- Email: [email protected]
RETROFITTING EXISTING TOOLS ACROSS THE ALZHEIMER'S DISEASE SPECTRUM
P244 Featured Research Sessions: F4-03: Addressing the Challenges for Clinical Trial Design: An ADNI-PPSB Pre-Competitive Cross-Pharma Collaboration
therapeutic trials. Most trials included the MMSE (28/32), ADAS-Cog/11 (14/32) or a variant (11/32), CDR-SB (19/32), and a measure of function (ADCS-ADL [10/32] or DAD [10/32]). However, many instruments were not widely included (e.g., FAQ, BNT, Blessed Dementia Rating scale) or different versions measuring the same domain (NYU paragraph recall vs. WMS-R Logical Memory). Interestingly, only 1/11 MCI and 5/21 AD studies included a delayed word recall measure. Conclusions: The heterogeneity of clinical instruments included in the trials reviewed may reflect the field’s evolving knowledge of AD, neuropsychology, and/or statistical methodologies. Use of common assessments can statistically bridge between studies and may provide a reference point for the development of new assessments measuring cognition and function earlier in the disease continuum. Work in pre-competitive space within different consortia may help increase uniform use of empirically supported clinical measures in trials, as well as exploration of novel ones thereby advancing science, as well as the development of more effective AD therapies.
F4-03-03
VALIDATION OF NOVEL COMPOSITE OUTCOME MEASURES FOR PRE-DEMENTIA ALZHEIMER’S DISEASE
Nandini Raghavan1, Alette M. Wessels2, David M. Shera3, Enchi Liu4, Gerald Novak1, Jinping Wang5, Michael T. Ropacki1, Peng Yu2, Peter Castelluccio2, Tobias Verbeke6, Veronika Logovinsky5, Xin Zhao1, 1 Janssen Research & Development, Raritan, New Jersey, United States; 2Eli Lilly and Company, Indianapolis, Indiana, United States; 3Merck, North Wales, Pennsylvania, United States; 4Janssen Research & Development, Raritan, New Jersey, United States; 5Eisai Inc., Indianapolis, Indiana, United States; 6OpenAnalytics, Antwerpen, Belgium. Contact e-mail: [email protected] Background: Therapeutic trials in Alzheimer’s Disease (AD) are actively pursuing trial designs in patients in the pre-dementia stages of the disease. One of the biggest challenges in designing such trials is determining the right efficacy endpoint to capture change. Several novel endpoints have been recently proposed independently by various companies to meet the need for a clinical outcome sensitive to disease progression in mild cognitive
impairment (MCI) and prodromal AD. Methods: A key aim of the Clinical Endpoint Working Group (CEWG) was to evaluate the applicability and to assess the performance of novel composite outcome measures to currently available clinical data. To undertake this evaluation, the Working Group identified several evaluation criteria. Statisticians and analysts in the Working Group from the various participating companies collaborated to develop common programming code for the evaluation. The evaluation will be performed on both public and several company-proprietary datasets in order to study various attributes of proposed scales and come to a common understanding of their strengths and limitations. Results: In this presentation, we will describe the novel collaboration model and also present preliminary results from the evaluation. F4-03-04
RETROFITTING EXISTING TOOLS ACROSS THE ALZHEIMER’S DISEASE SPECTRUM
Alette M. Wessels1, Nandini Raghavan2, Peng Yu1, Peter Castelluccio1, Scott W. Andersen1, Veronika Logovinsky3, Zongjun Zhang1, 1Eli Lilly and Company, Indianapolis, Indiana, United States; 2Janssen Research & Development, Raritan, New Jersey, United States; 3Eisai Inc, Woodcliff Lake, New Jersey, United States. Contact e-mail: wessels_alette_maria@ lilly.com Background: Established instruments to measure cognition in subjects with Alzheimer’s disease (AD) lack sensitivity to disease progression and therapeutic response in early stages of the disease process. Several efforts have been initiated to develop a single scale optimized for trials in patients with mild cognitive impairment (MCI). The objectives of this work were to evaluate the performance of various cognitive/functional composites and to compare the performance of each composite against the others and against more commonly used endpoints such as the ADAS cog, CDR-SB and MMSE. Methods: Table 1 summarizes the composites evaluated. These composites were optimized for MCI and were proposed by various pharmaceutical companies. ADNI 1, GO, and 2 data (normal, MCI, AD subjects), and phase 3 semagacestat and solanezumab placebo and treatment data (mild AD subjects) were used for the analyses. Performance of composites was evaluated by comparing the signal to noise ratio (SNR) of each of the individual composites. 500 bootstraps of the
