surrounding APOE on chromosome 19 has shown consistent association signals with LOAD. However, common variants in the region remain signif- icant 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 Cauca- sian 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 as- sessed 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 re- gion 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. Conclu- sions: 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 illus- trate the role of next generation sequencing in assessing rare variants which may in turn help explain missing heritability in AD and other complex dis- eases. Table 1 Gene-based association results (p-values) for CSF Ab 1-42 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 8.75 x 10 -4 0.01245 CBLC 7.37 x 10 -5 0.00225 BCAM 6.32 x 10 -4 0.00345 PVRL2 2.77 x 10 -5 0.3378 TOMM40 1.69 x 10 -7 0.07042 APOE 5.21 x 10 -7 0.00214 APOC1 1.01 x 10 -4 0.02915 APOC4 8.18 x 10 -3 0.72409 RELB 7.01 x 10 -4 0.00931 P3-018 INFLUENCE OF RARE PSEN1 VARIANTS ON QUANTITATIVE STRUCTURAL IMAGING AND CSF PHENOTYPES IN LATE ONSETALZHEIMER’S DISEASE Kwangsik T. Nho 1 , Sungeun Kim 1 , Shannon Leigh Risacher 1 , Li Shen 1 , Tatiana Foroud 1 , Paul Aisen 2 , Ronald Petersen 3 , Clifford Jack 4 , Leslie Shaw 5 , John Q. Trojanowski 6 , Michael Walter Weiner 7 , Robert Green 8 , Arthur Toga 9 , Andrew J. Saykin 10 , 1 Indiana University School of Medicine, Indianapolis, Indiana, United States; 2 UCSD, La Jolla, California, United States; 3 Mayo Clinic, Rochester, Minnesota, United States; 4 Mayo Clinic, Rochester, Minnesota, United States; 5 University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, United States; 6 University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States; 7 Center 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; 9 The Institute for Neuroimaging and Informatics and Laboratory of Neuro Imaging, Los Angeles, California, United States; 10 Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, United States. Contact e-mail: knho@iupui.edu Background: Pathogenic mutations in PSEN1 are known to cause famil- ial 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 par- ticipants underwent WGS from a blood sample and high resolution T1- weighted structural MRI at baseline. An automated MRI analysis technique (FreeSurfer) was used to measure cortical thickness and volume of neuroan- atomical structures. We assessed imaging and cerebrospinal fluid (CSF) bio- markers as LOAD-related quantitative endophenotypes. Single variant analyses were performed using PLINK and gene-based analyses of rare var- iants 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 in- creases the risk of LOAD only in participants carrying APOE ε4 allele (Ta- ble 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 All Subjects (N¼576) Subjects with APOE ε4 (N¼230) Subjects without APOE ε4 (N¼346) Ab142 0.6199 0.0254 0.2733 Tau 0.3795 0.0125 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) Burden Optimal SKAT Optimal SKAT after adjusting APOE ε4 LEntCtx 0.007 0.013 0.008 REntCtx 0.017 0.030 0.021 EntCtx 0.006 0.011 0.007 (b) Empirical P values using common variants (MAF  0.05) LEntCtx 1.00 REntCtx 1.00 EntCtx 1.00 Poster Presentations: P3 P633