delay in AAO by w11 years. In the remaining exome, the strongest signal for AAO was observed at rs906815 in NPHP1 at 2q13 (P¼4.51E-6), and homozygous carriers of the rare allele had the onset w21 years earlier than carriers of the common allele. In addition, an effect variant rs6542814 in SH3RF3, flanking NPHP1, was associated with a delay in AAO by w9 years. In addition, these genes – SORBS2, SHR3RF3 and NPHP1 – were associated with AAO in individuals with LOAD (p¼3.8E-6, p¼2.7E-11, p¼5.5E-5, respectively). However, the differences in AAO in individuals with LOAD were much smaller than those observed in EOAD. Conclusions: We report that variants in a family of SH3 domain genes, SORBS2, SH3RF3 and NPHP1 may modify AAO of AD in Caribbean Hispanic carriers of the G206A variant. Further, these genes may play a role in AAO of LOAD. Given the related nature of these genes they are attractive therapeutic targets for further investigation. P3-017

P3-016

SORBS2, SH3RF3, AND NPHP1 MODIFY AGE AT ONSET IN CARRIERS OF THE G206A MUTATION IN PSEN1 WITH FAMILIAL ALZHEIMER’S DISEASE

Joseph H. Lee1, Rong Cheng1, Badri N. Vardarajan2, Rafael A. Lantigua3, Dolly Reyes-Dumeyer4, Ward Ortmann5, Robert Graham6, Tushar Bhangale5,

ASSOCIATION ANALYSIS OF RARE VARIANTS NEAR THE APOE REGION WITH CEREBROSPINAL FLUID (CSF) BIOMARKERS OF ALZHEIMER’S DISEASE

Kwangsik T. Nho1, Sungeun Kim1, Shannon Leigh Risacher1, Li Shen1, Tatiana Foroud1, Leslie Shaw2, John Q. Trojanowski3, Paul Aisen4, Ronald Petersen5, Clifford Jack6, Michael Walter Weiner7, Robert Green8, Arthur Toga9, Andrew J. Saykin10, 1Indiana University School of Medicine, Indianapolis, Indiana, United States; 2University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, United States; 3University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States; 4UCSD, La Jolla, California, United States; 5Mayo Clinic, Rochester, Minnesota, United States; 6Mayo Clinic, Rochester, Minnesota, United States; 7Center for Imaging of Neurodegenerative Diseases, VA Medical Center and UCSF, San Francisco, California, United States; 8 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States; 9Institute for Neuroimaging and Informatics and Laboratory of Neuro Imaging, Los Angeles, California, United States; 10Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, United States. Contact e-mail: [email protected] Background: The APOE ε4 allele is the most significant common genetic risk factor for late onset Alzheimer’s disease (LOAD). The region

Poster Presentations: P3 surrounding APOE on chromosome 19 has shown consistent association signals with LOAD. However, common variants in the region remain significant after adjusting for APOE ε4 (Jun et al, 2012). We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) biomarkers of LOAD. Methods: A whole genome sequencing (WGS) data set (N¼815) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort was used in this analysis. 576 non-Hispanic Caucasian participants underwent WGS from a blood sample and had CSF biomarkers at baseline. We extracted all rare variants (MAF < 0.05) within a 300 Kb region in APOE’ s vicinity including 9 Genes (Table 1). We assessed CSF biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). Age, sex, and number of APOE ε4 alleles were used as covariates. Results: A total of 2,608 rare or low frequency variants (MAF < 0.05) were found within a region of 610Kb from 9 genes near APOE. Among them, 76 rare non-synonymous variants were observed. All 8 genes except APOC4 spanning the entire region were significantly associated with CSF Ab 1-42 with TOMM40 showing near genome-wide level significance (p < 5 X 10 -7) (Table 1). However, gene-based analysis resulted in greatly diminished associations after adjusting for APOE ε4 allele count. Only 3 genes (CBLC, BCAM, APOE) remained significant after correcting for the number of tests (p < 0.05/9 ¼ 0.0056). Particularly noteworthy were rare variants in APOE that showed significant association independent of ε4 allele count. Conclusions: Rare variants within genes near the APOE region are significantly associated with CSF Ab 1-42 after adjusting for APOE ε4 allele count. BCAM may meditate intracellular signaling and CBLC plays important roles in cell signaling. These findings warrant further investigation and illustrate the role of next generation sequencing in assessing rare variants which may in turn help explain missing heritability in AD and other complex diseases. Table 1 Gene-based association results (p-values) for CSF Ab1-42 using only rare or low frequency variants (MAF < 0.05) before and after adjusting for the number of APOE ε4 alleles Gene