Table 1 Cognitive_Cognitive/functional composites and their individual components Composite
ADAS-Cog Items
ADCOMS (Eisai) Cognitive/ Functional TriAD (Janssen) Cognitive
Delayed word recall, Orientation Word recognition, Word finding Word Recall, Delayed word recall, Orientation
ADCCS (Janssen) Cognitive/ Functional ProADAS (Astra Zeneca) Cognitive AVLT Cognitive
Word Recall, Delayed word recall, Orientation, Word recognition Word Recall, Delayed word recall, Orientation, Word Finding, Number cancellation V1_Delayed word recall
AVLT
CDR
MMSE
CDR-SB
Orientation Constructionalpraxis
Other
CDR-SB-Cog (Memory, Judg&problem solv, Orient) CDR-SB
V2_Delayed word recall V3_Delayed + Immediate recall V4_Immediate recall V5_Immediate recall + retrieval efficiency (recognition – delayed word recall)
All items
Logical memory IIa delayed paragraph recall - Digit Symbol Substitution
Abbreviations: AD¼Alzheimer’s Disease; ADAS-Cog¼Alzheimer’s Disease Assessment Scale-Cognitive Subscale; ADCCS¼ Alzheimer’s Disease Clinical Composite Score; ADCOMS¼ Alzheimer’s disease COMposite Score; ADNI¼Alzheimer’s Disease Neuroimaging Initiative; AVLT¼Auditory Verbal Learning Test; CDR-SB¼Clinical Dementia Rating Scale-Sum of Boxes; CDR-SB-Cog¼CDR-Cognitive component; LSMean¼Least Squares Mean; MCI¼Mild Cognitive Impairment; MMRM¼Mixed Model Repeated Measures; MMSE¼Mini–Mental Sate Examination; ProADAS ¼ Prodromal Alzheimer’s Disease Assessment Scale; SD¼Standard Deviation; SNR¼Signal to Noise Ratio; TriAD¼ Tri-Domain Cognitive Composite for Alzheimer’s Disease;V¼version
Featured Research Sessions: F4-04: International Genomics of Alzheimer’s Disease Project (IGAP): GWAS and Beyond
original subject level dataset were performed and mixed-model repeated measures (MMRM) analyses of post-baseline changes up to 18 (semagacestat/solanezumab) or 24 (ADNI) months were run on each bootstrapped dataset. The SNR’s were calculated by dividing the least squares mean (LSMean) change from baseline to endpoint by the standard deviation change from baseline to endpoint. Bootstrap 95% confidence intervals were calculated to estimate the variability of the coefficient estimates. Results: For late MCI subjects in ADNI, Alzheimer’s Disease Clinical Composite Score (ADCCS) and Alzheimer’s Disease Composite Score (ADCOMS) outperform the ADAS-Cog11 and 13 and MMSE. In the solanezumab (but not semagecestat) placebo group, ADCOMS outperforms ADAS-cog 11 and 14. None of the composites showed improved performance over CDR-SB in any of the placebo analyses. The solanezumab treatment analyses revealed that ADAS-cog 11 and 14 outperform ADCCS and Prodromal Alzheimer’s Disease Assessment Scale (ProADAS) (but all are able to detect treatment separation from placebo). Conclusions: Different composites have different abilities to detect change due to disease progression and to treatment effects. Further study with additional datasets is needed to clarify the benefits of using a composite endpoint and to identify areas for improvement. WEDNESDAY, JULY 16, 2014 FEATURED RESEARCH SESSIONS F4-04 INTERNATIONAL GENOMICS OF ALZHEIMER’S DISEASE PROJECT (IGAP): GWAS AND BEYOND F4-04-01
EXOME CHIP META-ANALYSIS OF ALZHEIMER’S DISEASE IN THE IGAP CONSORTIUM
Sven J. van der Lee1, Adam Naj2, Cornelia van Duijn1, Gerard D. Schellenberg2, International Genomics of Alzheimer’s Project (IGAP)3, Johanna Jakobsdottir4, Julie Williams5, Li-San Wang2, Maria Vronskaya5, Philippe Amouyel6, Rebecca Sims5, Sudha Seshadri7, 1 Erasmus MC, Rotterdam, Netherlands; 2University of Pennsylvania, Philadelphia, Pennsylvania, United States; 3International Genomics of Alzheimer’s Project (IGAP), Rotterdam, Netherlands; 4Icelandic Heart Association, Reykjavik, Iceland; 5Cardiff University,Cardiff, Wales, United Kingdom; 6Institut Pasteur de Lille, Lille, France; 7Boston University, Boston, Massachusetts, United States. Contact e-mail: s.vanderlee@ erasmusmc.nl Background: Up until now 22 loci are known to be involved in Alzheimer disease (AD) including two recently identified rare exonic variants in the TREM2 and PLD3 genes. This has prompted us to a search for coding variants within the International Genomics of Alzheimer’s Project (IGAP). Methods: We screened the exomes of 15,788 AD cases and 19,795 controls of European ancestry for rare coding variants using the Illumina v1.0 (w90%) and v1.1 (10%) exome arrays. Genotype calling was performed independently within each group of IGAP. Analysis was performed based on a joint analyses plan using logistic regression within each cohort. The meta-analysis combining results from all participating cohorts showed 203,267 polymorphic variants in at least one study. Gene and variant annotations were done using dbNSFP. Results: We replicated association of several known genes including a common intronic variant, rs769449, at APOE (OR ¼ 3.1, p-value ¼ 1x10 -380), an exonic variant rs7412, part of the APOE2 (OR ¼ 0.43, p-value ¼ 2x10 -80), and common intronic variants around PICALM (OR ¼ 0.88, p-value ¼ 2.3 1x10 -11) and BIN1 (OR ¼ 0.89 p-value ¼ 3.9x10 -9). In addition to the previously known common variant we identified a novel common exonic variant in MS4A6A (OR ¼ 0.9, p-value ¼ 2.9x10 -7). We further identified a new rare exonic variant at TREM2 which had a consistent AD risk increasing effect over the studies resulting in an odds ratio of 1.53 (p-value ¼ 8.4x10 -7). Various suggestive new exonic rare variants were found (MAF < 0.001% and p-value < 1x10 -6) including variants in ABCA7 and TECTA, a gene expressed in multiple brain regions and previously associated with hereditary, non-syndromic deafness. Conclusions: We confirmed the association of common and rare variants previously associated to AD and identified new rare coding var-
P245
iants in TREM2 and MS4A6A. We are currently replicating the findings of the new genes and will report these at the meeting. F4-04-02
COMPREHENSIVE GENE-GENE INTERACTION META-ANALYSIS OF IGAP GWA STUDIES
Tim Becker1, Alfredo Ramirez2, Christine Herold1, Cornelia van Duijn3, Gerard D. Schellenberg4, International Genomics of Alzheimer’s Project (IGAP)5, Julie Williams6, Philippe Amouyel7, Qiong Yang8, Sudha Seshadri8, Sven J. van der Lee3, 1German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; 2University of Bonn, Bonn, Germany; 3Erasmus MC, Bonn, Germany; 4University of Pennsylvania, Philadelphia, Pennsylvania, United States; 5International Genomics of Alzheimer’s Project (IGAP), Bonn, Germany; 6Cardiff University, Bonn, Germany; 7Institut Pasteur de Lille, Lille, France; 8 Boston University, Boston, Massachusetts, United States. Contact e-mail: [email protected] Background: Genetic interaction is suspected to play an important role in genetically complex diseases such as AD. However, due to computational challenges, lack of a consensus statistical analysis method, and lack of power, no compelling evidence for any kind of epistasis has yet been given for AD. Methods: We conducted an exhaustive search for interacting SNP pairs in 6,415 AD patients and 19,492 controls from the IGAP consortium. The analysis was conducted in a two-stage meta-analysis fashion. In stage I, participating groups performed a Genome-wide Interaction Analysis (GWIA) of 1010 SNP pairs with a fast pre-test. The groups interchanged their top 2,000,000 results to form a joined list of candidate pairs which all groups re-analyzed in stage II. The full 8 degrees of freedom model was applied, using sex, age and leading PCAs as covariates. Meta-Analysis of the results was done using the "Sigma-method", an extension of fixed effects meta-analysis to multiple regression models. The linkage disequilibrium region surrounding APOE was excluded from the analysis region, since interaction with APOE is investigated in an own dedicated project. Results: A pair of SNP from the known PICALM gene and DOCK1 reaches experiment-wide significance (p < 6.5 x 10 -12). In addition, a SNP from TM4SF4, again together with PICALM, comes close to significance at the current stage of analysis. Conclusions: The analysis is ongoing and results from further participating groups are expected to arrive.