P value

P value after adjusting for APOE ε4

BCL3 CBLC BCAM PVRL2 TOMM40 APOE APOC1 APOC4 RELB

8.75 x 10-4 7.37 x 10-5 6.32 x 10-4 2.77 x 10-5 1.69 x 10-7 5.21 x 10-7 1.01 x 10-4 8.18 x 10-3 7.01 x 10-4

0.01245 0.00225 0.00345 0.3378 0.07042 0.00214 0.02915 0.72409 0.00931

P3-018

INFLUENCE OF RARE PSEN1 VARIANTS ON QUANTITATIVE STRUCTURAL IMAGING AND CSF PHENOTYPES IN LATE ONSETALZHEIMER’S DISEASE

Kwangsik T. Nho1, Sungeun Kim1, Shannon Leigh Risacher1, Li Shen1, Tatiana Foroud1, Paul Aisen2, Ronald Petersen3, Clifford Jack4, Leslie Shaw5, John Q. Trojanowski6, Michael Walter Weiner7, Robert Green8, Arthur Toga9, Andrew J. Saykin10, 1Indiana University School of Medicine, Indianapolis, Indiana, United States; 2UCSD, La Jolla, California, United States; 3Mayo Clinic, Rochester, Minnesota, United States; 4Mayo Clinic, Rochester, Minnesota, United States; 5University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, United States; 6 University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States; 7Center for Imaging of Neurodegenerative Diseases, VA Medical Center and UCSF, San Francisco, California, United States; 8Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States; 9The Institute for Neuroimaging and Informatics and

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Laboratory of Neuro Imaging, Los Angeles, California, United States; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, United States. Contact e-mail: [email protected] 10

Background: Pathogenic mutations in PSEN1 are known to cause familial early onset Alzheimer’s disease (EOAD) but common variants in PSEN1 have not been found to strongly influence late onset AD (LOAD). The association of rare variants in PSEN1 with LOAD-related endophenotypes has received little attention. In this study, we performed a rare variant association analysis of PSEN1 with quantitative biomarkers of LOAD using whole genome sequencing (WGS). Methods: A WGS data set (N¼815) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort was used in this analysis. 755 non-Hispanic Caucasian participants underwent WGS from a blood sample and high resolution T1weighted structural MRI at baseline. An automated MRI analysis technique (FreeSurfer) was used to measure cortical thickness and volume of neuroanatomical structures. We assessed imaging and cerebrospinal fluid (CSF) biomarkers as LOAD-related quantitative endophenotypes. Single variant analyses were performed using PLINK and gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). Results: A total of 901 rare or low frequency variants (MAF < 0.05) were found within a region of 610Kb from PSEN1. Among them, six exonic (three non-synonymous) variants were observed. A single variant association analysis showed that the PSEN1 p.E318G variant increases the risk of LOAD only in participants carrying APOE ε4 allele (Table 1) where individuals carrying the minor allele of this PSEN1 risk variant have lower CSF Ab142 and higher CSF tau. A gene-based analysis resulted in a significant association of rare but not common (MAF  0.05) PSEN1 variants with bilateral entorhinal cortical thickness (Table 2). Conclusions: The PSEN1 p.E318G variant increases the risk of LOAD only in APOE ε4 carriers (Benitez et al, 2013) and PSEN1 rare variants collectively show a significant association with the brain atrophy in regions preferentially affected by LOAD, providing further support for a role of PSEN1 in LOAD. Combining rare variants from sequencing with imaging and other intermediate phenotypes could help explain the missing heritability in LOAD. Table 1 Association results (p-values) of PSEN1 p.E318G variant for quantitative trait analysis using a dominant model

Ab142 Tau

All Subjects (N¼576)

Subjects with APOE ε4 (N¼230)

Subjects without APOE ε4 (N¼346)

0.6199 0.3795

0.0254 0.0125

0.2733 0.8673

Table 2 Gene-based association results (p-values) for imaging biomarkers using (a) rare or low frequency variants (MAF < 0.05); (b) common variants (MAF  0.05), where empirical p values were calculated using 10,000 permutations in PLINK (a)

LEntCtx REntCtx EntCtx

Burden

Optimal SKAT

Optimal SKAT after adjusting APOE ε4

0.007 0.017 0.006

0.013 0.030 0.011

0.008 0.021 0.007

(b) Empirical P values using common variants (MAF  0.05) LEntCtx REntCtx EntCtx

1.00 1.00 1.00