F4-04-03
DO THE VARIANTS IDENTIFIED IN IGAP IMPROVE RISK PREDICTION OF ALZHEIMER’S DISEASE?
Vincent Antoine Chouraki1, Anita DeStefano2, Celine Bellenguez3, Christiane Reitz4, Cornelia van Duijn5, David Bennett6, Fleur Maury3, International Genomics of Alzheimer’s Project (IGAP)7, JeanCharles Lambert3, Johanna Jakobsdottir8, Joshua C. Bis9, Lenore Launer10, Paul Crane9, Richard Mayeux4, Seung Hoan Choi2, Sudha Seshadri1, 1 Boston University School of Medicine, Boston, Massachusetts, United States; 2Boston University School of Public Health, Boston, Massachusetts, United States; 3Institut Pasteur de Lille, Lille, France; 4Columbia University, New York, New York, United States; 5Erasmus MC, Rotterdam, Netherlands; 6 Rush Medical Center, Chicago, Illinois, United States; 7International Genomics of Alzheimer’s Project (IGAP), Lille, France; 8Icelandic Heart Association, Kopavagur, Iceland; 9University of Washington, Seattle, Washington, United States; 10National Institute on Aging, Bethesda, Maryland, United States. Contact e-mail: [email protected] Background: The International Genomics of Alzheimer’s Project (IGAP) recently confirmed 8 of 9 previously known variants in addition to APOEε, and identified 11 new variants associated with risk of Alzheimer’s disease (AD), although all have low to moderate effect sizes. We created a genetic risk score (GRS) comprising these 19 variants and evaluated its association with incident AD. We also assessed the improvement in risk prediction, when this GRS was added to models that used previously known risk factors. Methods: We used data from the Framingham Heart Study. After excluding prevalent dementia and participants younger than age 65 years at DNA draw, we computed a genetic risk score as a weighted sum of risk allele doses,
therapeutic trials. Most trials included the MMSE (28/32), ADAS-Cog/11 (14/32) or a variant (11/32), CDR-SB (19/32), and a measure of function (ADCS-ADL [10/32] or DAD [10/32]). However, many instruments were not widely included (e.g., FAQ, BNT, Blessed Dementia Rating scale) or different versions measuring the same domain (NYU paragraph recall vs. WMS-R Logical Memory). Interestingly, only 1/11 MCI and 5/21 AD studies included a delayed word recall measure. Conclusions: The heterogeneity of clinical instruments included in the trials reviewed may reflect the field’s evolving knowledge of AD, neuropsychology, and/or statistical methodologies. Use of common assessments can statistically bridge between studies and may provide a reference point for the development of new assessments measuring cognition and function earlier in the disease continuum. Work in pre-competitive space within different consortia may help increase uniform use of empirically supported clinical measures in trials, as well as exploration of novel ones thereby advancing science, as well as the development of more effective AD therapies.
F4-03-03
VALIDATION OF NOVEL COMPOSITE OUTCOME MEASURES FOR PRE-DEMENTIA ALZHEIMER’S DISEASE
Nandini Raghavan1, Alette M. Wessels2, David M. Shera3, Enchi Liu4, Gerald Novak1, Jinping Wang5, Michael T. Ropacki1, Peng Yu2, Peter Castelluccio2, Tobias Verbeke6, Veronika Logovinsky5, Xin Zhao1, 1 Janssen Research & Development, Raritan, New Jersey, United States; 2Eli Lilly and Company, Indianapolis, Indiana, United States; 3Merck, North Wales, Pennsylvania, United States; 4Janssen Research & Development, Raritan, New Jersey, United States; 5Eisai Inc., Indianapolis, Indiana, United States; 6OpenAnalytics, Antwerpen, Belgium. Contact e-mail: [email protected] Background: Therapeutic trials in Alzheimer’s Disease (AD) are actively pursuing trial designs in patients in the pre-dementia stages of the disease. One of the biggest challenges in designing such trials is determining the right efficacy endpoint to capture change. Several novel endpoints have been recently proposed independently by various companies to meet the need for a clinical outcome sensitive to disease progression in mild cognitive
impairment (MCI) and prodromal AD. Methods: A key aim of the Clinical Endpoint Working Group (CEWG) was to evaluate the applicability and to assess the performance of novel composite outcome measures to currently available clinical data. To undertake this evaluation, the Working Group identified several evaluation criteria. Statisticians and analysts in the Working Group from the various participating companies collaborated to develop common programming code for the evaluation. The evaluation will be performed on both public and several company-proprietary datasets in order to study various attributes of proposed scales and come to a common understanding of their strengths and limitations. Results: In this presentation, we will describe the novel collaboration model and also present preliminary results from the evaluation. F4-03-04
RETROFITTING EXISTING TOOLS ACROSS THE ALZHEIMER’S DISEASE SPECTRUM
Alette M. Wessels1, Nandini Raghavan2, Peng Yu1, Peter Castelluccio1, Scott W. Andersen1, Veronika Logovinsky3, Zongjun Zhang1, 1Eli Lilly and Company, Indianapolis, Indiana, United States; 2Janssen Research & Development, Raritan, New Jersey, United States; 3Eisai Inc, Woodcliff Lake, New Jersey, United States. Contact e-mail: wessels_alette_maria@ lilly.com Background: Established instruments to measure cognition in subjects with Alzheimer’s disease (AD) lack sensitivity to disease progression and therapeutic response in early stages of the disease process. Several efforts have been initiated to develop a single scale optimized for trials in patients with mild cognitive impairment (MCI). The objectives of this work were to evaluate the performance of various cognitive/functional composites and to compare the performance of each composite against the others and against more commonly used endpoints such as the ADAS cog, CDR-SB and MMSE. Methods: Table 1 summarizes the composites evaluated. These composites were optimized for MCI and were proposed by various pharmaceutical companies. ADNI 1, GO, and 2 data (normal, MCI, AD subjects), and phase 3 semagacestat and solanezumab placebo and treatment data (mild AD subjects) were used for the analyses. Performance of composites was evaluated by comparing the signal to noise ratio (SNR) of each of the individual composites. 500 bootstraps of the
Table 1 Cognitive_Cognitive/functional composites and their individual components Composite
ADAS-Cog Items
ADCOMS (Eisai) Cognitive/ Functional TriAD (Janssen) Cognitive
Delayed word recall, Orientation Word recognition, Word finding Word Recall, Delayed word recall, Orientation
ADCCS (Janssen) Cognitive/ Functional ProADAS (Astra Zeneca) Cognitive AVLT Cognitive
Word Recall, Delayed word recall, Orientation, Word recognition Word Recall, Delayed word recall, Orientation, Word Finding, Number cancellation V1_Delayed word recall
AVLT
CDR
MMSE
CDR-SB
Orientation Constructionalpraxis
Other
CDR-SB-Cog (Memory, Judg&problem solv, Orient) CDR-SB
V2_Delayed word recall V3_Delayed + Immediate recall V4_Immediate recall V5_Immediate recall + retrieval efficiency (recognition – delayed word recall)
All items
Logical memory IIa delayed paragraph recall - Digit Symbol Substitution
Abbreviations: AD¼Alzheimer’s Disease; ADAS-Cog¼Alzheimer’s Disease Assessment Scale-Cognitive Subscale; ADCCS¼ Alzheimer’s Disease Clinical Composite Score; ADCOMS¼ Alzheimer’s disease COMposite Score; ADNI¼Alzheimer’s Disease Neuroimaging Initiative; AVLT¼Auditory Verbal Learning Test; CDR-SB¼Clinical Dementia Rating Scale-Sum of Boxes; CDR-SB-Cog¼CDR-Cognitive component; LSMean¼Least Squares Mean; MCI¼Mild Cognitive Impairment; MMRM¼Mixed Model Repeated Measures; MMSE¼Mini–Mental Sate Examination; ProADAS ¼ Prodromal Alzheimer’s Disease Assessment Scale; SD¼Standard Deviation; SNR¼Signal to Noise Ratio; TriAD¼ Tri-Domain Cognitive Composite for Alzheimer’s Disease;V¼version
Featured Research Sessions: F4-04: International Genomics of Alzheimer’s Disease Project (IGAP): GWAS and Beyond
original subject level dataset were performed and mixed-model repeated measures (MMRM) analyses of post-baseline changes up to 18 (semagacestat/solanezumab) or 24 (ADNI) months were run on each bootstrapped dataset. The SNR’s were calculated by dividing the least squares mean (LSMean) change from baseline to endpoint by the standard deviation change from baseline to endpoint. Bootstrap 95% confidence intervals were calculated to estimate the variability of the coefficient estimates. Results: For late MCI subjects in ADNI, Alzheimer’s Disease Clinical Composite Score (ADCCS) and Alzheimer’s Disease Composite Score (ADCOMS) outperform the ADAS-Cog11 and 13 and MMSE. In the solanezumab (but not semagecestat) placebo group, ADCOMS outperforms ADAS-cog 11 and 14. None of the composites showed improved performance over CDR-SB in any of the placebo analyses. The solanezumab treatment analyses revealed that ADAS-cog 11 and 14 outperform ADCCS and Prodromal Alzheimer’s Disease Assessment Scale (ProADAS) (but all are able to detect treatment separation from placebo). Conclusions: Different composites have different abilities to detect change due to disease progression and to treatment effects. Further study with additional datasets is needed to clarify the benefits of using a composite endpoint and to identify areas for improvement. WEDNESDAY, JULY 16, 2014 FEATURED RESEARCH SESSIONS F4-04 INTERNATIONAL GENOMICS OF ALZHEIMER’S DISEASE PROJECT (IGAP): GWAS AND BEYOND F4-04-01
EXOME CHIP META-ANALYSIS OF ALZHEIMER’S DISEASE IN THE IGAP CONSORTIUM
Sven J. van der Lee1, Adam Naj2, Cornelia van Duijn1, Gerard D. Schellenberg2, International Genomics of Alzheimer’s Project (IGAP)3, Johanna Jakobsdottir4, Julie Williams5, Li-San Wang2, Maria Vronskaya5, Philippe Amouyel6, Rebecca Sims5, Sudha Seshadri7, 1 Erasmus MC, Rotterdam, Netherlands; 2University of Pennsylvania, Philadelphia, Pennsylvania, United States; 3International Genomics of Alzheimer’s Project (IGAP), Rotterdam, Netherlands; 4Icelandic Heart Association, Reykjavik, Iceland; 5Cardiff University,Cardiff, Wales, United Kingdom; 6Institut Pasteur de Lille, Lille, France; 7Boston University, Boston, Massachusetts, United States. Contact e-mail: s.vanderlee@ erasmusmc.nl Background: Up until now 22 loci are known to be involved in Alzheimer disease (AD) including two recently identified rare exonic variants in the TREM2 and PLD3 genes. This has prompted us to a search for coding variants within the International Genomics of Alzheimer’s Project (IGAP). Methods: We screened the exomes of 15,788 AD cases and 19,795 controls of European ancestry for rare coding variants using the Illumina v1.0 (w90%) and v1.1 (10%) exome arrays. Genotype calling was performed independently within each group of IGAP. Analysis was performed based on a joint analyses plan using logistic regression within each cohort. The meta-analysis combining results from all participating cohorts showed 203,267 polymorphic variants in at least one study. Gene and variant annotations were done using dbNSFP. Results: We replicated association of several known genes including a common intronic variant, rs769449, at APOE (OR ¼ 3.1, p-value ¼ 1x10 -380), an exonic variant rs7412, part of the APOE2 (OR ¼ 0.43, p-value ¼ 2x10 -80), and common intronic variants around PICALM (OR ¼ 0.88, p-value ¼ 2.3 1x10 -11) and BIN1 (OR ¼ 0.89 p-value ¼ 3.9x10 -9). In addition to the previously known common variant we identified a novel common exonic variant in MS4A6A (OR ¼ 0.9, p-value ¼ 2.9x10 -7). We further identified a new rare exonic variant at TREM2 which had a consistent AD risk increasing effect over the studies resulting in an odds ratio of 1.53 (p-value ¼ 8.4x10 -7). Various suggestive new exonic rare variants were found (MAF < 0.001% and p-value < 1x10 -6) including variants in ABCA7 and TECTA, a gene expressed in multiple brain regions and previously associated with hereditary, non-syndromic deafness. Conclusions: We confirmed the association of common and rare variants previously associated to AD and identified new rare coding var-
P245
iants in TREM2 and MS4A6A. We are currently replicating the findings of the new genes and will report these at the meeting. F4-04-02
COMPREHENSIVE GENE-GENE INTERACTION META-ANALYSIS OF IGAP GWA STUDIES
Tim Becker1, Alfredo Ramirez2, Christine Herold1, Cornelia van Duijn3, Gerard D. Schellenberg4, International Genomics of Alzheimer’s Project (IGAP)5, Julie Williams6, Philippe Amouyel7, Qiong Yang8, Sudha Seshadri8, Sven J. van der Lee3, 1German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; 2University of Bonn, Bonn, Germany; 3Erasmus MC, Bonn, Germany; 4University of Pennsylvania, Philadelphia, Pennsylvania, United States; 5International Genomics of Alzheimer’s Project (IGAP), Bonn, Germany; 6Cardiff University, Bonn, Germany; 7Institut Pasteur de Lille, Lille, France; 8 Boston University, Boston, Massachusetts, United States. Contact e-mail: [email protected] Background: Genetic interaction is suspected to play an important role in genetically complex diseases such as AD. However, due to computational challenges, lack of a consensus statistical analysis method, and lack of power, no compelling evidence for any kind of epistasis has yet been given for AD. Methods: We conducted an exhaustive search for interacting SNP pairs in 6,415 AD patients and 19,492 controls from the IGAP consortium. The analysis was conducted in a two-stage meta-analysis fashion. In stage I, participating groups performed a Genome-wide Interaction Analysis (GWIA) of 1010 SNP pairs with a fast pre-test. The groups interchanged their top 2,000,000 results to form a joined list of candidate pairs which all groups re-analyzed in stage II. The full 8 degrees of freedom model was applied, using sex, age and leading PCAs as covariates. Meta-Analysis of the results was done using the "Sigma-method", an extension of fixed effects meta-analysis to multiple regression models. The linkage disequilibrium region surrounding APOE was excluded from the analysis region, since interaction with APOE is investigated in an own dedicated project. Results: A pair of SNP from the known PICALM gene and DOCK1 reaches experiment-wide significance (p < 6.5 x 10 -12). In addition, a SNP from TM4SF4, again together with PICALM, comes close to significance at the current stage of analysis. Conclusions: The analysis is ongoing and results from further participating groups are expected to arrive.
F4-04-03
DO THE VARIANTS IDENTIFIED IN IGAP IMPROVE RISK PREDICTION OF ALZHEIMER’S DISEASE?
Vincent Antoine Chouraki1, Anita DeStefano2, Celine Bellenguez3, Christiane Reitz4, Cornelia van Duijn5, David Bennett6, Fleur Maury3, International Genomics of Alzheimer’s Project (IGAP)7, JeanCharles Lambert3, Johanna Jakobsdottir8, Joshua C. Bis9, Lenore Launer10, Paul Crane9, Richard Mayeux4, Seung Hoan Choi2, Sudha Seshadri1, 1 Boston University School of Medicine, Boston, Massachusetts, United States; 2Boston University School of Public Health, Boston, Massachusetts, United States; 3Institut Pasteur de Lille, Lille, France; 4Columbia University, New York, New York, United States; 5Erasmus MC, Rotterdam, Netherlands; 6 Rush Medical Center, Chicago, Illinois, United States; 7International Genomics of Alzheimer’s Project (IGAP), Lille, France; 8Icelandic Heart Association, Kopavagur, Iceland; 9University of Washington, Seattle, Washington, United States; 10National Institute on Aging, Bethesda, Maryland, United States. Contact e-mail: [email protected] Background: The International Genomics of Alzheimer’s Project (IGAP) recently confirmed 8 of 9 previously known variants in addition to APOEε, and identified 11 new variants associated with risk of Alzheimer’s disease (AD), although all have low to moderate effect sizes. We created a genetic risk score (GRS) comprising these 19 variants and evaluated its association with incident AD. We also assessed the improvement in risk prediction, when this GRS was added to models that used previously known risk factors. Methods: We used data from the Framingham Heart Study. After excluding prevalent dementia and participants younger than age 65 years at DNA draw, we computed a genetic risk score as a weighted sum of risk allele doses,